Detection of expiratory airflow limitation in ventilated patient

Abstract
This disclosure describes systems and methods for monitoring and evaluating data associated with ventilatory parameters to detect expiratory airflow limitation in a ventilated patient. For example, a ventilator may monitor flow and/or pressure during ventilation of the patient. Based on the flow and/or pressure measurements, or ventilatory data derived therefrom, the ventilator may calculate expiratory resistance. Moreover, the ventilator may trend expiratory resistance over time to produce an expiratory resistance waveform. In embodiments, the ventilator may calculate the slope of the expiratory resistance waveform during an initial part of exhalation. If the slope of the expiratory resistance waveform during the initial part of exhalation breaches a defined slope threshold, the ventilator may determine that the patient exhibits expiratory airflow limitation.
Description
INTRODUCTION

A ventilator is a device that mechanically helps patients breathe by replacing some or all of the muscular effort required to inflate and deflate the lungs. In recent years, there has been an accelerated trend towards an integrated clinical environment. That is, medical devices are becoming increasingly integrated with communication, computing, and control technologies. As a result, modern ventilatory equipment has become increasingly complex, providing for detection, monitoring, and evaluation of myriad ventilatory parameters during ventilation of a patient.


For example, patients with advanced stages of chronic obstructive pulmonary disease (COPD), which is characterized by chronic inflammation and thickening of the airways, have difficulty exhaling due to a constriction of the lung bronchioles shortly after the start of exhalation (referred to as expiratory airflow limitation). It would be advantageous to detect when a patient is experiencing expiratory airflow limitation in order to provide appropriate ventilatory management.


Detection of Expiratory Airflow Limitation in Ventilated Patient

This disclosure describes systems and methods for monitoring and evaluating data associated with ventilatory parameters to detect expiratory airflow limitation in a ventilated patient. For example, a ventilator may monitor flow and/or pressure during ventilation of the patient. Based on the flow and/or pressure measurements, or ventilatory data derived therefrom, the ventilator may calculate expiratory airflow resistance (hereinafter referred to as “expiratory resistance”). Moreover, the ventilator may trend expiratory resistance over time to produce an expiratory resistance waveform. In embodiments, the ventilator may calculate the slope of the resistance waveform during an initial part of exhalation. If the slope of the expiratory resistance waveform during the initial part of exhalation breaches a defined slope threshold, the ventilator may determine that the patient exhibits expiratory airflow limitation. Alternatively, if the slope of the expiratory resistance waveform during the initial part of exhalation does not breach the defined slope threshold, the ventilator may determine that the patient does not exhibit expiratory airflow limitation.


According to embodiments, a ventilator-implemented method is provided for determining whether a ventilated patient exhibits an expiratory airflow limitation. The method comprises monitoring ventilatory parameters and trending airflow resistance over time during an expiratory phase to produce a resistance waveform. The method also comprises calculating a slope of the resistance waveform, comparing the slope of the resistance waveform to a defined slope threshold, and determining that the patient exhibits an expiratory airflow limitation if the slope of the resistance waveform is greater than or equal to the defined slope threshold.


According to additional embodiments, a system is provided that comprises at least one processor and at least one memory communicatively coupled to the at least one processor and containing instructions that, when executed by the at least one processor, cause a controller to determine whether the ventilated patient exhibits expiratory airflow limitation. The controller comprises a monitoring module for monitoring ventilatory parameters and an expiratory resistance detection module for calculating airflow resistance during an expiratory phase and trending airflow resistance over time during the expiratory phase to produce a resistance waveform. The controller further comprises an expiratory airflow limitation detection module for calculating a slope of the resistance waveform, comparing the slope of the resistance waveform to a defined slope threshold, and determining that the patient exhibits an expiratory airflow limitation if the slope of the resistance waveform is greater than or equal to the defined slope threshold.


According to additional embodiments, a computer storage device is provided that stores instructions, which when executed by a processor cause a controller to determine whether a ventilated patient exhibits an expiratory airflow limitation. The controller comprises a monitoring module for monitoring ventilatory parameters and an expiratory resistance detection module for trending airflow resistance over time during an expiratory phase to produce a resistance waveform. The controller further comprises an expiratory airflow limitation detection module for calculating a slope of the resistance waveform, comparing the slope of the resistance waveform to a defined slope threshold, and determining that the patient exhibits an expiratory airflow limitation if the slope of the resistance waveform is greater than or equal to the defined slope threshold.


These and various other features as well as advantages which characterize the systems and methods described herein will be apparent from a reading of the following detailed description and a review of the associated drawings. Additional features are set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the technology. The benefits and features of the technology will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.


It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are intended to provide further explanation of the claims.





BRIEF DESCRIPTION OF THE DRAWINGS

The following drawing figures, which form a part of this application, are illustrative of described technology and are not meant to limit the scope of the claims in any manner, which scope shall be based on the claims appended hereto.



FIG. 1 is a diagram illustrating an embodiment of an exemplary ventilator connected to a human patient.



FIG. 2 is a block-diagram illustrating an embodiment of a ventilatory system for determining whether a ventilated patient exhibits expiratory airflow limitation.



FIG. 3 is a graph illustrating pressure and flow waveforms for an example patient who does not exhibit expiratory airflow limitation.



FIG. 4 is a graph illustrating pressure and flow waveforms during exhalation for an example patient who does not exhibit expiratory airflow limitation.



FIG. 5 is a graph illustrating expiratory resistance waveforms for an example patient who does not exhibit expiratory airflow limitation.



FIG. 6 is a graph illustrating pressure and flow waveforms for an example patient who exhibits expiratory airflow limitation.



FIG. 7 is a graph illustrating pressure and flow waveforms during exhalation for an example patient who exhibits expiratory airflow limitation.



FIG. 8 is a graph illustrating expiratory resistance waveforms for an example patient who exhibits expiratory airflow limitation.



FIG. 9 is a graph illustrating the slope of initial expiratory lung resistance versus expiratory lung resistance values for a group of ventilated patients.



FIG. 10 is a flow chart illustrating an embodiment of a method for determining whether a ventilated patient exhibits expiratory airflow limitation.



FIG. 11 is a flow chart illustrating another embodiment of a method for determining whether a ventilated patient exhibits expiratory airflow limitation.





DETAILED DESCRIPTION

Although the techniques introduced above and discussed in detail below may be implemented for a variety of medical devices, the present disclosure will discuss the implementation of these techniques for use in a mechanical ventilator system. The reader will understand that the technology described in the context of a ventilator system could be adapted for use with other therapeutic equipment.


According to embodiments, a ventilator may be configured to detect expiratory airflow limitation in a ventilated patient. For example, the ventilator may detect expiratory airflow limitation in a ventilated patient based on evaluating, inter alia, ventilatory data (e.g., flow, volume, pressure, compliance, ventilator setup data, etc.), patient data (e.g., a patient body weight, a patient diagnosis, a patient gender, a patient age, etc.), and/or any suitable protocol, equation, etc. Specifically, based on the ventilatory data, the ventilator may calculate expiratory resistance, e.g., expiratory lung resistance. Moreover, the ventilator may trend expiratory resistance over time to produce an expiratory resistance waveform. In other embodiments, the ventilator may calculate the slope of the expiratory resistance waveform during an initial part of exhalation, e.g., from about the first 100 to 300 milliseconds (ms) of exhalation.


If the slope of the expiratory resistance waveform during the initial part of exhalation breaches a defined slope of resistance threshold (slope_RL, threshold) (e.g., 100 cmH2O/l/s/s), the ventilator may determine that the patient exhibits expiratory airflow limitation. Alternatively, if the slope of the expiratory resistance waveform during the initial part of exhalation does not breach the slope_RL threshold, the ventilator may determine that the patient does not exhibit expiratory airflow limitation. In some embodiments, the ventilator may further determine if the slope of the expiratory resistance waveform during the initial part of exhalation breaches the slope_RL threshold for a threshold number of breaths (or a threshold percentage of breaths). In this case, if the slope of the expiratory resistance waveform during the initial part of exhalation breaches the slope_RL threshold for a threshold number of breaths (or a threshold percentage of breaths), the ventilator may determine that the patient exhibits expiratory airflow limitation. Alternatively, if the slope of the expiratory resistance waveform during the initial part of exhalation does not breach the slope_RL threshold for the threshold number of breaths (or a threshold percentage of breaths), the ventilator may determine that the patient does not exhibit expiratory airflow limitation.


These and other embodiments will be discussed in further detail with reference to the following figures.



FIG. 1 is a diagram illustrating an embodiment of an exemplary ventilator connected to a human patient.



FIG. 1 illustrates ventilator 100 connected to a human patient 150 via a double-limb patient circuit connected to an artificial airway. Ventilator 100 includes a pneumatic system 102 (also referred to as a pressure generating system 102) for circulating breathing gases to and from patient 150 via the ventilation tubing system 130, which couples the patient to the pneumatic system 102 via an invasive (e.g., endotracheal tube, as shown) or a non-invasive (e.g., nasal mask, not shown) patient interface.


Ventilation tubing system 130 (also referred to as a patient circuit) may be a two-limb (shown) or a one-limb circuit (not shown) for carrying gases to and from the patient 150. In a two-limb embodiment, a fitting, typically referred to as a “wye-fitting” 170, may be provided to couple an endotracheal tube 180 (alternatively a tracheostomy tube 180 or a mask 180 may be employed) to an inspiratory limb 132 and an expiratory limb 134 of the ventilation tubing system 130.


Pneumatic system 102 may be configured in a variety of ways. In the present example, system 102 includes an inspiratory module 104 coupled with the inspiratory limb 132 and an expiratory module 108 coupled with the expiratory limb 134. Compressor 106 or other source(s) of pressurized gases (e.g., air, oxygen, and/or helium) is coupled with inspiratory module 104 to provide a gas source for ventilatory support via inspiratory limb 132.


The pneumatic system 102 may include a variety of other components, including mixing modules, valves, sensors, tubing, accumulators, filters, etc. Controller 110 is operatively coupled with pneumatic system 102, signal measurement and acquisition systems, and an operator interface 120 that may enable an operator to interact with the ventilator 100 (e.g., change ventilator settings, select operational modes, view monitored parameters, etc.). Controller 110 may include memory 112, one or more processors 116, storage 114, and/or other components of the type commonly found in command and control computing devices. In the depicted example, operator interface 120 includes a display 122 that may be touch-sensitive and/or voice-activated, enabling the display to serve both as an input and output device.


The memory 112 includes non-transitory, computer-readable storage media that stores software (or computer-readable instructions) that, when executed by the processor 116, controls the operation of the ventilator 100. In an embodiment, the memory 112 includes computer storage devices, e.g., one or more solid-state storage devices such as flash memory chips. In an alternative embodiment, the memory 112 may be mass storage connected to one or more processors 116 through a mass storage controller (not shown) and a communications bus (not shown). Although the description of computer-readable media contained herein refers to a solid-state storage, it should be appreciated by those skilled in the art that computer-readable storage media can be any available media that can be accessed by the one or more processors 116. That is, computer-readable storage media includes non-transitory, volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. For example, computer-readable storage media includes RAM, ROM, EPROM, EEPROM, flash memory or other solid state memory technology, CD-ROM, DVD, or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by the computer.


Communication between components of the ventilatory system or between the ventilatory system and other therapeutic equipment and/or remote monitoring systems may be conducted over a distributed network, as described further herein, via wired or wireless means. Further, the present methods may be configured as a presentation layer built over the TCP/IP protocol. TCP/IP stands for “Transmission Control Protocol/Internet Protocol” and provides a basic communication language for many local networks (such as intranets or extranets) and is the primary communication language for the Internet. Specifically, TCP/IP is a bi-layer protocol that allows for the transmission of data over a network. The higher layer, or TCP layer, divides a message into smaller packets, which are reassembled by a receiving TCP layer into the original message. The lower layer, or IP layer, handles addressing and routing of packets so that they are properly received at a destination.



FIG. 2 is a block-diagram illustrating an embodiment of a ventilatory system for determining whether a ventilated patient exhibits expiratory airflow limitation.


Ventilator system 200 includes ventilator 202 with its various modules and components. That is, ventilator 202 may further include a memory 210, one or more processors 208, user interface 212, and ventilation module 214 (which may further include an inspiratory module 216 and an expiratory module 218). Memory 210 is defined as described above for memory 112. Similarly, the one or more processors 208 are defined as described above for one or more processors 116. Processors 208 may further be configured with a clock whereby elapsed time may be monitored by the ventilator system 200.


The ventilator system 200 may also include a display module 204 communicatively coupled to ventilator 202. Display module 204 may provide various input screens, for receiving clinician input, and various display screens, for presenting data and information to the clinician. The display module 204 is configured to communicate with user interface 212 and may include a graphical user interface (GUI). The GUI may be an interactive display, e.g., a touch-sensitive screen or otherwise, and may provide various windows and elements for receiving input and interface command operations. Alternatively, other suitable means of communication with the ventilator 202 may be provided, for instance by a wheel, keyboard, mouse, or other suitable interactive device. Thus, user interface 212 may accept commands and input through display module 204. Display module 204 may also provide information in the form of various data regarding the physical condition of a patient and/or a prescribed respiratory treatment as well as the operational state of the ventilator. For example, the data may include collected, processed, or derived values for one or more ventilatory parameters. The information may be based on data collected by one or more sensors 206 associated with monitor module 220 or data derived or otherwise processed by data processing module 222, and the information may be displayed to the clinician in the form of graphs, waveform representations, pie graphs, or other suitable forms of graphic display.


The ventilator system 200 may also include one or more sensors 206 communicatively coupled to ventilator 202. Sensors 206 may communicate with various components of ventilator 202, e.g., ventilation module 214, monitor module 220, data processing module 222, expiratory resistance detection module 224, expiratory airflow limitation detection module 226, or any other suitable components and/or modules. Sensors 206 may collect data indicative of pressure and/or flow, for example. Sensors 206 may be placed in any suitable location, e.g., within the ventilatory circuitry or other devices communicatively coupled to the ventilator. For example, sensors may be affixed to the ventilatory tubing, may be imbedded in the tubing itself, or may be affixed to the patient. According to some embodiments, sensors may be provided at or near the lungs (or diaphragm) for detecting a pressure in the lungs. Additionally or alternatively, sensors may be affixed or imbedded in or near wye-fitting 170 and/or patient interface 180, as described above. Sensors may further be provided within components or modules of ventilator 202. For example, sensors may be coupled to the inspiratory and/or expiratory modules for detecting changes in, for example, circuit pressure and/or flow.


Sensors 206 may include pressure transducers that may detect changes in circuit pressure (e.g., electromechanical transducers including piezoelectric, variable capacitance, or strain gauge). Sensors 206 may further include various flowmeters for detecting airflow (e.g., differential pressure pneumotachometers, turbine flowmeters, etc.). Alternatively, sensors may utilize optical or ultrasound techniques for measuring changes in ventilatory parameters. Indeed, any sensory device useful for monitoring changes in measurable parameters during ventilatory treatment may be employed in accordance with embodiments described herein.


Ventilation module 214 may oversee ventilation of a patient according to prescribed ventilatory settings. By way of general overview, the basic elements impacting ventilation during inspiration may be described by the following simplified ventilatory equation (also known as the Equation of Motion):

PAPPL=[RTOT*Q]+[VT/C]−PMUS

Here it is understood that PAPPL is an inflation pressure (generally expressed in cmH2O) applied externally to the respiratory system, i.e., via patient interface 180 as depicted in FIG. 1, and that PMUS represents the neuromuscular pressure-generating system within the patient's thorax. Thus, during normal breathing PAPPL=zero and all the work of inspiration is supplied by the patient's respiratory-muscles. And conversely during anesthesia, PMUS is nominally quiescent and all of the work of inspiration is supplied by a breathing device. However, with partial ventilatory support, both PAPPL and PMUS will be non-zero during inspiration. In this equation RTOT (generally expressed as cmH2O/l/s) represents the airflow-resistive elements through which gas must flow (Q) (generally expresses as l/min or ml/min or alternately mL/min) to reach the capacitive element C (generally expressed as ml/cmH2O or alternately mL/cmH2O), whose value is assumed to remain nominally constant during ventilation. VT represents accumulated lung volume as generated by the forcing functions PAPPL and/or PMUS. As depicted in FIG. 1, RTOT=RT (artificial airway)+RL (lung). It is further understood that in a ventilator-patient system such as the one depicted in FIG. 1, PAPPL and/or PMUS will be continuous functions of time from beginning inspiration until inspiration ends. Therefore, if pressures and flows are measured/monitored/referenced to the PY (wye) position 170 in FIG. 1, the waveforms/time traces will mirror those shown in FIGS. 3 and 6. Data representative of any of the above ventilatory parameters may be measured, collected, processed, calculated and/or estimated by one or more components of ventilator system 200.


In embodiments, the ventilator-applied inflation pressure, PAPPL, may be measured by the ventilator by any suitable means and may be representative of the positive pressure existing at the patient airway, PY. In embodiments, PAPPL is uninfluenced by elements on the ventilator side of the patient circuit and reflects the pressure existing at the wye interface (i.e., PY at wye 170 in FIG. 1). For example, PAPPL may be measured by one or more pressure transducers placed at any suitable location, e.g., affixed to or imbedded in the ventilatory tubing (or patient circuit), affixed to or imbedded in or near wye-fitting and/or patient interface, or provided within components or modules of the ventilator, such as the inspiratory and/or expiratory modules. In embodiments, PAPPL may be measured in any suitable location by any suitable device, e.g., by a sensor associated with the wye fitting, by sensors associated with the expiratory-valve module, and/or by sensors associated with the inspiratory module and safety valve.


Volume refers to the amount of gas delivered to a patient's lungs, usually in liters (l). Flow refers to a change in volume over time (Q=ΔV/Δt). Flow is generally expressed in liters per minute (l/min) and, depending on whether gases are flowing into or out of the lungs, flow may be referred to as inspiratory flow or expiratory flow, respectively. According to embodiments, the ventilator may control the rate of delivery of gases to the patient, i.e., inspiratory flow, and may control the rate of release of gases from the patient, i.e., expiratory flow.


As may be appreciated, volume and flow are closely related. That is, where flow is known or regulated, volume may be derived based on elapsed time. In embodiments, flow may be measured by any suitable means, e.g., via one or more flow sensors associated with the patient circuit, patient wye, or any ventilator component or module, e.g., the inspiratory or expiratory module. In some embodiments, the flow signal received from the sensors may be compensated for humidity, or other consideration, to provide net flow, QNET, where QNET represents an estimate of the true flow entering and leaving the patient's lungs during inspiration and exhalation, respectively. As with other ventilatory parameters, QNET may be trended over time to provide a net flow waveform. Moreover, volume (or net volume) may be derived by integrating the flow (or net flow) waveform. According to embodiments, a tidal volume, VT, may be delivered upon reaching a set inspiratory time (TI) at set inspiratory flow. Alternatively, set VT and set inspiratory flow may determine the amount of time required for inspiration, i.e., TI.


Additional ventilatory parameters that may be measured and/or derived may include compliance and resistance, which refer to the load against which the patient and/or the ventilator must work to deliver gases to the lungs. Generally, compliance refers to a relative ease with which something distends and is the inverse of elastance, which refers to the tendency of something to return to its original form after being deformed. As related to ventilation, compliance refers to the lung volume achieved for a given amount of delivered pressure (C=ΔV/ΔP). To detect changes in compliance, one variable may be held constant at the end of inspiration and changes in the other variable may be utilized to determine whether compliance has changed and in what direction. Some lung diseases (e.g., acute respiratory distress syndrome (ARDS)) may decrease compliance and, thus, require increased pressure to inflate the lungs. Alternatively, other lung diseases may increase compliance, e.g., emphysema, and may require less pressure to inflate the lungs.


Resistance refers to frictional forces that resist airflow, e.g., due to synthetic structures (e.g., endotracheal tube, etc.), anatomical structures (e.g., trachea and major bronchiolar tree, small bronchi and terminal bronchioles, and terminal airways, etc.), or viscous tissues of the lungs (e.g., alveolar tissues). Resistance is highly dependent on the diameter of the airway. In fact, decreasing the diameter of the airway results in an exponential increase in resistance (e.g., two-times reduction of diameter increases resistance by sixteen times). As may be appreciated, resistance may increase due to a restriction of the airway that is the result of, inter alia, bronchial constriction, increased secretions, bronchial edema, mucous plugs, bronchospasm, and/or kinking of the patient interface (e.g., invasive endotracheal or tracheostomy tubes).


Although the Equation of Motion equation, briefly described above, provides a satisfactory model for understanding pressures and flows during the inspiratory phase of a breath in a patient-ventilator system, an alternate approach has been selected to meet the needs of this disclosure. At the end of the inspiratory phase just before the beginning of exhalation the lung receives a volume, VT. Assuming a passive exhalation and the cessation of either of the active agents of inflation, PAPPL or PMUS, the recoil pressure of the lung becomes manifest and equal to VT/C. It is not germane to this disclosure how VT or C are determined but the literature contains numerous references by which these variables may be measured, calculated, or estimated.


With reference to FIG. 3, it may be appreciated that during passive exhalation PLn=VTn/C at any value of TEn. Also known is that the total resistance impeding expiratory flow is given by RTOTn=RLn+RTn. With PLn determined and PYn monitored it is appreciated that for any TEn, RTOTn=(PLn−PYn)/Qn, where Qn is taken as QNETn. Once RTOTn is known, the value of RLn is found from RLn=RTOTn−RTn, where RTn is calculated using a look-up table or other suitable method.


Resistance is generally expressed in centimeters of water per liters per second (i.e., cmH2O/L/s or cmH2O/l/s). ΔPL refers to the driving pressure necessary to overcome resistive forces, including both lung resistance (RL) and tube resistance (RT), and during exhalation may be calculated as the difference between PY and PL. In embodiments, RL may be estimated by calculating the total resistance and subtracting RT. For a significant percentage of patients with expiratory airflow limitation, RL may be near normal immediately after the beginning of exhalation and then increase in value as exhalation continues due to constriction of the bronchioles. Accordingly, for a patient with expiratory airflow limitation, ΔP may be higher during an initial part of exhalation than during inspiration and/or flow may be lower during an initial part of exhalation than during inspiration. In embodiments, the calculations for resistance above are applicable for calculating expiratory lung resistance.


Ventilation module 214 may further include an inspiratory module 216 configured to deliver gases to the patient according to prescribed ventilatory settings. Specifically, inspiratory module 216 may correspond to the inspiratory module 104 or may be otherwise coupled to source(s) of pressurized gases (e.g., air, oxygen, and/or helium), and may deliver gases to the patient. Inspiratory module 216 may be configured to provide ventilation according to various ventilatory modes and/or breath types, e.g., via volume-targeted, pressure-targeted, spontaneous, mandatory, or via any other suitable type of ventilation.


For example, according to embodiments, the inspiratory module 216 may provide ventilation via a form of volume ventilation. Volume ventilation refers to various forms of volume-targeted ventilation that regulate volume delivery to the patient. For example, in volume-cycled ventilation, an end of inspiration is determined based on monitoring the volume delivered to the patient. For volume-cycled ventilation, when the delivered volume is equal to the prescribed VT, the ventilator may initiate exhalation. According to alternative embodiments, the inspiratory module 216 may provide ventilation via a form of pressure ventilation. Pressure-targeted ventilation may be provided by regulating the pressure delivered to the patient in various ways. For example, during pressure ventilation, the ventilator may maintain a pressure waveform at the mouth, PAPPL, until an inspiratory pressure (PI) is reached, at which point the ventilator may initiate exhalation or until both a desired inspiratory pressure (PI) and a desired inspiratory time (TI) have been attained.


In some embodiments, the inspiratory module 216 may provide pressure-targeted ventilation via a proportional assist type of ventilation. In this case, the ventilator delivers breathing gases to a spontaneously-breathing patient in synchrony with the patient's effort to reduce the patient's work of inspiration (which comprises the greater part of the WOB). The patient's WOB is essentially dependent on the load against which the patient inhales, including patient respiratory characteristics (i.e., anatomical resistance and compliance) and the resistance associated with the synthetic structures (e.g., endotracheal or tracheostomy tube, etc.). In embodiments, during proportional assist ventilation, the ventilator may deliver a real-time, calculated inspiratory target pressure to the patient airway that is a function of monitored flow, a clinician-selected amount of support pressure, a clinician-selected positive end-expiratory pressure (PEEP), an estimate of the patient's resistance and elastance, and a calculation of the tube resistance (dependent on the internal diameter of the endotracheal or tracheostomy tube). In other embodiments the ventilator may algorithmically determine the patient's resistance and compliance, control the support pressure, and manage other aspects of the breathing algorithm.


Ventilation module 214 may further include an expiratory module 218 configured to release gases from the patient's lungs according to prescribed ventilatory settings. Expiratory module 218 may correspond to expiratory module 108 or may otherwise be associated with and/or controlling an expiratory valve for releasing gases from the patient. By way of general overview, a ventilator may initiate exhalation based on lapse of an inspiratory time setting (TI) or other cycling criteria set by the clinician or derived from ventilator settings (e.g., detecting delivery of prescribed VT or prescribed inspiratory pressure based on a reference trajectory). Upon initiating the expiratory phase, expiratory module 218 may allow the patient to exhale by controlling the expiratory valve.


As should be appreciated, with reference to the Equation of Motion, ventilatory parameters are highly interrelated and, according to embodiments, may be directly or indirectly monitored. For example, the sensors may provide raw data to the monitor module 220. The raw data may further be provided to the data processing module 222 for processing and/or deriving (e.g., by calculation, estimation, etc.) ventilatory data. That is, parameters may be directly monitored by one or more sensors, as described above, or may be indirectly monitored by derivation according to the Equation of Motion or other equation, algorithm, etc.


Ventilator 202 may further include a data processing module 222. As noted above, sensors may collect data regarding various ventilatory parameters. A ventilatory parameter refers to any factor, characteristic, or measurement associated with the ventilation of a patient, whether monitored by the ventilator or by any other device. Sensors may further transmit collected data to the monitor module 220 and/or the data processing module 222. According to embodiments, the data processing module may 222 be configured to collect data regarding some ventilatory parameters, to derive data regarding other ventilatory parameters, and/or to transform the collected and/or derived ventilatory data into digital or graphical data for display to the clinician and/or other modules of the ventilatory system. According to embodiments, the collected, derived digital, and/or graphically transformed data may be generally defined as ventilatory data.


For example, according to embodiments, data processing module 222 may be configured to monitor flow and/or pressure. As may be appreciated, flow decreases as resistance increases, making it more difficult to pass gases into and out of the lungs (i.e., Q=ΔP/RTOT). According to embodiments, an increase in ΔP or a decrease in flow may be indicative of an increase in resistance, while a decrease in ΔP or an increase in flow may be indicative of a decrease in resistance (i.e., RTOT=ΔP/Q). For example, increased resistance may be observed in patients with obstructive disorders, such as COPD, asthma, etc.


Ventilator 202 may further include expiratory resistance detection module 224. According to embodiments, expiratory resistance detection module 224 may evaluate the ventilatory data to calculate expiratory resistance for the patient. The expiratory resistance detection module 224 may further trend expiratory resistance values for the patient via any suitable means. “Trending,” as used herein, means collecting and/or calculating data over a plurality of breaths (or at predetermined intervals of time). For example, PL, PY, ΔP and/or flow may be trended over time, based on data collected, processed and/or derived by the ventilator. Moreover, the resistance detection module 224 may trend RTOT, RL and/or RT over time based on calculations associated with the pressure and/or flow waveforms, as described above. Additionally, upon trending RTOT, RL and/or RT over time, the ventilator 202 may produce and/or display waveforms for one or more of RTOT, RL and/or RT.


Ventilator 202 may further include an expiratory airflow limitation detection module 226 for determining whether a ventilated patient has expiratory airflow limitation. For purposes of this disclosure, “expiratory airflow limitation” refers to a difficulty in exhaling. For example, for patients with COPD, resistance may be relatively normal during inspiration but may be significantly higher during exhalation. Difficulty exhaling, or expiratory airflow limitation, results when the intra-thoracic pressure (which is high at the end of inspiration) acts to compress the bronchioles shortly after the start of exhalation.


In order to determine whether a patient has expiratory airflow limitation, the expiratory airflow limitation detection module 226 may calculate a rate of change (or slope) of resistance for the patient. In some embodiments, the ventilator may calculate the slope of total resistance, RTOT. In other embodiments, the expiratory airflow limitation detection module 226 may calculate the slope of lung resistance, RL. As noted above, total resistance is equal to ΔP divided by flow (RTOT=ΔP/Q). Total resistance is further equal to tube resistance, RT, plus lung resistance, RL (RTOT=RT+RL). Accordingly, lung resistance, RL, is equal to ΔP divided by flow minus tube resistance, RT (RL=[ΔP/Q]−RT). In embodiments, as described above, RL may be trended over time to result in a RL waveform. The slope of the RL waveform may be calculated over a period of time, e.g., between about 0.100 and 0.300 s (or 100 and 300 ms) after exhalation begins.


In further embodiments, expiratory airflow limitation detection module 226 may compare the slope of the RL waveform (or the RTOT waveform) to a defined slope of resistance threshold (slope_RL threshold) in order to determine whether the patient has expiratory airflow limitation. In embodiments, the slope_RL threshold may be equal to about 100 cmH2O/l/s/s. In other embodiments, the slope_RL threshold may be equal to another suitable value based on a statistical evaluation of COPD patients or otherwise. In embodiments, if the slope of the RL waveform for a patient is greater than or equal to the slope_RL threshold, the expiratory airflow limitation detection module 226 may determine that the patient has expiratory airflow limitation. Alternatively, if the slope of the RL waveform for a patient is less than the slope_RL threshold, the expiratory airflow limitation detection module 226 may determine that the patient does not have expiratory airflow limitation.


In some embodiments, the expiratory airflow limitation detection module 226 may determine that the patient has expiratory airflow limitation based on evaluating the slope of the RL waveform (or the RTOT waveform) over a plurality of breaths. In this case, the expiratory airflow limitation detection module 226 may determine that the patient has expiratory airflow limitation if the slope of the RL waveform for the patient is greater than or equal to the slope_RL threshold for a threshold number of breaths (or a threshold percentage of breaths, etc.). For example, the expiratory airflow limitation detection module 226 may determine that the patient has expiratory airflow limitation if the slope of the RL waveform for the patient is greater than or equal to the slope_RL threshold for 4 of 5 consecutive breaths, or for 5 of 10 consecutive breaths, or in 60% of breaths. In this example, the expiratory airflow limitation detection module 226 may determine that the patient does not have expiratory airflow limitation when the slope of the RL waveform for the patient is greater than or equal to the slope_RL threshold for less than the threshold number of breaths (or the threshold percentage of breaths).


Upon determining that a patient has expiratory airflow limitation, the ventilator 202 may recommend or automatically adjust ventilatory settings in order to provide appropriate ventilation. For example, appropriate changes may include, but are not limited to, an adjusted WOB estimation (e.g., using a default value for R) for the proportional assist ventilation breath type, a lower respiratory rate (resulting in a higher expiratory time (TE) for complete exhalation of gases), an alternate waveform setting for mandatory breath types, etc.


Ventilator system 200 is exemplary and explanatory and is intended to provide further explanation of the claims. However, it is contemplated that ventilator 200 may have more or fewer components within the spirit of the present disclosure and description of the various components and modules of ventilator 200 is not intended to be limiting.



FIG. 3 is a graph illustrating pressure and flow waveforms for an example patient who does not exhibit expiratory airflow limitation.



FIG. 3 provides a graphical representation of pressure and flow waveforms over time (in seconds) during an inspiratory phase 302 and an expiratory phase 304 of a breath cycle for a ventilated patient. A pressure (PY) measured during inspiration 302 is an inflation pressure (PAPPL) if it exceeds the initial end-exhalation pressure of the previous breath. That is, the pressure (PY) waveform 306 during inspiratory phase 302 is equivalent to PAPPL as defined in this application. Thus, in embodiments, while PAPPL properly refers to an applied pressure during inspiration, PY may be used to refer to pressure readings during either inspiration or expiration. An inspiratory-expiratory pressure (PY) waveform 306 is presented in units of centimeters of water (cmH2O), a net flow (QNET) waveform 308 is presented in units of liters per minute (l/min), and an estimated lung pressure (PE) waveform 310 is presented in units of cmH2O.


As illustrated by net flow (QNET) waveform 308, QNET increases to a peak flow 312 around a middle part of inspiration and then decreases for the remainder of inspiration. Conceptually, the ventilator terminates inspiratory flow (QNET) at event 316. Thereafter, the ventilator enters the expiratory phase in which QNET is assigned negative values. Immediately after the beginning of exhalation 316, QNET increases sharply to about −60 l/min or more as the direction of the flow of gases switches from entering the lungs to exiting the lungs. Note that gas flow is identified as a negative value because gases are exiting the lungs; however, the rate of exit is high (i.e., increases) just as exhalation begins. Thereafter, as exhalation progresses, the flow of air exiting the lungs gradually decreases to about zero l/min at the end of exhalation, at which point equilibrium is reached and gas no longer exits the lungs.


As illustrated by pressure (PY) waveform 306, PAPPL increases to a peak pressure 314 at the end of inspiration. At the beginning of exhalation 316, PY (PAPPL technically transitions to PY at 316) decreases sharply in the first few tenths of a second (e.g., first 100 ms) of exhalation when the ventilator discontinues positive pressure to the patient airway and the direction of gas flow switches from entering to exiting the patient's lungs. Thereafter, PY stabilizes and, as exhalation progresses, PY decreases gradually toward the clinician-set PEEP level (in this example, about 5 cmH2O). In embodiments, PEEP is an amount of end-expiratory pressure that is maintained in the lungs at the end of exhalation to prevent collapse of the alveoli and/or promote gas exchange. PEEP may be set on a per patient basis and may include any appropriate value between nominally zero to five cmH2O and 10 to 20 or more cmH2O.


As illustrated by PL waveform 310, PL is roughly equal to peak pressure 314 at the beginning of exhalation 316. Thereafter, for a patient who is not exhibiting expiratory airflow limitation, PL decreases gradually over exhalation to about the PEEP level (in this example, about 5 cmH2O). For some patients, PL may be slightly greater than the PEEP setting due to a condition called “air trapping,” which is also referred to as intrinsic PEEP (PEEPi) or Auto-PEEP.



FIG. 3 further illustrates a method for deriving a delta P (ΔP) time curve, which is illustrated in subsequent figures. Specifically, at the first moment of exhalation the ventilator calculates the difference between PL and PY at the same value of time (TE) as TE spans the interval between TE=0 until TE exceeds about 300 ms (as shown, the dashed line represents TEn 318 at about 300 ms). In the example illustrated, ΔPn=PLn 320−PYn 322 at time TEn 318. Additionally, as illustrated, QNETn 324 is the net flow at TEn 318.



FIG. 4 is a graph illustrating pressure and flow waveforms during exhalation for an example patient who does not exhibit expiratory airflow limitation.



FIG. 4 provides a graphical representation of pressure and flow waveforms over time (in seconds) during an expiratory phase for a ventilated patient. Specifically, a delta pressure (ΔP) waveform 402 is presented in units of centimeters of water (cmH2O) and a net flow (QNET) waveform 404 is presented in units of liters per minute (l/min).


As described above, ΔP is the difference between the PY waveform and the PL waveform. With reference to FIG. 3, PY decreases sharply during about the first 100 ms of exhalation when the ventilator discontinues positive pressure and the direction of gas flow switches from entering to exiting the patient's lungs. Thereafter, for a patient who does not exhibit expiratory airflow limitation, PY stabilizes and, as exhalation progresses, PY declines gradually toward the clinician-set PEEP level (in this example, about 5 cmH2O). PL also decreases gradually over exhalation to about the PEEP level (in this example, about 5 cmH2O). Accordingly, for a patient who is not exhibiting expiratory airflow limitation, the difference between PL and PY (or ΔP) is greatest 406 shortly after about 100 ms of exhalation and gradually decreases as PL and PY converge toward the PEEP setting at the end of exhalation. In embodiments, as PL may be greater than PEEP (which is the PY target) at the end of exhalation, ΔP may be positive at the end of exhalation.


As illustrated by net flow (QNET) waveform 404, QNET initially increases to a peak flow of about −60 l/min when gas flow switches from entering to exiting the lungs. After about the first 100 ms of exhalation, for a patient who does not exhibit expiratory airflow limitation, QNET gradually decreases from about −60 l/min toward zero l/min at the end of exhalation, at which point equilibrium is reached and air no longer exits the lungs. In the example shown, exhalation may not be complete after 1 second and gases may continue to exit the lungs until QNET is roughly equal to zero l/min (not shown).



FIG. 5 is a graph illustrating resistance waveforms during exhalation for an example patient who does not exhibit expiratory airflow limitation.



FIG. 5 provides a graphical representation of resistance waveforms over time (in seconds) during an expiratory phase for a ventilated patient. Specifically, a total resistance (RTOT) waveform 502 is presented in units of centimeters of water per liters per second (cmH2O/l/s), a lung resistance (RL) waveform 504 is presented in units of cmH2O/l/s, and a tube resistance (RT) waveform 506 is presented in units of cmH2O/l/s.


In embodiments, during about the first 100 to 300 ms of exhalation, the ΔP waveform and the net flow (QNET) waveform may be evaluated to determine total resistance, RTOT, based on the following equation: RTOT=ΔP/QNET. As described above, RTOT is equal to RL plus RT. Accordingly, RL is equal to (ΔP divided by QNET) minus RT (RL=[ΔP/QNET]−RT). As described above, RTOT, RL and/or RT may be trended over time.


In embodiments, for a patient who does not exhibit expiratory airflow limitation, RL may increase gradually over the period between about 100 and 300 ms of exhalation. That is, the rate of change (or slope 508) of RL may increase at a relatively low rate between about 100 and 300 ms of exhalation (e.g., less than 100 cmH2O/l/s/s). In the example shown, the slope 508 of the RL waveform 504 is equal to about 16 cmH2O/l/s/s. In further embodiments, for a patient who does not exhibit expiratory airflow limitation, after about 300 ms of exhalation, the RL waveform may be relatively flat (or exhibit a slight decrease) for the remainder of exhalation.



FIG. 6 is a graph illustrating pressure and flow waveforms for an example patient who exhibits expiratory airflow limitation.



FIG. 6 provides a graphical representation of pressure and flow waveforms over time (in seconds) during an inspiratory phase 602 and an expiratory phase 604 of a breath cycle for a ventilated patient. A pressure (PY) measured during inspiration 602 is an inflation pressure (PAPPL) if it exceeds the initial end-exhalation pressure of the previous breath. That is, the pressure (PY) waveform 606 during inspiratory phase 602 is equivalent to PAPPL as defined in this application. The inspiratory-expiratory pressure (PY) waveform 606 is presented in units of centimeters of water (cmH2O), a net flow (QNET) waveform 608 is presented in units of liters per minute (l/min), and an estimated lung pressure (PL) waveform 610 is presented in units of cmH2O.


As illustrated by net flow QNET waveform 608, inspiratory QNET increases to a peak flow 612 around a middle part of inspiration and then decreases for the remainder of inspiration. Conceptually, the ventilator terminates inspiratory flow (QNET) at event 616. Thereafter, the ventilator enters the expiratory phase in which QNET is assigned negative values by convention. Immediately after the beginning of exhalation 616, QNET increases sharply to about −60 l/min as the direction of the flow of air switches from entering the lungs to exiting the lungs. Thereafter, QNET decreases sharply within about the first 100-200 ms of exhalation to about −50 l/min. Thereafter, as exhalation progresses, QNET gradually decreases toward zero l/min at the end of exhalation, at which point equilibrium is reached and expired volume no longer exits the lungs. In cases of severe expiratory airflow limitation, flow may not reach zero at the end of exhalation, resulting in autoPEEP (or PEEPi). As illustrated by FIG. 6, when equilibrium is reached before QNET reaches zero at the end of exhalation, the example patient is maintained in a state of perpetual autoPEEP. As should be appreciated, with reference to FIG. 3, for a patient not exhibiting expiratory airflow limitation, QNET decreases at a relatively steady rate from about 100 ms to the end of exhalation. In contrast, for a patient exhibiting expiratory airflow limitation, QNET decreases sharply in the first 100-200 ms of exhalation, and then decreases gradually at a relatively slower, steady rate to the end of exhalation with a high likelihood that the following inspiration will begin before exhalation is complete.


As illustrated by pressure (PY) waveform 606, PAPPL increases to a peak pressure 614 at the end of inspiration. At the beginning of exhalation 616, PY (PAPPL technically transitions to PY at 616) decreases sharply in the first 100-200 ms of exhalation when the ventilator discontinues positive pressure to the patient airway and recoil force of the combined lungs and thorax drives gas out of the patient's lungs. In fact, in the case of a patient exhibiting severe expiratory airflow limitation, PY may decline almost to the clinician-set PEEP level within the first 100-200 ms of exhalation. Thereafter, PY may abruptly stabilize and, as exhalation progresses, gradually decrease at a minimal rate toward the clinician-set PEEP level. In some cases (not illustrated here), with PEEP set to finite positive values, the PEEP controller may for a brief interval in early exhalation automatically set the PEEP target to near atmospheric, atmospheric, or below atmospheric pressure to enhance the pressure gradient driving gas from the lungs. As should be appreciated, with reference to FIG. 3, for a patient not exhibiting expiratory airflow limitation, PY decreases at a relatively steady rate after the first 100 ms of exhalation toward the clinician-set PEEP level. In contrast, for a patient exhibiting expiratory airflow limitation, PY decreases sharply to almost the clinician-set PEEP level in the first 100-200 ms of exhalation, and then decreases gradually at a minimal rate to the end of exhalation. That is, in either case, the PY curve is somewhat biconcave during exhalation. However, in the case of expiratory airflow limitation, the biconcave appearance is enhanced. Moreover, in the case of expiratory airflow limitation, the flow curve is exaggerated.


As illustrated by PL waveform 610, at the beginning of exhalation 616, PL increases to peak PL 618, which is greater than peak PAPPL 614. Thereafter, for a patient who exhibits expiratory airflow limitation, PL decreases sharply in the first 100-200 ms of exhalation and then decreases gradually over the remainder of exhalation to about the clinician-set PEEP level (in this case, about 0 cmH2O). In this example, the PL and the PY waveforms converge at atmospheric pressure (about 0 cmH2O) at the end of exhalation.


Although not illustrated on FIG. 6, the method for deriving the delta P (ΔP) curve discussed in connection with FIG. 3 applies to FIG. 6. At the first moment of exhalation the ventilator calculates the difference between PL and PY at corresponding values of TE until TE exceeds about 300 ms.



FIG. 7 is a graph illustrating pressure and flow waveforms during exhalation for an example patient who exhibits expiratory airflow limitation.



FIG. 7 provides a graphical representation of pressure and flow waveforms over time (in seconds) during an expiratory phase for a ventilated patient. Specifically, a delta pressure (ΔP) waveform 702 is presented in units of centimeters of water (cmH2O) and a net flow (QNET) waveform 704 is presented in units of liters per minute (l/min).


As described above, ΔP is the difference between the PY waveform and the PL waveform. With reference to FIG. 6, for a patient who exhibits expiratory airflow limitation, PY decreases sharply to almost the clinician-set PEEP level during about the first 100-200 ms of exhalation. Thereafter, PY stabilizes, declining at a noticeably lower rate toward the clinician-set PEEP level as exhalation progresses (in this example, PEEP is set to zero). In contrast, PL increases to peak PL and then decreases sharply in the first 100-200 ms of exhalation. Thereafter, PL decreases gradually over the remainder of exhalation to about the clinician-set PEEP level. Accordingly, for a patient who is exhibiting expiratory airflow limitation, the difference between PL and PY (or ΔP) is greatest 706 shortly after about 100 ms of exhalation and gradually decreases as PL and PY converge toward the PEEP setting at the end of exhalation.


As illustrated by QNET waveform 704, for a patient who exhibits expiratory airflow limitation, QNET increases to a peak expiratory flow of about −50 l/min (point 708) just after beginning exhalation when gas flow switches from entering to exiting the lungs. Between about 100 and 200 ms of exhalation, QNET decreases sharply from about −50 l/min (point 708) to about −10 l/min (point 710). After approximately 200 ms of exhalation, QNET appears to linearly decrease toward about zero l/min, indicating air can no longer exit the lungs. For the example patient shown, exhalation may not be complete after 1 second and gases may continue to exit the lungs until QNET is approximately equal to zero l/min (not shown).



FIG. 8 is a graph illustrating resistance waveforms during exhalation for an example patient who exhibits expiratory airflow limitation.



FIG. 8 provides a graphical representation of resistance waveforms over time (in seconds) during an expiratory phase for a ventilated patient. Specifically, a total resistance (RTOT) waveform 802 is presented in units of centimeters of water per liter per second (cmH2O/l/s), a lung resistance (RL) waveform 804 is presented in units of cmH2O/l/s, and a tube resistance (RT) waveform 806 is presented in units of cmH2O/l/s.


In embodiments, during about the first 100 to 300 ms of exhalation, the ΔP waveform and the net flow (QNET) waveform may be evaluated to determine total resistance, RTOT, based on the following equation: RTOT=ΔP/QNET. As described above, RTOT is equal to RL plus RT. Accordingly, RL is equal to (ΔP divided by QNET) minus RT (RL=[ΔP/QNET]−RT). Moreover, as described above, RTOT, RL and/or RT may be trended over time.


In embodiments, for a patient who exhibits expiratory airflow limitation, RL (or RTOT) may increase sharply over the period between about 100 and 300 ms of exhalation. That is, the rate of change (or slope 808) of RL may increase quickly between about 100 and 300 ms of exhalation (e.g., a slope of more than approximately 100 cmH2O/l/s/s). For a patient who exhibits expiratory airflow limitation, this sharp increase in resistance occurs because the bronchioles constrict shortly after the start of exhalation (greatly increasing expiratory resistance due to anatomical structures, RL). This increase in expiratory resistance further causes a sharp decrease in the airflow exiting the lungs between about 100 and 200 ms of exhalation (see FIG. 7, QNET waveform 704).


In the example shown, the slope 808 of the RL waveform 804 is equal to approximately 303 cmH2O/l/s/s. In further embodiments, for a patient who exhibits expiratory airflow limitation, after about 300 ms of exhalation, the RL waveform decreases gradually for the remainder of exhalation. In contrast, with reference to FIG. 5, for a patient who does not exhibit expiratory airflow limitation, the slope of expiratory resistance lies below a defined threshold value (slope_RL threshold) and, after approximately 300 ms of exhalation, the slope of the RL waveform is approximately constant until ΔP and QNET lose resolution.



FIG. 9 is a graph illustrating the slope of resistance versus resistance values for a group of ventilated patients.



FIG. 9 provides a comparison of patients who exhibit expiratory airflow limitation and patients who do not exhibit expiratory airflow limitation. Specifically, FIG. 9 displays lung resistance (RL) in units of cmH2O/l/s versus the slope of RL (slope_RL) in units of cmH2O/l/s/s for the group of ventilated patients. The group of ventilated patients is described in Table 1 below.











TABLE 1







Expiratory Airflow


Patient
Symptoms and/or Diagnosis
Limitation?







A
COPD
Expiratory Airflow




Limitation


B
Acute Respiratory Failure (ARF)



with COPD


C
ARF


D
COPD
Expiratory Airflow




Limitation


E
ARF


F
COPD
Expiratory Airflow




Limitation


G
ARF with Pulmonary Edema and



COPD


H
ARF


I
ARF with Pulmonary Edema,



moderate COPD, obesity


J
COPD
Expiratory Airflow




Limitation


K
ARF


L
ARF with COPD


M
Coma









As provided in Table 1, while patients A, B, D, F, G, I, J, and L have been diagnosed with COPD, only patients A, D, F, and J exhibit COPD with expiratory airflow limitation. Accordingly, a method for distinguishing between COPD patients who exhibit and who do not exhibit expiratory airflow limitation would be advantageous.



FIG. 9 illustrates RL data for one or more breaths for each of patients A-M. A slope_RL threshold 902 of 100 cmH2O/l/s/s is identified by a dashed line. As illustrated by FIG. 9, the slope_RL data for patients B, C, E, G, H, I, K, L, and M fall below the slope_RL threshold 902. According to embodiments, by comparing the slope_RL data to the slope_RL threshold 902, it may be determined that patients B, C, E, G, H, I, K, L, and M do not exhibit expiratory airflow limitation. Indeed, as provided in Table 1, patients B, C, E, G, H, I, K, L, and M do not exhibit expiratory airflow limitation.


As illustrated by FIG. 9, the slope_RL data for patients A, F and J fall above the slope_RL threshold 902 for each of a plurality of breaths. According to embodiments, by comparing the slope_RL data to the slope_RL threshold 902, it may be determined that patients A, F and J exhibit expiratory airflow limitation. Indeed, as provided in Table 1, patients A, F and J exhibit expiratory airflow limitation.


With respect to patient D, the slope_RL data for one breath falls below the slope_RL threshold 902, and the slope_RL data for seven breaths fall above the slope_RL threshold 902. That is, for patient D, in 7 of 8 breaths, the slope_RL data fall above the slope_RL threshold 902. According to embodiments, by comparing the slope_RL data to the slope_RL threshold 902 over a threshold number of breaths (e.g., 6 of 8) or a threshold percentage of breaths (e.g., 75%), it may be determined that patient D exhibits expiratory airflow limitation. Indeed, as provided in Table 1, patient D exhibits expiratory airflow limitation.



FIG. 10 is a flow chart illustrating an embodiment of a method for determining whether a ventilated patient exhibits expiratory airflow limitation.


Method 1000 begins with an initiate ventilation operation 1002. Initiate ventilation operation 1002 may further include various additional operations. For example, initiate ventilation operation 1002 may include receiving one or more ventilatory settings associated with ventilation of a patient, e.g., a clinician-selected PEEP level, an inspiratory pressure (PI), a tidal volume (VT), a clinician-selected amount of support pressure, etc. Upon receiving the one or more ventilatory settings, the ventilator may initiate ventilation based on a selected breath type, e.g., a pressure-targeted, volume-targeted, mandatory, or spontaneous breath type.


At monitor operation 1004, the ventilator may monitor various ventilatory parameters, including volume, pressure, flow, etc. For example, the ventilator may monitor ventilator-applied inflation pressure (PAPPL) by any suitable means, e.g., via one or more pressure transducers associated with the patient circuit, patient wye, or any ventilator component or module (e.g., a face mask). Moreover, in embodiments, the ventilator may calculate or otherwise estimate lung pressure (PL). For example, where other variables are known, PL may be calculated based on the Equation of Motion (PMUS+PAPPL=VT/C+R*Q), as described above. The ventilator may further trend pressure (PAPPL or PY, as appropriate) over time to provide a pressure (PY) waveform and may trend PL over time to provide a PL waveform. In embodiments, the pressure (PY) waveform and/or the PL waveform may be trended over one or more inspiratory and expiratory phases for the ventilated patient. Additionally, the ventilator may calculate ΔP, which is the difference between PY and PL. In embodiments, the ventilator may also trend ΔP over time to provide a ΔP waveform.


In further embodiments, at monitor operation 1004, the ventilator may monitor flow (Q) by any suitable means, e.g., via one or more flow sensors associated with the patient circuit, patient wye, or any ventilator component or module. In some embodiments, the flow signal received from the flow sensors may be compensated for humidity, or other consideration, to provide net flow, QNET. As with other ventilatory parameters, QNET may be trended over time to provide a QNET waveform over one or more inspiratory and expiratory phases for the ventilated patient.


At calculate operation 1006, the ventilator may calculate resistance for the ventilated patient. For example, the ΔP waveform and the QNET waveform may be evaluated to determine total resistance, RTOT, based on the following equation: RTOT=ΔP/QNET. As described above, RTOT is equal to lung resistance (RL) plus tube resistance (RT). Accordingly, RL is equal to (ΔP divided by QNET) minus RT (RL=[ΔP/QNET]−RT). Since RT a function of gas flow, knowing the tube type and size allows its value to be obtained using a lookup table or other standardized formula.


At trend operation 1008, the ventilator may trend RTOT, RL and/or RT over time to provide RTOT, RL and/or RT waveforms. In embodiments, the ventilator may trend RTOT, RL and/or RT over time during one or more expiratory phases for a ventilated patient.


At calculate slope operation 1010, the ventilator may calculate a slope of the resistance waveform for the ventilated patient. In embodiments, the ventilator may calculate the slope of the resistance waveform between the first 100 and 300 ms of exhalation for a ventilated patient. In some embodiments, the ventilator may calculate the slope of the RL waveform between the first 100 and 300 ms of exhalation for a ventilated patient.


At determination operation 1012, the ventilator may compare the slope of the resistance waveform with a defined slope of resistance threshold. In some embodiments, the ventilator may compare the slope of the RL waveform with a defined slope of lung resistance threshold (slope_RL threshold). In other embodiments, the ventilator may compare the slope of the RTOT waveform with a defined slope of total resistance threshold (slope_RTOT threshold). The slope RL threshold and the slope_RTOT threshold may be determined by any suitable means. For example, the slope_RL and slope_RTOT thresholds may be determined by statistically analyzing resistance data for a group of ventilated patients, some of which exhibit expiratory airflow limitation and some of which do not exhibit expiratory airflow limitation. In some embodiments, the slope_RL threshold may be equal to approximately 100 cmH2O/l/s/s. If the slope of the RL waveform is greater than or equal to the slope_RL threshold, or the slope of the RTOT waveform is greater than or equal to the slope_RTOT threshold, the ventilator may progress to determine operation 1014. Alternatively, if the slope of the RL waveform is less than the slope_RL threshold, or the slope of the RTOT waveform is less than the slope_RTOT threshold, the ventilator may return to monitor operation 1004.


At determine operation 1014, where the slope of the RL waveform is greater than or equal to the slope_RL threshold, or the slope of the RTOT waveform is greater than or equal to the slope_RTOT threshold, the ventilator may determine that the ventilated patient exhibits expiratory airflow limitation. According to embodiments, when the patient exhibits expiratory airflow limitation during exhalation, the ventilator may recommend or automatically adjust the ventilatory settings to provide sufficient ventilation to the patient. For example, appropriate changes may include, but are not limited to, an adjusted WOB estimation (e.g., using a default value for R) for the proportional assist ventilation breath type, a lower respiratory rate (resulting in a higher expiratory time (TE) for complete exhalation of gases), an alternate waveform setting for mandatory breath types, etc.


As should be appreciated, the particular steps of method 1000 described above are not exclusive and, as will be understood by those skilled in the art, the particular ordering of steps as described herein is not intended to limit the method, e.g., steps may be performed in differing order, additional steps may be performed, and disclosed steps may be excluded without departing from the spirit of the present disclosure.



FIG. 11 is a flow chart illustrating another embodiment of a method for determining whether a ventilated patient exhibits expiratory airflow limitation.


Method 1100 begins with an initiate ventilation operation 1102. Initiate ventilation operation 1102 is similar to initiate ventilation operation 1002, as described above.


At monitor operation 1104, the ventilator may monitor various ventilatory parameters, including volume, pressure, flow, etc., as described with respect to monitor operation 1004. For example, the ventilator may monitor and trend pressure (PAPPL or PY, as appropriate) and may estimate and trend lung pressure (PL) by any suitable means. Additionally, at monitor operation 1104, the ventilator may calculate and trend ΔP, which is the difference between PY and PL. In further embodiments, the ventilator may monitor and trend flow (Q) or net flow (QNET) by any suitable means.


At calculate operation 1106, the ventilator may calculate resistance for the ventilated patient as described with respect to calculate operation 1006. For example, the ΔP waveform and the QNET waveform may be evaluated to determine total resistance, RTOT, based on the following equation: RTOT=ΔP/QNET. As described above, RTOT is equal to lung resistance (RL) plus tube resistance (RT). Accordingly, RL is equal to (ΔP divided by QNET) minus RT (RL=[ΔP/QNET]−RT). Since RT a function of gas flow, knowing the tube type and size allows its value to be obtained using a lookup table or other standardized formula.


At trend operation 1108, the ventilator may trend RTOT, RL and/or RT over time to provide RTOT, RL and/or RT waveforms as described with respect to trend operation 1008. In embodiments, the ventilator may trend RTOT, RL and/or RT over time during one or more expiratory phases for a ventilated patient.


At calculate slope operation 1110, the ventilator may calculate a slope of the resistance waveform for the ventilated patient as described with respect to calculate slope operation 1010. In embodiments, the ventilator may calculate the slope of the RL waveform between the first 100 and 300 ms of exhalation for a ventilated patient. In some embodiments, the ventilator may calculate the slope of the RTOT waveform between the first 100 and 300 ms of exhalation for a ventilated patient.


At determination operation 1112, the ventilator may compare the slope of the RL waveform with a slope_RL threshold or the slope of the RTOT waveform with a slope_RTOT threshold, as described with respect to determination operation 1012. The slope_RL threshold and the slope_RTOT threshold may be determined by any suitable means. In some embodiments, the slope_RL threshold may be equal to approximately 100 cmH2O/l/s/s. If the slope of the RL waveform is greater than or equal to the slope_RL threshold, or the slope of the RTOT waveform is greater than or equal to the slope_RTOT threshold, the ventilator may progress to determination operation 1114. Alternatively, if the slope of the RL waveform is less than the slope_RL threshold, or the slope of the RTOT waveform is less than the slope_RTOT threshold, the ventilator may return to monitor operation 1104.


At determination operation 1114, the ventilator may compare the number of breaths in which the slope of the RL waveform breaches the slope_RL threshold or the RTOT waveform breaches the slope_RTOT threshold to a breath threshold (or a percentage threshold). For example, the breath threshold may require that, for a certain number of breaths, the slope of the RL waveform (or the RTOT waveform) is greater than or equal to the slope_RL threshold (or the slope_RTOT threshold, respectively), e.g., for 4 of 5 consecutive breaths, for 5 of 10 consecutive breaths, etc. In embodiments, the breath threshold may be determined by any suitable means, e.g., by statistically analyzing resistance data for a group of ventilated patients, some of which exhibit expiratory airflow limitation and some of which do not exhibit expiratory airflow limitation. In other embodiments, a percentage threshold may require that, for a certain percentage of breaths, the slope of the RL waveform (or the RTOT waveform) is greater than or equal to the slope_RL threshold (or the slope_RTOT threshold, respectively), e.g., for 60% of breaths, for 75% of breaths, etc. In embodiments, the percentage threshold may be determined by any suitable means, e.g., as described above for the breath threshold. If the number of breaths in which the slope of the RL waveform (or the RTOT waveform) breaches the slope_RL threshold (or the slope_RTOT threshold, respectively) is greater than or equal to the breath threshold (or the percentage threshold), the method progresses to determine operation 1116. Alternatively, if the number of breaths in which the slope of the RL waveform (or the RTOT waveform) breaches the slope_RL threshold (or the slope_RTOT threshold, respectively) is less than the breath threshold (or the percentage threshold), the ventilator may return to monitor operation 1104.


At determine operation 1116, where the slope of the RL waveform (or the RTOT waveform) breaches the slope_RL threshold (or the slope_RTOT threshold, respectively) for a threshold number (or percentage) of breaths, the ventilator may determine that the ventilated patient exhibits expiratory airflow limitation. According to embodiments, when the patient exhibits expiratory airflow limitation during exhalation, the ventilator may recommend or automatically adjust the ventilatory settings to provide sufficient ventilation to the patient. For example, appropriate changes may include, but are not limited to, an adjusted WOB estimation (e.g., using a default value for R) for the proportional assist ventilation breath type, a lower respiratory rate (resulting in a higher expiratory time (TE) for complete exhalation of gases), an alternate waveform setting for mandatory breath types, etc.


As should be appreciated, the particular steps of method 1100 described above are not exclusive and, as will be understood by those skilled in the art, the particular ordering of steps as described herein is not intended to limit the method, e.g., steps may be performed in differing order, additional steps may be performed, and disclosed steps may be excluded without departing from the spirit of the present disclosure.


It will be clear that the systems and methods described herein are well adapted to attain the ends and advantages mentioned as well as those inherent therein. Those skilled in the art will recognize that the methods and systems within this specification may be implemented in many manners and as such is not to be limited by the foregoing exemplified embodiments and examples. In other words, functional elements being performed by a single or multiple components, in various combinations of hardware and software, and individual functions can be distributed among software applications at either the client or server level. In this regard, any number of the features of the different embodiments described herein may be combined into one single embodiment and alternative embodiments having fewer than or more than all of the features herein described are possible.


While various embodiments have been described for purposes of this disclosure, various changes and modifications may be made which are well within the scope of the present disclosure. Numerous other changes may be made which will readily suggest themselves to those skilled in the art and which are encompassed in the spirit of the disclosure and as defined in the appended claims.

Claims
  • 1. A ventilator-implemented method for determining whether a ventilated patient exhibits an expiratory airflow limitation, the method comprising: delivering a flow of gases to a patient;monitoring ventilatory parameters;trending airflow resistance over time during an expiratory phase to produce a resistance waveform, wherein airflow resistance is a measure of frictional forces hampering the delivered flow of gases;calculating a slope of the resistance waveform for an initial portion of the expiratory phase;comparing the slope of the initial portion of the expiratory phase of the resistance waveform to a defined slope threshold;determining that the patient exhibits an expiratory airflow limitation when the slope of the initial portion of the expiratory phase of the resistance waveform is greater than or equal to the defined slope threshold; andin response to a determination that the patient exhibits the expiratory airflow limitation, adjusting at least one ventilatory setting.
  • 2. The method of claim 1, further comprising: determining that the patient does not exhibit an expiratory airflow limitation when the slope of the initial portion of the expiratory phase of the resistance waveform is less than the defined slope threshold.
  • 3. The method of claim 1, wherein the airflow resistance is lung resistance.
  • 4. The method of claim 1, wherein the airflow resistance is total resistance.
  • 5. The method of claim 1, further comprising: determining that the patient exhibits an expiratory airflow limitation when the slope of the resistance waveform is greater than or equal to the defined slope threshold for a threshold number of breaths.
  • 6. The method of claim 1, further comprising: determining that the patient exhibits expiratory airflow limitation when the slope of the resistance waveform is greater than or equal to the defined slope threshold for a threshold percentage of breaths.
  • 7. The method of claim 1, wherein the defined slope threshold is a lung resistance slope threshold (slope_RL threshold).
  • 8. A system, comprising: at least one processor; andat least one memory, communicatively coupled to the at least one processor and containing instructions that, when executed by the at least one processor, cause a controller to determine whether a ventilated patient exhibits expiratory airflow limitation, the controller comprising: a gas source for delivering a flow of gases to a patient;a monitoring module for monitoring ventilatory parameters;an expiratory resistance detection module for: calculating airflow resistance during an expiratory phase;trending airflow resistance over time during the expiratory phase to produce a resistance waveform, wherein airflow resistance is a measure of frictional forces hampering the delivered flow of gases;an expiratory airflow limitation detection module for: calculating a slope of the resistance waveform for an initial portion of the expiratory phase;comparing the slope of the initial portion of the expiratory phase of the resistance waveform to a defined slope threshold; anddetermining that the patient exhibits an expiratory airflow limitation when the slope of the initial portion of the expiratory phase of the resistance waveform is greater than or equal to the defined slope threshold; anda ventilation module for:in response to the determination that the patient exhibits the expiratory airflow limitation, adjusting at least one ventilatory setting.
  • 9. The system of claim 8, the expiratory airflow limitation detection module further configured for determining that the patient does not exhibit an expiratory airflow limitation when the slope of the initial portion of the expiratory phase of the resistance waveform is less than the defined slope threshold.
  • 10. The system of claim 8, wherein the airflow resistance is lung resistance.
  • 11. The system of claim 8, wherein the airflow resistance is total resistance.
  • 12. The system of claim 8, the expiratory airflow limitation detection module further configured for determining that the patient exhibits an expiratory airflow limitation when the slope of the resistance waveform is greater than or equal to the defined slope threshold for a threshold number of breaths.
  • 13. The system of claim 8, the expiratory airflow limitation detection module further configured for determining that the patient exhibits an expiratory airflow limitation when the slope of the resistance waveform is greater than or equal to the defined slope threshold for a threshold percentage of breaths.
  • 14. The system of claim 8, wherein the defined slope threshold is a total resistance slope threshold (slope_RTOT threshold).
  • 15. A computer storage device storing instructions that, when executed by a processor, cause a controller to determine whether a ventilated patient exhibits an expiratory airflow limitation comprising: delivering a flow of gases to a patient;monitoring ventilatory parameters;trending airflow resistance over time during an expiratory phase to produce a resistance waveform, wherein airflow resistance is a measure of frictional forces hampering the delivered flow of gases;calculating a slope of the resistance waveform for an initial portion of the expiratory phase;comparing the slope of the initial portion of the expiratory phase of the resistance waveform to a defined slope threshold;determining that the patient exhibits an expiratory airflow limitation when the slope of the initial portion of the expiratory phase of the resistance waveform is greater than or equal to the defined slope threshold;in response to the determination that the patient exhibits the expiratory airflow limitation, adjusting at least one ventilatory setting.
  • 16. The computer storage device of claim 15, the controller further configured for determining that the patient does not exhibit an expiratory airflow limitation when the slope of the initial portion of the expiratory phase of the resistance waveform is less than the defined slope threshold.
  • 17. The computer storage device of claim 15, wherein the airflow resistance is lung resistance.
  • 18. The computer storage device of claim 15, wherein the airflow resistance is total resistance.
  • 19. The computer storage device of claim 15, the controller further configured for determining that the patient exhibits an expiratory airflow limitation when the slope of the resistance waveform is greater than or equal to the defined slope threshold for a threshold number of breaths.
  • 20. The computer storage device of claim 15, the controller further configured for determining that the patient exhibits an expiratory airflow limitation when the slope of the resistance waveform is greater than or equal to the defined slope threshold for a threshold percentage of breaths.
US Referenced Citations (396)
Number Name Date Kind
4622980 Kunig Nov 1986 A
4739987 Nicholson Apr 1988 A
4752089 Carter Jun 1988 A
4921642 LaTorraca May 1990 A
4954799 Kumar Sep 1990 A
5057822 Hoffman Oct 1991 A
5072737 Goulding Dec 1991 A
5150291 Cummings et al. Sep 1992 A
5161525 Kimm et al. Nov 1992 A
5237987 Anderson et al. Aug 1993 A
5271389 Isaza et al. Dec 1993 A
5279549 Ranford Jan 1994 A
5299568 Forare et al. Apr 1994 A
5301921 Kumar Apr 1994 A
5319540 Isaza et al. Jun 1994 A
5325861 Goulding Jul 1994 A
5333606 Schneider et al. Aug 1994 A
5339807 Carter Aug 1994 A
5343857 Schneider et al. Sep 1994 A
5351522 Lura Oct 1994 A
5357946 Kee et al. Oct 1994 A
5368019 LaTorraca Nov 1994 A
5383449 Forare et al. Jan 1995 A
5385142 Brady et al. Jan 1995 A
5390666 Kimm et al. Feb 1995 A
5401135 Stoen et al. Mar 1995 A
5402796 Packer et al. Apr 1995 A
5407174 Kumar Apr 1995 A
5413110 Cummings et al. May 1995 A
5419314 Christopher May 1995 A
5438980 Phillips Aug 1995 A
5443075 Holscher Aug 1995 A
5513631 McWilliams May 1996 A
5517983 Deighan et al. May 1996 A
5520071 Jones May 1996 A
5524615 Power Jun 1996 A
5531221 Power Jul 1996 A
5542415 Brady Aug 1996 A
5544674 Kelly Aug 1996 A
5549106 Gruenke et al. Aug 1996 A
5582182 Hillsman Dec 1996 A
5596984 O'Mahony et al. Jan 1997 A
5630411 Holscher May 1997 A
5632270 O'Mahony et al. May 1997 A
5645048 Brodsky et al. Jul 1997 A
5660171 Kimm et al. Aug 1997 A
5664560 Merrick et al. Sep 1997 A
5664562 Bourdon Sep 1997 A
5671767 Kelly Sep 1997 A
5672041 Ringdahl et al. Sep 1997 A
5673689 Power Oct 1997 A
5715812 Deighan et al. Feb 1998 A
5762480 Adahan Jun 1998 A
5771884 Yarnell et al. Jun 1998 A
5791339 Winter Aug 1998 A
5794986 Gansel et al. Aug 1998 A
5813399 Isaza et al. Sep 1998 A
5826575 Lall Oct 1998 A
5829441 Kidd et al. Nov 1998 A
5864938 Gansel et al. Feb 1999 A
5865168 Isaza Feb 1999 A
5881717 Isaza Mar 1999 A
5881723 Wallace et al. Mar 1999 A
5884623 Winter Mar 1999 A
5909731 O'Mahony et al. Jun 1999 A
5915379 Wallace et al. Jun 1999 A
5915380 Wallace et al. Jun 1999 A
5915382 Power Jun 1999 A
5918597 Jones et al. Jul 1999 A
5921238 Bourdon Jul 1999 A
5934274 Merrick et al. Aug 1999 A
5944680 Christopherson Aug 1999 A
6024089 Wallace et al. Feb 2000 A
6041780 Richard et al. Mar 2000 A
6047860 Sanders Apr 2000 A
6076523 Jones et al. Jun 2000 A
6116240 Merrick et al. Sep 2000 A
6116464 Sanders Sep 2000 A
6123073 Schlawin et al. Sep 2000 A
6135106 Dirks et al. Oct 2000 A
6142150 O'Mahoney et al. Nov 2000 A
6161539 Winter Dec 2000 A
6220245 Takabayashi et al. Apr 2001 B1
6269812 Wallace et al. Aug 2001 B1
6273444 Power Aug 2001 B1
6283119 Bourdon Sep 2001 B1
6305373 Wallace et al. Oct 2001 B1
6321748 O'Mahoney Nov 2001 B1
6325785 Babkes et al. Dec 2001 B1
6357438 Hansen Mar 2002 B1
6360745 Wallace et al. Mar 2002 B1
6369838 Wallace et al. Apr 2002 B1
6412483 Jones et al. Jul 2002 B1
6439229 Du et al. Aug 2002 B1
6467478 Merrick et al. Oct 2002 B1
6546930 Emerson et al. Apr 2003 B1
6553991 Isaza Apr 2003 B1
6557553 Borrello May 2003 B1
6571795 Bourdon Jun 2003 B2
6622726 Du Sep 2003 B1
6644310 Delache et al. Nov 2003 B1
6668824 Isaza et al. Dec 2003 B1
6675801 Wallace et al. Jan 2004 B2
6718974 Moberg Apr 2004 B1
6725447 Gilman et al. Apr 2004 B1
6739337 Isaza May 2004 B2
6761167 Nadjafizadeh et al. Jul 2004 B1
6761168 Nadjafizadeh et al. Jul 2004 B1
6814074 Nadjafizadeh et al. Nov 2004 B1
6866040 Bourdon Mar 2005 B1
6960854 Nadjafizadeh et al. Nov 2005 B2
7036504 Wallace et al. May 2006 B2
7077131 Hansen Jul 2006 B2
RE39225 Isaza et al. Aug 2006 E
7117438 Wallace et al. Oct 2006 B2
7270126 Wallace et al. Sep 2007 B2
7334581 Doshi Feb 2008 B2
7369757 Farbarik May 2008 B2
7370650 Nadjafizadeh et al. May 2008 B2
7428902 Du et al. Sep 2008 B2
7460959 Jafari Dec 2008 B2
7487773 Li Feb 2009 B2
7654802 Crawford, Jr. et al. Feb 2010 B2
7676276 Karell Mar 2010 B2
7694677 Tang Apr 2010 B2
7717113 Andrieux May 2010 B2
D618356 Ross Jun 2010 S
7735491 Doshi et al. Jun 2010 B2
7735492 Doshi et al. Jun 2010 B2
7784461 Figueiredo et al. Aug 2010 B2
7798148 Doshi et al. Sep 2010 B2
7823588 Hansen Nov 2010 B2
7855716 McCreary et al. Dec 2010 B2
D632796 Ross et al. Feb 2011 S
D632797 Ross et al. Feb 2011 S
7891354 Farbarik Feb 2011 B2
7893560 Carter Feb 2011 B2
D638852 Skidmore et al. May 2011 S
7984714 Hausmann et al. Jul 2011 B2
D643535 Ross et al. Aug 2011 S
7992557 Nadjafizadeh et al. Aug 2011 B2
7992563 Doshi Aug 2011 B2
7992564 Doshi et al. Aug 2011 B2
8001967 Wallace et al. Aug 2011 B2
D645158 Sanchez et al. Sep 2011 S
8020700 Doshi et al. Sep 2011 B2
8021310 Sanborn et al. Sep 2011 B2
D649157 Skidmore et al. Nov 2011 S
D652521 Ross et al. Jan 2012 S
D652936 Ross et al. Jan 2012 S
D653749 Winter et al. Feb 2012 S
8113062 Graboi et al. Feb 2012 B2
D655405 Winter et al. Mar 2012 S
D655809 Winter et al. Mar 2012 S
D656237 Sanchez et al. Mar 2012 S
8172765 Maksym et al. May 2012 B2
8181645 Houzego et al. May 2012 B2
8181648 Perine et al. May 2012 B2
8181656 Danek et al. May 2012 B2
8210173 Vandine Jul 2012 B2
8210174 Farbarik Jul 2012 B2
8215308 Doshi et al. Jul 2012 B2
8235046 Doshi et al. Aug 2012 B2
8240309 Doshi et al. Aug 2012 B2
8240684 Ross et al. Aug 2012 B2
8267085 Jafari et al. Sep 2012 B2
8272379 Jafari et al. Sep 2012 B2
8272380 Jafari et al. Sep 2012 B2
8291909 Doshi et al. Oct 2012 B2
8302600 Andrieux et al. Nov 2012 B2
8302602 Andrieux et al. Nov 2012 B2
8302606 Doshi et al. Nov 2012 B2
8312879 Choncholas et al. Nov 2012 B2
8347883 Bird Jan 2013 B2
8365736 Doshi et al. Feb 2013 B2
8457706 Baker, Jr. Jun 2013 B2
D692556 Winter Oct 2013 S
D693001 Winter Nov 2013 S
D701601 Winter Mar 2014 S
8792949 Baker, Jr. Jul 2014 B2
D731048 Winter Jun 2015 S
D731049 Winter Jun 2015 S
D731065 Winter Jun 2015 S
D736905 Winter Aug 2015 S
D744095 Winter Nov 2015 S
20010052344 Doshi Dec 2001 A1
20030100843 Hoffman May 2003 A1
20030159693 Melker et al. Aug 2003 A1
20040194780 Doshi Oct 2004 A1
20050039748 Andrieux Feb 2005 A1
20050076907 Stenzler Apr 2005 A1
20050139212 Bourdon Jun 2005 A1
20050161046 Michaels Jul 2005 A1
20050178385 Dellaca' Aug 2005 A1
20060032497 Doshi Feb 2006 A1
20070017515 Wallace et al. Jan 2007 A1
20070077200 Baker Apr 2007 A1
20070185406 Goldman Aug 2007 A1
20070227537 Bemister et al. Oct 2007 A1
20070272241 Sanborn et al. Nov 2007 A1
20070284361 Nadjafizadeh et al. Dec 2007 A1
20080053441 Gottlib et al. Mar 2008 A1
20080072896 Setzer et al. Mar 2008 A1
20080072902 Setzer et al. Mar 2008 A1
20080078390 Milne et al. Apr 2008 A1
20080083644 Janbakhsh et al. Apr 2008 A1
20080092894 Nicolazzi et al. Apr 2008 A1
20080097234 Nicolazzi et al. Apr 2008 A1
20080149097 Haj-Yehia Jun 2008 A1
20080202517 Mitton et al. Aug 2008 A1
20080221470 Sather et al. Sep 2008 A1
20090025713 Keller et al. Jan 2009 A1
20090145441 Doshi et al. Jun 2009 A1
20090156978 Faul et al. Jun 2009 A1
20090165795 Nadjafizadeh et al. Jul 2009 A1
20090171176 Andersohn Jul 2009 A1
20090194109 Doshi et al. Aug 2009 A1
20090205661 Stephenson et al. Aug 2009 A1
20090205663 Vandine et al. Aug 2009 A1
20090241952 Nicolazzi et al. Oct 2009 A1
20090241953 Vandine et al. Oct 2009 A1
20090241956 Baker, Jr. et al. Oct 2009 A1
20090241957 Baker, Jr. Oct 2009 A1
20090241958 Baker, Jr. Oct 2009 A1
20090241962 Jafari et al. Oct 2009 A1
20090247849 McCutcheon et al. Oct 2009 A1
20090247853 Debreczeny Oct 2009 A1
20090247891 Wood Oct 2009 A1
20090301486 Masic Dec 2009 A1
20090301487 Masic Dec 2009 A1
20090301490 Masic Dec 2009 A1
20090301491 Masic et al. Dec 2009 A1
20090314291 Anderson et al. Dec 2009 A1
20100000528 Palmer et al. Jan 2010 A1
20100011307 Desfossez et al. Jan 2010 A1
20100024820 Bourdon Feb 2010 A1
20100051026 Graboi Mar 2010 A1
20100051029 Jafari et al. Mar 2010 A1
20100069761 Karst et al. Mar 2010 A1
20100071689 Thiessen Mar 2010 A1
20100071692 Porges Mar 2010 A1
20100071695 Thiessen Mar 2010 A1
20100071696 Jafari Mar 2010 A1
20100071697 Jafari et al. Mar 2010 A1
20100078017 Andrieux et al. Apr 2010 A1
20100078026 Andrieux et al. Apr 2010 A1
20100081119 Jafari et al. Apr 2010 A1
20100081955 Wood, Jr. et al. Apr 2010 A1
20100139660 Adahan Jun 2010 A1
20100147303 Jafari et al. Jun 2010 A1
20100186744 Andrieux Jul 2010 A1
20100218765 Jafari et al. Sep 2010 A1
20100218766 Milne Sep 2010 A1
20100218767 Jafari et al. Sep 2010 A1
20100236555 Jafari et al. Sep 2010 A1
20100242961 Mougel et al. Sep 2010 A1
20100249549 Baker, Jr. et al. Sep 2010 A1
20100282259 Figueiredo et al. Nov 2010 A1
20100286548 Lazar et al. Nov 2010 A1
20100288283 Campbell et al. Nov 2010 A1
20100300442 Houzego et al. Dec 2010 A1
20100300446 Nicolazzi et al. Dec 2010 A1
20110005520 Doshi et al. Jan 2011 A1
20110011400 Gentner et al. Jan 2011 A1
20110023878 Thiessen Feb 2011 A1
20110023879 Vandine et al. Feb 2011 A1
20110023880 Thiessen Feb 2011 A1
20110023881 Thiessen Feb 2011 A1
20110029910 Thiessen Feb 2011 A1
20110041849 Chen et al. Feb 2011 A1
20110041850 Vandine et al. Feb 2011 A1
20110108041 Sather et al. May 2011 A1
20110126829 Carter et al. Jun 2011 A1
20110126832 Winter et al. Jun 2011 A1
20110126834 Winter et al. Jun 2011 A1
20110126835 Winter et al. Jun 2011 A1
20110126836 Winter et al. Jun 2011 A1
20110126837 Winter et al. Jun 2011 A1
20110128008 Carter Jun 2011 A1
20110132361 Sanchez Jun 2011 A1
20110132362 Sanchez Jun 2011 A1
20110132364 Ogilvie et al. Jun 2011 A1
20110132365 Patel et al. Jun 2011 A1
20110132366 Ogilvie et al. Jun 2011 A1
20110132367 Patel Jun 2011 A1
20110132368 Sanchez et al. Jun 2011 A1
20110132369 Sanchez Jun 2011 A1
20110132371 Sanchez et al. Jun 2011 A1
20110133936 Sanchez et al. Jun 2011 A1
20110138308 Palmer et al. Jun 2011 A1
20110138309 Skidmore et al. Jun 2011 A1
20110138311 Palmer Jun 2011 A1
20110138315 Vandine et al. Jun 2011 A1
20110138323 Skidmore et al. Jun 2011 A1
20110146681 Jafari et al. Jun 2011 A1
20110146683 Jafari et al. Jun 2011 A1
20110154241 Skidmore et al. Jun 2011 A1
20110175728 Baker, Jr. Jul 2011 A1
20110196251 Jourdain et al. Aug 2011 A1
20110209702 Vuong et al. Sep 2011 A1
20110209704 Jafari et al. Sep 2011 A1
20110209707 Terhark Sep 2011 A1
20110213215 Doyle et al. Sep 2011 A1
20110218451 Lai et al. Sep 2011 A1
20110230780 Sanborn et al. Sep 2011 A1
20110249006 Wallace et al. Oct 2011 A1
20110259330 Jafari et al. Oct 2011 A1
20110259332 Sanchez et al. Oct 2011 A1
20110259333 Sanchez et al. Oct 2011 A1
20110265024 Leone et al. Oct 2011 A1
20110271960 Milne et al. Nov 2011 A1
20110273299 Milne et al. Nov 2011 A1
20120000467 Milne et al. Jan 2012 A1
20120000468 Milne et al. Jan 2012 A1
20120000469 Milne et al. Jan 2012 A1
20120000470 Milne et al. Jan 2012 A1
20120029317 Doyle et al. Feb 2012 A1
20120030611 Skidmore Feb 2012 A1
20120060841 Crawford, Jr. et al. Mar 2012 A1
20120071729 Doyle et al. Mar 2012 A1
20120090611 Graboi et al. Apr 2012 A1
20120096381 Milne et al. Apr 2012 A1
20120103337 Avni May 2012 A1
20120133519 Milne et al. May 2012 A1
20120136222 Doyle et al. May 2012 A1
20120137249 Milne et al. May 2012 A1
20120137250 Milne et al. May 2012 A1
20120167885 Masic et al. Jul 2012 A1
20120185792 Kimm et al. Jul 2012 A1
20120197578 Vig et al. Aug 2012 A1
20120197580 Vij et al. Aug 2012 A1
20120211008 Perine et al. Aug 2012 A1
20120216809 Milne et al. Aug 2012 A1
20120216810 Jafari et al. Aug 2012 A1
20120216811 Kimm et al. Aug 2012 A1
20120226444 Milne et al. Sep 2012 A1
20120247471 Masic et al. Oct 2012 A1
20120272960 Milne Nov 2012 A1
20120272961 Masic et al. Nov 2012 A1
20120272962 Doyle et al. Nov 2012 A1
20120277616 Sanborn et al. Nov 2012 A1
20120279501 Wallace et al. Nov 2012 A1
20120285470 Sather et al. Nov 2012 A9
20120289852 Van Den Aardweg Nov 2012 A1
20120304995 Kauc Dec 2012 A1
20120304997 Jafari et al. Dec 2012 A1
20130000644 Thiessen Jan 2013 A1
20130006133 Doyle et al. Jan 2013 A1
20130006134 Doyle et al. Jan 2013 A1
20130008443 Thiessen Jan 2013 A1
20130025596 Jafari et al. Jan 2013 A1
20130025597 Doyle et al. Jan 2013 A1
20130032151 Adahan Feb 2013 A1
20130042869 Andrieux et al. Feb 2013 A1
20130047983 Andrieux et al. Feb 2013 A1
20130047989 Vandine et al. Feb 2013 A1
20130053717 Vandine et al. Feb 2013 A1
20130074844 Kimm et al. Mar 2013 A1
20130081536 Crawford, Jr. et al. Apr 2013 A1
20130104896 Kimm et al. May 2013 A1
20130146055 Jafari et al. Jun 2013 A1
20130152923 Andrieux et al. Jun 2013 A1
20130158370 Doyle et al. Jun 2013 A1
20130159912 Baker, Jr. Jun 2013 A1
20130167842 Jafari et al. Jul 2013 A1
20130167843 Kimm et al. Jul 2013 A1
20130186397 Patel Jul 2013 A1
20130186400 Jafari et al. Jul 2013 A1
20130186401 Jafari et al. Jul 2013 A1
20130192599 Nakai et al. Aug 2013 A1
20130220324 Jafari et al. Aug 2013 A1
20130233314 Jafari et al. Sep 2013 A1
20130233319 Winter et al. Sep 2013 A1
20130239038 Skidmore et al. Sep 2013 A1
20130239967 Jafari et al. Sep 2013 A1
20130255682 Jafari et al. Oct 2013 A1
20130255685 Jafari et al. Oct 2013 A1
20130276788 Masic Oct 2013 A1
20130283197 Skidmore Oct 2013 A1
20130284172 Doyle et al. Oct 2013 A1
20130284173 Masic et al. Oct 2013 A1
20130284177 Li et al. Oct 2013 A1
20140000606 Doyle et al. Jan 2014 A1
20140012150 Milne et al. Jan 2014 A1
20140123979 Doyle et al. May 2014 A1
20140182590 Platt et al. Jul 2014 A1
20140224250 Sanchez et al. Aug 2014 A1
20140251328 Graboi et al. Sep 2014 A1
20140261409 Dong et al. Sep 2014 A1
20140261410 Sanchez et al. Sep 2014 A1
20140261424 Doyle et al. Sep 2014 A1
20140276176 Winter Sep 2014 A1
20140373845 Dong Dec 2014 A1
20150034082 Kimm et al. Feb 2015 A1
20150039045 Ni Feb 2015 A1
20140034054 Angelico et al. May 2015 A1
Non-Patent Literature Citations (4)
Entry
7200 Series Ventilator, Options, and Accessories: Operator's Manual. Nellcor Puritan Bennett, Part No. 22300 A, Sep. 1990, pp. 1-196.
7200 Ventilatory System: Addendum/Errata. Nellcor Puritan Bennett, Part No. 4-023576-00, Rev. A, Apr. 1998, pp. 1-32.
800 Operator's and Technical Reference Manual. Series Ventilator System, Nellcor Puritan Bennett, Part No. 4-070088-00, Rev. L, Aug. 2010, pp. 1-476.
840 Operator's and Technical Reference Manual. Ventilator System, Nellcor Puritan Bennett, Part No. 4-075609-00, Rev. G, Oct. 2006, pp. 1-424.
Related Publications (1)
Number Date Country
20150045687 A1 Feb 2015 US