Abstract: Secretions that have accumulated at or near an airway of a subject (12) as the subject (12) is being mechanically ventilated are removed by suctioning. Before, during, and/or after the removal of the secretions, steps are taken to mitigated the impact of the suctioning used for secretion removal on the subject (12). As such, the timing of suction used to remove secretions may be influenced or controlled, ventilation of the subject (12) during suction may be adjusted, ventilation of the subject (12) prior to secretion removal may be adjusted to prepare the lungs of the subject (12) for secretion removal, ventilation of the subject (12) subsequent to suction for secretion removal may be adjusted, and/or other techniques for reducing the impact of suctioning for secretion removal on the subject (12) may be implemented.

Abstract: The disclosure describes improved systems and methods for displaying a trend history of the patient condition using pictorial representations that dynamically change as the clinician advances and reverses through an independent parameter. The present application displays changes in patient condition as a pictorial instead of a number or waveform. By displaying changes in patient condition in a pictorial, a clinician may be able to quickly understand how the dependent parameters have changed as a function of an independent parameter. As the pictorial changes, it animates from one condition to the next to more effectively indicate changes in patient condition. A representation of the normal or desired condition for a parameter is shown as a static pictorial that is overlaid with the dynamically changing trend. In this manner the clinician can determine how the patient condition is changing relative to a desired state.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent multiple ventilatory parameters. However, many clinicians may not easily recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of double triggering during ventilation.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent multiple ventilatory parameters. However, many clinicians may not easily recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of double triggering during ventilation.

Abstract: This disclosure describes systems and methods for monitoring ventilatory parameters, analyzing ventilatory data associated with those parameters, and providing useful notifications and/or recommendations to clinicians. For example, many clinicians may not easily identify or recognize data patterns and correlations indicative of a fluctuation in resistance during mechanical ventilation of a patient. Furthermore, clinicians may not easily determine potential causes for the fluctuation in resistance and/or steps for mitigating the fluctuation in resistance. According to embodiments, a ventilator may be configured to monitor and evaluate diverse ventilatory parameters to detect fluctuations in resistance and may issue suitable notifications and recommendations to the clinician based on potential causes of the fluctuation, ventilatory and/or patient data, etc.

Abstract: This disclosure describes systems and methods for issuing a prompt in response to one or more proposed settings adjustments. Specifically, the prompt may include a projected impact of the one or more proposed settings adjustments on patient condition and/or patient treatment. The prompt may further provide an impact level and/or an alert associated with the projected impact. According to embodiments, one or more recommendations for alternative settings adjustments may be provided on the prompt or on an extension of the prompt. According to embodiments, a clinician may scroll through a plurality of potential settings adjustments until a desired impact level is displayed on the prompt (e.g., a positive impact level). According to still other embodiments, a plurality of proposed settings adjustments may be received. In this case, the projected impact displayed on the prompt may represent a combined projected impact of the plurality of proposed settings adjustments received.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent multiple ventilatory parameters. However, many clinicians may not easily recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during volume ventilation of a non-triggering patient exhibiting an obstructive component.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent multiple ventilatory parameters. However, many clinicians may not easily recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during volume ventilation of a triggering patient exhibiting an obstructive component.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing ventilatory data associated with those parameters, and providing useful notifications and/or recommendations to clinicians. Modern ventilators monitor, evaluate, and graphically represent a myriad of ventilatory parameters. However, many clinicians may not easily identify or recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during various types of pressure ventilation of a patient exhibiting an obstructive component.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing ventilatory data associated with those parameters, and providing useful notifications and/or recommendations to clinicians. Modern ventilators monitor, evaluate, and graphically represent a myriad of ventilatory parameters. However, many clinicians may not easily identify or recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during various types of pressure ventilation.

Abstract: The present invention provides a filter assembly for filtering a gas stream. The filter assembly including a number of filter elements structured to be disposed in a gas stream. The filter assembly further including a heating element for heating each of the number of filter elements, the heating element being structured to be disposed in the gas stream for directly heating the gas stream as the gas stream passes therethrough.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent a myriad of ventilatory parameters. However, many clinicians may not easily identify or recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during volume ventilation of a triggering patient.

Abstract: This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent a myriad of ventilatory parameters. However, many clinicians may not easily identify or recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during volume ventilation of a non-triggering patient.

Abstract: A system (10) and method of insufflating-exsufflating a subject (12) that enables monitoring and/or control over an enhanced set of breathing parameters during insufflation-exsuffiation. The system and/or method may include automatic triggering and/or notification to a caregiver of insufflation-exsuffiation. The insufflation-exsuffiation of the subject may be preceded by a secretion loosing routine that loosens secretions in the airway of the subject without moving the loosened secretions up the airway.

Abstract: A medical ventilator system and method that triggers, cycles, or both based on patient effort, which is determined from cross-correlating patient flow and patient pressure. The medical ventilator is also controlled such that sensitivity to a patient initiated trigger increases as the expiratory phase of the breathing cycle progresses. The present invention also provides adaptive adjustment of cycling criteria to optimize the cycling operation.