Abstract: Systems and methods to provide remote patient monitoring for viral-respiratory symptoms, including coronavirus or COVID-19 symptoms are disclosed, including a signal receiver circuit configured to receive first and second physiologic information of a patient, the first physiologic information comprising respiration rate information of a patient and the second physiologic information different than the first physiologic information, and an assessment circuit configured to determine an indication of patient viral-respiratory disease using the received first and second physiologic information.

Abstract: This document discusses, among other things, systems and methods for managing pain of a subject. A system includes a first sensor circuit to sense a first signal indicative of a functional state of the subject, a second sensor circuit to sense a second signal different from the first signal, and a controller circuit. The controller circuit may determine an operating mode of the second sensor circuit according to the sensed first signal, trigger the second senor circuit to sense the second signal under the determined operating mode, and generate a pain score using at least the second signal sensed under the determined operating mode. The pain score may be output to a patient or used for closed-loop control of a pain therapy.

Abstract: Systems, devices, and methods for monitoring and assessing blood glucose level in a patient are discussed. An exemplary system receives physiologic information from a patient using an ambulatory medical device. The physiologic information is correlated to, and different from, a direct glucose level measurement. The system determines a glucose index indicative of an abnormal blood glucose level using the received physiologic information by the two or more physiologic sensors. The system may use the glucose index to initiate or adjust a therapy, or to trigger a glucose sensor, separate from the two or more physiologic sensors, to directly measure blood glucose concentration.

Abstract: Systems and methods for detecting worsening cardiac conditions such as worsening heart failure events are described. A system may include sensor circuits to sense physiological signals and signal processors to generate from the physiological signals first and second signal metrics. The system may include a risk stratifier circuit to produce a cardiac risk indication. The system may use at least the first signal metric to generate a primary detection indication, and use at least the second signal metric and the risk indication to generate a secondary detection indication. The risk indication may be used to modulate the second signal metric. A detector circuit may detect the worsening cardiac event using the primary and secondary detection indications.

Abstract: Systems and methods for managing pain in patient are described. A system may include sensors configured to sense physiological or functional signals, and a pain analyzer to generate signal metrics from the physiological or functional signals. The pain analyzer also generates weight factors corresponding to the signal metrics. The weight factors may indicate the signal metrics reliability in representing an intensity of the pain. The pain analyzer generates a pain score using a plurality of signal metrics and a plurality of weight factors. The pain score may be output to a user or a process. The system may additionally include an electrostimulator to generate and deliver closed-loop pain therapy according to the pain score.

Abstract: Systems and methods to detect pneumonia in cardiovascular patients are disclosed, including receiving physiologic information of a patient from an ambulatory medical device (AMD), the physiologic information comprising respiration information of the patient, and determining a pneumonia score of the patient using the received respiration information.

Abstract: Systems and methods for detecting worsening cardiac conditions such as worsening heart failure events are described. A system may include sensor circuits to sense physiological signals and signal processors to generate from the physiological signals first and second signal metrics. The system may include a risk stratifier circuit to produce a cardiac risk indication. The system may use at least the first signal metric to generate a primary detection indication, and use at least the second signal metric and the risk indication to generate a secondary detection indication. The risk indication may be used to modulate the second signal metric. A detector circuit may detect the worsening cardiac event using the primary and secondary detection indications.

Abstract: Systems and methods for monitoring patients with respiratory diseases are described. A system may include a sensor circuit configured to sense one or more physiological signals indicative of respiratory sounds, and a spectral analyzer to generate first and second spectral contents at respective first and second frequency bands. The system may produce a respiratory anomaly indicator using the first and second spectral contents, or additionally with other physiological parameters. The system may detect an onset or progression of a target respiratory condition such as asthma or chronic obstructive pulmonary disease using the respiratory anomaly indicator, or to trigger or adjust a therapy.

Abstract: This document discusses, among other things, systems and methods for managing pain of a subject. A system includes one or more physiological sensors configured to sense a physiological signal indicative of patient brain activity. The physiological signals may include an electroencephalography signal, a magnetoencephalography signal, or a brain-evoked potential. The system may extract from the brain activity signal one or more signal metrics indicative of strength or pattern of brain electromagnetic activity associated with pain, and generate a pain score using the one or more signal metrics. The pain score can be output to a patient or a process. The system may select an electrode configuration for pain-relief electrostimulation based on the pain score, and deliver a closed-loop pain therapy according to the selected electrode configuration.

Abstract: Systems and methods for detecting heart sound information from a subject's head are described. A system embodiment includes a headgear to be worn on the subject's head, and first and second sensors to sense respectively first and second physiologic signals each representing vibration, motion, or displacement conducted through patient body tissue. The sensed physiologic signals contain heart sound information. At least one of the first or the second sensor is included in the headgear, and placed at a head location to sense a physiologic signal indicative of heart sounds. The system includes a processor to generate a composite signal using the sensed first and second physiologic signals. The system may generate a heart sound metric using the composite signal, and detect a cardiac event such as an arrhythmia or worsening heart failure.

Abstract: Systems and methods for monitoring patients for risk of worsening heart failure (WHF) are discussed. A patient management system includes a sensor circuit to receive respiration measurements, and an input device to receive patient dyspnea descriptor indicating dyspnea symptom severity. The system includes a risk analyzer circuit to trend the respiration measurement over time, and to generate a WHF risk indicator using both the trended respiration measurement and the received dyspnea descriptor. A control circuit controls the receiver circuit to receive the dyspnea descriptor in response to the trended respiration measurement satisfying a specific condition. The system can present the WHF risk indicator to a user or a process, or deliver or adjust a HF therapy based on the WHF risk indicator.

Abstract: Systems and methods are described for subject rehospitalization management. In an example, multiple physiologic signals can be obtained from a subject using multiple sensors. In response to a hospitalization event, pre-hospitalization characteristics of the multiple physiologic signals can be identified. Post-hospitalization characteristics of the multiple physiologic signals can be identified, including characteristics that differ from their corresponding pre-hospitalization characteristics. Later subsequent physiologic signals can be further monitored after the hospitalization event, such as using the same multiple sensors, and subsequent physiologic signal characteristics can be identified. In an example, a heart failure diagnostic indication can be determined using information about the pre-hospitalization characteristics, the post-hospitalization characteristics, and the subsequent characteristics.

Abstract: Systems and methods to predict a patient mortality risk are disclosed, including determining a risk value for a plurality of physiologic measures and determining a mortality risk metric indicative of a risk of patient mortality as a weighted combination of the plurality of physiologic measures having risk values satisfying a pre-determined condition.

Abstract: An example of a system for managing pain may include a pain monitoring circuit, a pain relief device, and a control circuit. The pain monitoring circuit may include a parameter analyzer and a pain score generator. The parameter analyzer may be configured to receive and analyze at least two parameters selected from a physiological parameter indicative of a physiological function or state of a patient, a functional parameter indicative of a physical activity or state of the patient, or a patient parameter including subjective information provided by the patient. The pain score generator may be configured to compute a composite pain score using an outcome of the analysis. The composite pain score may indicate a degree of the pain. The pain relief device may be configured to deliver a pain-relief therapy. The control circuit may be configured to control the delivery of the pain-relief therapy using the composite pain score.

Abstract: Systems and methods are described for subject rehospitalization management. In an example, multiple physiologic signals can be obtained from a subject using multiple sensors. In response to a hospitalization event, pre-hospitalization characteristics of the multiple physiologic signals can be identified. Post-hospitalization characteristics of the multiple physiologic signals can be identified, including characteristics that differ from their corresponding pre-hospitalization characteristics. Later subsequent physiologic signals can be further monitored after the hospitalization event, such as using the same multiple sensors, and subsequent physiologic signal characteristics can be identified. In an example, a heart failure diagnostic indication can be determined using information about the pre-hospitalization characteristics, the post-hospitalization characteristics, and the subsequent characteristics.

Abstract: Systems and methods to determine an indication of patient dehydration are disclosed, including receiving first and second physiologic information of a patient, the first physiologic information including heart sound information of the patient and the second physiologic information different than the first physiologic information, and determining the indication of patient dehydration using the received first and second physiologic information.

Abstract: Systems and methods are disclosed to detect a potential syncope event using cardiac acceleration information of a patient and to transition a medical device from a first low-power mode to a second high-power mode in response to the detected potential syncope event.

Abstract: Systems and methods for assessing a cardiac arrhythmia risk of a patient, such as a risk for developing atrial fibrillation, are disclosed. An exemplary medical-device system includes a risk stratifier circuit configured to, in an absence of prior and present atrial arrhythmia, determine a composite risk of the patient developing a future atrial arrhythmia using a trained machine-learning model and a plurality of features of physiological information sensed from the patient and an arrhythmia monitor circuit configured to adjust an arrhythmia monitoring parameter based at least in part on the composite risk and to detect an atrial arrhythmia event using the adjusted arrhythmia monitoring parameter.

Abstract: Systems and methods for monitoring patient vasoactivity are discussed. An exemplary patient monitor system includes a sensor circuit configured to generate a heart sound (HS) metric using a HS signal sensed from a patient, and a vasoactivity monitor configured to monitor vasoactivity, such as degree of vasoconstriction or vasodilation, using the HS metric. The system can provide the monitored vasoactivity to a user to alert patient hemodynamic responses to vasoactive drugs, or initiate or adjust a vasoactive therapy according to the vasoactivity. The system may use the monitored vasoactivity to detect a medical condition such as worsening heart failure, pulmonary edema, or syncope.

Abstract: This document discusses, among other things, systems and methods to determine an alert state for a patient using received physiologic information, determine an event rate for the alert state, and adjust determination of a composite risk for the patient using the determined event rate.