摘要:
Techniques, systems, and devices, for generating a patient management report based on clinician input and patient data are described. For example, one or more processors may be configured to receive a clinician input selecting at least one reporting characteristic for each of a plurality of diagnostic metrics and organize the diagnostic metrics based on the selected reporting characteristic. In addition, the one or more processors may be configured to receive patient data for at least one patient, determine a value for at least a subset of the diagnostic metrics based on the patient data, and generate a patient management report comprising the diagnostic metrics having a value that exceeds a respective threshold. The diagnostic metrics may be ordered in the patient management report based on the organization.
摘要:
A medical device system senses cardiac signals and generates and stores sensing data including sensed cardiac events. A processor receiving the sensing data is configured to detect undersensed and oversensed events. The processor generates an episode display comprising event identifying codes in response to the received sensing data and produces an adjusted episode display in response to an event being identified as an undersensed event or an oversensed event.
摘要:
The present disclosure is directed to the classification of cardiac episodes using an algorithm. In various examples, an episode classification algorithm evaluates electrogram signal data from a near-field channel and a far-field channel. The episode classification algorithm classifies the cardiac episode based on the evaluation of the electrogram signal data for at least one of the near-field and far-field channels. In some examples, a cardiac episode being classified may be an episode that resulted in treatment being provided by an implantable medical device. Possible classifications of the cardiac episode may include, for example, unknown, inappropriate, appropriate, supraventricular tachycardia, ventricular tachycardia, ventricular fibrillation or ventricular over-sensing.
摘要:
Embodiments of the present invention provide a system in which a medical device selects less than all of its stored information and provides the selected subset of information to a data mart for storage, processing, and/or communication to one or more interested parties. In many embodiments, customers, patients, or even components of the medical device or of the remote patient management system can access selected medical device information (e.g., customers can access medical device information tailored to the care they are providing to one or more patients). In many embodiments, customers can receive such medical device information according to a schedule that best suits their care (or whenever they desire such information, irrespective of a schedule). In many embodiments, providing less than full transmissions to the data mart reduces the strain on medical device batteries.
摘要:
A method for identifying and classifying various types of oversensing in implantable medical devices (IMDs), such as implantable cardioverter defibrillators (ICDs), to assist a physician in choosing corrective action to reduce the likelihood of oversensing and inappropriate therapy delivery. Far-field electrogram (EGM) signals are analyzed to detect the occurrence of R-waves, and the result is compared to the number and pattern of R-waves sensed by the IMD and indicated on the marker channel. A marker channel with more sensed R-waves than indicated by analysis of the far-field EGM indicates the presence of oversensing, including double-counting of R-waves, T-wave oversensing, lead malfunction or failure, poor lead connections, noise associated with electromagnetic interference, non-cardiac myopotentials, etc. Identification of the type of oversensing may be determined by analysis of the number and pattern of marker channel sensed R-waves with respect to the timing of the R-waves detected from the far-field EGM.
摘要:
The present disclosure is directed to the classification of cardiac episodes using an algorithm. In various examples, an episode classification algorithm evaluates electrogram signal data to determine whether T-wave oversensing has occurred. The T-wave oversensing analysis may include, for example, identifying beat runs within the cardiac episode whether the beats within the run have at least one characteristic that alternates beat to be or clustering beats within the cardiac episode based on beat to beat interval length. The T-wave oversensing determination may be based on probabilistic analysis in some examples.
摘要:
The present disclosure is directed to generating and displaying an electrogram (EGM) summary for use by physicians or other clinicians. An implantable medical device (IMD) transmits EGM signal data for a number of cardiac episodes to an external computing device. The external computing device selects a subset of the cardiac episodes for which information or images are displayed to the user. In various examples, cardiac episodes may be selected for display based at least in part on a retrospective analysis classification of the cardiac episode.
摘要:
In general, the disclosure relates to techniques for calculating mean impedance values and impedance variability values to detect a possible condition with a lead or device-lead pathway or connection. In one example, a device may be configured to determine an impedance value for an electrical path based on a plurality of measured impedance values for the electrical path, wherein the electrical path comprises a plurality of electrodes, and to determine an impedance variability value based on at least one of the plurality of measured impedance values. The device may be further configured to determine a threshold value based on the determined impedance value and the impedance variability value, compare a newly measured impedance value for the electrical path to the threshold value, and indicate a possible condition of the electrical path based on the comparison.
摘要:
The present disclosure is directed to the classification of cardiac episodes using an algorithm. In various examples, an episode classification algorithm evaluates electrogram signal data using a probabilistic ventricular oversensing algorithm. The algorithm may look at a plurality of factors weighing for and against a determination of ventricular oversensing. In some examples, the algorithm may also determine whether the cardiac episode includes atrial sensing issues.
摘要:
The present disclosure is directed to the classification of cardiac episodes using an algorithm. In various examples, an episode classification algorithm evaluates electrogram signal data to determine whether T-wave oversensing has occurred. The T-wave oversensing analysis may include, for example, identifying beat runs within the cardiac episode whether the beats within the run have at least one characteristic that alternates beat to be or clustering beats within the cardiac episode based on beat to beat interval length. The T-wave oversensing determination may be based on probabilistic analysis in some examples.