Abstract: Embodiments of the disclosure are related to systems and methods for utilizing biomarker panel data with respect to medical devices and methods, amongst other things. In an embodiment, the disclosure can include a method of predicting the likelihood of response to CRT therapy. The method can include quantifying levels of one or more biomarkers in a biological sample of a patient, analyzing the quantified levels to determine response to CRT therapy, wherein a panel of biomarkers includes at least two selected from the group consisting of CRP, SGP-130, sIL-2R, sTNFR-II, IFNg, BNP, sST2, MMP-2, MMP-9, TIMP-1, TIMP-2, TIMP-4. Other embodiments are also included herein.

Abstract: A heart rate variability or heart rate variation can be identified using sensed and/or paced heart beats. One or more patient metrics, such as a variability index or a variation index, can correspond to the identified heart rate variability or heart rate variation. The patient metrics can be used to identify a need for a particular therapy, such as a rate-responsive pacing therapy. The patient metrics can be used to identify patients at an elevated risk of death. Methods and systems to identify therapy indications or at-risk patients are provided. In an example, a patient risk profile can be adjusted, such as in response to an identified patient heart rate variability or heart rate variation. In an example, a rate-responsive pacing mode can be used to adjust the patient risk profile.

Abstract: A heart rate variability or heart rate variation can be identified using sensed and/or paced heart beats. One or more patient metrics, such as a variability index or a variation index, can correspond to the identified heart rate variability or heart rate variation. The patient metrics can be used to identify a need for a particular therapy, such as a rate-responsive pacing therapy. The patient metrics can be used to identify patients at an elevated risk of death. Methods and systems to identify therapy indications or at-risk patients are provided. In an example, a patient risk profile can be adjusted, such as in response to an identified patient heart rate variability or heart rate variation. In an example, a rate-responsive pacing mode can be used to adjust the patient risk profile.

Abstract: Embodiments of the disclosure are related to systems and methods for utilizing biomarker panel data with respect to medical devices and methods, amongst other things. In an embodiment, the disclosure can include a method of predicting the likelihood of response to CRT therapy. The method can include quantifying levels of one or more biomarkers in a biological sample of a patient, analyzing the quantified levels to determine response to CRT therapy, wherein a panel of biomarkers includes at least two selected from the group consisting of CRP, SGP-130, sIL-2R, sTNFR-II, IFNg, BNP, sST2, MMP-2, MMP-9, TIMP-1, TIMP-2, TIMP-4. Other embodiments are also included herein.

Abstract: Embodiments of the disclosure are related to systems and methods for utilizing biomarker panel data and related medical devices and methods, amongst other things. An embodiment can include a method of screening patients. The method can include quantifying levels of one or more of a panel of biomarkers in a biological sample of a patient. The method can further include analyzing the quantified levels. In some embodiments, the panel of biomarkers includes at least two selected from the group consisting of CRP, SGP-130, sIL-2R, sTNFR-II, IFNg, BNP, sST2, MMP-2, MMP-9, TIMP-1, TIMP-2, TIMP-4. In an embodiment, the disclosure can include a method of diagnosing a patient. The method can include quantifying levels of one or more of a panel of biomarkers in a biological sample of a patient. The method can further include diagnosing the patient based at least in part on the quantified levels.

Abstract: A heart rate variability or heart rate variation can be identified using sensed and/or paced heart beats. One or more patient metrics, such as a variability index or a variation index, can correspond to the identified heart rate variability or heart rate variation. The patient metrics can be used to identify a need for a particular therapy, such as a rate-responsive pacing therapy. The patient metrics can be used to identify patients at an elevated risk of death. Methods and systems to identify therapy indications or at-risk patients are provided. In an example, a patient risk profile can be adjusted, such as in response to an identified patient heart rate variability or heart rate variation. In an example, a rate-responsive pacing mode can be used to adjust the patient risk profile.

Abstract: A heart rate variability or heart rate variation can be identified using sensed and/or paced heart beats. One or more patient metrics, such as a variability index or a variation index, can correspond to the identified heart rate variability or heart rate variation. The patient metrics can be used to identify a need for a particular therapy, such as a rate-responsive pacing therapy. The patient metrics can be used to identify patients at an elevated risk of death. Methods and systems to identify therapy indications or at-risk patients are provided. In an example, a patient risk profile can be adjusted, such as in response to an identified patient heart rate variability or heart rate variation. In an example, a rate-responsive pacing mode can be used to adjust the patient risk profile.

Abstract: In a graphical user interface displayed in an electronic display of a computing device, a first device profile and second device profile are presented, the first and second device profiles each comprising at least one device parameter used to configure a medical device of a subject. A user input control is presented to select one of the first or second device profiles to provide a selected device profile. A probabilistic outcome of the subject corresponding to the selected device profile is then presented.