Abstract: Techniques for determining a likeliness that a patient may incur an adverse health event are described. An example technique may include utilizing a probability model that uses as evidence nodes various diagnostic states of physiological parameters, which may include one or more subcutaneous impedance parameters. The probability model may include a Bayesian Network that determines a posterior probability of the adverse health event occurring within a predetermined period of time.

Abstract: Techniques for obtaining impedance data to provide an early warning for heart failure decompensation are described. An example device may be configured to measure subcutaneous impedance values, and increment an impedance score. In some examples, the device may use an adaptive threshold and fluid index in incrementing the impedance score. In some examples, the impedance score is compared to a threshold to determine a heart failure status of a patient. In some examples, may cause resets in fluid index values and/or determine positions or orientations of the device when determining the impedance score.

Abstract: Techniques for obtaining impedance data to provide an early warning for heart failure decompensation are described. An example device may be configured to measure subcutaneous impedance values, and increment an impedance score. In some examples, the device may use an adaptive threshold and fluid index in incrementing the impedance score. In some examples, the impedance score is compared to a threshold to determine a heart failure status of a patient.