The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 24, 2015

Filed:

Mar. 28, 2011
Applicants:

Rodolphe Katra, Blaine, MN (US);

Niranjan Chakravarthy, Minneapolis, MN (US);

Imad Libbus, St. Paul, MN (US);

Inventors:

Rodolphe Katra, Blaine, MN (US);

Niranjan Chakravarthy, Minneapolis, MN (US);

Imad Libbus, St. Paul, MN (US);

Assignee:

Corventis, Inc., St. Paul, MN (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/05 (2006.01); A61B 5/0205 (2006.01); A61B 5/107 (2006.01); A61B 5/00 (2006.01); A61B 6/00 (2006.01); A61B 5/053 (2006.01); A61N 1/00 (2006.01);
U.S. Cl.
CPC ...
A61B 5/0205 (2013.01); A61B 5/1079 (2013.01); A61B 5/6833 (2013.01); A61B 5/1072 (2013.01); A61B 5/4872 (2013.01); A61B 5/0075 (2013.01); A61B 5/1073 (2013.01); A61B 6/482 (2013.01); A61B 5/0004 (2013.01); A61B 5/0537 (2013.01); A61B 5/4878 (2013.01); A61B 5/4875 (2013.01); A61B 5/7225 (2013.01); A61B 5/1075 (2013.01); A61B 5/7282 (2013.01); A61N 1/00 (2013.01);
Abstract

Methods and apparatus combine patient measurement data with demographic or physiological data of the patient to determine an output that can be used to diagnose and treat the patient. A customized output can be determined based the demographics of the patient, physiological data of the patient, and data of a population of patients. In another aspect, patient measurement data is used to predict an impending cardiac event, such as acute decompensated heart failure. At least one personalized value is determined for the patient, and a patient event prediction output is generated based at least in part on the personalized value and the measurement data. For example, bioimpedance data may be used to establish a baseline impedance specific to the patient, and the patient event prediction output generated based in part on the relationship of ongoing impedance measurements to the baseline impedance. Multivariate prediction models may enhance prediction accuracy.


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