System for Clinical Research and Clinical Management of Cardiovascular Risk Using Ambulatory Blood Pressure Monitoring and Actigraphy

• US 20110035233A1
• Filed: 08/04/2010
• Published: 02/10/2011
• Est. Priority Date: 08/05/2009
• Status: Active Grant

• Current Assignee: Universidad de Vigo
• Original Assignee: Universidad de Vigo
• Inventors: DOMINGUEZ, RAMÓN HERMIDA, OJEA, ARTEMIO MOJÓN, BERNÁRDEZ, JOSÉ RAMÓN FERNÁNDEZ
• Granted Patent: US 8,428,965 B2
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Disclosed embodiments include a web-enabled system especially adapted for clinical research and clinical management of cardiovascular risk using ambulatory blood pressure monitoring (ABPM) data, actigraphy data, and clinical data. According to a disclosed embodiment the web-enabled system comprises (a) a web-enabled graphical user interface to enable a user to securely authenticate, securely upload clinical data, and navigate through a plurality of software modules; (b) a database to store user profiles, protocols, clinical data, ambulatory blood pressure monitoring (ABPM) recordings, actigraphy recordings, research data, and study results; and (c) a plurality of statistical methods and analysis techniques especially designed to automatically analyze the clinical cardiovascular risk data, and create customized reports of the results designed to assess cardiovascular risk based on ABPM and actigraphy.

Claims

1. A system for clinical research and clinical management of cardiovascular risk implemented on a computer system with one or more processors and one or more storage elements, comprising:

(a) a web-enabled graphical user interface to enable a user to securely authenticate, securely upload clinical data, and securely navigate through a plurality of software modules;

(b) a database to store user profiles, user permissions, protocols, cardiovascular risk clinical data, and study results; and

(c) a plurality of statistical methods and analysis techniques to automatically analyze said cardiovascular risk clinical data, and create customized reports of the results.

2. The system according to claim 1, wherein said cardiovascular risk clinical data comprises ambulatory blood pressure monitoring (ABPM) data.

3. The system according to claim 2, wherein said cardiovascular risk clinical data further comprises actigraphy data.

4. The system according to claim 3, wherein said cardiovascular risk clinical data further comprises a) demographic data and patient habits, b) patient medical history, c) analytical data including biochemical parameters, d) office blood pressure data, and e) drug therapy data.

5. The system according to claim 1, wherein said statistical methods and analysis techniques are designed to analyze said cardiovascular risk clinical data in order to provide a) hypertension diagnosis, b) assessment of antihypertensive therapies, c) evaluation and stratification of cardiovascular risk, d) classification of dipper status , e) detection of metabolic syndrome, and f) ABPM derived parameters.

6. The system according to claim 5, wherein said hypertension diagnosis comprises a plurality of methods for ABPM and actigraphy data to calculate a plurality of metrics including a) 24-hour global mean and associated standard error, b) detection of awake and asleep period, c) awake and asleep periods means and associated standard errors, d) awake/asleep ratio, and e) dipper classification.

7. The system according to claim 5, wherein said ABPM derived parameters include hyperbaric index and percent of time of elevation, hypobaric index and percent of time of deficit, conventional descriptive statistics, a rhythmometric analysis comprising estimations of rhythm-adjusted mean (MESOR), global amplitude, orthophase and bathyphase with their confidence intervals, morning surge and BP load, and ambulatory arterial stiffness index (AASI).

8. The system according to claim 5, wherein said statistical methods and analysis techniques include methods assessment of antihypertensive treatment reduction, duration, and homogeneity, as well as treatment efficacy.

9. The system according to claim 8, wherein said methods for assessment of antihypertensive treatment reduction, duration, and homogeneity include TP ratio, smoothness index (SI), normalized smoothness index (SIn), and reduction-duration-homogeneity index (RDH) for individual subjects and research populations.

10. The system according to claim 8, further comprising means for analyzing and visualizing administration-time dependent effects and chronotherapy.

11. The system according to claim 6, wherein said means and associated standard errors are calculated based on first calculating an ABPM mean for each hourly interval and then calculating said global mean as a mean of the hourly means.