Clinical Trial: Logical Analysis of Data and Cardiac Surgery Risk

Study Status: Completed
Recruit Status: Completed
Study Type: Observational

Official Title:

Brief Summary: To use a new statistical method, the Logical Analysis of Data (LAD), to predict cardiac surgery risk.

Detailed Summary:

BACKGROUND:

One of the most important tasks that cardiovascular clinicians perform is risk stratification, as that enables appropriate targeting of aggressive treatments to patients that are most likely to benefit from them. Contemporary risk stratification strategies include clinical scoring systems along with performance of noninvasive tests. Although these approaches are commonly used, clinicians still find themselves needing to incorporate multiple pieces of clinical information into a cohesive global risk assessment. The concept of utilizing data from large observational data sets to develop complex risk scores and to encourage their use in routine practice is therefore gradually evolving and gaining acceptance. The Logical Analysis of Data (LAD) is a potentially useful approach for systematically analyzing large databases for the purpose of developing and validating clinically useful risk prediction schemes. Unlike standard regression techniques, LAD does not primarily focus on individual risk factors and two-way interactions between them. Rather, LAD is designed to identify complex patterns of findings, or syndromes, that predict outcomes. This method has been applied to problems in economics, seismology and oil exploration, but not to medicine.

DESIGN NARRATIVE:

The study has three specific aims: 1). to apply LAD to develop and validate risk prediction instruments among patients undergoing different types of cardiac surgery. 2. to compare the predictive value of LAD predictive instruments with predictive instruments developed using standard statistical methods, including multiple time-phase parametric modeling. 3. to develop predictive instruments using relative risk forests, a new Monte Carlo method for estimating risk values in large survival data settings with la
Sponsor: National Heart, Lung, and Blood Institute (NHLBI)

Current Primary Outcome:

Original Primary Outcome:

Current Secondary Outcome:

Original Secondary Outcome:

Information By: National Heart, Lung, and Blood Institute (NHLBI)

Dates:
Date Received: April 19, 2004
Date Started: July 2004
Date Completion:
Last Updated: July 28, 2016
Last Verified: January 2008