Uncovering Interim Clinical Events at the Time of Clinical Encounter by Reviewing Intrathoracic Impedance Threshold Crossings

Autor: W. H. Wilson Tang, William J. Wickemeyer, Robin E. Germany, Bobbi L. Hoppe, John A. Andriulli, Peter A. Brady, Shantanu Sarkar, Douglas A. Hettrick, Roy S. Small
Rok vydání: 2011
Předmět:
Zdroj: Journal of Cardiac Failure. 17:893-898
ISSN: 1071-9164
DOI: 10.1016/j.cardfail.2011.07.005
Popis: Background Acute decreases in intrathoracic impedance monitored by implanted devices have been shown to precede heart failure exacerbations, although there is still debate regarding its clinical utility in predicting and preventing future events. However, the usefulness of such information to direct patient encounter and enhance patient recall of relevant preceding clinical events at the point of care has not been carefully examined. Methods and Results In this multicenter study, we interviewed 326 patients with heart failure who received an implanted device with intrathoracic impedance–monitoring capabilities both before and after device information was reviewed. We compared the self-reported clinically relevant events (including heart failure hospitalizations, signs and symptoms of worsening heart failure, changes in diuretic therapy, or other fluid-related events) obtained before and after device interrogation, and then examined the relationship between such events with impedance trends documented by the devices. Over 333 ± 96 days of device monitoring, 215 of 326 patients experienced 590 intrathoracic impedance fluid index threshold–crossing events at the nominal threshold value (60 Ω-d). Review of device-derived information led to the discovery of 221 (37%) previously unreported clinically relevant events in 138 subjects. This included 60 subjects not previously identified as having had clinically relevant events (or 35% of the 171 subjects who did not report events). Conclusions Our data demonstrated that reviewing device-derived intrathoracic impedance trends at the time of clinical encounter may help uncover self-reporting of potential clinically relevant events.
Databáze: OpenAIRE