ABSTRACT
ABSTRACT: Deceleration capacitiy for rapid risk stratification in stroke patientsCerebral ischemia is a major cause of neurologic deficit and patients suffering from ischemic stroke bear a relevant risk of mortality. Identifying stroke patients at high mortality risk is of crucial clinical relevance. Deceleration capacity of heart rate (DC) as a parameter of cardiac autonomic function is an excellent predictor of mortality in myocardial infarction and heart failure patients.The aim of our study was to evaluate whether DC provides prognostic information regarding mortality risk in patients with acute ischemic stroke.From September 2015 to March 2018 we prospectively enrolled consecutive patients presenting at the Stroke Unit of our university hospital with acute ischemic stroke who were in sinus rhythm. In these patients 24 hours-Holter-ECG recordings and evaluation of National Institute of Health Stroke Scale (NIHSS) were performed. DC was calculated according to a previously published algorithm. Primary endpoint was intrahospital mortality.Eight hundred seventy eight stroke patients were included in the study. Intrahospital mortality was 2.8% (25 patients). Both DC and NIHSS were significantly different between non-survivors and survivors (Meanâ±âSD: DC: 4.1â±â2.8 ms vs 6.3â±â3.3 ms, Pâ<â.001) (NIHSS: 7.6â±â7.1 vs 4.3â±â5.5, Pâ=â.02). DC achieved an area under the curve value (AUC) of 0.708 for predicting intrahospital mortality, while the AUC value of NIHSS was 0.641. In a binary logistic regression analysis, DC, NIHSS and age were independent predictors for intrahospital mortality (DC: HR CI 95%: 0.88 (0.79-0.97); Pâ=â.01; NIHSS: HR CI 95%: 1.08 (1.02-1.15); Pâ=â.01; Age: HR CI 95%: 1.07 (1.02-1.11); Pâ=â.004. The combination of NIHSS, age and DC in a prediction model led to a significant improvement of the AUC, which was 0.757 (Pâ<â.001, incremental development index [IDI] 95% CI: 0.037 (0.018-0.057)), compared to the individual risk parameters.Our study demonstrated that DC is suitable for both objective and independent risk stratification in patients suffering from ischemic stroke. The application of a prediction model combining NIHSS, age and DC is superior to the single markers in identifying patients at high mortality risk.