Background: Introduction of simple bedside tools for assessing patients’ condition in different settings improves triaging. However, these indices are less frequently used in heart failure. This study aims to evaluate the utility of shock index, age shock index, modified shock index, and age-modified shock index in the prediction of in-hospital mortality in acute decompensated heart failure individuals.
Materials and Methods: We conducted this retrospective study on 3652 acute decompensated heart failure individuals in the context of Persian Registry of Cardiovascular Disease/heart failure. Shock index, age shock index, modified shock index, and age-modified shock index were assessed during admission. Receiver operating characteristic curve was used to define the optimum cut-off point. Odds ratio models were used for investigating the association of in-hospital mortality according to each specified cut-off value.
Results: Mean age was 70.12 ± 12.56 years (males: 62.6%). Optimum cut-off point for shock index, age shock index, modified shock index, and age-modified shock index were set to be 0.71 (sensitivity: 63%, specificity: 60%), 50.5 (sensitivity: 65%, specificity: 60%), 0.94 (sensitivity: 60%, specificity: 60%), and 66.7 (sensitivity: 62%, specificity: 60%), respectively. Participants with higher shock index derivatives in all domains had significantly higher likelihood of death. Compared to those with shock index, age shock index, modified shock index, and age-modified shock index values of less than cut-off points, adjusted model revealed patients with higher values had 2.59 (95% CI: 1.94-3.46, P<.001), 2.61 (95% CI: 1.95-3.48, P <.001), 2.14 (95% CI: 1.61-2.84, P <.001), and 2.28 (95% CI: 1.72- 3.03, P <.001) times increase in-hospital death risk, respectively.
Conclusions: Shock index, age shock index, modified shock index, and age-modified shock index are simple bedside tools to reliably predict in-hospital mortality in acute decompensated heart failure patients to better prioritize high-risk subjects.