జర్నల్ ఆఫ్ పెయిన్ మేనేజ్‌మెంట్ & మెడిసిన్

నైరూప్య

A New Predictive Model for the Time of Cardiac Arrest in-ICU Palliative Care Patients: A Single Center Retrospective Cohort Study

Shunsuke Takaki

Objective: The aim of this study was to develop a predictive model for the time of cardiac arrest in the palliative care setting in the intensive care unit.

Design: We retrospectively collected patients’ data in intensive care unit between 2010 and 2016. Vital signs were collected until cardiac arrest occurred and Systolic Blood Pressure (SBP) was continuously recorded when it was less than 80 mmHg. We hypothesized that a breakdown of the autonomic nervous system was associated with the time of cardiac arrest. We aimed develop predictive model for determine a time at 120 minutes before cardiac arrest. We used the Shock Index (SI) defined as heart rate divided by SBP as the ratio variable to identify an end-of-life phase.

Results: A total of 4,330 patients were admitted to the ICU and 19 patients out of them were included to this study. We developed a prediction model by using SI and SBP: predicted SI=0.995+(6.931-0.995) e-0.035 x SBP with AUC 0.650 (0.512 to 0.788). The disparity between the actual and predicted heart rate was -10 bpm (49.9%, sensitivity; 75.8%, specificity; and likelihood ratio, 2.06). In the validation set, sensitivity was 52.7%, specificity was 79.8%, positive predictive value was 35.7%, negative predictive value was 88.8%, and likelihood ratio was 2.61.

Conclusion: Our new prediction model estimates the time to death 120 minutes before cardiac arrest occurs based on the information of fluctuation of shock index.