A prognostic model for 1-month mortality in the postoperative intensive care unit.

Purposes: Recognizing which patients admitted postsurgically to the intensive care unit (ICU) are at greater risk of mortality assists medical staff to identify who will benefit most from the care. We developed a prediction model for the 1-month mortality of postsurgical ICU patients.

Methods: From May, 2019 to May, 2020, we conducted a prospective cohort study in the postsurgical ICU of a teaching hospital affiliated with our University of Medical Sciences. The outcome was death within 1 month of admission and the predictors were a variety of anthropometric and clinical features. The subjects of this analysis were 805 consecutive adult postsurgical patients with a mean (SD) age of 54.8 (18.9) years.

Results: Overall, the resulted logistic model was well-fitted [χ (26) = 772.097, p < 0.001, Nagelkerke R = 0.814] accurate (88%), and specific (92%). The adjusted odds ratio for body temperature was 0.51, p < 0.001. Patients with comorbidities and those undergoing multiple operations were at a greater risk of mortality, odds = 10.00 and 10.65 (both p < 0.001).

Conclusions: Higher body temperature at the time of postoperative ICU admission is a protective factor against 1-month mortality. Our study found that patients with several comorbidities and those who have undergone multiple operations are at a greater risk of a poor outcome.