Introduction:

the incidence of postoperative low cardiac output syndrome is variable in the different published series, from 4% to 15%, with a mortality that approaches 20%. Although in patients over 70 years of age the syndrome may be present in up to 63%, despite the development of better cardioprotection techniques and postoperative care, the incidence of this syndrome in high-risk populations has not changed in a significant proportion.

Objective:

build a predictive model of postoperative low cardiac output syndrome through risk factors.

Methods:

an analytical study of cases and controls was carried out in patients with postoperative low cardiac output syndrome treated at the Cardiology and Cardiovascular Surgery Center of the “Saturnino Lora” Provincial Teaching Hospital of Santiago de Cuba, in a period of three years; Logistic regression with adjustments was used to obtain the model.

Results:

the most valuable predictive risk factors are: age >65 years, decreased right ventricular systolic function, aortic cross-clamping time and postoperative bleeding, which were those shown by the logistic regression model. Its internal validation was carried out by data division.

Conclusions:

the predictive model developed from logistic regression was composed of the predictors: age >65 years, decreased right ventricular systolic function, aortic clamping time >90 minutes and prolonged postoperative bleeding; It presented good fit and discriminating power, especially positive predictive value.

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