To analyze, hierarchically, factors associated with hospital readmissions for acute coronary syndrome.
Hospital readmissions have risen, especially in patients with multiple comorbidities, which are most often chronic. The leading causes of hospital readmission include acute coronary syndrome, which is costly and often preventable. Determining clinical and non-clinical variables that increase the chances of readmission is important to assess and evaluate patients hospitalized for coronary heart diseases.
A case-control study whose dependent variable was hospital readmission for acute coronary syndrome.
The study included 277 inpatients, of whom 132 were in their first hospitalization and 145 had already been hospitalized for acute coronary syndrome. The independent variables for this hierarchical model were sociodemographic conditions, life habits, access to health services, and physical health measures. Data were obtained by interviews, anthropometric measurements, and patient records. Logistic regression analysis was performed using the stepwise technique, with Microsoft Excel and R version 3.2.3. The research was reported via the Reporting of Observational Studies in Epidemiology (STROBE).
In the final hierarchical logistic model, the following risk factors were associated with readmission for acute coronary syndrome: inadequate drug therapy adherence, stress, history of smoking for 30 years or more, and the lack of use of primary care health services.
Clinical and non-clinical variables are related to hospital readmission for acute coronary syndrome and can increase the chance of readmission by up to six times.
The predictive model can be used to avoid readmission for acute coronary syndrome, and it represents an advance in the prediction of the occurrence of the outcome. This implies the need for a reorientation of the network for post-discharge care in the first hospitalization for acute coronary syndrome.

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