Artificial Inteligence-Based Decision for the Prediction of Cardioembolism in Patients with Chagas Disease and Ischemic Stroke.

BACKGROUND: Chagas disease (CD) and ischemic stroke (IS) have a close, but poorly understood, association. There is paucity of evidence on the ideal secondary prophylaxis and etiological determination, with few cardioembolic patients being identified. AIMS: This study aimed to describe a multicenter cohort of patients with concomitant CD and IS admitted in tertiary centers and to create a predictive model for cardioembolic embolism in CD and IS. MATERIALS AND METHODS: We retrospectively studied data obtained from electronic medical and regular medical records of patients with CD and IS in several academic, hospital-based, and university hospitals across Brazil. Descriptive analyses of cardioembolic and non-cardioembolic patients were performed. A prediction model for cardioembolism was proposed with 70% of the sample as the derivation sample, and the model was validated in 30% of the sample. RESULTS: A total of 499 patients were analyzed. The median age was similar in both groups; however, patients with cardioembolic embolism were younger and tended to have higher alcoholism, smoking, and death rates. The predictive model for the etiological classification showed close relation with the number of abnormalities detected on echocardiography and electrocardiography as well as with vascular risk factors. CONCLUSIONS: Our results replicate in part those previously published, with a higher prevalence of vascular risk factors and lower median age in patients with cardioembolic etiology. Our new model for predicting cardioembolic etiology can help identify patients with higher recurrence rate and therefore allow an optimized strategy for secondary prophylaxis.

Mortality and Stroke Recurrence in a Rehabilitation Cohort of Patients with Cerebral Infarcts and Chagas Disease.

BACKGROUND: Chagas disease is related to ischemic stroke (IS), although few epidemiological studies have evaluated the associated mortality and recurrence. Our objective is to determine factors associated with mortality and recurrence of IS in patients with IS and Chagas disease. METHODS: We retrospectively studied data obtained from electronic medical records of patients admitted at SARAH Hospitals across Brazil between 2009 and 2013. Using Cox regression analysis for mortality and logistic regression for recurrence, we assessed primary population characteristics and statistical associations between risk factors and outcomes. RESULTS: We analyzed 279 patients who were followed up until 2016. The mean age at stroke onset was 61 with a 10% frequency of death. Multivariate analysis assessing mortality demonstrated that the associated factors were age at stroke (hazard ratio [HR] 1.04), initial modified Rankin Scale (mRS; HR 20.91), bladder dysfunction (HR 2.51), diabetes mellitus (DM; HR 3.64), and alcoholism (HR 3.37). Multivariate analysis assessing recurrence demonstrated that the associated factors were age at ictus (OR 0.96), cognitive deficit (OR 0.44), initial mRS (OR 1.84), cardioembolic etiology (OR 2.47), and female sex (OR 2.73). CONCLUSIONS: Cardiac conditions did not correlate with mortality or recurrence. Age was a protective factor against recurrence, probably due to cumulative risk of IS over time, while initial mRS was associated with both outcomes. Treating diseases such as DM and bladder dysfunction, and early treatment to reduce the initial mRS could potentially prevent both outcomes; also, establishing a correct etiological diagnosis is important.