Abstract
Background Cardiogenic brain abscess (CBA) is the commonest noncardiac cause of morbidity and mortality in cyanotic heart disease (CHD). The clinical diagnosis of a CBA is often delayed due to its nonspecific presentations and the scarce availability of computed tomography (CT) imaging in resource-restricted settings. We attempted to identify parameters that reliably point to the diagnosis of a CBA in patients with Tetralogy of Fallot (TOF). Methods From among 150 children with TOF treated at a tertiary care institute over a 15-year period from 2001 to 2016, 30 consecutive patients with CBAs and 85 age- and sex-matched controls without CBAs were included in this retrospective case-control study. Demographic and clinical features, laboratory investigations, and baseline echocardiographic findings were analyzed for possible correlations with the presence of a CBA. Statistical Analysis Variables demonstrating significant bivariate correlations with the presence of a CBA were further analyzed using multivariate logistic regression (LR) analysis. Various LR models were tested for their predictive value, and the best model was then validated on a hold-out dataset of 25 patients. Results Among the 26 variables tested for bivariate associations with the presence of a CBA, some of the clinical, echocardiographic, and laboratory variables demonstrated significant correlations ( p < 0.05). LR analysis revealed elevated neutrophil-lymphocyte ratio and erythrocyte sedimentation rate values and a lower age-adjusted resting heart rate percentile to be the strongest independent biomarkers of a CBA. The LR model was statistically significant, (χ (2) = 23.72, p = <0.001), and it fitted the data well. It explained 53% (Nagelkerke R 2 ) of the variance in occurrence of a CBA, and correctly classified 83.93% of cases. The model demonstrated a good predictive value (area under the curve: 0.80) on validation analysis. Conclusions This study has identified simple clinical and laboratory parameters that can serve as reliable pointers of a CBA in patients with TOF. A scoring model-the 'BA-TOF' score-that predicts the occurrence of a CBA has been proposed. Patients with higher scores on the proposed model should be referred urgently for a CT confirmation of the diagnosis. Usage of such a diagnostic aid in resource-limited settings can optimize the pickup rates of a CBA and potentially improve outcomes.