Clinical and Laboratory Markers of Brain Abscess in Tetralogy of Fallot ('BA-TOF' Score): Results of a Case-Control Study and Implications for Community Surveillance.

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.