Hamsi Scoring in the Prediction of Unfavorable Outcomes from Tuberculous Meningitis: Results of Haydarpasa-II Study

Abstract

Predicting unfavorable outcome is of paramount importance in clinical decision making. Accordingly, we designed this multinational study, which provided the largest case series of tuberculous meningitis (TBM). 43 centers from 14 countries (Albania, Croatia, Denmark, Egypt, France, Hungary, Iraq, Italy, Macedonia, Romania, Serbia, Slovenia, Syria, Turkey) submitted data of microbiologically confirmed TBM patients hospitalized between 2000 and 2012. Unfavorable outcome was defined as survival with significant sequela or death. In developing our index, binary logistic regression models were constructed via 200 replicates of database by bootstrap resampling methodology. The final model was built according to the selection frequencies of variables. The severity scale included variables with arbitrary scores proportional to predictive powers of terms in the final model. The final model was internally validated by bootstrap resampling. A total of 507 patients' data were submitted among which 165 had unfavorable outcome. Eighty-six patients died while 119 had different neurological sequelae in 79 (16 %) patients. The full model included 13 variables. Age, nausea, vomiting, altered consciousness, hydrocephalus, vasculitis, immunosuppression, diabetes mellitus and neurological deficit remained in the final model. Scores 1-3 were assigned to the variables in the severity scale, which included scores of 1-6. The distribution of mortality for the scores 1-6 was 3.4, 8.2, 20.6, 31, 30 and 40.1 %, respectively. Altered consciousness, diabetes mellitus, immunosuppression, neurological deficits, hydrocephalus, and vasculitis predicted the unfavorable outcome in the scoring and the cumulative score provided a linear estimation of prognosis.