Systemic Inflammation Predict Neurological Functional Outcome in Patients with Tuberculous Meningitis: A Multicenter Retrospective Cohort Study in China.

Abstract

Background: The predictors associated with clinical outcomes in patients with tuberculous meningitis (TBM) remain unclear. We aimed to analyse the relationship between systemic inflammation and clinical outcomes, as well as to explore whether systemic inflammation level influences the effectiveness of dexamethasone on treatment.

Methods: Between January 2011 and December 2021, TBM patients admitted to five hospitals were observed consecutively. Baseline and post-treatment systemic inflammation levels were calculated using the neutrophil-lymphocyte-ratio (NLR). Generalized linear mixed models were employed to identify predictors of clinical outcomes. Propensity score matching and subgroup analyses were conducted to evaluate the effect of dexamethasone on treatment outcomes across different NLR levels.

Results: A total of 1203 TBM patients were included in the study. During the follow-up, 144 (13.6%) participants experienced early neurological deterioration within 7 days after admission, and 345 (28.67%) exhibited poor functional outcome at the 12-month follow-up. Multivariate analysis revealed that post-treatment NLR was significantly associated with early neurological deterioration (OR=1.25; 95% CI, 1.14-1.33; P<0.001), and poor outcome (OR=1.34; 95% CI, 1.26-1.45; P<0.001). After propensity score matching, dexamethasone treatment was not associated with early neurological deterioration (OR=0.83; 95% CI, 0.42-1.66; P=0.610) or poor outcome (OR=1.22; 95% CI, 0.49-2.11; P=0.490) in the highest quartile of post-treatment NLR. The effect of dexamethasone on treatment outcomes did not significantly vary with disease severity stratification.

Conclusion: Elevated systemic inflammation is an independent risk factor for neurological outcome in TBM patients. Further studies are required to investigate systemic inflammation in more severely affected population to better predict the outcomes following anti-inflammatory therapies.