Influence of inflammatory status in the acute phase of stroke on post-stroke depression.

ABSTRACT

BACKGROUND: Thirty percent of stroke patients will suffer from post-stroke depression (PSD). Recent data suggest that inflammation accounts for a substantial amount of depression. Our primary objective was to assess the association between standard inflammation biomarkers in the acute phase of stroke and PSD at three months. The secondary objective was to elaborate a predictive model of PSD from clinical, biological and radiological data. METHODS: We performed a retrospective analysis of a single-centre cohort of stroke patients with a three-month follow-up. Serum levels of C-reactive protein (CRP), fibrinogen, leukocyte count and neutrophil to lymphocyte ratio (NLR) were tested at admission and at peak. Mood was assessed at three months using the depression sub-scale of the Hospital Anxiety and Depression Scale (HADS). Association between inflammation biomarkers and HADS was evaluated with multi-linear regression adjusted on clinical and radiological parameters. Logistic predictive models of PSD at three months, with and without inflammation biomarkers, were compared. RESULTS: Three hundred and forty-eight patients were included, of whom 20.06% developed PSD. Baseline and peak values of all inflammatory markers were associated with the severity of PSD at three months. Area under the curve for the receiver operating characteristic curve of PSD prediction was 0.746 (CI 95% 0.592-0.803) with selected inflammation biomarkers and 0.744 (CI 95% 0.587-0.799) without. CONCLUSION: Most inflammation biomarkers are weakly associated with PSD, adding negligible value to predictive models. While they suggest the implication of inflammation in PSD pathogenesis, they are useless for the prediction of PSD, underscoring the need for more specific biomarkers.