Predictive roles of inflammatory indicators (NLR, PLR, LMR and SII) in poststroke depression rehabilitation: a systematic review

Acute ischemic stroke (AIS) is a leading cause of mortality and long-term disability worldwide. Almost all AIS survivors suffer physical disabilities and neuropsychiatric disturbances, among which poststroke depression (PSD) is a typical poststroke complication. The development of new tools to diagnose PSD at the early stage and predict its long-term outcome has attracted the attention of clinicians and researchers. Neuroinflammation has been increasingly considered a critical modulator of stroke evolution. Following an IS, an inflammatory response arises in the CNS, characterized by the activation of microglia; the recruitment of peripheral immune cells, including neutrophils, monocytes, and lymphocytes; and the release of proinflammatory cytokines. In this review, we present a comprehensive and critical examination of the diagnostic and predictive roles of inflammatory indicators, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammation index (SII), in PSD. A systematic literature search on PubMed, Google Scholar, Web of Science, and CNKI was performed up to January 31, 2026. Quality assessment was conducted using the Newcastle–Ottawa Scale (NOS), and heterogeneity was evaluated using the I 2 statistic. Nine original studies involving 2,626 patients were included. Compared with non-PSD (NPSD) patients, PSD patients had a significantly greater NLR ( MD = 0.47, 95% CI [0.39, 0.56], I 2 = 49%), PLR ( MD = 20.79, 95% CI [12.25, 29.33], I 2 = 90%), and SII ( MD = 123.92, 95% CI [68.85, 178.98], I 2 = 70%) and a significantly lower LMR ( MD = −0.21, 95% CI [−0.34, −0.08], I 2 = 64%). Most included studies were rated as moderate-to-high quality on the basis of their NOS scores. These findings suggest that the NLR, PLR, LMR, and SII may serve as accessible peripheral blood biomarkers for early risk assessment of PSD, although further research is needed to establish optimal cutoff values and validate their predictive utility across different stroke subtypes.