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Abstract
The neutrophil-to-lymphocyte ratio is an established biomarker reflecting systemic inflammation and immune dysregulation. However, single baseline measurements upon hospital admission often fail to capture the highly dynamic immunological trajectory of patients infected with the severe acute respiratory syndrome coronavirus 2. This study aimed to evaluate the prognostic superiority of early variations in the neutrophil-to-lymphocyte ratio, defined as ΔNLR, compared to static baseline measurements for predicting in-hospital mortality among patients admitted to the emergency department and general medical wards. A systematic review and meta-analysis were strictly conducted according to PRISMA guidelines. Data were meticulously extracted from ten selected observational cohort studies. The primary outcome assessed was in-hospital mortality. Standardized mean differences and 95 percent confidence intervals were calculated utilizing a DerSimonian-Laird random-effects model to appropriately account for anticipated clinical heterogeneity. The comprehensive meta-analysis integrated data from 4582 patients across ten independent studies. Both the baseline neutrophil-to-lymphocyte ratio and the early ΔNLR were significantly elevated in non-survivors compared to survivors. However, the early variation in the ratio, measured precisely at 24 to 48 hours post-admission, demonstrated a significantly higher predictive value for in-hospital mortality. The pooled standardized mean difference for baseline measurements between non-survivors and survivors was 0.82 (95 percent confidence interval: 0.61 to 1.03, p less than 0.001). In stark contrast, the pooled standardized mean difference for the early ΔNLR was 1.34 (95 percent confidence interval: 1.05 to 1.63, p less than 0.001), indicating a substantially stronger effect size and superior prognostic discrimination. In conclusion, early dynamic variations in the neutrophil-to-lymphocyte ratio offer superior prognostic value compared to static baseline measurements for predicting fatal outcomes in COVID-19 patients. Integrating kinetic monitoring into emergency and ward triage protocols can significantly optimize early risk stratification.
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