Objectives: Stroke is the second leading cause of death and the third leading cause of disability globally, so monitoring inflammation and nutritional levels is essential for the secondary prevention. The impact of the Prognostic Nutritional Index (PNI) on tumor and perioperative outcomes has been demonstrated as an optimal combination of immune and nutritional indicators. However, the role of PNI on hospitalized outcomes in stroke patients remains unknown. This study aimed to investigate the clinical predictive value of PNI on hospitalized outcomes in stroke patients.
Materials and methods: In this study, stroke cases in the Medical Information Mart for Intensive Care IV database were analyzed using two-sample comparisons, proportional hazards model, subgroup analyses, and ROC analyses, and a nomogram was constructed.
Results: 1795 stroke cases were included in this study, including 1537 in the survival group and 258 in the death group. The results showed that PNI was higher in the survival group than in the death group (43.98±0.21 vs. 36.09±0.49, P=0.001). The optimal regression equation obtained after screening variables using COX stepwise regression included age, GCS score, hypertension, PNI, leukocytes, and PT (C-index=0.730). The optimal regression equation showed that each increase in the PNI value was associated with a 6.6 % reduction in patient mortality, holding all other factors constant (HR 0.934, 95 %CI 0.914-0.954, P<0.008). Subgroup analyses showed that the Optimum regression equation was more effective in predicting hospitalized mortality in Hemorrhagic Stroke than in Ischemic Stroke (C-index: 0.803 vs. 0.703). ROC analysis revealed that the cut-off value of PNI for predicting hospital mortality in stroke patients was 37.45. The Kaplan-Meier curves clearly show that patients with PNI>37.45 have a higher survival rate than the low PNI group.
Conclusions: Higher PNI is associated with better hospitalization outcomes for stroke patients. PNI can be used as a supplement to existing indicators, which helps predict the survival of stroke inpatients and provides reference value for clinical treatment.
Keywords: Hemorrhagic stroke; Ischemic stroke; Nomograms; Nutrition Assessment; Prognostic Nutritional Index; Proportional hazards models; Stroke.
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