Clinical application of HALP score to predict early neurological deterioration in elderly acute cerebral infarction patients

Abstract Background : Early neurological deterioration (END) may be associated with poor prognosis in elderly AIS patients. The objective of this study was to examine the relationship between a composite biomarker HALP score and END, to identify patients at risk for poor neurological function. METHODS : This study retrospectively examined elderly patients with AIS admitted to Nanjing Drum Tower Hospital from January 2016 to December 2021. NIHSS were collected within 7 days of admission. END was defined as a 2 point increase in NIHSS within 7 days.. the formula for HALP score was lymphocytes (/L) ×hemoglobin (g/L) ×albumin (g/L) / platelets (/L). Multivariate logistic regression was used to construct a prediction model for HALP score, ROC curves and calibration graphs were computed. Results : A total of 431 elderly AIS patients were included, with END accounting for 34.34%. Univariate analysis showed that age, baseline NIHSS score, white blood cell count, lymphocyte count, hemoglobin, triglycerides, HALP score, CRP, Hcy, Lp-PLA2, infectious events and death events differed between the two groups ( P < 0.05). Multifactorial logistic regression analysis revealed that HALP score (OR 0.965, 95% CI 0.943 to 0.988, P =0.003) and baseline NIHSS score (OR 1.169, 95% CI 1.119 to 1.220, P <0.001) were good at predicting END. The area under the ROC curve for HALP score <27.69 and NIHSS score >5.5 was 0.727 (95CI: 0.676-0.778); 0.868 (95CI: 0.834-0.903), respectively, and the combined AUC was 0.883 (95%CI: 0.850-0.916). Additionally, HALP score was significantly negatively correlated with baseline NIHSS ( r =-0.411, P <0.001) and admission day 7 NIHSS ( r =-0.348, P <0.001), respectively. More often the lower HALP score, the higher END percentage and the worse 90-day functional outcomes. Conclusion : A low HALP score at admission is associated with the occurrence of END within one week in elderly AIS patients, which may help clinicians to identify high-risk END patients early.