北华大学学报(自然科学版)

目的 基于单核细胞与高密度脂蛋白比值(MHR)、脑源性神经营养因子(BDNF)、入院NIHSS评分构建急性缺血性脑卒中患者预后的列线图预测模型。方法 纳入急性缺血性脑卒中患者110例作为急性缺血性脑卒中组，同期招募年龄、性别匹配的健康体检者55名作为对照组。收集两组受试者的性别、年龄、饮酒史、吸烟史及急性缺血性脑卒中患者合并基础疾病(糖尿病、高血压)情况、入院时NIHSS评分。采集两组受试者空腹静脉血，检测单核细胞绝对值及高密度脂蛋白、BDNF水平，计算MHR。出院后随访3个月，随访结束时使用改良Rankin量表(mRS)评估患者预后，分为预后良好(0～2分)、预后不良(3～5分)。结果 急性缺血性脑卒中组MHR高于对照组，血清BDNF水平低于对照组(均P<0.05)。预后不良的急性缺血性脑卒中患者MHR高于预后良好患者，血清BDNF水平低于预后良好患者(均P<0.01)。入院NIHSS评分、MHR、BDNF水平是患者预后的独立影响因素。使用R语言绘制上述独立影响因素对急性缺血性脑卒中患者预后的列线图预测模型；使用Bootstrap内部验证法验证模型的区分度，结果显示，校准曲线接近理想曲线，具有较高的校准能力；通过ROC曲线验证该模型，AUC为0.909,95%CI:0.830～0.988,在预测患者预后方面具有较高的准确性。结论 急性缺血性脑卒中患者MHR升高、BDNF水平降低，且与预后密切相关，结合MHR、BDNF水平及入院NIHSS评分构建的列线图预测模型可有效预测患者预后。

Objective To construct a nomogram prediction model for the prognosis of acute ischemic stroke patients based on the monocyte-to-high-density lipoprotein ratio(MHR),brain-derived neurotrophic factor(BDNF),and admission NIHSS scores.Methods A total of 110 patients with acute ischemic stroke were enrolled as acute ischemic stroke group, while 55 age and sex-matched healthy subjects were recruited as control group during the same period.Data on gender, age, alcohol consumption history, smoking status, comorbidities(diabetes, hypertension) with acute ischemic stroke patients, as well as admission NIHSS scores, were collected from both groups.Fasting venous blood samples were collected from both groups to measure absolute monocyte count, high-density lipoprotein, and BDNF levels, and calculate MHR.At the end of the 3-month follow-up after discharge, patient prognosis was assessed using the modified Rankin Scale(mRS),categorized as good prognosis(mRS 0-2) or poor prognosis(mRS 3-5).Results Acute ischemic stroke group demonstrated significantly higher MHR levels compared to control group, while serum BDNF levels were notably lower(both P<0.05).Among acute ischemic stroke patients, those with poor prognosis exhibited markedly elevated MHR and reduced BDNF levels relative to those with good prognosis(both P<0.01).Admission NIHSS scores, MHR,and BDNF levels were independent influencing factors of patient prognosis.Using R language, a nomogram prediction model for the prognosis of patients with acute ischemic stroke was constructed based on the above independent influencing factors.The model's discriminative ability was validated using the Bootstrap internal validation method, and the results showed that the calibration curve was close to the ideal curve, indicating high calibration capability.The model was further validated using the ROC curve, with an AUC of 0.909(95% CI:0.830-0.988),demonstrating high accuracy in predicting patient prognosis.Conclusion In patients with acute ischemic stroke, elevated MHR and decreased BDNF levels are closely associated with prognosis.A nomogram prediction model incorporating MHR,BDNF levels, and admission NIHSS scores can effectively predict patient prognosis.