目的：各种血炎症指标对急性重症脑梗死患者短期预后,为临床预测急性重症脑梗死患者短期预后。

方法：选择2012年11月1日至2023年12月30日期间在本医院NICU住院治疗的200例急性重度脑梗死患者，记录入院后30天的预后结果（存活或死亡），将其分为存活组86例，死亡组有114例。在这两组患者中，收集了患者的性别、年龄、民族、既往病史等信息。年龄>18岁，发病时间<72小时的患者被纳入我们的研究对象。所有患者在住院后24小时内采血检测白蛋白、hs-CRP、中性粒细胞、淋巴细胞和血小板，计算HS-mGPS(HS-mGPS评分并不是简单的比值，而是基于特定标准的评分系统)，并分别计算NLR和PLR。使用NIH卒中量表评分（NIHSS评分）和测量梗死体积来评估患者的病情。数据采用SPSS 27.0软件进行统计学分析，对于正态分布的定量数据，本研究采用均值±标准差进行描述。独立样本t检验用于评估两组间均值的差异。对于非正态分布数据，本研究采用中位数(Md)和四分位数间距(IQR)进行描述，并使用Mann-Whitney U检验来比较两组间的分布差异。定性数据的比较则通过卡方检验(χ²)进行。利用ROC曲线法分析HS-mGPS和各项炎症指标预测30天内急性重度脑梗死患者的临床意义，使用二元逻辑回归分析法评估影响死亡的危险因素，P<0.05被认为是具有统计学意义。

结果：

1.两组患者在性别、年龄、民族、糖尿病、高血压和复发性脑梗死方面的差异均不显著（P＞0.05）。

2.性别、梗死体积及NIHSS评分被识别为影响患者生存的独立预测因子，且统计显著性水平低于0.05。

3.WBC计数、NLR、hs-mGPS评分在两组患者间显示出显著性统计学差异（P<0.05），而白蛋白和血小板计数则未观察到显著差异（P>0.05）。

4.HS-mGPS评分用于预测急性重度脑梗死患者30天内死亡的ROC曲线分析显示，其AUC值为0.627，95%置信区间（CI）为0.524至0.731，且P=0.022。以1作为评分的截止值，其敏感性为25.81%，特异性为91.84%。

5. 各种炎症标志物预测急性重度脑梗死患者30天内死亡的ROC曲线AUC值：NLR为0.658，NLR 0.657、hs-CRP为0.637和WBC0.634。

 

 

结论：

1.急性重症脑梗死患者的梗死体积和NIHSS评分是影响患者死亡的独立因素。

2.HS-mGPS评分、hs-CRP和NLR可预测重症脑梗死患者短期死亡率，其中NLR预测效果最佳。

 

关键词：急性重症脑梗死：NLR：HS-mGPS 评分，Hs-CRP。

 

Objectives: To explore the use of various blood inflammatory indicators for predicting the short-term prognosis of patients with acute severe cerebral infarction and to provide clinical guidance based on these indicators.

Method: Based on their 30-day result (survival or death), a cohort of 200 individuals suffering from acute severe cerebral infarction was admitted to the NICU ward of Yanbian University Hospital's Department of Neurology between November 2012 and December 2023 were collected and split into two groups. The group that survived consisted of 86 cases, whereas the group that died consisted of 114 cases. Among both the group, the information like the patient's name, gender, age, ethnicity, history of prior illnesses was gathered. Patient’s age >18 years were only included in our study with onset of symptoms being <72 hours of duration. While patients hospitalised for a non-neurological condition and experienced a stroke while inpatient and having a documented history of infectious disease and a known history of tumours prior to admission and medical background of severe renal and liver disorders were excluded from our study. All patients had blood sampled within 24 hours of their hospitalisation, and markers including albumin, hs-CRP, neutrophils, lymphocytes, and platelets were measured. HS-mGPS was carried out using albumin and hs-CRP, and NLR and PLR were determined, respectively. Assessment of the patient’s condition done using NIH stroke scale score (NIHSS score) and by measurement of the infract volume. The SPSS 27.0 software package was used for statistical analysis of the data. Means ± and standard deviations were utilized to characterize the distribution of quantitative data that conformed to a normal distribution. Comparative analyses between groups were conducted using independent sample t test. The median and quartiles were used to describe non-normal distribution. For the distribution of quantitative data, the Mann-Whitney U test was used to compare differences between groups; for qualitative data, the x² test was used. The number of indicators were correlated between the two groups, independent factors influencing death were assessed using binary logistic regression analysis, and the predictive efficacy of inflammatory biomarkers, including HS-mGPS, NLR, hs-CRP, and other measures on short term clinical outcomes of paitents with acute severe cerebral infarction within thirty day timeframe was evaluated using a ROC curve. In this study, all statistical assessments are conducted useing two-tailed tests（P<0.05）.

Results:

1. Age, ethnicity, diabetes mellitus, hypertension, and recurrent cerebral infarction did not significantly differ between the death group and the survivor cohort (P<0.05).

2. Between the two groups, gender, and NIHSS score were independent predictors of death (P<0.05).

3. The two groups differed significantly in terms of white blood cell and neutrophil count, NLR, and HS-mGPS scores (P<0.05). Albumin and platelet counts showed no significant difference between groups (P>0.05).

4. The following were the findings of the ROC curve of the HS-mGPS score for the prediction of mortality in patients who had an acute, severe cerebral infarction within thirty days: The HS-mGPS score demonstrated an AUC of 0.627, with a 95% CI of 0.524-0.731 and a P-value of 0.022, using a cut-off of 1, yielding 25.81% sensitivity and 91.84% specificity.

 5. The AUC values of various inflammatory markers' ROC curves for predicting the death within 30 days in patients with acute severe cerebral infarction are as follows: NLR is 0.658, NLR 0.657, hs-CRP is 0.637, and WBC is 0.634.

Conclusion:

1.The infarct volume and NIHSSscore are independent factors affecting the mortality of patients with acute severe cerebral infarction.

2.The High Sensitivity Glasgow Prognostic Score (HS-mGPS), high-sensitivity C-reactive protein (hs-CRP), and Neutrophil-to-Lymphocyte Ratio (NLR) can predict the short-term mortality rate in patients with severe cerebral infarction, with the NLR showing the best predictive effect.

Key words: Acute severe cerebral infarction; NLR；HS-mGPS score;  hs-CRP

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