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白细胞与血红蛋白比值对重症脑出血患者30天死亡率的预测价值

Predictive value of white blood cell to hemoglobin ratio for 30-day mortality in patients with severe intracerebral hemorrhage.

作者信息

Liu Lei, Dong Xuetao, Liu Yaodong, Wang Shaozhen, Wei Liudong, Duan Lian, Zhang Qingjun, Zhang Kun

机构信息

Department of Neurosurgery, Chui Yang Liu Hospital Affiliated to Tsinghua University, Beijing, China.

出版信息

Front Neurol. 2024 Jan 12;14:1222717. doi: 10.3389/fneur.2023.1222717. eCollection 2023.

DOI:10.3389/fneur.2023.1222717
PMID:38283683
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10811233/
Abstract

AIM

To explore the predictive value of white blood cell to hemoglobin ratio (WHR) for 30-day mortality in patients with intracerebral hemorrhage (ICH).

METHODS

In this cohort study, 2,848 patients with ICH were identified in the Medical Information Mart for Intensive Care (MIMIC)-III and MIMIC-IV. Least absolute shrinkage and selection operator (LASSO) regression screened covariates of 30-day mortality of ICH patients. COX regression analysis was used to study the association of different levels of WHR, white blood cell (WBC), and hemoglobin (Hb) with 30-day mortality. The median follow-up time was 30 (20.28, 30.00) days.

RESULTS

In total, 2,068 participants survived at the end of the follow-up. WHR was negatively correlated with the Glasgow Coma Score (GCS) (spearman correlation coefficient = -0.143, < 0.001), and positively associated with the Sepsis-related Organ Failure Assessment (SOFA) score (spearman correlation coefficient = 0.156, < 0.001), quick SOFA (qSOFA) score (spearman correlation coefficient = 0.156, < 0.001), and Simplified Acute Physiology Score II (SAPS-II) (spearman correlation coefficient = 0.213, < 0.001). After adjusting for confounders, WHR >0.833 (HR = 1.64, 95%CI: 1.39-1.92) and WBC >10.9 K/uL (HR = 1.49, 95%CI: 1.28-1.73) were associated with increased risk of 30-day mortality of patients with ICH. The area under the curve (AUC) value of the prediction model based on WHR and other predictors was 0.78 (95%CI: 0.77-0.79), which was higher than SAPSII (AUC = 0.75, 95%CI: 0.74-0.76), SOFA score (AUC = 0.69, 95%CI: 0.68-0.70) and GCS (AUC = 0.59, 95%CI: 0.57-0.60).

CONCLUSION

The level of WHR was associated with 30-day mortality in patients with severe ICH, and the WHR-based prediction model might provide a tool to quickly predict 30-day mortality in patients with ICH.

摘要

目的

探讨白细胞与血红蛋白比值(WHR)对脑出血(ICH)患者30天死亡率的预测价值。

方法

在本队列研究中,从重症监护医学信息数据库(MIMIC)-III和MIMIC-IV中识别出2848例ICH患者。采用最小绝对收缩和选择算子(LASSO)回归筛选ICH患者30天死亡率的协变量。使用COX回归分析研究不同水平的WHR、白细胞(WBC)和血红蛋白(Hb)与30天死亡率的关联。中位随访时间为30(20.28,30.00)天。

结果

共有2068名参与者在随访结束时存活。WHR与格拉斯哥昏迷评分(GCS)呈负相关(斯皮尔曼相关系数=-0.143,<0.001),与脓毒症相关器官功能衰竭评估(SOFA)评分(斯皮尔曼相关系数=0.156,<0.001)、快速SOFA(qSOFA)评分(斯皮尔曼相关系数=0.156,<0.001)和简化急性生理学评分II(SAPS-II)呈正相关(斯皮尔曼相关系数=0.213,<0.001)。在调整混杂因素后,WHR>0.833(HR=1.64,95%CI:1.39-1.92)和WBC>10.9 K/μL(HR=1.49,95%CI:1.28-1.73)与ICH患者30天死亡风险增加相关。基于WHR和其他预测因素的预测模型的曲线下面积(AUC)值为0.78(95%CI:0.77-0.79),高于SAPSII(AUC=0.75,95%CI:0.74-0.76)、SOFA评分(AUC=0.69,95%CI:0.68-0.70)和GCS(AUC=0.59,95%CI:0.57-0.60)。

结论

WHR水平与重症ICH患者的30天死亡率相关,基于WHR的预测模型可能为快速预测ICH患者的30天死亡率提供一种工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95fc/10811233/df717bfc30b9/fneur-14-1222717-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95fc/10811233/fa53f96c13ac/fneur-14-1222717-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95fc/10811233/152f1a465e53/fneur-14-1222717-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95fc/10811233/df717bfc30b9/fneur-14-1222717-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95fc/10811233/fa53f96c13ac/fneur-14-1222717-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95fc/10811233/152f1a465e53/fneur-14-1222717-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95fc/10811233/df717bfc30b9/fneur-14-1222717-g003.jpg

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本文引用的文献

1
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JAMA Netw Open. 2023 Mar 1;6(3):e231455. doi: 10.1001/jamanetworkopen.2023.1455.
2
Intracerebral Hemorrhage Genetics.脑出血遗传学。
Genes (Basel). 2022 Jul 15;13(7):1250. doi: 10.3390/genes13071250.
3
Cerebral Hemorrhage: Pathophysiology, Treatment, and Future Directions.脑出血:病理生理学、治疗和未来方向。
Circ Res. 2022 Apr 15;130(8):1204-1229. doi: 10.1161/CIRCRESAHA.121.319949. Epub 2022 Apr 14.
4
The impact of heart rate circadian rhythm on in-hospital mortality in patients with stroke and critically ill: Insights from the eICU Collaborative Research Database.心率昼夜节律对卒中及危重症患者院内死亡率的影响:来自 eICU 协作研究数据库的见解。
Heart Rhythm. 2022 Aug;19(8):1325-1333. doi: 10.1016/j.hrthm.2022.03.1230. Epub 2022 Mar 31.
5
Impact of central venous pressure on the mortality of patients with sepsis-related acute kidney injury: a propensity score-matched analysis based on the MIMIC IV database.中心静脉压对脓毒症相关急性肾损伤患者死亡率的影响:基于MIMIC IV数据库的倾向评分匹配分析
Ann Transl Med. 2022 Feb;10(4):199. doi: 10.21037/atm-22-588.
6
Novel targets, treatments, and advanced models for intracerebral haemorrhage.脑出血的新靶点、新疗法和先进模型。
EBioMedicine. 2022 Feb;76:103880. doi: 10.1016/j.ebiom.2022.103880. Epub 2022 Feb 12.
7
Long-Term Survival, Causes of Death, and Trends in 5-Year Mortality After Intracerebral Hemorrhage: The Tromsø Study.脑出血后长期生存、死因和 5 年死亡率趋势:特罗姆瑟研究。
Stroke. 2021 Dec;52(12):3883-3890. doi: 10.1161/STROKEAHA.120.032750. Epub 2021 Sep 9.
8
Monocyte to high-density lipoprotein cholesterol ratio is associated with the presence of carotid artery disease in acute ischemic stroke.单核细胞/高密度脂蛋白胆固醇比值与急性缺血性脑卒中患者颈动脉疾病的发生有关。
Biomark Med. 2021 May;15(7):489-495. doi: 10.2217/bmm-2020-0705. Epub 2021 Apr 15.
9
Intracerebral Hemorrhage Incidence, Mortality, and Association With Oral Anticoagulation Use: A Population Study.脑出血发病率、死亡率及其与口服抗凝药物使用的关系:一项人群研究。
Stroke. 2021 May;52(5):1673-1681. doi: 10.1161/STROKEAHA.120.032550. Epub 2021 Mar 9.
10
Predicting new silent cerebral infarction after intracerebral hemorrhage using serum white blood cell count.利用血清白细胞计数预测脑出血后新发无症状性脑梗死
Caspian J Intern Med. 2021 Winter;12(1):97-102. doi: 10.22088/cjim.12.1.97.