整合中性粒细胞白蛋白比值和甘油三酯:预测急性缺血性脑卒中患者自发性出血转化的新指标。

IF 4.8 1区 医学 Q1 NEUROSCIENCES
Jiajia Bao, Mengmeng Ma, Kongyuan Wu, Jian Wang, Muke Zhou, Jian Guo, Ning Chen, Jinghuan Fang, Li He
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引用次数: 0

摘要

背景:出血性转化(HT)是急性缺血性卒中(AIS)的一种悲剧性并发症,即使没有再灌注治疗,自发性HT (sHT)也会发生。尽管有证据表明几种炎症生物标志物与HT密切相关,但其在sHT风险分层中的应用仍不清楚。本研究旨在识别和整合与sHT相关的有效炎症生物标志物,并建立一种新的早期检测sHT的nomogram模型。方法:采用前瞻性维护的数据库,对2022年3月至2023年3月仅接受常规药物治疗的AIS患者进行回顾性观察队列研究。所有患者均于入院后7天内行CT随访,观察该时间段内发生sHT的情况。收集了人口统计学、临床信息、实验室结果和影像学数据。队列分为训练集和验证集(7:3)。最小绝对收缩和选择算子(LASSO)回归选择炎症生物标志物为一个新的指数。进行单变量和多变量logistic回归,以确定独立的sHT危险因素。受试者工作特征(ROC)分析确定了连续因素的最佳截止值。在内部和外部开发并验证了nomogram。使用ROC曲线下面积(AUC)和校准图评估预测准确性。决策曲线分析(DCA)评价临床有效性。结果:803例AIS患者中,325例纳入最终分析。sHT发生率为9.5%(31例)。训练组(n = 228)和验证组(n = 97)没有统计学或临床差异。LASSO回归将中性粒细胞与白蛋白比率(NAR)和甘油三酯(tg)整合成一个新的指标- natg。独立的sHT危险因素包括基线美国国立卫生研究院卒中量表(NIHSS) (OR = 1.09, 95% CI (1.02, 1.16), p = 0.0095)、NATG (OR = 1534.87, 95% CI (5.02, 446638.44), p = 0.0120)、d -二聚体(DD) (OR = 1.12, 95% CI (1.01, 1.25), p = 0.0249)和总胆固醇(TC) (OR = 1.01, 95% CI (1.00, 1.01), p = 0.0280),其最佳临界值分别为13、0.059、0.86和3.6。利用这些因素在训练队列中建立nomogram,训练队列的AUC为0.804 (95% CI, 0.643-0.918),验证队列的AUC为0.713 (95% CI, 0.499-0.868),证明了校准的一致性。DCA证实了nomogram在两个队列中的临床适用性。结论:一种结合NAR和TG的新指标与AIS患者的sHT呈正相关。构建的nomogram (nomogram),将这一新的指标与其他危险因素相结合,为识别sHT风险提供了一个有价值的工具,有助于临床决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Integrating Neutrophil-To-Albumin Ratio and Triglycerides: A Novel Indicator for Predicting Spontaneous Hemorrhagic Transformation in Acute Ischemic Stroke Patients

Integrating Neutrophil-To-Albumin Ratio and Triglycerides: A Novel Indicator for Predicting Spontaneous Hemorrhagic Transformation in Acute Ischemic Stroke Patients

Background

Hemorrhagic transformation (HT) is a tragic complication of acute ischemic stroke (AIS), with spontaneous HT (sHT) occurring even without reperfusion therapies. Despite evidence suggesting that several inflammation biomarkers are closely related to HT, its utility in sHT risk stratification remains unclear. This study aimed to identify and integrate effective inflammatory biomarkers associated with sHT and to develop a novel nomogram model for the early detection of sHT.

Methods

We conducted a retrospective observational cohort study of AIS patients receiving conventional medical treatment solely from March 2022 to March 2023, using a prospectively maintained database. All patients underwent CT follow-up within 7 days after admission, with sHT occurrence within this period as the outcome. Data on demographics, clinical information, laboratory results, and imaging were collected. The cohort was divided into training and validation sets (7:3). Least absolute shrinkage and selection operator (LASSO) regression selected inflammatory biomarkers for a novel index. Univariable and multivariable logistic regressions were conducted to identify independent sHT risk factors. Receiver operating characteristic (ROC) analysis determined optimal cut-off values for continuous factors. A nomogram was developed and validated internally and externally. Predictive accuracy was assessed using the area under the ROC curve (AUC) and calibration plots. Decision curve analysis (DCA) evaluated clinical usefulness.

Results

Of 803 AIS patients, 325 were included in the final analysis. sHT was found in 9.5% (31 patients). Training (n = 228) and validation (n = 97) cohorts showed no significant demographic or clinical differences. LASSO regression integrated neutrophil-to-albumin ratio (NAR) and triglycerides (TGs) into a novel index—NATG. Independent sHT risk factors included baseline National Institute of Health Stroke Scale (NIHSS) (OR = 1.09, 95% CI (1.02, 1.16), p = 0.0095), NATG (OR = 1534.87, 95% CI (5.02, 469638.44), p = 0.0120), D-dimer (DD) (OR = 1.12, 95% CI (1.01, 1.25), p = 0.0249), and total cholesterol (TC) (OR = 1.01, 95% CI (1.00, 1.01), p = 0.0280), with their respective optimal cut-off values being 13, 0.059, 0.86, and 3.6. These factors were used to develop the nomogram in the training cohort, which achieved an AUC of 0.804 (95% CI, 0.643–0.918) in the training cohort and 0.713 (95% CI, 0.499–0.868) in the validation cohort, demonstrating consistent calibration. DCA confirmed the nomogram's clinical applicability in both cohorts.

Conclusions

A novel indicator combining NAR and TG is positively associated with sHT in AIS patients. The constructed nomogram, integrating this novel indicator with other risk factors, provides a valuable tool for identifying sHT risk, aiding in clinical decision-making.

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来源期刊
CNS Neuroscience & Therapeutics
CNS Neuroscience & Therapeutics 医学-神经科学
CiteScore
7.30
自引率
12.70%
发文量
240
审稿时长
2 months
期刊介绍: CNS Neuroscience & Therapeutics provides a medium for rapid publication of original clinical, experimental, and translational research papers, timely reviews and reports of novel findings of therapeutic relevance to the central nervous system, as well as papers related to clinical pharmacology, drug development and novel methodologies for drug evaluation. The journal focuses on neurological and psychiatric diseases such as stroke, Parkinson’s disease, Alzheimer’s disease, depression, schizophrenia, epilepsy, and drug abuse.
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