用于预测延髓外侧梗死中枢性神经源性呼吸衰竭的LARyNGTH评分开发
Development of the LARyNGTH score to predict central neurogenic respiratory failure in lateral medullary infarction.
文献信息
| PMID | 42903130 |
|---|---|
| 原文 | 在 PubMed 查看原文 ↗ |
| 发表日期 | 2026 |
| 作者 | Yoon Sub Kim |
| 作者单位 | Department of Neurology, Ajou University School of Medicine, Suwon, Republic of Korea. |
| 期刊 | Frontiers in neurology |
| SCI 分区 | Q2 |
| IF | 3.5 |
| 研究类型 | 临床研究 · 临床 |
| 所属专科 | 咽喉科 |
中文摘要
背景： 中枢性神经源性呼吸衰竭（CNRF）是延髓外侧梗死（LMI）相关的致命并发症。其识别可能对及时干预和降低死亡风险至关重要。本研究旨在确定LMI患者CNRF的临床预测因素。
方法： 本研究纳入2010年至2022年间在一所大学医院收治的LMI患者。CNRF定义为因高碳酸血症导致的非预期插管、因呼吸原因导致的心肺复苏，或临床检测到CNRF。同时收集临床、神经学和影像学数据。进行单变量和多变量分析以确定呼吸并发症的临床预测因素。
结果： 在214例患者中，12例（5.6%）发生CNRF。CNRF组中高血压（91.7% vs. 55.9%，p = 0.033）和糖尿病（58.3% vs. 26.2%，p = 0.04）更为常见。CNRF患者表现出更高的美国国立卫生研究院卒中量表（NIHSS）评分（6.0 [4.25-7.0] vs. 2.0 [1.0-4.0]，p < 0.001）和更低的改良Gugging吞咽筛查（GUSS）测试评分（9.0 [3.5-13.75] vs. 15 [13-15]，p = 0.014）。影像学显示大范围吻侧梗死（83.3% vs. 9.4%，p < 0.001）和合并髓外病变（50.0% vs. 13.4%，p < 0.001）的比例更高。多变量分析确定了LARyNGTH评分，该评分包括上述变量。评分 >5.5 预测CNRF的AUROC为0.968（95% CI：0.940-0.996），敏感性为91.7%，特异性为94.6%，准确性为94.4%。
结论： 在LMI患者中，联合预测模型可以预测CNRF并促进抢先干预。
英文摘要
BACKGROUND: Central neurogenic respiratory failure (CNRF) is a fatal complication associated with lateral medullary infarcts (LMI). Its detection may be critical for timely intervention and to reduce the risk of mortality. This study aimed to identify the clinical predictors of CNRF in patients with LMI.
METHODS: This study included patients with LMI who were admitted to a university hospital between 2010 and 2022. CNRF was defined as unexpected intubations due to hypercapnia, cardiopulmonary resuscitation owing to respiratory causes, or clinical detection of CNRF. Clinical, neurological, and imaging data were also collected. Univariable and multivariable analyses were performed to identify the clinical predictors of respiratory complications.
RESULTS: Among the 214 patients, 12 (5.6%) developed CNRF. Hypertension (91.7% vs. 55.9%, p = 0.033) and diabetes mellitus (58.3% vs. 26.2%, p = 0.04) were more common in the CNRF group. Patients with CNRF exhibited higher National Institutes of Health Stroke Scale (NIHSS) scores (6.0 [4.25-7.0] vs. 2.0 [1.0-4.0], p < 0.001) and lower modified Gugging Swallowing Screen (GUSS) test scores (9.0 [3.5-13.75] vs. 15 [13-15], p = 0.014). Imaging showed a higher rate of large rostral infarcts (83.3% vs. 9.4%, p < 0.001) and combined extramedullary lesions (50.0% vs. 13.4%, p < 0.001). Multivariable analysis identified the LARyNGTH score, which included the above variables. A score >5.5 predicted CNRF with an AUROC of 0.968 (95% CI: 0.940-0.996), a sensitivity of 91.7%, a specificity of 94.6%, and an accuracy of 94.4%.
CONCLUSION: In patients with LMI, a combined predictive model can predict CNRF and facilitate preemptive intervention.