Department of Emergency Medicine, The First People's Hospital of Kunshan, Kunshan, China.
Department of Endocrinology, The First People's Hospital of Kunshan, Kunshan, China.
Front Public Health. 2024 Aug 2;12:1373585. doi: 10.3389/fpubh.2024.1373585. eCollection 2024.
The inflammatory response holds paramount significance in the context of intracerebral hemorrhage (ICH) and exhibits a robust correlation with mortality rates. Biological markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune inflammation index (SII), and systemic inflammatory response index (SIRI) play crucial roles in influencing the systemic inflammatory response following ICH. This study aims to compare the predictive efficacy of NLR, PLR, LMR, SII, and SIRI concerning the risk of mortality in the intensive care unit (ICU) among critically ill patients with ICH. Such a comparison seeks to elucidate their early warning capabilities in the management and treatment of ICH.
Patients with severe ICH requiring admission to the ICU were screened from the Medical Information Marketplace for Intensive Care (MIMIC-IV) database. The outcomes studied included ICU mortality and 30 day ICU hospitalization rates, based on tertiles of the NLR index level. To explore the relationship between the NLR index and clinical outcomes in critically ill patients with ICH, we utilized receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and multivariate logistic regression analysis.
A total of 869 patients (51.9% male) were included in the study, with an ICU mortality rate of 22.9% and a 30 day ICU hospitalization rate of 98.4%. Among the five indicators examined, both the ROC curve and DCA indicated that NLR (AUC: 0.660, 95%CI: 0.617-0.703) had the highest predictive ability for ICU mortality. Moreover, this association remained significant even after adjusting for other confounding factors during multivariate analysis (HR: 3.520, 95%CI: 2.039-6.077). Based on the results of the multivariate analysis, incorporating age, albumin, lactic acid, NLR, and GCS score as variables, we developed a nomogram to predict ICU mortality in critically ill patients with ICH.
NLR emerges as the most effective predictor of ICU mortality risk among critically ill patients grappling with ICH when compared to the other four indicators. Furthermore, the integration of albumin and lactic acid indicators into the NLR nomogram enhances the ability to promptly identify ICU mortality in individuals facing severe ICH.
炎症反应在脑出血（ICH）中具有至关重要的意义，与死亡率密切相关。中性粒细胞与淋巴细胞比值（NLR）、血小板与淋巴细胞比值（PLR）、淋巴细胞与单核细胞比值（LMR）、全身免疫炎症指数（SII）和全身炎症反应指数（SIRI）等生物标志物在影响 ICH 后全身炎症反应方面发挥着重要作用。本研究旨在比较 NLR、PLR、LMR、SII 和 SIRI 对重症 ICH 患者 ICU 死亡率的预测效能，以明确其在 ICH 管理和治疗中的预警作用。
从 MIMIC-IV 数据库中筛选出需要入住 ICU 的重症 ICH 患者。研究终点包括 ICU 死亡率和 30 天 ICU 住院率，以 NLR 指数水平的三分位数为依据。为了探讨 NLR 指数与重症 ICH 患者临床结局的关系，我们采用 ROC 分析、决策曲线分析（DCA）和多因素 logistic 回归分析。
共纳入 869 例患者（51.9%为男性），ICU 死亡率为 22.9%，30 天 ICU 住院率为 98.4%。在这 5 个指标中，ROC 曲线和 DCA 均表明 NLR（AUC：0.660，95%CI：0.617-0.703）对 ICU 死亡率的预测能力最高。此外，多因素分析调整其他混杂因素后，该相关性仍然显著（HR：3.520，95%CI：2.039-6.077）。基于多因素分析结果，我们将年龄、白蛋白、乳酸、NLR 和 GCS 评分作为变量，构建了预测重症 ICH 患者 ICU 死亡率的列线图。
与其他 4 个指标相比，NLR 是重症 ICH 患者 ICU 死亡率风险的最有效预测指标。此外，将白蛋白和乳酸指标纳入 NLR 列线图可增强对严重 ICH 患者 ICU 死亡率的快速识别能力。
