Department of Orthopedics, Foshan Fosun Chancheng Hospital, Foshan, 528010, China.
Department of Orthopedics, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China.
Neurol Sci. 2024 May;45(5):2149-2163. doi: 10.1007/s10072-023-07199-5. Epub 2023 Nov 23.
Subarachnoid hemorrhage (SAH) is associated with high rates of mortality and permanent disability. At present, there are few definite clinical tools to predict prognosis in SAH patients. The current study aims to develop and assess a predictive nomogram model for estimating the 28-day mortality risk in both non-traumatic or post-traumatic SAH patients.
The MIMIC-III database was searched to select patients with SAH based on ICD-9 codes. Patients were separated into non-traumatic and post-traumatic SAH groups. Using LASSO regression analysis, we identified independent risk factors associated with 28-day mortality and incorporated them into nomogram models. The performance of each nomogram was assessed by calculating various metrics, including the area under the curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).
The study included 999 patients with SAH, with 631 in the non-traumatic group and 368 in the post-traumatic group. Logistic regression analysis revealed critical independent risk factors for 28-day mortality in non-traumatic SAH patients, including gender, age, glucose, platelet, sodium, BUN, WBC, PTT, urine output, SpO, and heart rate and age, glucose, PTT, urine output, and body temperature for post-traumatic SAH patients. The prognostic nomograms outperformed the commonly used SAPSII and APSIII systems, as evidenced by superior AUC, NRI, IDI, and DCA results.
The study identified independent risk factors associated with the 28-day mortality risk and developed predictive nomogram models for both non-traumatic and post-traumatic SAH patients. The nomogram holds promise in guiding prognosis improvement strategies for patients with SAH.
蛛网膜下腔出血（SAH）与高死亡率和永久性残疾有关。目前，很少有确定的临床工具可以预测 SAH 患者的预后。本研究旨在开发和评估一种预测nomogram 模型，以估计非创伤性或创伤性 SAH 患者的 28 天死亡率风险。
从 MIMIC-III 数据库中搜索基于 ICD-9 编码的 SAH 患者。将患者分为非创伤性和创伤性 SAH 组。使用 LASSO 回归分析，我们确定了与 28 天死亡率相关的独立危险因素，并将其纳入 nomogram 模型。通过计算各种指标，包括曲线下面积（AUC）、净重新分类改善（NRI）、综合判别改善（IDI）和决策曲线分析（DCA），评估每个 nomogram 的性能。
该研究纳入了 999 例 SAH 患者，其中 631 例为非创伤性，368 例为创伤性。Logistic 回归分析显示，非创伤性 SAH 患者 28 天死亡率的关键独立危险因素包括性别、年龄、血糖、血小板、钠、BUN、白细胞、PTT、尿量、SpO2 和心率以及年龄、血糖、PTT、尿量和体温对于创伤性 SAH 患者。预后 nomogram 优于常用的 SAPSII 和 APSIII 系统，表现在 AUC、NRI、IDI 和 DCA 结果更好。
本研究确定了与 28 天死亡率风险相关的独立危险因素，并为非创伤性和创伤性 SAH 患者开发了预测 nomogram 模型。该 nomogram 有望指导 SAH 患者的预后改善策略。
