The First Affiliated Hospital of Jinan University, Guangzhou, China.
Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Eur J Med Res. 2023 Nov 24;28(1):539. doi: 10.1186/s40001-023-01515-7.
The incidence of nonhip femoral fractures is gradually increasing, but few studies have explored the risk factors for in-hospital death in patients with nonhip femoral fractures in the ICU or developed mortality prediction models. Therefore, we chose to study this specific patient group, hoping to help clinicians improve the prognosis of patients.
This is a retrospective study based on the data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Least absolute shrinkage and selection operator (LASSO) regression was used to screen risk factors. The receiver operating characteristic (ROC) curve was drawn, and the areas under the curve (AUC), net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the discrimination of the model. The consistency between the actual probability and the predicted probability was assessed by the calibration curve and Hosmer-Lemeshow goodness of fit test (HL test). Decision curve analysis (DCA) was performed, and the nomogram was compared with the scoring system commonly used in clinical practice to evaluate the clinical net benefit.
The LASSO regression analysis showed that heart rate, temperature, red blood cell distribution width, blood urea nitrogen, Glasgow Coma Scale (GCS), Simplified Acute Physiology Score II (SAPSII), Charlson comorbidity index and cerebrovascular disease were independent risk factors for in-hospital death in patients with nonhip femoral fractures. The AUC, IDI and NRI of our model in the training set and validation set were better than those of the GCS and SAPSII scoring systems. The calibration curve and HL test results showed that our model prediction results were in good agreement with the actual results (P = 0.833 for the HL test of the training set and P = 0.767 for the HL test of the validation set). DCA showed that our model had a better clinical net benefit than the GCS and SAPSII scoring systems.
In this study, the independent risk factors for in-hospital death in patients with nonhip femoral fractures were determined, and a prediction model was constructed. The results of this study may help to improve the clinical prognosis of patients with nonhip femoral fractures.
非髋部股骨骨折的发病率逐渐增加，但很少有研究探讨 ICU 中非髋部股骨骨折患者院内死亡的危险因素，也没有开发出死亡率预测模型。因此，我们选择研究这一特定患者群体，希望能帮助临床医生改善患者的预后。
这是一项基于医疗信息汇总-IV（MIMIC-IV）数据库数据的回顾性研究。使用最小绝对收缩和选择算子（LASSO）回归筛选危险因素。绘制受试者工作特征（ROC）曲线，计算曲线下面积（AUC）、净重新分类指数（NRI）和综合判别改善（IDI），以评估模型的判别能力。通过校准曲线和 Hosmer-Lemeshow 拟合优度检验（HL 检验）评估实际概率与预测概率之间的一致性。进行决策曲线分析（DCA），并将列线图与临床实践中常用的评分系统进行比较，以评估临床净获益。
LASSO 回归分析显示，心率、体温、红细胞分布宽度、血尿素氮、格拉斯哥昏迷评分（GCS）、简化急性生理学评分 II（SAPSII）、Charlson 合并症指数和脑血管疾病是非髋部股骨骨折患者院内死亡的独立危险因素。我们的模型在训练集和验证集中的 AUC、IDI 和 NRI 均优于 GCS 和 SAPSII 评分系统。校准曲线和 HL 检验结果表明，我们的模型预测结果与实际结果吻合良好（训练集的 HL 检验 P=0.833，验证集的 HL 检验 P=0.767）。DCA 显示我们的模型比 GCS 和 SAPSII 评分系统具有更好的临床净获益。
本研究确定了非髋部股骨骨折患者院内死亡的独立危险因素，并构建了预测模型。本研究结果可能有助于改善非髋部股骨骨折患者的临床预后。
Zotero 插件
