Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures

被引:0
|
作者
Xing, Zhibin [1 ]
Xu, Yiwen [1 ]
Wu, Yuxuan [1 ]
Fu, Xiaochen [1 ]
Shen, Pengfei [1 ]
Che, Wenqiang [2 ,3 ]
Wang, Jing [1 ]
机构
[1] Jinan Univ, Affiliated Hosp 1, Guangzhou, Peoples R China
[2] Jinan Univ, Dept Clin Res, Affiliated Hosp 1, Guangzhou, Peoples R China
[3] Jinan Univ, Dept Neurosurg, Affiliated Hosp 1, Guangzhou, Peoples R China
关键词
Nonhip femoral fracture; Intensive care unit; In-hospital mortality; Nomogram; CELL DISTRIBUTION WIDTH; DISTAL FEMUR FRACTURES; TRAUMA PATIENTS; HEART-RATE; HYPOTHERMIA; INJURY; CARE;
D O I
10.1186/s40001-023-01515-7
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
BackgroundThe 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.MethodsThis 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.ResultsThe 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.ConclusionIn 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.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] In-hospital Mortality Risk for Femoral Neck Fractures Among Patients Receiving Medicare
    Erickson, Brandon J.
    Nwachukwu, Benedict U.
    Kiriakopoulos, Emmanouil
    Frank, Rachel M.
    Levine, Brett
    Villarroel, Leonardo
    McCormick, Frank M.
    ORTHOPEDICS, 2015, 38 (07) : E593 - E596
  • [22] A nomogram for predicting the in-hospital mortality after large hemispheric infarction
    Sun, Wenzhe
    Li, Guo
    Liu, Ziqiang
    Miao, Jinfeng
    Yang, Zhaoxia
    Zhou, Qiao
    Liu, Run
    Zhu, Suiqiang
    Zhu, Zhou
    BMC NEUROLOGY, 2019, 19 (01)
  • [23] A nomogram for predicting the in-hospital mortality after large hemispheric infarction
    Wenzhe Sun
    Guo Li
    Ziqiang Liu
    Jinfeng Miao
    Zhaoxia Yang
    Qiao Zhou
    Run Liu
    Suiqiang Zhu
    Zhou Zhu
    BMC Neurology, 19
  • [24] Development and Validation of a Simple-to-Use Nomogram for Predicting In-Hospital Mortality in Patients With Acute Heart Failure Undergoing Continuous Renal Replacement Therapy
    Gao, Luyao
    Bian, Yuan
    Cao, Shengchuan
    Sang, Wentao
    Zhang, Qun
    Yuan, Qiuhuan
    Xu, Feng
    Chen, Yuguo
    FRONTIERS IN MEDICINE, 2021, 8
  • [25] Predicting in-hospital mortality for MIMIC-III patients: A nomogram combined with SOFA score
    Liu, Ran
    Liu, Haiwang
    Li, Ling
    Wang, Zhixue
    Li, Yan
    MEDICINE, 2022, 101 (42) : E31251
  • [26] Development and validation of a predicting nomogram for in-hospital mortality of COVID-19 Omicron variant: A cohort study of 1324 cases in Beijing Anzhen Hospital
    Shi, Yuchen
    Ma, Ying
    Zheng, Ze
    Qin, Yanwen
    Du, Zhiyong
    Liu, Jinghua
    HELIYON, 2024, 10 (07)
  • [27] Development and validation of a prediction model for in-hospital mortality in patients with sepsis
    Shi, Wen
    Xie, Mengqi
    Mao, Enqiang
    Yang, Zhitao
    Zhang, Qi
    Chen, Erzhen
    Chen, Ying
    NURSING IN CRITICAL CARE, 2025, 30 (03)
  • [28] DEVELOPMENT OF A NOMOGRAM TO PREDICT IN-HOSPITAL MORTALITY OF PATIENTS ADMITTED DUE TO EXACERBATION OF COPD
    Sakamoto, Y.
    Yamauchi, Y.
    Yasunaga, H.
    Takeshima, H.
    Hasegawa, W.
    Jo, T.
    Sasabuchi, Y.
    Matsui, H.
    Fushimi, K.
    Nagase, T.
    RESPIROLOGY, 2016, 21 : 177 - 177
  • [29] Development and Validation of a Nomogram Model for Predicting in-Hospital Mortality in non-Diabetic Patients with non-ST-Segment Elevation Acute Myocardial Infarction
    Li, Panpan
    Yao, Wensen
    Wu, Jingjing
    Gao, Yating
    Zhang, Xueyuan
    Hu, Wei
    CLINICAL AND APPLIED THROMBOSIS-HEMOSTASIS, 2024, 30
  • [30] Validation of the NaURSE rule for predicting in-hospital mortality in nonagenarians
    Perez, N.
    Urreta, I.
    Elola, M.
    Aranegui, P.
    REVISTA CLINICA ESPANOLA, 2018, 218 (02): : 110 - 111