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
  • [31] Develop ment and validation of a prognostic dynamic nomogram for in-hospital mortality in patients with Stanford type B aortic dissection
    Yang, Lin
    Wang, Yasong
    He, Xiaofeng
    Liu, Xuanze
    Sui, Honggang
    Wang, Xiaozeng
    Wang, Mengmeng
    FRONTIERS IN CARDIOVASCULAR MEDICINE, 2023, 9
  • [32] Development and validation of an interpretable machine learning model for predicting in-hospital mortality for ischemic stroke patients in ICU
    Luo, Xiao
    Li, Binghan
    Zhu, Ronghui
    Tai, Yaoyong
    Wang, Zongyu
    He, Qian
    Zhao, Yanfang
    Bi, Xiaoying
    Wu, Cheng
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2025, 198
  • [33] Nomogram for predicting in-hospital mortality of nonagenarians with community-acquired pneumonia
    Zan, Yumin
    Song, Weiwei
    Wang, Yu
    Shao, Jiaofang
    Wang, Zhiyong
    Zhao, Weihong
    Wu, Jianqing
    Xu, Wei
    GERIATRICS & GERONTOLOGY INTERNATIONAL, 2022, 22 (08) : 635 - 641
  • [34] Risk factor analysis and nomogram for predicting in-hospital mortality in ICU patients with sepsis and lung infection
    Ren, Yinlong
    Zhang, Luming
    Xu, Fengshuo
    Han, Didi
    Zheng, Shuai
    Zhang, Feng
    Li, Longzhu
    Wang, Zichen
    Lyu, Jun
    Yin, Haiyan
    BMC PULMONARY MEDICINE, 2022, 22 (01)
  • [35] Development and validation of a prognostic nomogram for predicting in-hospital mortality of COVID-19: a multicenter retrospective cohort study of 4086 cases in China
    Li, Li
    Fang, Xiaoyu
    Cheng, Lixia
    Wang, Penghao
    Li, Shen
    Yu, Hao
    Zhang, Yao
    Jiang, Nan
    Zeng, Tingting
    Hou, Chao
    Zhou, Jing
    Li, Shiru
    Pan, Yingzi
    Li, Yitong
    Nie, Lili
    Li, Yang
    Sun, Qidi
    Jia, Hong
    Li, Mengxia
    Cao, Guoqiang
    Ma, Xiangyu
    AGING-US, 2021, 13 (03): : 3176 - 3189
  • [36] Risk factor analysis and nomogram for predicting in-hospital mortality in ICU patients with sepsis and lung infection
    Yinlong Ren
    Luming Zhang
    Fengshuo Xu
    Didi Han
    Shuai Zheng
    Feng Zhang
    Longzhu Li
    Zichen Wang
    Jun Lyu
    Haiyan Yin
    BMC Pulmonary Medicine, 22
  • [37] DEVELOPMENT AND VALIDATION OF A NOMOGRAM FOR PREDICTING 28-DAY IN-HOSPITAL MORTALITY IN SEPSIS PATIENTS BASED ON AN OPTIMIZED ACUTE PHYSIOLOGY AND CHRONIC HEALTH EVALUATION II SCORE
    Yuan, Yamin
    Meng, Yanfei
    Li, Yihui
    Zhou, Jinquan
    Wang, Jiaqi
    Jiang, Yujing
    Ma, Li
    SHOCK, 2024, 61 (05): : 718 - 727
  • [38] Establishment of a mortality risk nomogram for predicting in-hospital mortality of sepsis: cohort study from a Chinese single center
    Wu, Hongsheng
    Jia, Shichao
    Liao, Biling
    Ji, Tengfei
    Huang, Jianbin
    Luo, Yumei
    Cao, Tiansheng
    Ma, Keqiang
    FRONTIERS IN MEDICINE, 2024, 11
  • [39] Development and validation of a nomogram for predicting the prognosis in cancer patients with sepsis
    Yang, Yong
    Dong, Jun
    Li, Yang
    Chen, Renxiong
    Tian, Xiuyun
    Wang, Hongzhi
    Hao, Chunyi
    CANCER MEDICINE, 2022, 11 (12): : 2345 - 2355
  • [40] Development and external validation of a nomogram for predicting renal function based on preoperative data from in-hospital patients with simple renal cysts
    Chen, Yiding
    Chen, Lei
    Meng, Jialin
    Zhang, Meng
    Xu, Yuchen
    Fan, Song
    Liang, Chaozhao
    Liao, Guiyi
    JOURNAL OF INTERNATIONAL MEDICAL RESEARCH, 2022, 50 (03)