Risk factors for short-term mortality in elderly hip fracture patients with complicated heart failure in the ICU: A MIMIC-IV database analysis using nomogram

被引:3
|
作者
Lu, Yining [1 ,2 ]
Chen, Wei [1 ,2 ]
Guo, Yuhui [1 ,3 ]
Wang, Yujing [1 ,3 ]
Wang, Ling [1 ,3 ]
Zhang, Yingze [1 ,2 ]
机构
[1] Hebei Med Univ, Hosp 3, Dept Orthoped Res Ctr, Shijiazhuang, Hebei, Peoples R China
[2] Hebei Med Univ, Hosp 3, Dept Orthoped Surg, Shijiazhuang, Hebei, Peoples R China
[3] Hebei Med Univ, Hosp 3, Dept Orthoped Oncol, Shijiazhuang, Hebei, Peoples R China
关键词
30-day all-cause mortality; Geriatric hip fractures; Heart failure; Nomogram; Infection; Neutrophils; IRON-DEFICIENCY; ANEMIA; DYSFUNCTION; PREDICTORS; CREATININE; PNEUMONIA; DIAGNOSIS; PROGNOSIS; OUTCOMES; SURGERY;
D O I
10.1186/s13018-023-04258-7
中图分类号
R826.8 [整形外科学]; R782.2 [口腔颌面部整形外科学]; R726.2 [小儿整形外科学]; R62 [整形外科学(修复外科学)];
学科分类号
摘要
BackgroundHip fracture is a prevalent and hazardous injury among the elderly population that often results in intensive care unit (ICU) admission due to various complications, despite advanced medical science. One common complication experienced in the ICU by elderly hip fracture patients is heart failure, which significantly impacts short-term survival rates. Currently, there is a deficit of adequate predictive models to forecast the short-term risk of death following heart failure for elderly hip fracture patients in the ICU. This study aims to identify independent risk factors for all-cause mortality within 30 days for elderly patients with hip fractures and heart failure while in the ICU in order to develop a predictive model.MethodA total of 641 elderly patients with hip fractures combined with heart failure were recruited from the Medical Information Mart for Intensive Care IV dataset and randomized to the training and validation sets. The primary outcome was all-cause mortality within 30 days. The least absolute shrinkage and selection operator regression was used to reduce data dimensionality and select features. Multivariate logistic regression was used to build predictive models. Consistency index (C-index), receiver operating characteristic curve, and decision curve analysis (DCA) were used to measure the predictive performance of the nomogram.ResultOur results showed that these variables including MCH, MCV, INR, monocyte percentage, neutrophils percentage, creatinine, and combined sepsis were independent factors for death within 30 days in elderly patients with hip fracture combined with heart failure in the ICU. The C-index was 0.869 (95% CI 0.823-0.916) and 0.824 (95% CI 0.749-0.900) for the training and validation sets, respectively. The results of the area under the curve and decision curve analysis (DCA) confirmed that the nomogram performed well in predicting elderly patients with hip fractures combined with heart failure in the ICU.ConclusionWe developed a new nomogram model for predicting 30-day all-cause mortality in elderly patients with hip fractures combined with heart failure in the ICU, which could be a valid and useful clinical tool for clinicians for targeted treatment and prognosis prediction.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Risk factors for short-term mortality in elderly hip fracture patients with complicated heart failure in the ICU: A MIMIC-IV database analysis using nomogram
    Yining Lu
    Wei Chen
    Yuhui Guo
    Yujing Wang
    Ling Wang
    Yingze Zhang
    [J]. Journal of Orthopaedic Surgery and Research, 18
  • [2] Nomogram establishment for short-term survival prediction in ICU patients with aplastic anemia based on the MIMIC-IV database
    Tu, Yan
    Zhang, Jingcheng
    Zhao, Mingzhe
    He, Fang
    [J]. HEMATOLOGY, 2024, 29 (01)
  • [3] Incidence and interaction factors of delirium as an independent risk of mortality in elderly patients in the intensive units: a retrospective analysis from MIMIC-IV database
    Hui Liu
    Qing Zhao
    Xiaoli Liu
    Xin Hu
    Li Wang
    Feihu Zhou
    [J]. Aging Clinical and Experimental Research, 2022, 34 : 2865 - 2872
  • [4] Incidence and interaction factors of delirium as an independent risk of mortality in elderly patients in the intensive units: a retrospective analysis from MIMIC-IV database
    Liu, Hui
    Zhao, Qing
    Liu, Xiaoli
    Hu, Xin
    Wang, Li
    Zhou, Feihu
    [J]. AGING CLINICAL AND EXPERIMENTAL RESEARCH, 2022, 34 (11) : 2865 - 2872
  • [5] Establishment of ICU Mortality Risk Prediction Models with Machine Learning Algorithm Using MIMIC-IV Database
    Pang, Ke
    Li, Liang
    Wen, Ouyang
    Liu, Xing
    Tang, Yongzhong
    [J]. DIAGNOSTICS, 2022, 12 (05)
  • [6] The association between frailty and the risk of mortality in critically ill congestive heart failure patients: findings from the MIMIC-IV database
    Shi, Wenhua
    Lin, Hong
    Zhang, Xinyu
    Xu, Wenjing
    Lan, Taohua
    Jiang, Wei
    Chen, Xiankun
    Lu, Weihui
    [J]. FRONTIERS IN ENDOCRINOLOGY, 2024, 15
  • [7] Association between glycemic variability and short-term mortality in patients with acute kidney injury: a retrospective cohort study of the MIMIC-IV database
    Guo, Yifan
    Qiu, Yue
    Xue, Taiqi
    Zhou, Yi
    Yan, Pu
    Liu, Shiyi
    Liu, Shiwei
    Zhao, Wenjing
    Zhang, Ning
    [J]. SCIENTIFIC REPORTS, 2024, 14 (01):
  • [8] Development of a nomogram to predict 30-day mortality of sepsis patients with gastrointestinal bleeding: An analysis of the MIMIC-IV database
    Sun, Bing
    Man, Yu-lin
    Zhou, Qi-yuan
    Wang, Jin-dong
    Chen, Yi-min
    Fu, Yu
    Chen, Zhao-hong
    [J]. HELIYON, 2024, 10 (04)
  • [9] Effect of heart failure on postoperative short and long-term mortality in elderly patients with hip fracture
    Cha, Yong-Han
    Ha, Yong-Chan
    Ryu, Hyun-Jun
    Lee, Young-Kyun
    Park, Sang Hyun
    Lee, Kwang Je
    Koo, Kyung-Hoi
    [J]. INJURY-INTERNATIONAL JOURNAL OF THE CARE OF THE INJURED, 2020, 51 (03): : 694 - 698
  • [10] Clinical nomogram prediction model to assess the risk of prolonged ICU length of stay in patients with diabetic ketoacidosis: a retrospective analysis based on the MIMIC-IV database
    Shi, Jincun
    Chen, Fujin
    Zheng, Kaihui
    Su, Tong
    Wang, Xiaobo
    Wu, Jianhua
    Ni, Bukao
    Pan, Yujie
    [J]. BMC ANESTHESIOLOGY, 2024, 24 (01)