PMID- 37891456
OWN - NLM
STAT- MEDLINE
DCOM- 20231030
LR  - 20231102
IS  - 1471-2318 (Electronic)
IS  - 1471-2318 (Linking)
VI  - 23
IP  - 1
DP  - 2023 Oct 27
TI  - Development and validation of a risk prediction model for osteoporosis in elderly 
      patients with type 2 diabetes mellitus: a retrospective and multicenter study.
PG  - 698
LID - 10.1186/s12877-023-04306-1 [doi]
LID - 698
AB  - BACKGROUND: This study aimed to construct a risk prediction model to estimate the 
      odds of osteoporosis (OP) in elderly patients with type 2 diabetes mellitus 
      (T2DM) and evaluate its prediction efficiency. METHODS: This study included 
      21,070 elderly patients with T2DM who were hospitalized at six tertiary hospitals 
      in Southwest China between 2012 and 2022. Univariate logistic regression analysis 
      was used to screen for potential influencing factors of OP and least absolute 
      shrinkage. Further, selection operator regression (LASSO) and multivariate 
      logistic regression analyses were performed to select variables for developing a 
      novel predictive model. The area under the receiver operating characteristic 
      curve (AUROC), calibration curve, decision curve analysis (DCA), and clinical 
      impact curve (CIC) were used to evaluate the performance and clinical utility of 
      the model. RESULTS: The incidence of OP in elderly patients with T2DM was 7.01% 
      (1,476/21,070). Age, sex, hypertension, coronary heart disease, cerebral 
      infarction, hyperlipidemia, and surgical history were the influencing factors. 
      The seven-variable model displayed an AUROC of 0.713 (95% confidence interval 
      [CI]:0.697-0.730) in the training set, 0.716 (95% CI: 0.691-0.740) in the 
      internal validation set, and 0.694 (95% CI: 0.653-0.735) in the external 
      validation set. The optimal decision probability cut-off value was 0.075. The 
      calibration curve (bootstrap = 1,000) showed good calibration. In addition, the 
      DCA and CIC demonstrated good clinical practicality. An operating interface on a 
      webpage ( https://juntaotan.shinyapps.io/osteoporosis/ ) was developed to provide 
      convenient access for users. CONCLUSIONS: This study constructed a highly 
      accurate model to predict OP in elderly patients with T2DM. This model 
      incorporates demographic characteristics and clinical risk factors and may be 
      easily used to facilitate individualized prediction.
CI  - (c) 2023. The Author(s).
FAU - Tan, Juntao
AU  - Tan J
AD  - Operation Management Office, Affiliated Banan Hospital of Chongqing Medical 
      University, Chongqing, 401320, China.
FAU - Zhang, Zhengyu
AU  - Zhang Z
AD  - Medical Records Department, the First Affiliated Hospital, College of Medicine, 
      Zhejiang University, Hangzhou, 310003, China.
FAU - He, Yuxin
AU  - He Y
AD  - Department of Medical Administration, Affiliated Banan Hospital of Chongqing 
      Medical University, Chongqing, 401320, China.
FAU - Xu, Xiaomei
AU  - Xu X
AD  - Department of Infectious Diseases, Chengdu Fifth People's hospital, Chengdu, 
      611130, China.
FAU - Yang, Yanzhi
AU  - Yang Y
AD  - Department of Endocrinology and Metabolism, Chengdu First People's Hospital, 
      Chengdu, 610041, China.
FAU - Xu, Qian
AU  - Xu Q
AD  - College of Medical Informatics, Chongqing Medical University, Chongqing, 400016, 
      China.
AD  - Medical Data Science Academy, Chongqing Medical University, Chongqing, 400016, 
      China.
AD  - Library, Chongqing Medical University, Chongqing, 400016, China.
FAU - Yuan, Yuan
AU  - Yuan Y
AD  - Medical Records Department, Women and Children's Hospital of Chongqing Medical 
      University, Chongqing, 401147, China.
FAU - Wu, Xin
AU  - Wu X
AD  - Department of Gastrointestinal surgery, Third Affiliated Hospital of Chongqing 
      Medical University, Chongqing, 401120, China.
FAU - Niu, Jianhua
AU  - Niu J
AD  - Department of Critical Care, the First Affiliated Hospital, Zhejiang University 
      School of Medicine, 79 Qing Chun Road, Hangzhou, 310003, Zhejiang, China.
FAU - Tang, Songjia
AU  - Tang S
AD  - Plastic and Aesthetic Surgery Department, Affiliated Hangzhou First People's 
      Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, Zhejiang, 
      China. tangsj@zju.edu.cn.
FAU - Wu, Xiaoxin
AU  - Wu X
AD  - State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National 
      Clinical Research Centre for Infectious Diseases, the First Affiliated Hospital, 
      Zhejiang University School of Medicine, 79 Qing Chun Road, Hangzhou, 310003, 
      Zhejiang, China. xiaoxinwu@zju.edu.cn.
FAU - Hu, Yongjun
AU  - Hu Y
AD  - Department of Orthopedics, Affiliated Banan Hospital of Chongqing Medical 
      University, Chongqing, 401320, China. lionhu@sina.com.
LA  - eng
PT  - Journal Article
PT  - Multicenter Study
PT  - Research Support, Non-U.S. Gov't
DEP - 20231027
PL  - England
TA  - BMC Geriatr
JT  - BMC geriatrics
JID - 100968548
SB  - IM
MH  - Aged
MH  - Humans
MH  - *Diabetes Mellitus, Type 2/complications/diagnosis/epidemiology
MH  - Retrospective Studies
MH  - *Osteoporosis/diagnosis/epidemiology
MH  - Risk Factors
MH  - Cerebral Infarction
PMC - PMC10604807
OTO - NOTNLM
OT  - Elderly patients
OT  - Osteoporosis
OT  - Prediction model
OT  - Type 2 diabetes mellitus
COIS- The authors declare no competing interests. The authors of this article declared 
      that there was no conflict of interest related to this manuscript.
EDAT- 2023/10/28 11:42
MHDA- 2023/10/30 06:46
PMCR- 2023/10/27
CRDT- 2023/10/27 23:40
PHST- 2023/05/20 00:00 [received]
PHST- 2023/09/11 00:00 [accepted]
PHST- 2023/10/30 06:46 [medline]
PHST- 2023/10/28 11:42 [pubmed]
PHST- 2023/10/27 23:40 [entrez]
PHST- 2023/10/27 00:00 [pmc-release]
AID - 10.1186/s12877-023-04306-1 [pii]
AID - 4306 [pii]
AID - 10.1186/s12877-023-04306-1 [doi]
PST - epublish
SO  - BMC Geriatr. 2023 Oct 27;23(1):698. doi: 10.1186/s12877-023-04306-1.