PMID- 36600212
OWN - NLM
STAT- MEDLINE
DCOM- 20230106
LR  - 20230203
IS  - 1471-2253 (Electronic)
IS  - 1471-2253 (Linking)
VI  - 23
IP  - 1
DP  - 2023 Jan 4
TI  - A nomogram for predicting the mortality of patients with type 2 diabetes mellitus 
      complicated with acute kidney injury in the intensive care unit.
PG  - 4
LID - 10.1186/s12871-022-01961-6 [doi]
LID - 4
AB  - BACKGROUND: There is no predictive tool for type 2 diabetes mellitus (T2DM) 
      patients with acute kidney injury (AKI). Our study aimed to establish an 
      effective nomogram model for predicting mortality in T2DM patients with AKI. 
      METHOD: Data on T2DM patients with AKI were obtained from the Medical Information 
      Mart for Intensive Care III. 70% and 30% of the patients were randomly selected 
      as the training and validation cohorts, respectively. Univariate and multivariate 
      logistic regression analyses were used to identify factors associated with death 
      in T2DM patients with AKI. Factors significantly associated with survival 
      outcomes were used to construct a nomogram predicting 90-day mortality. The 
      nomogram effect was evaluated by receiver operating characteristic curve 
      analysis, Hosmer‒Lemeshow test, calibration curve, and decision curve analysis 
      (DCA). RESULTS: There were 4375 patients in the training cohort and 1879 in the 
      validation cohort. Multivariate logistic regression analysis showed that age, 
      BMI, chronic heart failure, coronary artery disease, malignancy, stages of AKI, 
      white blood cell count, blood urea nitrogen, arterial partial pressure of oxygen 
      and partial thromboplastin time were independent predictors of patient survival. 
      The results showed that the nomogram had a higher area under the curve value than 
      the sequential organ failure assessment score and simplified acute physiology 
      score II. The Hosmer‒Lemeshow test and calibration curve suggested that the 
      nomogram had a good calibration effect. The DCA curve showed that the nomogram 
      model had good clinical application value. CONCLUSION: The nomogram model 
      accurately predicted 90-day mortality in T2DM patients with AKI. It may provide 
      assistance for clinical decision-making and treatment, thereby reducing the 
      medical burden.
CI  - (c) 2023. The Author(s).
FAU - Liu, Shizhen
AU  - Liu S
AD  - Department of Nephrology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital 
      of Sun Yat-Sen University, Jiangmen, Guangdong, China. 1107309479@qq.com.
FAU - Qiu, Chuangye
AU  - Qiu C
AD  - Department of Nephrology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital 
      of Sun Yat-Sen University, Jiangmen, Guangdong, China.
FAU - Li, Xingai
AU  - Li X
AD  - Department of Nephrology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital 
      of Sun Yat-Sen University, Jiangmen, Guangdong, China.
FAU - Yu, Zongchao
AU  - Yu Z
AD  - Department of Nephrology, The First Affiliated Hospital of Jinan University, 
      Guangzhou, Guangdong, 510630, China.
FAU - Liu, Fanna
AU  - Liu F
AD  - Department of Nephrology, The First Affiliated Hospital of Jinan University, 
      Guangzhou, Guangdong, 510630, China.
FAU - Hu, Guoqiang
AU  - Hu G
AD  - Department of Nephrology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital 
      of Sun Yat-Sen University, Jiangmen, Guangdong, China. tonyhu1001@163.com.
LA  - eng
PT  - Journal Article
DEP - 20230104
PL  - England
TA  - BMC Anesthesiol
JT  - BMC anesthesiology
JID - 100968535
SB  - IM
MH  - Humans
MH  - *Diabetes Mellitus, Type 2/complications
MH  - Nomograms
MH  - Intensive Care Units
MH  - *Acute Kidney Injury
MH  - Critical Care
MH  - Retrospective Studies
PMC - PMC9811712
OTO - NOTNLM
OT  - Acute kidney injury
OT  - Intensive care unit
OT  - Mortality
OT  - Nomogram
OT  - Type 2 diabetes mellitus
COIS- The authors declare no conflicts of interest.
EDAT- 2023/01/05 06:00
MHDA- 2023/01/07 06:00
PMCR- 2023/01/04
CRDT- 2023/01/04 23:33
PHST- 2022/10/05 00:00 [received]
PHST- 2022/12/28 00:00 [accepted]
PHST- 2023/01/04 23:33 [entrez]
PHST- 2023/01/05 06:00 [pubmed]
PHST- 2023/01/07 06:00 [medline]
PHST- 2023/01/04 00:00 [pmc-release]
AID - 10.1186/s12871-022-01961-6 [pii]
AID - 1961 [pii]
AID - 10.1186/s12871-022-01961-6 [doi]
PST - epublish
SO  - BMC Anesthesiol. 2023 Jan 4;23(1):4. doi: 10.1186/s12871-022-01961-6.