PMID- 34234604
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20220424
IS  - 1179-1608 (Print)
IS  - 1179-1608 (Electronic)
IS  - 1179-1608 (Linking)
VI  - 13
DP  - 2021
TI  - Development and Validation of a Nomogram for Predicting Obstructive Sleep Apnea 
      in Bariatric Surgery Candidates.
PG  - 1013-1023
LID - 10.2147/NSS.S316674 [doi]
AB  - BACKGROUND: Obstructive sleep apnea (OSA) is highly prevalent in bariatric 
      surgery patients and can lead to potential perioperative risks, but some 
      screening tools lack adequate performance in this population. Thus, we aimed to 
      develop and validate a clinical nomogram for predicting OSA in bariatric surgery 
      candidates. METHODS: We retrospectively collected the data of 482 bariatric 
      surgery patients between September 2015 and January 2020. Patients were randomly 
      classified into training cohort (n=338) and validation cohort (n=144). The Lasso 
      regression was used to select potentially relevant features; then, multivariable 
      logistic regression analysis was used to establish the nomogram. Discrimination, 
      calibration and clinical usefulness of the nomogram were assessed using the 
      C-index, calibration curve and decision curve analysis (DCA). RESULTS: The 
      overall prevalence of OSA was 71.0% and higher in males (88.2%) compared to 
      females (60.1%). Of these, 26.1% had mild OSA, 14.9% had moderate OSA, and 44.8% 
      had severe OSA. The nomogram consisted of gender, habitual snoring, type 2 
      diabetes mellitus (T2DM), neck circumference, body mass index (BMI) and age. The 
      nomogram provided favorable discrimination, with a C-indexes for the training and 
      validation cohort of 0.856 (95% CI: 0.816-0.897) and 0.829 (95% CI: 0.76-0.895), 
      respectively, and good calibration. The DCA displayed that the nomogram was 
      clinically useful. CONCLUSION: We established a concise and practical nomogram 
      that could facilitate the preoperative individualized prediction of OSA before 
      bariatric surgery, which may help clinicians select bariatric surgery patients 
      with high-risk OSA for polysomnography (PSG).
CI  - (c) 2021 Chen et al.
FAU - Chen, Wenhui
AU  - Chen W
AD  - Department of Metabolic and Bariatric Surgery, The First Affiliated Hospital of 
      Jinan University, Guangzhou, People's Republic of China.
FAU - Feng, Jia
AU  - Feng J
AD  - Department of Cellular Biology, Institute of Biomedicine, Jinan University, 
      Guangzhou, People's Republic of China.
FAU - Wang, Yucheng
AU  - Wang Y
AD  - Department of Metabolic and Bariatric Surgery, The First Affiliated Hospital of 
      Jinan University, Guangzhou, People's Republic of China.
FAU - Wang, Cunchuan
AU  - Wang C
AD  - Department of Metabolic and Bariatric Surgery, The First Affiliated Hospital of 
      Jinan University, Guangzhou, People's Republic of China.
FAU - Dong, Zhiyong
AU  - Dong Z
AD  - Department of Metabolic and Bariatric Surgery, The First Affiliated Hospital of 
      Jinan University, Guangzhou, People's Republic of China.
CN  - Chinese Obesity and Metabolic Surgery Collaborative
LA  - eng
PT  - Journal Article
DEP - 20210629
PL  - New Zealand
TA  - Nat Sci Sleep
JT  - Nature and science of sleep
JID - 101537767
PMC - PMC8254541
OTO - NOTNLM
OT  - bariatric surgery
OT  - nomogram
OT  - obesity
OT  - obstructive sleep apnea
OT  - predictors
COIS- The authors declare no conflicts of interest for this work.
EDAT- 2021/07/09 06:00
MHDA- 2021/07/09 06:01
PMCR- 2021/06/29
CRDT- 2021/07/08 06:38
PHST- 2021/04/28 00:00 [received]
PHST- 2021/06/10 00:00 [accepted]
PHST- 2021/07/08 06:38 [entrez]
PHST- 2021/07/09 06:00 [pubmed]
PHST- 2021/07/09 06:01 [medline]
PHST- 2021/06/29 00:00 [pmc-release]
AID - 316674 [pii]
AID - 10.2147/NSS.S316674 [doi]
PST - epublish
SO  - Nat Sci Sleep. 2021 Jun 29;13:1013-1023. doi: 10.2147/NSS.S316674. eCollection 
      2021.