Development and independent validation of a hypoxemia risk prediction model (HAPPY-12K) for sedated gastrointestinal endoscopy: a multicentre prospective cohort study.

Authors

Nana Li, Xiaoshuang Xu, Maojie Xue, Jiacheng Zhou, Xiang Wang, Junbei Wu, Leyi Chen, Yuqing Yang, Jiajin Chen, Tianlin Zhou, Jigang Zhang, Yanna Si, Yanxiang Miao, Guoxiang Fan, Dong Shao, Xin Liu, Liang Sun, Chaolin Guo, Feng Chen, David C Christiani, YunHong Lu, Hui Peng, Xiaofei Cao, Ruyang Zhang

Published in

EClinicalMedicine. Volume 98. Pages 104090. Epub Jul 23, 2026.

Abstract

Hypoxemia is a common and serious complication during sedated gastrointestinal endoscopy for out- and in-patients. Though diagnostic and severity scoring systems of obstructive sleep apnea (OSA) and difficult airway assessment (DAA) are widely used to assess hypoxemia risk, there is no exclusively designed prediction model and convenient tool in real-world practice. We aimed to develop and validate a robust and accurate hypoxemia risk prediction model for pre-operative use in this context.
Using data from out-patients undergoing gastrointestinal endoscopy between May 2020 and November 2023 across seven hospitals in China with diverse regional and ethnic backgrounds, we developed and independently validated a hypoxemia risk prediction model for sedated gastrointestinal endoscopy (HAPPY-12K). The model was developed to pre-operatively predict occurrence of hypoxemia during sedated gastrointestinal endoscopy, defined as SpO₂ falling below 95% for a duration exceeding 10 s. HAPPY-12K was a logistic regression model incorporating eight predictors: body mass index, Mallampati grade, limited jaw protrusion, short thyromental distance, large tongue, history of snoring, short neck with large circumference and pre-operative mean arterial pressure. The model was constructed by a well-established 3-D modeling strategy composed of Double types of effects, Double steps of screening, and Double steps of modeling. The discriminative ability was evaluated using the area under the receiver operating characteristic curve (AUC). The model calibration was examined through calibration slope, expected-to-observed (E:O) ratio and Brier score. For clinical utility, decision curve analysis was performed to assess net benefit (NB) and net reduction (NR). Furthermore, we systematically compared HAPPY-12K with other newly developed models using scores or raw variables from questionaries of OSA and DAA using DeLong's test. This study is registered in the Chinese Clinical Trial Registry (ChiCTR2300074128).
We included 11,957 patients, divided into a Training Set (n = 2,518, hypoxemia rate 10.37%), and five validation sets (n = 9,439, hypoxemia rate raining from 8.40% to 28.45%). HAPPY-12K was developed in a Han Chinese population and exhibited satisfactory discrimination ability with AUCs ranging from 0.818 to 0.895 in external populations of the same ethnicity, and an acceptable AUC of 0.771 in a Uygur Chinese population. Although its Brier scores were satisfactory across all ethnic populations, HAPPY-12K displayed acceptable calibration (calibration slope < 1.2) in external Han Chinese populations, and good calibration (E:O ratio = 0.962) in independent homogenous populations comparable to the training set. The average NB and NR were 45.2‰ and 59.5%, respectively. It was estimated that HAPPY-12K would identify over half a million patients with truly developing hypoxemia during sedated gastrointestinal endoscopy and could help avoid over six million unnecessary interventions annually in China. Meanwhile, a head-to-head comparison revealed that HAPPY-12K outperformed other models. HAPPY-12K has been implemented as an interactive online tool available at http://bigdata.njmu.edu.cn/HAPPY-12K/.
HAPPY-12K could enable efficient and precise hypoxemia risk assessment before sedated gastrointestinal endoscopy, providing timely alerts for high-risk outpatients.
National Natural Science Foundation of China; Noncommunicable Chronic Diseases-National Science and Technology Major Project; Science and Technology Project of Jiangsu Disease Control and Prevention Administration; Science and Technology Development Project of Nanjing Medical University; Priority Academic Program Development of Jiangsu Higher Education Institutions; and Outstanding Young Level Academic Leadership Training Program of Nanjing Medical University.

PMID:
42542617
Bibliographic data and abstract were imported from PubMed on 02 Aug 2026.

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