ArticleJournal of advanced nursing2025
Predictive Model for Hypoglycaemia Risk in Type 2 Diabetes Mellitus Patients During the Peri-Colonoscopy Period: A Retrospective Cohort Study.
Article in Journal of advanced nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Abstract
aimsTo identify factors influencing hypoglycaemia in patients with type 2 diabetes mellitus (T2DM) undergoing colonoscopy and to construct a predictive model for assessing hypoglycaemia risk.
designA retrospective cohort study.
methodsWe retrospectively collected data on 598 T2DM patients who underwent colonoscopy and randomised them into a developmental cohort and a validation cohort in a 7:3 ratio. We used multivariate logistic regression to develop a predictive model for hypoglycaemia during colonoscopy and identify independent predictors in pre- and post-colonoscopy hypoglycaemia groups.
resultsWe identified 112 of 598 (18.7%) T2DM patients who experienced hypoglycaemia during the peri-colonoscopy period: 43 pre-colonoscopy, 61 post-colonoscopy and 8 at both junctures. Ultimately, five predictors-insulin, SGLT2 inhibitors, fasting after colonoscopy, fasting C-peptide and estimated glomerular filtration rate (eGFR)-were integrated into the predictive model. The AUC for predicting hypoglycaemia was 0.78 (95% CI, 0.71-0.84) and 0.82 (95% CI, 0.74-0.90) in the development and validation cohort, respectively. Variables associated with pre-colonoscopy hypoglycaemia included SGLT2 inhibitors, fasting C-peptide and eGFR, whereas the post-colonoscopy hypoglycaemia group was associated with metformin, duration of diabetes, fasting C-peptide and fasting after the examination.
conclusionThis study successfully developed and validated a predictive model for assessing hypoglycaemia risk in T2DM patients during peri-colonoscopy. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Early identification of patients at high risk for peri-colonoscopy hypoglycaemia allows nurses to implement personalised preventive strategies. The predictive model enables clinical nurses to deliver tailored interventions based on individual risk factors, potentially reducing hypoglycaemia-related complications and improving patient safety outcomes. IMPACT: This study provides nurses with a validated risk prediction tool for identifying high-risk type 2 diabetes patients during colonoscopy, enabling targeted blood glucose monitoring protocols and preventive interventions in clinical practice. REPORTING
methodThis study follows the STROBE guidelines for reporting cohort studies. PATIENT OR PUBLIC CONTRIBUTION: Diabetes patients contributed electronic health record datasets.
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