Prediction of Hypoglycemia in Diabetic Patients During Colonoscopy Preparation

Abstract

Objective To explore the clinical outcomes and establish a predictive model of hypoglycemia during colonoscopy preparation for diabetic patients.

Methods Three-hundred ninety-four patients with diabetes who received colonoscopy were retrospectively enrolled in this study and assigned to hypoglycemia or non-hypoglycemia groups. Information about clinical characteristics and outcomes during colonoscopy preparation was collected and compared between the two groups. Logistic regression analysis was applied to identify the risk factors of hypoglycemia. These risk factors were used to construct a hypoglycemia predictive model verified by the receiver operating characteristic (ROC) curve and Hosmer-Lemeshow goodness fit test.

Results Among 394 participants, 66 (16.8%) underwent a total of 88 hypoglycemia attacks during the bowel preparation. Grade 1 hypoglycemia (≤3.9 mmol/L) comprised 90.9% (80/88) of all hypoglycemia attacks and grade 2 hypoglycemia accounted for 9.1% (8/88), signifying that grade 1 hypoglycemia is the most common type. No severe hypoglycemia was identified. The incidence of nocturnal hypoglycemia was 15.9%. Logistic regression analyses revealed that the main risk factors of hypoglycemia during colonoscopy preparation were postprandial C-peptide, serum triglyceride, gender, type of diabetes mellitus, and insulin injection frequencies. The area under the ROC curve of the hypoglycemia prediction model was 0.777 (95% CI: 0.720–0.833).

Conclusion Diabetic patients are prone to develop mild to moderate hypoglycemia during colonoscopy preparation. This study proposes a predictive model that could provide a reference for identifying patients with a high risk of hypoglycemia during colonoscopy preparation.

Key words

diabetes - colonoscopy - hypoglycemia - predictive model

^* These authors contributed equally to this work. Xiaohua Lu, Lingqiao Xie

Publikationsverlauf

Eingereicht: 28. September 2022
Eingereicht: 10. Februar 2023

Angenommen: 13. Februar 2023

Artikel online veröffentlicht:
26. April 2023

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