High incidence of glucocorticoid-induced hyperglycaemia in inflammatory bowel disease: metabolic and clinical predictors identified by machine learning

Abstract

BackgroundGlucocorticosteroids (GC) are long-established, widely used agents for induction of remission in inflammatory bowel disease (IBD). Hyperglycaemia is a known complication of GC treatment with implications for morbidity and mortality. Published data on prevalence and risk factors for GC-induced hyperglycaemia in the IBD population are limited. We prospectively characterise this complication in our cohort, employing machine-learning methods to identify key predictors of risk.MethodsWe conducted a prospective observational study of IBD patients receiving intravenous hydrocortisone (IVH). Electronically triggered three times daily capillary blood glucose (CBG) monitoring was recorded alongside diabetes mellitus (DM) history, IBD biomarkers, nutritional and IBD clinical activity scores. Hyperglycaemia was defined as CBG ≥11.1 mmol/L and undiagnosed DM as glycated haemoglobin ≥48 mmol/mol. Random forest (RF) regression models were used to extract predictor-patterns present within the dataset.Results94 consecutive IBD patients treated with IVH were included. 60% (56/94) of the cohort recorded an episode of hyperglycaemia, including 57% (50/88) of those with no history of DM, of which 19% (17/88) and 5% (4/88) recorded a CBG ≥14 mmol/L and ≥20 mmol/L, respectively. The RF models identified increased C-reactive protein (CRP) followed by a longer IBD duration as leading risk predictors for significant hyperglycaemia.ConclusionHyperglycaemia is common in IBD patients treated with intravenous GC. Therefore, CBG monitoring should be included in routine clinical practice. Machine learning methods can identify key risk factors for clinical complications. Steroid-sparing treatment strategies may be considered for those IBD patients with higher admission CRP and greater disease duration, who appear to be at the greatest risk of hyperglycaemia.

Machine Learning Prediction Model for Inflammatory Bowel Disease Based on Laboratory Markers. Working Model in a Discovery Cohort Study

“…Moreover, it was demonstrated that machine learning methods may be applied to identify risk of therapy complications in IBD. For instance, McDonell et al demonstrated that random forest (RF) regression models identified higher levels of CRP and longer duration of disease as predictors for hyperglycemia in IBD patients treated with intravenous glucocorticosteroids [ 16 ]. In turn, Choi et al developed a machine learning model to predict the five-year risk of starting biologic therapy in IBD patients [ 17 ].…”

Infliximab rescue therapy in a case of severe granulomatous colitis associated with rituximab use

“…Due to the severity of inflammation, colorectal surgeons were asked to review the patient to consider colectomy, as supportive care with systemic steroids and exclusive enteral nutrition did not lead to an improvement in the patient’s condition after 3 days. Intravenous steroids were stopped due to lack of efficacy, hyperglycaemia9 and concerns of increasing perioperative complications in case of colectomy. This was an IBD multidisciplinary team (MDT) decision in this individual case and it should be noted that systemic steroids are an important therapy in severe ulcerative colitis management 10.…”

Efficacy and safety of dual therapy - biological and small molecules in patients with ulcerative colitis

“…Кроме того, у некоторых пациентов на протяжении всего заболевания наблюдаются множественные сопутствующие заболевания, связанные в том числе с длительным приемом кортикостероидов (сахарный диабет, остеопороз, надпочечниковая недостаточность и др. ), которые часто применяют у больных с субоптимальным клиническим ответом [5].…”

“…Эффективность и безопасность двой ной терапии -биологической и малыми молекулами у пациентов с язвенным колитом (стр. [5][6][7][8][9][10][11][12] To article Effi cacy and safety of dual therapy -biological and small molecules in patients with ulcerative colitis (p. 5-12)…”