Predicting inpatient mortality in patients with inflammatory bowel disease: A machine learning approach

Background and Aim

Data are lacking on predicting inpatient mortality (IM) in patients admitted for inflammatory bowel disease (IBD). IM is a critical outcome; however, difficulty in its prediction exists due to infrequent occurrence. We assessed IM predictors and developed a predictive model for IM using machine-learning (ML).

Methods

Using the National Inpatient Sample (NIS) database (2005–2017), we extracted adults admitted for IBD. After ML-guided predictor selection, we trained and internally validated multiple algorithms, targeting minimum sensitivity and positive likelihood ratio (+LR) ≥ 80% and ≥ 3, respectively. Diagnostic odds ratio (DOR) compared algorithm performance. The best performing algorithm was additionally trained and validated for an IBD-related surgery sub-cohort. External validation was done using NIS 2018.

Results

In 398 426 adult IBD admissions, IM was 0.32% overall, and 0.87% among the surgical cohort (n = 40 784). Increasing age, ulcerative colitis, IBD-related surgery, pneumonia, chronic lung disease, acute kidney injury, malnutrition, frailty, heart failure, blood transfusion, sepsis/septic shock and thromboembolism were associated with increased IM. The QLattice algorithm, provided the highest performance model (+LR: 3.2, 95% CI 3.0–3.3; area-under-curve [AUC]:0.87, 85% sensitivity, 73% specificity), distinguishing IM patients by 15.6-fold when comparing high to low-risk patients. The surgical cohort model (+LR: 8.5, AUC: 0.94, 85% sensitivity, 90% specificity), distinguished IM patients by 49-fold. Both models performed excellently in external validation. An online calculator ( https://clinicalc.ai/im-ibd/ ) was developed allowing bedside model predictions.

Conclusions

An online prediction-model calculator captured > 80% IM cases during IBD-related admissions, with high discriminatory effectiveness. This allows for risk stratification and provides a basis for assessing interventions to reduce mortality in high-risk patients.     

Case Report- A rare case of giant hyperplastic polyp

Giant gastric hyperplastic polyps are the most common benign epithelial tumors in the stomach. These are non-neoplastic epithelial proliferations of the stomach which are strongly associated with inflammatory conditions like chronic gastritis, helicobacter pylori gastritis, reactive or chemical gastritis. A 60 years old gentleman presented with history of two bouts of hematemesis preceded by multiple intermittent episodes of epigastric pain, nausea and few episodes of non-bilious vomiting without any history of previous gastrointestinal bleed, loss of appetite or significant weight loss. Work up with ultrasonography of abdomen, upper gastrointestinal endoscopy, contrast enhanced computed tomography abdomen, laboratory investigations followed by biopsy and histopathology was done which confirmed the diagnosis. Giant hyperplastic polyps are benign epithelial tumor of stomach often resulting from excessive regenerative hyperplasia in areas of chronic inflammation with no site predilection and nearly no malignant potential. Usually asymptomatic, these are incidentally detected on upper gastrointestinal endoscopy with characteristic appearance of such polyps on double contrast barium study followed by upper gastrointestinal endoscopy and biopsy is definitive for diagnosis.