Exploring relationships between in-hospital mortality and hospital case volume using random forest: results of a cohort study based on a nationwide sample of German hospitals, 2016–2018

Background Relationships between in-hospital mortality and case volume were investigated for various patient groups in many empirical studies with mixed results. Typically, those studies relied on (semi-)parametric statistical models like logistic regression. Those models impose strong assumptions on the functional form of the relationship between outcome and case volume. The aim of this study was to determine associations between in-hospital mortality and hospital case volume using random forest as a flexible, nonparametric machine learning method. Methods We analyzed a sample of 753,895 hospital cases with stroke, myocardial infarction, ventilation > 24 h, COPD, pneumonia, and colorectal cancer undergoing colorectal resection treated in 233 German hospitals over the period 2016–2018. We derived partial dependence functions from random forest estimates capturing the relationship between the patient-specific probability of in-hospital death and hospital case volume for each of the six considered patient groups. Results Across all patient groups, the smallest hospital volumes were consistently related to the highest predicted probabilities of in-hospital death. We found strong relationships between in-hospital mortality and hospital case volume for hospitals treating a (very) small number of cases. Slightly higher case volumes were associated with substantially lower mortality. The estimated relationships between in-hospital mortality and case volume were nonlinear and nonmonotonic. Conclusion Our analysis revealed strong relationships between in-hospital mortality and hospital case volume in hospitals treating a small number of cases. The nonlinearity and nonmonotonicity of the estimated relationships indicate that studies applying conventional statistical approaches like logistic regression should consider these relationships adequately.

Superior Mesenteric Artery Syndrome: A Community Hospital Case Series

Superior mesenteric artery syndrome is an obstruction of the small bowel between the aorta and the superior mesenteric artery. Patients with this disease are initially managed medically and those patients who fail medical treatment require surgery. A retrospective case series of thirteen patients diagnosed with SMAS at Flushing Hospital, Flushing, NY, from 2011 to 2020 was performed. Descriptive statistics were used to summarize the characteristics of the entire cohort, and comparative statistics were used to compare the patients who failed medical treatment and required surgery to those who were successfully managed medically. Nine patients were managed conservatively and four patients required operative intervention. BMI was significantly lower in patients requiring operation compared to those who were successfully managed medically. This retrospective community hospital case series adds to the literature on SMAS and provides evidence of BMI as a potential predictor of requiring surgery in SMAS.

Analysis of complications after hemorrhoidectomy: clinical case

The term "hemorrhoids" refers to a pathological increase in hemorrhoids, which is manifested by periodic "exacerbation", bleeding from the nodes and their prolapse from the anal canal. This pathology is one of the most common in adult coloproctological practice all over the world. The article presents a brief analysis of hospital case histories of patients with hemorrhoidal disease and complications after hemorrhoidectomy, who were treated in the Coloproctology Unit of the First Republican Clinical Hospital of the Udmurt Republic as well as the analysis of a clinical case.