Prophylactic Use of Haloperidol and Changes in Glucose Levels in Hospitalized Older Patients

Determine independent gut microbiota-diseases association by eliminating the effects of human lifestyle factors

Lifestyle and physiological variables on human disease risk have been revealed to be mediated by gut microbiota. Low concordance between case-control studies for detecting disease-associated microbe existed due to limited sample size and population-wide bias in lifestyle and physiological variables. To infer gut microbiota-disease associations accurately, we propose to build machine learning models by including both human variables and gut microbiota. When the model's performance with both gut microbiota and human variables is better than the model with just human variables, the independent gut microbiota -disease associations will be confirmed. By building models on the American Gut Project dataset, we found that gut microbiota showed distinct association strengths with different diseases. Adding gut microbiota into human variables enhanced the classification performance of IBD significantly; independent associations between occurrence information of gut microbiota and irritable bowel syndrome, C. difficile infection, and unhealthy status were found; adding gut microbiota showed no improvement on models' performance for diabetes, small intestinal bacterial overgrowth, lactose intolerance, cardiovascular disease. Our results suggested that although gut microbiota was reported to be associated with many diseases, a considerable proportion of these associations may be very weak. We proposed a list of microbes as biomarkers to classify IBD and unhealthy status. Further functional investigations of these microbes will improve understanding of the molecular mechanism of human diseases.

Diabetes mellitus in patients using psychotropic medications: How does it work?

Diabetes mellitus (DM) is not a single disease, but a group of diseases that are characterized by chronic hyperglycemia and risk of damage to tissues and organs. The mechanisms of its development are different and due mainly to disorders of insulin secretion or its effects. For this reason, 4 types of DM have been distinguished. One of them is a specific type of DM, determined, inter alia, by the use of certain psychotropic medications. Chronic hyperglycemia often occurs in association with some of these drugs, but in many cases it is categorized erroneously as type 2 (T2DM) or 1 (T1DM). The relationship between DM and psychiatric disorders is bi-directional, involving two mutually independent risk factors for the development of the disease. However, not all patients with a mental illness develop carbohydrate metabolism disorders, which is due to a varied diabetogenic potential and mechanisms of action of psychotropic medications. In clinical practice, questions concerning the frequency of this type of DM, risk factors of its development and hyperglycemic mechanism of psychotropic medications arise. Therefore, the aim of this article is to attempt to answer these questions. From a practical point of view, obtaining such information should allow for the development of appropriate diagnostic and therapeutic procedures.