RESUMEN
Introduction: Antibiotic resistant bacterial infections (ARBIs) are extremely common in nursing home residents. These infections typically occur after a course of antibiotics, which eradicate both pathological and beneficial organisms. The eradication of beneficial organisms likely facilitates subsequent ARBIs. Autologous fecal microbiota transplant (aFMT) has been proposed as a potential treatment to reduce ARBIs in nursing home residents. Our objective was to determine the feasibility and safety of aFMT in a nursing home population. Methods: Pilot clinical trial. We evaluated feasibility as total number of stool samples collected for aFMT production and safety as the number and relatedness of serious (SAE) and non-serious adverse events (AE). Results: We screened 468 nursing home residents aged ≥18 years for eligibility; 67 enrolled, distributed among three nursing homes. Participants were 62.7% female and 35.8% Black. Mean age was 82.2 ± 8.5 years. Thirty-three participants underwent successful stool collection. Seven participants received antibiotics; four participants underwent aFMT. There were 40 SAEs (17 deaths) and 11 AEs. In the aFMT group, there were 3 SAEs (2 deaths) and 10 AEs. All SAEs and AEs were judged unrelated to the study intervention. Conclusions: In this pilot study of aFMT in nursing home residents, less than half were able to provide adequate stool samples for aFMT. There were no related SAEs or AEs during the study. In sum, we conclude aFMT has limited feasibility in a nursing home population due to logistic and technical challenges but is likely safe. Trial registration: ClinicalTrials.gov Identifier: NCT03061097.
RESUMEN
Polypharmacy, the use of five or more medications, is common in older adults. It can lead to the use of potentially inappropriate medications and severe adverse outcomes. Deprescribing is an essential step of the thoughtful prescribing process and it can decrease the use of potentially inappropriate medications. Studies have demonstrated that deprescribing is feasible in the clinical setting, especially when it incorporates patient preferences, shared decision making, and an interdisciplinary team. Medication-specific algorithms can facilitate deprescribing in the clinical setting.
