RESUMEN
INTRODUCTION: The aim of the study was to examine whether disinfection of bacillus Calmette-Guerin-containing urine with etaprocohol® (ethanol 76.9-81.4 vol % and isopropanol as an additive) is safer than disinfection with sodium hypochlorite. METHOD: In prospective research, safety and efficacy was analyzed in 5 patients in the etaprocohol® disinfection group and 5 patients in the sodium hypochlorite disinfection group. The primary endpoint was the temperature change after disinfection and the secondary endpoint was the unpleasantness of the odor caused by disinfection. Additionally, concentration of gas produced was also examined. Sensory tests were taken from staff who performed urine disinfection and the odor generated by disinfection was evaluated. As a safety protocol, post-BCG-treated urine is cultured to verify the negativity for mycobacteria. RESULTS: Mycobacteria were disinfected in all cases. The temperature rise following disinfection was significantly higher in the sodium hypochlorite group. The sensory test outcomes were significantly worse in the group disinfected with sodium hypochlorite. The concentration of gas generated immediately after disinfection in both groups reached the maximum value and declined quickly. CONCLUSIONS: Disinfection of bacillus Calmette-Guerin-containing urine with etaprocohol® was safer than disinfection with sodium hypochlorite, and an equivalent disinfection effect was achieved.
RESUMEN
Medical interviews are expected to undergo a major transformation through the use of artificial intelligence. However, artificial intelligence-based systems that support medical interviews are not yet widespread in Japan, and their usefulness is unclear. A randomized, controlled trial to determine the usefulness of a commercial medical interview support system using a question flow chart-type application based on a Bayesian model was conducted. Ten resident physicians were allocated to two groups with or without information from an artificial intelligence-based support system. The rate of correct diagnoses, amount of time to complete the interviews, and number of questions they asked were compared between the two groups. Two trials were conducted on different dates, with a total of 20 resident physicians participating. Data for 192 differential diagnoses were obtained. There was a significant difference in the rate of correct diagnosis between the two groups for two cases and for overall cases (0.561 vs. 0.393; p = 0.02). There was a significant difference in the time required between the two groups for overall cases (370 s (352-387) vs. 390 s (373-406), p = 0.04). Artificial intelligence-assisted medical interviews helped resident physicians make more accurate diagnoses and reduced consultation time. The widespread use of artificial intelligence systems in clinical settings could contribute to improving the quality of medical care.
