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BACKGROUND AND AIMS: Extra-intestinal manifestations (EIMs) are a common complication of inflammatory bowel diseases (IBD), affecting up to half of the patients. Despite their high prevalence, information on standardised definitions, diagnostic strategies, and treatment targets is limited. METHODS: As a starting point for a national EIM study network, an interdisciplinary expert panel of 12 gastroenterologists, 4 rheumatologists, 3 ophthalmologists, 6 dermatologists, and 4 patient representatives was assembled. Modified Delphi consensus methodology was used. Fifty-four candidate items were derived from the literature review and expert opinion focusing on five major EIMs (erythema nodosum, pyoderma gangrenosum, uveitis, peripheral arthritis, and axial arthritis) were rated in three voting rounds. RESULTS: For use in a clinical practice setting and as part of the creation of a prospective registry of patients with EIMs, the panel developed definitions for erythema nodosum, pyoderma gangrenosum, uveitis, peripheral arthritis, and axial arthritis; identified the appropriate and optimal subspecialists to diagnose and manage each; provided methods to monitor disease course; offered guidance regarding monitoring intervals; and defined resolution and recurrence. CONCLUSIONS: Consensus criteria for appropriate and optimal means of diagnosing and monitoring five EIMs have been developed as a starting point to inform clinical practice and future trial design. Key findings include straightforward diagnostic criteria, guidance regarding who can appropriately and optimally diagnose each, and monitoring options that include patient and physician-reported outcomes. These findings will be used in a national multicenter study network to optimise the management of EIMs.

Background: Natural language processing models such as ChatGPT can generate text-based content and are poised to become a major information source in medicine and beyond. The accuracy and completeness of ChatGPT for medical queries is not known. Methods: Thirty-three physicians across 17 specialties generated 284 medical questions that they subjectively classified as easy, medium, or hard with either binary (yes/no) or descriptive answers. The physicians then graded ChatGPT-generated answers to these questions for accuracy (6-point Likert scale; range 1 – completely incorrect to 6 – completely correct) and completeness (3-point Likert scale; range 1 – incomplete to 3 - complete plus additional context). Scores were summarized with descriptive statistics and compared using Mann-Whitney U or Kruskal-Wallis testing. Results: Across all questions (n=284), median accuracy score was 5.5 (between almost completely and completely correct) with mean score of 4.8 (between mostly and almost completely correct). Median completeness score was 3 (complete and comprehensive) with mean score of 2.5. For questions rated easy, medium, and hard, median accuracy scores were 6, 5.5, and 5 (mean 5.0, 4.7, and 4.6; p=0.05). Accuracy scores for binary and descriptive questions were similar (median 6 vs. 5; mean 4.9 vs. 4.7; p=0.07). Of 36 questions with scores of 1-2, 34 were re-queried/re-graded 8-17 days later with substantial improvement (median 2 vs. 4; pConclusions: ChatGPT generated largely accurate information to diverse medical queries as judged by academic physician specialists although with important limitations. Further research and model development are needed to correct inaccuracies and for validation.

BACKGROUND Inflammatory bowel diseases (IBD) are chronic inflammatory conditions of the gastrointestinal tract often requiring long-term medical therapy. While adherence to IBD therapies is associated with improved clinical outcomes, overall adherence is poor with reports demonstrating adherence rates ranging from 40% to 80%. Consequently, there is a critical need to develop interventions that monitor adherence in-real time and identify reasons for non-adherence to support clinical teams in initiating effective interventions. Recently, electronic- and virtual-based platforms have been developed to routinely monitor adherence and guide appropriate interventions. A novel remote therapeutic monitoring (RTM) technology, the TapptTM digital health system, has been developed to monitor real-time medication adherence patterns through smart label technologies, capture patient reported outcomes (PROs) and barriers to care, and process patient data through algorithms that trigger personalized digital and human touchpoints between clinical visits. Such digital health solution enables care teams to proactively identify and mitigate nonadherence and worsening clinical outcomes. OBJECTIVE We propose a 12-month, multicenter, randomized, controlled trial to assess the effectiveness of TapptTM digital health system on adherence, clinical outcomes, and healthcare utilization among patients diagnosed with IBD starting a new oral or subcutaneous therapy. METHODS Specifically, we will (Aim 1) compare adherence as measured by the Medication Possession Ratio (MPR) in participants using the RTM compared to standard of care and (Aim 2) compare clinical outcomes and healthcare utilization in participants using the RTM compared to standard of care. RESULTS We anticipate starting recruitment in August 2022. CONCLUSIONS Effective medication adherence monitoring and intervention programs need to be cost-efficient, pose little to no burden to the patient, be unobtrusive, record reliable data in real-time, and provide actionable insights to the healthcare team. We anticipate the TapptTM digital health system to improve the MPR, clinical outcomes, and healthcare utilization compared to standard of care. CLINICALTRIAL NCT05316584

The World Health Organization has set a standard of maintaining a core body temperature above 36°C in the perioperative period. The purpose of this study was to examine the relationship between both intraoperative temperature (IOT) and immediate postop core body temperature as it relates to postop complications. A retrospective analysis of a prospective database of patients who underwent an elective segmental colectomy without a stoma, for 3 diagnoses was performed. Six postoperative outcomes were examined: length of stay (LOS), placement of a nasogastric tube, return to the operating room, placement of an interventional drain, diagnosed leak, and surgical site infection (SSI). Statistics were calculated using a two-sample Wilcoxon rank-sum (Mann-Whitney) test. Seventy-nine patients met the inclusion criteria and there were no preoperative differences between the groups (those with a postop complication vs without). LOS9 days (36.64°C vs 35.98°C; P = 0.011) and clinical leak (37.06°C vs 35.99°C; P = 0.005) both had a statistically higher average IOT than those who did not. Patients with SSI trended to a higher IOT (36.44°C vs 35.99°C; P = 0.062). When the last IOT recorded was compared with the six outcomes, again length of stay and leak both were statistically significant (P = 0.018, P = 0.012) showing a higher temperature related to a higher complication rate. No other complications were related to IOT, nor did postop temperature relate to complication. In our data, relatively lower IOTs were protective for LOS and clinical leaks, with a trend of lower SSI rates. Further research is needed to fully endorse or refute the absolute recommendations for core body temperature.