Citations

Abstract Background Large language models (LLMs) offer promise for systematic review data extraction, but performance in complex multidisciplinary domains and utility for clinical statement generation remain insufficiently described. Objectives To evaluate Google NotebookLM for AI-assisted data extraction and RAND/UCLA consensus statement generation in a systematic review of IBD, obesity, and cardiometabolic comorbidities. Methods Studies were organized into domain-specific notebooks; structured prompts generated standardized evidence tables. Two independent reviewers validated outputs against full-text articles using a four-category error classification. Cell-level accuracy and critical accuracy (cells free of major factual errors) were the primary metrics; workflow time was compared against a published conventional extraction benchmark. Concordance between AI-generated and expert-finalized statements was assessed. Results Across 57 articles, 1,710 data cells were extracted; 151 (8.83%) were flagged, yielding 91.17% cell-level accuracy. Major factual errors occurred in only 4 cells (0.23%), for a critical accuracy of 99.77%. Most errors were minor omissions (59.6%) or incomplete extractions (30.5%); domain error rates ranged from 7.08% to 11.33%. The pipeline required 17.7 versus a projected 165.1 person-hours (89.3% reduction). PICO-structured prompting generated 70 candidate statements; 58 of 112 finalized panel statements (51.8%) were AI-derived, and 85.7% were retained in the finalized set. Conclusion Google NotebookLM demonstrates feasibility as a primary extraction and synthesis tool in a multidisciplinary systematic review, with extractive incompleteness as the principal limitation and substantial time savings over conventional approaches. Its novel application to RAND/UCLA consensus statement generation extends AI-assisted evidence synthesis to clinical consensus generation workflow.

Introduction Obesity and related cardiometabolic comorbidities, including hypertension, dyslipidaemia, diabetes, metabolic dysfunction-associated steatotic liver disease and atherosclerotic cardiovascular disease, are increasingly prevalent among individuals with inflammatory bowel disease (IBD). These conditions influence disease activity, therapeutic response, surgical outcomes and overall quality of life, yet evidence remains fragmented. The M odulate O besity and relate D metabolic compl I cations F or Y ielding improvements in IBD outcomes (MODIFY-IBD) initiative aims to synthesise evidence and generate consensus recommendations to guide practice and future research in this area. This study describes a protocol for a structured evidence synthesis and Research ANd Development/University of California, Los Angeles (RAND/UCLA) Appropriateness Method (RUAM) consensus process. Methods and analysis We will conduct three systematic reviews and a structured evidence synthesis organised into three domains: (1) the impact of obesity on IBD outcomes, (2) the burden of cardiometabolic complications in IBD and (3) the management of overweight, obesity and cardiometabolic comorbidities in IBD. A multidisciplinary international panel of gastroenterologists, surgeons, endocrinologists, hepatologists, cardiologists and dietitians will assess each statement using the RAND/UCLA appropriateness method. Panellists will rate the appropriateness of each statement (only those that fall within their area of expertise) on a 1–9 scale (1–3=inappropriate, 4–6=uncertain and 7–9=appropriate), with medians rounded up (eg, 6.5=appropriate). Agreement will be assessed using the RAND Disagreement Index (DI<1.0=agreement). Ethics and dissemination This study will not involve direct patient participation, as it is based on evidence synthesis and expert consensus; therefore, formal research ethics committee approval will not be required. Patient representatives will contribute to the consensus process to provide contextual perspectives but no identifiable data will be collected. Findings will be disseminated through publication in peer-reviewed journals, presentation at major gastroenterology and IBD conferences and communication with professional societies. A lay summary and patient-friendly infographic will also be developed to facilitate translation of recommendations into clinical practice. PROSPERO registration numbers CRD420251178843: a systematic review of the impact of obesity on inflammatory bowel disease outcomes. CRD420251178799: a systematic review of cardiometabolic complications in inflammatory bowel disease. CRD420251174653: management of overweight, obesity and cardiometabolic comorbidities in inflammatory bowel disease: a systematic review.

Background: Home telemetry has been shown to reduce 30-day readmissions in patients at high risk for readmission. It remains unclear whether this finding is due to the telemetry itself or the nurse contact that follows detection of an abnormal parameter. Purpose: This study was a subgroup analysis from a prior trial comparing patients on home telemetry for 30 days to usual care after discharge to determine if nurse contact affected readmission rates. Methods: Patients randomized to telemetry who had at least 1 nurse contact were compared to those who had none to see if the contact reduced the rate of readmissions. Results: Of 449 home telemetry patients, 292 (65.0%) received 1 or more nurse contacts. Single and multivariable logistic regression models exploring the association of contact with 30-day readmission did not find any statistically significant associations of nurse contact with readmission (all unadjusted P ≥ .13, all adjusted P ≥ .18). Conclusion: Our subset analysis did not show that the nurse contact was the factor that reduced readmission in patients on home telemetry.

Abstract Background: Home telemonitoring has been shown to reduce 30-day readmissions patients at high risk for return to the hospital. The reason for this remains unclear. The aim of this study was to explore the association of nurse contact with 30-day hospital readmission in these high risk patients. Methods: This study was a subgroup analysis from a prior randomized control comparing home telemonitoring for readmission for 30 days to usual care at discharge. Patients randomized to the home telemonitoring who had vital signs outside a preset range, triggered an alert flag for the monitoring nurse, which generated a contact to the patient. We compared patients who had at least one nurse contact to those who had none to see if the contact reduced the rate of readmissions in patients being monitored. Results: Of 449 patients, 292 (65.0%) received 1 or more telemonitoring flags. Single variable and multivariable logistic regression models exploring the association of flag type with hospital 30-day readmission did not find any statistically significant associations of telemonitoring flags with hospital 30-day readmission (all unadjusted P≥0.13, all adjusted P≥0.18). Conclusion: While post-hospitalization home telemetry has been shown to reduce 30-day readmission, our subset analysis did not show that the nurse contact was the factor that reduced readmission in these patients. Trial registration: ClinicalTrials.gov identifier: NCT02136186, registration date May 12, 2014.