Restarting Antithrombotic Therapies After Endoscopic Sinus Surgery: A Systematic Review.

OBJECTIVES: Antithrombotic therapies, comprised of both anticoagulant and antiplatelet agents, are routinely paused prior to endoscopic sinus surgery (ESS) to reduce the risk of perioperative hemorrhage. At present, no clear guidelines exist to guide otolaryngologists on when to resume these agents after ESS. Our goal was to systematically review the existing literature related to this topic. METHODS: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically queried the PubMed, Embase, Ovid, Web of Science, Cochrane, and CINAHL databases to identify publications reporting on antithrombotic and antiplatelet therapy in the context of ESS. The primary outcomes we sought were recommendations on the timing of antithrombotic therapy resumption after ESS. RESULTS: Of the 104 unique articles identified, all were screened for relevance by 2 independent reviewers based on title and abstract, 20 underwent full-text review, and 6 met inclusion criteria for analysis. Of these, 3 were literature reviews, 2 were case-control studies, and 1 was a cohort study. All publications discussed when to pause antithrombotic therapy prior to surgery while only 3 articles discussed resumption of these agents. Recommendations were mixed. CONCLUSION: A paucity of literature exists on the resumption of antithrombotic therapies after ESS. As a major determining factor in patient morbidity, guideline-based resumption of these therapies is needed.

ChatGPT for Automated Cross-Checking of Authors' Conflicts of Interest Against Industry Payments.

OBJECTIVE: The Centers for Medicare & Medicaid Services "OpenPayments" database tracks industry payments to US physicians to improve research conflicts of interest (COIs) transparency, but manual cross-checking of articles' authors against this database is labor-intensive. This study aims to assess the potential of large language models (LLMs) like ChatGPT to automate COI data analysis in medical publications. STUDY DESIGN: An observational study analyzing the accuracy of ChatGPT in automating the cross-checking of COI disclosures in medical research articles against the OpenPayments database. SETTING: Publications regarding Food and Drug Administration-approved biologics for chronic rhinosinusitis with nasal polyposis: omalizumab, mepolizumab, and dupilumab. METHODS: First, ChatGPT evaluated author affiliations from PubMed to identify those based in the United States. Second, for author names matching 1 or multiple payment recipients in OpenPayments, ChatGPT undertook a comparative analysis between author affiliation and OpenPayments recipient metadata. Third, ChatGPT scrutinized full article COI statements, producing an intricate matrix of disclosures for each author against each relevant company (Sanofi, Regeneron, Genentech, Novartis, and GlaxoSmithKline). A random subset of responses was manually checked for accuracy. RESULTS: In total, 78 relevant articles and 294 unique US authors were included, leading to 980 LLM queries. Manual verification showed accuracies of 100% (200/200; 95% confidence interval [CI]: 98.1%-100%) for country analysis, 97.4% (113/116; 95% CI: 92.7%-99.1%) for matching author affiliations with OpenPayments metadata, and 99.2% (1091/1100; 95% CI: 98.5%-99.6%) for COI statement data extraction. CONCLUSION: LLMs have robust potential to automate author-company-specific COI cross-checking against the OpenPayments database. Our findings pave the way for streamlined, efficient, and accurate COI assessment that could be widely employed across medical research.

Cost-effectiveness of rapid vs in-house vs send-out ADAMTS13 testing for immune thrombotic thrombocytopenic purpura.

ABSTRACT: While awaiting confirmatory results, empiric therapy for patients suspected to have immune thrombotic thrombocytopenic purpura (iTTP) provides benefits and also accrues risks and costs. Rapid assays for ADAMTS13 may be able to avoid the cost and risk exposure associated with empiric treatment. We conducted, to our knowledge, the first cost-effectiveness evaluation of testing strategies with rapid vs traditional ADAMTS13 assays in patients with intermediate- to high-risk PLASMIC scores, with and without caplacizumab use. We built a Markov cohort simulation with 4 clinical base-case analyses: (1) intermediate-risk PLASMIC score with caplacizumab; (2) intermediate-risk PLASMIC score without caplacizumab; (3) high-risk PLASMIC score with caplacizumab; and (4) high-risk PLASMIC score without caplacizumab. Each of these evaluated 3 testing strategies: (1) rapid assay (<1-hour turnaround); (2) in-house fluorescence resonance energy transfer (FRET)-based assay (24-hour turnaround); and (3) send-out FRET-based assay (72-hour turnaround). The primary outcome was the incremental net monetary benefit reported over a 3-day time horizon and across accepted willingness-to-pay thresholds in US dollars per quality-adjusted life-year (QALY). While accruing the same amount of QALYs, the rapid assay strategy saved up to $46 820 (95% CI, $41 961-$52 486) per patient tested. No parameter variation changed the outcome. In probabilistic sensitivity analyses, the rapid assay strategy was favored in 100% (3 base cases and scenario analyses) and 99% (1 base-case and scenario analysis) across 100 000 Monte Carlo iterations within each. Rapid ADAMTS13 testing for patients with intermediate- or high-risk PLASMIC scores yields significant per patient cost savings, achieved by reducing the costs associated with unnecessary therapeutic plasma exchange and caplacizumab therapy in patients without iTTP.