vida: extract claims from 2025-xx-pmc-glp1-psychiatric-disproportionality-faers-cvarod-daen

- Source: inbox/queue/2025-xx-pmc-glp1-psychiatric-disproportionality-faers-cvarod-daen.md
- Domain: health
- Claims: 0, Entities: 0
- Enrichments: 4
- Extracted by: pipeline ingest (OpenRouter anthropic/claude-sonnet-4.5)

Pentagon-Agent: Vida <PIPELINE>

domains/health/glp1-eating-disorder-pharmacovigilance-signal-class-effect-obesity-population-specific.md

@@ -17,3 +17,24 @@ related: ["glp1-eating-disorder-risk-subtype-specific-protective-bed-harmful-res
 # GLP-1 eating disorder pharmacovigilance signal (aROR 4.17-6.80) is a class effect that emerged specifically in the obesity treatment population after June 2021, not in the prior metabolic population
 
 Analysis of 2,061,901 adverse event reports through December 2024 found eating disorder signals with adjusted Reporting Odds Ratios between 4.17 and 6.80 across dulaglutide, semaglutide, and liraglutide—the highest magnitude psychiatric signal in the study. Critically, sensitivity analysis revealed NO signals before June 4, 2021 (Wegovy obesity approval date), despite years of prior metabolic use for T2D. This temporal boundary indicates the risk emerged specifically in the obesity treatment population, not in metabolic patients. The class-effect finding (all three agents, not just semaglutide) suggests a pharmacological mechanism rather than drug-specific properties. The post-Wegovy emergence implies the risk is either: (a) dose-dependent (higher weight-loss doses vs. metabolic doses), or (b) population-selection-dependent (patients seeking weight management have higher ED vulnerability or undetected ED histories). Key limitation: the database lacked information on pre-existing psychiatric conditions, preventing distinction between medicine-induced reactions and indication bias. The aROR magnitude (4.17-6.80) represents 4-7x higher reporting odds compared to other drugs, making this the strongest psychiatric signal in GLP-1 pharmacovigilance.
+
+
+## Supporting Evidence
+
+**Source:** PMC cross-national pharmacovigilance analysis, FAERS/CVAROD/DAEN 2025
+
+Cross-national disproportionality analysis confirms eating disorder signal across US (FAERS), Canadian (CVAROD), and Australian (DAEN) databases. Dulaglutide ROR = 1.47 (95%CI 1.26-1.71) in FAERS and ROR = 17.66 (95%CI 2.45-127.37) in Australian DAEN. Tirzepatide ROR = 1.58 (95%CI 1.14-2.20) in FAERS. Geographic consistency across three national regulatory databases increases biological plausibility of the signal beyond single-database findings.
+
+
+## Extending Evidence
+
+**Source:** PMC cross-national analysis vs. VigiBase comparison
+
+Methodological discrepancy between studies reveals sensitivity of signal detection to analytical approach: this study's unadjusted ROR (1.47-1.58) is 2.8-4.6x lower than VigiBase's adjusted ROR (4.17-6.80). The VigiBase aROR controls for co-reported adverse events while this analysis may not, suggesting the adjusted analysis provides more reliable effect size estimates. The cross-study discrepancy is itself informative about pharmacovigilance methodology limitations.
+
+
+## Extending Evidence
+
+**Source:** PMC DAEN analysis, Australia 2025
+
+Australian DAEN database shows exceptionally high ROR (17.66) for dulaglutide eating disorder reports compared to US/Canadian databases, suggesting either: (1) small denominator effects in lower-volume database, (2) population-specific differences in drug response or reporting patterns, or (3) higher clinical awareness/reporting rates in Australian healthcare system. This geographic heterogeneity in signal strength warrants investigation of population-level moderators.

domains/health/glp1-eating-disorder-screening-gap-structural-capacity-not-clinical-knowledge.md

@@ -11,9 +11,16 @@ sourced_from: health/2025-xx-neda-anad-glp1-eating-disorders-clinical-guidance.m
 scope: structural
 sourcer: NEDA/ANAD
 supports: ["ai-telehealth-glp1-prescribing-commoditizes-at-scale-but-generates-systematic-safety-and-fraud-failures"]
-related: ["the-mental-health-supply-gap-is-widening-not-closing", "ai-telehealth-glp1-prescribing-commoditizes-at-scale-but-generates-systematic-safety-and-fraud-failures", "glp-1-therapy-requires-nutritional-monitoring-infrastructure-but-92-percent-receive-no-dietitian-support"]
+related: ["the-mental-health-supply-gap-is-widening-not-closing", "ai-telehealth-glp1-prescribing-commoditizes-at-scale-but-generates-systematic-safety-and-fraud-failures", "glp-1-therapy-requires-nutritional-monitoring-infrastructure-but-92-percent-receive-no-dietitian-support", "glp1-pre-treatment-eating-disorder-screening-recommended-not-required", "glp1-eating-disorder-risk-subtype-specific-protective-bed-harmful-restrictive"]
 ---
 
 # GLP-1 eating disorder screening gap is structural capacity failure not clinical knowledge deficit because professional society guidance requires tri-specialist care teams unavailable in primary care settings where most prescriptions originate
 
 NEDA and ANAD jointly recommend that GLP-1 prescribing for patients with eating disorder risk factors require a tri-specialist care team: a physician versed in both GLP-1s and eating disorders, a therapist experienced with both GLP-1s and ED treatment, and a dietitian familiar with this medication class and recovery nutrition. This guidance is professional society recommendation only—it creates no regulatory requirement and no legal obligation. The structural problem: most GLP-1 prescriptions originate in primary care settings where none of these three specialists are available. Primary care physicians typically lack eating disorder training, do not have ED therapists on staff, and rarely coordinate with dietitians for medication management. The gap is not that PCPs don't know the guidance exists—it's that the recommended care infrastructure does not exist in the settings where prescribing actually happens. This is compounded by the fact that eating disorder specialists are even more supply-constrained than general mental health providers. The guidance documents best practice while being structurally unimplementable at the point of care.
+
+
+## Supporting Evidence
+
+**Source:** PMC pharmacovigilance methodology limitations 2025
+
+Study explicitly acknowledges indication bias limitation: 'The databases used in this study did not contain information on any pre-existing psychiatric conditions in patients reporting AEs' and researchers could not 'distinguish between a medicine-induced reaction and an event related to a patient's ongoing health issues.' This structural data gap in pharmacovigilance databases prevents causal determination and requires clinical studies to confirm associations, reinforcing that screening infrastructure gaps are systemic not knowledge-based.

inbox/archive/health/2025-xx-pmc-glp1-psychiatric-disproportionality-faers-cvarod-daen.md

@@ -7,10 +7,13 @@ date: 2025-01-01
 domain: health
 secondary_domains: []
 format: paper
-status: unprocessed
+status: processed
+processed_by: vida
+processed_date: 2026-05-04
 priority: medium
 tags: [glp1, pharmacovigilance, eating-disorders, faers, disproportionality, psychiatric-adverse-events, cross-national]
 intake_tier: research-task
+extraction_model: "anthropic/claude-sonnet-4.5"
 ---
 
 ## Content