Abstract 087: Postdiagnostic Anxiety and Depression Increase Rupture Risk but Reduce Preventive Treatment in Unruptured Intracranial Aneurysms: A Multi‐national Multi‐institutional Study
Bibliographic record
Abstract
Background and Purpose The impact of postdiagnostic development of anxiety and depression on management decisions and outcomes in patients with unruptured intracranial aneurysms (UIAs) is underexplored, despite their high prevalence. We aimed to assess the relationship between these conditions and treatment choices, rupture rates, mortality, and healthcare utilization using a large, multi‐institutional database. Methods This retrospective cohort study utilized electronic health records from the TriNetX Global Collaborative Network (2015‐2025) to identify adult patients (18‐80 years) with documented UIAs. We created two cohorts based on presence/absence of anxiety and/or depression diagnoses developing after unruptured aneurysm diagnosis but before rupture events, excluding patients with pre‐existing psychiatric conditions or post‐rupture symptoms. We conducted 1:1 propensity score matching based on demographics (age, sex, race/ethnicity), comorbidities (hypertension, diabetes, hyperlipidemia, obesity, smoking), and neuroimaging patterns (CT, CTA, MRA). Primary outcomes included endovascular treatment rates, aneurysm rupture, all‐cause mortality, and psychiatric medication utilization. Secondary analyses examined medication adherence (proportion of days covered), specific psychiatric diagnoses, medication classes, treatment timing, and healthcare utilization patterns. Statistical methods included Kaplan‐Meier survival analysis, Cox proportional hazards regression, and multivariable modeling with subgroup analyses by diagnosis type, comorbidity burden, and medication adherence levels. Results After propensity score matching, 14,915 patient pairs were included with balanced baseline characteristics. Patients with anxiety/depression had significantly higher endovascular treatment rates (4.8% vs. 4.1%, P=0.016), aneurysm rupture (3.8% vs. 2.5%, P<0.001), and all‐cause mortality (8.1% vs. 5.1%, P<0.001) over median follow‐up of 1,045 vs. 579 days. Despite 52% higher rupture rates, psychiatric patients received less preventive treatment (1.6% vs. 2.0%, P<0.05), though equivalent emergency treatment rates (85% both groups). Multivariable Cox regression confirmed anxiety/depression as independent mortality predictor (HR 1.31, 95% CI 1.19‐1.43). Clear dose‐response relationships emerged between medication adherence and mortality: low adherence (HR 1.56, 95% CI 1.30‐1.87), moderate adherence (HR 1.34, 95% CI 1.12‐1.60), high adherence (HR 1.18, 95% CI 1.01‐1.38). Mortality risk varied by diagnosis: major depressive disorder (HR 1.38, 95% CI 1.19‐1.60), mixed anxiety/depression (HR 1.36, 95% CI 1.15‐1.61), generalized anxiety disorder (HR 1.25, 95% CI 1.08‐1.44). Benzodiazepine users had highest mortality risk (HR 1.45, 95% CI 1.20‐1.75) versus SSRIs (HR 1.18, 95% CI 0.98‐1.42, non‐significant). Treatment delays were longer (median 136 vs. 98 days, P=0.003). Healthcare utilization increased substantially: hospitalizations (26.0% vs. 19.0%, OR 1.50), emergency visits (38.0% vs. 29.0%, OR 1.49), annual outpatient visits (12.6 vs. 8.4, difference 4.2). Psychiatric medication utilization was 58.1% vs. 17.7% (RR 3.28). Sensitivity analyses with alternative matching methods confirmed robustness of findings. Conclusion Anxiety and depression developing after UIA diagnosis significantly increase rupture risk and mortality. Despite elevated risk, these patients receive less preventive treatment, highlighting critical management gaps. Findings underscore the need for integrated psychiatric care, systematic mental health screening, and improved preventive treatment access in UIA management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".