Mental health problems associated with idiopathic anaphylaxis
Bibliographic record
Abstract
BACKGROUND: Idiopathic Anaphylaxis (IA) is the most common anaphylactic syndrome in adults. Mental health problems associated with IA are not well recognised. We aimed to assess if patients diagnosed with IA were more likely to experience mental health problems compared to a normative Australian population. We additionally hypothesised that the number of anaphylactic episodes would correlate with symptoms of anxiety. METHODS: A total of 34 patients with at least one episode of IA were recruited from an adult immunology clinic. Patients were recruited as part of a separate study evaluating alternative aetiologies in IA. Mental health problems were measured using the Depression, Anxiety and Stress Scale (DASS-21). An extension of the survey included questions specifically focused on the psychological impact of IA. RESULTS: Compared to population norms, those with IA had significantly higher levels of mental health problems. Statistically significant DASS-21 scores were identified for depression 4.24 vs. 2.57 (p < 0.001), anxiety 4.76 vs. 1.74 (p < 0.012), stress 7.35 vs. 3.95 (p < 0.001) and total score 16.35 vs. 8.00 (p < 0.001). There was no association between two or more episodes of anaphylaxis and increased anxiety levels (β = 0.52, CI -2.59-3.62, p = 0.74). CONCLUSIONS: This is the first paper to demonstrate that patients living with idiopathic anaphylaxis are more symptomatic for mental illness than those in the community. Screening for mental illness and referral for psychological support should be undertaken in people with IA.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".