Factors contributing to non-compliance with on-demand treatment guidelines in hereditary angioedema
Bibliographic record
Abstract
BACKGROUND: Hereditary angioedema (HAE) is a rare genetic disorder characterized by painful and potentially life-threatening tissue swelling due to a deficiency or dysfunction of the C1 esterase inhibitor protein. Despite the availability of comprehensive on-demand treatment guidelines, compliance to guideline recommendations remains suboptimal, resulting in persisting unmet need. METHODS: This observational, online survey was conducted between September 6, 2022, and October 19, 2022 to understand the behaviors and perspectives of individuals in the US with hereditary angioedema (HAE). Participants were recruited by the US Hereditary Angioedema Association and were eligible if they were US residents with clinician-diagnosed HAE type I or II and had experienced at least one HAE attack. The survey included multiple-choice, rank-order, and scale-based responses using a 5-point Likert scale for agreement and an 11-point Likert scale for anxiety. Statistical analysis was performed using Microsoft Excel, summarizing continuous variables as means, medians, and ranges, and categorical variables as frequency distributions and percentages. RESULTS: A total of 107 out of 155 participants completed the survey (mean age = 41 years; 80.4% female). Half of the respondents used both prophylaxis and on-demand therapy, while the other half used on-demand therapy only. Icatibant was the most commonly used on-demand treatment (78.5%). The survey revealed that 57% of respondents did not treat all HAE attacks, and only 14% treated attacks immediately. Delays in treatment were common, with a mean time to treatment of 2.4 h, and younger patients were less likely to carry on-demand treatment. Reasons for delaying treatment included the perceived severity of the attack, lack of on-demand treatment availability, and pain associated with treatment. Additionally, 32.7% of respondents experienced the return of an HAE attack after initial treatment, with those delaying treatment more likely to experience recurrence. The survey also found that delayed treatment led to more severe attacks and longer recovery times, impacting work, social activities, and overall quality of life. CONCLUSIONS: Although guidelines recommend early treatment of HAE attacks, many respondents do not treat immediately. This finding underscores the importance of incorporating open patient-physician communication to improve guideline compliance and the management of HAE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".