Omalizumab Reduces Unplanned Healthcare Interactions in Irish Patients With Chronic Spontaneous Urticaria
Bibliographic record
Abstract
Chronic spontaneous urticaria (CSU) is a common, debilitating skin disorder associated with impaired quality of life and psychological comorbidity. Symptoms can be difficult to control and many individuals will not respond to first line treatment. Due to the chronic and unpredictable nature of the disorder, patients frequently have repeated healthcare attendances. Despite this, little is known about healthcare resource utilization internationally. Furthermore, there is no Irish data to inform fundholding decision makers. Omalizumab is an anti IgE monoclonal antibody used in refractory urticaria. It is a comparatively high cost medicine and access to this treatment can be challenging. Recent assessments of omalizumab compared with usual care suggest that omalizumab is a cost-effective treatment for refractory urticaria. We carried out a retrospective review of 47 patients commenced on omalizumab. We evaluated unplanned primary and secondary care attendances and urticaria symptomatology before and after treatment. As expected, patients with refractory disease that were commenced on omalizumab had objective improvements in urticaria symptoms. Importantly, we show that this is reflected in a dramatic reduction in unplanned healthcare interactions at primary care and emergency departments. These data suggest that omalizumab may benefit these patients by reducing disease activity and thereby reducing the need for unplanned healthcare interactions.
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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 | 0.001 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".