Xolair® (omalizumab) enrollment in a tertiary care allergy and asthma clinic in Canada
Bibliographic record
Abstract
Xolair (omalizumab) has been approved in Canada since 2004 for the treatment of moderate to severe persistent allergic asthma in patients 12 years of age. The use of omalizumab in severe persistent allergic asthma may lead to decrease health care utilization through emergency room (ER) visits, hospitalizations, visits to health care providers, as well as, decrease the use of corticosteroids and improve the overall quality of life (QoL). Data collected from patient enrollment and QoL questionnaires completed at specific intervals during treatment with omalizumab at our large tertiary care clinic from 2004 to 2014 was analyzed. A steady number of patients were enrolled each year since 2004, showing its greatest increase in enrollment numbers since 2012. Our data indicates that the majority of patients improved with significantly less asthma exacerbation, less ER visits and hospitalizations, less use of inhaled and oral corticosteroids and better QoL. Omalizumab is effective in the treatment of moderate and severe allergic asthma. It improves QoL and reduces asthma exacerbations, ER visits and hospitalizations, and use of inhaled and oral corticosteroids.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".