New visions for anaphylaxis: an iPAC summary and future trends
Bibliographic record
Abstract
Anaphylaxis is an increasing emergency in Western countries, especially in children. In the last decade, efforts have been attempted to widely understand anaphylaxis from several angles but at present, there are still numerous issues to be clarified and tackled for its earlier identification. The discrepancies in the operational definitions and diagnostic criteria of anaphylaxis represent one of the most controversial issues in casting light upon its epidemiology. Furthermore, the lack of reliable markers of the disease hampers its diagnosis. Further basic and clinical research is urgently needed to confirm the recent promising results derived from studies on animal models, and to clarify the key role of selected mediators and markers in the different steps of the reaction, in its severity and in the recurrences. The underuse of adrenaline is another important issue, as available data demonstrate physicians' preference for steroids and anti-histamines despite the current lack of evidence of their effectiveness. In the near future, the management of anaphylaxis will be strongly influenced by the development of a stepwise approach, as well as by the creation of a system improving transmission of good quality data between the emergency room, the allergist and the family doctor. This process will certainly be enhanced by the establishment of a network of Centres of Excellence collaborating for high quality research and care and involved in the dissemination of new knowledge at a primary care level. This review will seek to briefly overview our current knowledge and highlight the key questions that need to be addressed in the next decade to improve clinical care to children and will focus on the epidemiology of anaphylaxis, the identification of individuals at risk of anaphylaxis, the special issues related to infants, community management of children at risk of anaphylaxis and school related issues.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".