Gaps in anaphylaxis management at the level of physicians, patients, and the community: a systematic review of the literature
Bibliographic record
Abstract
Diagnosis and management of anaphylaxis can be a challenge because reactions are often unexpected and progress quickly. The focus of anaphylaxis management has mostly been on the acute episode, with little attention given to the long-term management of patients at risk. This is compounded by conflicting information in current guidelines and a general lack of agreement among clinicians about which management strategies are the most appropriate. We systematically reviewed the literature to identify and summarize studies that investigated gaps in anaphylaxis management. Our search included MEDLINE, EMBASE, CINAHL, and Evidence-Based Medicine Reviews. Studies were included if they addressed an outcome describing gaps in anaphylaxis knowledge, education, anaphylaxis management, and quality of life (QOL). Populations of interest were health care professionals involved in the care of patients at risk for anaphylaxis, and patients of any age, their parents, caregivers, and teachers in primary care, hospital or community settings. Of 5014 citations that were identified, the final 59 studies (selected from 75 full-text articles) met the inclusion criteria. Two hundred and two gaps were identified and classified according to major themes: gaps in knowledge and anaphylaxis management (physicians and patients); gaps in follow-up care (physicians); and QOL of patients and caregivers. Findings from this systematic review revealed gaps in anaphylaxis management at the level of physicians, patients, and the community. Findings will be used to provide a basis for developing interventional strategies to help address these deficiencies.
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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 | 0.016 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.018 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".