Penicillin allergy SHACK : Survey of hospital and community knowledge
Bibliographic record
Abstract
Aim \n \nPenicillin allergy accounts for the majority of all reported adverse drug reactions in adults and children. Foregoing first-line antibiotic therapy due to penicillin allergy label is associated with an increased prevalence of infections by resistant organisms and longer hospitalisation. Clinician awareness of allergy assessment, referral indications, management of allergy and anaphylaxis is therefore vital but globally lacking. We aim to assess the knowledge of penicillin allergy, assessment and management in Western Australian health professionals. \n \nMethods \n \nAn anonymous survey was distributed to pharmacists, nurses and physicians within Western Australian paediatric and adult Hospitals, Community and General Practice. \n \nResults \n \nIn total, 487/611 were completed and included in the statistical analysis. Only 62% (301/487) of respondents routinely assessed for patient medication allergies. Of those who assessed allergy, 9% (28/301) of respondents met the Australian standards for allergy assessment. Only 22% (106/487) of participants correctly cited all indications for management with adrenaline in anaphylaxis to antibiotics and 67% (197/292) of physicians rarely or never referred to an allergy service. Paediatric clinicians had an increased understanding of allergy assessment and anaphylaxis management. Recent penicillin allergy education within a 5-year period led to significant improvements in allergy knowledge. \n \nConclusion \n \nOverall, knowledge, assessment and management of penicillin allergies among practitioners in Western Australia are currently inadequate in adults and paediatric clinicians to provide safe and effective clinical care. The implementation of a targeted education program for WA health professionals is urgently required and is expected to improve clinician knowledge and aid standardised penicillin assessment (de-labelling) practices.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".