Drug allergies in primary care practice in Romania: a questionnaire - based survey
Bibliographic record
Abstract
INTRODUCTION: Recent data from literature have shown many difficulties in managing allergic diseases in primary care in most countries and a consequently clear need for standardized educational programmes. Drug allergies represent an important medical issue for general practitioners (GPs) in Romania, though no national data about incidence, severity and management exist.The aim of our study was to evaluate epidemiological aspects of drug allergies in primary care practice in Bucharest, especially the diagnostic and therapeutic attitudes of family doctors and their need for education and training in this field of pathology. FINDINGS: A questionnaire with 21specific questions was addressed to 800 family doctors from Bucharest, either directly or via internet, with a response rate of 31,87%.The answers showed a significant interest of GPs in drug allergies, which are considered an increasing pathology. Almost half of the responders had never attended any form of education in allergology and 96% expressed a clear interest to participate in specialized educational programmes. We have noticed an underestimation of the severity of drug allergy, a surprisingly high percentage of allergy skin tests or blood tests recommended by GPs without specialist advice, and persistant confidence in alternative medicine. CONCLUSIONS: We concluded that the attitude towards and the competence regarding drug allergies of GPs in this study, as well as their collaboration with allergists, are not standardized and updated according to current guidelines. Further educational programs for GPs in drug allergies, based on standardized guidelines and national epidemiological studies for evaluation of drug allergy-related morbidity and mortality are needed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".