COVID‐19 pandemic: Practical considerations on the organization of an allergy clinic—An EAACI/ARIA Position Paper
Bibliographic record
Abstract
BACKGROUND: The coronavirus disease 2019 (COVID-19) has evolved into a pandemic infectious disease transmitted by the severe acute respiratory syndrome coronavirus (SARS-CoV-2). Allergists and other healthcare providers (HCPs) in the field of allergies and associated airway diseases are on the front line, taking care of patients potentially infected with SARS-CoV-2. Hence, strategies and practices to minimize risks of infection for both HCPs and treated patients have to be developed and followed by allergy clinics. METHOD: The scientific information on COVID-19 was analysed by a literature search in MEDLINE, PubMed, the National and International Guidelines from the European Academy of Allergy and Clinical Immunology (EAACI), the Cochrane Library, and the internet. RESULTS: Based on the diagnostic and treatment standards developed by EAACI, on international information regarding COVID-19, on guidelines of the World Health Organization (WHO) and other international organizations, and on previous experience, a panel of experts including clinicians, psychologists, IT experts, and basic scientists along with EAACI and the "Allergic Rhinitis and its Impact on Asthma (ARIA)" initiative have developed recommendations for the optimal management of allergy clinics during the current COVID-19 pandemic. These recommendations are grouped into nine sections on different relevant aspects for the care of patients with allergies. CONCLUSIONS: This international Position Paper provides recommendations on operational plans and procedures to maintain high standards in the daily clinical care of allergic patients while ensuring the necessary safety measures in the current COVID-19 pandemic.
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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 | 0.114 | 0.140 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.019 | 0.022 |
| Open science | 0.009 | 0.009 |
| Research integrity | 0.036 | 0.025 |
| Insufficient payload (model declined to judge) | 0.019 | 0.011 |
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".