Recommendations for antibiotic prescriptions for upper respiratory symptoms in children in Trinidad and Tobago: GRADE-ADOLOPMENT APPROACH
Bibliographic record
Abstract
Background: In Trinidad and Tobago, 22,329 and 18,594 cases of acute respiratory infections (ARI) in children less than 5 years were recorded for 2016 and 2017 respectively. Often, antimicrobials are over prescribed without proof of bacterial infection. Recommendations for management of ARIs are needed. Methods: The GRADE-ADOLOPMENT approach was used to formulate recommendations. We established a guideline panel who met in person or by web conferences. We prioritised recommendation questions and searched for guidelines and systematic reviews from 2010 to July 2018 in several medical databases and guideline producer websites. We also searched for patients’ values and preferences, acceptability, resources, and feasibility studies specific to the Caribbean or Trinidad and Tobago. We summarised the evidence in evidence-to-decision frameworks and formulated recommendations by consensus. Results: The guideline panel developed recommendations including: 1. For children 5 years old or younger who present with fever and respiratory symptoms not suggestive of serious illness, we recommend to either not prescribe antibiotics or to provide a delayed prescription (48 hours later) of amoxicillin or clarithromycin (when children have a history of allergy to penicillin) rather than an immediate prescription; 2. For children with symptoms suggestive of serious illness, we recommend immediate prescription of amoxicillin or clarithromycin (when children have a history of allergy to penicillin); and, 3. We suggest 7-10 days of treatment, depending on the suspected illness and antibiotic used. Conclusion: Guidelines aid medical practitioners, patients and supply chain managers. This guideline will form the backbone of the 1st national standardisation of treatment using the GRADE-ADOLOPMENT approach.
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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 | 0.048 | 0.132 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.014 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".