Antibiotics after incision and drainage for uncomplicated skin abscesses: a clinical practice guideline
Bibliographic record
Abstract
What role do antibiotics have in the treatment of uncomplicated skin abscesses after incision and drainage? A recent study suggested that, for small uncomplicated skin abscesses, antibiotics after incision and drainage improve the chance of short term cure compared with placebo. Triggered by this trial, the Rapid Recommendation team produced a new systematic review. Relying on this review and using the GRADE framework according to the BMJ Rapid Recommendation process, an expert panel makes a weak recommendation in favour of trimethoprim-sulfamethoxazole (TMP-SMX, co-trimoxazole) or clindamycin in addition to incision and drainage over incision and drainage alone. For patients who have chosen to initiate antibiotics, the panel issues a strong recommendation for TMP-SMX or clindamycin rather than a cephalosporin and a weak recommendation for TMP-SMX rather than clindamycin. Box 1 shows the articles and evidence linked to this Rapid Recommendation. The infographic presents the recommendations together with other pertinent information, including an overview of the absolute benefits and harms of candidate antibiotics in the standard GRADE format. The panel emphasises shared decision making in the choice of whether to initiate antibiotics and in which antibiotic to use, because the desirable and undesirable consequences are closely balanced: clinicians using MAGICapp ( http://magicapp.org/goto/guideline/jlRvQn/section/ER5RAn ) will find decision aids to support the discussion with patients. Table 2 below shows any evidence that has emerged since the publication of this article. ### What you need to know
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.009 |
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".