Ultrasonography-guided drainage versus surgical drainage for deep neck space abscesses: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Objective To compare ultrasonography-guided drainage versus conventional surgical incision and drainage in deep neck space abscesses. Methods The study was pre-registered on the National Institute of Health Research Prospective Register of Systematic Reviews (CRD42023466809) and adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Medline, Embase and Central databases were searched. Primary outcomes were length of hospital stay and recurrence. Heterogeneity and bias risk were assessed, and a fixed-effects model was applied. Results Of 646 screened articles, 7 studies enrolling 384 participants were included. Ultrasonography-guided drainage was associated with a significantly shorter hospital stay (mean difference = −2.31, p < 0.00001), but no statistically significant difference was noted in recurrence rate compared to incision and drainage (odds ratio = 2.02, p = 0.21). Ultrasonography-guided drainage appeared to be associated with cost savings and better cosmetic outcomes. Conclusion Ultrasonography-guided drainage was associated with a shorter hospital stay, making it a viable and perhaps more cost-effective alternative. More randomised trials with adequate outcomes reporting are recommended to optimise the available evidence.
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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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.024 | 0.030 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".