Surgical vs ultrasound-guided drainage of deep neck space abscesses: a randomized controlled trial: Surgical vs ultrasound drainage
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Deep neck space abscesses (DNAs) are relatively common otolaryngology-head and neck surgery emergencies and can result in significant morbidity with potential mortality. Traditionally, surgical incision and drainage (I&D) with antibiotics has been the mainstay of treatment. Some reports have suggested that ultrasound-guided drainage (USD) is a less invasive and effective alternative in select cases. OBJECTIVES: To compare I&D vs USD of well-defined DNAs, using a randomized controlled clinical trial design. The primary outcome measure was effectiveness (length of hospital stay (LOHS) and safety), and the secondary outcome measure was overall cost to the healthcare system. METHODS: Patients presenting to the University of Alberta Emergency Department with a well-defined deep neck space abscess were recruited in the study. Patients were randomized to surgical or US-guided drainage, placed on intravenous antibiotics and admitted with airway precautions. Following drainage with either intervention, abscess collections were cultured and drains were left in place until discharge. RESULTS: Seventeen patients were recruited in the study. We found a significant difference in mean LOHS between patients who underwent USD (3.1 days) vs I&D (5.2 days). We identified significant cost savings associated with USD with a 41% cost reduction in comparison to I&D. CONCLUSIONS: USD drainage of deep neck space abscesses in a certain patient population is effective, safe, and results in a significant cost savings to the healthcare system.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it