Survey of the Use of Suction Drains in Head and Neck Surgery and Analysis of Their Biomechanical Properties
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
BACKGROUND: Closed suction drains have an important role in surgical wound healing. Although most surgeons use them routinely, indications for use and their postoperative management (emptying, removal) vary. The purpose of this study was to assess drain use by head and neck surgeons in Canada, to conduct a biomechanical analysis of the drains in a laboratory setting, and to make recommendations for drain use and management. METHODS: A survey was mailed to 343 active members of the Canadian Society of Otolaryngology. Three sets of experimental trials were conducted on the most commonly used drains to assess the effect of increased reservoir filling on suction generated through (1) incrementally increasing the amount of fluid within the reservoir, (2) compression of the reservoir with no fluid within, and (3) compression with the reservoirs while filled to 25% capacity with fluid. RESULTS: A 41% response rate was obtained. It was found that the majority of head and neck surgeons in Canada use Hemovac and Jackson-Pratt drainage systems routinely. There is considerable variability in practice with regard to drain emptying and timing of removal. Experimental results indicate that as filling of the reservoir increases, suction generated decreases sharply, to between 13 and 20% of initial values at 50% capacity. CONCLUSION: Postoperative drain management has important implications in surgical wound healing. Drain reservoirs should be monitored frequently to ensure adequate compression, particularly in the first 24 hours after insertion. Anticipated volume of drainage should dictate in part which reservoir is chosen. A larger reservoir is preferable in most cases. Drains should be removed promptly to decrease the risk of wound contamination.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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