Surgeon Preferences Worldwide in Wound Drain Utilization in Open Lumbar Fusion Surgery for Degenerative Pathologies
Bibliographic record
Abstract
Study Design Cross-sectional survey. Objective Although literature does not recommend routine wound drain utilization, there is a disconnect between the evidence and clinical practice. This study aims to explore into this controversy and analyze the surgeon preferences related to drain utilization, and the factors influencing drain use and criterion for removal. Methods A survey was distributed to AO Spine members worldwide. Surgeon demographics and factors related to peri-operative drain use in 1 or 2-level open fusion surgery for lumbar degenerative pathologies were collected. Multivariate analyses by drain utilization, and criterion of removal were conducted. Results 231 surgeons participated, including 220 males (95.2%), orthopedics (178, 77.1%), and academic/university-affiliated (114, 49.4%). Most surgeons preferred drain use (186, 80.5%) and subfascial drains (169, 73.2%). Drains were removed based on duration by 52.87% of the surgeons, but 27.7% removed drains based on outputs. On multivariable analysis, significant predictors of drain use were surgeon’s aged 35-44 (OR = 11.9, 95% CI = 1.2-117.2, P = .034), 45-54 (29.1, 3.1-269.6, P = .003), 55-64 (8.9, 1.4-56.5, .019), and wound closure using coaptive films (6.0, 1.2-29.0, P = .025). Additionally, surgeons from Asia Pacific (OR = 5.19, 95% CI = 1.65-16.38, P = .005), Europe (3.55, 1.22-10.31, P = .020), and Latin America (4.40, 1.09-17.83, .038) were more likely to remove drain based on time duration, but surgeons <5 years of experience (10.23, 1.75-59.71, P = .010) were more likely to remove drains based on outputs. Conclusions Most spine surgeons worldwide prefer to place a subfascial wound drain for degenerative open lumbar surgery. The choice for drain placement is associated with the surgeon’s age and use of coaptive films for wound closure, while the criterion for drain removal is associated with the surgeons’ region of practice and experience.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".