Are sequential compression devices routinely necessary following enhanced recovery after thoracic surgery?
Bibliographic record
Abstract
OBJECTIVES: The prominence of "enhanced recovery after surgery" (ERAS) protocols being adopted in thoracic surgery requires a re-evaluation of mechanical venous thromboembolism (VTE) prophylaxis guidelines. The goal of this study was to assess the role of sequential compression devices (SCD) in the prevention of VTEs such as deep vein thrombosis and pulmonary embolism (PE) in thoracic surgical patients. METHODS: We identified 200 patients who underwent elective oncological thoracic surgery between December 2018 and December 2020 in 2 cohorts-1 with SCDs and 1 without (i.e. non-SCD). All patients followed a standardized enhanced recovery after surgery (ERAS) protocol. The quality of care provided by SCDs was evaluated by the incidence and severity of postoperative and follow-up VTEs. Cohorts were compared by the Caprini score (CS) and the Charlson Comorbidity Index (CCI) with a two one-sided t-test analysis. Secondary outcomes include perioperative characteristics and follow-up data. RESULTS: Only 2 patients within the SCD group developed a PE with average CS and CCI metrics, both after hospital discharge and treated with anticoagulants, raising concern over the prophylactic nature of SCDs. The CS (6.9 ± 1.3 and 6.9 ± 1.5; P = 0.96) and the CCI (3.8 ± 2.0 and 4.1 ± 2.6; P = 0.33) for non-SCD and SCD, respectively, did not differ. The two one-sided t-test analysis for CS (P < 0.001) and CCI (P < 0.001) demonstrated equivalence. CONCLUSIONS: Although larger studies are required to confirm these results, routine SCD use may not be required when implementing ERAS protocols because clinically significant VTE rates were minimal.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".