Calculation of individual expected pleural drainage from total body lymph flow: a guide for fast-tracking removal of chest drains
Bibliographic record
Abstract
We read with great interest the recent original research article by Bjerregaard et al. [1]. By reporting pertinent 30-day outcomes for fast-track chest tube removal following video-assisted thoracoscopic (VATS) lobectomy with <500 ml in 24 h, this paper has the potential to change thoracic surgical practice regarding safe acceptable upper limits of pleural fluid drainage. As mentioned in the Discussion section on study limitations, we propose that it may be interesting for the authors to pursue their 24-h pleural fluid output data prior to chest tube removal. It is unclear how many of the analysed patients actually had pleural fluid drainage approaching the stated upper limit of 500 ml in 24 h. If they are not a majority, this might change the ultimate study conclusion, with implications for patient management. Understanding that the national database employed for this research limited the authors to providing data on ‘<500 ml in 24 h’, we would like to know if the authors consider it feasible to conduct an institutional level chart review on their reported cases with the following two goals: To determine the pleural fluid drainage in the 24 h prior to chest tube removal, and if there is a definable upper limit associated with the primary outcome of recurrent pleural effusion requiring intervention. To obtain basic patient anthropomorphic data to estimate maximal pleural drainage volumes, and to determine if there is an association with the primary outcome [2, 3]. To our knowledge, no previous studies on postoperative pleural drainage have assessed the relationship of calculated maximal pleural drainage volumes of individual patients to complications of recurrent pleural effusion. Instead of all-encompassing 24-h upper limits of pleural fluid drainage such as 500, 450, 400 or 300 ml set forth by previous authors [1, 4–6], it may be more appropriate to calculate the expected maximal daily pleural volume of individual patients to determine their safe upper limit for chest tube removal. The literature on pleural physiology informs us that these calculations are feasible and simple [2, 3]. This approach to expected pleural drainage is analogous to calculating an individual's appropriate IV fluid maintenance infusion rate based on anthropomorphic data. We congratulate the authors for their contribution to the thoracic surgical literature on fast-tracking removal of pleural drains.
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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 | 0.005 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.018 |
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".