Plasma DNA: A Molecular Marker of Surgical Insult and Postoperative Recovery in Esophageal Cancer
Bibliographic record
Abstract
AIM: To assess plasma DNA changes intraoperatively, to relate plasma DNA to the magnitude of the surgical insult and to monitor the changes during the postoperative recovery period. MATERIAL AND METHOD: Prospective study of 35 patients with esophageal cancer who had esophagectomy of different magnitudes: 19 esophagectomy without thoracotomy and 16 esophagectomy with thoracotomy. The plasma DNA was measured prior to surgery, throughout the course of the operation on four different intervals, and on postoperative days 1, 3, 5, and 7. RESULTS: A significant difference was seen in the median plasma DNA intraoperatively between the two groups: esophagectomy without thoracotomy, 507 ng/ml/min (range 211-2,708), esophagectomy with thoracotomy, median 1,098 ng/ml/min (range 295-22,284; p = 0.014). Postoperative complications were identified in 6 patients who demonstrated a significant elevation in plasma DNA on postoperative days 5 and 7. CONCLUSION: Plasma DNA increases during surgery as a result of cell damage and the rise correlates with the magnitude of surgery. The descent of plasma DNA postoperatively correlates with surgical recovery. Elevation of the plasma DNA during the postoperative period correlates with postoperative complications. Plasma DNA is an objective molecular marker of surgical insult and can be used to monitor postoperative recovery after esophagectomy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".