Effect of intraoperative hypovolemic phlebotomy on transfusion and clinical outcomes in patients undergoing hepatectomy: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: There is no consensus on how to best achieve a low central venous pressure during hepatectomy for the purpose of reducing blood loss and red blood cell (RBC) transfusions. We analyzed the associations between intraoperative hypovolemic phlebotomy (IOHP), transfusions, and postoperative outcomes in cancer patients undergoing hepatectomy. METHODS: Using surgical and transfusion databases of patients who underwent hepatectomy for cancer at one institution (11 January 2011 to 22 June 2017), we retrospectively analyzed associations between IOHP and RBC transfusion on the day of surgery (primary outcome), and with total perioperative transfusions, intraoperative blood loss, and postoperative complications (secondary outcomes). We fitted logistic regression models by inverse probability of treatment weighting to adjust for confounders and reported adjusted odds ratio (aOR). RESULTS: There were 522 instances of IOHP performed during 683 hepatectomies, with a mean (standard deviation) volume of 396 (119) mL. The IOHP patients had a 6.9% transfusion risk on the day of surgery compared with 12.4% in non-IOHP patients (aOR, 0.53; 95% confidence interval [CI], 0.29 to 0.98; P = 0.04). Total perioperative RBC transfusion tended to be lower in IOHP patients compared with non-IOHP patients (14.9% vs 22.4%, respectively; aOR, 0.72; 95% CI, 0.44 to 1.16; P = 0.18). In patients with a predicted risk of ≥ 47.5% perioperative RBC transfusion, 24.6% were transfused when IOHP was used compared with 56.5% without IOHP. The incidence of severe postoperative complications (Clavien-Dindo scores ≥ 3) was similar in patients whether or not IOHP was performed (15% vs 16% respectively; aOR, 0.97; 95% CI, 0.53 to 1.54; P = 0.71). CONCLUSIONS: The use of IOHP during hepatectomy was associated with less RBCs transfused on the same day of surgery. Trials comparing IOHP with other techniques to reduce blood loss and transfusion are needed in liver surgery.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".