Phlebotomy resulting in controlled hypovolaemia to prevent blood loss in major hepatic resections (PRICE-1): a pilot randomized clinical trial for feasibility
Bibliographic record
Abstract
BACKGROUND: Major liver resection is associated with blood loss and transfusion. Observational data suggest that hypovolaemic phlebotomy can reduce these risks. This feasibility RCT compared hypovolaemic phlebotomy with the standard of care, to inform a future multicentre trial. METHODS: Patients undergoing major liver resections were enrolled between June 2016 and January 2018. Randomization was done during surgery and the surgeons were blinded to the group allocation. For hypovolaemic phlebotomy, 7-10 ml per kg whole blood was removed, without intravenous fluid replacement. Co-primary outcomes were feasibility and estimated blood loss (EBL). RESULTS: A total of 62 patients were randomized to hypovolaemic phlebotomy (31) or standard care (31), at a rate of 3·1 patients per month, thus meeting the co-primary feasibility endpoint. The median EBL difference was -111 ml (P = 0·456). Among patients at high risk of transfusion, the median EBL difference was -448 ml (P = 0·069). Secondary feasibility endpoints were met: enrolment, blinding and target phlebotomy (mean(s.d.) 7·6(1·9) ml per kg). Blinded surgeons perceived that parenchymal resection was easier with hypovolaemic phlebotomy than standard care (16 of 31 versus 10 of 31 respectively), and guessed that hypovolaemic phlebotomy was being used with an accuracy of 65 per cent (20 of 31). There was no significant difference in overall complications (10 of 31 versus 15 of 31 patients), major complications or transfusion. Among those at high risk, transfusion was required in two of 15 versus three of nine patients (P = 0·326). CONCLUSION: Endpoints were met successfully, but no difference in EBL was found in this feasibility study. A multicentre trial (PRICE-2) powered to identify a difference in perioperative blood transfusion is justified. Registration number: NCT02548910 ( http://www.clinicaltrials.gov).
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".