The incidence of postoperative vasopressor usage, a prospective international observational study: ‘SQUEEZE’
Bibliographic record
Abstract
Abstract Background: Postoperative hypotension is common after major non-cardiac surgery, due predominantly to vasodilatation. Administration of infused vasopressors postoperatively may often be considered a surrogate indicator of vasodilatation. The incidence of postoperative vasopressors and outcomes associated with their use has never been described. We hypothesise that there is variation across centres in using vasopressors after surgery. There may also be a variation in the incidence of organ dysfunction, organ support use, and clinical outcomes in patients treated with postoperative vasopressor therapy. Method: The primary objective of this study is to determine what proportion of patients receive postoperative vasopressor infusions. We will identify factors in variation of care (patient, condition, surgery, and intraoperative management) associated with the receipt of postoperative vasopressor infusions. We will also assess the incidence of associated organ dysfunction and clinical outcomes among those who receive vasopressors. This will be accomplished with a prospective, international, multicentre cohort study that includes all adult (≥18 years) non-cardiac surgical patients in participating centres. Patients undergoing cardiac, obstetric or day-case surgery will be excluded. We will recruit two cohorts of patients: Cohort A will include all eligible patients admitted to participating hospitals for seven consecutive days. Cohort B will include 30 sequential patients per hospital, with the single additional inclusion criterion of postoperative vasopressor usage. We expect to collect data on approximately 40,000 patients for cohort A and 12,800 patients for cohort B. Discussion: While in cardiac surgery, clinical trials have informed the choice of vasopressors used to treat postoperative vasoplegia, there remains equipoise over the best approach in non-cardiac surgery. Our study will represent the first large-scale assessment of the use of vasopressors after non-cardiac surgery. These data will inform future studies, including trials of different vasopressors and potential management options to improve outcomes and reduce resource use after surgery. Trial registration: ClinicalTrials.gov Identifier: NCT03805230, 15th January 2019
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".