Intraoperative measurement of the respiratory exchange ratio predicts postoperative complications after liver transplantation
Bibliographic record
Abstract
Abstract Background During surgery, any mismatch between oxygen delivery (DO2) and consumption (VO2) can promote the development of postoperative complications. The respiratory exchange ratio (RER), defined as the ratio of carbon dioxide (CO2) production (VCO2) to VO2, may be a useful noninvasive tool for detecting inadequate DO2. The primary objective of this study was to test the hypothesis that RER measured during liver transplantation may predict postoperative morbidity. Secondary objectives were to assess the ability of other variables used to assess the DO2/VO2 relationship, including arterial lactate, mixed venous oxygen saturation, and veno-arterial difference in the partial pressure of carbon dioxide (VAPCO2gap), to predict postoperative complications. Methods This retrospective study included consecutive adult patients who underwent liver transplantation for end stage liver disease from June 27th, 2020, to September 5th, 2021. Patients with acute liver failure were excluded. All patients were routinely equipped with a pulmonary artery catheter. The primary analysis was a receiver operating characteristic (ROC) curve constructed to investigate the discriminative ability of the mean RER measured during surgery to predict postoperative complications. RER was calculated at five standardized time points during the surgery, at the same time as measurement of blood lactate levels and arterial and mixed venous blood gases, which were compared as a secondary analysis. Results Of the 115 patients included, 57 developed at least one postoperative complication. The mean RER (median [25–75] percentiles) during surgery was significantly higher in patients with complications than in those without (1.04[0.96–1.12] vs 0.88[0.84–0.94]; p < 0.001). The area under the ROC curve was 0.87 (95%CI: 0.80–0.93; p < 0.001) with a RER value (Youden index) of 0.92 giving a sensitivity of 91% and a specificity of 74% for predicting the occurrence of postoperative complications. The RER outperformed all other measured variables assessing the DO2/VO2 relationship (arterial lactate, SvO2, and VAPCO2gap) in predicting postoperative complications. Conclusion During liver transplantation, the RER can reliably predict postoperative complications. Implementing this measure intraoperatively may provide a warning for physicians of impending complications and justify more aggressive optimization of oxygen delivery. Further studies are required to determine whether correcting the RER is feasible and could reduce the incidence of complications.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".