Right ventricular failure after left ventricular assist device insertion: preoperative risk factors
Bibliographic record
Abstract
Right ventricular failure after left ventricular assist device placement is the major concern on weaning from cardiopulmonary bypass and it is one of the most serious complications in the postoperative period. This complication has a poor prognosis and is generally unpredictable. The identification of pre-operative risk factor for this serious complication is incomplete yet. In order to determine pre-operative risk for severe right ventricular failure after left ventricular assist device support we analyzed preoperative hemodynamics, laboratory data and characteristics of 48 patients who received Novacor (World Heart Corp., Ottawa, ON, Canada). We compared the data from the patients who developed right ventricular failure and the patients who did not. Right ventricular failure occurred in 16% of the patients. There was no significant difference between the groups in demographic characteristics. We identified as preoperative risk factors the pre-operative low mean pulmonary artery and the impairment of hepatic and renal function on laboratory data. Our results confirm in part the findings of the few previous studies. This information may be useful for the patient selection for isolated left ventricular assist device implantation, but other studies are necessary before establishing criteria for patient selection for univentricular support universally accepted.
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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 | 0.002 |
| 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 | 0.001 |
| 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".