Best Management Practices on Temporary Mechanical Circulatory Support: Joint Consensus Report of the PeriOperative Quality Initiative and the Enhanced Recovery After Surgery Cardiac Society
Bibliographic record
Abstract
BACKGROUND: Effective use of temporary mechanical circulatory support (tMCS) mandates a multifaceted understanding of patient physiology, device technology, procedural techniques, patient-device interactions, and interdisciplinary collaboration. The consensus statement presented here endeavors to provide clinicians with a practical roadmap incorporating evidence-based best practices in several key areas that delineate the initial priorities in mechanical ventilation, anticoagulation, sedation, and monitoring for patients requiring tMCS. METHODS: With an interdisciplinary, international group of clinicians and through a structured literature review, a modified Delphi method was used to achieve consensus on best practices in tMCS. RESULTS: Nine key questions were developed with accompanying statements to direct areas that institutions and providers should prioritize to optimize care. These questions included: What expertise is required within the interdisciplinary team to optimize patient care? How should medical centers facilitate escalation of care when indicated? What is the optimal ventilation management strategy? What are the recommended gas exchange targets to preserve end-organ function? What is the recommended timing to start or resume anticoagulation? What anticoagulation agent and monitoring approach should be used routinely? What is the optimal strategy for patient comfort and device interactions? Can a patient on tMCS be mobilized? What routine monitoring needs to be performed? CONCLUSIONS: A comprehensive review is provided of key management strategies incorporating interdisciplinary team and evidence-based medical knowledge to improve patient outcomes while using tMCS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".