Escalation and De-escalation of Temporary Mechanical Circulatory Support: Joint Consensus Report of the PeriOperative Quality Initiative and the Enhanced Recovery After Surgery Cardiac Society
Bibliographic record
Abstract
BACKGROUND: Temporary mechanical circulatory support (tMCS) for cardiogenic shock (CS) is increasing despite knowledge gaps and variations in management practices. This document was created to provide clinicians with guidance regarding initiation, escalation, and de-escalation of tMCS in patients with CS. METHODS: An interdisciplinary, international expert panel using a structured literature appraisal and modified Delphi method derived consensus statements regarding triggers for prompt patient assessment and initiating tMCS in CS, assessing adequacy of support, readiness for tMCS weaning, and next steps in nonrecovery. Individual statements were graded on the basis of the quality of available evidence. RESULTS: The panel addressed 4 main questions aimed at initiation, escalation, and de-escalation of tMCS. On the basis of available literature review and expert consensus, 11 recommendations were formulated. Key principles included recognition of the need for patients with CS who have ongoing hemodynamic compromise, tissue hypoperfusion, and metabolic derangements to be considered for early tMCS initiation. An interdisciplinary shock team should be involved in management, with early referral when patient conditions require care beyond center capabilities. Discussions providing anticipatory guidance should be performed with patients and decision makers before initiating tMCS. Management of tMCS involves frequent, timely hemodynamic and tissue perfusion reassessments to determine the need for escalation or weaning. For patients unable to be weaned from tMCS, evaluation should include interdisciplinary assessment for advanced therapies, with palliation included as a consideration in care discussions. CONCLUSIONS: A practical guide to initiation, escalation, and de-escalation of tMCS is provided. Center-specific approaches that are based on local capabilities should be implemented.
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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 | 0.216 | 0.190 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| 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".