Temporary Mechanical Circulatory Support in Cardiogenic Shock: Executive Summary of the Joint Consensus Reports of the PeriOperative Quality Initiative and the Enhanced Recovery After Surgery Cardiac Society
Bibliographic record
Abstract
BACKGROUND: The identification, triage, and management of cardiogenic shock (CS) are complex and resource intensive, particularly given the recent surge in the use of temporary mechanical circulatory support (tMCS) devices. This document is an executive summary of a series of consensus statements that guide the bedside clinician regarding the management of tMCS in the setting of CS. METHODS: The PeriOperative Quality Initiative (POQI) and Enhanced Recovery After Surgery (ERAS) Cardiac Society convened an interdisciplinary, international panel of experts and used a structured appraisal of the literature and the modified Delphi method to derive consensus on a series of topics related to both CS and tMCS. RESULTS: The effort resulted in 3 manuscripts with guidance related to the diagnosis, escalation or de-escalation, and best practices associated with CS and the provision of tMCS. Group consensus was derived around existing clinical questions, summary guidance statements, and the quality of the existing evidence. CONCLUSIONS: The POQI/ERAS cardiac consensus series derived 27 unique statements regarding the care of patients with CS and the provision of tMCS. Key themes emerged, including the need for immediate and systematic assessment of CS severity, early initiation of tMCS, an algorithmic approach to the escalation and de-escalation of tMCS therapies, and adoption of high-quality best practices associated with tMCS management.
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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 | 0.176 | 0.163 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".