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Record W4411532565 · doi:10.1002/ccd.31698

Personalizing Mechanical Circulatory Support for Cardiogenic Shock: A Review and Comparison of Current Devices

2025· review· en· W4411532565 on OpenAlexaff
Bradley Fujiuchi, Kevin Benavente, Hafeez Ul Hassan Virk, Mahboob Alam, Jacob C. Jentzer, Ryan J. Tedford, Sean van Diepen, Chayakrit Krittanawong

Bibliographic record

VenueCatheterization and Cardiovascular Interventions · 2025
Typereview
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCardiogenic shockMedicineCirculatory systemIntensive care medicineMyocardial infarctionCardiologyImpellaInternal medicinePopulationHeart failureVentricular assist deviceShock (circulatory)

Abstract

fetched live from OpenAlex

Cardiogenic shock (CS) remains a high morbidity and mortality condition worldwide frequently complicating acute myocardial infarction (AMI) and decompensated heart failure (HF). Within the management of CS, mechanical circulatory support (MCS) devices play a critical role in maintaining hemodynamic stability, preserving end-organ perfusion and bridging patients through to recovery, implantation of durable support or transplantation. Despite their use, optimal timing of initiation, as well as patient and device selection remain unclear. This review explores the current landscape of MCS devices, surrounding evidence and key distinctions between devices. With increasing acknowledgment for the heterogeneity of CS, understanding the strengths and limitations of each device remains crucial to improving outcomes in this high-risk population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.089
GPT teacher head0.362
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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