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Record W4410520456 · doi:10.3390/jpm15050207

Point of View: A Holistic Four-Interface Conceptual Model for Personalizing Shock Resuscitation

2025· review· en· W4410520456 on OpenAlexaff
Philippe Rola, Eduardo Kattan, Matthew Siuba, Korbin Haycock, Sara Crager, Rory Spiegel, Maxwell A. Hockstein, Vimal Bhardwaj, Ashley Miller, Jon‐Émile S. Kenny, Gustavo A. Ospina‐Tascón, Glenn Hernández

Bibliographic record

VenueJournal of Personalized Medicine · 2025
Typereview
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsHealth Sciences NorthUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal
Fundersnot available
KeywordsShock (circulatory)ResuscitationMedicineVentricleIntensive care medicinePulmonary arteryHemodynamicsCardiologyComputer scienceInternal medicineSurgery

Abstract

fetched live from OpenAlex

The resuscitation of a patient in shock is a highly complex endeavor that should go beyond normalizing mean arterial pressure and protocolized fluid loading. We propose a holistic, four-interface conceptual model of shock that we believe can benefit both clinicians at the bedside and researchers. The four circulatory interfaces whose uncoupling results in shock are as follows: the left ventricle to arterial, the arterial to capillary, the capillary to venular, and finally the right ventricle to pulmonary artery. We review the pathophysiology and clinical consequences behind the uncoupling of these interfaces, as well as how to assess them, and propose a strategy for approaching a patient in shock. Bedside assessment of shock may include these critical interfaces in order to avoid hemodynamic incoherence and to focus on microcirculatory restoration rather than simply mean arterial pressure. The purpose of this model is to serve as a mental model for learners as well as a framework for further resuscitation research that incorporates these concepts.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.660
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.128
GPT teacher head0.420
Teacher spread0.292 · 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 teacher head, not a consensus.

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

Citations7
Published2025
Admission routes1
Has abstractyes

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