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Record W4413011619 · doi:10.1016/j.jacadv.2025.102037

Caring for Two

2025· review· en· W4413011619 on OpenAlexaff
Mena Gewarges, Andrew Cao, Konstantinos Alexopoulos, Maha Al-Mandhari, Filio Billia, Danielle Massarella, Marina Vainder, Candice Silversides, Stephen E. Lapinsky, Adriana Luk

Bibliographic record

VenueJACC Advances · 2025
Typereview
Languageen
FieldMedicine
TopicCardiovascular Issues in Pregnancy
Canadian institutionsMount Sinai HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Critical cardiac illness in the setting of pregnancy presents a unique and complex challenge requiring multidisciplinary expertise and coordination. Physiologic changes of pregnancy can unmask or exacerbate underlying cardiac disease, placing both patient and fetus at significant risk. This review provides a comprehensive approach to the management of critically ill pregnant individuals with cardiac disease within the cardiac intensive care unit. We discuss the nuances of hemodynamic monitoring, mechanical ventilation strategies, and pharmacotherapy tailored to the pregnant state. Special emphasis is placed on cardiac arrest management, as well as the diagnosis and treatment of acute cardiac conditions such as acute coronary syndromes, heart failure, cardiogenic shock, and valvular heart disease. Practical considerations for fetal monitoring, delivery planning, and postpartum care are also highlighted. This review aims to equip cardiac intensivists, obstetricians, anesthesiologists, and maternal-fetal medicine specialists with evidence-based strategies to optimize outcomes for both pregnant individual and fetus.

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)0.006
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 score0.024
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0240.005

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 head0.037
GPT teacher head0.415
Teacher spread0.378 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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