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Record W4406655232 · doi:10.1016/j.jaccao.2024.06.006

Cardiovascular Considerations After Cancer Therapy

2025· review· en· W4406655232 on OpenAlexaff
Anne Blaes, Anju Nohria, Saro H. Armenian, Carmen Bergom, Paaladinesh Thavendiranathan, Ana Barac, Gabriela Sanchez‐Petitto, Sanjal Desai, Leah L. Zullig, Amee Morgans, Joerg Herrmann

Bibliographic record

VenueJACC CardioOncology · 2025
Typereview
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsTed Rogers Centre for Heart Research
Fundersnot available
KeywordsCancerMedicineCancer therapyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Cancer survivors, particularly those treated with anthracyclines and chest radiation, face an elevated risk of cancer therapy-related cardiovascular toxicity. These complications affect not only physical health, but also life expectancy. Risk factors for cancer therapy-related cardiovascular toxicity include age at which cancer treatment was received, the use of (potentially) cardiotoxic cancer therapies, and the presence of concomitant cardiovascular risk factors. Current guidelines provide recommendations for cardiovascular surveillance after cancer therapy, including type and frequency. All cancer survivors are advised to undergo annual clinical screenings and optimization of cardiovascular risk factors. Those at higher risk should undergo additional cardiovascular testing. This document aims to summarize the available evidence, present practical recommendations, and outline existent gaps in the current literature regarding cardiovascular care after cancer therapies.

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)0.002
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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
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 head0.065
GPT teacher head0.376
Teacher spread0.311 · 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

Citations43
Published2025
Admission routes1
Has abstractyes

Explore more

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