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Record W2560090805 · doi:10.1097/hco.0000000000000361

Chemotherapy-related cardiac dysfunction

2016· review· en· W2560090805 on OpenAlexaff
Rohit Moudgil, Haissam Haddad

Bibliographic record

VenueCurrent Opinion in Cardiology · 2016
Typereview
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineCardiac dysfunctionAnthracyclineIntensive care medicineChemotherapyCardiomyopathyTrastuzumabInternal medicineHeart failureCancerBreast cancer

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The main aim of this review is to address and challenge an old nomenclature of reversible versus irreversible chemotherapy-induced cardiomyopathy. RECENT FINDINGS: Chemotherapy-related cardiac dysfunction (CRCD) has been often characterized as type I or type II. Type I CRCD (e.g., anthracycline) represents a group of chemotherapeutic agents that has often been correlated with irreversible cardiac dysfunction. Conversely, type II CRCD (e.g., trastuzumab) represents a group of anticancer agents that has been considered as reversible. Recent evidence suggests that this nomenclature may not hold true, thus affecting clinical prognosis as well as timely management. It is prudent to address this concern so that physicians are armed with appropriate information, thus providing our oncological patients with informed care. The purpose is to highlight the grey area in this dichotomous classification. SUMMARY: Type I CRCD can be reversible if cardioprotective medications are administered in a timely manner. Conversely, a small proportion of type II CRCD may develop irreversible dysfunction and therefore, will require a long-term follow-up. Therefore, every case should be dealt on an individual basis and an appropriate prognosis should be given to patients based on the clinical evidence on hand.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.080
GPT teacher head0.392
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 teacher head, not a consensus.

Study designOther design
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

Citations8
Published2016
Admission routes1
Has abstractyes

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