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Baseline left atrial reservoir strain provides independent and incremental prognostic value in predicting chemotherapy related cardiotoxicity

2022· article· en· W4306319354 on OpenAlexaff
Christopher Yu, Tomoko Negishi, Paaladinesh Thavendiranathan, Faraz Pathan, Martin Pěnička, M Cote, Richard J. Massey, S Miyazaki, Mitra Shirazi, Ciro Santoro, Dragoş Vinereanu, Wojciech Kosmala, L. Thomas, Thomas H. Marwick, Kazuaki Negishi

Bibliographic record

VenueEuropean Heart Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecUniversity of Toronto
Fundersnot available
KeywordsMedicineCardiotoxicityEjection fractionInternal medicineHazard ratioCardiologyAsymptomaticProportional hazards modelBreast cancerUnivariate analysisHeart failureSurgeryChemotherapyCancerConfidence intervalMultivariate analysis

Abstract

fetched live from OpenAlex

Abstract Background Currently, few baseline imaging biomarkers can predict chemotherapy induced cardiotoxicity (CTx). The early identification of CTx is critically important as it determines the prospect of LV function recovery (1). Purpose We aimed to determine if baseline left atrial (LA) reservoir strain (LAS) is predictive of CTx. Methods We performed retrospective analysis of the SUCCOUR study, an international multicentre randomized controlled trial. CTx was defined as an asymptomatic drop of >10% in left ventricular ejection fraction (LVEF) compared to baseline to <55%. LAS analysis was performed using semi-automated speckling tracking of the LA in the four and two chamber views using EchoPAC. Analysis was performed at one year follow up. Cox proportional hazard analysis, c-statistics and Akaike information criterion (AIC) statistical analysis was performed. Results After excluding 78 with inadequate images, 229 were included in the analysis. Most participants were female (n=215, 94%), with a mean age of 54±12 years. Median follow up was 1.02 years (IQR 0.98–1.07). A smoking history was the commonest cardiac risk factor (n=68, 30%). Breast cancer was the main cancer type (n=205, 90%). The mean baseline 3D LVEF, LV global longitudinal strain (GLS), LAS, and LA volume index (LAVI) were 61±4%, 20.6±2.5%, 28.6±7.9%, and 28±9ml/m2, respectively. Participants that developed CTx had a lower LAS at baseline compared to those that did not (25.5±7.4% vs 29.0±7.9% respectively; p=0.027). At 1-year follow-up, 29 patients (13%) developed CTx. On univariable Cox proportional hazard analysis, higher baseline LAS was associated with a lower risk of CTx (HR 0.95, 95% CI 0.90–0.99; p=0.026) but other parameters including baseline GLS was not (p=0.17). In nested Cox models (Figure 1), adding LAS significantly improved the model's predictive accuracy for CTx compared to other clinical and imaging parameters. When LAS was added to the same models it showed improvements in the c-statistics and AIC score (Figure 1). Conclusion Baseline LAS is an independent and incremental predictor of CTx. LAS could be used for baseline risk stratification in oncology patients who receive potentially cardiotoxic chemotherapy. Funding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): GE Healthcare

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.283
Teacher spread0.259 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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