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Record W3129034864 · doi:10.1093/ehjci/jeaa356.052

Early surveillance of anthracycline induced cardiotoxicity in children using echocardiography and biomarkers: A prospective study

2021· article· en· W3129034864 on OpenAlexafffund
Mariana L. Henry, M Esmaeilzadeh, Anne Christie, Emily Lam, J Wheately, Cheryl Fackoury, Cameron Slorach, Wei Hui, Emily Somerset, S. Fan, Paul C. Nathan, Luc Mertens

Bibliographic record

VenueEuropean Heart Journal - Cardiovascular Imaging · 2021
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsUniversity Health NetworkHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsAnthracyclineMedicineCardiotoxicityEjection fractionProspective cohort studyInternal medicineCardiologyTroponinTroponin IHeart failureCardiac function curveBiomarkerChemotherapyCancerBreast cancerMyocardial infarction

Abstract

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Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): CIHR Background Anthracyclines, which are commonly used in cancer treatment can induce myocardial damage, result in heart failure during treatment and have cardiac effects even decades after treatment. Monitoring of cardiotoxicity during treatment is largely based on the use of echocardiographic functional markers like ejection fraction and more recently myocardial strain imaging. Some studies have also looked at the utility of biomarkers like troponin and BNP. The utility of this surveillance strategy remains controversial as larger prospective studies are lacking. Purpose The aim of this study was to prospectively describe the impact of anthracycline treatment on echocardiographic functional parameters and cardiac biomarkers (high sensitivity troponin T and NT-Pro BNP) during the treatment period and twelve months after completion of treatment. In the current study we wanted to look at whether monitoring parameters during treatment were predictive of left ventricular function 12 months after treatment. Methods This was a prospective multi-centre nested case-control study of 256 children diagnosed with cancer requiring anthracycline therapy. Baseline functional echocardiographic parameters and cardiac biomarkers were obtained prior to starting anthracycline therapy, during the treatment protocol, and 12 months after treatment completion. Patients were assigned to one of two comparison groups based on the fractional shortening at the12-month echocardiogram: patients in group 1 had normal fractional shortening, (FS ³ 28%) while patients in group 2 had reduced fractional shortening (FS < 28%). Results A total of 917 echoes were performed, 376 of these occurred during the treatment period. FS was reduced in 27 (7%) of echoes obtained during the treatment period with 22 patients developing new onset dysfunction. Twelve months after treatment completion 232 patients had normal FS (Group 1), while 24 patients showed reduced FS (Group 2). Both groups had normal systolic function and cardiac biomarkers at baseline, however patients in group 2 were older at diagnosis (13.2 years (11.8-16) vs 6.5 years (3.4-13.2), p = 0.003) and received a higher cumulative anthracycline dose (200 mg/m2 (143-318) vs 125 mg/m2 (75-200), p= 0.005). One third (8/24) of patients in group 2 had at least 1 abnormal echo during the treatment period compared to 7% (16/232) in the normal group P < 0.001. The proportion of patients with at least one abnormal biomarker during this period however, was similar between groups. Conclusion(s) Patients receiving higher accumulative anthracycline doses and those with abnormal FS during the treatment period are at higher risk of having reduced cardiac function 12 months after treatment. High sensitivity troponin and NT-Pro BNP levels during the treatment period fail to discriminate patients at risk of developing early reduced systolic function. The relationship of these early results to long term cardiac function remains to be demonstrated.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.023
GPT teacher head0.284
Teacher spread0.262 · 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 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
Published2021
Admission routes2
Has abstractyes

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