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Record W4391729454 · doi:10.1111/echo.15766

Utility of apical four‐chamber longitudinal strain in the assessment of childhood cancer survivors: A multicenter study

2024· article· en· W4391729454 on OpenAlexaff
Matthew Mosgrove, Ritu Sachdeva, Kayla Stratton, Saro H. Armenian, Aarti Bhat, Kasey J. Leger, Christina J. Yang, Wendy M. Leisenring, Lillian R. Meacham, Karim Thomas Sadak, Shanti L. Narasimhan, Paul C. Nathan, Eric J. Chow, William L. Border

Bibliographic record

VenueEchocardiography · 2024
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Cancer Institute
KeywordsMedicineGold standard (test)PopulationNuclear medicineInternal medicineStandard errorLongitudinal studyLimits of agreementCardiologyStandard deviationPathologyStatisticsMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: A previous multicenter study showed that longitudinal changes in standard cardiac functional parameters were associated with the development of cardiomyopathy in childhood cancer survivors (CCS). Evaluation of the relationship between global longitudinal strain (GLS) changes and cardiomyopathy risk was limited, largely due to lack of quality apical 2- and 3-chamber views in addition to 4-chamber view. We sought to determine whether apical 4-chamber longitudinal strain (A4LS) alone can serve as a suitable surrogate for GLS in this population. METHODS: A4LS and GLS were measured in echocardiograms with acceptable apical 2-, 3-, and 4-chamber views. Correlation was evaluated using Pearson and Spearman coefficients, and agreement was evaluated with Bland-Altman plots. The ability of A4LS to identify normal and abnormal values compared to GLS as the reference was evaluated. RESULTS: Among a total of 632 reviewed echocardiograms, we identified 130 echocardiograms from 56 patients with adequate views (38% female; mean age at cancer diagnosis 8.3 years; mean follow-up 9.4 years). Correlation coefficients between A4LS and GLS were .89 (Pearson) and .85 (Spearman), with Bland-Altman plot of GLS-A4LS showing a mean difference of -.71 ± 1.8. Compared with GLS as the gold standard, A4LS had a sensitivity of 86% (95% CI 79%-93%) and specificity of 82% (69%-95%) when using normal range cutoffs and 90% (82%-97%) and 70% (58%-81%) when using ±2 standard deviations. CONCLUSION: A4LS performs well when compared with GLS in this population. Given the more recent adoption of apical 2- and 3-chamber views in most pediatric echocardiography laboratories, A4LS is a reasonable stand-alone measurement in retrospective analyses of older study cohorts and echocardiogram biorepositories.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.474

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.341
Teacher spread0.309 · 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.

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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