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Record W3008757291 · doi:10.1136/heartjnl-2019-316297

Variability in echocardiography and MRI for detection of cancer therapy cardiotoxicity

2020· article· en· W3008757291 on OpenAlex
James A. Lambert, M. Lamacie, Babitha Thampinathan, Mustafa A. Altaha, Maryam Esmaeilzadeh, Mark Nolan, Camila Urzua Fresno, Emily Somerset, Eitan Amir, Thomas H. Marwick, Bernd J. Wintersperger, Paaladinesh Thavendiranathan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHeart · 2020
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsToronto General HospitalPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsMedicineCardiotoxicityRadiologyCancer therapyInternal medicineCardiologyCancerChemotherapy

Abstract

fetched live from OpenAlex

OBJECTIVES: To compare variability of echocardiographic and cardiovascular magnetic resonance (CMR) measured left ventricular (LV) function parameters and their relationship to cancer therapeutics-related cardiac dysfunction (CTRCD). METHODS: We prospectively recruited 60 participants (age: 49.8±11.6 years), 30 women with human epidermal growth factor receptor 2-positive breast cancer (15 with CTRCD and 15 without CTRCD) and 30 healthy volunteers. Patients were treated with anthracyclines and trastuzumab. Participants underwent three serial CMR (1.5T) and echocardiography studies at ~3-month intervals. Cine-CMR for LV ejection fraction (LVEF), myocardial tagging for global longitudinal strain (GLS) and global circumferential strain (GCS), two-dimensional (2D) echocardiography for strain and LVEF and three-dimensional (3D) echocardiography for LVEF measurements were obtained. Temporal, interobserver and intraobserver variability were calculated as the coefficient of variation and as the SE of the measurement (SEM). Minimal detected difference (MDD) was defined as 2xSEM. RESULTS: Patients with CTRCD demonstrated larger mean temporal changes in all parameters compared with those without: 2D-LVEF: 4.6% versus 2.8%; 3D-LVEF: 5.2% vs 2.3%; CMR-LVEF: 6.6% versus 2.7%; 2D-GLS: 1.9% versus 0.7%, 2D-GCS: 2.5% versus 2.2%; CMR-GCS: 2.7% versus 1.6%; and CMR-GLS: 2.1% versus 1.4%, with overlap in 95% CI for 2D-LVEF, 2D-GCS, CMR-GLS and CMR-GCS. The respective mean temporal variability/MDD in healthy volunteers were 3.3%/6.5%, 1.8%/3.7%, 2.2%/4.4%, 0.8%/1.5%, 1.9%/3.7%, 1.8%/3.6% and 1.4%/2.8%. Although the mean temporal variability in healthy volunteers was lower than the mean temporal changes in CTRCD, at the individual level, 2D-GLS, 3D-LVEF and CMR-LVEF had the least overlap. 2D-GLS and CMR-LVEF had the lowest interobserver/intraobserver variabilities. CONCLUSION: Temporal changes in 3D-LVEF, 2D-GLS and CMR LVEF in patients with CTRCD had the least overlap with the variability in healthy volunteers; however, 2D-GLS appears to be the most suitable for clinical application in individual patients.

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.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.297
Teacher spread0.271 · 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