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<i>Z</i> Scores for Pediatric Echocardiography Dimensions Adjusted for Body Size, BMI, and Age

2025· article· en· W4412110105 on OpenAlexaffabout
Jonathan Lauzon-Schnittka, Virginie Plante, Nagib Dahdah, Steven C. Greenway, Christian Drolet, Kenny K. Wong, Andrew S. Mackie, Luc Mertens, Tíscar Cavallé-Garrido, Joshua Penslar, Derek Wong, Luis Martín Garrido‐García, Frédéric Dallaire

Bibliographic record

VenueCirculation Cardiovascular Imaging · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsChildren's Hospital of Eastern OntarioHospital for Sick ChildrenUniversity of AlbertaCentre Hospitalier Universitaire Sainte-JustineDalhousie UniversityLibin Cardiovascular Institute of AlbertaIzaak Walton Killam Health CentreAlberta Children's HospitalQueen's UniversityMontreal Children's HospitalCentre hospitalier universitaire de QuébecCentre Hospitalier Universitaire de Sherbrooke
Fundersnot available
KeywordsMedicineBody surface areaBody mass indexConfoundingOverweightCardiologyStandard scoreSample size determinationMass indexInternal medicinePediatricsStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: Cardiovascular dimensions measured during pediatric echocardiograms must be normalized for body size. However, other variables may confound their interpretation, such as age and abnormal body habitus. This retrospective cross-sectional study of the Canadian Congenital and Pediatric Cardiology Research Network aimed to create Z score equations for commonly measured dimensions in pediatric 2-dimensional echocardiography that were free of residual confounding effects of body size, body mass index, and age. METHODS: The reference sample consisted of &gt;20 000 children without heart disease from 9 institutions who underwent clinical echocardiography that was reported as normal. A generalized additive model for location, scale, and shape (GAMLSS) was used to model the expected distributions of measurements as a function of sex, height, weight, body mass index, and age. RESULTS: Compared with a model that only considered body surface area, the proposed Z scores demonstrated less bias in subgroups of overweight, young, and early school-aged children. CONCLUSIONS: The proposed Z score equations may improve diagnostic and therapeutic accuracy by ensuring that body size, body mass index, and age do not confound the interpretation of measurements.

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)0.001
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: none
Teacher disagreement score0.704
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
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 head0.012
GPT teacher head0.252
Teacher spread0.240 · 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".

Quick stats

Citations4
Published2025
Admission routes2
Has abstractyes

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