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Record W4309924764 · doi:10.4329/wjr.v14.i11.367

Interobserver reliability between pediatric radiologists and residents in ultrasound evaluation of intraventricular hemorrhage in premature infants

2022· article· en· W4309924764 on OpenAlexaff
Muhammad Danish Barakzai, Ayimen Khalid, Zara Za Sheer, Faheemullah Khan, Naila Nadeem, Noman Khan, Kiran Hilal

Bibliographic record

VenueWorld Journal of Radiology · 2022
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineIntraventricular hemorrhageUltrasoundPediatric RadiologyGrading (engineering)RadiologyGestational ageNeuroradiologyNeonatal intensive care unitPediatricsPregnancyNeurology

Abstract

fetched live from OpenAlex

BACKGROUND: Germinal matrix intraventricular hemorrhage (IVH) may contribute to significant morbidity and mortality in premature infants. Timely identification and grading of IVH affect decision-making and clinical outcomes. There is possibility of misinterpretation of the ultrasound appearances, and the interobserver variability has not been investigated between radiology resident and board-certified radiologist. AIM: To assess interobserver reliability between senior radiology residents performing bedside cranial ultrasound during on-call hours and pediatric radiologists. METHODS: From June 2018 to June 2020, neonatal cranial ultrasound examinations were performed in neonatal intensive care unit. Ultrasound findings were recorded by the residents performing the ultrasound and the pediatric attending radiologists. RESULTS: In total, 200 neonates were included in the study, with a mean gestational age of 30.9 wk. Interobserver agreement for higher grade (Grade III & IV) IVH was excellent. There was substantial agreement for lower grade (Grade I & II) IVH. CONCLUSION: There is strong agreement between radiology residents and pediatric radiologists, which is higher for high grade IVHs.

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)0.029
metaresearch head score (Gemma)0.085
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 score0.029
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.085
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.285
Teacher spread0.266 · 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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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