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Record W3010458352 · doi:10.1002/uog.22012

Diagnostic accuracy of postmortem ultrasound <i>vs</i> postmortem 1.5‐T MRI for non‐invasive perinatal autopsy

2020· article· en· W3010458352 on OpenAlexfundno aff
Susan C. Shelmerdine, Neil J. Sebire, Owen J. Arthurs

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2020
Typearticle
Languageen
FieldMedicine
TopicAutopsy Techniques and Outcomes
Canadian institutionsnot available
FundersMedical Research Council CanadaRoyal College of RadiologistsMedical Research CouncilNational Institute for Health and Care Research
KeywordsMedicineAutopsyConcordanceMagnetic resonance imagingRadiologyProspective cohort studyThorax (insect anatomy)Nuclear medicineSurgeryPathologyInternal medicineAnatomy

Abstract

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OBJECTIVES: To determine the diagnostic accuracy of postmortem magnetic resonance imaging (PM-MRI) and postmortem ultrasound (PM-US) for perinatal autopsy in the same patient cohort, and to determine whether PM-US can provide the same anatomical information as PM-MRI. METHODS: In this prospective, 5-year (July 2014-July 2019) single-center study, we performed 1.5-T PM-MRI and PM-US in an unselected cohort of perinatal deaths. The diagnostic accuracies of both modalities were calculated, using autopsy as the reference standard. As a secondary objective, the concordance rates between the two imaging modalities for the overall main diagnosis and for five anatomical regions (brain, spine, thorax, heart and abdomen) were calculated. RESULTS: During the study period, 136 cases underwent both PM-US and PM-MRI, of which 88 (64.7%) also underwent autopsy. There was no significant difference in the rates of concordance with autopsy between the two modalities for overall diagnosis (PM-US, 86.4% (95% CI, 77.7-92.0%) vs PM-MRI, 88.6% (95% CI, 80.3-93.7%)) or in the sensitivities and specificities for individual anatomical regions. There were more non-diagnostic PM-US than PM-MRI examinations for the brain (22.8% vs 3.7%) and heart (14.7% vs 5.1%). If an 'imaging-only' autopsy had been performed, PM-US would have achieved the same diagnosis as 1.5-T PM-MRI in 86.8% (95% CI, 80.0-91.5%) of cases, with the highest rates of agreement being for spine (99.3% (95% CI, 95.9-99.9%)) and cardiac (97.3% (95% CI, 92.4-99.1%)) findings and the lowest being for brain diagnoses (85.2% (95% CI, 76.9-90.8%)). CONCLUSION: Although there were fewer non-diagnostic cases using PM-MRI than for PM-US, the high concordance rate for overall diagnosis suggests that PM-US could be used for triaging cases when PM-MRI access is limited or unavailable. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

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)0.004
metaresearch head score (Gemma)0.021
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 score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.015
GPT teacher head0.272
Teacher spread0.258 · 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

Citations18
Published2020
Admission routes1
Has abstractyes

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