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Record W2461967460 · doi:10.1111/hae.13023

Correlating clinical and radiological assessment of joints in haemophilia: results of a cross sectional study

2016· article· en· W2461967460 on OpenAlexaffabout
Pradeep Mathew Poonnoose, Pamela Hilliard, Andréa S. Doria, Shyamkumar N. Keshava, Sridhar Gibikote, M. Kavitha, Brian M. Feldman, V. Blanchette, Alok Srivastava

Bibliographic record

VenueHaemophilia · 2016
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsSickKids FoundationUniversity of TorontoHospital for Sick Children
FundersBayer HealthCare
KeywordsMedicineHaemophiliaRadiological weaponArthropathySoft tissuePhysical examinationUltrasoundMagnetic resonance imagingRadiologyOsteoarthritisSurgeryPathology

Abstract

fetched live from OpenAlex

OBJECTIVES: This study was undertaken to determine the correlation between the radiological changes in haemophilic arthropathy [X-ray, Ultrasound (US) and MRI] and clinical assessment as determined by the Hemophilia Joint Health Score (HJHS); and to document the US and MRI changes in joints that appear normal on plain X-ray and clinical evaluation. MATERIALS AND METHODS: Of 55 study joints (22 knees and 33 ankles) in 51 patients with haemophilia/von Willebrand disease, with a median age of 15 years (range: 5-17) were assessed using X-rays (Pettersson score) and clinical examination (HJHS) at two centres (Toronto, Canada; Vellore, India). MRI and ultrasonographic scoring was done through a consensus assessment by imagers at both centres using the IPSG MRI and US scores. RESULTS: 0.19; 0.26 respectively). Of the 18 joints with a Pettersson score of zero, 88.9% had changes that were detected clinically by the HJHS. Osteochondral abnormalities were identified in 38.9% of these joints by the MRI, while US images of the same joints were deemed abnormal in 83.3% by the current criteria. US identified haemosiderin and other soft tissue changes in all of the joints, while the same changes were noted in 94.4% of these joints on MRI. There were four joints with a HJHS of zero, all of which had soft tissue changes on MRI (score 1-7) and US (score 2-7). Osteochondral changes were detected in three of these joints by US and in 2 by MRI. There were four joints with an MRI score of 0-1 that had significant US scores (3-5) and HJHS scores (0-6). CONCLUSION: US and MRI are able to identify pathological changes in joints with normal X-ray imaging and clinical examination. However, further studies are required to be able to differentiate early abnormalities from normal. Clinical (HJHS) and radiological assessment (US/MRI) provide complimentary information and should be considered conjointly in the assessment of early joint arthropathy.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.123
GPT teacher head0.454
Teacher spread0.331 · 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

Citations62
Published2016
Admission routes2
Has abstractyes

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