A systematic review of ultrasound imaging as a tool for evaluating haemophilic arthropathy in children and adults
Bibliographic record
Abstract
The purpose of this study was to semi-quantitatively assess the evidence on the value of ultrasound (US) for assessment of haemophilic arthropathy (HA) in children and adults based on the following questions: (1) Does early diagnosis of pathological findings, using available US techniques, impact the functional status of the joint? (2) Do current available US techniques have the ability to accurately detect pathological changes in target joints in haemophilic patients? (3) Does treatment (prophylaxis) improve US evidence of haemophilic arthropathy in children and adults? (4) Is there any association between various US scoring systems and other clinical/radiological constructs? Of the 6880 citations identified searching databases such as MEDLINE, Embase, CENTRAL and Web of Science, 20 articles investigating either the diagnostic accuracy of US and/or US scanning protocols and scoring systems for assessment of HA met the inclusion criteria for the study. Of these, 14 articles evaluating the diagnostic accuracy of US were assessed by two independent reviewers for reporting quality using the Standards for Reporting of Diagnostic Accuracy (STARD) tool and for methodological quality using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Using STARD, 1/14 studies (7%) was scored as of high reporting quality and 8/14 (57%), of moderate quality. Assessment with QUADAS-2 reported 2/14 (14%) studies as having high methodological quality and 6/14 (43%) as having moderate quality. There is fair evidence (Grade B) to recommend US as an accurate technique for early diagnosis of HA, to demonstrate that US scores correlate with clinical/US constructs and to prove an association between US findings and functional status of the joint. However, there is insufficient evidence (Grade I) to conclude that US-detectable findings in HA are sensitive to changes in therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".