Blinding practices during acute point-of-care ultrasound research: the BLIND-US meta-research study
Bibliographic record
Abstract
OBJECTIVES: Point-of-care ultrasound (POCUS) diagnostic accuracy research has significant variation in blinding practices. This study characterises the blinding practices during acute POCUS research to determine whether research methodology adequately reflects POCUS use in routine clinical practice. DESIGN, SETTINGS AND PARTICIPANTS: journals from January 2016 to January 2020 was performed. Studies were included if they were primary diagnostic accuracy studies. The study year, journal impact factor, population, hospital area, body region, study design, blinding of the POCUS interpreter to clinical information, whether the person performing the POCUS scan was the same person interpreting the scan, and whether the study reported incremental diagnostic yield were extracted in duplicate by two authors. Descriptive statistics were provided and prespecified subgroup analysis was performed. MAIN OUTCOME MEASURES: The primary outcome was the number of studies that blinded the POCUS interpreter to at least some part of the clinical information. Secondary outcomes included whether the person performing the POCUS scan was the same person interpreting it and whether the study reported incremental diagnostic yield. RESULTS: 520 abstracts were screened with 97 studies included. The POCUS interpreter was blinded to clinical information in 37 studies (38.1%), not blinded in 34 studies (35.1%) and not reported in 26 studies (26.8%). The POCUS interpreter was the same person obtaining the images in 72 studies (74.2%), different in 14 studies (14.4%) and not reported in 11 studies (11.3%). Only four studies (4.1%) reported incremental diagnostic yield for POCUS. Inter-rater reliability was moderate (k=0.64). Subgroup analysis based on impact factor, body region, hospital area, patient population and study design did not show significant differences after completing pairwise comparisons. CONCLUSIONS: Although blinding the POCUS interpreter to clinical information may be done in a perceived attempt to limit bias, this may result in accuracy estimates that do not reflect routine clinical practice. Similarly, having a different clinician perform and interpret the POCUS scan significantly limits generalisability to practice as it does not truly reflect 'point-of-care' ultrasound at all. Reporting incremental diagnostic yield from implementing POCUS into a diagnostic pathway better reflects the value of POCUS; however, this methodology was infrequently used. TRIAL REGISTRATION NUMBER: The study protocol was registered on Open Science Framework (https://osf.io/h5fe7/).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.289 | 0.491 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.033 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".