Assessing Adherence to the PRISMA-DTA Guideline in Diagnostic Test Accuracy Systematic Reviews: A Five-Year Follow-up Analysis
Bibliographic record
Abstract
BACKGROUND: We evaluated reporting of diagnostic test accuracy (DTA) systematic reviews using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-DTA and PRISMA-DTA for abstracts. METHODS: We searched MEDLINE for recent DTA systematic reviews (September 2023-Mar 2024) to achieve a sample size of 100. Analyses evaluated adherence to PRISMA-DTA (and abstracts), on a per-item basis. Association of reporting with journal, country, impact factor (IF), index-test type, subspecialty area, use of supplemental material, PRISMA citation, word count, and PRISMA adoption was evaluated. Comparison to the baseline evaluation from 2019 was done. Protocol: https://doi.org/10.17605/OSF.IO/P25TE. RESULTS: Overall adherence (n = 100) was 78% (20.3/26.0 items, SD = 2.0) for PRISMA-DTA and 52% (5.7/11.0 items, SD = 1.6) for abstracts. Infrequently reported items (<33% of studies): eligibility criteria, definitions for data extraction, synthesis of results, and characteristics of the included studies. Infrequently reported items in abstracts were characteristics of the included studies, strengths and limitations, and funding. Reporting completeness for full text was minimally higher in studies in higher IF journals [20.7 vs 19.8 items; 95% confidence interval (95%CI) (0.09; 1.77)], as well as studies that cited PRISMA [21.1 vs 20.1 items; 95%CI (0.04; 1.95)], or used supplemental material (20.7 vs 19.2 items; 95%CI (0.63; 2.35)]. Variability in reporting was not associated with author country, journal, abstract word count limitations, PRISMA adoption, structured abstracts, study design, subspecialty, open-access status, or index test. No association with word counts was observed among full text or abstracts. Compared to the baseline evaluation, reporting was improved for full texts [71% to 78%; 95%CI (1.18; 2.26)] but not for abstracts [50% to 52%; 95%CI (-0.20; 0.60)]. CONCLUSIONS: Compared to the baseline evaluation published in 2019, we observed modest improved adherence to PRISMA-DTA and no improvement in PRISMA-DTA for abstracts reporting.
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 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 | 0.339 | 0.452 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.014 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads 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".