Completeness of Reporting of Systematic Reviews of Diagnostic Test Accuracy Based on the PRISMA-DTA Reporting Guideline
Bibliographic record
Abstract
Abstract BACKGROUND We evaluated the completeness of reporting of diagnostic test accuracy (DTA) systematic reviews using the recently developed Preferred Reporting Items for Systematic Reviews and MetaAnalyses (PRISMA)-DTA guidelines. METHODS MEDLINE® was searched for DTA systematic reviews published October 2017 to January 2018. The search time span was modulated to reach the desired sample size of 100 systematic reviews. Reporting on a per-item basis using PRISMA-DTA was evaluated. RESULTS One hundred reviews were included. Mean reported items were 18.6 of 26 (71%; SD = 1.9) for PRISMA-DTA and 5.5 of 11 (50%; SD = 1.2) for PRISMA-DTA for abstracts. Items in the results were frequently reported. Items related to protocol registration, characteristics of included studies, results synthesis, and definitions used in data extraction were infrequently reported. Infrequently reported items from PRISMA-DTA for abstracts included funding information, strengths and limitations, characteristics of included studies, and assessment of applicability. Reporting completeness was higher in higher impact factor journals (18.9 vs 18.1 items; P = 0.04), studies that cited PRISMA (18.9 vs 17.7 items; P = 0.003), or used supplementary material (19.1 vs 18.0 items; P = 0.004). Variability in reporting was associated with author country (P = 0.04) but not journal (P = 0.6), abstract word count limitations (P = 0.9), PRISMA adoption (P = 0.2), structured abstracts (P = 0.2), study design (P = 0.8), subspecialty area (P = 0.09), or index test (P = 0.5). Abstracts with a higher word count were more informative (R = 0.4; P < 0.001). No association with word counts was observed for full-text reports (R = −0.03; P = 0.06). CONCLUSIONS Recently published reports of DTA systematic reviews are not fully informative when evaluated against the PRISMA-DTA guidelines. These results should guide knowledge translation strategies, including journal level (e.g., PRISMA-DTA adoption, increased abstract word count, and use of supplementary material) and author level (PRISMA-DTA citation awareness) strategies.
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 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 | 0.651 | 0.836 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.017 | 0.038 |
| Bibliometrics | 0.037 | 0.032 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.011 | 0.011 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".