Completeness of reporting for systematic reviews of point-of-care ultrasound: a meta-research study
Bibliographic record
Abstract
OBJECTIVES: Systematic reviews are often considered among the highest quality of evidence. Completely reported systematic reviews, however, are required so readers can assess for generalisability of the research to practice and risk of bias. The objective of this study was to assess the completeness of reporting for systematic reviews assessing the diagnostic accuracy of point-of-care ultrasound (POCUS) using the Preferred Reporting Items for Systematic Reviews and Meta-analyses for Diagnostic Test Accuracy (PRISMA-DTA) checklist that was published in 2018. DESIGN AND SETTING: databases were searched, with no date restriction, on March 1st, 2020 for systematic reviews assessing the diagnostic accuracy of POCUS. Adherence to PRISMA-DTA for the main text and abstract was scored independently and in duplicate using a modified checklist. Prespecified subgroup analyses were performed. MAIN OUTCOME MEASURES: The primary outcome was the mean PRISMA-DTA checklist adherence for the full-text and abstract. RESULTS: A total of 71 studies published from 2008 to 2020 met the inclusion criteria. The overall adherence for the full-text was moderate: 19.8 out of 26.0 items (76%) and for the abstract was 7.0 out of 11.0 items (64%). Although many items in the PRISMA-DTA checklist were frequently reported, several were r infrequently reported (<33% of studies), including item 5 (protocol registration), item D2 (minimally acceptable test accuracy) and item 14 (variability in target condition, index test and reference standards). Subgroup analyses showed a higher PRISMA-DTA mean adherence (SD) for high impact journals (20.9 (2.52) vs 18.9 (1.95); p<0.001), studies including supplemental materials (20.6 (2.48) vs 18.9 (2.28); p=0.004), studies citing adherence to PRISMA reporting guidelines (20.4 (1.95) vs 19.0 (3.00); p=0.038) and studies published in journals endorsing PRISMA guidelines (20.2 (2.47) vs 18.6 (2.37); p=0.025). There was variable adherence based on journal of publication (p=0.006), but not for study population (adult vs paediatric vs mixed) (p=0.62), year of publication (p=0.94), body region (p=0.78) or country (p=0.40). There was no variability in abstract adherence based on whether the abstract was structured with subheadings or not (p=0.25). A Spearman's correlation found moderate correlation between higher word counts and abstractand full-text adherence (R=0.45, p<0.001 and R=0.38, p=0.001), respectively. CONCLUSIONS: Overall, the reporting of POCUS diagnostic accuracy systematic reviews and meta-analyses was moderate. We identified deficits in several key areas including the preregistration of systematic reviews in an online repository, handling of multiple definitions of target conditions, index tests and reference standards and specifying minimally acceptable test accuracy. Prospective registration of reviews and detailed reporting as per PRISMA-DTA during the research process could improve reporting completeness. At an editorial level, word count and supplemental material limitations may impede reporting completeness, whereas endorsement of reporting guidelines on journal websites could improve 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 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 | 0.450 | 0.736 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.023 | 0.059 |
| Bibliometrics | 0.026 | 0.028 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".