Completeness of reporting for systematic reviews of point-of-care ultrasound: a meta-research study
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,450 | 0,736 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,005 |
| Méta-épidémiologie (sens large) | 0,023 | 0,059 |
| Bibliométrie | 0,026 | 0,028 |
| Études des sciences et des technologies | 0,003 | 0,005 |
| Communication savante | 0,011 | 0,012 |
| Science ouverte | 0,006 | 0,008 |
| Intégrité de la recherche | 0,006 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».