Objectives: The objective of this study was to evaluate whether higher reported accuracy estimates are associated with shorter time to publication among imaging diagnostic accuracy studies.
Methods: We included primary imaging diagnostic accuracy studies, included in meta-analyses from systematic reviews published in 2015. For each primary study, we extracted accuracy estimates, participant recruitment periods and publication dates. Our primary outcome was the association between Youden's index (sensitivity + specificity - 1, a single measure of diagnostic accuracy) and time to publication.
Results: We included 55 systematic reviews and 781 primary studies. Study completion dates were missing for 238 (30%) studies. The median time from completion to publication in the remaining 543 studies was 20 months (IQR 14-29). Youden's index was negatively correlated with time from completion to publication (rho = -0.11, p = 0.009). This association remained significant in multivariable Cox regression analyses after adjusting for seven study characteristics: hazard ratio of publication was 1.09 (95% CI 1.03-1.16, p = 0.004) per unit increase for logit-transformed estimates of Youden's index. When dichotomizing Youden's index by a median split, time from completion to publication was 20 months (IQR 13-33) for studies with a Youden's index below the median, and 19 months (14-27) for studies with a Youden's index above the median (p = 0.104).
Conclusion: Imaging diagnostic accuracy studies with higher accuracy estimates were weakly associated with a shorter time to publication.
Key Points: • Higher accuracy estimates are weakly associated with shorter time to publication. • Lag in time to publication remained significant in multivariate Cox regression analyses. • No correlation between accuracy and time from submission to publication was identified.
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Rheumatol Int
January 2025
School of Medicine, The University of Western Australia, 35 Stirling Highway, Perth, WA, 6009, Australia.
This study aims to review the literature and estimate the global pooled prevalence of interstitial lung disease among patients with rheumatoid arthritis (RA-ILD). The influence of risk factors like geography, socioeconomic status, smoking and DMARD use will be explored. A systematic review was performed according to the PRISMA and JBI guidelines.
View Article and Find Full Text PDFMem Cognit
January 2025
School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, USA.
Fifty years ago, Tversky and Kahneman (Cognitive Psychology, 5[2], 207-232, 1973) reported that people's speeded estimations of 8 × 7 × 6 × 5 × 4 × 3 × 2 × 1 were notably higher than their estimations for the equivalent expression in the opposite order, 1 × 2 × 3 × 4 × 5 × 6 × 7 × 8 (Median = 2,250 vs. 512, respectively). On top of this order effect, both groups grossly underestimated the correct value (40,320).
View Article and Find Full Text PDFUpdates Surg
January 2025
Department of Surgery, University Health Network, 200 Elizabeth St, 10 Eaton North, Room 216, Toronto, ON, M5G 2C4, Canada.
The applicability of risk assessment tools (RATs) for preoperative risk assessment (PRA) in Emergency General Surgery (EGS) is unclear. Limited knowledge of surgeons' approach to risk assessment is available. We investigated how Canadian surgeons approach PRA for EGS and their awareness of available RATs.
View Article and Find Full Text PDFNat Commun
January 2025
Division of Cancer Epigenomics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
DNA methylation (DNAm) is a key epigenetic mark that shows profound alterations in cancer. Read-level methylomes enable more in-depth analyses, due to their broad genomic coverage and preservation of rare cell-type signals, compared to summarized data such as 450K/EPIC microarrays. Here, we propose MethylBERT, a Transformer-based model for read-level methylation pattern classification.
View Article and Find Full Text PDFUltrasound Med Biol
January 2025
Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong; Biomedical Engineering Programme, The University of Hong Kong, Hong Kong. Electronic address:
Objective: Near-field (NF) clutter filters are critical for unveiling true myocardial structure and dynamics. Randomized singular value decomposition (rSVD) stands out for its proven computational efficiency and robustness. This study investigates the effect of rSVD-based NF clutter filtering on myocardial motion estimation.
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