10.18735/W9QC-9H39
Halloran, Jason
Jason
Halloran
https://orcid.org/0000-0001-5866-6583
Washington State University
Abdollahi Nohouji, Neda
Neda
Abdollahi Nohouji
https://orcid.org/0000-0002-9604-132X
Cleveland Clinic
Hafez, Mhd Ammar
Mhd Ammar
Hafez
Cleveland State University
Besier, Thor
Thor
Besier
https://orcid.org/0000-0003-0818-7554
University of Auckland
Chokhandre, Snehal
Snehal
Chokhandre
https://orcid.org/0000-0001-7158-4320
Cleveland Clinic
Elmasry, Shady
Shady
Elmasry
https://orcid.org/0000-0003-0193-7711
Hospital for Special Surgery
Hume, Donald
Donald
Hume
https://orcid.org/0000-0001-9081-358X
University of Denver
Imhauser, Carl
Carl
Imhauser
https://orcid.org/0000-0003-2445-7112
Hospital for Special Surgery
Rooks, Nynke
Nynke
Rooks
https://orcid.org/0000-0002-9088-7404
University of Auckland
Schneider, Marco
Marco
Schneider
https://orcid.org/0000-0002-4918-1389
University of Auckland
Schwartz, Ariel
Ariel
Schwartz
https://orcid.org/0000-0001-6313-9171
Cleveland Clinic
Shelburne, Kevin
Kevin
Shelburne
https://orcid.org/0000-0003-3377-2712
University of Denver
Zaylor, William
William
Zaylor
https://orcid.org/0000-0002-2463-226X
Cleveland State University
Erdemir, Ahmet
Ahmet
Erdemir
https://orcid.org/0000-0002-4629-8055
Cleveland Clinic
Reproducibility Paper Data: Data and analysis package for the draft manuscript that assesses reporting and reproducibility across a cohort of literature-based knee modeling studies. The package contains the raw data, which are the reviews performed by the KneeHub team members, and the corresponding statistical analysis.
SimTK
2022
Dataset
https://simtk.org/projects/kneehub
Reproducible research serves as a pillar of the scientific method and is a foundation for scientific advancement. However, estimates for irreproducibility of preclinical science range from 75% to 90%. The importance of reproducible science has not been assessed in the context of mechanics-based modeling of human joints such as the knee, despite this being an area that has seen dramatic growth. Framed in the context of five experienced teams currently documenting knee modeling procedures, the aim of this work was to evaluate reporting and the perceived potential for reproducibility across studies the teams viewed as important contributions to the literature. A cohort of studies was selected by polling, which resulted in an assessment of nine studies as opposed to a broader analysis across the literature. Using a published checklist for reporting of modeling features, the cohort was evaluated for both “reporting” and their potential to be “reproduced”, which was delineated into six major modeling categories and three subcategories. Logistic regression analysis revealed that for individual modeling categories, the proportion of “reported” occurrences ranged from 0.31, 95% confidence interval (CI) [0.23, 0.41] to 0.77, 95% CI [0.68, 0.86]. The proportion of whether a category was perceived as “reproducible” ranged from 0.22, 95% CI [0.15, 0.31] to 0.44, 95% CI [0.35, 0.55]. The relatively low ratios highlight an opportunity to improve reporting and reproducibility of knee modeling studies. Ongoing efforts, including our findings, contribute to a dialogue that facilitates adoption of practices that provide both credibility and translation possibilities.
National Institute of Biomedical Imaging and Bioengineering
https://doi.org/10.13039/100000070
R01EB024573