ArticleJournal of experimental orthopaedics2015
A new graphical method to display data sets representing biomechanical knee behaviour.
Article in Journal of experimental orthopaedics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- High congruency MB insert design: stabilizing knee joint even with PCL deficiency.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2020Article
- Asymmetric polyethylene inserts promote favorable kinematics and better clinical outcome compared to symmetric inserts in a mobile bearing total knee arthroplasty.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2019Article
- Sensitivity analysis of the material properties of different soft-tissues: implications for a subject-specific knee arthroplasty.Muscles, ligaments and tendons journalReview
- Change in knee biomechanics during squat and walking induced by a modification in TKA size.Journal of orthopaedicsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWhen researchers describe data from their studies, there is no rule defining the best way to represent results. Therefore, collecting and explaining results from personal research or understanding data from publications is not always straightforward. These issues are even worse in fields such as biomedical engineering, where researchers from different backgrounds, usually engineers and surgeons, need to interact and exchange information. For these reasons, the purpose of this study is to introduce and illustrate an innovative method to represent, concisely and intuitively, biomechanical knee behavior, called KneePrints.
methodsTo test the KneePrints method, a huge amount of data from previously published sensitivity analyses were used and represented both with conventional techniques and with this new graphical method. Then, a survey has been distributed among different international specialists in the orthopedic field, such as surgeons and researchers. In the survey, interviewees were asked to select the favorite method that addressed to be the most effective to show the same results.
resultsCollecting the outcomes from the survey, the KneePrints method resulted to be more effective than standard graphs, such as tables and histograms. KneePrints method has been selected to be clearer in representing outputs and more immediate in results understanding independently from the occupation of the interviewees by the survey. The general preference for the KneePrints is 63 %, up to 74 % being surgeons' choice.
conclusionsThe innovative KneePrints method has been endorsed to be effective in representing and making more understandable knee joint outputs. This method can be extended also to other topics.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.