ArticleArthroplasty today2022
Comparison of a Smartphone App to Manual Knee Range of Motion Measurements.
Article in Arthroplasty today, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 11 citations in OpenAlex.
- Effects of metformin phonophoresis and exercise therapy on pain, range of motion, and physical function in chronic knee osteoarthritis: randomized clinical trial.Journal of orthopaedic surgery and research · 2024Trial
- Criterion Validity and Inter-Method Reliability of a Smartphone Sensor-Based Application for Lower-Limb Range of Motion: In-Person vs. Tele-Assessment.Sensors (Basel, Switzerland) · 2026Article
- Accuracy of a Smartphone Software Application Compared With a Handheld Goniometer for Measuring Shoulder Range of Motion in Asymptomatic Adults.Orthopaedic journal of sports medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Digital technology has emerged as a useful tool for preoperative and postoperative patient engagement and for remote patient monitoring. Smartphones are equipped with motion-sensing technology, and apps can be designed which use these features to create a simple method for measuring range of motion. The purpose of this study was to determine the accuracy of digital technology in assessing knee range of motion using a smartphone app, compared to traditional goniometric measurements in an office setting. Methods: Fifty-three (53) patients in a clinical practice were enrolled between October 2019 and March 2020. Three separate measurements were taken during the patient encounter: (1) the surgeon, (2) the app, and (3) the physical therapist. Intraclass correlations were computed to assess the agreement between (1) the surgeon and app and (2) that between the physical therapist and surgeon. Results: When measuring flexion, the correlation between either the surgeon or therapist with the app was good, whereas the comparison between the surgeon and therapist was moderate. All extension measurement comparisons, between the app, surgeon, and therapist, showed moderate correlation. Limits of agreements showed that 80% of the difference between surgeon and app is within 10 degrees for extension and 11 degrees for flexion. Body mass index did not affect the accuracy of the measurements. Conclusion: Digital app measurements were comparable to measurements made by either a surgeon or physical therapist with a manual goniometer in the clinical setting and may be beneficial for measuring and monitoring patients' range of motion remotely.
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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.