ArticleNeurology2026
Test-Retest Reliability of Remote Assessments in Patients With Myotonic Dystrophy Type 1.
Article in Neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed.
- Treatment updates in myotonic disorders.Journal of neurology · 2026Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
BACKGROUND AND
objectivesWe previously demonstrated the feasibility of remote assessments in individuals with myotonic dystrophy type 1 (DM1). This study aimed to evaluate test-retest reliability and agreement of remote assessments and the interrater reliability of video-recorded functional assessments in DM1.
methodsParticipants were remotely recruited from the National Registry and provided with a toolkit containing a tablet equipped with videoconferencing software and devices for strength and functional assessments. Two remote study visits (RSV1, RSV2) were conducted within 3 months. During each visit, participants completed video-supervised assessments: handgrip, pinch grip (PG), 9-hole peg test (9HPT), video hand opening time (vHOT), timed up and go (TUG), 10-meter walk/run test (10MWRT), sitting and supine forced vital capacity (FVC), sniff nasal inspiratory pressure (SNIP), and tongue and buccal strength tests. Timed tests were video-recorded and scored using standardized protocols. Intraclass correlation coefficients (ICCs) were calculated using 2-way mixed-effects model for test-retest reliability and 2-way random-effects model for interrater reliability. Agreement was evaluated using Bland-Altman plots and measurement sensitivity with minimal detectable differences at 95% confidence (MDD95%). Patient-reported outcomes (PROs) assessing dysphagia (Eating Assessment Tool-10 [EAT-10]) and upper and lower extremity function (Upper Extremity Function Index [UEFI], Lower Extremity Functional Scale [LEFS]) were collected at RSV1 and correlated with quantitative assessments (Spearman coefficient, ρ).
resultsForty individuals with DM1 (average age 47, 55% female) completed both RSVs. Test-retest reliability (ICC, 95% CI) was excellent for handgrip (0.99, 0.98-0.99), sitting and supine FVC (0.98, 0.96-0.99), 10MWRT (0.96, 0.91-0.98), TUG (0.94, 0.89-0.97), and 9HPT (0.93, 0.86-0.97) with adequate measurement sensitivity (MDD95% <30% for all). ICCs were acceptable for PG (0.96, 0.92-0.98), tongue strength (0.93, 0.86-0.96), right (0.93, 0.85-0.97) and left buccal strength (0.88, 0.75-0.94), and SNIP (0.88, 0.77-0.94) and moderate for vHOT (thumb 0.67, 0.42-0.83; middle finger 0.66, 0.40-0.83), but with inadequate measurement sensitivity (MDD95% >30% for all). Interrater reliability (ICC, 95% CI) was excellent for 9HPT (1), vHOT (thumb 0.99, 0.98-0.99; middle finger 0.98, 0.97-0.99), 10MWRT, and TUG (both 0.99, 0.98-0.99). Bland-Altman plots showed no systematic bias. Correlation (ρ, |95% CI|) was strong between handgrip and UEFI (+0.70, 0.49-0.84), 10MWRT and LEFS (-0.72, 0.86-0.49), and moderate between PG and UEFI (+0.60, 0.30-0.82), TUG and LEFS (-0.53, 0.73-0.23), and tongue strength and EAT-10 (-0.49, 0.71-0.20). DISCUSSION: Remote assessments are feasible and safe. Many measurements demonstrate high reliability, show adequate measurement sensitivity, and correlate with PROs. These findings support remote research, facilitating broad participation, and reducing participant burden.
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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.