Evidence map›Paper›PMID 35723109›Full record

ArticleJournal of neuromuscular diseases2022

The Black Box of Technological Outcome Measures: An Example in Duchenne Muscular Dystrophy.

Karin J Naarding, Mariska M H P Janssen, Ruben D Boon, Paulina J M Bank, Robert P Matthew, Gregorij Kurillo, Jay J Han, Jan J G M Verschuuren, Imelda J M de Groot, Menno van der Holst and 2 more

Abstract read
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Article in Journal of neuromuscular diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Karin J NaardingDepartment of Neurology, Leiden University Medical Center (LUMC), Leiden, Zuid-Holland, Netherlands.
Mariska M H P JanssenDuchenne CenterNetherlands.
Ruben D BoonC.J. Gorter MRI Center, Dept. of Radiology, LUMC, Leiden, Zuid-Holland, Netherlands.
Paulina J M BankDepartment of Neurology, Leiden University Medical Center (LUMC), Leiden, Zuid-Holland, Netherlands.
Robert P MatthewDepartment of Physical Therapy and Rehabilitation Science, University of California at San Francisco, San Francisco, CA, USA.
Gregorij KurilloDepartment of Orthopaedic Surgery, University of California at San Francisco, SanFrancisco, CA, USA.
Jay J HanDepartment of Physical Medicine & Rehabilitation, UC Irvine School of Medicine, Irvine, CA, USA.
Jan J G M VerschuurenDepartment of Neurology, Leiden University Medical Center (LUMC), Leiden, Zuid-Holland, Netherlands.
Imelda J M de GrootDuchenne CenterNetherlands.
Menno van der HolstDuchenne CenterNetherlands.
Hermien E KanDuchenne CenterNetherlands.
Erik H NiksDepartment of Neurology, Leiden University Medical Center (LUMC), Leiden, Zuid-Holland, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOutcome measures for non-ambulant Duchenne muscular dystrophy (DMD) patients are limited, with only the Performance of the Upper Limb (PUL) approved as endpoint for clinical trials.

objectiveWe assessed four outcome measures based on devices developed for the gaming industry, aiming to overcome disadvantages of observer-dependency and motivation.

methodsTwenty-two non-ambulant DMD patients (range 8.6-24.1 years) and 14 healthy controls (HC; range 9.5-25.4 years) were studied at baseline and 16 patients at 12 months using Leap Motion to quantify wrist/hand active range of motion (aROM) and a Kinect sensor for reached volume with Ability Captured Through Interactive Video Evaluation (ACTIVE), Functional Workspace (FWS) summed distance to seven upper extremity body points, and trunk compensation (KinectTC). PUL 2.0 was performed in patients only. A stepwise approach assessed quality control, construct validity, reliability, concurrent validity, longitudinal change and patient perception.

resultsLeap Motion aROM distinguished patients and HCs for supination, radial deviation and wrist flexion (range p = 0.006 to <0.001). Reliability was low and the manufacturer's hand model did not match the sensor's depth images. ACTIVE differed between patients and HCs (p < 0.001), correlated with PUL (rho = 0.76), and decreased over time (p = 0.030) with a standardized response mean (SRM) of -0.61. It was appraised as fun on a 10-point numeric rating scale (median 9/10). PUL decreased over time (p < 0.001) with an SRM of -1.28, and was appraised as fun (median 7/10). FWS summed distance distinguished patients and HCs (p < 0.001), but reliability in patients was insufficient. KinectTC differed between patients and HCs (p < 0.01), but correlated insufficiently with PUL (rho = -0.69).

conclusionsOnly ACTIVE qualified as potential outcome measure in non-ambulant DMD patients, although the SRM was below the commonly used threshold of 0.8. Lack of insight in technological constraints due to intellectual property and software updates made the technology behind these outcome measures a kind of black box that could jeopardize long-term use in clinical development.

Indexed as

Muscular Dystrophy, DuchenneHumansRange of Motion, ArticularReproducibility of ResultsTechnologyUpper Extremitybiomarkersduchennekinectleap motionMuscular dystrophy

Identifiers

PMID35723109
PMCPMC9398077

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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.