Evidence map›Paper›PMID 35716143›Full record

ArticleMovement disorders : official journal of the Movement Disorder Society2022

Resolving Missing Data from the Movement Disorder Society Unified Parkinson's Disease Rating Scale: Implications for Telemedicine.

Sheng Luo, Christopher G Goetz, Dongrak Choi, Sanket Aggarwal, Tiago A Mestre, Glenn T Stebbins

Open access · greenAbstract read
In one paragraph

Article in Movement disorders : official journal of the Movement Disorder Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 28% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. The Importance of Standardized Assessment.Movement disorders clinical practice · 2024
    Article
  5. 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

6 authors at 3 institutions in 2 countries.

Sheng LuoDepartment of Biostatistics & Bioinformatics, Duke University, Durham, North Carolina, USA.ORCID 0000-0003-4214-5809
Christopher G GoetzDepartment of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA.
Dongrak ChoiDepartment of Biostatistics & Bioinformatics, Duke University, Durham, North Carolina, USA.
Sanket AggarwalDepartment of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA.
Tiago A MestreOttawa Hospital Research Institute, University of Ottawa Brain and Mind Research Institute, Division of Neurology, Department of Medicine, University of Ottawa, The Ottawa Hospital, Ottawa, Ontario, Canada.ORCID 0000-0002-6973-7479
Glenn T StebbinsDepartment of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA.ORCID 0000-0001-7905-9336
Rush University Medical Center · USDuke University · USUniversity of Ottawa · CA

Funding

Resource Core 3 - Metabolomics CoreP30AG028716 · NIA · DUKE UNIVERSITY · PI Sarah B. Peskoe · 2006 to 2026
$24.6M
Research Education Component CoreP30AG072958 · NIA · DUKE UNIVERSITY · PI GWENN A GARDEN, Heather E. Whitson · 2021 to 2026
$24.1M
Integrative modeling and dynamic prediction of Alzheimer's diseaseR01AG064803 · NIA · DUKE UNIVERSITY · PI LUO, SHENG · 2020 to 2024
$2.3M
NIA NIH HHS P30 AG028716NIA NIH HHS P30 AG072958NIA NIH HHS R01 AG064803
6 · The paper itself

Abstract

backgroundTelemedicine has become standard in clinical care and research during the coronavirus disease 2019 pandemic. Remote administration of Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III (Motor Examination) precludes ratings of all items, because Rigidity and Postural Stability (six scores) require in-person rating.

objectiveThe objective of this study was to determine imputation accuracy for total-sum and item-specific MDS-UPDRS Motor Examination scores in remote administration.

methodsWe applied multivariate imputation by chained equations techniques in a cross-sectional dataset where patients had one MDS-UPDRS rating (International Translational Program, n = 8,588) and in a longitudinal dataset where patients had multiple ratings (Rush Program, n = 396). Successful imputation was stringently defined as (1) generalized Lin's concordance correlation coefficient >0.95, reflecting near-perfect agreement between total-sum score with complete data and surrogate score, calculated without patients' actual Rigidity and Postural Stability scores; and (2) perfect agreement for item-level scores for Rigidity and Postural Stability items.

resultsFor total-sum score when Rigidity and Postural Stability scores were withdrawn, using one or multiple visits, multivariate imputation by chained equations imputation reached near-perfect agreement with the original total-sum score. However, at the item level, the degree of perfect agreement between the surrogate and actual Rigidity items and Postural Stability scores always fell below threshold.

conclusionsThe MDS-UPDRS Part III total-sum score, a key clinical outcome in research and in clinical practice, can be accurately imputed without the Rigidity and Postural Stability items that cannot be rated by telemedicine. No formula, however, allows for specific item-level imputation. When Rigidity and Postural Stability item scores are of key clinical or research interest, patients with PD must be scored in person. © 2022 International Parkinson and Movement Disorder Society.

Indexed as

COVID-19Parkinson DiseaseTelemedicineCross-Sectional StudiesHumansMental Status and Dementia TestsSeverity of Illness Indexmultiple imputationParkinson's diseaserating scale

Identifiers

PMID35716143
PMCPMC9391277
OpenAlexW4283068729

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.