Vehicle Control as a Measure of Real-World Driving Performance in Patients With Rheumatoid Arthritis.


Journal

Arthritis care & research
ISSN: 2151-4658
Titre abrégé: Arthritis Care Res (Hoboken)
Pays: United States
ID NLM: 101518086

Informations de publication

Date de publication:
02 2023
Historique:
revised: 06 08 2021
received: 23 02 2021
accepted: 12 08 2021
pmc-release: 01 02 2024
pubmed: 17 8 2021
medline: 14 2 2023
entrez: 16 8 2021
Statut: ppublish

Résumé

To quantify vehicle control as a metric of automobile driving performance in patients with rheumatoid arthritis (RA). Naturalistic driving assessments were completed in patients with active RA and controls without disease. Data were collected using in-car, sensor-based instrumentation installed in the participants' own vehicles to observe typical driving habits. RA disease status, disease activity, and functional status were associated with vehicle control (lateral [steering] and longitudinal [braking/accelerating] acceleration variability) using mixed-effect linear regression models stratified by road type (defined by roadway speed limit). Across 1,292 driving hours, RA drivers (n = 33) demonstrated differences in vehicle control compared to controls (n = 23), with evidence of significant statistical interaction between disease status and road type (P < 0.001). On residential roads, participants with RA demonstrated overall lower braking/accelerating variability than controls (P ≤ 0.004) and, when disease activity was low, lower steering variability (P = 0.03). On interstates/highways, RA was associated with increased steering variability among those with moderate/high Clinical Disease Activity Index scores (P = 0.04). In models limited to RA, increases in disease activity and physical disability over 12 weeks of observation were associated with a significant increase in braking/accelerating variability on interstate/highways (both P < 0.05). Using novel naturalistic assessments, we linked RA and worsening RA disease severity with aberrant vehicle control. These findings support the need for further research to map these observed patterns in vehicle control to metrics of driver risk and, in turn, to link patterns of real-world driving behavior to diagnosis and disease activity.

Identifiants

pubmed: 34397172
doi: 10.1002/acr.24769
pmc: PMC8847538
mid: NIHMS1733286
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

252-259

Subventions

Organisme : CSRD VA
ID : IK2 CX002203
Pays : United States
Organisme : BLRD VA
ID : IS1 BX004790
Pays : United States
Organisme : NIAAA NIH HHS
ID : R25 AA020818
Pays : United States
Organisme : NIGMS NIH HHS
ID : U54 GM115458
Pays : United States

Informations de copyright

© 2021 American College of Rheumatology.

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Auteurs

Ted R Mikuls (TR)

University of Nebraska Medical Center and VA Nebraska-Western Iowa Health Care System, Omaha, Nebraska.

Jennifer Merickel (J)

University of Nebraska Medical Center, Omaha.

Yeongjin Gwon (Y)

University of Nebraska Medical Center, Omaha.

Harlan Sayles (H)

University of Nebraska Medical Center, Omaha.

Alison Petro (A)

University of Nebraska Medical Center, Omaha.

Amy Cannella (A)

University of Nebraska Medical Center and VA Nebraska-Western Iowa Health Care System, Omaha, Nebraska.

Marcus H Snow (MH)

University of Nebraska Medical Center, Omaha.

Michael Feely (M)

University of Nebraska Medical Center and VA Nebraska-Western Iowa Health Care System, Omaha, Nebraska.

Bryant R England (BR)

University of Nebraska Medical Center and VA Nebraska-Western Iowa Health Care System, Omaha, Nebraska.

Kaleb Michaud (K)

University of Nebraska Medical Center, Omaha, and FORWARD, The National Databank for Rheumatic Diseases, Wichita, Kansas.

Matthew Rizzo (M)

University of Nebraska Medical Center, Omaha.

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Classifications MeSH