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Study Objectives: <p>Individuals with isolated rapid eye movement sleep behavior disorder (iRBD) are at high risk of neurodegenerative parkinsonian disorders or dementia (NPD). Determining which characteristics predict greatest risk could improve clinical care. Our objectives were to utilize electronic health record data to apply prodromal Parkinson’s disease research diagnostic criteria to outpatients with iRBD and determine their utility for identifying patients with iRBD at high vs low risk for NPD diagnosis.</p> Methods: <p>This was a retrospective cohort study at a tertiary care center in western Pennsylvania. Diagnosis of iRBD was confirmed with expert manual chart review. Prodromal risk markers and signs and symptoms were determined with diagnostic codes. Multivariable Cox proportional hazards models examined a range of covariates as predictors of time to NPD diagnosis.</p> Results: <p>Of 448 patients with iRBD, 82 (18.30%) were diagnosed with NPD. Forty-nine (10.93%) had &gt; 80% prodromal Parkinson’s disease probability. There was no difference in time to NPD among those who met vs did not meet &gt; 80% probability (log-rank <i>P</i> = .49). In a Cox model that included all assessed criteria features, risk of diagnosis was associated with male sex (hazard ratio = 2.06, 95% confidence interval = 1.04–1.10), older baseline age (hazard ratio = 1.07, 95% confidence interval = 1.05–1.10), and cognitive dysfunction diagnostic code (hazard ratio = 2.83, 95% confidence interval = 1.79–4.46). Time to NPD diagnosis among patients with predicted high vs low risk was significantly different (log-rank test <i>P</i> = .012).</p> Conclusions: <p>In outpatients with iRBD, a model combining individual Parkinson’s disease risk factors and prodromal features accurately identifies individuals at high risk for NPD diagnosis. Results demonstrate the potential of electronic health record data to translate research on prodromal Parkinson’s disease to the clinic.</p> Citation: <p>Chahine LM, Newman A, Boyce RD, Brooks MM. Prodromal features and risk of neurodegenerative disorders diagnosis in outpatients with REM sleep behavior disorder. <i>J Clin Sleep Med</i>. 2025;21(11):1857–1869.</p>

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Prodromal features and risk of neurodegenerative disorders diagnosis in outpatients with REM sleep behavior disorder

  • 期刊论文

  • 发表日期：

    2025年11月1日

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  • Lana M. Chahine,
  • Anne Newman,
  • Richard D. Boyce,
  • Maria M. Brooks

摘要

Study Objectives:

Individuals with isolated rapid eye movement sleep behavior disorder (iRBD) are at high risk of neurodegenerative parkinsonian disorders or dementia (NPD). Determining which characteristics predict greatest risk could improve clinical care. Our objectives were to utilize electronic health record data to apply prodromal Parkinson’s disease research diagnostic criteria to outpatients with iRBD and determine their utility for identifying patients with iRBD at high vs low risk for NPD diagnosis.

Methods:

This was a retrospective cohort study at a tertiary care center in western Pennsylvania. Diagnosis of iRBD was confirmed with expert manual chart review. Prodromal risk markers and signs and symptoms were determined with diagnostic codes. Multivariable Cox proportional hazards models examined a range of covariates as predictors of time to NPD diagnosis.

Results:

Of 448 patients with iRBD, 82 (18.30%) were diagnosed with NPD. Forty-nine (10.93%) had > 80% prodromal Parkinson’s disease probability. There was no difference in time to NPD among those who met vs did not meet > 80% probability (log-rank P = .49). In a Cox model that included all assessed criteria features, risk of diagnosis was associated with male sex (hazard ratio = 2.06, 95% confidence interval = 1.04–1.10), older baseline age (hazard ratio = 1.07, 95% confidence interval = 1.05–1.10), and cognitive dysfunction diagnostic code (hazard ratio = 2.83, 95% confidence interval = 1.79–4.46). Time to NPD diagnosis among patients with predicted high vs low risk was significantly different (log-rank test P = .012).

Conclusions:

In outpatients with iRBD, a model combining individual Parkinson’s disease risk factors and prodromal features accurately identifies individuals at high risk for NPD diagnosis. Results demonstrate the potential of electronic health record data to translate research on prodromal Parkinson’s disease to the clinic.

Citation:

Chahine LM, Newman A, Boyce RD, Brooks MM. Prodromal features and risk of neurodegenerative disorders diagnosis in outpatients with REM sleep behavior disorder. J Clin Sleep Med. 2025;21(11):1857–1869.