| 21. |
- Ygland Rödström, Emil, et al.
(författare)
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Clinical classification systems and long-term outcome in mid- and late-stage Parkinson’s disease
- 2021
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Ingår i: npj Parkinson's Disease. - : Springer Nature. - 2373-8057. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- Parkinson’s disease shows a heterogeneous course and different clinical subtyping systems have been described. To compare the capabilities of two clinical classification systems, motor-phenotypes, and a simplified clinical motor-nonmotor subtyping system, a cohort was included at mean 7.9 ± 5.3 years of disease duration, classified using both clinical systems, and reexamined and reclassified at the end of an observation period. Time-points were retrospectively extracted for five major disease milestones: death, dementia, Hoehn and Yahr stage 5, nursing home living, and walking aid use. Eighty-nine patients were observed for 8.1 ± 2.7 years after inclusion. Dementia developed in 32.9% of the patients and 36.0–67.4% reached the other milestones. Motor-phenotypes were unable to stratify risks during this period, but the worst compared with the more favorable groups in the motor-nonmotor system conveyed hazard ratios between 2.6 and 63.6 for all milestones. A clear separation of risks for dying, living at the nursing home, and reaching motor end-stage was also shown when using only postural instability and gait disorder symptoms, without weighing them against the severity of the tremor. At reexamination, 29.4% and 64.7% of patients had changed classification groups in the motor-phenotype and motor-nonmotor systems, respectively. The motor-nonmotor system thus stratified risks of reaching crucial outcomes in mid–late Parkinson’s disease far better than the well-studied motor-phenotypes. Removing the tremor aspect of motor-phenotypes clearly improved this system, however. Classifications in both systems became unstable over time. The simplification of the motor-nonmotor system was easily applicable and showed potential as a prognostic marker during a large part of Parkinson’s disease.
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| 23. |
- Ygland Rödström, Emil, et al.
(författare)
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Serum Neurofilament Light Chain as a Marker of Progression in Parkinson's Disease : Long-Term Observation and Implications of Clinical Subtypes
- 2022
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Ingår i: Journal of Parkinson's Disease. - : IOS Press. - 1877-7171. ; 12:2, s. 571-584
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Tidskriftsartikel (refereegranskat)abstract
- Background: Biochemical and clinical biomarkers correlate with progression rate and disease severity in Parkinson's disease (PD) but are not sufficiently studied in late PD. Objective: To examine how serum neurofilament light chain (S-NfL) alone or combined with clinical classifications predicts PD outcome in later disease stages. Methods: Eighty-five patients with 7.9±5.1 years of PD duration were included in an observational cohort. Clinical scores were obtained at two separate examinations 8.2±2.0 years apart. S-NfL levels were determined with single molecule array (SiMoA). Five predefined disease progression milestones were assessed. After affirming combination potential of S-NfL and either of two clinical classifications, three combined models were constructed based on these factors and age at onset in different combinations. Results: S-NfL levels showed significant hazard ratios for four out of five disease progression milestones: walking-aid usage (HR 3.5; 95% CI 1.4-8.5), nursing home living (5.1; 2.1-12.5), motor end-stage (6.2; 2.1-17.8), and death (4.1; 1.7-9.7). Higher S-NfL levels were associated with lower ability in activities of daily living and poorer cognition at baseline and/or at follow-up. Combined models showed significantly improved area under receiver operating characteristic curves (0.77-0.91) compared to S-NfL levels alone (0.68-0.71) for predicting the five disease milestones. Conclusion: S-NfL levels stratified patients according to their likelihood to reach clinically relevant progression milestones during this long-term observational study. S-NfL alone reflected motor and social outcomes in later stages of PD. Combining S-NfL with clinical factors was possible and exploratory combined models improved prognostic accuracy.
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