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Extensive validation study of the Parkinson's Disease Composite Scale.

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Title: Extensive validation study of the Parkinson's Disease Composite Scale.
Authors: Martinez‐Martin, P. (AUTHOR), Radicati, F. G. (AUTHOR), Rodriguez Blazquez, C. (AUTHOR), Wetmore, J. (AUTHOR), Kovacs, N. (AUTHOR), Ray Chaudhuri, K. (AUTHOR), Stocchi, F. (AUTHOR), Vuletic, Vladimira (AUTHOR), Falup‐Pecurariu, Cristian (AUTHOR), Diaconu, Ştefania (AUTHOR), Johansson, Anders (AUTHOR), Sundgren, Mathias (AUTHOR), Simitsi, Athima (AUTHOR), Stefanis, Leonidas (AUTHOR), Gurevich, Tanya (AUTHOR), Migirov‐Sanderovich, Angel (AUTHOR), Ezra, Adi (AUTHOR), Guekht, Alla (AUTHOR), Popov, Georgy (AUTHOR), Stamelou, Maria (AUTHOR)
Source: European Journal of Neurology. Oct2019, Vol. 26 Issue 10, p1281-1288. 8p. 6 Charts.
Subjects: Parkinson's disease, Measurement errors, Intraclass correlation, Cronbach's alpha, Movement disorders
Abstract: Background and purpose: A composite instrument able to rapidly and reliably assess the most relevant motor and non‐motor afflictions suffered by Parkinson's disease (PD) patients in a real world clinic setting is an unmet need. The recently validated PD Composite Scale (PDCS) was designed to fulfil this gap as a quick, comprehensive PD assessment. The objective of this study was extensive evaluation of the PDCS's clinimetric properties using a large international sample. Methods: This was a cross‐sectional study in which the PDCS, the Movement Disorder Society Unified Parkinson's Disease Rating Scale and the Clinical Impression of Severity Index for PD were applied. Basic clinimetric attributes of the PDCS were analysed. Results: In total, 776 PD patients were included. The PDCS total score showed negligible floor and ceiling effects. Three factors (54.5% of the variance) were identified: factor 1 included motor impairment, fluctuations and disability; factor 2, non‐motor symptoms; and factor 3, tremor and complications of therapy. Cronbach's alpha was from 0.66 to 0.79. Inter‐rater reliability showed weighted kappa values from 0.79 to 0.98 for items and intraclass correlation coefficient values from 0.95 (Disability) to 0.99 (Motor and total score). The Bland–Altmann method, however, showed irregular concordance. PDCS standard error of measurement and convergent validity with equivalent constructs of other measures were satisfactory (≥0.70). PDCS scores significantly differed by Hoehn and Yahr stage. Conclusion: Overall, in line with previous findings, the PDCS is a feasible, acceptable, valid, reliable and precise instrument for quickly and comprehensively assessing PD patients. [ABSTRACT FROM AUTHOR]
Copyright of European Journal of Neurology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Extensive validation study of the Parkinson's Disease Composite Scale.
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  Data: <searchLink fieldCode="AR" term="%22Martinez‐Martin%2C+P%2E%22">Martinez‐Martin, P.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Radicati%2C+F%2E+G%2E%22">Radicati, F. G.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rodriguez+Blazquez%2C+C%2E%22">Rodriguez Blazquez, C.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wetmore%2C+J%2E%22">Wetmore, J.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kovacs%2C+N%2E%22">Kovacs, N.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ray+Chaudhuri%2C+K%2E%22">Ray Chaudhuri, K.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Stocchi%2C+F%2E%22">Stocchi, F.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Vuletic%2C+Vladimira%22">Vuletic, Vladimira</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Falup‐Pecurariu%2C+Cristian%22">Falup‐Pecurariu, Cristian</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Diaconu%2C+Ştefania%22">Diaconu, Ştefania</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Johansson%2C+Anders%22">Johansson, Anders</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sundgren%2C+Mathias%22">Sundgren, Mathias</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Simitsi%2C+Athima%22">Simitsi, Athima</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Stefanis%2C+Leonidas%22">Stefanis, Leonidas</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gurevich%2C+Tanya%22">Gurevich, Tanya</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Migirov‐Sanderovich%2C+Angel%22">Migirov‐Sanderovich, Angel</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ezra%2C+Adi%22">Ezra, Adi</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Guekht%2C+Alla%22">Guekht, Alla</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Popov%2C+Georgy%22">Popov, Georgy</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Stamelou%2C+Maria%22">Stamelou, Maria</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22European+Journal+of+Neurology%22">European Journal of Neurology</searchLink>. Oct2019, Vol. 26 Issue 10, p1281-1288. 8p. 6 Charts.
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  Data: <searchLink fieldCode="DE" term="%22Parkinson's+disease%22">Parkinson's disease</searchLink><br /><searchLink fieldCode="DE" term="%22Measurement+errors%22">Measurement errors</searchLink><br /><searchLink fieldCode="DE" term="%22Intraclass+correlation%22">Intraclass correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Cronbach's+alpha%22">Cronbach's alpha</searchLink><br /><searchLink fieldCode="DE" term="%22Movement+disorders%22">Movement disorders</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background and purpose: A composite instrument able to rapidly and reliably assess the most relevant motor and non‐motor afflictions suffered by Parkinson's disease (PD) patients in a real world clinic setting is an unmet need. The recently validated PD Composite Scale (PDCS) was designed to fulfil this gap as a quick, comprehensive PD assessment. The objective of this study was extensive evaluation of the PDCS's clinimetric properties using a large international sample. Methods: This was a cross‐sectional study in which the PDCS, the Movement Disorder Society Unified Parkinson's Disease Rating Scale and the Clinical Impression of Severity Index for PD were applied. Basic clinimetric attributes of the PDCS were analysed. Results: In total, 776 PD patients were included. The PDCS total score showed negligible floor and ceiling effects. Three factors (54.5% of the variance) were identified: factor 1 included motor impairment, fluctuations and disability; factor 2, non‐motor symptoms; and factor 3, tremor and complications of therapy. Cronbach's alpha was from 0.66 to 0.79. Inter‐rater reliability showed weighted kappa values from 0.79 to 0.98 for items and intraclass correlation coefficient values from 0.95 (Disability) to 0.99 (Motor and total score). The Bland–Altmann method, however, showed irregular concordance. PDCS standard error of measurement and convergent validity with equivalent constructs of other measures were satisfactory (≥0.70). PDCS scores significantly differed by Hoehn and Yahr stage. Conclusion: Overall, in line with previous findings, the PDCS is a feasible, acceptable, valid, reliable and precise instrument for quickly and comprehensively assessing PD patients. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of European Journal of Neurology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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