The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Validity of the MoCA and MMSE in the detection of MCI and dementia in Parkinson disease
Open accessAbstract
BACKGROUND: Due to the high prevalence of mild cognitive impairment (MCI) and dementia in Parkinson disease (PD), routine cognitive screening is important for the optimal management of patients with PD. The Montreal Cognitive Assessment (MoCA) is more sensitive than the commonly used Mini-Mental State Examination (MMSE) in detecting MCI and dementia in patients without PD, but its validity in PD has not been established. METHODS: A representative sample of 132 patients with PD at 2 movement disorders centers was administered the MoCA, MMSE, and a neuropsychological battery with operationalized criteria for deficits. MCI and PD dementia (PDD) criteria were applied by an investigator blinded to the MoCA and MMSE results. The discriminant validity of the MoCA and MMSE as screening and diagnostic instruments was ascertained. RESULTS: Approximately one third of the sample met diagnostic criteria for a cognitive disorder (12.9% PDD and 17.4% MCI). Mean (SD) MoCA and MMSE scores were 25.0 (3.8) and 28.1 (2.0). The overall discriminant validity for detection of any cognitive disorder was similar for the MoCA and the MMSE (receiver operating characteristic area under the curve [95% confidence interval]): MoCA (0.79 [0.72, 0.87]) and MMSE (0.76 [0.67, 0.85]), but as a screening instrument the MoCA (optimal cutoff point = 26/27, 64% correctly diagnosed, lack of ceiling effect) was superior to the MMSE (optimal cutoff point = 29/30, 54% correctly diagnosed, presence of ceiling effect). CONCLUSIONS: The Montreal Cognitive Assessment, but not the Mini-Mental State Examination, has adequate psychometric properties as a screening instrument for the detection of mild cognitive impairment or dementia in Parkinson disease. However, a positive screen using either instrument requires additional assessment due to suboptimal specificity at the recommended screening cutoff point.
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Cites
The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment
Nasreddine, Z. S., Phillips, N. A., Bédirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J. L., & Chertkow, H. (2005) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2005.53221.x · Cited by 25,553
Sheikh (1986) · doi:10.1300/j018v05n01_09 · Cited by 7,236
Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L. ‐., Nordberg, A., Bäckman, L., Albert, M., Almkvist, O., et al. (2004) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2004.01380.x · Cited by 4,946
Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Lijmer, J. G., Moher, D., Rennie, D., & de Vet, H. C. W. (2003) · BMJ · doi:10.1136/bmj.326.7379.41 · Cited by 3,215
Towards Complete and Accurate Reporting of Studies of Diagnostic Accuracy: The STARD Initiative
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Lijmer, J. G., Moher, D., Rennie, D., & de Vet, H. C. W. (2003) · Radiology · doi:10.1148/radiol.2261021292 · Cited by 3,215
Clinical diagnostic criteria for dementia associated with Parkinson’s disease
Emre, M., Aarsland, D., Brown, R., Burn, D. J., Duyckaerts, C., Mizuno, Y., Broe, G. A., Cummings, J., Dickson, D. W., Gauthier, S., et al. (2007) · Movement Disorders · doi:10.1002/mds.21507 · Cited by 3,027
Diagnostic Criteria for Parkinson Disease
Gelb, D. J., Oliver, E., & Gilman, S. (1999) · Archives of Neurology · doi:10.1001/archneur.56.1.33 · Cited by 2,822
Individual-patient monitoring in clinical practice: are available health status surveys adequate?
McHorney, C. A., & Tarlov, A. R. (1995) · Quality of Life Research · doi:10.1007/bf01593882 · Cited by 2,206
Cognitive profile of patients with newly diagnosed Parkinson disease
Muslimović, D., Post, B., Speelman, J. D., & Schmand, B. (2005) · Neurology · doi:10.1212/01.wnl.0000180516.69442.95 · Cited by 1,007
Cognitive impairment in incident, untreated Parkinson disease: The Norwegian ParkWest Study
Aarsland, D., Brønnick, K., Larsen, J. P., Tysnes, O. B., & Alves, G. (2009) · Neurology · doi:10.1212/01.wnl.0000338632.00552.cb · Cited by 625
Cited by
Litvan, I., Goldman, J. G., Tröster, A. I., Schmand, B. A., Weintraub, D., Petersen, R. C., Mollenhauer, B., Adler, C. H., Marder, K., Williams‐Gray, C. H., et al. (2012) · Movement Disorders · doi:10.1002/mds.24893 · Cited by 2,609
Self-citationParkinson disease-associated cognitive impairment
Aarsland, D., Batzu, L., Halliday, G. M., Geurtsen, G. J., Ballard, C., Ray Chaudhuri, K., & Weintraub, D. (2021) · Nature Reviews Disease Primers · doi:10.1038/s41572-021-00280-3 · Cited by 1,371
Self-citationA re‐examination of Montreal Cognitive Assessment (MoCA) cutoff scores
Carson, N., Leach, L., & Murphy, K. J. (2018) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.4756 · Cited by 935
EFNS/MDS‐ES recommendations for the diagnosis of Parkinson's disease
Berardelli, A., Wenning, G. K., Antonini, A., Berg, D., Bloem, B. R., Bonifati, V., Brooks, D., Burn, D. J., Colosimo, C., Fanciulli, A., et al. (2013) · European Journal of Neurology · doi:10.1111/ene.12022 · Cited by 489
Parkinson’s disease dementia: a neural networks perspective
Gratwicke, J., Jahanshahi, M., & Foltynie, T. (2015) · Brain · doi:10.1093/brain/awv104 · Cited by 435
Metadata
- Authors
- Hoops, S., Nazem, S., Siderowf, A. D., Duda, J. E., Xie, S. X., Stern, M. B., & Weintraub, D.
- Venue
- Neurology
- Published
- 2009-11-24
- Volume
- 73
- Issue
- 21
- Pages
- 1738-1745
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- OpenAlex
- W2014636870
- Cited by
- 1,260
- References
- 11
- FWCI
- 19.93
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Hoops, S., Nazem, S., Siderowf, A. D., Duda, J. E., Xie, S. X., Stern, M. B., & Weintraub, D. (2009). Validity of the MoCA and MMSE in the detection of MCI and dementia in Parkinson disease. Neurology. https://doi.org/10.1212/wnl.0b013e3181c34b47
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