Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-17T15:25:46.516Z Has data issue: false hasContentIssue false
  • English
  • Français

Predictors of Cognitive Impairment Severity in Rural Patients at a Memory Clinic

Published online by Cambridge University Press:  02 December 2014

Catherine Lacny ,
Andrew Kirk ,
Debra G. Morgan  and
Chandima Karunanayake
Catherine Lacny*
Affiliation:
College of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Andrew Kirk
Affiliation:
Division of Neurology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Debra G. Morgan
Affiliation:
Canadian Centre for Health and Safety in Agriculture, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Chandima Karunanayake
Affiliation:
Canadian Centre for Health and Safety in Agriculture, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
*
College of Medicine, University of Saskatchewan, 123 Forsyth Crescent, Saskatoon, Saskatchewan, S7N 4H2, Canada. Email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Objective:

Patients with dementia benefit from early assessment and diagnosis. In an attempt to identify factors leading to delay in referral, we investigated socio-demographic, clinical, and functional predictors of greater severity of cognitive impairment in dementia patients presenting to a memory clinic in Saskatoon, Saskatchewan.

Methods:

Data collection began in 2004 at the Rural and Remote Memory Clinic in Saskatoon, where non-institutionalized patients were referred by their family physicians. The patient and caregiver questionnaires and assessments administered at the clinic day appointment provided the socio-demographic, clinical, and functional patient variables, as well as the caregiver stress and burden variables. The dependent variable was patient cognitive impairment, as measured by Modified Mini-Mental State Examination (3MS) scores. Variables underwent univariate linear regression with 3MS scores in order to determine possible associations. A multiple regression analysis was conducted to determine predictors of cognitive impairment severity at clinic presentation.

Results:

Our sample included 198 patients (62% female). The mean age was 73.9 years (SD=9.2). We found that an age and gender interaction, years of formal education, Functional Activities Questionnaire score, and Brief Symptom Inventory score were significantly associated with 3MS scores (p<0.05).

Conclusions:

Increased cognitive impairment at presentation was predicted by fewer years of formal education, poorer functional ability, and less caregiver psychological distress. There was a significant interaction between age and gender: younger females were more cognitively impaired than younger males at clinic day, while in older patients, males were more cognitively impaired than females.

Résumé

RÉSUMÉ Objectif:

Les patients atteints de démence bénéficient d'une évaluation et d'un diagnostic précoces. Nous avons examiné les facteurs de prédiction sociodémographiques, cliniques et fonctionnels d'un déficit cognitif plus sévère chez les patients atteints de démence lors de leur première consultation à une clinique de la mémoire à Saskatoon, en Saskatchewan, afm d'identifier les facteurs qui contribuent à une orientation plus tardive de ces patients vers un spécialiste.

Méthode:

Nous avons commencé à recueillir les données en 2004 à la Rural and Remote Memory Clinic à Saskatoon, une clinique de la mémoire où les patients externes sont référés par leur médecin de famille. Les données sociodémographiques, cliniques et fonctionnelles des patients ainsi que le niveau de stress et le fardeau rapporté par les soignants ont été recueillis au moyen de questionnaires et d'évaluations faites chez les patients et les soignants au moment de la visite initiale à la clinique. La variable dépendante était le déficit cognitif du patient mesuré par l'échelle de statut mental modifié (3MS). Nous avons utilisé une analyse de régression linéaire univariée pour déterminer les facteurs de prédiction de la sévérité du déficit cognitif au moment de la première visite à la clinique.

Résultats:

Notre échantillon était composé de 198 patients, dont 62% étaient des femmes et l'âge moyen était de 73,9 ans (ÉT = 9,2). Nous avons constaté qu'une interaction entre l'âge et le sexe, le nombre d'années de scolarité, le score au questionnaire d'évaluation de la capacité fonctionnelle et le score à l'inventaire bref des symptômes étaient associés de façon significative aux scores du 3MS (p < 0,05).

Conclusions:

Un niveau de scolarité plus faible, des capacités fonctionnelles moindres et moins de détresse psychologique chez le soignant étaient des facteurs de prédiction d'un déficit cognitif plus élevé au moment de la première consultation. Il existait une interaction significative au point de vue statistique entre l'âge et le sexe: les femmes plus jeunes avaient une atteinte cognitive plus sévère que les hommes plus jeunes au moment de leur première visite à la clinique alors que, chez les patients plus âgés, les hommes avaient une atteinte cognitive plus importante que les femmes.

Type
Original Articles
Information
Canadian Journal of Neurological Sciences , Volume 39 , Issue 6 , November 2012 , pp. 774 - 781
Copyright
Copyright © The Canadian Journal of Neurological 2012

References

1. Rising tide: The impact of Dementia on Canadian Society Executive Summary. Alzheimer Society of Canada. 2010.Google Scholar
2. Innes, A, Morgan, D, Kostineuk, J. Dementia care in rural and remote settings: A systematic review of informal/family caregiving. Maturitas. 2011;68:34–46.Google Scholar
3. The Canadian Study of Health and Aging Working Group. Patterns and health effects of caring for people with dementia. The impact of changing cognitive and residential status. Gerontologist. 2002;42:643–52.Google Scholar
4. Keefover, RW, Rankin, ED, Keyl, PM, et al. Dementing illnesses in rural populations: the need for research and challenges confronting investigators. J Rural Health. 1996;12(3):178–87.Google Scholar
5. Teel, CS. Rural practitioners’ experiences in dementia diagnosis and treatment. Aging Ment Health. 2004;8(5):422–9.Google Scholar
6. Statistics Canada, Census of Population, 1851 to 2006: Population, urban and rural, by province and territory. Available from: http://www40.statcan.ca/l01/cst01/demo62i-eng.htm Google Scholar
7. Projected population, by projection scenario, sex and age group as of July 1, Canada, provinces and territories, annual (CANSIM table 052-0005). Ottawa: Statistics Canada, 2010. Available from: http://www4.hrsdc.gc.ca/[email protected]?iid=33 Google Scholar
8. Bradford, A, Kunik, ME, Schulz, P, Williams, SP, Singh, H. Missed and delayed diagnosis of dementia in primary care. Alzheimer Dis Assoc Discord. 2009;23:306–14.CrossRefGoogle ScholarPubMed
9. Innes, A, Cox, S, Smith, A, Mason, A. Service provision for people with dementia in rural Scotland: difficulties and innovations. Dementia. 2006;5(2):249–70.Google Scholar
10. Morgan, DG, Crossley, M, Kirk, A, et al. Improving access to dementia care: development and evaluation of a rural and remote memory clinic. Aging Ment Health. 2009;13:17–30.Google Scholar
11. Morgan, DG, Crossley, M, Kirk, A, et al. Evaluation of telehealth for preclinic assessment and follow-up in an interprofessional rural and remote memory clinic. sJ App Gerontol. 2011;30(3):304–31.Google Scholar
12. Boller, F, Verny, M, Hugonot-Diener, L, Saxton, J. Clinical features and assessment of severe dementia. A review. Eur J Neurol. 2002;9:125–36.Google Scholar
13. McKhann, G, Drachman, D, Folstein, M, et al. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA work group under the auspices of department of health and human services task force on Alzheimer’s disease. Neurology. 1984; 34:939–44.Google Scholar
14. McKeith, IG, Galasko, D, Kosaka, K, et al. Consensus guidelines for the clinical and pathologic diagnosis of dementia with Lewy bodies (DLB): report of the consortium on DLB international workshop. Neurology. 1996;47:1113–24.Google Scholar
15. Roman, GC, Tatemichi, TK, Erkinjuntti, T, et al. Vascular dementia: diagnostic criteria for research studies. Report of the NINDS-AIREN International Workshop. Neurology. 1993;43(2):250–60.Google Scholar
16. Neary, D, Snowden, JS, Gustafson, L, et al. Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology. 1998;51:1546–54.CrossRefGoogle ScholarPubMed
17. McNiven, C, Puderer, H, Janes, D. Census metropolitan area and census agglomeration influenced zones (MIZ): a description of the methodology. 2000. Ottawa: Statistics Canada, Geography Division .Google Scholar
18. Pfeffer, R, Kurosaki, T, Harrah, C, Chance, J, Filos, S. Measurement of functional activities in older adults in the community. J Gerontology. 1982;37:323–9.Google Scholar
19. Cummings, J, Mega, M, Gray, K, Rosengerg-Thompson, S, Carusi, D, Gornbien, J. The Neuropsychiatric Inventory: Comprehensive assessment of psychopathology in dementia. Neurology. 1994; 44:2308–14.Google Scholar
20. Bedard, M, Molloy, M, Squire, L, Dubois, S, Lever, J, O’Donnell, M. The Zarit Burden Interview: A new short version and screening version. Gerontologist. 2001;41:652–7.Google Scholar
21. O’Rourke, N, Tuokko, H. Psychometric properties of an abridged version of the Zarit Burden Interview within a representative Canadian caregiver sample. Gerontologist. 2003;43:121–7.Google Scholar
22. Derogatis, L, Melisaratos, N. The brief symptom inventory: An introductory report. Psychol Med. 1983;13:595–605.Google Scholar
23. Teng, EL, Chui, HC. The modified Mini-Mental State (3MS) Examination. J Clin Psychiatr. 1987;48:314–8.Google Scholar
24. Folstein, MF, Folstein, SE, McHugh, PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189–98.Google Scholar
25. McDowell, I, Kristjansson, B, Hill, GB, Hebert, R. Community screening for dementia: the Mini Mental State Exam (MMSE) and the Modified Mini-Mental State Exam (3MS) Compared. J Clin Epidemiol. 1997;50:377–83.Google Scholar
26. Ngandu, T, von Strauss, E, Helkala, EL, et al. Education and dementia: what lies behind the association? Neurology. 2007;69: 1442–50.Google Scholar
27. Karp, A, Kareholt, I, Qiu, C, Bellander, T, Winblad, B, Fratiglioni, L. Relation of education and occupation-based socioeconomic status to incident Alzheimer’s disease. Am J Epidemiol. 2004; 159:175–83.Google Scholar
28. Chen, J, Lin, K, Chen, Y. Risk Factors for Dementia. J Formos Med Assoc. 2009;108(10):754–61.Google Scholar
29. Scarmeas, N, Albert, SM, Manly, JJ, Stern, Y. Education and rates of cognitive decline in incident Alzheimer’s disease. J Neurol Neurosurg Psychiatry. 2006;77:308–16.Google Scholar
30. Musicco, M, Salamone, G, Caltagirone, C, et al. Neuropsychological predictors of rapidly progression patient with Alzheimer’s disease. Dement Geriatr Cogn. 2010;30(3):219–28.Google Scholar
31. Mussico, M, Palmer, K, Salamone, G, et al. Predictors of progression of cognitive decline in Alzheimer’s disease: the role of vascular and sociodemographic factors. J Neurol. 2009;256:1288–95.Google Scholar
32. Paradise, M, Cooper, C, Livingston, G. Systematic review of the effect of education on survival in Alzheimer’s disease. Int Psychogeriatrics. 2009;21:25–32.Google Scholar
33. Wilson, RS, Hebert, LE, Scherr, PA, Barnes, LL, Mendes de Leon, CF, Evans, DA. Educational attainment and cognitive decline in old age. Neurology. 2009;72:460–5.Google Scholar
34. Moritz, DJ, Petitti, DB. Association of education with reported age of onset and severity of Alzheimer’s disease at presentation: implication for the use of clinical samples. Am J Epidemiol. 1993;137:456–62.Google Scholar
35. Marra, TA, Pereira, DS, Faria, CDCM, Tirado, LSM, Pereira, LSM. Influence of socio-demographic, clinical and functional factors on the severity of dementia. Arch Gerontol Geriat. 2011;53: 210–5.Google Scholar
36. Njegovan, V, Man-Son-Hing, M, Mitchell, SL, Molnar, FJ. The hierarchy of functional loss associated with cognitive decline in older persons. J Gerontol A Biol Sci Med Sci. 2001;56A: M638–43.Google Scholar
37. Cattel, C, Gambassi, G, Sgadari, A, Zuccala, G, Carbonin, P, Bernabei, R. Correlates of delayed referral for the diagnosis of dementia in an outpatient population. J Gerontol A Biol Sci Med Sci. 2000;55A:M98–M102.Google Scholar
38. Swanwich, GRJ, Coen, RF, Maguire, CP, et al. The association between demographic factors, disease severity and the durations of symptoms at clinical presentation in elderly people with dementia. Age Ageing. 1999;28:295–9.Google Scholar
39. Ott, BR, Tate, CA, Gordon, NM, Heindel, WC. Gender differences in the behavioural manifestations of Alzheimer’s disease. J Am Geriatr Soc. 1996;44:583–7.Google Scholar
40. Steward, N, Morgan, D, Cammer, D, Karunanayake, C, Minish, D. Gender differences in caregiver distress over time. Poster presented at the 26th International Conference of Alzheimer’s Disease International, March 2011, Toronto, Ont. Google Scholar
41. Statistics Canada, Life tables, Canada, Provinces and Territories, 2000-02. Life expectancy at birth, by sex, by province: http://www.statcan.gc.ca/tables-tableaux/sum-som/l01/cst01/health26-eng.htm Google Scholar