Hostname: page-component-848d4c4894-jbqgn Total loading time: 0 Render date: 2024-07-05T04:04:52.960Z Has data issue: false hasContentIssue false
  • English
  • Français

Ascertainment of Chronic Diseases in the Canadian Longitudinal Study on Aging (CLSA), Systematic Review*

Published online by Cambridge University Press:  01 September 2009

Parminder S. Raina ,
Christina Wolfson ,
Susan A. Kirkland ,
Homa Keshavarz ,
Lauren E. Griffith ,
Christopher Patterson ,
Jennifer Uniat ,
Geoff Strople ,
Amélie Pelletier  and
Camille L. Angus
Parminder S. Raina*
Affiliation:
McMaster Evidence-based Practice Center, McMaster University Department of Clinical Epidemiology and Biostatistics, McMaster University
Christina Wolfson
Affiliation:
Division of Clinical Epidemiology, McGill University Health Centre Department of Epidemiology & Biostatistics and Occupational Health, and Department of Medicine, McGill University
Susan A. Kirkland
Affiliation:
Department of Community Health and Epidemiology, Dalhousie University Department of Medicine, Dalhousie University
Homa Keshavarz
Affiliation:
McMaster Evidence-based Practice Center, McMaster University Department of Clinical Epidemiology and Biostatistics, McMaster University
Lauren E. Griffith
Affiliation:
McMaster Evidence-based Practice Center, McMaster University Department of Clinical Epidemiology and Biostatistics, McMaster University
Christopher Patterson
Affiliation:
Department of Medicine, McMaster University
Jennifer Uniat
Affiliation:
Division of Clinical Epidemiology, McGill University Health Centre
Geoff Strople
Affiliation:
Department of Community Health and Epidemiology, Dalhousie University
Amélie Pelletier
Affiliation:
Division of Clinical Epidemiology, McGill University Health Centre
Camille L. Angus
Affiliation:
Department of Community Health and Epidemiology, Dalhousie University
*
†Correspondence and requests for offprints should be sent to: / La correspondance et les demandes de tirés-à-part doivent être adressés à : Parminder S. Raina, PhD Professor/Director McMaster University, Evidence-based Practice Center 1280 Main St. W. DTC Room 310 Hamilton, Ontario, L8S 4L8 praina@mcmaster.ca
Get access Rights & Permissions [Opens in a new window]

Abstract

Standard clinical diagnostic procedures are often inappropriate and frequently not feasible to apply in population-based studies, yet ascertaining accurate disease status is essential. We conducted a systematic review to identify algorithms, criteria, and tools used to ascertain 17 chronic diseases, and assessed the feasibility of developing algorithms for the CLSA. Of the 29,616 citations screened, 668 papers met all inclusion criteria. We determined that the information included in a disease algorithm will differ by condition type. The diagnosis of some symptomatic conditions, such as osteoarthritis and arthritis, will require substantiation by clinical criteria (e.g., x-rays, bone density measurement) while other conditions, such as depression, will rely solely on self-report. Asymptomatic conditions, such as hypertension, are more difficult to ascertain by self-report and will require additional physiologic measures (e.g., blood pressure) as well as laboratory measures (e.g., glucose). This pilot study identified the tools necessary to develop disease ascertainment algorithms.

Résumé

Les procédures diagnostiques cliniques standards sont souvent inappropriées et fréquemment non applicables dans des études basées sur la population; pourtant, vérifier le statut précis d’une maladie est essentiel. Nous avons fait une revue systématique pour identifier des algorithmes, des critères, et des outils utilisés pour identifier 17 maladies chroniques, et avons fait la praticabilité de développer des algorithmes pour l’ÉLCV. Des 29 616 citations examinées, 668 papiers ont rencontré tous les critères d’inclusion. Nous avons déterminé que l’information incluse dans un algorithme de maladie différera selon le type de condition. Le diagnostic de quelques conditions symptomatiques, telles l’arthrose et l’arthrite, exigera la justification par des critères cliniques (par exemple, rayons X, mesure de densité osseuse) tandis que d’autres conditions, telles la dépression, se baseront seulement sur les dires des individus. Les conditions asymptomatiques, telles l’hypertension, sont plus difficiles à vérifier par les dires des individus et exigeront des mesures physiologiques additionnelles (par exemple, tension artérielle) et des mesures de laboratoire (par exemple, glucose). Cette étude pilote a identifié les outils nécessaires pour développer des algorithmes d’évaluation de diagnostic.

Keywords

l’algorithme d’évaluation de la maladierevue systématiquediagnosemaladie chroniquesanté de la populationvieillissementétude éventuelledisease asertainment algorithmsystematic reviewdiagnosischronic diseasepopulation healthagingprospective study
Type
Articles
Information
Canadian Journal on Aging / La Revue canadienne du vieillissement , Volume 28 , Issue 3: Special Issue on the Canadian Longitudinal Study on Aging (CLSA) , September 2009 , pp. 275 - 285
Copyright
Copyright © Canadian Association on Gerontology 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

Parminder Raina holds a Canadian Institute of Health Research Investigator award, an Ontario Premier’s Research Excellence award, and a Labarge Chair in Research and Knowledge Application for Optimal Aging.

Funding for the Canadian Longitudinal Study on Aging was provided by the Canadian Institutes of Health Research (CIHR), Le Fonds de la recherche en santé du Québec (FRSQ)–Réseau québécois de recherche sur le vieillissement.

References

1.Raina, P, Kirkland, S, Wolfson, C, Keshavarz, H. The Canadian Longitudinal Study on Aging: development and evaluation of disease ascertainment algorithms feasibility study protocol. Available from: URL: http://www.clsa-elcv.ca/images/uploads/Study_9.pdf 2009.Google Scholar
2.Cook, DJ, Mulrow, CD, Haynes, RB. Systematic reviews: Synthesis of best evidence for clinical decisions. Ann Intern Med 1997;126(5):376–80.CrossRefGoogle ScholarPubMed
3.Cook, DJ, Sackett, DL, Spitzer, WO. Methodologic guidelines for systematic reviews of randomized control trials in health-care from the Potsdam consultation on meta-analysis. J Clin Epidemiol 1995;48(1):167–71.CrossRefGoogle ScholarPubMed
4.O’Blenis, P, Garritty, C. The electronic systematic review handbook: practical concepts and methods for electronic screening and data abstraction. Ottawa (Canada): TrialStat Corporation, 2004.Google Scholar
5.TrialStat. TrialStat beyond conventional thinking. Available from: URL: http://www.trialstat.com 2007.Google Scholar
6.Di Bari, M. Disease diagnostic ascertainment algorithm. ICARe Dicomano Study. Personal comm. 4-15-2005.Google Scholar
7.Corti, MC. Disease diagnostic ascertainment algorithm. PRO.V.A. Study. Personal comm. 3-18-2005.Google Scholar
8.Guralnik, JM. Disease diagnostic ascertainment algorithm. Women’s Health and Aging Study (WHAS). 12-12-2004.Google Scholar
9.Fitzpatrick, AL, DeMont, R. Disease diagnostic ascertainment algorithm. Cardiovascular Health Study (CHS). Personal comm, 2000.Google Scholar
10.Psaty, BM, Kuller, LH, Bild, D, Burke, GL, Kittner, SJ, Mittelmark, M, et al. . Methods of assessing prevalent cardiovascular disease in the Cardiovascular Health Study. Ann Epidemiol 1995;5(4):270–77.CrossRefGoogle ScholarPubMed
11.Fried, LP, Kasper, JD, Williamson, JD, Skinner, EA, Morris, CD, Hochberg, MC. The women’s health and aging study: disease ascertainment algorithms. Women’s Health and Aging Study. Bethesda (MD): National Institute on Aging. [NIH publication No. 95–4009, App E] 1995:E1–E3.Google Scholar
12.Guralnik, JM, Fried, LP, Simonsick, EM, Williamson, JD, Skinner, EA, Morris, CD, et al. . The women’s health and aging study: health and social characteristics of older women with disability. Women’s Health and Aging Study. Bethesda, MD: National Institute on Aging. [NIH publication No. 95–4009, App E] 1995:E1–E3.CrossRefGoogle Scholar
13.Volmink, J, Newton, J, Hicks, N, Sleight, P, Fowler, G, Neil, HA. Coronary event and case fatality rates in an English population: results of the Oxford myocardial infarction incidence study. The Oxford Myocardial Infarction Incidence Study Group. Heart (British Cardiac Society), 1998;80:40–4.Google Scholar
14.Sato, T, Yoshinouchi, T, Sakamoto, T, Fujieda, H, Murao, S, Sato, H, et al. . Hepatocyte growth factor (HGF): a new biochemical marker for acute myocardial infarction. Heart Vessels 1997;12(5):241–46.CrossRefGoogle ScholarPubMed
15.Zimmerman, J, Fromm, R, Meyer, D, Boudreaux, A, Wun, C, Smalling, R, et al. . Diagnostic marker cooperative study for the diagnosis of myocardial infarction. Circulation 1999;99(13):1671–77.CrossRefGoogle ScholarPubMed
16.Margolis, JR, Gillum, RF, Feinleib, M, Brasch, R, Fabsitz, R. Community surveillance for coronary heart disease: Framingham Cardiovascular Disease survey. Comparisons with the Framingham Heart Study and previous short-term studies. Am J Cardiol 1976;37(1):61–7.CrossRefGoogle ScholarPubMed
17.Rose, G. The diagnosis of ischaemic heart pain and intermittent claudication in field surveys. Bull World Health Organ 1962;27(6):645–58.Google ScholarPubMed
18.The Italian Longitudinal Study on Aging Working Group. Prevalence of chronic diseases in older Italians: comparing self-reported and clinical diagnoses. Int J Epidemiol 1997;26(5):995–1002.CrossRefGoogle Scholar
19.Toole, JF, Lefkowitz, DS, Chambless, LE, Wijnberg, L, Paton, CC, Heiss, G. Self-reported transient ischemic attack and stroke symptoms: methods and baseline prevalence. The ARIC study, 1987-1989. Am J Epidemiol 1996; 144(9):849–56.CrossRefGoogle ScholarPubMed
20.Asplund, K, Bonita, R, Kuulasmaa, K, Rajakangas, AM, Feigin, V, Schaedlich, H, et al. . Multinational comparisons of stroke epidemiology: evaluation of case ascertainment in the WHO MONICA Stroke Study. Stroke 1995;26(3):355–60.CrossRefGoogle ScholarPubMed
21.Del Brutto, O, Idrovo, L, Santibanez, R, Diaz-Calderon, E, Mosquera, A, Cuesta, F, et al. . Door-to-door survey of major neurological diseases in rural Ecuador. The Atahualpa Project: methodological aspects. Neuroepidemiology 2004;23(6):310–16.CrossRefGoogle ScholarPubMed