Ascertainment of chronic diseases in the Canadian longitudinal study on aging (CLSA), systematic review.
ABSTRACTStandard 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.
Raina
Parminder S
PS
McMaster Evidence-based Practice Center, McMaster University, Canada.
Wolfson
Christina
C
Kirkland
Susan A
SA
Keshavarz
Homa
H
Griffith
Lauren E
LE
Patterson
Christopher
C
Uniat
Jennifer
J
Strople
Geoff
G
Pelletier
Amélie
A
Angus
Camille L
CL
D000375:Aging; D000465:Algorithms; D002170:Canada; D002908:Chronic Disease / Q000453:epidemiology*; D006801:Humans; D008137:Longitudinal Studies; D008403:Mass Screening; D010865:Pilot Projects