Noll L Campbell1,2,3, Kathleen A Lane4, Sujuan Gao2,4, Malaz A Boustani2,3,5, Fred Unverzagt6. 1. Purdue University College of Pharmacy, West Lafayette, IN. 2. Indiana University Center for Aging Research, Regenstrief Institute, Inc., Indianapolis, IN. 3. Sandra Eskenazi Center for Brain Care Innovation, Eskenazi Health, Indianapolis, IN. 4. Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN. 5. Department of Medicine, Indiana University School of Medicine, Indianapolis, IN. 6. Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN.
Abstract
STUDY OBJECTIVE: To determine the influence of anticholinergic medications on transitions in cognitive diagnosis of older adults in primary care. DESIGN: This observational cohort study was conducted over a mean follow-up of 3.2 years. Anticholinergic exposure was defined by pharmacy dispensing and claims records. Cognitive diagnosis was performed by an expert panel at baseline and annually up to 4 years. DATA SOURCE: Medication exposure and other clinical data were extracted from the Indiana Network for Patient Care (INPC). The cognitive diagnosis was derived from a cognitive screening and diagnosis study. PARTICIPANTS: A total of 350 adults 65 years and older without dementia and receiving primary care in a safety net health care system. MEASUREMENT AND MAIN RESULTS: Cognitive diagnosis followed a two-phase screening and consensus-based neuropsychiatric examination to determine a baseline diagnosis as normal cognition, mild cognitive impairment (MCI), or dementia, with a follow-up neuropsychiatric examination and consensus-based diagnosis repeated annually. The Anticholinergic Cognitive Burden scale was used to identify anticholinergics dispensed up to 10 years before enrollment and annually throughout the study. A total standard daily dose of anticholinergics was calculated by using pharmacy dispensing data from the INPC. Among 350 participants, a total of 978 diagnostic assessments were completed over a mean follow-up of 3.2 years. Compared with stable cognition, increasing use of strong anticholinergics calculated by total standard daily dose increased the odds of transition from normal cognition to MCI (odds ratio [OR] 1.15, 95% confidence interval [CI] 1.01-1.31, p = 0.0342). Compared with stable MCI, strong anticholinergics did not influence the reversion of MCI to normal cognition (OR 0.95, 95% CI 0.86-1.05, p = 0.3266). CONCLUSION: De-prescribing interventions in older adults with normal cognition should test anticholinergics as potentially modifiable risk factors for cognitive impairment.
STUDY OBJECTIVE: To determine the influence of anticholinergic medications on transitions in cognitive diagnosis of older adults in primary care. DESIGN: This observational cohort study was conducted over a mean follow-up of 3.2 years. Anticholinergic exposure was defined by pharmacy dispensing and claims records. Cognitive diagnosis was performed by an expert panel at baseline and annually up to 4 years. DATA SOURCE: Medication exposure and other clinical data were extracted from the Indiana Network for Patient Care (INPC). The cognitive diagnosis was derived from a cognitive screening and diagnosis study. PARTICIPANTS: A total of 350 adults 65 years and older without dementia and receiving primary care in a safety net health care system. MEASUREMENT AND MAIN RESULTS: Cognitive diagnosis followed a two-phase screening and consensus-based neuropsychiatric examination to determine a baseline diagnosis as normal cognition, mild cognitive impairment (MCI), or dementia, with a follow-up neuropsychiatric examination and consensus-based diagnosis repeated annually. The Anticholinergic Cognitive Burden scale was used to identify anticholinergics dispensed up to 10 years before enrollment and annually throughout the study. A total standard daily dose of anticholinergics was calculated by using pharmacy dispensing data from the INPC. Among 350 participants, a total of 978 diagnostic assessments were completed over a mean follow-up of 3.2 years. Compared with stable cognition, increasing use of strong anticholinergics calculated by total standard daily dose increased the odds of transition from normal cognition to MCI (odds ratio [OR] 1.15, 95% confidence interval [CI] 1.01-1.31, p = 0.0342). Compared with stable MCI, strong anticholinergics did not influence the reversion of MCI to normal cognition (OR 0.95, 95% CI 0.86-1.05, p = 0.3266). CONCLUSION: De-prescribing interventions in older adults with normal cognition should test anticholinergics as potentially modifiable risk factors for cognitive impairment.
Authors: Sujuan Gao; Frederick W Unverzagt; Kathleen S Hall; Kathleen A Lane; Jill R Murrell; Ann M Hake; Valerie Smith-Gamble; Hugh C Hendrie Journal: Am J Geriatr Psychiatry Date: 2013-07-03 Impact factor: 4.105
Authors: Shannon L Risacher; Brenna C McDonald; Eileen F Tallman; John D West; Martin R Farlow; Fredrick W Unverzagt; Sujuan Gao; Malaz Boustani; Paul K Crane; Ronald C Petersen; Clifford R Jack; William J Jagust; Paul S Aisen; Michael W Weiner; Andrew J Saykin Journal: JAMA Neurol Date: 2016-06-01 Impact factor: 18.302
Authors: Antonella Caccamo; Salvatore Oddo; Lauren M Billings; Kim N Green; Hilda Martinez-Coria; Abraham Fisher; Frank M LaFerla Journal: Neuron Date: 2006-03-02 Impact factor: 17.173
Authors: Gobhathai Sittironnarit; David Ames; Ashley I Bush; Noel Faux; Leon Flicker; Jonathan Foster; Sarah Hilmer; Nicola T Lautenschlager; Paul Maruff; Colin L Masters; Ralph N Martins; Christopher Rowe; Cassandra Szoeke; Kathryn A Ellis Journal: Dement Geriatr Cogn Disord Date: 2011-03-09 Impact factor: 2.959
Authors: Noll L Campbell; Anthony J Perkins; Pamela Bradt; Sinem Perk; Ronald C Wielage; Malaz A Boustani; Daniel B Ng Journal: Pharmacotherapy Date: 2016-11-05 Impact factor: 4.705
Authors: Shelly L Gray; Sascha Dublin; Onchee Yu; Rod Walker; Melissa Anderson; Rebecca A Hubbard; Paul K Crane; Eric B Larson Journal: BMJ Date: 2016-02-02
Authors: Taylor J Krivanek; Seth A Gale; Brittany M McFeeley; Casey M Nicastri; Kirk R Daffner Journal: J Alzheimers Dis Date: 2021 Impact factor: 4.472
Authors: Richard J Holden; Noll L Campbell; Ephrem Abebe; Daniel O Clark; Denisha Ferguson; Kunal Bodke; Malaz A Boustani; Christopher M Callahan Journal: Res Social Adm Pharm Date: 2019-02-26
Authors: Mary Ganguli; Yichen Jia; Tiffany F Hughes; Beth E Snitz; Chung-Chou H Chang; Sarah B Berman; Kevin J Sullivan; M Ilyas Kamboh Journal: J Am Geriatr Soc Date: 2018-11-16 Impact factor: 5.562
Authors: Ephrem Abebe; Noll L Campbell; Daniel O Clark; Wanzhu Tu; Jordan R Hill; Addison B Harrington; Gracen O'Neal; Kimberly S Trowbridge; Christian Vallejo; Ziyi Yang; Na Bo; Alexxus Knight; Khalid A Alamer; Allie Carter; Robin Valenzuela; Philip Adeoye; Malaz A Boustani; Richard J Holden Journal: Res Social Adm Pharm Date: 2020-10-22
Authors: Alexandra J Weigand; Mark W Bondi; Kelsey R Thomas; Noll L Campbell; Douglas R Galasko; David P Salmon; Daniel Sewell; James B Brewer; Howard H Feldman; Lisa Delano-Wood Journal: Neurology Date: 2020-09-02 Impact factor: 9.910