BACKGROUND: The extent and patterns of cognitive change regularly occurring in elderly patients who experience prolonged hospitalisation have not been well examined. OBJECTIVE: To describe patterns of cognitive change during and 6 months after hospitalisation and to identify prognostic factors associated with different patterns of changes. DESIGN: A prospective cohort study. SETTING: Five med-surgical units at a tertiary hospital in Taipei, Taiwan. PARTICIPANTS: Patients ≥65 years old without preexisting profound cognitive impairment (Mini-Mental State Examination score ≥20) and with an expected hospital length of stay >5 days were drawn from consecutive admissions. Of 351 patients, 82.9% (138 women, 153 men, mean age=71.6 years) completed all four scheduled assessments. METHODS: Cognition was measured by the Mini-Mental State Examination at 4 times: admission, discharge, and 3 and 6 months post-discharge. Possible prognostic factors at admission included demographics, comorbidities, number of medications, serum haemoglobin, length of hospital stay, and surgery. RESULTS: Four cognitive-change patterns with a high prevalence of decline were identified by cluster analysis. The worsening then improve group (n=47) had a deep V-shape with a mean fluctuation of 3.9 points on the Mini-Mental State Examination, and the low continuous group (n=83) had little change. Both the start high and decline (n=66) and start low and decline (n=95) groups showed persistent and accelerated declines, with baseline cognitive scores of 29.1 and 25.5 points, respectively. Predictor variables at admission for different patterns of cognitive change were age, total education (years), cardiovascular comorbidities, number of medications, functional and nutritional status, depressive symptoms, surgical treatment, and haemoglobin level <12 g/dL. CONCLUSIONS: Cognitive decline during and after hospitalisation shows four heterogeneous patterns of change. Different patterns of change were predicted by age, education, cardiovascular comorbidities, number of medications, functional and nutritional status, depressive symptoms, surgical treatment, and haemoglobin level <12 g/dL, most of which are potentially modifiable factors.
BACKGROUND: The extent and patterns of cognitive change regularly occurring in elderly patients who experience prolonged hospitalisation have not been well examined. OBJECTIVE: To describe patterns of cognitive change during and 6 months after hospitalisation and to identify prognostic factors associated with different patterns of changes. DESIGN: A prospective cohort study. SETTING: Five med-surgical units at a tertiary hospital in Taipei, Taiwan. PARTICIPANTS: Patients ≥65 years old without preexisting profound cognitive impairment (Mini-Mental State Examination score ≥20) and with an expected hospital length of stay >5 days were drawn from consecutive admissions. Of 351 patients, 82.9% (138 women, 153 men, mean age=71.6 years) completed all four scheduled assessments. METHODS: Cognition was measured by the Mini-Mental State Examination at 4 times: admission, discharge, and 3 and 6 months post-discharge. Possible prognostic factors at admission included demographics, comorbidities, number of medications, serum haemoglobin, length of hospital stay, and surgery. RESULTS: Four cognitive-change patterns with a high prevalence of decline were identified by cluster analysis. The worsening then improve group (n=47) had a deep V-shape with a mean fluctuation of 3.9 points on the Mini-Mental State Examination, and the low continuous group (n=83) had little change. Both the start high and decline (n=66) and start low and decline (n=95) groups showed persistent and accelerated declines, with baseline cognitive scores of 29.1 and 25.5 points, respectively. Predictor variables at admission for different patterns of cognitive change were age, total education (years), cardiovascular comorbidities, number of medications, functional and nutritional status, depressive symptoms, surgical treatment, and haemoglobin level <12 g/dL. CONCLUSIONS: Cognitive decline during and after hospitalisation shows four heterogeneous patterns of change. Different patterns of change were predicted by age, education, cardiovascular comorbidities, number of medications, functional and nutritional status, depressive symptoms, surgical treatment, and haemoglobin level <12 g/dL, most of which are potentially modifiable factors.
Authors: Phillip J Schulte; David O Warner; David P Martin; Atousa Deljou; Michelle M Mielke; David S Knopman; Ronald C Petersen; Toby N Weingarten; Matthew A Warner; Alejandro A Rabinstein; Andrew C Hanson; Darrell R Schroeder; Juraj Sprung Journal: Crit Care Med Date: 2019-08 Impact factor: 7.598
Authors: Junxia X Tang; Feras Mardini; Breanna M Caltagarone; Sean T Garrity; Rosie Q Li; Shannon L Bianchi; Olubusola Gomes; Frank M Laferla; Roderic G Eckenhoff; Maryellen F Eckenhoff Journal: Alzheimers Dement Date: 2011-07-13 Impact factor: 21.566
Authors: Bryan D James; Robert S Wilson; Ana W Capuano; Patricia A Boyle; Raj C Shah; Melissa Lamar; E Wesley Ely; David A Bennett; Julie A Schneider Journal: Neurology Date: 2019-01-11 Impact factor: 9.910
Authors: Bryan D James; Robert S Wilson; Ana W Capuano; Patricia A Boyle; Raj C Shah; Melissa Lamar; E Wesley Ely; David A Bennett; Julie A Schneider Journal: Ann Neurol Date: 2019-10-23 Impact factor: 10.422
Authors: Juraj Sprung; David S Knopman; Ronald C Petersen; Michelle M Mielke; Toby N Weingarten; Maria Vassilaki; David P Martin; Phillip J Schulte; Andrew C Hanson; Darrell R Schroeder; Mariana L Laporta; Robert J White; Prashanthi Vemuri; David O Warner Journal: J Am Geriatr Soc Date: 2020-10-31 Impact factor: 7.538