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Cheung Y.B.,National University of Singapore | Cheung Y.B.,University of Tampere | Xu Y.,National University of Singapore | Feng L.,National University of Singapore | And 7 more authors.
American Journal of Geriatric Psychiatry | Year: 2015

Objective: The conventional practice of assessing cognitive status and monitoring change over time in older adults using normative values of the Mini-Mental State Exam (MMSE) based on age bands is imprecise. Moreover, population-based normative data on changes in MMSE score over time are scarce and crude because they do not include age- and education-specific norms. This study aims to develop unconditional standards for assessing current cognitive status and conditional standards that take prior MMSE score into account for assessing longitudinal change, with percentile curves as smooth functions of age. Methods: Cross-sectional and longitudinal data of a modified version of the MMSE for 2,026 older Chinese adults from the Singapore Longitudinal Aging Study, aged 55-84, in Singapore were used to estimate quantile regression coefficients and create unconditional standards and conditional standards. Results: We presented MMSE percentile curves as a smooth function of age in education strata, for unconditional and conditional standards, based on quantile regression coefficient estimates. We found the 5th and 10th percentiles were more strongly associated with age and education than were higher percentiles. Model diagnostics demonstrated the accuracy of the standards. Conclusion: The development and use of unconditional and conditional standards should facilitate cognitive assessment in clinical practice and deserve further studies. © 2015 American Association for Geriatric Psychiatry. Source


Tay L.,Tan Tock Seng Hospital | Tay L.,Institute of Geriatrics and Active Ageing | Chua K.C.,Kings College London | Chan M.,Tan Tock Seng Hospital | And 7 more authors.
International Psychogeriatrics | Year: 2014

Background: Discordance between patient- and caregiver-reported quality of life (QoL) is well recognized. This study sought to (i) identify predictors of discrepancy between patient- and caregiver-rated QoL amongst community-dwelling persons with mild-to-moderate dementia, and (ii) differentiate between patients who systematically rate their QoL lower versus those who rate their QoL higher relative to their caregiver ratings. Methods: We recruited 165 patient-caregiver dyads with mild-to-moderate dementia. Quality of life in Alzheimer's disease (QoL-AD) scale was administered separately to patients and caregivers. Data on socio-demographics, interpersonal relationship, and disease-related characteristics (cognitive performance, mood, neuropsychiatric symptoms, functional ability, and caregiver burden) were collected. Patient-caregiver dyads were categorized based on whether patient-rated QoL was lower or higher than their respective caregiver ratings. Univariate analyses and multiple regression models were performed to identify predictors of dyadic rating discrepancy. Results: Mean patient-rated QoL was significantly higher than caregiver rating (mean difference: 3.8 ± 7.1, p < 0.001). Majority (111 (67.2%)) of patients had more positive self-perceived QoL (QoL-ADp (QoL-AD self rated by the patient) > QoL-ADc (QoL-AD proxy-rated by a caregiver)), compared with those (44 (26.7%)) with poorer self-perceived QoL (QoL-ADp < QoL-ADc). Patient's education level, depressive symptoms, and severity of neuropsychiatric symptoms predicted magnitude of discrepancy. Depression (OR = 1.17, 95% CI = 1.02-1.35) and being cared for by other relative (non-spouse/adult child; OR = 7.54, 95% CI = 1.07-53.03) predicted poorer self-perceived QoL. Conclusions: Dyadic rating discrepancy in QoL should draw the clinician's attention to patient depression and neuropsychiatric symptoms. Consideration should also be given to nature of patient-caregiver relationship when discordance between patient and caregiver assessments of QoL is observed. © International Psychogeriatric Association 2014. Source


Ding Y.Y.,Institute of Geriatrics and Active Ageing | Ding Y.Y.,National Healthcare Services | Kader B.,Center for Healthcare Organization and Implementation Research | Kader B.,Boston University | And 4 more authors.
Journal of the American College of Cardiology | Year: 2015

Background There is a paucity of randomized clinical trial data on the use of red blood cell (RBC) transfusion in critically ill patients, specifically in the setting of cardiac disease. Objectives This study examined how hemoglobin (Hgb) level and cardiac disease modify the relationship of RBC transfusion with hospital mortality. The aim was to estimate the Hgb level threshold below which transfusion would be associated with reduced hospital mortality. Methods We performed secondary data analyses of Veterans Affairs intensive care unit (ICU) episodes across 5 years. Logistic regression quantified the effect of transfusion on hospital mortality while adjusting for nadir Hgb level, demographic characteristics, admission information, comorbid conditions, and ICU admission diagnoses. Results Among 258,826 ICU episodes, 12.4% involved transfusions. Hospital death occurred in 11.6%. Without comorbid heart disease, transfusion was associated with decreased adjusted hospital mortality when Hgb was approximately <7.7 g/dl, but transfusion increased mortality above this Hgb level. Corresponding Hgb level thresholds were approximately 8.7 g/dl when comorbid heart disease was present and approximately 10 g/dl when the ICU admission diagnosis was acute myocardial infarction (AMI). Sensitivity analysis using additional adjustment for selected blood tests in a subgroup of 182,792 ICU episodes lowered these thresholds by approximately 1 g/dl. Conclusions Transfusion of critically ill patients was associated with reduced hospital mortality when Hgb level was <8 to 9 g/dl in the presence of comorbid heart disease. This Hgb level threshold for transfusion was 9 to 10 g/dl when AMI was the ICU admission diagnosis. © 2015 American College of Cardiology Foundation. Source


Yang Y.X.,Institute of Geriatrics and Active Ageing | Chong M.S.,Institute of Geriatrics and Active Ageing | Tay L.,Institute of Geriatrics and Active Ageing | Yew S.,Institute of Geriatrics and Active Ageing | And 2 more authors.
Magnetic Resonance Materials in Physics, Biology and Medicine | Year: 2016

Objectives: To develop and validate a machine learning based automated segmentation method that jointly analyzes the four contrasts provided by Dixon MRI technique for improved thigh composition segmentation accuracy. Materials and methods: The automatic detection of body composition is formulized as a three-class classification issue. Each image voxel in the training dataset is assigned with a correct label. A voxel classifier is trained and subsequently used to predict unseen data. Morphological operations are finally applied to generate volumetric segmented images for different structures. We applied this algorithm on datasets of (1) four contrast images, (2) water and fat images, and (3) unsuppressed images acquired from 190 subjects. Results: The proposed method using four contrasts achieved most accurate and robust segmentation compared to the use of combined fat and water images and the use of unsuppressed image, average Dice coefficients of 0.94 ± 0.03, 0.96 ± 0.03, 0.80 ± 0.03, and 0.97 ± 0.01 has been achieved to bone region, subcutaneous adipose tissue (SAT), inter-muscular adipose tissue (IMAT), and muscle respectively. Conclusion: Our proposed method based on machine learning produces accurate tissue quantification and showed an effective use of large information provided by the four contrast images from Dixon MRI. © 2016 ESMRMB Source


Kua J.,Institute of Geriatrics and Active Ageing | Ramason R.,Institute of Geriatrics and Active Ageing | Rajamoney G.,Tan Tock Seng Hospital | Chong M.S.,Institute of Geriatrics and Active Ageing
Archives of Orthopaedic and Trauma Surgery | Year: 2016

Introduction: Current pre-operative assessment using, e.g., American Society of Anaesthesiologists score does not accurately predict post-operative outcomes following hip fracture. The multidimensional aspect of frailty syndrome makes it a better predictor of post-operative outcomes in hip fracture patients. We aim to discover which frailty measure is more suitable for prediction of early post-operative outcomes in hip fracture patients. Methods: Hundred consecutive hip fracture patients seen by the orthogeriatric service were included. We collected baseline demographic, functional and comorbidity data. In addition to ASA, a single blinded rater measured frailty using two scales (i) modified fried criteria (MFC) and (ii) reported edmonton frail scale (REFS). The MFC adopted a surrogate gait speed measure with two questions: (i) Climbing one flight of stairs and (ii) Ability to walk 1 km in the last 2 weeks. Immediate post-operative complications during the inpatient stay were taken as the primary outcome measure. Results: Subjects had mean age of 79.1 ± 9.6 years. Sixty six percent were female and 87 % of Chinese ethnicity. Eighty two percent had surgery, of which 37.8 % (n = 31) had post-operative complications. Frailty, measured by MFC (OR 4.46, p = 0.04) and REFS (OR 6.76, p = 0.01) were the only significant predictors of post-operative complications on univariate analyses. In the hierarchical logistic regression model, only REFS (OR 3.42, p = 0.04) predicted early post-operative complications. At 6 months follow-up, REFS significantly predicted [basic activities of daily living (BADL)] function on the multivariable logistic regression models. (BADL, OR 6.19, p = 0.01). Conclusions: Frailty, measured by the REFS is a good predictor of early post-operative outcomes in our pilot study of older adults undergoing hip surgery. It is also able to predict 6 months BADL function. We intend to review its role in longer-term post-operative outcomes and validate its potential role in pre-operative assessment of older adults undergoing hip surgery. © 2016, Springer-Verlag Berlin Heidelberg. Source

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