Preclinical evidence shows that activation of the cholinergic anti-inflammatory pathway (CAP) may have direct and indirect beneficial effects on the kidney. Cholinesterase inhibitors (ChEIs) are... Show morePreclinical evidence shows that activation of the cholinergic anti-inflammatory pathway (CAP) may have direct and indirect beneficial effects on the kidney. Cholinesterase inhibitors (ChEIs) are specific Alzheimer's dementia (AD) therapies that block the action of cholinesterases and activate CAP. Here, we explored a plausible effect of ChEIs on slowing kidney function decline by comparing the risk of CKD progression among patients with newly diagnosed AD that initiated ChEI or not within 90 days. Using complete information of routine serum creatinine tests, we evaluated changes in estimated glomerular filtration rate (eGFR) and defined the outcome of chronic kidney disease (CKD) progression as the composite of an eGFR decline of over 30%, initiation of dialysis/transplant or death attributed to CKD. A secondary outcome was death. Inverse probability of treatment-weighted Cox regression was used to estimate hazard ratios. Among 11, 898 patients, 6,803 started on ChEIs and 5,095 did not. Mean age was 80 years During a median 3.0 years of follow-up, and compared to non-use, ChEI use was associated with 18% lower risk of 95% confidence interval 0.71-0.96) and a 21% lower risk of death (0.79; 0.72-0.86). Results were consistent across subgroups, ChEI subclasses and after accounting for competing risks. Thus, in patients with AD undergoing routine care, use of ChEI (vs no-use) was associated with lower risk of CKD progression. Show less
Haaksma, M.L.; Eriksdotter, M.; Rizzuto, D.; Leoutsakos, J.M.S.; Rikkert, M.G.M.O.; Melis, R.J.F.; Garcia-Ptacek, S. 2019
Objective To develop survival prediction tables to inform physicians and patients about survival probabilities after the diagnosis of dementia and to determine whether survival after dementia... Show moreObjective To develop survival prediction tables to inform physicians and patients about survival probabilities after the diagnosis of dementia and to determine whether survival after dementia diagnosis can be predicted with good accuracy.Methods We conducted a nationwide registry-linkage study including 829 health centers, i.e., all memory clinics and ≈75\% of primary care facilities, across Sweden. Data including cognitive function from 50,076 people with incident dementia diagnoses >=65 years of age and registered with the Swedish Dementia Register in 2007 to 2015 were used, with a maximum follow-up of 9.7 years for survival until 2016. Sociodemographic factors, comorbidity burden, medication use, and dates of death were obtained from nationwide registries. Cox proportional hazards regression models were used to create tables depicting 3-year survival probabilities for different risk factor profiles.Results By August 2016, 20,828 (41.6\%) patients in our cohort had died. Median survival time from diagnosis of dementia was 5.1 (interquartile range 2.9{\textendash}8.0) years for women and 4.3 (interquartile range 2.3{\textendash}7.0) years for men. Predictors of mortality were higher age, male sex, increased comorbidity burden and lower cognitive function at diagnosis, a diagnosis of non-Alzheimer dementia, living alone, and using more medications. The developed prediction tables yielded c indexes of 0.70 (95\% confidence interval [CI] 0.69{\textendash}0.71) to 0.72 (95\% CI 0.71{\textendash}0.73) and showed good calibration.Conclusions Three-year survival after dementia diagnosis can be predicted with good accuracy. The survival prediction tables developed in this study may aid clinicians and patients in shared decision-making and advance care planning.AD=Alzheimer disease; CCI=Charlson Comorbidity Index; CI=confidence interval; HR=hazard ratio; ICD-10=International Classification of Diseases, 10 revision; IQR=interquartile range; MMSE=Mini-Mental State Examination; SveDem=Svenska Demensregistret Show less
Objectives: The predictive value of frailty and comorbidity, in addition to more readily available information, is not widely studied. We determined the incremental predictive value of frailty and... Show moreObjectives: The predictive value of frailty and comorbidity, in addition to more readily available information, is not widely studied. We determined the incremental predictive value of frailty and comorbidity for mortality and institutionalization across both short and long prediction periods in persons with dementia.Design: Longitudinal clinical cohort study with a follow-up of institutionalization and mortality occurrence across 7 years after baseline.Setting and Participants: 331 newly diagnosed dementia patients, originating from 3 Alzheimer centers (Amsterdam, Maastricht, and Nijmegen) in the Netherlands, contributed to the Clinical Course of Cognition and Comorbidity (4C) Study.Measures: We measured comorbidity burden using the Cumulative Illness Rating Scale for Geriatrics (CIRS-G) and constructed a Frailty Index (FI) based on 35 items. Time-to-death and time-to-institutionalization from dementia diagnosis onward were verified through linkage to the Dutch population registry.Results: After 7 years, 131 patients were institutionalized and 160 patients had died. Compared with a previously developed prediction model for survival in dementia, our Cox regression model showed a significant improvement in model concordance (U) after the addition of baseline CIRS-G or FI when examining mortality across 3 years (FI: U = 0.178, P = .005, CIRS-G: U = 0.180, P = .012), but not for mortality across 6 years (FI: U = 0.068, P = .176, CIRS-G: U = 0.084, P = .119). In a competing risk regression model for time-to-institutionalization, baseline CIRS-G and FI did not improve the prediction across any of the periods.Conclusions: Characteristics such as frailty and comorbidity change over time and therefore their predictive value is likely maximized in the short term. These results call for a shift in our approach to prognostic modeling for chronic diseases, focusing on yearly predictions rather than a single prediction across multiple years. Our findings underline the importance of considering possible fluctuations in predictors over time by performing regular longitudinal assessments in future studies as well as in clinical practice. (C) 2018 AMDA - The Society for Post-Acute and Long-Term Care Medicine. Show less
