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Aggregation of phosphorylated tau (pTau) is a hallmark feature of Alzheimer’s disease (AD). Novel assays now allow pTau to be measured in plasma. Elevated plasma pTau predicts subsequent development of AD, cortical atrophy and AD-related pathologies in the brain. We aimed to determine whether elevated pTau is associated with cognitive functioning in older adults prior to the development of dementia.
Participants and Methods:
Independently living older adults (N = 48, mean age = 70.0 years; SD = 7.7; age range 55-88 years; 35.4% male) free of dementia or clinical stroke were recruited from the community and underwent blood draw and neuropsychological assessment. Plasma was assayed using the Quanterix Simoa® pTau-181 V2 Advantage Kit to quantify pTau-181 levels and APOE genotyping was conducted on the blood cell pellet fraction obtained from plasma separation. Global cognition was assessed using the Dementia Rating Scale-2 (DRS-2) and executive function was assessed using the Stroop, D-KEFS-2 Fluency, and Trails Making Test. Diagnosis of mild cognitive impairment (MCI) was determined based on overall neuropsychological performance. Participants were diagnosed as MCI if they scored >1 SD below norm-referenced values on 2 or more tests within a domain (language, executive, memory) or on 3 tests across domains.
Results:
Multiple linear regression analysis revealed a significant negative association between plasma pTau-181 levels and DRS-2 (B = -2.57, 95% CI (-3.68, -1.47), p <.001), Stroop Color-Word score (B = -2.64, 95% CI (-4.56, - 0.71), p = .009) and Fruits and Vegetables Fluency (B = -1.67, 95% CI (-2.84, -0.49), p = .007), adjusting for age, sex, education and APOE4 status. MCI diagnosis was determined for 43 participants, of which 8 (18.6%) met criteria. Logistic regression analysis revealed that pTau-181 levels are associated with increased odds of MCI diagnosis (OR = 2.18, 95% CI (1.01, 4.68), p = .046), after accounting for age, sex, education and APOE4 status.
Conclusions:
Elevated plasma pTau-181 is associated with worse cognition, particularly executive function, and predicts MCI diagnosis in older adults. Higher plasma pTau-181 was associated with increased odds of MCI diagnosis. Detection of pTau-181 in plasma allows a novel, non-invasive method to detect burden of one form of AD pathology. These findings lend support to the use of plasma pTau-181 as a valuable marker in detecting even early cognitive changes prior to the development of AD. Additional longitudinal studies are warranted to explore the prognostic value of plasma pTau-181 over time.
Blood pressure variability (BPV), independent of traditionally targeted average blood pressure levels, is an emerging vascular risk factor for stroke, cerebrovascular disease, and dementia, possibly through links with vascular-endothelial injury. Recent evidence suggests visit-to-visit (e.g., over months, years) BPV is associated with cerebrovascular disease severity, but less is known about relationships with short-term (e.g., < 24 hours) fluctuations in blood pressure. Additionally, it is unclear how BPV may be related to angiogenic growth factors that play a role in cerebral arterial health.
Participants and Methods:
We investigated relationships between short-term BPV, white matter hyperintensities on MRI, and levels of plasma vascular endothelial growth factor (VEGF) in a sample of community-dwelling older adults (n = 57, ages 55-88) without history of dementia or stroke. Blood pressure was collected continuously during a 5-minute resting period. BPV was calculated as variability independent of mean, a commonly used index of BPV uncorrelated with average blood pressure levels. Participants underwent T2-FLAIR MRI to determine severity of white matter lesion burden. Severity of lesions was classified as Fazekas scores (0-3). Participants also underwent venipuncture to determine levels of plasma VEGF. Ordinal logistic regression examined the association between BPV and Fazekas scores. Multiple linear regression explored relationships between BPV and VEGF. Models controlled for age, sex, and average blood pressure.
Results:
Elevated BPV was related to greater white matter lesion burden (i.e., Fazekas score) (systolic: OR = 1.17 [95% CI 1.01, 1.37]; p = .04; diastolic: OR = 2.47 [95% CI 1.09, 5.90]; p = .03) and increased levels of plasma VEGF (systolic: ß = .39 [95% CI .11, .67]; adjusted R2 = .16; p = .007; diastolic: ß = .48 [95% CI .18, .78]; adjusted R2 = .18; p = .003).
Conclusions:
Findings suggest short-term BPV may be related to cerebrovascular disease burden and angiogenic growth factors relevant to cerebral arterial health, independent of average blood pressure. Understanding the role of BPV in cerebrovascular disease and vascular-endothelial health may help elucidate the increased risk for stroke and dementia associated with elevated BPV.
A community survey and subsequent clinical assessment of 192 Cree aged 65 years and over registered in two Reserves in Northern Manitoba identified only one case of probable Alzheimer's disease among eight cases of dementia, giving a prevalence of 0.5% for Alzheimer's disease and 4.2% for all dementias. This contrasted with an age-adjusted prevalence of 3.5% for Alzheimer's disease and 4.2% for all dementias in an age-stratified sample of 241 English-speaking residents of Winnipeg. Although it was not so for all dementias, the difference between the groups for prevalence of Alzheimer's disease was highly significant (p < .001). The age-specific patterns of all dementias in the two groups were significantly different, however (p = .0254).
To describe the derivation and validation of a pulmonary tuberculosis (TB) prediction model that would enable early discontinuation of unnecessary respiratory isolation.
Design:
Patients placed in isolation for suspected pulmonary TB were studied retrospectively (derivation cohort) and prospectively (validation cohort). Independent predictors of pulmonary TB in the derivation cohort (January 1992-March 1994) were identified by retrospective analysis. Predictors in the model were assigned weights on the basis of the results of the multivariate analysis in order to quantitate the risk of TB in an individual patient. The prospective validation consisted of application of the model to patients placed in isolation during the period April 1994 to June 1995. The predictability of the model in the derivation and validation cohorts was evaluated using receiver operating characteristics (ROC), curve analysis, and calculation of the area under the ROC curve (AUC).
Setting:
A university-affiliated, urban, public hospital with a large population of prison inmates and patients with human immunodeficiency virus infection.
Interventions:
Prospective application of the prediction model to patients placed in isolation during the validation period.
Results:
Four factors were found to be independent predictors of pulmonary TB among 296 isolation episodes in the derivation cohort: positive acid-fast sputum smear (odds ratio [OR], 5.8; 95% confidence interval [CI95], 3.0-11.0; weight=3 points), localized chest radiograph findings (OR, 2.5; CI95,1.3-4.9; weight=2 points), residence in a correctional facility (OR, 2.3; CI95, 1.2-4.4; weight=2 points), and history of weight loss (OR, 1.8; CI95, 1.0-3.2; weight=1 point). Infection control practitioners applied the model prospectively to 220 isolation episodes. The mean (土SE) AUCs of the ROC curve for the derivation and validation cohorts were not significantly different (.86±.04 vs.86±.07; P=.90). There was a significant decline in the mean duration of isolation from the onset of an automatic TB isolation policy in August 1992 to the end of the study (P=.045 by analysis of variance).
Conclusions:
A pulmonary TB prediction model was derived and validated prospectively in a hospital with a moderately high prevalence of TB. The model quantitated the risk of TB in an individual patient and aided infection control practitioners and primary-care physicians in their decisions to discontinue isolation during the validation period. Utilization of the model was responsible, in part, for a decrease in the mean duration of isolation during the study period. Although the model may not have general applicability due to the uniqueness of the patient population studied, this study illustrates how prediction models can be developed and used effectively to deal with a clinical problem.