216 research outputs found

    Recommendations for Care of the Asymptomatic Patient

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    We present a set of reasonable guidelines for the care of healthy, asymptomatic individuals based upon recommendations prepared by an Internal Medicine review committee of Henry Ford Hospital. There recommendations have four goals: to prevent disease, to detect disease in an asymptomatic and potentially curable state, to enhance the patient\u27s quality of life, and to help physicians teach patients good health habits. Recommendations are made for infectious diseases, cancer, metabolic diseases, neurosensory conditions like visual and hearing loss, and general health habits. Some recommendations are at variance with those of well recognized authorities and should be viewed only as a suggested protocol for the care of the asymptomatic patient. Results of ongoing studies may alter our understanding of some areas of controversy and mandate revision of these guidelines periodically

    Pregnancy insulin, glucose, and BMI contribute to birth outcomes in nondiabetic mothers.

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    OBJECTIVE: We investigated the effects of normal variations in maternal glycemia on birth size and other birth outcomes. RESEARCH DESIGN AND METHODS: Women in two unselected birth cohorts, one retrospective (n = 3,158) and one prospective (n = 668), underwent an oral glucose challenge at 28 weeks of gestation. In the retrospective study, glycemia was linked to routine birth records. In the prospective study, offspring adiposity was assessed by skinfold thickness from birth to age 24 months. RESULTS: In the retrospective study, within the nondiabetic range (2.1-7.8 mmol/l), each 1 mmol/l rise in the mother's 60-min glucose level was associated with a (mean +/- SEM) 2.1 +/- 0.8% (P = 0.006) rise in absolute risk of assisted vaginal delivery, a 3.4 +/- 0.8% (P 90th centile) was independently related to the mother's fasting glucose (odds ratio 2.61 per +1 mmol/l [95% CI 1.15-5.93]) and prepregnancy BMI (1.10 per +1 kg/m(2) [1.04-1.18]). The mother's higher fasting glycemia (P = 0.004), lower insulin sensitivity (P = 0.01), and lower insulin secretion (P = 0.02) were independently related to greater offspring adiposity at birth. During postnatal follow-up, the correlation between the mother's glycemia and offspring adiposity disappeared by 3 months, whereas prepregnancy BMI was associated with offspring adiposity that was only apparent at 12 and 24 months (both P < 0.05). CONCLUSIONS: Prepregnancy BMI, pregnancy glycemia, insulin sensitivity, and insulin secretion all contribute to offspring adiposity and macrosomia and may be separate targets for intervention to optimize birth outcomes and later offspring health

    Predicting Cognitive Decline in Nondemented Elders Using Baseline Metrics of AD Pathologies, Cerebrovascular Disease, and Neurodegeneration

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    BACKGROUND AND OBJECTIVES: Dementia is a growing socio-economic challenge that requires early intervention. Identifying biomarkers that reliably predict clinical progression early in the disease process would better aid selection of individuals for future trial participation. Here we compared the ability of baseline, single time-point biomarkers (CSF amyloid 1-42, CSF ptau-181, white matter hyperintensities (WMH), cerebral microbleeds (CMB), whole-brain volume, and hippocampal volume) to predict decline in cognitively normal individuals who later converted to mild cognitive impairment (MCI) (CNtoMCI), and those with MCI who later converted to an Alzheimer's disease (AD) diagnosis (MCItoAD). METHODS: Standardised baseline biomarker data from ADNI2/Go, and longitudinal diagnostic data (including ADNI3), were used. Cox regression models assessed biomarkers in relation to time to change in clinical diagnosis using all follow-up timepoints available. Models were fit for biomarkers univariately, and together in a multivariable model. Hazard Ratios (HR) were compared to evaluate biomarkers. Analyses were performed separately in CNtoMCI and MCItoAD groups. RESULTS: For CNtoMCI (n = 189), there was strong evidence that higher WMH volume (individual model: HR 1.79, p = .002; fully-adjusted model: HR 1.98, p = .003), and lower hippocampal volume (individual: HR 0.54, p = .001; fully-adjusted: HR 0.40, p < .001) were associated with conversion to MCI individually and independently. For MCItoAD (n = 345), lower hippocampal (individual model: HR 0.45, p < .001; fully-adjusted model: HR 0.55, p < .001) and whole-brain volume (individual: HR 0.31, p < .001; fully-adjusted: HR 0.48, p = .02), increased CSF ptau (individual: HR 1.88, p < .001; fully-adjusted: HR 1.61, p < .001), and lower CSF amyloid (individual: HR 0.37, p < .001, fully-adjusted: HR 0.62, p = .008) were most strongly associated with conversion to AD individually and independently. DISCUSSION: Lower hippocampal volume was a consistent predictor of clinical conversion to MCI and AD. CSF and brain volume biomarkers were predictive of conversion to AD from MCI, while WMH were predictive of conversion to MCI from cognitively normal. The predictive ability of WMH in the CNtoMCI group may be interpreted as some being on a different pathological pathway, such as vascular cognitive impairment

    Predicting Cognitive Decline in Older Adults Using Baseline Metrics of AD Pathologies, Cerebrovascular Disease, and Neurodegeneration

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    BACKGROUND AND OBJECTIVES: Dementia is a growing socioeconomic challenge that requires early intervention. Identifying biomarkers that reliably predict clinical progression early in the disease process would better aid selection of individuals for future trial participation. Here, we compared the ability of baseline, single time-point biomarkers (CSF amyloid 1-42, CSF ptau-181, white matter hyperintensities (WMH), cerebral microbleeds, whole-brain volume, and hippocampal volume) to predict decline in cognitively normal individuals who later converted to mild cognitive impairment (MCI) (CNtoMCI) and those with MCI who later converted to an Alzheimer disease (AD) diagnosis (MCItoAD). METHODS: Standardized baseline biomarker data from AD Neuroimaging Initiative 2 (ADNI2)/GO and longitudinal diagnostic data (including ADNI3) were used. Cox regression models assessed biomarkers in relation to time to change in clinical diagnosis using all follow-up time points available. Models were fit for biomarkers univariately and together in a multivariable model. Hazard ratios (HRs) were compared to evaluate biomarkers. Analyses were performed separately in CNtoMCI and MCItoAD groups. RESULTS: For CNtoMCI (n = 189), there was strong evidence that higher WMH volume (individual model: HR 1.79, p = 0.002; fully adjusted model: HR 1.98, p = 0.003) and lower hippocampal volume (individual: HR 0.54, p = 0.001; fully adjusted: HR 0.40, p < 0.001) were associated with conversion to MCI individually and independently. For MCItoAD (n = 345), lower hippocampal (individual model: HR 0.45, p < 0.001; fully adjusted model: HR 0.55, p < 0.001) and whole-brain volume (individual: HR 0.31, p < 0.001; fully adjusted: HR 0.48, p = 0.02), increased CSF ptau (individual: HR 1.88, p < 0.001; fully adjusted: HR 1.61, p < 0.001), and lower CSF amyloid (individual: HR 0.37, p < 0.001; fully adjusted: HR 0.62, p = 0.008) were most strongly associated with conversion to AD individually and independently. DISCUSSION: Lower hippocampal volume was a consistent predictor of clinical conversion to MCI and AD. CSF and brain volume biomarkers were predictive of conversion to AD from MCI, whereas WMH were predictive of conversion to MCI from cognitively normal. The predictive ability of WMH in the CNtoMCI group may be interpreted as some being on a different pathologic pathway, such as vascular cognitive impairment

    Caveolin contributes to the modulation of basal and β-adrenoceptor stimulated function of the adult rat ventricular myocyte by simvastatin: A novel pleiotropic effect

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    The number of people taking statins is increasing across the globe, highlighting the Importance of fully understanding statins effects on the cardiovascular system. The beneficial impact of statins extends well beyond regression of atherosclerosis to include direct effects on tissues of the cardiovascular system (pleiotropic effects). Pleiotropic effects on the cardiac myocyte are often overlooked. Here we consider the contribution of the caveolin protein, whose expression and cellular distribution is dependent on cholesterol, to statin effects on the cardiac myocyte. Caveolin is a structural and regulatory component of caveolae, and is a key regulator of cardiac contractile function and adrenergic responsiveness. We employed an experimental model in which inhibition of myocyte HMG CoA reductase could be studied in the absence of paracrine influences from non-myocyte cells. Adult rat ventricular myocytes were treated with 10 μM simvastatin for 2 days. Simvastatin treatment reduced myocyte cholesterol, caveolin 3 and caveolar density. Negative inotropic and positive lusitropic effects (with corresponding changes in [Ca2]¡) were seen in statin-treated cells. Simvastatin significantly potentiated the inotropic response to β2-, but not β1-, adrenoceptor stimulation. Under conditions of β2-adrenoceptor stimulation, phosphorylation of phospholamban at Ser16and troponin I at Ser23/24was enhanced with statin treatment. Simvastatin increased NO production without significant effects on eNOS expression or phosphorylation (Ser1177), consistent with the reduced expression of caveolin 3, its constitutive Inhibitor. In conclusion, statin treatment can reduce caveolin 3 expression, with functional consequences consistent with the known role of caveolae in the cardiac cell. These data are likely to be of significance, particularly during the early phases of statin treatment, and in patients with heart failure who have altered ß-adrenoceptor signalling. In addition, as caveolin is ubiquitously expressed and has myriad tissue-specific functions, the impact of statin-dependent changes in caveolin is likely to have many other functional sequelae
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