Patterns of statin use and cholesterol goal attainment in a high-risk cardiovascular population: A retrospective study of primary care electronic medical records.

OBJECTIVE: To describe real-life patterns of statin use and cholesterol goal attainment in a retrospective cohort of patients with high cardiovascular risk. METHODS: Retrospective cohort study of 21,636 individuals, 18.34% women, mean age 63.30 years (standard deviation 6.29). New statin users aged 35 to 74 years at high cardiovascular risk and with no previous cardiovascular disease in primary care electronic medical records (2006-2011). Patterns of statin use were based on statin type, potency, and 1-year statin switches. OUTCOMES: Relative mean reductions over 1 year and probability of goal attainment (<3.3 mmol/L). Natural patterns of statin use were identified using multiple correspondence analysis; general linear and logistic models were used to estimate low-density lipoprotein cholesterol (LDL-C) reductions and goal attainment probability. RESULTS: Three patterns of statin use were defined: low (3.82% of the population), moderate (71.94%), and high intensity (24.24%). After 1 year, potency decreased 42.74%, 64.16%, and 50.94%, respectively, and 37.41%, 29.47%, and 30.16% of the population stopped taking statins in low, moderate, and high patterns, respectively. Relative reductions in LDL-C: low intensity, 15.7% (95% confidence interval [CI]: -22.96 to 54.36); moderate intensity, 29.72% (95% CI: 29.12-30.32); and high intensity, 24.20% (95% CI: -8.08 to 40.32). There was a direct relationship between higher intensity patterns and greater probability of goal attainment. CONCLUSIONS: Three real-life patterns of statin use were identified. Lipid management strategies in primary care should focus on improving adherence to treatment. People starting at low potency should switch to a moderate pattern; more intensive therapies should be considered in who require a larger LDL-C reduction to reach therapeutic targets, patients with good treatment adherence who do not achieve the goal with a moderate pattern of therapy or patients at very high risk.

Lower serum osteocalcin concentrations are associated with brain microstructural changes and worse cognitive performance.

OBJECTIVE: Rodent models have found that osteocalcin crosses the blood-brain barrier and regulates behaviour. No data are available on osteocalcin's effects on brain microstructure and cognitive performance in humans. We evaluated the association between serum osteocalcin concentrations and (i) brain microstructural changes on magnetic resonance imaging (MRI) and (ii) neuropsychological performance. DESIGN, PATIENTS AND MEASUREMENTS: We studied 24 consecutive obese subjects (13 women; age, 49·8 ± 8·1 years; body mass index [BMI], 43·9 ± 4·54 kg/m(2) ) and 20 healthy volunteers (10 women; age, 48·8 ± 9·5 years; BMI, 24·3 ± 3·54 kg/m(2) ) in a cross-sectional study within the multicentre FLORINASH Project. FLAIR signal intensity and DTI-metrics (primary (λ1 ), secondary (λ2 ) and tertiary (λ3 ) eigenvalues; fractional anisotropy (FA); and mean diffusivity) in the caudate, hypothalamus, thalamus and putamen, and in subcortical white matter were assessed. Cognitive performance evaluated by neuropsychological test battery. RESULTS: Lower osteocalcin concentrations were associated with BMI, higher λ1, λ2 and λ3 values at the caudate and lower FLAIR signal intensity at the caudate and putamen. Obese patients with lower osteocalcin concentrations had higher FA at putamen and thalamus. Lower osteocalcin concentrations were associated with higher Iowa Gambling Task (IGT) scores. FLAIR signal intensity at the caudate <601·832 yielded 85·7% sensitivity, 64·3% specificity, 70·6% negative predictive value and 81·8% positive predictive value for IGT score. Lower osteocalcin was an independent predictor of worse cognitive performance on multivariate analysis (F = 3·551, P = 0·01343; R(2) = 0·103). Bayesian information criterion demonstrated that osteocalcin had the predominant role in predicting IGT score. CONCLUSIONS: Lower serum osteocalcin concentrations are associated with brain microstructural changes and worse cognitive performance.

High-resolution blood-pool-contrast-enhanced MR angiography in glioblastoma: tumor-associated neovascularization as a biomarker for patient survival. A preliminary study.

INTRODUCTION: The objective of the study was to determine whether tumor-associated neovascularization on high-resolution gadofosveset-enhanced magnetic resonance angiography (MRA) is a useful biomarker for predicting survival in patients with newly diagnosed glioblastomas. METHODS: Before treatment, 35 patients (25 men; mean age, 64 ± 14 years) with glioblastoma underwent MRI including first-pass dynamic susceptibility contrast (DSC) perfusion and post-contrast T1WI sequences with gadobutrol (0.1 mmol/kg) and, 48 h later, high-resolution MRA with gadofosveset (0.03 mmol/kg). Volumes of interest for contrast-enhancing lesion (CEL), non-CEL, and contralateral normal-appearing white matter were obtained, and DSC perfusion and DWI parameters were evaluated. Prognostic factors were assessed by Kaplan-Meier survival and Cox proportional hazards model. RESULTS: Eighteen (51.42 %) glioblastomas were hypervascular on high-resolution MRA. Hypervascular glioblastomas were associated with higher CEL volume and lower Karnofsky score. Median survival rates for patients with hypovascular and hypervascular glioblastomas treated with surgery, radiotherapy, and chemotherapy were 15 and 9.75 months, respectively (P < 0.001). Tumor-associated neovascularization was the best predictor of survival at 5.25 months (AUC = 0.794, 81.2 % sensitivity, 77.8 % specificity, 76.5 % positive predictive value, 82.4 % negative predictive value) and yielded the highest hazard ratio (P < 0.001). CONCLUSIONS: Tumor-associated neovascularization detected on high-resolution blood-pool-contrast-enhanced MRA of newly diagnosed glioblastoma seems to be a useful biomarker that correlates with worse survival.

Gut Microbiota Interacts With Brain Microstructure and Function.

CONTEXT: Evidence from animals suggests that gut microbiota affects brain structure and function but evidence in humans is scarce. OBJECTIVE: This study sought to evaluate potential interactions among gut microbiota composition, brain microstructure, and cognitive tests in obese and nonobese subjects. DESIGN, SETTING, AND PARTICIPANTS: This was a cross-sectional study at a tertiary hospital including 20 consecutive obese and 19 nonobese subjects similar in age and sex. MAIN OUTCOME MEASURES: Gut microbiota (16S bacterial gene pyrosequencing), brain microstructure (diffusion tensor imaging of brain white and gray matter and R2* sequences in magnetic resonance imaging) and cognitive tests. RESULTS: Hierarchical clustering revealed a specific gut microbiota-brain map profile for obese individuals who could be discriminated from nonobese subjects (accuracy of 0.81). Strikingly, Shannon index was linked to R2* and fractional anisotropy of the hypothalamus, caudate nucleus, and hippocampus, suggesting sparing of these brain structures with increased bacterial biodiversity. Microbiota profile also clustered with cognitive function. The relative abundance of Actinobacteria phylum was linked not only to magnetic resonance imaging diffusion tensor imaging variables in the thalamus, hypothalamus, and amygdala but also to cognitive test scores related to speed, attention, and cognitive flexibility. CONCLUSIONS: In sum, obesity status affects microbiota-brain microstructure and function crosstalk.

Improving prevalence estimation through data fusion: methods and validation.

BACKGROUND: Estimation of health prevalences is usually performed with a single survey. Some attempts have been made to integrate more than one source of data. We propose here to validate this approach through data fusion. Data Fusion is the process of integrating two sources of data into one combined file. It allows us to take even greater advantage of existing information collected in databases. Here, we use data fusion to improve the estimation of health prevalences for two primary health factors: cardiovascular diseases and diabetes. METHODS: We use a real data fusion operation on population health, where the imputation of basic health risk factors is used to enrich a large-scale survey on self-reported health status. We propose choosing the imputation methodology for this problem through a suite of validation statistics that assess the quality of the fused data. The compared imputation techniques have been chosen from among the main imputation methodologies: k-nearest neighbor, probabilistic modeling and regression. We use the 2006 Health Survey of Catalonia, which provides a complete report of the perceived health status. In order to deal with the uncertainty problem, we compare these methodologies under the single and multiple imputation frames. RESULTS: A suite of validation statistics allows us to discern the strengths and weaknesses of studied imputation methods. Multiple outperforms single imputation by providing better and much more stable estimates, according to the computed validation statistics. The summarized results indicate that the probabilistic methods preserve the multivariate structure better; sequential regression methods deliver greater accuracy of imputed data; and nearest neighbor methods end up with a more realistic distribution of imputed data. CONCLUSIONS: Data fusion allows us to integrate two sources of information in order to take grater advantage of the available data. Multiple imputed sequential regression models have the advantage of grater interpretability and can be used for health policy. Under certain conditions, more accurate estimates of the prevalences can be obtained using fused data (the original data plus the imputed data) than just by using only the observed data.

Hypothalamic damage is associated with inflammatory markers and worse cognitive performance in obese subjects.

CONTEXT: Growing evidence implicates hypothalamic inflammation in the pathogenesis of diet-induced obesity and cognitive dysfunction in rodent models. Few studies have addressed the association between obesity and hypothalamic damage in humans and its relevance. OBJECTIVE: This study aimed to determine markers of obesity-associated hypothalamic damage on diffusion tensor imaging (DTI) and to determine whether DTI metrics are associated with performance on cognitive testing. DESIGN AND PARTICIPANTS: This cross-sectional study analyzed DTI metrics (primary [λ(1)], secondary [λ(2)], and tertiary [λ(3)] eigenvalues; fractional anisotropy; and mean diffusivity) in the hypothalamus of 24 consecutive middle-age obese subjects (13 women; 49.8 ± 8.1 y; body mass index [BMI], 43.9 ± 0.92 kg/m(2)) and 20 healthy volunteers (10 women; 48.8 ± 9.5 y; BMI, 24.3 ± 0.79 kg/m(2)). OUTCOME: measures: Hypothalamic damage assessed by DTI metrics and cognitive performance evaluated by neuropsychological test battery. RESULTS: λ(1) values in the hypothalamus were significantly lower in obese subjects (P < .0001). The sensitivity, specificity, and positive and negative predictive values for obesity-associated hypothalamic damage by λ(1) < 1.072 were 75, 87.5, 83.3, and 80.7%, respectively. Patients with hypothalamic λ(1) < 1.072 had higher values of BMI, fat mass, inflammatory markers, carotid-intima media thickness, and hepatic steatosis and lower scores on cognitive tests. Combined BMI and alanine aminotransferase had the strongest association with hypothalamic damage reflected by λ(1) < 1.072 (area under the curve = 0.89). CONCLUSIONS: DTI detects obesity-associated hypothalamic damage associated with inflammatory markers and worse cognitive performance. This study highlights the potential utility of λ(1) as a surrogate marker of obesity-associated hypothalamic damage.

Carotid pulse wave velocity by magnetic resonance imaging is increased in middle-aged subjects with the metabolic syndrome.

Arterial pulse wave velocity (PWV), an independent predictor of cardiovascular disease, physiologically increases with age; however, growing evidence suggests metabolic syndrome (MetS) accelerates this increase. Magnetic resonance imaging (MRI) enables reliable noninvasive assessment of arterial stiffness by measuring arterial PWV in specific vascular segments. We investigated the association between the presence of MetS and its components with carotid PWV (cPWV) in asymptomatic subjects without diabetes. We assessed cPWV by MRI in 61 individuals (mean age, 55.3 ± 14.1 years; median age, 55 years): 30 with MetS and 31 controls with similar age, sex, body mass index, and LDL-cholesterol levels. The study population was dichotomized by the median age. To remove the physiological association between PWV and age, unpaired t tests and multiple regression analyses were performed using the residuals of the regression between PWV and age. cPWV was higher in middle-aged subjects with MetS than in those without (p = 0.001), but no differences were found in elder subjects (p = 0.313). cPWV was associated with diastolic blood pressure (r = 0.276, p = 0.033) and waist circumference (r = 0.268, p = 0.038). The presence of MetS was associated with increased cPWV regardless of age, sex, blood pressure, and waist (p = 0.007). The MetS components contributing independently to an increased cPWV were hypertension (p = 0.018) and hypertriglyceridemia (p = 0.002). The presence of MetS is associated with an increased cPWV in middle-aged subjects. In particular, hypertension and hypertriglyceridemia may contribute to early progression of carotid stiffness.

Nonalcoholic fatty liver disease and age are strong indicators for atherosclerosis in morbid obesity.

OBJECTIVE: Whether nonalcoholic fatty liver disease (NAFLD) can predict atherosclerosis in obese patients remains unclear. The aim of our study was to investigate the usefulness of NAFLD and other cardiometabolic parameters in predicting subclinical atherosclerosis in obese patients. DESIGN, PATIENTS AND MEASUREMENTS: We studied 314 consecutive obese subjects (223 women; mean age, 45·04 ± 9·34 years; body mass index 44·3 ± 5 kg/m(2) ) and 47 healthy lean individuals. Hepatic steatosis and atherosclerosis [carotid intima-media thickness (cIMT) >0·8 mm and/or presence of plaques] were evaluated ultrasonographically. Liver biopsies were obtained in 51 patients. RESULTS: In obese patients, mean c-IMT was greater in those with NAFLD (P < 0·001). Hepatic steatosis and age were independent predictors of atherosclerosis: the NAFLD-associated OR for atherosclerosis was 5·96 (95%CI, 1·60-22·25; P = 0·008) in men and 8·26 (95%CI, 4·02-16·99; P < 0·001) in women, and the age-associated OR for atherosclerosis was 1·14 (95%CI, 1·07-1·22; P < 0·001) in men and 1·12 (95%CI, 1·08-1·17; P < 0·001) in women. The sensitivity, specificity and positive and negative predictive values of steatosis for atherosclerosis were 78·70%, 70·50%, 74·00% and 75·60% (AUC = 0·840) in men ≥43·5 years and 86·90%, 52·50%, 68·80% and 76·80% (AUC = 0·761) in women ≥47·5 years, respectively. Agreement between ultrasound-diagnosed steatosis and histology was good (ICC = 0·79). Combined NAFLD and age was the strongest predictor of atherosclerosis in obesity. CONCLUSIONS: Nonalcoholic fatty liver disease and age may be independent risk factors for carotid atherosclerosis in obese individuals. Obese men and women with steatosis aged over 43·5 and 47·5 years, respectively, should be screened for carotid atherosclerosis. However, further evidence is necessary before suggesting an intervention based on current findings.

Brain iron overload, insulin resistance, and cognitive performance in obese subjects: a preliminary MRI case-control study.

OBJECTIVE: The linkage among the tissue iron stores, insulin resistance (IR), and cognition remains unclear in the obese population. We aimed to identify the factors that contribute to increased hepatic iron concentration (HIC) and brain iron overload (BIO), as evaluated by MRI, and to evaluate their impact on cognitive performance in obese and nonobese subjects. RESEARCH DESIGN AND METHODS: We prospectively recruited 23 middle-aged obese subjects without diabetes (13 women; age 50.4 ± 7.7 years; BMI 43.7 ± 4.48 kg/m2) and 20 healthy nonobese volunteers (10 women; age 48.8 ± 9.5 years; BMI 24.3 ± 3.54 kg/m2) in whom iron load was assessed in white and gray matter and the liver by MRI. IR was measured from HOMA-IR and an oral glucose tolerance test. A battery of neuropsychological tests was used to evaluate the cognitive performance. Multivariate regression analysis was used to identify the independent associations of BIO and cognitive performance. RESULTS: A significant increase in iron load was detected at the caudate nucleus (P < 0.001), lenticular nucleus (P = 0.004), hypothalamus (P = 0.002), hippocampus (P < 0.001), and liver (P < 0.001) in obese subjects. There was a positive correlation between HIC and BIO at caudate (r = 0.517, P < 0.001), hypothalamus (r = 0.396, P = 0.009), and hippocampus (r = 0.347, P < 0.023). The area under the curve of insulin was independently associated with BIO at the caudate (P = 0.001), hippocampus (P = 0.028), and HIC (P = 0.025). BIOs at the caudate (P = 0.028), hypothalamus (P = 0.006), and lenticular nucleus (P = 0.012) were independently associated with worse cognitive performance. CONCLUSIONS: Obesity and IR may contribute to increased HIC and BIO being associated with worse cognitive performance. BIO could be a potentially useful MRI biomarker for IR and obesity-associated cognitive dysfunction.

Decreased corticospinal tract fractional anisotropy predicts long-term motor outcome after stroke.

BACKGROUND AND PURPOSE: Nearly 50% of patients have residual motor deficits after stroke, and long-term motor outcome is difficult to predict. We assessed the predictive value of axonal damage to the corticospinal tract indexed by diffusion tensor imaging fractional anisotropy for long-term motor outcome. METHODS: Consecutive patients with middle cerebral artery stroke underwent multimodal MRI, including diffusion tensor imaging ≤12 hours, 3 days, and 30 days after onset. Clinical severity, infarct volume, location of corticospinal tract damage on diffusion tensor tractography, and ratios of fractional anisotropy (rFA) between affected and unaffected sides of the corticospinal tract at the pons were evaluated. Severity of motor deficit at 2 years was categorized using the Motricity Index as no deficit (Motricity Index, 100), slight-moderate deficit (Motricity Index, 99-50), or severe deficit (Motricity Index, <50). RESULTS: We evaluated 70 patients (28 women; 72±12 years). rFA values at day 30 correlated with the degree of motor deficit at 2 years (P<0.001). rFA at day 30 was the only independent predictor of long-term motor outcome (odds ratio, 1.60; 95% confidence interval, 1.26-2.03; P<0.001). The sensitivity, specificity, and positive and negative predictive values of the cutoffs rFA<0.982 for predicting slight-moderate deficit and rFA<0.689 for severe deficit were 94.4%, 84.6%, 73.9%, and 97.1%, respectively, and 100%, 83.3%, 81.3%, and 100%, respectively. CONCLUSIONS: rFA at day 30 is an independent predictor of long-term motor outcome after stroke.

Increased corticospinal tract fractional anisotropy can discriminate stroke onset within the first 4.5 hours.

BACKGROUND AND PURPOSE: The role of diffusion tensor imaging in determining stroke age remains unclear. We tested the ability of diffusion tensor imaging metrics to discriminate ischemic stroke <4.5 hours of onset. METHODS: We enrolled 60 consecutive patients for multimodal 1.5 T MRI within 12 hours of middle cerebral artery ischemic stroke onset. We measured fractional anisotropy (FA), mean diffusivity (MD), apparent diffusion coefficient (ADC), and T2-weighted signal intensity in affected ipsilateral and unaffected contralateral deep gray matter, cortical gray matter, deep white matter in the corticospinal tract (CST), and subcortical white matter and calculated ipsilateral-to-contralateral ratios (r). Hyperintensity in infarcted tissue was considered fluid-attenuated inversion recovery-positive. RESULTS: We analyzed the 48 patients (17 women; mean age, 68 ± 14 years) with known onset. In 25 (52.1%) patients, onset was ≤ 4.5 hours (mean, 182.3 ± 65.6 minutes). Variables differing significantly between infarcts <4.5 hours and >4.5 hours were rFA CST (P = 0.001), rMD cortical gray matter (P = 0.036), rADC cortical gray matter (P = 0.009), rT2 CST (P = 0.006), and fluid-attenuated inversion recovery (P<0.001). rFA at CST was the most reliable to discriminate infarcts <4.5 hours (Goodman-Kruskal = 0.76). The sensitivity, specificity, and positive and negative predictive values for infarct <4.5 hours of onset by rFA at CST >0.970 were 93.8%, 84.6%, 88.2%, and 91.7%, respectively. CONCLUSIONS: These preliminary results suggest rFA at CST may be a surrogate marker of acute stroke age.

Albumin-binding MR blood pool contrast agent improves diagnostic performance in human brain tumour: comparison of two contrast agents for glioblastoma.

OBJECTIVE: We qualitatively and quantitatively compared MRI enhancement obtained with gadofosveset, an albumin-binding blood-pool contrast agent, and with gadobutrol, an extracellular contrast agent, in patients with glioblastoma. METHODS: Thirty-five patients (25 men; 64 ± 14 years) with histologically proven glioblastoma underwent MRI including pre- and post-contrast T1-weighted SE images acquired 5 min after gadobutrol (0.1 mmol/kg) and, 48 h later, images acquired with identical parameters 5 min and 3, 6, and 24 h after gadofosveset (0.03 mmol/kg). Lesion extent, delineation, internal morphology, multifocality, and global diagnostic preference were evaluated quantitatively for the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and contrast enhancement (CE). RESULTS: Mean values of SNR, CNR, and tumour CE were highest 6 h after gadofosveset. Multifocality was seen in 17 (48.6 %) patients; additional lesions had stronger enhancement 6 h after gadofosveset in 12 patients (70.6 %). In 21 (60 %) patients, radiologists' global preference was highest in images acquired 6 h after gadofosveset (kappa = 0.764). In 22 patients (62.8 %), all qualitative endpoints were better at 5 min after gadobutrol than in images acquired 5 min after gadofosveset injection. CONCLUSIONS: Gadobutrol gives significant tumour enhancement in early postcontrast imaging. However, images acquired 6 h after gadofosveset injection have significantly better diagnostic information endpoints and contrast enhancement.

Reliability of the ABC/2 method in determining acute infarct volume.

BACKGROUND AND PURPOSE: Infarct volume is used as a surrogate outcome measure in clinical trials of therapies for acute ischemic stroke. ABC/2 is a fast volumetric method, but its accuracy remains to be determined. We aimed to study the accuracy and reproducibility of ABC/2 in determining acute infarct volume with diffusion-weighted imaging. METHODS: We studied 86 consecutive patients with acute ischemic stroke. Three blinded observers determined volume with the ABC/2 method, and the results were compared with those of the manual planimetric method. RESULTS: The ABC/2 technique overestimated infarct volume by a median false increase (variable ABC/2 volume minus planimetric volume) of 7.33 cm(3) (1.29, 22.170, representing a 162.56% increase over the value of the gold standard (variable ABC/2 volume over planimetric volume) (121.70, 248.52). In each method, the interrater reliability was excellent: the intraclass correlations were .992 and .985 for the ABC/2 technique and planimetric method, respectively. CONCLUSIONS: ABC/2 is volumetric method with clinical value but it consistently overestimates the real infarct volume.

Magnetic resonance imaging biomarkers of ischemic stroke: criteria for the validation of primary imaging biomarkers.

Ischemic stroke is associated with a high rate of disability and death. Establishing valid biomarkers could help accelerate the approval of promising new therapies for stroke. Whereas many serum biomarkers have been evaluated, possible imaging biomarkers of stroke lack validation. Magnetic resonance imaging (MRI) is a very sensitive technique to study acute stroke and MRI parameters have been established to assess the outcome of acute stroke. This review reassesses the criteria for the validation of MRI biomarkers of acute ischemic stroke (MRI-BAS). Seven criteria were used to review the validity of the main MRI-BAS: vascular status, lesion volume, reversibility on diffusion-weighted imaging, perfusion alteration, penumbra studied with diffusion-perfusion mismatch, clinical-diffusion mismatch, diffusion-angiography mismatch and hemorrhagic transformation. We analyzed the definitions of these biomarkers and the extent to which each fulfills the criteria for validation and found that few MRI-BAS have been fully validated. Further studies should help to improve the validation of current MRI-BAS and develop new biomarkers.