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Objective: To determine prevalence and intensity of pain after stroke, focusing on patients’ perspectives. Methods: During a one year period, 416 first-ever stroke patients were included in the population based Lund Stroke Register. After 4 and 16 months (median), 297 patients (98% of survivors) were followed up. Worst pain intensity during the previous 48 hours was assessed on a visual analogue scale (VAS), range 0 to 100: a score of 0 to 30 was defined as no or mild pain; 40 to 100 as moderate to severe pain. NIH stroke scale (NIHSS) score and HbA1c were assessed at baseline. At 16 months, screening for depression was done using the geriatric depression scale (GDS-20), and cognition with the mini-mental state examination (MMSE). Predictors of pain were determined by multivariate analyses. Results: Moderate to severe pain was reported by 96 patients (32%) after four months (VAS median = 60). Predictors of pain were younger age (p = 0.01), female sex (p = 0.006), higher NIHSS score (p Conclusions: Although prevalence of pain after stroke decreased with time, after 16 months 21% had moderate to severe pain. Late pain after stroke was on average more severe, and profoundly affected the patients’ wellbeing.

Background and Purpose— We examined longitudinal changes of quality of life (QOL) covering physical and mental factors in an unselected group of stroke patients and their informal caregivers. Our hypothesis was that informal caregivers would have better QOL than patients at both follow-ups, and that changes, if any, would be related to the patients’ status. Methods— QOL of 304 consecutive stroke patients and their 234 informal caregivers from the population-based Lund Stroke Register was assessed 4 months after stroke onset with the Short Form 36 (SF-36) questionnaire. SF-36 was repeated for both groups after 16 months together with Mini Mental State Examination (MMSE) and Geriatric Depression Scale (GDS-20) for patients. Results— The patients’ mean QOL scores improved between 4 and 16 months after stroke in the socio-emotional and mental SF-36 domains and decreased in the domain physical function. Multivariate analyses showed that the patients’ most important determinants of QOL after 16 months were GDS-20 score, functional status, age, and gender. Informal caregivers had better QOL than patients except for the domain role emotional and the mental component summary. The caregivers’ most important determinants of QOL were their own age and the patients’ functional status. Conclusions— Our study highlights depressive symptoms in determining QOL of stroke patients. Despite self-perceived deterioration in physical function over time, several other components of QOL improved, suggesting internal adaptation to changes in their life situations. Informal caregivers of stroke patients may be under considerable strain as suggested by their lower emotional–mental scores.

The knowledge within medicine is growing rapidly. It has become more and more difficult to decide what knowledge that has to be taught to medical students during their University Medical Degree (MD) education and what has to be omitted from their study plans. As help for teachers and students, a core curriculum of the education defines what is of importance for all students. However, there is a risk of "curriculum overload" with too much information being put into a short time interval. To avoid this and to define what is really the "core" of a course, a national consensus decision may be useful. As an example of this approach, we here report a new joint Swedish core curriculum in neurology for medical students. Teachers responsible for neurological education at all six universities giving University MD education in Sweden have in January 2003 agreed upon the core curriculum that we present. It is our hope that this method can be useful also for other clinical specialities.

The prognosis after TIA may be more serious than previously thought. Recent studies suggest that the risk of subsequent stroke after a TIA may be 5% within the first two days after a TIA, which emphasizes the need for urgent management and institution of therapy. A correct diagnosis is essential, but sometimes difficult because many conditions mimic TIA symptoms. Routine diagnostic procedures include a careful patient history, neurological examination, EKG, CT scan of the brain, and in selected cases carotid and cardiac ultrasound examinations. A recent survey of clinical management after TIA indicates that these investigations are sometimes delayed, particularly in non-hospitalized patients. Patients with a new TIA should immediately be referred to hospital, and ultrasound examination of the carotid arteries (when indicated) should be performed within one week (preferably even earlier) after the TIA onset.

CONTEXT: It has been suggested that total blood homocysteine concentrations are associated with the risk of ischemic heart disease (IHD) and stroke. OBJECTIVE: To assess the relationship of homocysteine concentrations with vascular disease risk. DATA SOURCES: MEDLINE was searched for articles published from January 1966 to January 1999. Relevant studies were identified by systematic searches of the literature for all reported observational studies of associations between IHD or stroke risk and homocysteine concentrations. Additional studies were identified by a hand search of references of original articles or review articles and by personal communication with relevant investigators. STUDY SELECTION: Studies were included if they had data available by January 1999 on total blood homocysteine concentrations, sex, and age at event. Studies were excluded if they measured only blood concentrations of free homocysteine or of homocysteine after a methionine-loading test or if relevant clinical data were unavailable or incomplete. DATA EXTRACTION: Data from 30 prospective or retrospective studies involving a total of 5073 IHD events and 1113 stroke events were included in a meta-analysis of individual participant data, with allowance made for differences between studies, for confounding by known cardiovascular risk factors, and for regression dilution bias. Combined odds ratios (ORs) for the association of IHD and stroke with blood homocysteine concentrations were obtained by using conditional logistic regression. DATA SYNTHESIS: Stronger associations were observed in retrospective studies of homocysteine measured in blood collected after the onset of disease than in prospective studies among individuals who had no history of cardiovascular disease when blood was collected. After adjustment for known cardiovascular risk factors and regression dilution bias in the prospective studies, a 25% lower usual (corrected for regression dilution bias) homocysteine level (about 3 micromol/L [0.41 mg/L]) was associated with an 11% (OR, 0.89; 95% confidence interval [CI], 0.83-0.96) lower IHD risk and 19% (OR, 0.81; 95% CI, 0.69-0.95) lower stroke risk. CONCLUSIONS: This meta-analysis of observational studies suggests that elevated homocysteine is at most a modest independent predictor of IHD and stroke risk in healthy populations. Studies of the impact on disease risk of genetic variants that affect blood homocysteine concentrations will help determine whether homocysteine is causally related to vascular disease, as may large randomized trials of the effects on IHD and stroke of vitamin supplementation to lower blood homocysteine concentrations.

Object. Predictors of early (30-day) and long-term (1-year) mortality rates after primary intracerebral hemorrhage (ICH) were studied in a large population in southern Sweden. Methods. All cases of primary ICH, verified using computerized tomography (CT) scanning or autopsy study, were prospectively registered at the 12 hospitals covering a defined population of 1.14 million during the calendar year 1996. Mortality was analyzed in relation to CT findings (hematoma location and volume and ventricular extension) and clinical parameters (patient age and sex, level of consciousness on admission, and history of preictal risk factors) by using univariate and multivariate statistical methods. Three hundred forty-one cases of primary ICH were detected. The overall mortality rate was 36% at the 30-day and 47% at the 1-year follow up. Multivariate analysis revealed that initial level of consciousness, hematoma volume, and a history of heart disease were independent predictors of death at 30 days postictus. One year after bleeding, independent predictors of mortality were the initial level of consciousness, patient age, and hematoma location. Conclusions. Primary ICH remains a stroke subtype associated with a high mortality rate and for which the level of consciousness on admission is the strongest predictor of fatal outcome both at 30 days and during the 1st year after bleeding. A preictal history of heart disease increased the 30-day mortality rate.

Despite the growing evidence that elevated total homocysteine (tHcy) in plasma is a cardiovascular risk factor, the mechanism underlying the vascular injury is still unknown. Studies are difficult due to the fact that little is known about the formation of different homocysteine species in vivo. In the present study we have investigated the different fractions of tHcy in 21 patients with acute coronary syndromes and elevated concentration of plasma tHcy. A subgroup of the patients (n=16) was investigated before and after a 3 months study period with or without vitamin supplementation (folic acid 5 mg, pyridoxine 40 mg and cyanocobalamin 1 mg once daily). A major finding is that these patients had a lowered ratio (0.95%) between the concentration of reduced homocysteine (HcyH) and tHcy compared to controls (1.38%). A low ratio HcyH/tHcy in plasma in combination with elevated plasma tHcy concentrations might reflect increased oxidative activity or decreased reducing capacity in plasma from the patients. Another main finding in the present study is that, although vitamin supplementation of these patients normalized plasma tHcy, the ratio between HcyH and tHcy did not normalize. Since substantial evidence indicates that progression of arteriosclerosis is related to enhanced oxidant activity, the premature vascular disease associated with increased plasma tHcy concentration might be due to increased oxidative activity and the elevated plasma tHcy concentration may only reflect the increased oxidative stress.

Background and Purpose — Several studies report declining early stroke case fatality, but the findings are not consistent across geographic areas. Corresponding changes in long-term survival are less well documented. We recently reported increased stroke incidence among patients aged Methods — Patients living within the Lund-Orup, Sweden, hospital district and fulfilling the diagnostic criteria for first-ever stroke during 1983–1985 (n=998) and 1993–1995 (n=1318) were followed up concerning survival status at 28 days, 1 year, and 3 years. Age and sex adjustments were performed. The possible influence of Oxfordshire Community Stroke Project (OCSP) stroke subtypes on survival was also analyzed. Results — Overall survival improved between the study periods (Cox proportional hazards regression: hazard ratio, 0.84; 95% confidence limits, 0.75 to 0.94; P =0.0019). The 28-day case fatality was 15% for stroke patients from both study periods. One-year case fatality was 31% for 1983–1985 patients and 27% for 1993–1995 patients. The corresponding figures at 3 years were 44% and 40%, respectively. In the group aged P Conclusions — The recently observed increase in stroke incidence among patients aged

BACKGROUND AND PURPOSE A low risk of recurrent stroke and death after lacunar infarction has previously been reported, but follow-up has been limited to/=5 years.One hundred eighty patients with pure motor stroke, collected between 1983 and 1986 from a hospital-based stroke registry, were followed up until at least 10 years after the index stroke. Two patients were lost to follow-up. Survival status was determined from the official population registry and compared with survival rates of the Swedish population, matched for age and sex. Cox proportional hazards regression analyses were used to identify independent prognostic predictors.During follow-up 106 (60%) of the 178 patients died, most commonly as a result of coronary heart disease. During the first 5 years after the stroke, survival rates were similar to those of the general population. Beyond this time the risk of death was increased among patients with pure motor stroke, with an excess of 10 to 15 percent units compared with the general population. Independent determinants for death were age (P0.01), male sex (P0.01), and nonuse of acetylsalicylic acid (P=0.02). Recurrent stroke occurred in 42 (23.5%) of the patients, corresponding to an annual risk of 2.4%. Hypertension (P=0.025) and diabetes (P=0.024) were independent risk factors for recurrent stroke.For the first few years after lacunar infarct, the risk of death was similar to that of the general population, but later a clear excess of death was observed. The long-term prognosis in lacunar infarction appears less favorable than previously reported.

Multiple small infarcts of different ages are common in small-vessel disease. Diffusion-weighted imaging (DWI) is a powerful method for discriminating new from chronic lesions. This can be done on the diffusion-weighted images provided that b is sufficiently high. Our purpose was to determine that critical value of b. We reviewed DWI from a previous study of acute, mainly lacunar strokes, and selected 18 old lacunar infarcts, well defined on uncoded images with b 0 s/m2 (i. e., T2-weighted images) but invisible on DWI with b 1,200 x 10(6) s/m2. We used a 1.5 tesla imager and single-shot echo-planar technique. We had seven separate acquisitions with echo time 123 ms and b in steps between 0 and 1,200 x 10(6) s/m2. Two neuroradiologists blinded to the selection of lesions carried out two different lesion-detection procedures, thereby testing each lesion four times, giving a total of 72 tests of b values. The results were consistent, indicating a level for detection of 800 x 10(6) s/m2 in two tests, 400-600 x 10(6) s/m2 in 65 tests and at lower values in the remainder. For imagers up to 1.5 tesla, at long repetition times and an echo time up to 120 ms T2-shine through of old lacunar infarcts can be avoided using b of 1,000 x 10(6) s/m2.

Objective: Perfusion-related parameters obtained by intravoxel incoherent motion (IVIM) MR imaging (MRI) were compared with cerebral blood volume and flow (CBV and CBF), retrieved by dynamic susceptibility-contrast (DSC) MRI. Material and Methods: Twenty-eight volunteers (average age 68.5 years) were investigated. Spin-echo echo-planar imaging with IVIM-encoding gradients was employed (36 different b values, 0-1200 s/mm2). The perfusion fraction and the pseudo-diffusion coefficient were calculated for regions in thalamus gray matter and frontal white matter, using asymptotic and full fitting. In DSC-MRI, a Gd-DTPA-BMA contrast-agent bolus was monitored using simultaneous-dual FLASH. Deconvolution of the measured tissue concentration-versus-time curve with an arterial input function from the carotid artery was applied, and maps of CBV and CBF were calculated. Results: The correlation between the perfusion fraction and CBV was r=0.56 ( p Conclusion: The IVIM concept provided results that agreed reasonably with conventional CBV and CBF. The non-linear fitting to noisy signal data was problematic, in accordance with previously presented simulations.

Absolute regional cerebral blood flow (CBF) was measured in ten healthy volunteers, using both dynamic susceptibility-contrast (DSC) magnetic resonance imaging (MRI) and Xe-133 SPECT within 4 h. After i.v. injection of Gd-DTPA-BMA (0.3 mmol/kg b.w.), the bolus was monitored with a Simultaneous Dual FLASH pulse sequence (1.5 s/image), providing one slice through brain tissue and a second slice through the carotid artery. Concentration C(t) is proportional to -(1/TE) ln[S(t)/S(0)] was related to CBF as C(t) = CBF [AIF(t) x R(t)], where AIF is the arterial input function and R(t) is the residue function. A singular-value-decomposition-based deconvolution technique was used for retrieval of R(t). Absolute CBF was given by Zierler's area-to-height relation and the central volume principle. For elimination of large vessels (ELV), all MRI-based CBF values exceeding 2.5 times the mean CBF value of the slice were excluded. A correction for partial-volume effects (CPVE) in the artery used for AIF monitoring was based on registration of signal in a phantom with tubes of various diameters (1.5-6.5 mm), providing an individual concentration correction factor applied to AIF data registered in vivo. In the Xe-133 SPECT investigation, 3,000-4,000 MBq of Xe-133 was administered intravenously, and CBF was calculated using the Kanno Lassen algorithm. When ELV and CPVE were applied, DSC-MRI showed average CBF values from the entire slice of 43 +/- 10 ml/(min 100 g) (small-artery AIF) and 48 +/- 17 ml/(min 100 g) (carotid-artery AIF) (mean +/- S.D., n = 10). The corresponding Xe-133-SPECT-based CBF was 33 +/- 6 ml/(min 100 g) (n = 10). The relationships of CBF(MRI) versus CBF(SPECT) showed good linear correlation (r = 0.74-0.83).

Udgivelsesdato: null-null PURPOSE: Relative regional cerebral blood flow (rCBF) at rest was measured in 44 volunteers using both dynamic susceptibility contrast (DSC) MRI and (99m)Tc-HMPAO SPECT on the same day. METHOD: In MRI, a Gd-DTPA-BMA contrast agent bolus (0.3 mmol/kg body wt) was monitored with a simultaneous dual FLASH pulse sequence (time resolution 1.5 s). MRI-based rCBF images were calculated by singular value decomposition-based deconvolution of the measured tissue concentration-time curve with an arterial input function from a small artery within the imaging slice. In the SPECT investigation, 900 MBq of (99m)Tc-HMPAO was injected intravenously. Relative rCBF in gray matter in the thalamus and in frontal white matter was determined. RESULTS: The ratio of relative rCBF in gray matter to relative rCBF in white matter was 2.21 +/- 0.57 using MRI and 2.24 +/- 0.54 using SPECT (mean +/- SD). CONCLUSION: Relative rCBF maps from DSC MRI and (99m)Tc-HMPAO SPECT showed good agreement, and the MRI-based rCBF ratio correlated with the corresponding SPECT-based ratio (r = 0.79, p < 0.0000006).

The magnetic resonance imaging (MRI) and computed tomography findings in 28 patients with the clinical diagnosis of frontotemporal dementia (FTD) were compared with the findings in a control group of 76 individuals without dementia or stroke. A pattern of frontal and temporal atrophy with predominantly frontal white matter changes was found in the FTD patients, and this was significantly different from the radiological findings in the control group. Six of the FTD patients have undergone autopsy. Histopathological evaluation showed a primary cortical degenerative disease (frontal lobe degeneration of non-Alzheimer type) in 3 of them, and primary white matter disorder, mainly frontal, of basically ischemic type (selective incomplete white matter infarction) in 3 of them. MRI could be a helpful tool to support the clinical diagnosis FTD, especially in young patients. MRI may also be helpful for the differentiation of a primary neurodegenerative from a mainly ischemic-vascular type of dementia.

Regional cerebral blood flow (rCBF) was assessed using dynamic susceptibility-contrast MRI at 1.5 T. A simultaneous dual FLASH pulse sequence and Gd-DTPA-BMA (0.3 mmol/kg b.w.) were used for examination of 43 volunteers, measuring rCBF in frontal white matter (WM) and in gray matter in the thalamus (GM). Arterial input functions (AIFs) were registered 1) in the carotid artery and 2) in an artery within the GM/WM slice. The measured concentration-vs. -time curve was deconvolved with the AIF using both Fourier Transform (FT) and Singular Value Decomposition (SVD). Relative rCBF was given by the height of the deconvolved response curve. For each volunteer, eight different rCBF maps were calculated, representing different combinations of deconvolution techniques, AIFs, and filters. The average GM-WM rCBF ratios ranged from 2.0-2.2, depending on methodology. Absolute rCBF was 68 +/- 28 ml/(min 100 g) in GM and 35 +/- 13 ml/(min 100g) in WM (mean +/- SD, n = 39). GM-WM rCBF ratios obtained using SVD were 6-10% higher than corresponding ratios obtained using FT.

Plasma thiols have been the object of growing interest because numerous studies have indicated that even a mild degree of hyperhomocysteinemia is associated with an increased risk of developing occlusive vascular diseases (1)(2)(3)(4)(5). However, the mechanism behind the vascular injuries is still unknown. Studies of the possible pathogenetic mechanism of increased plasma homocysteine concentrations are difficult because little is known about the mechanism for the formation of different homocysteine species in vivo. We recently published a method that measures reduced and total fractions of homocysteine, cysteine, glutathione, and cysteinylglycine(6). In a preliminary study, we found that patients suffering from stroke have hyperhomocysteinemia, whereas their reduced homocysteine was within the health-related reference interval(7). We hypothesized that the increased concentrations of the oxidized forms of homocysteine in plasma were attributable to a hyperoxidative state in the plasma. We also observed (8) that patients suffering from renal failure had concentrations of reduced homocysteine within the reference interval despite increased total homocysteine. The redox state of homocysteine in plasma may be influenced by other thiols (9), such as glutathione, which is involved in maintaining the intracellular thiols in reduced form. In the present study, we therefore investigated the relationships between homocysteine, cysteine, and glutathione in 29 healthy subjects and 15 patients with renal or liver failure. We used a newly developed preparation procedure, especially designed to minimize several known pitfalls that frequently influence plasma glutathione determinations. Increased hemolysis during sample collection causes falsely increased plasma glutathione measurements because of the high glutathione contents in the blood cells. Plasma glutathione also decreases with time because of the activity of γ-glutamyltransferase in plasma. Furthermore, reduced glutathione disappears within minutes in cell-free plasma because of oxidation(7)(10)(11)(12). In the present study, …

Introduction: In patients with atrial fribrillation (AF), the leading cause of ischemic stroke is cardioembolism. In many patients with stroke, its cause remains unknown and may be due to underdiagnosis of AF, which may become apparent after stroke. We aimed to assess whether the incidence of new-onset AF in patients with unknown etiology stroke exceeds the one in stroke-free population during 10-year follow-up (FU). Methods: Patients with first-ever ischemic stroke (n=336, age 74±11 y, 200 men) and 1:1 age- and gender-matched control subjects without stroke were enrolled in Lund Stroke Register in 2001. AF history prior to admission and new-onset AF during FU were assessed using medical records, an electronic ECG archive and by record linkage with the Swedish Hospital Discharge Register. The mechanism of stroke was assessed using TOAST criteria. Results: By enrolment, 32% of stroke patients and 13% of controls had AF history (p

Transoesophageal echocardiography renders a better image than transthoracic echocardiography of cardiac changes especially at the atrial level, and of atherosclerotic changes in the aorta. Although several studies on stroke patients have included transthoracic and transoesophageal echocardiography, the relevance of the reported findings remains unclear because of limited information on the prevalence of cardiac changes related to cardioembolism in a control population without stroke. In order to define a non-hospitalized group of volunteers without previous stroke or transient ischaemic attack, we randomly selected a group of 68 volunteers (mean age 65.4 years). These volunteers were divided into two groups: the elderly group, 65 years or older (n = 38) and the younger group, younger than 65 years (n = 30). The subjects underwent transthoracic and transoesophageal echocardiography, sonography of the carotid arteries, and magnetic resonance imaging of the brain. The prevalences of atrial septal aneurysm, patent foramen ovale, mitral annulus calcification, and protruding plaque in the aorta were investigated. We found atrial septal aneurysm in 13%, patent foramen ovale in 22%, protruding plaque in the aorta in 7%, and mitral annular calcification in 22% of the 68 subjects. No significant differences were found between the two age groups with the exception of mitral annular calcification, which was seen more often in the older group (P < 0.001). Total cardiac changes related to thromboembolism (including three cases with atrial fibrillation in the older group and other less common cardiac embolic sources) were more common in the older than in the younger group (23/38 vs 9/30; P < 0.05). If mitral annular calcification was excluded, no difference was found between the elderly and the younger group, 14/38 vs 8/30; ns. Even when subjects with a history of heart disease or a pathological ECG were omitted, no differences between the two age groups were found. The causal relationship between a possible embolic source and a clinical embolic event remains unsettled. The high prevalence of cardiac changes in a control population has to be considered when evaluating the significance of similar findings in patients with stroke.

Background and Purpose Abnormal endogenous fibrinolytic activity may be a risk factor for stroke. Since the possible variation of tissue-type plasminogen activator (TPA) antigen and plasminogen activator inhibitor-1 (PAI-1) antigen concentrations over time after stroke has been rarely studied, it was examined in plasma from stroke patients in the acute and convalescent phases of the disease and in a control group. Methods Plasma concentrations of TPA and PAI-1 were determined in 135 stroke patients and in 77 control subjects. All but 4 patients were examined within 7 days after stroke onset, and 32 patients and 18 control subjects were reexamined 2 to 4 years later. Results In the acute phase, stroke patients had significantly higher TPA (median, 10 μg/L) and PAI-1 (median, 14 μg/L) antigen concentrations, compared with control subjects (median values, 6 μg/L [ P =.0001] and 8 μg/L [ P P =.0001), whereas the corresponding difference for PAI-1 antigen levels just failed to reach significance ( P =.05). TPA antigen levels were correlated with concentrations of serum cholesterol (Spearman’s ρ=0.15; P P =.0001), and plasma homocysteine (ρ=0.19; P P =.0001). At reexamination after 2 to 4 years, neither TPA nor PAI-1 levels had changed significantly from the baseline values. Conclusions In stroke patients, high TPA antigen concentrations may indicate an activation of the fibrinolytic system or may be due to a delayed clearance of TPA complexed with inhibitors. High PAI-1 antigen concentrations in patients with cerebral infarction represent increased fibrinolytic inhibition. The findings in this longitudinal study suggest that TPA and PAI-1 antigen concentrations both differ little between the acute and convalescent phases after stroke.

We determined plasma activity of the isoenzymes of beta-hexosaminidase (Hex) in 151 patients with cerebral infarction, since earlier findings have shown a relation between Hex isoenzymes and risk factors for vascular disease in normal subjects. Compared with 206 control subjects, an elevated level of plasma Hex isoenzymes was found in patients with cerebral infarction, particularly females. However, there was no relation to the clinical subtypes of diagnosis or to the presence of any risk factors for vascular disease, such as carotid artery stenosis, major potential cardio-embolic risk factors on echocardiography, hypertension, heart disease, diabetes mellitus or tobacco smoking. Instead, our findings indicate that Hex isoenzymes in patients with cerebral infarction are more influenced by the level of serum aspartate aminotransferase and blood glucose. The main conclusion is that the liver function as reflected by the level of liver enzymes and glucose metabolism are the major determinants of Hex isoenzymes in plasma.

Assessment of the value of blood analysis of the astroglia protein, S-100, and neuron-specific enolase for the detection of nervous system dysfunction after cardiac surgery.Prospective study. Neurologists blinded from laboratory results.University hospital.38 patients undergoing cardiac surgery.21 patients were operated for coronary artery disease; seven patients with replacement of the aortic valve of whom 2 also had coronary bypass. Four patients had mitral valve replacement of whom 2 also had coronary bypass. One patient had both aortic and mitral valve replacement and coronary bypass. Two patients were operated on because of aortic arch aneurysm.Neurologic examinations were performed before and after surgery. General behavior of the patients was repeatedly assessed. Blood samples for analysis were collected before operation and on the second day after surgery. In 8/38 patients (21%), a neurologic complication, one of which was lethal, occurred. In 27 patients (71%), the neurologic outcome was uncomplicated, and in 3 (8%), it could not be classified. Elevated S-100 and neuron-specific enolase levels were found in 7/8 patients who endured a neurologic complication and in 4/27 free of complication. (Fisher's exact test p0.001). Positive and negative predictive values were 64% and 96%, respectively. S-100 (range 0.5 to 1.3 micrograms/L) and neuron-specific enolase levels (range 8.6 to 16.7 micrograms/L) were lower for the 7 patients with nonlethal complications than for the patient who died (9.5 micrograms/L and 31.3 micrograms/L, respectively).S-100 and neuron-specific enolase levels after cardiac surgery are associated with neurologic complications. The results have implications on patient-related treatment and prognosis as well as for the development of safer perfusion techniques.

Objectives. Moderate hyperhomocysteinaemia is an independent risk factor for cardiovascular disease which may be causal. We investigated whether the concentration of plasma homocysteine changes between the acute phase of myocardial infarction and follow-up, and whether treatment with oral folic acid was effective in lowering homocysteine levels in patients with myocardial infarction. Design and subjects. Plasma total homocysteine levels 24–36 h (baseline) after onset of acute myocardial infarction were compared with the levels obtained at 6 weeks' follow-up and with the levels in the controls. In the same patients, we studied the effect on plasma homocysteine of 6 weeks' treatment with daily oral folic acid doses of 2.5 or 10 mg compared to no treatment. Results. At baseline, 12 of 68 patients (18%) had moderate hyperhomocysteinaemia (>17.3 μmol L−1; P < 0.05). Between baseline and follow-up, plasma homocysteine levels increased from 13.1 ± 4.6 to 14.8 ± 4.8 μmol L−1 (mean ± SD; P < 0.001). Treatment with nitroglycerin, streptokinase, beta blockers, or acetylsalicylic acid seemed not to have caused this change. Folic acid lowered plasma homocysteine in all but two of 33 treated patients with a mean decrease of 4.4 μmol L−1 (–27%; P < 0.001). There was no difference between the effect of 2.5 and 10 mg of folic acid. In the untreated group (n = 20), plasma homocysteine increased with a mean increase of 0.6 μmol L−1 (+ 4%; P < 0.05). Conclusions. Plasma homocysteine seems to increase in the post myocardial infarction period, the cause of which warrants further study. Folic acid appears to be an effective treatment for the reduction of both normal and increased plasma homocysteine concentrations in patients with myocardial infarction. This suggests that folic acid should be used for intervention when studying the effect of homocysteine-lowering therapy on the risk on myocardial infarction.

Objectives. Hyperhomocysteinaemia is an independent risk factor for cardiovascular disease. We explored possible determinants of plasma homocysteine and cysteine concentrations amongst middle-aged and elderly subjects. Design and subjects. Of 501 35–95-year-old randomly selected residents of Lund and Malmo, Sweden, 244 (49%; 131 men, 113 women) were investigated. Results. Total plasma homocysteine concentrations were higher in men than in women (mean ± SD: 13.9 ± 4.1 and 12.3 ± 4.1 μmol L−1; P < 0.001), increased markedly with age (Spearman's p = 0.488; P < 0.001), and were correlated (P < 0.001) to concentrations of blood folate, serum vitamin B12, and serum creatine (p = −0.366, −0.338, and 0.463). Users of multivitamins had lower homocysteine levels than nonusers [10.5 ± 3.3 μmol L−1 (n = 31) and 13.5 ± 4.2 μmol L−1 (n = 213), respectively; P < 0.001]. Total plasma cysteine concentrations also increased significantly with age and increasing serum creatinine, but were unrelated to gender, blood folate, serum vitamin B12 and use of multivitamins. Conclusions. Age, gender, folate, serum vitamin B12, serum creatinine and multivitamin usage are all important determinants of the plasma homocysteine concentration, whereas only age and serum creatinine are determinants of the plasma cysteine concentration. The age-related increase in homocysteine and cysteine may be linked to the age-related impairment of renal function, whereas the sex difference in plasma homocysteine may be because of the fact that more homocysteine is formed in men than in women in conjunction with creatine-creatinine synthesis.

To assess the prevalence of asymptomatic abnormalities on magnetic resonance imaging of the brain and their possible relation to hypertension, heart disease, and carotid artery disease, we studied 77 randomly selected subjects (mean age, 65.1 years; range, 36 to 95 years) with no history of focal brain lesions. The study protocol included magnetic resonance imaging of the brain, transthoracic and transesophageal echocardiography, ultrasonography of the carotid arteries, and electrocardiographic recording. Deep and periventricular white matter hyperintensities on magnetic resonance imaging were assessed both separately and together. On magnetic resonance imaging of the brain 62.3% (95% confidence interval [CI], 51.5% to 73.2%) of the subjects had white matter hyperintensities. These abnormalities increased significantly with age (chi 2 test; P = .0001), from 13.6% (95% CI, 0% to 28.0%) of subjects aged younger than 55 years to 85.2% (95% CI, 71.8% to 98.6%) of subjects aged 75 years or older. Six subjects had deep gray matter hyperintensities localized in the basal ganglia, and one had a cerebellar infarction. Stepwise logistic regression analysis identified age and a history of heart disease (but not echocardiographic findings) to be independently associated with deep and periventricular white matter hyperintensities. Hypertension was only independently associated with periventricular white matter hyperintensities. Of the 68 subjects examined with both transthoracic and transesophageal echocardiography, potential cardioembolic sources were detected in 38.2% (95% CI, 26.7% to 49.8%) of the subjects with transthoracic echocardiography and in 47.1% (95% CI, 35.2% to 58.9%) of those with transthoracic and transesophageal echocardiography combined. In subjects aged 75 years or older, a possible cardiac embolic source was detected in 64.0% on transthoracic echocardiography and in 72.0% on transthoracic and transesophageal echocardiography combined, compared with 5.3% and 15.8%, respectively, in subjects aged younger than 55 years. White matter hyperintensities and potential cardioembolic sources are frequently present in asymptomatic individuals, stressing the need for age-matched control subjects in studies of patients with stroke or dementia.

Consecutive electrocardiograms were recorded in 28 stroke patients without signs of primary heart disease. Individuals with subarachnoidal haemorrhage, or electrolyte disturbances were excluded. A computerized tomography of the brain was performed in each case and showed a cerebral haemorrhage (n = 4), cortical infarction (n = 6), subcortical infarction (n = 14) and normal finding (n = 4). One patient developed atrial fibrillation but no other case of serious disturbances in rate of rhythm occurred. None developed AV block, bundle branch blocks or significant changes in QRS complexes. The most common abnormalities in ECG were transient STT changes in lateral leads, which were seen in 13 cases. The typical findings were flat or slightly negative T waves, horizontal or down-sloping ST segments and sometimes a small ST depression. In no case did ECG show typical signs of acute myocardial infarction. A transient prolonged QT interval was seen in three patients and transient U waves in four. ECG did not correlate to the location of the vascular lesion seen on CT or the clinical outcome. It is concluded that STT changes of a small magnitude are seen in about half of the cases of stroke patients without primary heart disease and that they do not resemble the typical pattern of acute myocardial ischaemia.

Moderate hyperhomocysteinaemia is a frequent finding in atherothrombotic cerebrovascular disease. This study confirms and extends this observation. Hyperhomocysteinaemia was present in 57 of 142 survivors with stroke (40%) and in four of 66 controls (6%). Plasma homocysteine concentrations were increased not only in carotid artery disease or lacunar stroke but also in haemorrhagic or embolic strokes. Homocysteine values were unrelated to the presence of hypertension, smoking, or hypercholester-olaemia, or to the concentrations of blood glucose, glycosylated haemoglobin, and plasma fibrinogen. Multiple regression analysis of the patient data showed that about 40% of the variation in plasma homocysteine concentrations could be predicted by the values for the homocysteine metabolism cofactors, blood folate and plasma pyridoxal 5-phosphate and by renal function as reflected in the values for serum creatinine. In patients, urine excretion of homocysteine per unit creatinine was significantly increased and strongly correlated both to the plasma homocysteine concentration and to the values for blood folate, plasma pyridoxal 5-phosphate, and serum vitamin B12. We conclude that moderate hyperhomocysteinaemia is frequently present in cases of stroke, is independent of other stroke risk factors or the type of stroke, and is partly related to renal function and the concentrations of homocysteine metabolism cofactors.

Does Peroral Administration of Factor VIII Induce Oral Tolerance in Patients with Acquired Haemophilia A?

Di-(2-ethylhexyl)phthalate (DEHP), a plasticizer used for polyvinylchloride polymers, has been reported to leach from blood transfusion bags and the plastic material in hemodialysis units into the blood. Phthalate esters are known to be hepatotoxic and teratogenic in experimental animals. Reports on the distribution and metabolism of DEHP indicate that the compound in largely excreted from the body within a few days. In the present investigation the distribution and tissue retention after administration of [14C]DEHP (carbonyl-14C or 2-ethylhexyl-1-14c) was studied in pregnant and non-pregnant mice with whole body autoradiography. Initially a high activity was observed in the brown fat, liver, gall bladder, intestinal contents, kidney and urinary bladder. Pretreatment with DEHP, phenobarbital sodium or 3-methylcholanthrene caused a relative increase of the activity in the brown fat, indicating that induced metabolic conversion of DEHP leads to an increased deposition of radioactivity in brown fat. After administration of DEHP (carbonyl-14C), but not DEHP (2-ethylhexyl-1-14C),marked retention was observed in the skin, cartilage and tendons. The mechanism responsible for the slow accumulation in these connective tissues is not known. In the early embryo a high concentration was observed in the neuroepithelium. This pronounced uptake may be correlated to the DEHP-induced malformations exencephaly and spina bifida observed in mice.

The distribution and retention of arsenic in Marmoset monkeys, given 74As-arsenite (0.4 mg As/kg body weight) i.p., were studied by means of whole-body autoradiography and determination of 74As-levels in tissues and excreta. Only about 30% of the dose was eliminated over 4 days, mainly via the kidneys. All of the arsenic in urine and tissues was found to be in inorganic form. Tissues with highest accumulation 4 days after dosing were liver (about 20% of the dose), squamous epithelium of oral cavity and esophagus, kidney cortex, skin, testes (mainly tubuli seminiferi) and intestinal wall. As a rule the major part of the arsenic in these tissues was found to be associated with cellular organelles. In the liver about 50% of the arsenic was strongly bound to the rough microsomal membranes. In the soluble extract of tissues, arsenic was mainly associated with macromolecular constituents. The long retention time and tight binding of arsenic could partly be explained by the fact that no biotransformation into methylated arsenic occurred, in contrast to all other species studied so far.

The distribution of a number of metals of significance in the work environment has been studied in pregnant experimental animals. Particular interest has been paid to cadmium, inorganic and metallic mercury, lead, chromium and arsenic in different forms. The degree of uptake in the conceptus and the embryonic and fetal distribution patterns vary considerably between different metals and with the stage of development. Cadmium and inorganic mercury showed high placental but low fetal concentrations, except for the early organogenetic period. Metallic mercury was more easily transferred to the fetus than inorganic mercury and was retained in several fetal organs after oxidation to inorganic mercury. Lead was slowly transferred to the fetus; lead levels increased during gestation, a pattern observed with other foreign compounds. Highest levels of lead were seen in fetal blood, liver and skeleton. Arsenite and arsenate both passed relatively freely to the fetus throughout gestation and accumulated preferentially in squamous epithelia. Chromium VI reached higher fetal levels than chromium III and was also more toxic to embryonic cells in vitro, which explains its higher fetotoxicity as compared to chromium III. A number of fetal organs and parental reproductive organs are also listed according to their tendency to accumulate toxic metals.

203Pb(NO3)2 was administered i.v. to pregnant C57BL mice at different stages, from day 8 to day 18 of gestation. The whole animals or excised uteri were subjected to autoradiography or were autopsied for scintillation counting of excised organs. Lead appeared in embryonic and fetal tissues at all stages of gestation. Early (approx. day 8–11) lead was restricted mainly to the embryonic blood, suggesting that free lead was essentially not transferred to the embryo but may have been incorporated in the embryonic hemoglobin when the erythrocytes were formed in the yolk sac placenta (an extraembryonic membrane). From day 12 and later, an uptake was seen in the liver and the cartilaginous skeleton, and from day 14, a strong accumulation was found in calcified bone. This means that the overall fetal concentration increased successively with gestational age of the conceptus. The uptake in fetal liver may be related to the erythropoiesis taking place in the liver in later gestation. While an accumulation of lead was observed in proximal tubuli of the maternal kidney, no corresponding uptake occurred in the fetal kidney. Although lead is teratogenic, causing among others skeletal defects, no effect of inorganic lead in mM concentration was seen on a chondrogenic cell system in vitro. Due to the predominance of lead in hemoglobin, a mechanism of teratogensis based on inhibition of fetal hemoglobin synthesis or function is discussed.

Occupation exposure to metals has been related to impaired reproduction in males. This report summarizes autoradiographic studies on the distribution of cadmium (Cd), chromium (Cr) and arsenic (As) in the testis and epididymis of rodents. Cd and Cr strongly accumulated in the interstitial tissues, indicating an effect on hormone production (Leydig cells) and blood supply or both. Arsenic accumulated in the lumen of the duct of epididymis causing long-term exposure of the semen.

Background and Purpose Stroke patients frequently manifest moderate hyperhomocysteinemia. In most published studies, plasma homocysteine was measured at least 1 month after stroke (or the interval was not reported). To determine whether plasma homocysteine concentrations change in the acute phase, we compared acute-phase values with both convalescent-phase and control values. Methods Plasma homocysteine concentrations were measured in the acute phase (mean, 2 days after stroke onset) in 162 first-ever stroke patients aged 50 years or more (median, 75 years) and again at a median interval of 583 days (range, 460 to 645 days) after stroke onset in a subgroup of 17 patients, with values for 60 age-matched subjects serving as controls. Twenty of the control subjects were reexamined 2 to 3 years after their initial examination. Results The median plasma homocysteine concentration was 13.4 μmol/L in the patient group compared with 13.8 μmol/L for control subjects (NS, Mann-Whitney U test) and increased from 11.4 μmol/L in the acute phase to 14.5 μmol/L in the convalescent phase in the subgroup of patients examined twice ( P Conclusions The post–acute-phase increase in plasma homocysteine may explain why higher values were obtained for stroke patients than for control subjects in previous studies. Possible reasons for the variation in plasma homocysteine concentrations over time are (1) an acute-phase reduction secondary to a decrease in plasma albumin and (2) an increase in plasma homocysteine during the convalescent phase due to modified vitamin intake and/or lifestyle. The timing of plasma homocysteine measurements relative to stroke onset is a factor to be considered in the interpretation of results.

Reduced and total homocysteine, cysteine, glutathione and cysteinylglycine in plasma were investigated in 19 patients with chronic obstructive pulmonary disease and in 29 healthy subjects. The purpose was to examine the influence of pro-oxidant activity caused by the lung disease on the metabolism of homocysteine and other plasma thiols. We observed a decreased concentration of reduced glutathione and a decreased ratio of reduced/total glutathione in the patients compared to the healthy individuals, which supports the hypothesis of an association between free radicals and pathogenesis in some lung diseases. We also observed an increased total plasma homocysteine. The influence of a possible extracellular pro-oxidant activity on the concentration of total plasma homocysteine is discussed.

The aim of the study was to determine the prevalences of carotid artery disease and major and minor potential cardioembolic sources (1) in patients with cerebral infarction and age-matched control subjects and (2) in different clinical subtypes of cerebral infarction. A series of 166 consecutive patients with cerebral infarction and 59 control subjects was examined. The study protocol included clinical subtyping of the cerebral infarctions, ultrasonography of the carotid arteries, transthoracic echocardiography (TTE), transesophageal echocardiography (TEE), ECG, and examination of the brain with computed tomography, magnetic resonance imaging, or autopsy. Carotid artery stenosis > or = 80% or occlusion was present in 35 (21%) patients but in no control subjects (P < .001; chi 2 test). A major potential cardioembolic source was detected in 65 (39%) patients and 3 (5%) control subjects. Atrial fibrillation was present in 35 (21%) patients and 3 (5%) control subjects at initial ECG (P < .01) and in 47 (28%) patients at repeat examination; 17 patients had paroxysmal atrial fibrillation. Sinus rhythm and a major potential cardioembolic source were detected in 18 (11%) patients but in no control subjects (P < .01) at TTE (all patients and control subjects examined) or TEE (118 patients and 52 control subjects examined). The frequency of a minor potential cardioembolic source detectable at TTE or TEE was similar in the patient and control groups (51% and 53%, respectively [NS]) and increased significantly with age. A finding of carotid artery stenosis > or = 80% or occlusion, atrial fibrillation, or a major cardioembolic source detected at TTE or TEE was more frequent among patients with cortical symptoms from anterior or middle cerebral artery territories than among those with lacunar syndromes (66% versus 22%, respectively). The probable source of cerebral infarction was identified in most of the 166 patients: cardiac embolism in 28% of cases (n = 46), carotid artery disease in 8% (n = 14), both cardiac embolism and carotid artery disease in 7% (n = 11), and lacunar infarction in 23% (n = 38). In 57 (34%) of the patients no unequivocal cause of the cerebral infarction was found. The prevalences of carotid artery and heart disease differ significantly between clinical subtypes of cerebral infarction. The cause of cerebral infarction remains uncertain in one third of patients. Because a minor potential cardioembolic source occurs in about 50% of both patients and control subjects, this finding is of questionable value as a risk factor for stroke in the elderly.

Objective: The objective of this study was to assess the level of agreement between stroke subtype classifications made using the Trial of Org 10172 Acute Stroke Treatment (TOAST) and Causative Classification of Stroke (CCS) systems. Methods: Study subjects included 13,596 adult men and women accrued from 20 US and European genetic research centers participating in the National Institute of Neurological Disorders and Stroke (NINDS) Stroke Genetics Network (SiGN). All cases had independently classified TOAST and CCS stroke subtypes. Kappa statistics were calculated for the 5 major ischemic stroke subtypes common to both systems. Results: The overall agreement between TOAST and CCS was moderate (agreement rate, 70%; kappa = 0.59, 95% confidence interval [CI] 0.58-0.60). Agreement varied widely across study sites, ranging from 28% to 90%. Agreement on specific subtypes was highest for large-artery atherosclerosis (kappa = 0.71, 95% CI 0.69-0.73) and lowest for small-artery occlusion (kappa = 0.56, 95% CI 0.54-0.58). Conclusion: Agreement between TOAST and CCS diagnoses was moderate. Caution is warranted when comparing or combining results based on the 2 systems. Replication of study results, for example, genome-wide association studies, should utilize phenotypes determined by the same classification system, ideally applied in the same manner.

Preclinical studies suggest that stem cell therapy (SCT) may improve sensorimotor recovery after stroke. Upper extremity motor impairment (UEMI) is common after stroke, often entailing substantial disability. To evaluate the feasibility of post-stroke UEMI as a target for SCT, we examined a selected sample of stroke patients potentially suitable for SCT, aiming to assess the frequency and recovery of UEMI, as well as its relation to activity limitations and participation restrictions. Patients aged 20–75 years with first-ever ischemic stroke, and National Institutes of Health Stroke Scale (NIHSS) scores 1–18, underwent brain diffusion-weighted MRI within 4 days of stroke onset (n = 108). Survivors were followed up after 3–5 years, including assessment with NIHSS, Fugl-Meyer assessment of upper extremity (FMA-UE), modified Rankin Scale (mRS), and Stroke Impact Scale (SIS). UEMI was defined as NIHSS arm/hand score ≥1. UEMI recovery was evaluated with change in NIHSS arm/hand scores between baseline and follow-up. Of 97 survivors, 84 were available to follow-up. Among 76 subjects (of 84) without recurrent stroke, 41 had UEMI at baseline of which 10 had residual UEMI at follow-up. The FMA-UE showed moderate-severe impairment in seven of 10 survivors with residual UEMI. UEMI was correlated to mRS (r s = 0.49, p

Publisher's version (útgefin grein), Objective: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. Methods We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n=20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. Results: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p[BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p[BI]= 4.4 × 10-10; p [SSBI] = 1.2 × 10 -4), diabetes (p[BI] = 1.7 × 10 -8; p [SSBI] = 2.8 × 10 -3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10 -24), and MRI-defined white matter hyperintensity burden (p [BI]=1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. Conclusion: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI., CHAP: R01-AG-11101, R01-AG-030146, NIRP-14-302587. SMART: This study was supported by a grant from the Netherlands Organization for Scientific Research–Medical Sciences (project no. 904-65–095). LBC: The authors thank the LBC1936 participants and the members of the LBC1936 research team who collected and collated the phenotypic and genotypic data. The LBC1936 is supported by Age UK (Disconnected Mind Programme grant). The work was undertaken by The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross-council Lifelong Health and Wellbeing Initiative (MR/K026992/1). The brain imaging was performed in the Brain Research Imaging Centre (https://www.ed.ac.uk/clinical-sciences/edinburgh-imaging), a center in the SINAPSE Collaboration (sinapse.ac.uk) supported by the Scottish Funding Council and Chief Scientist Office. Funding from the UK Biotechnology and Biological Sciences Research Council (BBSRC) and the UK Medical Research Council is acknowledged. Genotyping was supported by a grant from the BBSRC (ref. BB/F019394/1). PROSPER: The PROSPER study was supported by an investigator-initiated grant obtained from Bristol-Myers Squibb. Prof. Dr. J.W. Jukema is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Support for genotyping was provided by the seventh framework program of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810). SCES and SiMES: National Medical Research Council Singapore Centre Grant NMRC/CG/013/2013. C.-Y.C. is supported by the National Medical Research Council, Singapore (CSA/033/2012), Singapore Translational Research Award (STaR) 2013. Dr. Kamran Ikram received additional funding from the Singapore Ministry of Health's National Medical Research Council (NMRC/CSA/038/2013). SHIP: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs, as well as the Social Ministry of the Federal State of Mecklenburg–West Pomerania, and the network “Greifswald Approach to Individualized Medicine (GANI_MED)” funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany, and the Federal State of Mecklenburg–West Pomerania. Whole-body MRI was supported by a joint grant from Siemens Healthineers, Erlangen, Germany, and the Federal State of Mecklenburg–West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. OATS (Older Australian Twins Study): OATS was supported by an Australian National Health and Medical Research Council (NHRMC)/Australian Research Council (ARC) Strategic Award (ID401162) and by a NHMRC grant (ID1045325). OATS was facilitated via access to the Australian Twin Registry, which is supported by the NHMRC Enabling Grant 310667. The OATS genotyping was partly supported by a Commonwealth Scientific and Industrial Research Organisation Flagship Collaboration Fund Grant. NOMAS: The Northern Manhattan Study is funded by the NIH grant “Stroke Incidence and Risk Factors in a Tri-Ethnic Region” (NINDS R01NS 29993). TASCOG: NHMRC and Heart Foundation. AGES: The study was funded by the National Institute on Aging (NIA) (N01-AG-12100), Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament), with contributions from the Intramural Research Programs at the NIA, the National Heart, Lung, and Blood Institute (NHLBI), and the National Institute of Neurological Disorders and Stroke (NINDS) (Z01 HL004607-08 CE). ERF: The ERF study as a part of European Special Populations Research Network (EUROSPAN) was supported by European Commission FP6 STRP grant no. 018947 (LSHG-CT-2006-01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007–2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme “Quality of Life and Management of the Living Resources” of 5th Framework Programme (no. QLG2-CT-2002-01254). High-throughput analysis of the ERF data was supported by a joint grant from Netherlands Organization for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043). Exome sequencing analysis in ERF was supported by the ZonMw grant (project 91111025). Najaf Amin is supported by the Netherlands Brain Foundation (project no. F2013[1]-28). ARIC: The Atherosclerosis Risk in Communities study was performed as a collaborative study supported by NHLBI contracts (HHSN268201100005C, HSN268201100006C, HSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), R01HL70825, R01HL087641, R01HL59367, and R01HL086694; National Human Genome Research Institute contract U01HG004402; and NIH contract HHSN268200625226C. Infrastructure was partly supported by grant no. UL1RR025005, a component of the NIH and NIH Roadmap for Medical Research. This project was also supported by NIH R01 grant NS087541 to M.F. FHS: This work was supported by the National Heart, Lung and Blood Institute's Framingham Heart Study (contracts no. N01-HC-25195 and no. HHSN268201500001I), and its contract with Affymetrix, Inc. for genotyping services (contract no. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. This study was also supported by grants from the NIA (R01s AG033040, AG033193, AG054076, AG049607, AG008122, and U01-AG049505) and the NINDS (R01-NS017950, UH2 NS100605). Dr. DeCarli is supported by the Alzheimer's Disease Center (P30 AG 010129). ASPS: The research reported in this article was funded by the Austrian Science Fund (FWF) grant nos. P20545-P05, P13180, and P20545-B05, by the Austrian National Bank Anniversary Fund, P15435, and the Austrian Ministry of Science under the aegis of the EU Joint Programme–Neurodegenerative Disease Research (JPND) (jpnd.eu). LLS: The Leiden Longevity Study has received funding from the European Union's Seventh Framework Programme (FP7/2007–2011) under grant agreement no. 259679. This study was supported by a grant from the Innovation-Oriented Research Program on Genomics (SenterNovem IGE05007), the Centre for Medical Systems Biology, and the Netherlands Consortium for Healthy Ageing (grant 050-060-810), all in the framework of the Netherlands Genomics Initiative, Netherlands Organization for Scientific Research (NWO), UnileverColworth, and by BBMRI-NL, a Research Infrastructure financed by the Dutch government (NWO 184.021.007). CHS: This CHS research was supported by contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, N01HC15103, and HHSN268200960009C and grants U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, R01HL085251, and R01HL130114 from the NHLBI with additional contribution from NINDS. Additional support was provided through R01AG023629 from the NIA. A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Rotterdam Study: The generation and management of GWAS genotype data for the Rotterdam Study is supported by the Netherlands Organisation of Scientific Research (NWO) Investments (no. 175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/NWO project no. 050-060-810. The Rotterdam Study is funded by Erasmus MC Medical Center and Erasmus MC University, Rotterdam, Netherlands Organization for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. M.A.I. is supported by an NWO Veni grant (916.13.054). The 3-City Study: The 3-City Study is conducted under a partnership agreement among the Institut National de la Santé et de la Recherche Médicale (INSERM), the University of Bordeaux, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study is also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, Mutuelle Générale de l’Education Nationale (MGEN), Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Programme “Cohortes et collections de données biologiques.” C.T. and S.D. have received investigator-initiated research funding from the French National Research Agency (ANR) and from the Fondation Leducq. S.D. is supported by a starting grant from the European Research Council (SEGWAY), a grant from the Joint Programme of Neurodegenerative Disease research (BRIDGET), from the European Union's Horizon 2020 research and innovation programme under grant agreements No 643417 & No 640643, and by the Initiative of Excellence of Bordeaux University. Part of the computations were performed at the Bordeaux Bioinformatics Center (CBiB), University of Bordeaux. This work was supported by the National Foundation for Alzheimer's Disease and Related Disorders, the Institut Pasteur de Lille, the Labex DISTALZ, and the Centre National de Génotypage. ADGC: The Alzheimer Disease Genetics Consortium is supported by NIH. NIH-NIA supported this work through the following grants: ADGC, U01 AG032984, RC2 AG036528; NACC, U01 AG016976; NCRAD, U24 AG021886; NIA LOAD, U24 AG026395, U24 AG026390; Banner Sun Health Research Institute, P30 AG019610; Boston University, P30 AG013846, U01 AG10483, R01 CA129769, R01 MH080295, R01 AG017173, R01 AG025259, R01AG33193; Columbia University, P50 AG008702, R37 AG015473; Duke University, P30 AG028377, AG05128; Emory University, AG025688; Group Health Research Institute, UO1 AG06781, UO1 HG004610; Indiana University, P30 AG10133; Johns Hopkins University, P50 AG005146, R01 AG020688; Massachusetts General Hospital, P50 AG005134; Mayo Clinic, P50 AG016574; Mount Sinai School of Medicine, P50 AG005138, P01 AG002219; New York University, P30 AG08051, MO1RR00096, UL1 RR029893, 5R01AG012101, 5R01AG022374, 5R01AG013616, 1RC2AG036502, 1R01AG035137; Northwestern University, P30 AG013854; Oregon Health & Science University, P30 AG008017, R01 AG026916; Rush University, P30 AG010161, R01 AG019085, R01 AG15819, R01 AG17917, R01 AG30146; TGen, R01 NS059873; University of Alabama at Birmingham, P50 AG016582, UL1RR02777; University of Arizona, R01 AG031581; University of California, Davis, P30 AG010129; University of California, Irvine, P50 AG016573, P50, P50 AG016575, P50 AG016576, P50 AG016577; University of California, Los Angeles, P50 AG016570; University of California, San Diego, P50 AG005131; University of California, San Francisco, P50 AG023501, P01 AG019724; University of Kentucky, P30 AG028383, AG05144; University of Michigan, P50 AG008671; University of Pennsylvania, P30 AG010124; University of Pittsburgh, P50 AG005133, AG030653; University of Southern California, P50 AG005142; University of Texas Southwestern, P30 AG012300; University of Miami, R01 AG027944, AG010491, AG027944, AG021547, AG019757; University of Washington, P50 AG005136; Vanderbilt University, R01 AG019085; and Washington University, P50 AG005681, P01 AG03991. The Kathleen Price Bryan Brain Bank at Duke University Medical Center is funded by NINDS grant NS39764, NIMH MH60451, and by GlaxoSmithKline. Genotyping of the TGEN2 cohort was supported by Kronos Science. The TGen series was also funded by NIA grant AG041232, the Banner Alzheimer's Foundation, The Johnnie B. Byrd Sr. Alzheimer's Institute, the Medical Research Council, and the state of Arizona and also includes samples from the following sites: Newcastle Brain Tissue Resource (funding via the Medical Research Council [MRC], local NHS trusts, and Newcastle University), MRC London Brain Bank for Neurodegenerative Diseases (funding via the Medical Research Council), South West Dementia Brain Bank (funding via numerous sources including the Higher Education Funding Council for England [HEFCE], Alzheimer's Research Trust [ART], BRACE, as well as North Bristol NHS Trust Research and Innovation Department and DeNDRoN), The Netherlands Brain Bank (funding via numerous sources including Stichting MS Research, Brain Net Europe, Hersenstichting Nederland Breinbrekend Werk, International Parkinson Fonds, Internationale Stiching Alzheimer Onderzoek), Institut de Neuropatologia, Servei Anatomia Patologica, and Universitat de Barcelona). ADNI: Funding for ADNI is through the Northern California Institute for Research and Education by grants from Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, GlaxoSmithKline, Innogenetics, Johnson & Johnson, Eli Lilly and Co., Medpace, Inc., Merck and Co., Inc., Novartis AG, Pfizer Inc, F. Hoffman-La Roche, Schering-Plough, Synarc, Inc., Alzheimer's Association, Alzheimer's Drug Discovery Foundation, the Dana Foundation, and the National Institute of Biomedical Imaging and Bioengineering and NIA grants U01 AG024904, RC2 AG036535, and K01 AG030514. Support was also provided by the Alzheimer's Association (LAF, IIRG-08-89720; MAP-V, IIRG-05-14147) and the US Department of Veterans Affairs Administration, Office of Research and Development, Biomedical Laboratory Research Program. SiGN: Stroke Genetic Network (SiGN) was supported in part by award nos. U01NS069208 and R01NS100178 from NINDS. Genetics of Early-Onset Stroke (GEOS) Study was supported by the NIH Genes, Environment and Health Initiative (GEI) grant U01 HG004436, as part of the GENEVA consortium under GEI, with additional support provided by the Mid-Atlantic Nutrition and Obesity Research Center (P30 DK072488); and the Office of Research and Development, Medical Research Service, and the Baltimore Geriatrics Research, Education, and Clinical Center of the Department of Veterans Affairs. Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to Johns Hopkins University (contract no. HHSN268200782096C). Assistance with data cleaning was provided by the GENEVA Coordinating Center (U01 HG 004446; PI Bruce S. Weir). Study recruitment and assembly of datasets were supported by a Cooperative Agreement with the Division of Adult and Community Health, Centers for Disease Control and Prevention, and by grants from NINDS and the NIH Office of Research on Women's Health (R01 NS45012, U01 NS069208-01). METASTROKE: ASGC: Australian population control data were derived from the Hunter Community Study. This research was funded by grants from the Australian National and Medical Health Research Council (NHMRC Project Grant ID: 569257), the Australian National Heart Foundation (NHF Project Grant ID: G 04S 1623), the University of Newcastle, the Gladys M Brawn Fellowship scheme, and the Vincent Fairfax Family Foundation in Australia. E.G.H. was supported by a Fellowship from the NHF and National Stroke Foundation of Australia (ID: 100071). J.M. was supported by an Australian Postgraduate Award. BRAINS: Bio-Repository of DNA in Stroke (BRAINS) is partly funded by a Senior Fellowship from the Department of Health (UK) to P.S., the Henry Smith Charity, and the UK-India Education Research Institutive (UKIERI) from the British Council. GEOS: Genetics of Early Onset Stroke (GEOS) Study, Baltimore, was supported by GEI Grant U01 HG004436, as part of the GENEVA consortium under GEI, with additional support provided by the Mid-Atlantic Nutrition and Obesity Research Center (P30 DK072488), and the Office of Research and Development, Medical Research Service, and the Baltimore Geriatrics Research, Education, and Clinical Center of the Department of Veterans Affairs. Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to the Johns Hopkins University (contract no. HHSN268200782096C). Assistance with data cleaning was provided by the GENEVA Coordinating Center (U01 HG 004446; PI Bruce S. Weir). Study recruitment and assembly of datasets were supported by a Cooperative Agreement with the Division of Adult and Community Health, Centers for Disease Control and Prevention, and by grants from NINDS and the NIH Office of Research on Women's Health (R01 NS45012, U01 NS069208-01). HPS: Heart Protection Study (HPS) (ISRCTN48489393) was supported by the UK MRC, British Heart Foundation, Merck and Co. (manufacturers of simvastatin), and Roche Vitamins Ltd. (manufacturers of vitamins). Genotyping was supported by a grant to Oxford University and CNG from Merck and Co. J.C.H. acknowledges support from the British Heart Foundation (FS/14/55/30806). ISGS: Ischemic Stroke Genetics Study (ISGS)/Siblings With Ischemic Stroke Study (SWISS) was supported in part by the Intramural Research Program of the NIA, NIH project Z01 AG-000954-06. ISGS/SWISS used samples and clinical data from the NIH-NINDS Human Genetics Resource Center DNA and Cell Line Repository (ccr.coriell.org/ninds), human subjects protocol nos. 2003-081 and 2004-147. ISGS/SWISS used stroke-free participants from the Baltimore Longitudinal Study of Aging (BLSA) as controls. The inclusion of BLSA samples was supported in part by the Intramural Research Program of the NIA, NIH project Z01 AG-000015-50, human subjects protocol no. 2003-078. The ISGS study was funded by NIH-NINDS Grant R01 NS-42733 (J.F.M.). The SWISS study was funded by NIH-NINDS Grant R01 NS-39987 (J.F.M.). This study used the high-performance computational capabilities of the Biowulf Linux cluster at the NIH (biowulf.nih.gov). MGH-GASROS: MGH Genes Affecting Stroke Risk and Outcome Study (MGH-GASROS) was supported by NINDS (U01 NS069208), the American Heart Association/Bugher Foundation Centers for Stroke Prevention Research 0775010N, the NIH and NHLBI's STAMPEED genomics research program (R01 HL087676), and a grant from the National Center for Research Resources. The Broad Institute Center for Genotyping and Analysis is supported by grant U54 RR020278 from the National Center for Research resources. Milan: Milano–Besta Stroke Register Collection and genotyping of the Milan cases within CEDIR were supported by the Italian Ministry of Health (grant nos.: RC 2007/LR6, RC 2008/LR6; RC 2009/LR8; RC 2010/LR8; GR-2011-02347041), FP6 LSHM-CT-2007-037273 for the PROCARDIS control samples. WTCCC2: Wellcome Trust Case-Control Consortium 2 (WTCCC2) was principally funded by the Wellcome Trust, as part of the Wellcome Trust Case Control Consortium 2 project (085475/B/08/Z and 085475/Z/08/Z and WT084724MA). The Stroke Association provided additional support for collection of some of the St George's, London cases. The Oxford cases were collected as part of the Oxford Vascular Study, which is funded by the MRC, Stroke Association, Dunhill Medical Trust, National Institute of Health Research (NIHR), and the NIHR Biomedical Research Centre, Oxford. The Edinburgh Stroke Study was supported by the Wellcome Trust (clinician scientist award to C.L.M.S.) and the Binks Trust. Sample processing occurred in the Genetics Core Laboratory of the Wellcome Trust Clinical Research Facility, Western General Hospital, Edinburgh. Much of the neuroimaging occurred in the Scottish Funding Council Brain Imaging Research Centre (https://www.ed.ac.uk/clinical-sciences/edinburgh-imaging), Division of Clinical Neurosciences, University of Edinburgh, a core area of the Wellcome Trust Clinical Research Facility, and part of the SINAPSE (Scottish Imaging Network: A Platform for Scientific Excellence) collaboration (sinapse.ac.uk), funded by the Scottish Funding Council and the Chief Scientist Office. Collection of the Munich cases and data analysis was supported by the Vascular Dementia Research Foundation. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements no. 666881, SVDs@target (to M.D.) and no. 667375, CoSTREAM (to M.D.); the DFG as part of the Munich Cluster for Systems Neurology (EXC 1010 SyNergy) and the CRC 1123 (B3) (to M.D.); the Corona Foundation (to M.D.); the Fondation Leducq (Transatlantic Network of Excellence on the Pathogenesis of Small Vessel Disease of the Brain) (to M.D.); the e:Med program (e:AtheroSysMed) (to M.D.) and the FP7/2007-2103 European Union project CVgenes@target (grant agreement no. Health-F2-2013-601456) (to M.D.). M.F. and A.H. acknowledge support from the BHF Centre of Research Excellence in Oxford and the Wellcome Trust core award (090532/Z/09/Z). VISP: The GWAS component of the Vitamin Intervention for Stroke Prevention (VISP) study was supported by the US National Human Genome Research Institute (NHGRI), grant U01 HG005160 (PI Michèle Sale and Bradford Worrall), as part of the Genomics and Randomized Trials Network (GARNET). Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to Johns Hopkins University. Assistance with data cleaning was provided by the GARNET Coordinating Center (U01 HG005157; PI Bruce S. Weir). Study recruitment and collection of datasets for the VISP clinical trial were supported by an investigator-initiated research grant (R01 NS34447; PI James Toole) from the US Public Health Service, NINDS, Bethesda, MD. Control data obtained through the database of genotypes and phenotypes (dbGAP) maintained and supported by the United States National Center for Biotechnology Information, US National Library of Medicine. WHI: Funding support for WHI-GARNET was provided through the NHGRI GARNET (grant no. U01 HG005152). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GARNET Coordinating Center (U01 HG005157). Funding support for genotyping, which was performed at the Broad Institute of MIT and Harvard, was provided by the GEI (U01 HG004424). R.L. is a senior clinical investigator of FWO Flanders. F.W.A. is supported by a Dekker scholarship-Junior Staff Member 2014T001–Netherlands Heart Foundation and UCL Hospitals NIHR Biomedical Research Centre.