OBJECTIVE:To discover, by using metabolomics, novel candidate biomarkers for stroke recurrence (SR) with a higher prediction power than present ones.
METHODS:Metabolomic analysis was performed by ...liquid chromatography coupled to mass spectrometry in plasma samples from an initial cohort of 131 TIA patients recruited <24 hours after the onset of symptoms. Pattern analysis and metabolomic profiling, performed by multivariate statistics, disclosed specific SR and large-artery atherosclerosis (LAA) biomarkers. The use of these methods in an independent cohort (162 subjects) confirmed the results obtained in the first cohort.
RESULTS:Metabolomics analyses could predict SR using pattern recognition methods. Low concentrations of a specific lysophosphatidylcholine (LysoPC16:0) were significantly associated with SR. Moreover, LysoPC(20:4) also arose as a potential SR biomarker, increasing the prediction power of age, blood pressure, clinical features, duration of symptoms, and diabetes scale (ABCD2) and LAA. Individuals who present early (<3 months) recurrence have a specific metabolomic pattern, differing from non-SR and late SR subjects. Finally, a potential LAA biomarker, LysoPC(22:6), was also described.
CONCLUSIONS:The use of metabolomics in SR biomarker research improves the predictive power of conventional predictors such as ABCD2 and LAA. Moreover, pattern recognition methods allow us to discriminate not only SR patients but also early and late SR cases.
In-hospital stroke death rate is an important sanitary issue. Despite advances in the acute phase management of stroke patients, mortality and disability rates remain high. In aging populations and ...with different mortality between the sexes in general, the study of sex- and age-related differences becomes increasingly relevant for optimization of post-acute clinical care of stroke patients.
We designed a cohort follow-up study with 13,932 consecutive ischemic stroke (IS) patients from 19 Spanish hospitals. Data was obtained from the Spanish Stroke Registry; transient ischemic attacks and ages <18 years were excluded. Patients were organised by age group and sex. We compared female and male patient cohorts within and across age groups univariately and used multivariable logistic regression to adjust for confounders in differential in-hospital mortality.
The median (percentiles 2.5 and 97.5%) age was 78 (41-92) years old for women and 71 (41-92) for men. IS women were more likely to be older, to exhibit cardio-embolic aetiology, and less likely to have been admitted to a stroke unit or to have had a stroke code activated. Both pre-stroke modified Rankin Scale and National Institute of Health Stroke Scale (NIHSS) scores at admission increased significantly with age and were higher in women than those in men. Differences in distributions of common risk factors for IS and of in-hospital outcomes between women and men actually changed with patient's age. It is to be noted here that although there were no statistically significant differences (p > 0.05) between the sexes within any age group, in-hospital mortality appeared significantly higher in women than that in men when analysed overall, due to confounding. Death was more closely related to stroke in women than in men and occurred earlier. Although there were some age-specific sex differences between the predictors for in-hospital mortality, stroke severity measured by NIHSS was the main predictor of in-hospital mortality for both sexes. Topographic classifications - partial anterior circulatory infarct and total anterior circulatory infarct - were significant prognostic factors for men aged <60 years and for those in the 60-69 years range respectively.
Although most of our findings were consistent with previous studies, it is important to take into account and highlight differences in in-hospital mortality between the sex and age group. Not to account for age-related differences between the sexes can give false results that may mislead management decisions. As most deaths in women were related to stroke, it is important to improve their early management, stroke code activation, access to stroke units and/or revascularisation therapies, especially in the older age groups.
Airway obstruction (AO) is associated with hypoxemia, systemic inflammation and oxidative stress. These conditions can favor the formation of Advanced Glycation End-products (AGEs) and induce ...mitochondrial stress. The latter can alter metabolite intermediates in the Krebs cycle leading to the formation of the cysteine-fumarate adduct S-(2-succino) cysteine (2SC) in proteins (protein succination). Protein succination has not been described in airways diseases.
To assess differences in levels of AGEs and 2SC between patients with AO and normal spirometry.
and Methods: In this case-control study, we investigated 35 moderate to severe AO patients and 31 subjects with normal spirometry, matched for age, gender, body mass index (BMI), tobacco history, prediabetes and adherence to Mediterranean diet. Plasma 2SC and AGEs concentrations were measured by GS/MS, and AGEs in skin were determined measuring autofluorescence (SAF). Multivariate logistic regression models explored the association between AGEs in the skin, 2SC and the presence of AO.
The population was predominantly middle-age (mean of 58.7 years-old), overweight (median of BMI 26.7 kg/m2) and male subjects (69.7%). Patients with AO showed higher values of SAF (p = 0.04) and 2SC (p = 0.047). No differences were observed for plasma AGEs. SAF and 2SC were significantly associated with the presence of AO after adjusting for age, gender, smoking history, BMI and Mediterranean diet score (p = 0.041 and p = 0.038, respectively).
Skin AGEs and 2SC are increased in patients with moderate to severe AO and independently associated with its presence. Further studies should confirm these findings and explore their potential role as a biomarker for the disease.
•Airway obstruction (AO) is associated with hypoxemia, systemic inflammation and oxidative stress.•These conditions can favor the formation of Advanced Glycation End-products (AGEs) and induce mitochondrial stress.•This leads the formation of the cysteine-fumarate adduct S-(2-succino) cysteine (2SC) in proteins (protein succination).•S-(2-succino) cysteine (2SC) levels and AGE skin levels are increased in moderate to severe AO patients.•These molecules have a potential role as biomarkers for AO.
Aim: Advanced glycation end-products (AGEs) have been involved in the atherogenic process in the high-risk population. The goal of this study was to demonstrate that AGEs are related to subclinical ...atheromatous disease in subjects with low to moderate vascular risk.Methods: A cross-sectional study in which 2,568 non-diabetic subjects of both sexes without cardiovascular disease were included. Subcutaneous content of AGEs was assessed by skin autofluorescence (SAF) and subclinical atheromatous disease was measured by assessing the atheromatous plaque burden in carotid and femoral regions using ultrasonography. In addition, serum pentosidine, carboxymethyl-lysine (CML) and AGE receptors (RAGE) were assessed in a nested case-control study with 41 subjects without plaque and 41 individuals subjects with generalized disease.Results: Patients with atheromatous plaque had a higher SAF than those with no plaque (1.9 1.7 to 2.3 vs. 1.8 1.6 to 2.1 arbitrary units (AU), p＜0.001). The SAF correlated with the total number of affected regions (r= 0.171, p＜0.001), increasing progressively from 1.8 1.6 to 2.1 AU in those without atheromatous disease to 2.3 1.9 to 2.7 AU in patients with ≥ 8 plaques (p＜0.001). A correlation was also observed between SAF and the total plaque area (r=0.113, p＜0.001). The area under the Receiver Operating Characteristic curve was 0.65 (0.61 to 0.68) for identifying male subjects with atheromatous disease. The multivariable logistic regression model showed a significant and independent association between SAF and the presence of atheromatous disease. However, no significant differences in serum pentosidine, CML, and RAGE were observed.Conclusions: Increased subcutaneous content of AGEs is associated with augmented atheromatous plaque burden. Our results suggest that SAF may provide clinically relevant information to the current strategies for the evaluation of cardiovascular risk, especially among the male population.
Aims
Patients with type 2 diabetes have been considered a susceptible group for pulmonary dysfunction. Our aim was to assess pulmonary function on the prediabetes stage.
Methods
Pulmonary function ...was assessed in 4,459 non-diabetic subjects, aged between 45 and 70 years, without cardiovascular disease or chronic pulmonary obstructive disease from the ongoing study ILERVAS. A “restrictive spirometric pattern”, an “abnormal FEV1” and an “obstructive ventilatory defect” were assessed. Prediabetes was defined by glycosylated hemoglobin (HbA1c) between 5.7 and 6.4% according to the American Diabetes Association criteria.
Results
Population was composed of 52.1% women, aged 57 53;63 years, a BMI of 28.6 25.8;31.8 kg/m
2
, and with a prevalence of prediabetes of 29.9% (
n
= 1392). Subjects with prediabetes had lower forced vital capacity (FVC: 93 82;105 vs. 96 84;106,
p
< 0.001) and lower forced expired volume in the first second (FEV1: 94 82;107 vs. 96 84;108,
p
= 0.011), as well as a higher percentage of the restrictive spirometric pattern (16.5% vs. 13.6%,
p
= 0.015) and FEV1 < 80% (20.3% vs. 17.2%,
p
= 0.017) compared to non-prediabetes group. In the prediabetes group, HbA1c was negatively correlated with both pulmonary parameters (FVC:
r
= − 0.113,
p
< 0.001; FEV1:
r
= − 0.079,
p
= 0.003). The multivariable logistic regression model in the whole population showed that there was a significant and independent association between HbA1c with both restrictive spirometric pattern OR = 1.42 (1.10–1.83),
p
= 0.008 and FEV1 < 80% OR = 1.50 (1.19–1.90),
p
= 0.001.
Conclusions
The deleterious effect of type 2 diabetes on pulmonary function appears to be initiated in prediabetes, and it is related to metabolic control.
Trial registration ClinicalTrials.gov
NCT03228459.
The delay in seeking medical care in patients who suffer a cerebrovascular disease (CVD) event depends, largely, on knowledge of the disease. Our aim is to study the evolution of the knowledge of ...patients admitted to hospital due to an ischaemic stroke.
A structured interview was used to determine the level of knowledge of CVD (terminology, risk factors, symptoms and attitude) of patients admitted due to an ischaemic stroke without language impairment or cognitive impairment in two distinct time periods: January 2011 and December 2013 (n = 295), and October 2015 and December 2016 (n = 325).
Better knowledge of the disease was observed over time, both in the number of terms recognised - 4.1 (standard deviation: 2) vs. 4.8 (standard deviation: 1.7); p < 0.001 - and in a good knowledge of symptoms (more than three factors and less than two distractors) (56.6 vs. 69.8%; p < 0.001). The proportion of patients who called the emergency services directly was significantly higher (17.3 vs. 24.6%; p = 0.003), as was the recognition of the term 'stroke' (51.9 vs. 74.5%; p < 0.001). There was no difference in the degree of knowledge of risk factors. Improvement in knowledge did not translate into a decrease in the delay between symptom onset and arrival at the hospital.
Despite improved knowledge of CVD, further efforts still need to be made to improve attitudes towards CVD and reduce the delay prior to hospital arrival.
Recent studies have demonstrated that there is a decrease in the risk of subsequent stroke after transient ischemic attack (TIA) when urgent care (UC) is administered. However, no meta-analysis has ...been developed with contemporaneous TIA studies. We perform a systematic review and a meta-analysis to establish the risk of early stroke recurrence (SR) considering data from studies that offered UC to TIA patients.
We searched for studies, without language restriction, from January 2007 to January 2015 according to PRISMA guidelines. We included studies with TIA patients who underwent UC and reported the proportion of SR at 90 days. We excluded studies that were centered on less than 100 patients and cohorts including both stroke and TIA, if stroke risk after TIA was not described. For its relevance, we included the TIAregistry.org study published in 2016. We performed both fixed and random effects meta-analyses to determine SR and assess sources of heterogeneity.
From 4,103 identified citations, we selected 15 papers that included 14,889 patients. There was great variation in terms of the number of patients included in each study, ranging from 115 to 4,160. Seven studies were TIA clinic based. The mean age and the percentage of men were similar among studies, ranging from 62.4 to 73.1 years and 45.1-62%, respectively. The reported risk of stroke ranged from 0 to 1.46% 2 days after TIA (9 studies included), 0-2.55% 7 days after TIA (11 studies included), 1.91-2.85% 30 days after TIA (4 studies included), and 0.62-4.76% 90 days after TIA (all studies included). The pooled stroke risk was 3.42% (95% CI 3.14-3.74) at 90 days, 2.78% (95% CI 2.47-3.12) at 30 days, 2.06% (95% CI 1.83-2.33) at 7 days and 1.36% (95% CI 1.15-1.59) at 2 days. Although we did not find statistically significant heterogeneity in SR among studies, those with a higher proportion of patients with motor weakness had a significantly higher risk of SR. No statistically significant association was observed between TIA clinic management and SR.
The pooled early SR is lower than in previous meta-analyses and homogeneous for all studies with an urgent assessment and management strategy regardless of vascular risk factors and clinical characteristics. Therefore, the best setting for TIA management can be individualized for each center.
BACKGROUND AND PURPOSE—Stroke Risk Analysis (SRA) comprises an algorithm for automated analysis of ECG monitoring, enabling the detection of paroxysmal atrial fibrillation (pxAF) and identifying ...patterns indicating a high risk of atrial fibrillation (R_AF). We compared Holter-enabled continuous ECG monitoring in combination with SRA (hSRA) with standard continuous ECG monitoring for pxAF detection in patients with acute ischemic stroke. Also, we sought to identify whether the detection of R_AF patterns during the first cycle (first 2 hours) of hSRA recording was associated with the detection of pxAF during the Stroke Unit stay.
METHODS—We enrolled 524 consecutive patients admitted in the Stroke Unit with acute ischemic stroke or transient ischemic attack with neither history of AF nor AF at admission into a prospective multicentric observational analytic clinical study with intrapatient comparison, who received both continuous ECG monitoring as well as hSRA up to 7 days. Investigators were blinded to hSRA results unless pxAF was detected on SRA.
RESULTS—Of the 524 consecutive acute stroke patients (median age, 70.0 years; 60% male; acute ischemic stroke 93%, transient ischemic attack 7%), 462 were eligible and included in the study. Among 462 patients with hSRA available for 66 hours, AF was documented by hSRA in 79 patients (17.1%). From this group, 45 AF cases (9.7%) were confirmed after review by an independent and blinded cardiologist. continuous ECG monitoring detected 21 AF cases (4.3%; P<0.0001). hSRA detected R_AF patterns in 92 patients. 35 out of the 92 R_AF patients showed an episode of AF during the Stroke Unit stay. Predictive values of R_AF patterns within the first cycle of hSRA weresensitivity 71%, specificity 86%, positive predictive value 38%, and negative predictive value 96%.
CONCLUSIONS—Automated analysis using SRA technology strongly improves pxAF detection in acute ischemic stroke patients compared with continuous ECG monitoring. The predictive value of a R_AF pattern, as detected by hSRA during the first few hours after admission, deserves further investigation.
Determining the time of stroke onset in order to apply recanalization therapies within the accepted therapeutic window and the correct diagnosis of transient ischemic attack (TIA) are two common ...clinical problems in acute cerebral ischemia management. Therefore, biomarkers helping in this conundrum could be very helpful. We developed mouse models of distal middle cerebral artery occlusion mimicking TIA and ischemic stroke (IS), respectively. Plasma samples were analyzed by metabolomics at 6, 12, 24, and 48 h post onset in order to find TIA- and time-related stroke biomarkers. The results were validated in a second experimental cohort. Plasma metabolomic profiles identified time after stroke events with a very high accuracy. Specific metabolites pointing to a recent event (< 6 h) were identified. A multivariate (partial least square discriminant analyses PLS-DA) model was also able to separate samples from TIA, IS, and sham events with high accuracy and to obtain specific metabolites for each time point. The combination of mice models of focal ischemia with plasma metabolomics allows the discovery of candidate biomarkers for the diagnosis and estimation of onset time of stroke and TIA diagnosis.
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