Combination of High Ankle–Brachial Index and Hard Coronary Heart Disease Framingham Risk Score in Predicting the Risk of Ischemic Stroke in General Population

Our previous study showed that the patients with more metabolic risk factors had higher risk of high ankle–brachial index (ABI), but the relationship between high ABI and the risk of severe cardiovascular and cerebrovascular diseases is still under debate. This study aims to evaluate this association in the general population. 1486 subjects of South China were recruited in the study. 61 subjects were defined as high ABI group (ABI≥1.3) and 65 subjects were randomly selected as normal ABI group (0.9<ABI<1.3). Biochemical parameters, clinical characteristics and 10-year hard coronary heart disease (HCHD) Framingham Risk Score (FRS) were compared between two groups. The results showed that the 10-year HCHD FRS of high ABI group was significantly higher than normal ABI group (7.87±6.11 vs. 3.98±2.90%, P<0.001). There was a positive correlation between ABI value and HCHD FRS in overweight participants (R = 0.576, P<0.01). The prevalence of ischemic stroke was higher in high ABI group than normal ABI group (21.3% vs. 6.2%, P<0.05), and it was higher in participants with HCHD FRS≥6% than those with HCHD FRS<6% (19.1% vs. 6.9%, P<0.05). Moreover, the prevalence of ischemic stroke was higher in participants with high ABI and HCHD FRS≥6% than those with normal ABI and HCHD FRS<6% (26.7% vs. 4.1%, P<0.05). BMI, hypertension, hsCRP and smoking were proved to be the independent factors and effective predictors for high ABI (P<0.05). In conclusion, high ABI combined with high HCHD FRS should be a potential predictor of ischemic stroke in the general population of South China.     

Development of a Novel Heart Failure Risk Tool: The Barcelona Bio-Heart Failure Risk Calculator (BCN Bio-HF Calculator)

Background

A combination of clinical and routine laboratory data with biomarkers reflecting different pathophysiological pathways may help to refine risk stratification in heart failure (HF). A novel calculator (BCN Bio-HF calculator) incorporating N-terminal pro B-type natriuretic peptide (NT-proBNP, a marker of myocardial stretch), high-sensitivity cardiac troponin T (hs-cTnT, a marker of myocyte injury), and high-sensitivity soluble ST2 (ST2), (reflective of myocardial fibrosis and remodeling) was developed.

Methods

Model performance was evaluated using discrimination, calibration, and reclassification tools for 1-, 2-, and 3-year mortality. Ten-fold cross-validation with 1000 bootstrapping was used.

Results

The BCN Bio-HF calculator was derived from 864 consecutive outpatients (72% men) with mean age 68.2±12 years (73%/27% New York Heart Association (NYHA) class I-II/III-IV, LVEF 36%, ischemic etiology 52.2%) and followed for a median of 3.4 years (305 deaths). After an initial evaluation of 23 variables, eight independent models were developed. The variables included in these models were age, sex, NYHA functional class, left ventricular ejection fraction, serum sodium, estimated glomerular filtration rate, hemoglobin, loop diuretic dose, β-blocker, Angiotensin converting enzyme inhibitor/Angiotensin-2 receptor blocker and statin treatments, and hs-cTnT, ST2, and NT-proBNP levels. The calculator may run with the availability of none, one, two, or the three biomarkers. The calculated risk of death was significantly changed by additive biomarker data. The average C-statistic in cross-validation analysis was 0.79.

Conclusions

A new HF risk-calculator that incorporates available biomarkers reflecting different pathophysiological pathways better allowed individual prediction of death at 1, 2, and 3 years.     

Predicting death in home care users: derivation and validation of the Risk Evaluation for Support: Predictions for Elder-Life in the Community Tool (RESPECT)

BACKGROUND:Prognostication tools that report personalized mortality risk and survival could improve discussions about end-of-life and advance care planning. We sought to develop and validate a mortality risk model for older adults with diverse care needs in home care using self-reportable information — the Risk Evaluation for Support: Predictions for Elder-Life in the Community Tool (RESPECT).METHODS:Using a derivation cohort that comprised adults living in Ontario, Canada, aged 50 years and older with at least 1 Resident Assessment Instrument for Home Care (RAI-HC) record between Jan. 1, 2007, and Dec. 31, 2012, we developed a mortality risk model. The primary outcome was mortality 6 months after a RAI-HC assessment. We used proportional hazards regression with robust standard errors to account for clustering by the individual. We validated this algorithm for a second cohort of users of home care who were assessed between Jan. 1 and Dec. 31, 2013. We used Kaplan–Meier survival curves to estimate the observed risk of death at 6 months for assessment of calibration and median survival. We constructed 61 risk groups based on incremental increases in the estimated median survival of about 3 weeks among adults at high risk and 3 months among adults at lower risk.RESULTS:The derivation and validation cohorts included 435 009 and 139 388 adults, respectively. We identified a total of 122 823 deaths within 6 months of a RAI-HC assessment in the derivation cohort. The mean predicted 6-month mortality risk was 10.8% (95% confidence interval [CI] 10.7%–10.8%) and ranged from 1.54% (95% CI 1.53%–1.54%) in the lowest to 98.1% (95% CI 98.1%–98.2%) in the highest risk group. Estimated median survival spanned from 28 days (11 to 84 d at the 25th and 75th percentiles) in the highest risk group to over 8 years (1925 to 3420 d) in the lowest risk group. The algorithm had a c-statistic of 0.753 (95% CI 0.750–0.756) in our validation cohort.INTERPRETATION:The RESPECT mortality risk prediction tool that makes use of readily available information can improve the identification of palliative and end-of-life care needs in a diverse older adult population receiving home care.

Most people in high-income countries die of causes with progressive, predictable trajectories of decline.^1–4 Since 2000, the 3 leading causes of death in Canada — accounting for 55% of all deaths — have been cancer, heart disease and stroke.¹ Other leading causes of death, such as dementia and chronic lower respiratory diseases, also share signs and symptoms of senescence that are common across chronic diseases, including deterioration of physical and cognitive function, as well as an increased need for assistance.Despite the predictable nature of most deaths, many Canadian residents who are at the end of life do not receive adequate home-based supports.⁵ In Ontario — the largest province in Canada with more than 14 million residents and the setting of this study — only 40% of decedents receive formal home care, and less than 20% receive a physician home visit in their last year of life.^6,7 Even among those who had received palliative and end-of-life care, the start of service was often too close to death and failed to have a positive impact on the quality of life in those last months.⁸ The lack of available and accurate prognostic information is a key challenge. There are few existing tools that can be used to inform palliative care planning for the general population of older adults who live in the community and in people without cancer.⁹ Other barriers to accurate prognostic estimates include clinicians’ reluctance or lack of time and existing prognostication tools’ reliance on complex or specialized inputs, such as laboratory data and previous health care use. As a result, many older and frail adults do not receive timely palliative care and do not have an advance care plan.^6,10–13Our primary objective was to develop and validate a model for predicting mortality risk among the general population of community-dwelling adults with and without cancer that spans an actionable period for end-of-life planning (5 yr to imminent death). The variables included in our prognostication model — the Risk Evaluation for Support: Predictions for Elder-life in the Community Tool (RESPECT) — were prespecified to include exposures that could be self-reported by patients and their caregivers, including family members.     

Evaluating the Use of Antibody Variable Region (Fv) Charge as a Risk Assessment Tool for Predicting Typical Cynomolgus Monkey Pharmacokinetics

The pharmacokinetic (PK) behavior of monoclonal antibodies in cynomolgus monkeys (cynos) is generally translatable to that in humans. Unfortunately, about 39% of the antibodies evaluated for PKs in cynos have fast nonspecific (or non-target-mediated) clearance (in-house data). An empirical model relating variable region (Fv) charge and hydrophobicity to cyno nonspecific clearance was developed to gauge the risk an antibody would have for fast nonspecific clearance in the monkey. The purpose of this study was to evaluate the predictability of this empirical model on cyno nonspecific clearance with antibodies specifically engineered to have either high or low Fv charge. These amino acid changes were made in the Fv region of two test antibodies, humAb4D5-8 and anti-lymphotoxin α. The humAb4D5-8 has a typical nonspecific clearance in cynos, and by making it more positively charged, the antibody acquires fast nonspecific clearance, and making it less positively charged did not impact its clearance. Anti-lymphotoxin α has fast nonspecific clearance in cynos, and making it more positively charged caused it to clear even faster, whereas making it less positively charged caused it to clear slower and within the typical range. These trends in clearance were also observed in two other preclinical species, mice and rats. The effect of modifying Fv charge on subcutaneous bioavailability was also examined, and in general bioavailability was inversely related to the direction of the Fv charge change. Thus, modifying Fv charge appears to impact antibody PKs, and the changes tended to correlate with those predicted by the empirical model.     

Development of Risk Score for Predicting 3-Year Incidence of Type 2 Diabetes: Japan Epidemiology Collaboration on Occupational Health Study

Objective

Risk models and scores have been developed to predict incidence of type 2 diabetes in Western populations, but their performance may differ when applied to non-Western populations. We developed and validated a risk score for predicting 3-year incidence of type 2 diabetes in a Japanese population.

Methods

Participants were 37,416 men and women, aged 30 or older, who received periodic health checkup in 2008–2009 in eight companies. Diabetes was defined as fasting plasma glucose (FPG) ≥126 mg/dl, random plasma glucose ≥200 mg/dl, glycated hemoglobin (HbA1c) ≥6.5%, or receiving medical treatment for diabetes. Risk scores on non-invasive and invasive models including FPG and HbA1c were developed using logistic regression in a derivation cohort and validated in the remaining cohort.

Results

The area under the curve (AUC) for the non-invasive model including age, sex, body mass index, waist circumference, hypertension, and smoking status was 0.717 (95% CI, 0.703–0.731). In the invasive model in which both FPG and HbA1c were added to the non-invasive model, AUC was increased to 0.893 (95% CI, 0.883–0.902). When the risk scores were applied to the validation cohort, AUCs (95% CI) for the non-invasive and invasive model were 0.734 (0.715–0.753) and 0.882 (0.868–0.895), respectively. Participants with a non-invasive score of ≥15 and invasive score of ≥19 were projected to have >20% and >50% risk, respectively, of developing type 2 diabetes within 3 years.

Conclusions

The simple risk score of the non-invasive model might be useful for predicting incident type 2 diabetes, and its predictive performance may be markedly improved by incorporating FPG and HbA1c.     

The Development of a Plant Risk Evaluation (PRE) Tool for Assessing the Invasive Potential of Ornamental Plants

Weed Risk Assessment (WRA) methods for evaluating invasiveness in plants have evolved rapidly in the last two decades. Many WRA tools exist, but none were specifically designed to screen ornamental plants prior to being released into the environment. To be accepted as a tool to evaluate ornamental plants for the nursery industry, it is critical that a WRA tool accurately predicts non-invasiveness without falsely categorizing them as invasive. We developed a new Plant Risk Evaluation (PRE) tool for ornamental plants. The 19 questions in the final PRE tool were narrowed down from 56 original questions from existing WRA tools. We evaluated the 56 WRA questions by screening 21 known invasive and 14 known non-invasive ornamental plants. After statistically comparing the predictability of each question and the frequency the question could be answered for both invasive and non-invasive species, we eliminated questions that provided no predictive power, were irrelevant in our current model, or could not be answered reliably at a high enough percentage. We also combined many similar questions. The final 19 remaining PRE questions were further tested for accuracy using 56 additional known invasive plants and 36 known non-invasive ornamental species. The resulting evaluation demonstrated that when “needs further evaluation” classifications were not included, the accuracy of the model was 100% for both predicting invasiveness and non-invasiveness. When “needs further evaluation” classifications were included as either false positive or false negative, the model was still 93% accurate in predicting invasiveness and 97% accurate in predicting non-invasiveness, with an overall accuracy of 95%. We conclude that the PRE tool should not only provide growers with a method to accurately screen their current stock and potential new introductions, but also increase the probability of the tool being accepted for use by the industry as the basis for a nursery certification program.     

Development of a Summarized Health Index (SHI) for Use in Predicting Survival in Sea Turtles

Veterinary care plays an influential role in sea turtle rehabilitation, especially in endangered species. Physiological characteristics, hematological and plasma biochemistry profiles, are useful references for clinical management in animals, especially when animals are during the convalescence period. In this study, these factors associated with sea turtle surviving were analyzed. The blood samples were collected when sea turtles remained alive, and then animals were followed up for surviving status. The results indicated that significantly negative correlation was found between buoyancy disorders (BD) and sea turtle surviving (p < 0.05). Furthermore, non-surviving sea turtles had significantly higher levels of aspartate aminotranspherase (AST), creatinine kinase (CK), creatinine and uric acid (UA) than surviving sea turtles (all p < 0.05). After further analysis by multiple logistic regression model, only factors of BD, creatinine and UA were included in the equation for calculating summarized health index (SHI) for each individual. Through evaluation by receiver operating characteristic (ROC) curve, the result indicated that the area under curve was 0.920 ± 0.037, and a cut-off SHI value of 2.5244 showed 80.0% sensitivity and 86.7% specificity in predicting survival. Therefore, the developed SHI could be a useful index to evaluate health status of sea turtles and to improve veterinary care at rehabilitation facilities.     

Relationship of Self-Rated Health to Stroke Incidence and Mortality in Older Individuals with and without a History of Stroke: A Longitudinal Study of the MRC Cognitive Function and Ageing (CFAS) Population

Introduction

Poor self-rated health (SRH) has been associated with increased risk of death and poor health outcomes even after adjusting for confounders. However its’ relationship with disease-specific mortality and morbidity has been less studied. SRH may also be particularly predictive of health outcomes in those with pre-existing conditions. We studied whether SRH predicts new stroke in older people who have never had a stroke, or a recurrence in those with a prior history of stroke.

Methods

MRC CFAS I is a multicentre cohort study of a population representative sample of people in their 65th year and older. A comprehensive interview at baseline included questions about presence of stroke, self-rated health and functional disability. Follow-up at 2 years included self-report of stroke and stroke death obtained from death certificates. Multiple logistical regression determined odds of stroke at 2 years adjusting for confounders including disability and health behaviours. Survival analysis was performed until June 2014 with follow-up for up to 13 years.

Results

11,957 participants were included, of whom 11,181 (93.8%) had no history of stroke and 776 (6.2%) one or more previous strokes. Fewer with no history of stroke reported poor SRH than those with stroke (5 versus 21%). In those with no history of stroke, poor self-rated health predicted stroke incidence (OR 1.5 (1.1–1.9)), but not stroke mortality (OR 1.2 (0.8–1.9)) at 2 years nor for up to 13 years (OR 1.2(0.9–1.7)). In those with a history of stroke, self-rated health did not predict stroke incidence (OR 0.9(0.6–1.4)), stroke mortality (OR 1.1(0.5–2.5)), or survival (OR 1.1(0.6–2.1)).

Conclusions

Poor self-rated health predicts risk of stroke at 2 years but not stroke mortality among the older population without a previous history of stroke. SRH may be helpful in predicting who may be at risk of developing a stroke in the near future.     

Dietary Patterns and Depressive Symptoms over Time: Examining the Relationships with Socioeconomic Position,Health Behaviours and Cardiovascular Risk

Introduction

Recent research suggests that diet quality influences depression risk; however, a lack of experimental evidence leaves open the possibility that residual confounding explains the observed relationships. The aim of this study was to document the cross-sectional and longitudinal associations between dietary patterns and symptoms of depression and to undertake a detailed examination of potential explanatory factors, particularly socioeconomic circumstances, in the diet-depression relationship.

Methods

Data were drawn from the Personality and Total Health (PATH) Through Life Study, a longitudinal community study following three age cohorts (20+; 40+; 60+yrs) from south-eastern Australia over three assessment periods (n = 3663). Regression analyses evaluated the cross-sectional and longitudinal relationships between dietary patterns, depressive symptoms, age, detailed measures of socioeconomic circumstances, other health behaviours, and cardiovascular risk factors.

Results

The lowest tertile of prudent (healthy) dietary pattern and the highest tertile of western (unhealthy) dietary pattern were associated with an increased likelihood of depressive symptoms. However, these contemporaneous associations were explained by adjustment for detailed measures of socioeconomic circumstances and physical activity. In prospective analyses, lower scores on the healthy dietary pattern and higher scores on the unhealthy dietary pattern independently predicted increased depressive symptoms across time, before and after adjustment for potential confounders and baseline depressive symptoms, but only for those in the oldest cohort. Dietary patterns did not explain the relationship between socioeconomic position and depressive symptoms.

Conclusion

The results of this study confirm that the relationship between habitual dietary intake and depressive symptoms is somewhat explained by socioeconomic circumstances and other health behaviours, but suggest that long term exposure to unhealthy dietary habits independently predisposes to depression over the lifecourse.     

Endothelial NO Synthase Gene Polymorphisms and Risk of Ischemic Stroke in Asian Population: A Meta-Analysis

Background

The association between polymorphism 4b/a, T-786C and G894T in endothelial NO synthase gene (eNOS) and ischemic stroke (IS) remains controversial in Asian. A meta-analysis was performed to better clarify the association between eNOS gene and IS risk.

Methods

Based on the search of PubMed, Web of Science (ISI), CNKI (National Knowledge Infrastructure), Wan Fang Med Online and CBM (Chinese Biology Medical Literature Database) databases, all eligible case-control or cohort studies were identified. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) from fixed and random effect models were calculated. Heterogeneity among studies was evaluated using the I². Meta-regression was used to explore the potential sources of between-study heterogeneity. Begg''s test was used to estimate publication bias.

Results

Our study included 27 articles, contained 28 independent case–control studies, involved a total of 3,742 cases and 3,691 controls about 4b/a, 1,800 cases and 1,751 controls about T-786C and 2,747 cases and 2,872 controls about G894T. A significant association of 4a allele with increased risk of IS was found in dominant (FEM: OR = 1.498, 95% CI = 1.329–1.689), recessive (FEM: OR = 2.132, 95% CI = 1.383–3.286) and codominant (REM: OR = 1.456, 95% CI = 1.235–1.716) models. For T-786C and G894T, there were significant associations with dominant and codominant genetic models, but not with recessive genetic model.

Conclusions

The meta-analysis indicated that eNOS gene 4b/a, T-786C, G894T polymorphism might be associated with IS.     

The Predictive Value of the Boston Acute Stroke Imaging Scale (BASIS) in Acute Ischemic Stroke Patients among Chinese Population

Objective

Evaluate the predictive value of Boston Acute Stroke Imaging Scale (BASIS) in acute ischemic stroke in Chinese population.

Methods

This was a retrospective study. 566 patients of acute ischemic stroke were classified as having a major stroke or minor stroke based on BASIS. We compared short-term outcome (death, occurrence of complications, admission to intensive care unit [ICU] or neurological intensive care unit [NICU]), long-term outcome (death, recurrence of stroke, myocardial infarction, modified Rankin scale) and economic index including in-hospital cost and length of hospitalization. Continuous variables were compared by using the Student t test or Kruskal-Wallis test. Categorical variables were tested with the Chisquare test. Cox regression analysis was applied to identify whether BASIS was the independent predictive variable of death.

Results

During hospitalization, 9 patients (4.6%) died in major stroke group while no patients died in minor stroke group (p<0.001), 12 patients in the major stroke group and 5 patients in minor stroke group were admitted to ICU/NICU (p = 0.001). There were more complications (cerebral hernia, pneumonia, urinary tract infection) in major stroke group than minor stroke group (p<0.05). Meanwhile, the average cost of hospitalization in major stroke group was 3,100 US$ and 1,740 US$ in minor stroke group (p<0.001); the average length of stay in major and minor stroke group was 21.3 days and 17.3 days respectively (p<0.001). Results of the follow-up showed that 52 patients (26.7%) died in major stroke group while 56 patients (15.1%) died in minor stroke group (P<0.001). 62.2% of the patients in major stroke group and 80.4% of the patients in minor stroke group were able to live independently (P = 0.002). The survival analysis showed that patients with major stroke had 80% higher of risk of death than patients with minor stroke even after adjusting traditional atherosclerotic factors and NIHSS at baseline (HR = 1.8, 95% CI: 1.1–3.1).

Conclusion

BASIS can predict in-hospital mortality, occurrence of complication, length of stay and hospitalization cost of the acute ischemic stroke patients and can also estimate the long term outcome (death and the dependency). BASIS could and should be used as a dichotomous stroke classification system in the daily practice.     

Association of the Genetic Polymorphisms in Pre-MicroRNAs with Risk of Ischemic Stroke in a Chinese Population

microRNA (miRNA) plays a role in the pathogenesis of ischemic stroke, and single nucleotide polymorphisms in miRNA genes may contribute to disease susceptibility. However, the effect of miR-146a, miR-196a2, and miR-499 polymorphisms on ischemic stroke susceptibility has been rarely reported. Using the TaqMan assay, we evaluated the association of hsa-miR-146a/rs2910164, hsa-miR-196a2/rs11614913, and hsa-miR-499/rs3746444 polymorphisms with the risk of ischemic stroke in a Chinese population with 531 ischemic stroke patients and 531 control subjects. Rs2910164 C/G genotypes were significantly associated with increased risk of ischemic stroke in different genetic model (homozygote comparison: OR = 2.00, 95% CI, 1.29–3.12, P = 0.002; additive model: OR = 1.35, 95% CI, 1.10–1.65, P = 0.004;dominant model: OR = 1.33, 95% CI, 1.00–1.75, P = 0.049; recessive model: OR = 1.82, 95% CI, 1.20–2.74, P = 0.004). Subjects with allele G of hsa-miR-146a/ rs2910164 also showed increased risk of ischemic stroke (OR = 1.33, 95% CI, 1.09–1.62, P = 0.005). Stratification analysis showed that the association between rs2910164 and the risk of ischemic stroke was more pronounced in subjects over 60 years old, females, non-drinkers, subjects without hypertension or diabetes mellitus. There were significant combined effects between miR-146a/rs2910164 and fasting glucose/low-density lipoprotein cholesterol levels on ischemic stroke susceptibility. However, we failed to find any association between the alleles/genotypes of rs11614913 T/C and ischemic stroke, respectively (P> 0.05). In summary, this study provides evidence that miR-146a/rs2910164 might be associated with a significantly increased risk of ischemic stroke in a Chinese population, and the combined effects between miRNA polymorphism and fasting glucose /blood lipid levels may contribute to stroke pathogenesis.     

Extinction Risk: Predicting and Redressing the Threat

Predicting and redressing the threat of species extinction is not a success story. The science of estimating extinction rates and risk prediction is approached in a manner that is difficult to apply in the field, and yet current integrated ecosystem management programmes in many parts of the world, which are trying to place the conservation of species into sustainable community projects, need predictive tools for planning land use programmes. Such programmes involve US$100s of millions of multilateral and bilateral aid; many predicated on a site's biodiversity importance, the risks of extinction, sustainable extraction, production forms of land use, community livelihoods, water, and many others factors, but increasingly on ensuring that after the pump-priming funds are finished the programmes are both environmentally and economically sustainable (Swingland 2002, 2003, 2004; Swingland et al. 2003). [Swingland I.R. 2002. In: Swingland I.R., Bettelheim E.C., Grace J., Prance G.T. and Saunders L.S. (eds), Carbon Biodiversity, Conservation and Income: An Analysis of a Free Market Approach to Land-use Change and Forestry in Developing and Developed Countries. Philosophical Transactions Royal Society London A: Mathematical, Physical and Engineering Sciences, London; Swingland I.R. (ed.) 2003. Capturing Biodiversity and Conserving Biodiversity: The Market Approach. Earthscan, London; Swingland I.R. (ed.) 2004. CO² e biodiversità. Un approccio integrato a favore del clima e del patrimonio naturale. Edizioni Ambiente, Milano, Italy, 296 pp.; Swingland I.R., Bettelheim E.C. and Niles J.O. 2003. In: Swingland I.R. (ed.), Capturing Biodiversity and Conserving Biodiversity: The Market Approach. Earthscan, London] This involves predictions of ‘what if?’ what if laws are changed to prevent over utilisation and prevent ‘The Tragedy of the Commons’ where land ownership is vested in the state and people degrade the environment, and instead institute private land ownership. In places like China and much of the Far East, biodiversity is over-exploited as nearly all their species are used for food, medicine and construction purposes, and private land ownership in rural areas is rudimentary or absent. Since most species extinction is anthropocentric, research on species extinction needs to be more accessible and focussed on global problems.     

Differential Risk Factors for Lacunar Stroke Depending on the MRI (White and Red) Subtypes of Microangiopathy

Background

Leukoaraiosis and cerebral microbleeds (CMB), which represent cerebral microangiopathy, commonly coexist in patients with acute lacunar stroke. Since they may have different impacts on stroke prognosis and treatment, it is important to know the factors associated with leukoaraiosis-predominant vs. CMB-predominant microangiopathies.

Methods

We prospectively recruited 226 patients with acute lacunar infarction and divided them into four groups according to the Fazekas’ score and the presence of CMB: mild, red (predominant CMB), white (predominant leukoaraiosis) and severe microangiopathy groups. For comparison, we also evaluated 50 patients with intracerebral hemorrhage (ICH). We evaluated the clinical and laboratory findings of microangiopathy subtypes in patients with acute lacunar stroke and then compared them with those of primary ICH.

Results

The risk factor profile was different among the groups. Patients with acute lacunar infarct but mild microangiopathy were younger, predominantly male, less hypertensive, and more frequently had smoking and heavy alcohol habits than other groups. The risk factor profile of red microangiopathy was similar to that of ICH but differed from that of white microangiopathy. The subjects in the white microangiopathy group were older and more frequently had diabetes than those in the red microangiopathy or ICH group. After adjustments for other factors, age [odds ratio (OR) 1.13; 95% confidence interval (CI) 1.08–1.18; p<0.001] and diabetes (OR 2.28; 95% CI 1.02–5.13; p = 0.045) were independently associated with white microangiopathy, and age (OR 1.05; 95% CI 1.01–1.08; p = 0.010) was independent predictor for red microangiopathy compared to mild microangiopathy.

Conclusion

Patients with acute lacunar infarction have a different risk factor profile depending on microangiopathic findings. Our results indicate that diabetes may be an one of determinants of white (leukoaraiosis-predominant) microangiopathy, whereas smoking and alcohol habits in relatively young people may be a determinants of mild microangiopahic changes in patients with lacunar infarction.     

Development and Validation of a Risk Model for Predicting Adverse Drug Reactions in Older People during Hospital Stay: Brighton Adverse Drug Reactions Risk (BADRI) Model

Background

Older patients are at an increased risk of developing adverse drug reactions (ADR). Of particular concern are the oldest old, which constitute an increasingly growing population. Having a validated clinical tool to identify those older patients at risk of developing an ADR during hospital stay would enable healthcare staff to put measures in place to reduce the risk of such an event developing. The current study aimed to (1) develop and (2) validate an ADR risk prediction model.

Methods

We used a combination of univariate analysis and multivariate binary logistic regression to identify clinical risk factors for developing an ADR in a population of older people from a UK teaching hospital. The final ADR risk model was then validated in a European population (European dataset).

Results

Six-hundred-ninety patients (median age 85 years) were enrolled in the development stage of the study. Ninety-five reports of ADR were confirmed by independent review in these patients. Five clinical variables were identified through multivariate analysis and included in our final model; each variable was attributed a score of 1. Internal validation produced an AUROC of 0.74, a sensitivity of 80%, and specificity of 55%. During the external validation stage the AUROC was 0.73, with sensitivity and specificity values of 84% and 43% respectively.

Conclusions

We have developed and successfully validated a simple model to use ADR risk score in a population of patients with a median age of 85, i.e. the oldest old. The model is based on 5 clinical variables (≥8 drugs, hyperlipidaemia, raised white cell count, use of anti-diabetic agents, length of stay ≥12 days), some of which have not been previously reported.