A user-friendly risk-score for predicting in-hospital cardiac arrest among patients admitted with suspected non ST-elevation acute coronary syndrome – the SAFER-score

Aim: To develop a simple risk-score model for predicting in-hospital cardiac arrest (CA) among patients hospitalized with suspected non-ST elevation acute coronary syndrome (NSTE-ACS). Methods: Using the Swedish Web-system for Enhancement and Development of Evidence-based care in Heart disease Evaluated According to Recommended Therapies (SWEDEHEART), we identified patients (n = 242 303) admitted with suspected NSTE-ACS between 2008 and 2014. Logistic regression was used to assess the association between 26 candidate variables and in-hospital CA. A risk-score model was developed and validated using a temporal cohort (n = 126 073) comprising patients from SWEDEHEART between 2005 and 2007 and an external cohort (n = 276 109) comprising patients from the Myocardial Ischaemia National Audit Project (MINAP) between 2008 and 2013. Results: The incidence of in-hospital CA for NSTE-ACS and non-ACS was lower in the SWEDEHEART-derivation cohort than in MINAP (1.3% and 0.5% vs. 2.3% and 2.3%). A seven point, five variable risk score (age ≥60 years (1 point), ST-T abnormalities (2 points), Killip Class >1 (1 point), heart rate <50 or ≥100 bpm (1 point), and systolic blood pressure <100 mmHg (2 points) was developed. Model discrimination was good in the derivation cohort (c-statistic 0.72) and temporal validation cohort (c-statistic 0.74), and calibration was reasonable with a tendency towards overestimation of risk with a higher sum of score points. External validation showed moderate discrimination (c-statistic 0.65) and calibration showed a general underestimation of predicted risk. Conclusions: A simple points score containing five variables readily available on admission predicts in-hospital CA for patients with suspected NSTE-ACS

Validation of risk scores for ischaemic stroke in atrial fibrillation across the spectrumof kidney function

Aims The increasing prevalence of ischaemic stroke (IS) can partly be explained by the likewise growing number of patients with chronic kidney disease (CKD). Risk scores have been developed to identify high-risk patients, allowing for personalized anticoagulation therapy. However, predictive performance in CKD is unclear. The aim of this study is to validate six commonly used risk scores for IS in atrial fibrillation (AF) patients across the spectrum of kidney function.Methods and results Overall, 36 004 subjects with newly diagnosed AF from SCREAM (Stockholm CREAtinine Measurements), a healthcare utilization cohort of Stockholm residents, were included. Predictive performance of the AFI, CHADS(2), Modified CHADS(2), CHA(2)DS(2)-VASc, ATRIA, and GARFIELD-AF risk scores was evaluated across three strata of kidney function: normal kidney function [estimated glomerular filtration rate (eGFR) >60 mL/min/1.73 m(2)], mild CKD (eGFR 30-60 mL/min/1.73 m(2)), and advanced CKD (eGFR <30 mL/min/1.73 m(2)). Predictive performance was assessed by discrimination and calibration. During 1.9 years, 3069 (8.5%) patients suffered an IS. Discrimination was dependent on eGFR: the median c-statistic in normal eGFR was 0.75 (range 0.68-0.78), but decreased to 0.68 (0.58-0.73) and 0.68 (0.55-0.74) for mild and advanced CKD, respectively. Calibration was reasonable and largely independent of eGFR. The Modified CHADS(2) score showed good performance across kidney function strata, both for discrimination [c-statistic: 0.78 (95% confidence interval 0.77-0.79), 0.73 (0.71-0.74) and 0.74 (0.69-0.79), respectively] and calibration.Conclusion In the most clinically relevant stages of CKD, predictive performance of the majority of risk scores was poor, increasing the risk of misclassification and thus of over- or undertreatment. The Modified CHADS2 score performed good and consistently across all kidney function strata, and should therefore be preferred for risk estimation in AF patients.Clinical epidemiolog

Metformin use and cardiovascular outcomes after acute myocardial infarction in patients with type 2 diabetes: a cohort study

Background: The use of metformin after acute myocardial infarction (AMI) has been associated with reduced mortality in people with type 2 diabetes mellitus (T2DM). However, it is not known if it is acutely cardioprotective in patients taking metformin at the time of AMI. We compared patient outcomes according to metformin status at the time of admission for fatal and non-fatal AMI in a large cohort of patients in England. Methods: This study used linked data from primary care, hospital admissions and death registry from 4.7 million inhabitants in England, as part of the CALIBER resource. The primary endpoint was a composite of acute myocardial infarction requiring hospitalisation, stroke and cardiovascular death. The secondary endpoints were heart failure (HF) hospitalisation and all-cause mortality. Results: 4,030 patients with T2DM and incident AMI recorded between January 1998 and October 2010 were included. At AMI admission, 63.9% of patients were receiving metformin and 36.1% another oral hypoglycaemic drug. Median follow-up was 343 (IQR: 1–1436) days. Adjusted analyses showed an increased hazard of the composite endpoint in metformin users compared to non-users (HR 1.09 [1.01–1.19]), but not of the secondary endpoints. The higher risk of the composite endpoint in metformin users was only observed in people taking metformin at AMI admission, whereas metformin use post-AMI was associated with a reduction in risk of all-cause mortality (0.76 [0.62–0.93], P = 0.009). Conclusions: Our study suggests that metformin use at the time of first AMI is associated with increased risk of cardiovascular disease and death in patients with T2DM, while its use post-AMI might be beneficial. Further investigation in well-designed randomised controlled trials is indicated, especially in view of emerging evidence of cardioprotection from sodium-glucose co-transporter-2 (SGLT2) inhibitors

The 10th Biennial Hatter Cardiovascular Institute workshop: cellular protection—evaluating new directions in the setting of myocardial infarction, ischaemic stroke, and cardio-oncology

Due to its poor capacity for regeneration, the heart is particularly sensitive to the loss of contractile cardiomyocytes. The onslaught of damage caused by ischaemia and reperfusion, occurring during an acute myocardial infarction and the subsequent reperfusion therapy, can wipe out upwards of a billion cardiomyocytes. A similar program of cell death can cause the irreversible loss of neurons in ischaemic stroke. Similar pathways of lethal cell injury can contribute to other pathologies such as left ventricular dysfunction and heart failure caused by cancer therapy. Consequently, strategies designed to protect the heart from lethal cell injury have the potential to be applicable across all three pathologies. The investigators meeting at the 10th Hatter Cardiovascular Institute workshop examined the parallels between ST-segment elevation myocardial infarction (STEMI), ischaemic stroke, and other pathologies that cause the loss of cardiomyocytes including cancer therapeutic cardiotoxicity. They examined the prospects for protection by remote ischaemic conditioning (RIC) in each scenario, and evaluated impasses and novel opportunities for cellular protection, with the future landscape for RIC in the clinical setting to be determined by the outcome of the large ERIC-PPCI/CONDI2 study. It was agreed that the way forward must include measures to improve experimental methodologies, such that they better reflect the clinical scenario and to judiciously select combinations of therapies targeting specific pathways of cellular death and injury

Impact of an Early Invasive Strategy versus Conservative Strategy for Unstable Angina and Non-ST Elevation Acute Coronary Syndrome in Patients with Chronic Kidney Disease: A Systematic Review.

BACKGROUND: Clinical practice guidelines support an early invasive approach after NSTE-ACS in patients with chronic kidney disease (CKD). There is no direct randomised controlled trial evidence in the CKD population, and whether the benefit of an early invasive approach is maintained across the spectrum of severity of CKD remains controversial. METHODS: We conducted a systematic review to evaluate the association between an early invasive approach and all-cause mortality in patients with CKD. We searched MEDLINE and EMBASE (1990-May 2015) and article reference lists. Data describing study design, participants, invasive management strategies, renal function, all-cause mortality and risk of bias were extracted. RESULTS: 3,861 potentially relevant studies were identified. Ten studies, representing data on 147,908 individuals with NSTE-ACS met the inclusion criteria. Qualitative heterogeneity in the definitions of early invasive approach, comparison groups and renal dysfunction existed. Meta-analysis of the RCT derived and observational data were generally supportive of an early invasive approach in CKD (RR0.76 (95% CI 0.49-1.17) and RR0.50 (95%CI 0.42-0.59) respectively). Meta-analysis of the observational studies demonstrated a large degree of heterogeneity (I2 79%) driven in part by study size and heterogeneity across various kidney function levels. CONCLUSIONS: The observational data support that an early invasive approach after NSTE-ACS confers a survival benefit in those with early-moderate CKD. Local opportunities for quality improvement should be sought. Those with severe CKD and the dialysis population are high risk and under-studied. Novel and inclusive approaches for CKD and dialysis patients in cardiovascular clinical trials are needed

Semi-supervised prediction of protein subcellular localization using abstraction augmented Markov models

<p>Abstract</p> <p>Background</p> <p>Determination of protein subcellular localization plays an important role in understanding protein function. Knowledge of the subcellular localization is also essential for genome annotation and drug discovery. Supervised machine learning methods for predicting the localization of a protein in a cell rely on the availability of large amounts of labeled data. However, because of the high cost and effort involved in labeling the data, the amount of labeled data is quite small compared to the amount of unlabeled data. Hence, there is a growing interest in developing <it>semi-supervised methods</it> for predicting protein subcellular localization from large amounts of unlabeled data together with small amounts of labeled data.</p> <p>Results</p> <p>In this paper, we present an Abstraction Augmented Markov Model (AAMM) based approach to semi-supervised protein subcellular localization prediction problem. We investigate the effectiveness of AAMMs in exploiting <it>unlabeled</it> data. We compare semi-supervised AAMMs with: (i) Markov models (MMs) (which do not take advantage of unlabeled data); (ii) an expectation maximization (EM); and (iii) a co-training based approaches to semi-supervised training of MMs (that make use of unlabeled data).</p> <p>Conclusions</p> <p>The results of our experiments on three protein subcellular localization data sets show that semi-supervised AAMMs: (i) can effectively exploit unlabeled data; (ii) are more accurate than both the MMs and the EM based semi-supervised MMs; and (iii) are comparable in performance, and in some cases outperform, the co-training based semi-supervised MMs.</p

Heart failure and the risk of stroke: the Rotterdam Study

Patients with heart failure used to have an increased risk of stroke, but this may have changed with current treatment regimens. We assessed the association between heart failure and the risk of stroke in a population-based cohort that was followed since 1990. The study uses the cohort of the Rotterdam Study and is based on 7,546 participants who at baseline (1990–1993) were aged 55 years or over and free from stroke. The associations between heart failure and risk of stroke were assessed using time-dependent Cox proportional hazards models, adjusted for cardiovascular risk factors (smoking, diabetes mellitus, BMI, ankle brachial index, blood pressure, atrial fibrillation, myocardial infarction and relevant medication). At baseline, 233 participants had heart failure. During an average follow-up time of 9.7 years, 1,014 persons developed heart failure, and 827 strokes (470 ischemic, 75 hemorrhagic, 282 unclassified) occurred. The risk of ischemic stroke was more than five-fold increased in the first month after diagnosis of heart failure (age and sex adjusted HR 5.79, 95% CI 2.15–15.62), but attenuated over time (age and sex adjusted HR 3.50 [95% CI 1.96–6.25] after 1–6 months and 0.83 [95% CI 0.53–1.29] after 0.5–6 years). Additional adjustment for cardiovascular risk factors only marginally attenuated these risks. In conclusion, the risk of ischemic stroke is strongly increased shortly after the diagnosis of heart failure but returns to normal within 6 months after onset of heart failure

Renal function at the time of a myocardial infarction maintains prognostic value for more than 10 years

<p>Abstract</p> <p>Background</p> <p>Renal function is an important predictor of mortality in patients with myocardial infarction (MI), but changes in the impact over time have not been well described.</p> <p>We examined the importance of renal function by estimated GFR (eGFR) and se-creatinine as an independent long-term prognostic factor.</p> <p>Methods</p> <p>Prospective follow-up of 6653 consecutive MI patients screened for entry in the Trandolapril Cardiac Evaluation (TRACE) study. The patients were analysed by Kaplan-Meier survival analysis, landmark analysis and Cox proportional hazard models. Outcome measure was all-cause mortality.</p> <p>Results</p> <p>An eGFR below 60 ml per minute per 1.73 m², consistent with chronic renal disease, was present in 42% of the patients. We divided the patients into 4 groups according to eGFR. Overall, Cox proportional-hazards models showed that eGFR was a significant prognostic factor in the two groups with the lowest eGFR, hazard ratio 1,72 (confidence interval (CI) 1,56-1,91) in the group with the lowest eGFR. Using the eGFR group with normal renal function as reference, we observed an incremental rise in hazard ratio. We divided the follow-up period in 2-year intervals. Landmark analysis showed that eGFR at the time of screening continued to show prognostic effect until 16 years of follow-up. By multivariable Cox regression analysis, the prognostic effect of eGFR persisted for 12 years and of se-creatinine for 10 years. When comparing the lowest group of eGFR with the group with normal eGFR, prognostic significance was present in the entire period of follow-up with a hazard ratio between 1,97 (CI 1,65-2,35) and 1,35 (CI 0,99-1,84) in the 2-year periods.</p> <p>Conclusions</p> <p>One estimate of renal function is a strong and independent long-term prognostic factor for 10-12 years following a MI.</p

Heart failure in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies conference

The incidence and prevalence of heart failure (HF) and chronic kidney disease (CKD) are increasing, and as such a better understanding of the interface between both conditions is imperative for developing optimal strategies for their detection, prevention, diagnosis, and management. To this end, Kidney Disease: Improving Global Outcomes (KDIGO) convened an international, multidisciplinary Controversies Conference titled Heart Failure in CKD. Breakout group discussions included (i) HF with preserved ejection fraction (HFpEF) and nondialysis CKD, (ii) HF with reduced ejection fraction (HFrEF) and nondialysis CKD, (iii) HFpEF and dialysis-dependent CKD, (iv) HFrEF and dialysis-dependent CKD, and (v) HF in kidney transplant patients. The questions that formed the basis of discussions are available on the KDIGO website http://kdigo.org/conferences/heart-failure-in-ckd/, and the deliberations from the conference are summarized here