Early exclusion of major adverse cardiac events in emergency department chest pain patients: A prospective observational study

Background The current evaluation of patients with chest pain presenting to an emergency department (ED) with suspected acute coronary syndrome (ACS) is a lengthy process involving serial measurements of troponin. Objective We aimed to validate the diagnostic accuracy of a Thrombolysis in Myocardial Infarction (TIMI) score with single high-sensitive cardiac troponin T (hs-cTnT) for early rule out of 30-day major adverse cardiac events (MACE), and to compare the TIMI score with combinations of heart-type fatty acid binding protein (H-FABP) and a modified HEART (history, electrocardiogram, age, risk factors, troponin) score. Methods We recruited 602 consecutive adult patients with chest pain and suspected ACS in the ED. Each patient had TIMI and HEART scores, and a point-of-care H-FABP test. Results MACE occurred in 42 (7.0%) patients within 30 days. A low risk for 30-day MACE was identified by a modified TIMI score of 0 in 65 (11%) patients, and by a HEART score ≤ 2 in 96 (16%) patients. No MACE occurred in these groups, giving both scores a sensitivity of 100% (95% confidence interval [CI] 91.6–100%), and specificity of 11.6% (95% CI 9.2–14.5%) and 17.1% (95% CI 14.2–20.5%), respectively. Use of combined TIMI and HEART scores improved the specificity further to 22.0% (95% CI 18.7–25.6%) without lowering sensitivity. Early H-FABP measurement > 7 μg/L had a sensitivity of 41.5% (95% CI 27.8–56.6%) and a specificity of 91.1% (95% CI 88.4–93.2%) for predicting 30-day MACE. Conclusions A modified TIMI score of 0 or a HEART score of ≤ 2, incorporating a single hs-cTnT level, will identify patients with low risk of 30-day MACE for early discharge within 2 h of ED arrival

Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

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Circulating nucleic acids and critical illness

This article reviews some of the early work that has been performed to investigate the potential roles of circulating nucleic acids as prediction markers in acute illness and injury. Circulating DNA and RNA concentrations are elevated early in patients with trauma, stroke and ACS, and are generally highest in patients with a high risk of death. Circulating nucleic acids may be useful markers for the evaluation and risk-stratification of such patients

EMS systems in Hong Kong

Emergency medical services (EMS) in Hong Kong, now a Special Administrative Region of the People's Republic of China, have a distinguished history spanning more than 50 years. This paper outlines the history and the development of the Hong Kong EMS, with a particular focus on the ambulance service, the design of the system and the training of its staff