Machine learning to predict myocardial injury and death after non-cardiac surgery

Myocardial injury due to ischaemia within 30 days of non-cardiac surgery is prognostically relevant. We aimed to determine the discrimination, calibration, accuracy, sensitivity and specificity of single-layer and multiple-layer neural networks for myocardial injury and death within 30 postoperative days. We analysed data from 24,589 participants in the Vascular Events in Non-cardiac Surgery Patients Cohort Evaluation study. Validation was performed on a randomly selected subset of the study population. Discrimination for myocardial injury by single-layer vs. multiple-layer models generated areas (95%CI) under the receiver operating characteristic curve of: 0.70 (0.69–0.72) vs. 0.71 (0.70–0.73) with variables available before surgical referral, p < 0.001; 0.73 (0.72–0.75) vs. 0.75 (0.74–0.76) with additional variables available on admission, but before surgery, p < 0.001; and 0.76 (0.75–0.77) vs. 0.77 (0.76–0.78) with the addition of subsequent variables, p < 0.001. Discrimination for death by single-layer vs. multiple-layer models generated areas (95%CI) under the receiver operating characteristic curve of: 0.71 (0.66–0.76) vs. 0.74 (0.71–0.77) with variables available before surgical referral, p = 0.04; 0.78 (0.73–0.82) vs. 0.83 (0.79–0.86) with additional variables available on admission but before surgery, p = 0.01; and 0.87 (0.83–0.89) vs. 0.87 (0.85–0.90) with the addition of subsequent variables, p = 0.52. The accuracy of the multiple-layer model for myocardial injury and death with all variables was 70% and 89%, respectively.     

A Very Long-term Longitudinal Study on the Evolution and Clinical Outcomes of Persistent Iatrogenic Atrial Septal Defect After Cryoballoon Ablation

Background

Persistent iatrogenic atrial septal defect (iASD) is a common but poorly characterized complication after cryoballoon (CB) pulmonary vein isolation (PVI) procedures. We therefore investigate its prevalence, evolution, risk factors, and clinical outcomes in a prospective longitudinal study.

Hospitalization and mortality outcomes in the first 5 years after a childhood cancer diagnosis: a population-based study

Cancer Causes & Control - Children with cancer are frequently hospitalized. However, hospitalization and death by disease category are not well defined?&lt;?5&nbsp;years...     

Novel method using Hjorth mobility analysis for diagnosing attention-deficit hyperactivity disorder in girls

Background

Attention-deficit hyperactivity disorder (ADHD) is a common childhood neuropsychiatric disorder. Diagnosis of ADHD is based on core symptoms or checklists; however, practitioner subjectivity inevitably results in instances of over- or under-diagnosis. Although an elevated theta/beta ratio (TBR) of the electroencephalography (EEG) band has been approved by the Food and Drug Administration as a factor that may be used in diagnosis of ADHD, several studies have reported no significant differences between the TBR of patients with ADHD and controls.

Innovative Thinking on Endpoint Selection in Clinical Trials

ABSTRACT

In clinical trials, selection of appropriate study endpoints is critical for an accurate and reliable evaluation of safety and effectiveness of a test treatment under investigation. In practice, however, there are usually multiple endpoints available for measurement of disease status and/or therapeutic effect of the test treatment under study. For example, in cancer clinical trials, overall survival, response rate, and/or time to disease progression are usually considered as primary clinical endpoints for evaluation of safety and effectiveness of the test treatment under investigation. Once the study endpoints have been selected, sample size required for achieving a desired power is then determined. It, however, should be noted that different study endpoints may result in different sample sizes. In practice, it is usually not clear which study endpoint can best inform the disease status and measure the treatment effect. Moreover, different study endpoints may not translate one another although they may be highly correlated one another. In this article, we intend to develop an innovative endpoint namely therapeutic index based on a utility function to combine and utilize information collected from all study endpoints. Statistical properties and performances of the proposed therapeutic index are evaluated theoretically. A numerical example concerning a cancer clinical trial is given to illustrate the use of the proposed therapeutic index.     

An assessment of weight change associated with the initiation of a protease or integrase strand transfer inhibitor in patients with human immunodeficiency virus

Abstract

Objective

Evidence suggests that integrase strand transfer inhibitors (INSTIs) are associated with greater weight gain than other antiretrovirals. This real-world study compares weight/body mass index (BMI) change between insured US patients with human immunodeficiency virus (HIV-1) initiating a protease inhibitor (PI) or INSTI.