Towards a Change in the Diagnostic Algorithm of Autism Spectrum Disorders: Evidence Supporting Whole Exome Sequencing as a First-Tier Test.

Autism spectrum disorder (ASD) is a prevalent and extremely heterogeneous neurodevelopmental disorder (NDD) with a strong genetic component. In recent years, the clinical relevance of de novo mutations to the aetiology of ASD has been demonstrated. Current guidelines recommend chromosomal microarray (CMA) and a testing as first-tier tests, but there is increasing evidence that support the use of NGS for the diagnosis of NDDs.

Machine learning approaches to constructing predictive models of vitamin D deficiency in a hypertensive population: a comparative study.

Given the association between vitamin D deficiency and risk for cardiovascular disease, we used machine learning approaches to establish a model to predict the probability of deficiency. Determination of serum levels of 25-hydroxy vitamin D (25(OH)D) provided the best assessment of vitamin D status, but such tests are not always widely available or feasible. Thus, our study established predictive models with high sensitivity to identify patients either unlikely to have vitamin D deficiency or who should undergo 25(OH)D testing.

Unexpected Cause of Persistent Microcytosis and Neurological Symptoms in a Child: Niemann-Pick Disease Type C.

Atypical microcytic anemias are rare diseases of iron/heme metabolism that can be diagnostically challenging. We report the case of a 2-year-old twin boy with neurodevelopmental delay and persistent microcytosis in whom atypical microcytic anemias was initially suspected. He had low blood iron and transferrin saturation with normal/high ferritin despite iron therapy.

A New Solution to an Old Problem: Ultrasound-guided Cervical Retrolaminar Injection for Acute Cervical Radicular Pain: Prospective Clinical Pilot Study and Cadaveric Study.

Study Design: Prospective clinical pilot study and cadaveric study.

Objective: The aim of this study was to evaluate the spread of an ultrasound-guided interfascial plane blocks (UGIPBs) and its potential efficacy for cervical radiculopathy.

Summary Of Background Data: Cervical radiculopathy is a common disorder, potentially leading to severe pain and disability.

Predictive modeling of hypophosphatasia based on a case series of adult patients with persistent hypophosphatasemia.

Unlabelled: Approximately half of individuals with hypophosphatasemia (low levels of serum alkaline phosphatase) have hypophosphatasia, a rare genetic disease in which patients may have stress fractures, bone and joint pain, or premature tooth loss. We developed a predictive model based on specific biomarkers of this disease to better diagnose this condition.

Introduction: Hypophosphatasemia is a condition in which low levels of alkaline phosphatase (ALP) are detected in the serum.

The Use of Machine Learning Techniques to Determine the Predictive Value of Inflammatory Biomarkers in the Development of Type 2 Diabetes Mellitus.

Certain inflammatory biomarkers, such as interleukin-6, interleukin-1, C-reactive protein (CRP), and fibrinogen, are prototypical acute-phase parameters that can also be predictors of cardiovascular disease. However, this inflammatory response can also be linked to the development of type 2 diabetes mellitus (T2DM). We performed a cross-sectional, retrospective study of hypertensive patients in an outpatient setting.

Nursing Perspective of the Humanized Care of the Neonate and Family: A Systematic Review.

This systematic review aims to determine the extent to which published research articles show the perspective of health professionals in neonatal intensive care units (NICU), as facilitators of family empowerment. Studies conducted between 2013 and 2020 were retrieved from five databases (PubMed, Cochrane, CINHAL, Scopus, and Google Scholar). The search was carried out from January to October 2020.

Developing a Family-Centered Care Model in the Neonatal Intensive Care Unit (NICU): A New Vision to Manage Healthcare.

Family-centered care (FCC) currently takes a greater role in health care, due to the increasing empowerment parents experience. Within neonatal intensive care units (NICUs), family participation has an impact on the humanized care of the preterm newborn (PN). This integrative review conducted according to Whittemore and Knafl investigated current knowledge of the FCC model and its application in PN care in specific units.

Long-Term Outcomes of Infants with Congenital Zika Virus Infection in Ecuador: A Retrospective Longitudinal Study.

Background: Few congenital Zika syndrome (CZS) cases have been notified in Ecuador and, to our knowledge, there are no significant published studies dealing with their clinical evolution. We present a detailed clinical characterization of 21 children with congenital Zika virus (ZIKV) infection born in Ecuador who were followed up until September 2019.

Methods: We did a retrospective longitudinal study of children attended by the infectious disease specialists of Francisco Icaza Bustamante Children's Hospital (Guayaquil) due to congenital ZIKV infection suspicion.

Use of anti-CD20 therapy in follicular and marginal zone lymphoma: a review of the literature.

The identification of the CD20 antigen in 1979 was the first step in what would become a therapeutic milestone opening the use of immunotherapy in hematological diseases. This protein is expressed on the surface of developing B cells, but not the early progenitors or mature plasma cells. In 1997, rituximab was approved by the Food and Drug Administration, and since then it has revolutionized the treatment of B-cell malignancies.

Off-label use of inhaled bronchodilators in hospitalised patients in Spain: a multicentre observational study.

Background: Off-label prescription of inhaled bronchodilators (IB) is frequent, despite the fact that they can be ineffective and increase avoidable healthcare costs.

Objective: To analyse the frequency of off-label prescription of IB in hospitalised patients. Indications and level of evidence, involved drugs, medical specialties prescribing off-label IB and patients' adherence to IBs were also evaluated.

Use of a K-nearest neighbors model to predict the development of type 2 diabetes within 2 years in an obese, hypertensive population.

Prediabetes is a type of hyperglycemia in which patients have blood glucose levels above normal but below the threshold for type 2 diabetes mellitus (T2DM). Prediabetic patients are considered to be at high risk for developing T2DM, but not all will eventually do so. Because it is difficult to identify which patients have an increased risk of developing T2DM, we developed a model of several clinical and laboratory features to predict the development of T2DM within a 2-year period.

Logistic LASSO and Elastic Net to Characterize Vitamin D Deficiency in a Hypertensive Obese Population.

The primary objective of our research was to compare the performance of data analysis to predict vitamin D deficiency using three different regression approaches and to evaluate the usefulness of incorporating machine learning algorithms into the data analysis in a clinical setting. We included 221 patients from our hypertension unit, whose data were collected from electronic records dated between 2006 and 2017. We used classical stepwise logistic regression, and two machine learning methods [least absolute shrinkage and selection operator (LASSO) and elastic net].

Pulse Wave Velocity and Machine Learning to Predict Cardiovascular Outcomes in Prediabetic and Diabetic Populations.

Few studies have addressed the predictive value of arterial stiffness determined by pulse wave velocity (PWV) in a high-risk population with no prevalent cardiovascular disease and with obesity, hypertension, hyperglycemia, and preserved kidney function. This longitudinal, retrospective study enrolled 88 high-risk patients and had a follow-up time of 12.4 years.

Drug-related and psychopathological symptoms in HIV-positive men who have sex with men who inject drugs during sex (slamsex): Data from the U-SEX GESIDA 9416 Study.

Objectives: Sexualized intravenous drug use, also known as slamsex, seems to be increasing among HIV-positive men who have sex with men (MSM). Physical and psychopathological symptoms have previously been reported in this population, although research on the subject of slamsex is scarce. The objectives of our study were to describe the psychopathological background of a sample of HIV-positive MSM who engaged in slamsex during the previous year and to compare physical, psychopathological, and drug-related symptoms between these participants and those who engaged in non-injecting sexualized drug use.

Listeria monocytogenes infections: Analysis of 41 patients.

Objective: We describe and analyze Listeria-related demographics and clinical features to determine the predisposing conditions for severe infections.

Methods: We performed a retrospective study using positive isolation of Listeria monocytogenes from blood, cerebrospinal fluid, and other organic fluids. Electronic health records were used to determine the epidemiological and clinical features of infections caused by L.

Relevant Features in Nonalcoholic Steatohepatitis Determined Using Machine Learning for Feature Selection.

We investigated the prevalence and the most relevant features of nonalcoholic steatohepatitis (NASH), a stage of nonalcoholic fatty liver disease, (NAFLD) in which the inflammation of hepatocytes can lead to increased cardiovascular risk, liver fibrosis, cirrhosis, and the need for liver transplant. We analyzed data from 2239 hypertensive patients using descriptive statistics and supervised machine learning algorithms, including the least absolute shrinkage and selection operator and random forest classifier, to select the most relevant features of NASH. The prevalence of NASH among our hypertensive patients was 11.

Identification of clinically relevant features in hypertensive patients using penalized regression: a case study of cardiovascular events.

Appropriate management of hypertensive patients relies on the accurate identification of clinically relevant features. However, traditional statistical methods may ignore important information in datasets or overlook possible interactions among features. Machine learning may improve the prediction accuracy and interpretability of regression models by identifying the most relevant features in hypertensive patients.