Clinical prediction rule

Islet autoantibodies predict type 1 diabetes (T1D) but can be transient in murine and human T1D and are not thought to be directly pathogenic. Rather, these autoantibodies signal B cell activity as antigen-presenting cells (APCs) that present islet autoantigen to diabetogenic T cells to promote T1D pathogenesis. Disrupting B cell APC function prevents T1D in mouse models and has shown promise in clinical trials. Autoantigen-specific B cells thus hold potential as sophisticated T1D biomarkers and therapeutic targets...

BACKGROUND: Mortality due to immune-mediated thrombotic thrombocytopenic purpura (iTTP) remains significant. Predicting mortality risk may potentially help individualize treatment. The French Thrombotic Microangiopathy (TMA) Reference Score has not been externally validated in the United States. Recent advances in machine learning technology can help analyze large numbers of variables with complex interactions for the development of prediction models. OBJECTIVES: To validate the French TMA Reference Score in the United States Thrombotic Microangiopathy (USTMA) iTTP database and subsequently develop a novel mortality prediction tool, the USTMA TTP Mortality Index...

PURPOSE/OBJECTIVE: To investigate the occurrence of behavioral problems 7 years after severe pediatric traumatic brain injury (TBI), and their evolution from 3 months to 7 years postinjury. METHOD/DESIGN: Thirty-four participants, 38% girls, M ( SD ) age at injury 7.6 (4.7) years, age at assessment 15 (4.6) years, underwent comprehensive assessments 7 years after severe TBI from March 2014 to March 2016 and were matched to a control group by age, gender, and parental education...

PURPOSE: To rule out hemorrhage, non-contrast CT (NCCT) scans are used for early evaluation of patients with suspected stroke. Recently, artificial intelligence tools have been developed to assist with determining eligibility for reperfusion therapies by automating measurement of the Alberta Stroke Program Early CT Score (ASPECTS), a 10-point scale with > 7 or ≤ 7 being a threshold for change in functional outcome prediction and higher chance of symptomatic hemorrhage, and hypodense volume...

BACKGROUND: Thus far, all the clinical models developed to predict major bleeding in patients on extended anticoagulation therapy use the baseline predictors to stratify patients into different risk groups. Therefore, these models do not account for the clinical changes and events that occur after the baseline visit, which can modify risk of bleeding. However, it is difficult to develop predictive models from the routine follow-up clinical interviews which are irregular sequences of multivariate time series data...

IMPORTANCE: Macrosomia represents the most significant risk factor of shoulder dystocia (SD), which is a severe and emergent complication of vaginal delivery. They are both associated with adverse pregnancy outcomes. OBJECTIVE: The aim of this study was to review and compare the most recently published influential guidelines on the diagnosis and management of fetal macrosomia and SD. EVIDENCE ACQUISITION: A comparative review of guidelines from the American College of Obstetricians and Gynecologists (ACOG), the Royal College of Obstetricians and Gynaecologists, the National Institute for Health and Care Excellence, the Royal Australian and New Zealand College of Obstetricians and Gynaecologists (RANZCOG), and the Department for Health and Wellbeing of the Government of South Australia on macrosomia and SD was conducted...

Currently, clinically available coronary CT angiography (CCTA) derived fractional flow reserve (CT-FFR) is time-consuming and complex. We propose a novel artificial intelligence-based fully-automated, on-site CT-FFR technology, which combines the automated coronary plaque segmentation and luminal extraction model with reduced order 3 dimentional (3D) computational fluid dynamics. A total of 463 consecutive patients with 600 vessels from the updated China CT-FFR study in Cohort 1 undergoing both CCTA and invasive fractional flow reserve (FFR) within 90 d were collected for diagnostic performance evaluation...

Biomarker stratified clinical trial designs are versatile tools to assess biomarker clinical utility and address its relationship with clinical endpoints. Due to imperfect assays and/or classification rules, biomarker status is prone to errors. To account for biomarker misclassification, we consider a two-stage stratified design for survival outcomes with an adjustment for misclassification in predictive biomarkers. Compared to continuous and/or binary outcomes, the test statistics for survival outcomes with an adjustment for biomarker misclassification is much more complicated and needs to take special care...

BACKGROUND: Thrombotic microangiopathies (TMA) are a group of disorders with overlapping clinical features that require urgent intervention. Treatment is based on the recognition of the TMA type, which is often challenging. The aim of this study was to identify specific HLA associations with different TMA types to aid rapid diagnosis and appropriate treatment, since the HLA assay can be completed within five hours. METHODS: All 86 consecutive patients who presented to the University of Arkansas for Medical Sciences between May 2013 and January 2021 with a presumptive diagnosis of TMA were included in this study...

BACKGROUND: The long-term prognosis for patients with osteosarcoma (OS) metastasis remains unfavourable, highlighting the urgent need for research that explores potential biomarkers using innovative methodologies. METHODS: This study explored potential biomarkers for OS metastasis by analysing data from the Cancer Genome Atlas Program (TCGA) and Gene Expression Omnibus (GEO) databases. The synthetic minority oversampling technique (SMOTE) was employed to tackle class imbalances, while genes were selected using four feature selection algorithms (Monte Carlo feature selection [MCFS], Borota, minimum-redundancy maximum-relevance [mRMR], and light gradient-boosting machine [LightGBM]) based on the gene expression matrix...

Positive and negative estimates are commonly used by clinicians to evaluate the likelihood of a disease stage being present based on test results. The predicted values are dependent on the prevalence of the underlying illness. However, for certain diseases or clinical conditions, the prevalence is unknown or different from one region to another or from one population to another, leading to an erroneous diagnosis. This article introduces innovative post-test diagnostic precision measures for continuous tests or biomarkers based on the combined areas under the predictive value curves for all possible prevalence values...

The current standard of care for coronary artery disease (CAD) requires an intake of radioactive or contrast enhancement dyes, radiation exposure, and stress and may take days to weeks for referral to gold-standard cardiac catheterization. The CAD diagnostic pathway would greatly benefit from a test to assess for CAD that enables the physician to rule it out at the point of care, thereby enabling the exploration of other diagnoses more rapidly. We sought to develop a test using machine learning to assess for CAD with a rule-out profile, using an easy-to-acquire signal (without stress/radiation) at the point of care...

BACKGROUND: The intra-abdominal injury and traumatic brain injury prediction rules derived by the Pediatric Emergency Care Applied Research Network (PECARN) were designed to reduce inappropriate use of CT in children with abdominal and head trauma, respectively. We aimed to validate these prediction rules for children presenting to emergency departments with blunt abdominal or minor head trauma. METHODS: For this prospective validation study, we enrolled children and adolescents younger than 18 years presenting to six emergency departments in Sacramento (CA), Dallas (TX), Houston (TX), San Diego (CA), Los Angeles (CA), and Oakland (CA), USA between Dec 27, 2016, and Sept 1, 2021...

Deep learning algorithms have been widely used in microscopic image translation. The corresponding data-driven models can be trained by supervised or unsupervised learning depending on the availability of paired data. However, general cases are where the data are only roughly paired such that supervised learning could be invalid due to data unalignment, and unsupervised learning would be less ideal as the roughly paired information is not utilized. In this work, we propose a unified framework (U-Frame) that unifies supervised and unsupervised learning by introducing a tolerance size that can be adjusted automatically according to the degree of data misalignment...

No abstract text is available yet for this article.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease worldwide, affecting about 1/4th of the global population and causing a huge global economic burden. To date, no drugs have been approved for the treatment of NAFLD, making the correction of unhealthy lifestyles the principle method of treatment. Identifying patients with poor adherence to lifestyle correction and attempting to improve their adherence are therefore very important. AIM: To develop and validate a scale that can rapidly assess the adherence of patients with NAFLD to lifestyle interventions...

Recent advancements in science and technology, coupled with the proliferation of data, have also urged laboratory medicine to integrate with the era of artificial intelligence (AI) and machine learning (ML). In the current practices of evidence-based medicine, the laboratory tests analysing disease patterns through the association rule mining (ARM) have emerged as a modern tool for the risk assessment and the disease stratification, with the potential to reduce cardio-vascular disease (CVD) mortality. CVDs are the well recognised leading global cause of mortality with the higher fatality rates in the Indian population due to associated factors like hypertension, diabetes, and lifestyle choices...

INTRODUCTION: The aim of our study was to compare 3 diagnostic pathways: diastolic stress echocardiography (DSE) based on the ASE/EACVI 2016 guidelines, the 2018 H₂FPEF score, and the 2019 HFA-PEFF algorithm, in patients suspected of heart failure with preserved ejection fraction (HFpEF). MATERIAL AND METHODS: The study group included 80 consecutive patients with a clinical suspicion of HFpEF. The H₂FPEF and HFA-PEFF scores and serum NT-proBNP concentrations were assessed in all the patients before they were sent for DSE...

BACKGROUND: Single breath count test (SBCT) may be a reproducible, rapid, easy to perform and easy to interpret substitute to spirometry especially in low resource settings for certain conditions. Its interest has been rekindled with the recent COVID-19 pandemic and it can be done as a part of tele-medicine as well. OBJECTIVES: The objective of this review was to summarize the evidence of SBCT in clinical practice. METHODS: The authors searched EMBASE, PubMed and Google Scholar for all the relevant articles as per exclusion and inclusion criteria...

Kidney transplantation is the best option for kidney replacement therapy, even considering that most of the times the grafts do not survive as long as their recipients. In the Khalil et al 's experience, published in this issue of the Journal, they analyze their second kidney graft survival and describe those significant predictors of early loss. This editorial comments on the results and put in perspec tive that most of the times, long-term graft survival could be inadvertently jeopardized if the immunosuppressive therapy is reduced or withdrawn for any reason, and that it could happen frequently if the transplant physician intends to innovate with the clinical care without proper evidence-based data...