Phenotyping the Spectrum of Traumatic Brain Injury: A Review and Pathway to Standardization.

It is widely appreciated that the spectrum of traumatic brain injury (TBI), mild through severe, contains distinct clinical presentations, variably referred to as subtypes, phenotypes, and/or clinical profiles. As part of the Brain Trauma Blueprint TBI State of the Science, we review the current literature on TBI phenotyping with an emphasis on unsupervised methodological approaches, and describe five phenotypes that appear similar across reports. However, we also find the literature contains divergent analysis strategies, inclusion criteria, findings, and use of terms.

Predicting Survival in Veterans with Follicular Lymphoma Using Structured Electronic Health Record Information and Machine Learning.

The most accurate prognostic approach for follicular lymphoma (FL), progression of disease at 24 months (POD24), requires two years' observation after initiating first-line therapy (L1) to predict outcomes. We applied machine learning to structured electronic health record (EHR) data to predict individual survival at L1 initiation. We grouped 523 observations and 1933 variables from a nationwide cohort of FL patients diagnosed 2006-2014 in the Veterans Health Administration into traditionally used prognostic variables ("curated"), commonly measured labs ("labs"), and International Classification of Diseases diagnostic codes ("ICD") sets.

Computerized Mortality Prediction for Community-acquired Pneumonia at 117 Veterans Affairs Medical Centers.

Computerized severity assessment for community-acquired pneumonia could improve consistency and reduce clinician burden. To develop and compare 30-day mortality-prediction models using electronic health record data, including a computerized score with all variables from the original Pneumonia Severity Index (PSI) except confusion and pleural effusion ("ePSI score") versus models with additional variables. Among adults with community-acquired pneumonia presenting to emergency departments at 117 Veterans Affairs Medical Centers between January 1, 2006, and December 31, 2016, we compared an ePSI score with 10 novel models employing logistic regression, spline, and machine learning methods using PSI variables, age, sex and 26 physiologic variables as well as all 69 PSI variables.

Detection of Tachyarrhythmias in a Large Cohort of Infants Using Direct-to-Consumer Heart Rate Monitoring.

Objective: Current estimates of the incidence of tachyarrhythmias in infants rely on clinical documentation and may not reflect the true rate in the general population. Our aim was to describe the epidemiology of tachyarrhythmia detected in a large cohort of infants using direct-to-consumer heart rate (HR) monitoring.

Study Design: Data were collected from Owlet Smart Sock devices used in infants in the US with birthdates between February 2017 and February 2019.

Impact of Medial Meniscotibial Ligament Disruption Compared to Peripheral Medial Meniscal Tear on Knee Biomechanics.

Medial meniscotibial ligament (MTL) lesions may go unrecognized and untreated and have detrimental impact on knee biomechanics and joint pathology. Therefore, this study was designed to compare the biomechanical impact of midbody MTL disruption to corresponding peripheral medial meniscal (PMM) tears in anterior cruciate ligament (ACL) intact and ACL-deficient cadaveric knees. Cadaveric knees ( = 12; 6 matched pairs) were tested for laxity and ACL strain under anterior, valgus, and external rotation loading at 0, 30, and 90 degree of flexion.