Analysis of Presentation and Outcomes in Acute Limb Ischemia Patients During COVID-19 State of Emergency.

Background: During the COVID-19 pandemic, cardiovascular patients were found to be presenting to hospitals with myocardial infarctions and cerebrovascular accidents at progressed disease states. We noticed a parallel in acute limb ischemia (ALI) patients presenting during Massachusetts' COVID-19 State of Emergency declaration. We question whether patients developed a hesitancy to seek medical attention at hospitals due to fear of COVID-19.

Plasmapheresis as an Early Treatment for Severe Hypertriglyceridemia, Acute Pancreatitis, and Diabetic Ketoacidosis.

Objective: Severe hypertriglyceridemia (SHTG; plasma triglycerides >1000 mg/dL) is a rare but serious complication in children who develop diabetic ketoacidosis (DKA) from uncontrolled or new-onset type 1 diabetes.

Methods: We present the case of a severely malnourished 16-year-old with a 10-month history of presumed type 2 diabetes managed with lifestyle modifications and metformin, who presented with SHTG, acute pancreatitis, and DKA. On examination, there was no evidence of lipemia retinalis, cutaneous xanthomas, or xanthelasma.

The seventh pandemic of cholera in Europe revisited by microbial genomics.

In 1970, the seventh pandemic of cholera (7 P) reached both Africa and Europe. Between 1970 and 2011, several European countries reported cholera outbreaks of a few to more than 2,000 cases. We report here a whole-genome analysis of 1,324 7 P V.

Identifying incident dementia by applying machine learning to a very large administrative claims dataset.

Alzheimer's disease and related dementias (ADRD) are highly prevalent conditions, and prior efforts to develop predictive models have relied on demographic and clinical risk factors using traditional logistical regression methods. We hypothesized that machine-learning algorithms using administrative claims data may represent a novel approach to predicting ADRD. Using a national de-identified dataset of more than 125 million patients including over 10,000 clinical, pharmaceutical, and demographic variables, we developed a cohort to train a machine learning model to predict ADRD 4-5 years in advance.

Incident Hearing Loss and Comorbidity: A Longitudinal Administrative Claims Study.

Importance: Because hearing loss is highly prevalent and treatable, determining its association with morbidity has major public health implications for disease prevention and the maintenance of health in adults with hearing loss.

Objective: To investigate the association between the diagnosis of incident hearing loss and medical comorbidities in adults 50 years or older.

Design, Setting, And Participants: Retrospective, propensity-matched cohort study using administrative claims data from commercially insured and Medicare Advantage members in a geographically diverse US health plan.