PARCCS: A Machine Learning Risk-Prediction Model for Acute Peripartum Cardiovascular Complications During Delivery Admissions.

Background: Maternal mortality in the United States remains high, with cardiovascular (CV) complications being a leading cause.

Objectives: The purpose of this paper was to develop the PARCCS (Prediction of Acute Risk for Cardiovascular Complications in the Peripartum Period Score) for acute CV complications during delivery.

Methods: Data from the National Inpatient Sample (2016-2020) and International Classification of Diseases, Tenth Revision codes to identify delivery admissions were used.

Prediction of lactate concentrations after cardiac surgery using machine learning and deep learning approaches.

Background: Although conventional prediction models for surgical patients often ignore intraoperative time-series data, deep learning approaches are well-suited to incorporate time-varying and non-linear data with complex interactions. Blood lactate concentration is one important clinical marker that can reflect the adequacy of systemic perfusion during cardiac surgery. During cardiac surgery and cardiopulmonary bypass, minute-level data is available on key parameters that affect perfusion.

Right ventricular diastolic dysfunction and failure: a review.

Right ventricular diastolic dysfunction and failure (RVDDF) has been increasingly identified in patients with cardiovascular diseases, including heart failure and other diseases with cardiac involvement. It is unknown whether RVDDF exists as a distinct clinical entity; however, its presence and degree have been shown to be a sensitive marker of end-organ dysfunction related to multiple disease processes including systemic hypertension, pulmonary hypertension, heart failure, and endocrine disease. In this manuscript, we review issues pertaining to RVDDF including anatomic features of the right ventricle, physiologic measurements, RVDDF diagnosis, underlying mechanisms, clinical impact, and clinical management.

On-label compared to off-label four-factor prothrombin complex concentrate use: a retrospective, observational study.

Background: Four-factor prothrombin complex concentrate (4F-PCC) is US Food and Drug Administration approved for the urgent reversal of coagulation factor deficiency induced by a vitamin K antagonist complicated by acute major bleeding or in situations in which invasive procedures are urgently needed. Although recent evidence suggests the superiority of 4F-PCC over plasma for on-label indications, the off-label use of 4F-PCC has not been rigorously studied.

Study Design And Methods: Eighty-nine patients receiving 4F-PCC at a single institution from July 2016 to December 2017 were retrospectively analyzed.

Network injury to pulvinar with neonatal arterial ischemic stroke.

The purpose of this study is to establish that newborn stroke involving extensive parts of cerebral cortex immediately leads to secondary network injury in pulvinar. Seven term infants with cortical stroke presented with hypersignal in pulvinar on DWI. Stroke types included: complete MCA stroke (n=4); PCA stroke, ICA stroke and multiple artery stroke (1 each).