Deep embedded clustering generalisability and adaptation for integrating mixed datatypes: two critical care cohorts.

We validated a Deep Embedded Clustering (DEC) model and its adaptation for integrating mixed datatypes (in this study, numerical and categorical variables). Deep Embedded Clustering (DEC) is a promising technique capable of managing extensive sets of variables and non-linear relationships. Nevertheless, DEC cannot adequately handle mixed datatypes. Therefore, we adapted DEC by replacing the autoencoder with an X-shaped variational autoencoder (XVAE) and optimising hyperparameters for cluster stability. We call this model "X-DEC". We compared DEC and X-DEC by reproducing a previous study that used DEC to identify clusters in a population of intensive care patients. We assessed internal validity based on cluster stability on the development dataset. Since generalisability of clustering models has insufficiently been validated on external populations, we assessed external validity by investigating cluster generalisability onto an external validation dataset. We concluded that both DEC and X-DEC resulted in clinically recognisable and generalisable clusters, but X-DEC produced much more stable clusters.

A guide to sharing open healthcare data under the General Data Protection Regulation.

Sharing healthcare data is increasingly essential for developing data-driven improvements in patient care at the Intensive Care Unit (ICU). However, it is also very challenging under the strict privacy legislation of the European Union (EU). Therefore, we explored four successful open ICU healthcare databases to determine how open healthcare data can be shared appropriately in the EU. A questionnaire was constructed based on the Delphi method. Then, follow-up questions were discussed with experts from the four databases. These experts encountered similar challenges and regarded ethical and legal aspects to be the most challenging. Based on the approaches of the databases, expert opinion, and literature research, we outline four distinct approaches to openly sharing healthcare data, each with varying implications regarding data security, ease of use, sustainability, and implementability. Ultimately, we formulate seven recommendations for sharing open healthcare data to guide future initiatives in sharing open healthcare data to improve patient care and advance healthcare.

A Retrospective Cohort Study of Clinical Factors Associated with Transitions of Care among COVID-19 Patients.

Coronavirus Disease 2019 (COVID-19) is an international health crisis. In this article, we report on patient characteristics associated with care transitions of: 1) hospital admission from the emergency department (ED) and 2) escalation to the intensive care unit (ICU). Analysis of data from the electronic medical record (EMR) was performed for patients with COVID-19 seen in the ED of a large Western U.S. Health System from April to August of 2020, totaling 10,079 encounters. Of these, 5172 resulted in admission as an inpatient within 72 h. Inpatient encounters (n = 6079) were also considered for patients with positive COVID-19 test results, of which 970 resulted in a transfer to the ICU or in-hospital mortality. Laboratory results, vital signs, symptoms, and comorbidities were investigated for each of these care transitions. Different top risk factors were found, but two factors common to hospital admission and ICU transfer were respiratory rate and the need for oxygen support. Comorbidities common to both settings were cerebrovascular disease and congestive heart failure. Regarding laboratory results, the neutrophil-to-lymphocyte ratio was associated with transitions to higher levels of care, along with the ratio of aspartate aminotransferase (AST) to alanine aminotransferase (ALT).

Real-time magnetic resonance imaging-guided endovascular recanalization of chronic total arterial occlusion in a swine model.

BACKGROUND: Endovascular recanalization (guidewire traversal) of peripheral artery chronic total occlusion (CTO) can be challenging. X-ray angiography resolves CTO poorly. Virtually "blind" device advancement during x-ray-guided interventions can lead to procedure failure, perforation, and hemorrhage. Alternatively, MRI may delineate the artery within the occluded segment to enhance procedural safety and success. We hypothesized that real-time MRI (rtMRI)-guided CTO recanalization can be accomplished in an animal model. METHODS AND RESULTS: Carotid artery CTO was created by balloon injury in 19 lipid-overfed swine. After 6 to 8 weeks, 2 underwent direct necropsy analysis for histology, 3 underwent primary x-ray-guided CTO recanalization attempts, and the remaining 14 underwent rtMRI-guided recanalization attempts in a 1.5-T interventional MRI system. Real-time MRI intervention used custom CTO catheters and guidewires that incorporated MRI receiver antennae to enhance device visibility. The mean length of the occluded segments was 13.3+/-1.6 cm. The rtMRI-guided CTO recanalization was successful in 11 of 14 swine and in only 1 of 3 swine with the use of x-ray alone. After unsuccessful rtMRI (n=3), x-ray-guided attempts were also unsuccessful. CONCLUSIONS: Recanalization of long CTO is entirely feasible with the use of rtMRI guidance. Low-profile clinical-grade devices will be required to translate this experience to humans.