Tag: technology
Scientific Study Validates Usability of Post-ICU Digital Diary for Families of ICU Patients
In a groundbreaking pilot study, "The usability of a digital diary from the perspectives of intensive care patients’ relatives", researchers have unequivocally confirmed the practicality and effectiveness of Post-ICU for... read more
Ground-breaking New AI Technology for Severe Sepsis Rapid Identification
ASEP Medical Holdings Inc. announced the ground-breaking use of artificial intelligence (AI) to rapidly identify infections at increased risk of severe sepsis. The method was developed by the Hancock Lab, under the guidance... read more
Infusion Management Software Can Seamlessly Connect Thousands Pumps Across Facilities
A newly-launched next-generation infusion management platform provides organizations with a blend of real-time views and retrospective reporting capabilities, enhancing the understanding of their infusion pump fleet and associated... read more
High Speed Blood Flow Measurements Enabled by LW-iDCS
In this work we have demonstrated the development of long wavelength, interferometric diffuse correlation spectroscopy. Using a fiber optic probe with collocated detection fibers, we were able to directly compare measured... read more
Deep Learning-based Electrocardiographic Screening for Chronic Kidney Disease
Undiagnosed chronic kidney disease (CKD) is a common and usually asymptomatic disorder that causes a high burden of morbidity and early mortality worldwide. We developed a deep learning model for CKD screening from routinely... read more
Post-discharge Care Using Telemedicine: Pre-pandemic vs. Pandemic Care
Expansion of virtual post-discharge visits to include all patients and telephone calls did not negatively impact rates of 30-day post-discharge hospital encounters. Offering tele-health options for post-discharge follow-up... read more
Predicting Readmission or Death After Discharge From the ICU with Machine Learning
In this era of expanding availability of ML models, external validation and retraining are key steps to consider before applying machine learning (ML) models to new settings. Clinicians and decision-makers should take... read more
Intracranial Pressure: Current Perspectives on Physiology and Monitoring
Intracranial pressure (ICP) monitoring is now viewed as integral to the clinical care of many life-threatening brain insults, such as severe traumatic brain injury, subarachnoid hemorrhage, and malignant stroke. It serves... read more
Adapting FDA Regulation for AI-Powered Medical Devices
To keep up with the advancement of medical technology, the FDA has been working on a digital health pre-certification program that would allow the agency to pre-approve trusted manufacturers to update their software products.... read more
Algorithm that Detects Sepsis Cut Deaths by 18%
Hospital patients are at risk of a number of life-threatening complications, especially sepsis—a condition that can kill within hours and contributes to one out of three in-hospital deaths in the U.S. Overworked doctors... read more
Machine Learning Model Validation for Prediction of Potential PICU Transfer
We developed and externally validated a novel machine learning model that identifies ICU transfers in hospitalized children more accurately than current tools. Our model enables early detection of children at risk for... read more
Patients Monitored Using Wearable Monitors Experienced Fewer Unplanned ICU Admissions
Implementation of continuous monitoring of patient vital signs using wearable monitoring technology linked wirelessly to hospital systems was associated with a reduction in unplanned ICU admissions and rapid response team... read more
Voiceless Patients in ICU Regard High-tech AAC Devices As Useful
Although the existing evidence is limited, voiceless patients regard augmentative and alternative communication (high-tech AAC) devices as a useful, reliable, and acceptable alternative communication choice in the ICU. Multicenter,... read more
Standardized Data Collection in Prehospital Critical Care
The medical problems categorized by HEMS personnel can be seen as valid. The greatest challenges remain in the classification of stroke and other neurological emergencies. Patients treated by HEMS personnel are characterized... read more
AI Predicts If And When Cardiac Arrest Will Happen
Sudden cardiac death from arrhythmia is a major cause of mortality worldwide. In this study, we developed a novel deep learning (DL) approach that blends neural networks and survival analysis to predict patient-specific survival... read more
3D Printing PPE During COVID-19 Pandemic
Supply chain disruption during the COVID-19 pandemic has forced healthcare systems to look for alternative ways to meet dramatically increased demand for personal protective equipment (PPE). One potential solution to this... read more
ARDS Subphenotypes Validation and Utility Identified by Machine-learning Models
Classifier models using clinical variables alone can accurately assign ARDS subphenotypes in observational cohorts. Application of these models can provide valuable prognostic information and could inform management strategies... read more
Experiences of ICU Nurses with an Innovative Digital Diary Intervention
ICU nurses reported that the Post-ICU diary had added value for patients and their relatives. However, in the beginning they also experienced barriers such as lack of time, insufficient integration with their own work processes,... read more
The Intensivist’s Challenge: Aging and Career Growth in a High-Stress Medical Specialty
This book brings together personal narratives from critical care medicine specialists around the world. Most of these physicians started in critical care at or before the exponential increase in technological modalities to... read more
Telemedicine in the ICU
This text provides a concise, yet comprehensive overview of telemedicine in the ICU. The first part of the book reviews common issues faced by practitioners and hospital administrators in implementing and managing tele-ICU... read more
Bringing Biological ARDS Phenotypes to the Bedside with Machine-learning-based Classifiers
The identification of distinct phenotypes within heterogeneous disease states is a key component of personalised medicine, enabling enrichment of clinical trials, better prognostication, and delivery of tailored treatments... read more
Computer-assisted Individualized Hemodynamic Management Reduces Intraoperative Hypotension
In patients having intermediate- to high-risk surgery, computer-assisted individualized hemodynamic management significantly reduces intraoperative hypotension compared to a manually controlled goal-directed approach. All... read more
