Intensive Care Unit Telemedicine in the Era of Big Data, Artificial Intelligence, and Computer Clinical Decision Support Systems.

This article examines the history of the telemedicine intensive care unit (tele-ICU), the current state of clinical decision support systems (CDSS) in the tele-ICU, applications of machine learning (ML) algorithms to critical care, and opportunities to integrate ML with tele-ICU CDSS. The enormous quantities of data generated by tele-ICU systems is a major driver in the development of the large, comprehensive, heterogeneous, and granular data sets necessary to develop generalizable ML CDSS algorithms, and deidentification of these data sets expands opportunities for ML CDSS research.

Counterintuitive results from observational data: a case study and discussion.

Objective: To explore the issue of counterintuitive data via analysis of a representative case in which the data obtained was unexpected and inconsistent with current knowledge. We then discuss the issue of counterintuitive data while developing a framework for approaching such findings.

Design: The case study is a retrospective analysis of a cohort of coronary artery bypass graft (CABG) patients.

The association between autoimmune disease and 30-day mortality among sepsis ICU patients: a cohort study.

Introduction: Sepsis results from a dysregulated host response to an infection that is associated with an imbalance between pro- and anti-inflammatory cytokines. This imbalance is hypothesized to be a driver of patient mortality. Certain autoimmune diseases modulate the expression of cytokines involved in the pathophysiology of sepsis.

Lower 90-day Hospital Readmission Rates for Esophageal Variceal Bleeding After TIPS: A Nationwide Linked Analysis.

Objective: Hospital readmission rates following a transjugular intrahepatic portosystemic shunt (TIPS) insertion after an episode of esophageal variceal bleeding (EVB) has not been well studied. We aimed to address this gap in knowledge on a population level.

Methods: The Nationwide Readmission Database (NRD) was used to study the readmission rates for patients with decompensated cirrhosis who had a TIPS insertion performed for EVB.

Outcomes of in-hospital cardiopulmonary resuscitation for patients with end-stage liver disease.

Background And Aims: There have been improving survival trends after in-hospital cardiac arrest for the general population, but there is limited information on the outcomes of hospitalized patients with end-stage liver disease (ESLD) who undergo cardiopulmonary resuscitation (CPR). We aimed to examine survival to hospital discharge after receipt of in-hospital CPR in patients with ESLD using a nationally representative sample.

Methods: We used the Nationwide Inpatient Sample database from 2006 to 2014 to identify adult patients who underwent in-hospital CPR.

Withholding or withdrawing invasive interventions may not accelerate time to death among dying ICU patients.

Background: Critically ill patients may die despite invasive intervention. In this study, we examine trends in the application of two such treatments over a decade, namely, endotracheal ventilation and vasopressors and inotropes administration, as well as the impact of these trends on survival durations in patients who die within a month of ICU admission.

Methods: We considered observational data available from the MIMIC-III open-access ICU database and collected within a study period between year 2002 up to 2011.

Palliative medicine and hospital readmissions in end-stage liver disease.

Background: Patients with end-stage liver disease (ESLD) have a reduced life expectancy and a significant symptom burden. Our aim is to determine if inpatient palliative care (PC) referral for patients with ESLD is associated with decreased hospital readmission rates.

Methods: The 2013 US Nationwide Readmission Database (NRD) was used for the current analysis.

Assessment of Intensive Care Unit Laboratory Values That Differ From Reference Ranges and Association With Patient Mortality and Length of Stay.

Importance: Laboratory data are frequently collected throughout the care of critically ill patients. Currently, these data are interpreted by comparison with values from healthy outpatient volunteers. Whether this is the most useful comparison has yet to be demonstrated.

The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data.

Recent years have seen a surge of studies in machine learning in health and biomedicine, driven by digitalization of healthcare environments and increasingly accessible computer systems for conducting analyses. Many of us believe that these developments will lead to significant improvements in patient care. Like many academic disciplines, however, progress is hampered by lack of code and data sharing.

Feature selection and prediction of treatment failure in tuberculosis.

Background: Tuberculosis is a major cause of morbidity and mortality in the developing world. Drug resistance, which is predicted to rise in many countries worldwide, threatens tuberculosis treatment and control.

Objective: To identify features associated with treatment failure and to predict which patients are at highest risk of treatment failure.

Applying machine learning to continuously monitored physiological data.

The use of machine learning (ML) in healthcare has enormous potential for improving disease detection, clinical decision support, and workflow efficiencies. In this commentary, we review published and potential applications for the use of ML for monitoring within the hospital environment. We present use cases as well as several questions regarding the application of ML to the analysis of the vast amount of complex data that clinicians must interpret in the realm of continuous physiological monitoring.

Post-extrasystolic characteristics in the arterial blood pressure waveform are associated with right ventricular dysfunction in intensive care patients.

Right ventricular dysfunction (RVD) is associated with end-organ dysfunction and mortality, but has been an overlooked condition in the ICU. We hypothesized that analysis of the arterial waveform in the presence of ventricular extrasystoles could differentiate patients with RVD from patients with a normally functioning right ventricle, because the 2nd and 3rd post-ectopic beat could reflect right ventricular state (pulmonary transit time) during the preceding ectopy. We retrospectively identified patients with echocardiographic evidence of moderate-to-severe RVD and patients with a normal functioning right ventricle (control) from the MIMIC database.

The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care.

Sepsis is the third leading cause of death worldwide and the main cause of mortality in hospitals, but the best treatment strategy remains uncertain. In particular, evidence suggests that current practices in the administration of intravenous fluids and vasopressors are suboptimal and likely induce harm in a proportion of patients. To tackle this sequential decision-making problem, we developed a reinforcement learning agent, the Artificial Intelligence (AI) Clinician, which extracted implicit knowledge from an amount of patient data that exceeds by many-fold the life-time experience of human clinicians and learned optimal treatment by analyzing a myriad of (mostly suboptimal) treatment decisions.

Improved Survival of Cancer Patients Admitted to the Intensive Care Unit between 2002 and 2011 at a U.S. Teaching Hospital.

Purpose: Cancer patients are at increased risk of treatment- or disease-related admission to the intensive care unit. Over the past decades, both critical care and cancer care have improved substantially. Due to increased cancer-specific survival, we hypothesized that the number of cancer patients admitted to the intensive care unit (ICU) and survival have increased.

The Impact of Chronic Ozone and Particulate Air Pollution on Mortality in Patients With Sepsis Across the United States.

Objective: The impact of chronic exposure to air pollution on mortality in patients with sepsis is unknown. We attempted to quantify the relationship between air pollution, notably excess ozone, and particulate matter (PM), with in-hospital mortality in patients with sepsis nationwide.

Methods: The 2011 Nationwide Inpatient Sample (NIS) was linked with ambient air pollution data from the Environmental Protection Agency for both 8-hour ozone exposure and annual mean 2.

Mechanical power of ventilation is associated with mortality in critically ill patients: an analysis of patients in two observational cohorts.

Purpose: Mechanical power (MP) may unify variables known to be related to development of ventilator-induced lung injury. The aim of this study is to examine the association between MP and mortality in critically ill patients receiving invasive ventilation for at least 48 h.

Methods: This is an analysis of data stored in the databases of the MIMIC-III and eICU.

Impact of Intensive Care Unit Discharge Delays on Patient Outcomes: A Retrospective Cohort Study.

Objective: Patients often overstay in intensive care units (ICU) after they are deemed discharge ready. The objective of this study was to examine the impact of such discharge delays (DD) on subsequent in-hospital morbidity and mortality.

Design: Retrospective cohort study.

The eICU Collaborative Research Database, a freely available multi-center database for critical care research.

Critical care patients are monitored closely through the course of their illness. As a result of this monitoring, large amounts of data are routinely collected for these patients. Philips Healthcare has developed a telehealth system, the eICU Program, which leverages these data to support management of critically ill patients.

Vasopressin Administration Is Associated With Rising Serum Lactate Levels in Patients With Sepsis.

Background: Vasopressin is used in conjunction with norepinephrine during treatment of patients with septic shock. Serum lactate is often used in monitoring of patients with sepsis; however, its importance as a therapeutic target is unclear. The objective of this study is to examine the relationship of vasopressin use on serum lactate levels in patients with sepsis.