Doctor Facilitated Denial: A Barrier to Advance Care Planning Among COPD Patients.

Background: Many severe COPD patients are unaware of their treatment options and lack motivation for advance care planning. It is crucial to increase patient awareness regarding their chronic conditions.

Methods: The decision aid was used in outpatient clinical visits to inform patients about their COPD prognosis.

Understanding Causes of Death in Patients With Acute Respiratory Distress Syndrome: A Narrative Review.

Objectives: To provide a comprehensive summary of the published data on cause of death in patients with acute respiratory distress syndrome (ARDS).

Data Sources: PubMed (January 2015 to April 2024), bibliographies of relevant articles, and ARDS Network and Prevention & Early Treatment of Acute Lung Injury (PETAL) network websites.

Study Selection: Observational studies and clinical trials that reported on cause of death in greater than or equal to 30 patients with ARDS, not obtained from death certificates.

ARDSFlag: an NLP/machine learning algorithm to visualize and detect high-probability ARDS admissions independent of provider recognition and billing codes.

Background: Despite the significance and prevalence of acute respiratory distress syndrome (ARDS), its detection remains highly variable and inconsistent. In this work, we aim to develop an algorithm (ARDSFlag) to automate the diagnosis of ARDS based on the Berlin definition. We also aim to develop a visualization tool that helps clinicians efficiently assess ARDS criteria.

Should Transport Ventilators Be Used in Times of Crisis? The Use of Emergency Authorized Nonconventional Ventilators Is Associated With Mortality Among Patients With COVID-19 Acute Respiratory Distress Syndrome.

Objectives: Nonconventional ventilators (NCVs), defined here as transport ventilators and certain noninvasive positive pressure devices, were used extensively as crisis-time ventilators for intubated patients with COVID-19. We assessed whether there was an association between the use of NCV and higher mortality, independent of other factors.

Design: This is a multicenter retrospective observational study.

Drivers of mortality in COVID ARDS depend on patient sub-type.

The most common cause of death in people with COVID-19 is Acute Respiratory Distress Syndrome (ARDS). Prior studies have demonstrated that ARDS is a heterogeneous syndrome and have identified ARDS sub-types (phenoclusters). However, non-COVID-19 ARDS phenoclusters do not clearly apply to COVID-19 ARDS patients.

Application of the RE-AIM framework to evaluate the implementation of telehealth pulmonary rehabilitation in a randomized controlled trial among African-American and Hispanic patients with advanced stage Chronic Obstructive Pulmonary Disease.

Background: Pulmonary rehabilitation (PR) decreases rehospitalization for people with COPD. However, less than 2% receive PR, partly due to lack of referral and sparsity of PR facilities. This disparity is particularly pronounced in African American and Hispanic persons with COPD.

US and Dutch Perspectives on the Use of COVID-19 Clinical Prediction Models: Findings from a Qualitative Analysis.

Introduction: Clinical prediction models (CPMs) for coronavirus disease 2019 (COVID-19) may support clinical decision making, treatment, and communication. However, attitudes about using CPMs for COVID-19 decision making are unknown.

Methods: Online focus groups and interviews were conducted among health care providers, survivors of COVID-19, and surrogates (i.

Discriminating Acute Respiratory Distress Syndrome from other forms of respiratory failure via iterative machine learning.

Acute Respiratory Distress Syndrome (ARDS) is associated with high morbidity and mortality. Identification of ARDS enables lung protective strategies, quality improvement interventions, and clinical trial enrolment, but remains challenging particularly in the first 24 hours of mechanical ventilation. To address this we built an algorithm capable of discriminating ARDS from other similarly presenting disorders immediately following mechanical ventilation.

Prognostic models for COVID-19 needed updating to warrant transportability over time and space.

Background: Supporting decisions for patients who present to the emergency department (ED) with COVID-19 requires accurate prognostication. We aimed to evaluate prognostic models for predicting outcomes in hospitalized patients with COVID-19, in different locations and across time.

Methods: We included patients who presented to the ED with suspected COVID-19 and were admitted to 12 hospitals in the New York City (NYC) area and 4 large Dutch hospitals.

Hospitalized Patients With COVID-19 Have Higher Plasma Aldosterone-Renin Ratio and Lower ACE Activity Than Controls.

Context: SARS-CoV-2 infects cells via the angiotensin converting enzyme 2 (ACE2) receptor, whose downstream effects "counterbalance" the classical renin angiotensin aldosterone system (RAAS).

Objective: We aimed to determine to what extent circulating RAAS biomarker levels differ in persons with and without COVID-19 throughout the disease course.

Methods: We measured classical (renin, aldosterone, aldosterone/renin ratio [ARR], Ang2, ACE activity) and nonclassical (ACE2, Ang1,7) RAAS biomarkers in hospitalized COVID-19 patients vs SARS-CoV-2 negative controls.

MUlticenter STudy of tissue plasminogen activator (alteplase) use in COVID-19 severe respiratory failure (MUST COVID): A retrospective cohort study.

Background: Few therapies exist to treat severe COVID-19 respiratory failure once it develops. Given known diffuse pulmonary microthrombi on autopsy studies of COVID-19 patients, we hypothesized that tissue plasminogen activator (tPA) may improve pulmonary function in COVID-19 respiratory failure.

Methods: A multicenter, retrospective, observational study of patients with confirmed COVID-19 and severe respiratory failure who received systemic tPA (alteplase) was performed.

A Novel Method to Improve the Identification of Time of Intubation for Retrospective EHR Data Analysis During a Time of Resource Strain, the COVID-19 Pandemic.

Accurate determinations of the time of intubation (TOI) are critical for retrospective electronic health record (EHR) data analyses. In a retrospective study, the authors developed and validated an improved query (Ti) to identify TOI across numerous settings in a large health system, using EHR data, during the COVID-19 pandemic. Further, they evaluated the affect of Ti on peri-intubation patient parameters compared to a previous method-ventilator parameters (Tv).

Efficacy and Safety of Sarilumab in Hospitalized Patients With Coronavirus Disease 2019: A Randomized Clinical Trial.

Background: Open-label platform trials and a prospective meta-analysis suggest efficacy of anti-interleukin (IL)-6R therapies in hospitalized patients with coronavirus disease 2019 (COVID-19) receiving corticosteroids. This study evaluated the efficacy and safety of sarilumab, an anti-IL-6R monoclonal antibody, in the treatment of hospitalized patients with COVID-19.

Methods: In this adaptive, phase 2/3, randomized, double-blind, placebo-controlled trial, adults hospitalized with COVID-19 received intravenous sarilumab 400 mg or placebo.

Trajectories of hypoxemia and pulmonary mechanics of COVID-19 ARDS in the NorthCARDS dataset.

Background: Understanding heterogeneity seen in patients with COVIDARDS and comparing to non-COVIDARDS may inform tailored treatments.

Methods: A multidisciplinary team of frontline clinicians and data scientists worked to create the Northwell COVIDARDS dataset (NorthCARDS) leveraging over 11,542 COVID-19 hospital admissions. The data was then summarized to examine descriptive differences based on clinically meaningful categories of lung compliance, and to examine trends in oxygenation.

Using Telehealth to Improve the Accuracy of Delirium Screening by Bedside Critical Care Nurses.

Background: Delirium affects up to 80% of patients in the intensive care unit (ICU) but is missed in up to 75% of cases. Telehealth in the ICU (tele-ICU) has become the standard for providing timely, expert care to remotely located ICUs.

Objectives: This pilot study assessed the feasibility and acceptability of using tele-ICU to increase the accuracy of delirium screening and recognition by ICU nurses.

Hypertriglyceridemia-Induced Acute Pancreatitis, Euglycemic Diabetic Ketoacidosis and COVID-19 Infection in a Patient With Type 2 Diabetes Taking a Sodium-Glucose Cotransporter 2 Inhibitor.

Recent landmark trials have increased the use of sodium-glucose cotransporter 2 inhibitors (SGLT-2i) in patients with type 2 diabetes (T2D). A rare but serious side effect of SGLT-2i is euglycemic diabetic ketoacidosis (euDKA), which usually occurs in the setting of acute illness such as the coronavirus disease 2019 (COVID-19). We report a distinctive case of a patient with hyperlipidemia and T2D on SGLT-2i therapy who presented with hypertriglyceridemia-induced pancreatitis (HTGP) concurrently with euDKA and COVID-19.

The Value of Thromboelastography (TEG) in COVID-19 Critical Illness as Illustrated by a Case Series.

Objective: To develop a practical thromboelastograph guided (TEG) anticoagulation protocol to guide the management of COVID-19 critically ill patients.

Design: An inter disciplinary team reviewed the current literature on hypercoagulability in critically ill COVID-19 patients, clinical management practices and challenges with high rates of thrombotic events despite anticoagulant therapies.

Setting: The largest tertiary care hospital within the Northwell Health System in New York.

Improving delirium detection in intensive care units: Multicomponent education and training program.

Background: Delirium is a common, devastating, and underrecognized syndrome in the intensive care unit (ICU). The study aimed to describe and evaluate a multicomponent education and training program utilizing a "Train-The-Trainer" (TTT) model, to improve delirium detection across a large health system.

Methods: Fourteen ICUs across nine hospitals participated in a multicomponent delirium program consisting of a 1-day workshop that included: (1) patient testimonials, (2) small group discussions, (3) didactics, and (4) role-playing.

Humanizing the ICU Patient: A Qualitative Exploration of Behaviors Experienced by Patients, Caregivers, and ICU Staff.

Objectives: To understand how patients and family members experience dehumanizing or humanizing treatment when in the ICU.

Design: Qualitative study included web-based focus groups and open-ended surveys posted to ICU patient/family social media boards. Focus groups were audio recorded and transcribed.

Variation in Early Management Practices in Moderate-to-Severe ARDS in the United States: The Severe ARDS: Generating Evidence Study.

Background: Although specific interventions previously demonstrated benefit in patients with ARDS, use of these interventions is inconsistent, and patient mortality remains high. The impact of variability in center management practices on ARDS mortality rates remains unknown.

Research Question: What is the impact of treatment variability on mortality in patients with moderate to severe ARDS in the United States?

Study Design And Methods: We conducted a multicenter, observational cohort study of mechanically ventilated adults with ARDS and Pao to Fio ratio of ≤ 150 with positive end-expiratory pressure of ≥ 5 cm HO, who were admitted to 29 US centers between October 1, 2016, and April 30, 2017.

Survival models to support shared decision-making about advance care planning for people with advanced stage cystic fibrosis.

Background: For people with advanced stage cystic fibrosis (CF), tailored survival estimates could facilitate preparation for decision-making in the event of acutely deteriorating respiratory function.

Methods: We used the US CF Foundation national database (2008-2013) to identify adult people with incident advanced stage CF (forced expiratory volume in 1 s (FEV1) ≤45% predicted). Using the lasso method for variable selection, we divided the dataset into training and validation samples (2:1), and developed two multivariable Cox proportional hazards models to calculate probabilities of survival from baseline (T0 model), and from 1 year after (T12 model).