Critical Care Staffing in Pandemics and Disasters: A Consensus Report From a Subcommittee of the Task Force for Mass Critical Care - Systems Strategies to Sustain the Health Care Workforce.

Background: The COVID-19 pandemic has led to unprecedented mental health disturbances, burnout, and moral distress among health care workers, affecting their ability to care for themselves and their patients.

Research Question: In health care workers, what are key systemic factors and interventions impacting mental health and burnout?

Study Design And Methods: The Workforce Sustainment subcommittee of the Task Force for Mass Critical Care (TFMCC) utilized a consensus development process, incorporating evidence from literature review with expert opinion through a modified Delphi approach to determine factors affecting mental health, burnout, and moral distress in health care workers, to propose necessary actions to help prevent these issues and enhance workforce resilience, sustainment, and retention.

Results: Consolidation of evidence gathered from literature review and expert opinion resulted in 197 total statements that were synthesized into 14 major suggestions.

Telemedicine to Expand Access to Critical Care Around the World.

This multiauthored communication gives a state-of-the-art global perspective on the increasing adoption of tele-critical care. Exponentially increasing sophistication in the deployment of Computers, Information, and Communication Technology has ensured extending the reach of limited intensivists virtually and reaching the unreached. Natural disasters, COVID-19 pandemic, and wars have made tele-intensive care a reality.

Interfacility Transport of Critically Ill Patients.

Objectives: To assess recent advances in interfacility critical care transport.

Data Sources: PubMed English language publications plus chapters and professional organization publications.

Study Selection: Manuscripts including practice manuals and standard (1990-2021) focused on interfacility transport of critically ill patients.

Assessment of a Comparative Bayesian-Enhanced Population-Based Decision Model for COVID-19 Critical Care Prediction in the Dominican Republic Social Security Affiliates.

Introduction: The novel coronavirus disease 2019 (COVID-19) has been a major health concern worldwide. This study aims to develop a Bayesian model to predict critical outcomes in patients with COVID-19.

Methods: Sensitivity and specificity were obtained from previous meta-analysis studies.

Prehospital Mechanical Ventilation: An NAEMSP Position Statement and Resource Document.

Airway emergencies and respiratory failure frequently occur in the prehospital setting. Patients undergoing advanced airway management customarily receive manual ventilations. However, manual ventilation is associated with hypo- and hyperventilation, variable tidal volumes, and barotrauma, among other potential complications.

Seroprevalence of Specific Antibodies against SARS-CoV-2 from Hotspot Communities in the Dominican Republic.

Seroprevalence surveys are of utmost importance to assess the proportion of a population that has developed antibodies against a newly introduced virus and could therefore potentially exhibit immunologic protection against subsequent infection. This study aims to understand the distribution of IgM and IgG antibodies in the Dominican Republic. We surveyed a total of 12,897 participants between April and June 2020 in 10 provinces of the Dominican Republic.

Clinical validation demonstrates concordance of qSOFA and POC lactate Bayesian model: Results from the ACDC Phase-2 program.

Unlabelled: Sepsis is a common and lethal medical problem. The objective of this study was to validate a Bayesian Model that integrates qSOFA and prehospital Lactate, with a comparison analysis from a real clinical data of patients with sepsis.

Methods: We conducted a two tired validation study with one arm focusing on Bayesian modeling and a second retrospective observational arm addressing real data validation.

A dignitary medicine curriculum developed using a modified Delphi methodology.

Background: Dignitary medicine is an emerging field of training that involves the specialized care of diplomats, heads of state, and other high-ranking officials. In an effort to provide guidance on training in this nascent field, we convened a panel of experts in dignitary medicine and using the Delphi methodology, created a consensus curriculum for training in dignitary medicine.

Methods: A three-round Delphi consensus process was performed with 42 experts in the field of dignitary medicine.

A Bayesian decision support sequential model for severity of illness predictors and intensive care admissions in pneumonia.

Background: Community-acquired pneumonia (CAP) is one of the leading causes of morbidity and mortality in the USA. Our objective was to assess the predictive value on critical illness and disposition of a sequential Bayesian Model that integrates Lactate and procalcitonin (PCT) for pneumonia.

Methods: Sensitivity and specificity of lactate and PCT attained from pooled meta-analysis data.

Latin America intensive care unit disaster preparedness: Results from a web-based attitudes and perceptions survey.

Background: Disasters burden on hospital emergency intensive care units (ICUs). This burden is increased in Latin America (LATAM) where hospital resources, intrahospital disaster simulations, and perceived level of preparedness vary greatly among different communities. The objective of the study was to assess LATAM ICU leaders' knowledge and attitudes regarding disaster preparedness.

Natural Disasters.

Natural disasters are extreme events generally caused by abrupt climate change and other environmental factors. Intensive care units (ICUs) need to be prepared, because in the event of a natural disaster, the number of patients that require service stresses an already occupied facility. It is critical that personnel be able to do a proper ICU triage.

Development of multiple organ dysfunction syndrome in older and young adult trauma patients.

Objective: We sought out to determine the correlation between the injury severity score (ISS) and multiple organ dysfunction syndrome (MODS) between severely injured young adults (18-54 years) and elderly (>55 years) patients.

Materials And Methods: This was a cross-sectional observational study. We included all adult cases (>18 years) diagnosed with trauma defined by the International Classification of Diseases, Ninth Revision.

The acute care diagnostics collaboration: Performance assessment of contrast-enhanced ultrasound compared to abdominal computed tomography and conventional ultrasound in an emergency trauma score bayesian clinical decision scheme.

Background: Bayes' theorem describes the probability of an event, based on conditions that might be related to the event.[1] We developed the Bayesian Diagnostic Gains (BDG) method as a simple tool for interpreting diagnostic impact.[234567].

Racial and gender disparities in violent trauma: Results from the NEMSIS database.

Background: Barriers to EMS care can result in suboptimal outcomes and preventable morbidity and mortality. Large EMS databases such as the National Emergency Medical Services Information System (NEMSIS) dataset provide valuable data on the relative incidence of such barriers to care.

Methods: A retrospective cross-sectional analysis was performed using the NEMSIS database.

A Descriptive Analysis of Traction Splint Utilization and IV Analgesia by Emergency Medical Services.

Unlabelled: Study Objectives Traction splinting has been the prehospital treatment of midshaft femur fracture as early as the battlefield of the First World War (1914-1918). This study is the assessment of these injuries and the utilization of a traction splint (TS) in blunt and penetrating trauma, as well as intravenous (IV) analgesia utilization by Emergency Medical Services (EMS) in Miami, Florida (USA).

Methods: This is a retrospective study of patients who sustained a midshaft femur fracture in the absence of multiple other severe injuries or severe physiologic derangement, as defined by an injury severity score (ISS) <20 and a triage revised trauma score (T-RTS)≥10, who presented to an urban, Level 1 trauma center between September 2008 and September 2013.

Incremental diagnostic quality gain of CTA over V/Q scan in the assessment of pulmonary embolism by means of a Wells score Bayesian model: results from the ACDC collaboration.

Objective: Our objective was to evaluate the diagnostic value of computed tomography angiography (CTA) and ventilation perfusion (V/Q) scan in the assessment of pulmonary embolism (PE) by means of a Bayesian statistical model.

Methods: Wells criteria defined pretest probability. Sensitivity and specificity of CTA and V/Q scan for PE were derived from pooled meta-analysis data.

Acute Care Diagnostic Collaboration: Bayesian modeling comparative diagnostic assessment of lactate, procalcitonin and CRP in risk stratified population by Mortality in ED (MEDS) score.

Objective: To assess and compare the diagnostic value of lactate, procalcitonin (PCT) and C-reactive protein (CRP) in low, moderate, and high-risk stratified population applying Mortality in Emergency Department (MEDS) risk score using Bayesian statistical modeling.

Methods: MEDS criteria was used to risk stratify into low, moderate and high risk. Each population was attributed a percentage risk, and used as pre-test probability in the Bayesian nomogram.

Bayesian comparative assessment of diagnostic accuracy of low-dose CT scan and ultrasonography in the diagnosis of urolithiasis after the application of the STONE score.

Objective: The objective of our study was to assess the diagnostic quality of low-dose computed tomography (CT) when compared to ultrasound (US) in diagnosis of urolithiasis using STONE score as a predictor of pre-test probability and the Bayesian statistical model to calculate post-test probabilities (POST) for both diagnostic tests.

Methods: STONE score was used to form risk groups to obtain pre-test probabilities. Likelihood ratios (LR) were calculated from external data for low-dose CT and US.

Improved rule-out diagnostic gain with a combined aortic dissection detection risk score and D-dimer Bayesian decision support scheme.

Unlabelled: The objective of this study was to develop a Bayesian clinical decision support mathematical model that can assist in assessing a diagnostic utility integrating the aortic dissection detection risk score (ADD-RS) combined with the diagnostic quality of D-dimer testing.

Methods: Our method uses the Bayes nomogram. Pretest probability scoring for the ADD-RS was obtained using their derived precalculated effects models.

Bayesian comparative model of CT scan and ultrasonography in the assessment of acute appendicitis: results from the Acute Care Diagnostic Collaboration project.

The objective of this study was to develop a comparative diagnostic model for computed tomography (CT) and ultrasound (US) in the assessment of acute appendicitis using Alvarado risk score as a predictor of pretest probability and Bayesian statistical model as a tool to calculate posttest probabilities for both diagnostic test. Stratification was made by applying the Alvarado score for the prediction of acute appendicitis. Likelihood ratios were calculated using sensitivity and specificity of both CT and US from a Meta-analysis.

Acute Care Diagnostics Collaboration: Assessment of a Bayesian clinical decision model integrating the Prehospital Sepsis Score and point-of-care lactate.

Unlabelled: Previous research demonstrated that shock index and respiratory rate are highly predictive of intensive care unit admissions.

Objective: The objective of the study is to evaluate the integration of the prehospital sepsis project score (PSP-S) and point-of-care lactate in assisting prediction of severity of illness using Bayesian statistical modeling.

Methods: The PSP-S incorporates fever (38°C [100.