Awake Intubation Techniques, and Why It Is Still an Important Skill to Master

Purpose of Review: Awake intubation has been a staple of difficult airway management since the first American Society of Anesthesiologists difficult airway guidelines were developed in the 1980s. In current anesthetic practice, use of second generation supraglottic airways and video laryngoscopy are ubiquitous. The goal of this review is to examine the impact that these airway advances have had on the use of awake intubation and the need to maintain this skill. Recent Findings: Despite advancements, evidence suggests that the rate of awake intubation has changed little over the last two decades. Recent literature has focused on the use of alternatives to the flexible intubation scope, including awake intubation with video laryngoscopy, combined video laryngoscopy-flexible intubation, and combined supraglottic airway-flexible intubation. Summary: Awake intubation remains an essential technique in airway management. Future research should focus on determining the specific patient populations that would benefit from the variety of awake intubation techniques now described.Copyright © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

The COVID-19 Pandemic Evolution in Hawai‘i and New Jersey: A Lesson on Infection Transmissibility and the Role of Human Behavior

In this chapter we analyze the evolution of the COVID-19 pandemic, with specific focus on the states of Hawai‘i and New Jersey. The two states represent extreme cases, with the archipelagos reachable mainly by flights thus a contained environment, while the garden state located between two metropolitan areas. Agent-based and compartmental models are discussed with focus on factors limiting the possibility of accurate predictions, such as the difficulty in fitting the parameters to the specific characteristics of the pandemic evolution. The main message is the importance of building comprehensive models, including representation of the effect of human behavior on transmissibility and the sociodemographic characteristic of the modeled population, collect reliable and accurate data, and the creation of teams including mathematician, social scientists, and public health and policy experts to build such models. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Sub-epidemic Model Forecasts During the First Wave of the COVID-19 Pandemic in the USA and European Hotspots

Mathematical models have been widely used to understand the dynamics of the ongoing coronavirus disease 2019 (COVID-19) pandemic as well as to predict future trends and assess intervention strategies. The asynchronicity of infection patterns during this pandemic illustrates the need for models that can capture dynamics beyond a single-peak trajectory to forecast the worldwide spread and for the spread within nations and within other sub-regions at various geographic scales. Here, we demonstrate a five-parameter sub-epidemic wave modeling framework that provides a simple characterization of unfolding trajectories of COVID-19 epidemics that are progressing across the world at different spatial scales. We calibrate the model to daily reported COVID-19 incidence data to generate six sequential weekly forecasts for five European countries and five hotspot states within the United States. The sub-epidemic approach captures the rise to an initial peak followed by a wide range of post-peak behavior, ranging from a typical decline to a steady incidence level to repeated small waves for sub-epidemic outbreaks. We show that the sub-epidemic model outperforms a three-parameter Richards model, in terms of calibration and forecasting performance, and yields excellent short- and intermediate-term forecasts that are not attainable with other single-peak transmission models of similar complexity. Overall, this approach predicts that a relaxation of social distancing measures would result in continuing sub-epidemics and ongoing endemic transmission. We illustrate how this view of the epidemic could help data scientists and policymakers better understand and predict the underlying transmission dynamics of COVID-19, as early detection of potential sub-epidemics can inform model-based decisions for tighter distancing controls. © 2022, Springer Nature Switzerland AG.

Mount sinai hospital institute for critical care medicine COVID-19 pandemic policies and procedures

INTRODUCTION: COVID-19 2020 pandemic with New York City (NYC) as the epicenter necessitated an unprecedented increase in critical care capacity and development of institutional guidelines for care. We describe our drastic increased ICU capacity and how we created and disseminated our guidelines. We hope our experiences help others manage their COVID-19 peaks. METHODS: Mount Sinai Hospital System includes a medical school and eight campuses, the largest being Mount Sinai Hospital (MSH). Since 2013, MSH had system-wide staffing models, cross credentialed staff, and combined leadership. MSH has and Institute for Critical Care Medicine (ICCM) that includes seven adult ICUs, 45 critical care faculty, rapid response team (RRT), vascular access team (VAS), difficult airway team (DART), patient safety quality team (PSQ), clinical research team, and post-ICU recovery clinic. ICCM coordinated COVID-19 critical care response within MSHS. ICCM, Emergency Medicine, Anesthesiology, and Infection Prevention helped develop systemwide guidelines on our COVID-19 website accessible to all hospital employees. RESULTS: MSH expanded from 1139-beds, 104 ICU beds, to 1453 beds, 235 ICU beds during the COVID-19 peak. CONCLUSIONS: MSH's response to COVID-19 surge by expanding critical care bed capacity from 104 to over 200 ICU beds required teamwork across disciplines. We developed new guidelines for airway management, cardiac arrest, anticoagulation, vascular access, and proning that helped streamline workflow and accommodate the surge in critically ill patients. Non-ICU services and staff were deployed to augment the critical care work force and open new critical care units by leveraging a tiered staffing model. This approach to rapidly expanding bed availability and staffing across the system was made possible by the collaboration between ICCM, emergency department, anesthesia department, and infection prevention, and helped to provide the best care for our patients and saved lives.

Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020.

The initial cluster of severe pneumonia cases that triggered the COVID-19 epidemic was identified in Wuhan, China in December 2019. While early cases of the disease were linked to a wet market, human-to-human transmission has driven the rapid spread of the virus throughout China. The Chinese government has implemented containment strategies of city-wide lockdowns, screening at airports and train stations, and isolation of suspected patients; however, the cumulative case count keeps growing every day. The ongoing outbreak presents a challenge for modelers, as limited data are available on the early growth trajectory, and the epidemiological characteristics of the novel coronavirus are yet to be fully elucidated. We use phenomenological models that have been validated during previous outbreaks to generate and assess short-term forecasts of the cumulative number of confirmed reported cases in Hubei province, the epicenter of the epidemic, and for the overall trajectory in China, excluding the province of Hubei. We collect daily reported cumulative confirmed cases for the 2019-nCoV outbreak for each Chinese province from the National Health Commission of China. Here, we provide 5, 10, and 15 day forecasts for five consecutive days, February 5th through February 9th, with quantified uncertainty based on a generalized logistic growth model, the Richards growth model, and a sub-epidemic wave model. Our most recent forecasts reported here, based on data up until February 9, 2020, largely agree across the three models presented and suggest an average range of 7409-7496 additional confirmed cases in Hubei and 1128-1929 additional cases in other provinces within the next five days. Models also predict an average total cumulative case count between 37,415 and 38,028 in Hubei and 11,588-13,499 in other provinces by February 24, 2020. Mean estimates and uncertainty bounds for both Hubei and other provinces have remained relatively stable in the last three reporting dates (February 7th - 9th). We also observe that each of the models predicts that the epidemic has reached saturation in both Hubei and other provinces. Our findings suggest that the containment strategies implemented in China are successfully reducing transmission and that the epidemic growth has slowed in recent days.