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Introduction The number of subjects infected with the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the western hemisphere increased exponentially in the later months of 2020. With this increase in infection, the number of subjects requiring advanced ventilatory support increased concomitantly. We decided to compare the survival rates between coronavirus disease 2019 (COVID-19) subjects versus non-COVID-19 subjects undergoing intubation in the intensive care unit (ICU). We hypothesized that COVID-19 subjects would have lower rates of survival post-intubation. Methods We screened all subjects admitted to the adult critical care unit between January 2020 and June 2020 to determine if they met the inclusion criteria. These subjects were required to be spontaneously ventilating upon admission and eventually required intubation. Subjects were selected from our electronic health record (EHR) system EPIC© (Epic Systems, Verona, WI) through a retrospective ICU admission analysis. We identified and included 267 non-COVID-19 subjects and 56 COVID-19 subjects. Our primary outcome of interest was intubation-related mortality. We defined intubation mortality as unexpected death (within 48 hours of intubation). Our secondary outcomes were the length of stay in the ICU, length of time requiring ventilator support, and proportion of subjects requiring tracheostomy placement. Results Compared to non-coronavirus disease (COVID) subjects, COVID subjects were more likely to be intubated for acute respiratory distress. COVID subjects had longer stays in the ICU and longer ventilator duration than non-COVID subjects. COVID-positive subjects had a decreased hazard ratio for mortality (HR = 0.42, 95% CI: 0.20-0.87, P < 0.05) and increased chances of survival compared to non-COVID subjects. Conclusions We showed the rates of intubation survival were no different between the COVID and non-COVID groups. We attribute this finding to intubation preparation, a multidisciplinary team approach, and having the most experienced provider lead the intubation process.

BACKGROUND: The primary objective of this study was to employ a national database to evaluate the association of hospital urbanicity, urban versus rural, on mortality and length of hospital stay in patients hospitalized with acute respiratory failure. METHODS: We used the 2014 National Inpatient Sample database to evaluate the association of hospital urbanicity with (1) mortality and (2) prolonged hospital stay, defined as ≥ 75th percentile of the study population. We conducted a mixed-effects logistic regression analysis adjusting for sociodemographic variables and medical comorbidities. The random effect was hospital identification number (a unique value assigned in the NIS database for a specific institution). The odds ratio (OR), 95% CI, and P values were reported for each independent variable. RESULTS: The odds of inpatient mortality were significantly higher among urban teaching (OR 1.39, 95% CI 1.39-1.66, P < .001) and urban nonteaching hospitals (OR = 1.39, 95% CI 1.26-1.52, P < .001) compared to rural hospitals. The odds of prolonged hospital stay were significantly higher among urban teaching (OR = 1.82, 95% CI 1.66-2.0, P < .001) and urban nonteaching compared to rural hospitals (OR = 1.50, 95% CI 1.36-1.65, P < .001). CONCLUSIONS: This study supports the current body of literature that there are significant differences in patient populations among hospital type. Differences in health outcomes among different types of hospitals should be considered when designing policies to address health equity as these are unique populations with specific needs.

In 2019, a novel coronavirus called the severe acute respiratory syndrome coronavirus 2 led to the outbreak of the coronavirus disease 2019, which was deemed a pandemic by the World Health Organization in March 2020. Owing to the accelerated rate of mortality and utilization of hospital resources, health care systems had to adapt to these major changes. This affected patient care across all disciplines and specifically within the perioperative services. In this review, we discuss the strategies and pitfalls of how perioperative services in a large academic medical center responded to the initial onset of a pandemic, adjustments made to airway management and anesthesia specialty services - including critical care medicine, obstetric anesthesiology, and cardiac anesthesiology - and strategies for reopening surgical caseload during the pandemic.

PurposeSepsis remains amongst the most common causes of death worldwide. It has been described as a disease of the elderly, but contemporary data on risk factors and mortality is lacking.Materials and methodsMulti-center longitudinal cohort study using non-public, state of California data from January 1, 2008 to September 31, 2015. Patients with sepsis, severe sepsis, and septic shock were identified using ICD-9-CM diagnosis and procedure codes with age subgroups of 18-44, 45-64, 65-74, 75-84, and >85 years old. Descriptive statistics and a single direct logistic regression model were used to present data on incidence and mortality and to identify independent factors associated with mortality.ResultsOf 30,282,159 total inpatient encounters, 20,358,569 met inclusion criteria and 1,566,306 met sepsis criteria. Conditions associated with mortality included metastatic cancer, age, liver disease, residing in a care facility, and a gastrointestinal source of infection as well as fungal infection. Mortality in the >85-year-old subgroup with septic shock was 45.7%, lower than previously reported.ConclusionAge remains an important sepsis risk factor, but other conditions correlated more closely with sepsis-associated death. Patients over 85 years of age suffering from septic shock may have a better chance of survival than previously thought.

BackgroundDespite improvements in techniques and management of liver transplant patients, numerous perioperative complications that contribute to perioperative mortality remain. Models to predict intraoperative massive blood transfusion, prolonged mechanical ventilation, or in-hospital mortality in liver transplant recipients have not been identified. In this study we aim to identify preoperative factors associated with the above mentioned complications.MethodsA retrospective observational analysis was conducted on data collected from 124 orthotopic liver transplants performed at a single institution between 2014 and 2017. A multivariable logistic regression using backwards elimination was performed for three defined outcomes (massive transfusion ≥ 10 units packed red blood cells (PRBC), prolonged mechanical ventilation > 24 h, and in-hospital mortality) to identify associations with preoperative characteristics.ResultsStatistically significant (P < 0.05) associations with massive transfusion ≥ 10 units PRBC were hepatocellular carcinoma and preoperative transfusion of PRBC. Significant associations with prolonged mechanical ventilation > 24 h were hepatitis C, alcoholic hepatitis, elevated preoperative ALT, and hepatorenal syndrome. Male gender was protective for requiring prolonged mechanical ventilation. End-stage renal disease and hepatitis B were significantly associated with increased in-hospital mortality.ConclusionsThis study identified risk factors associated with common perioperative complications of liver transplantation. These factors may assist practitioners in risk stratification and may form the basis for further investigations of potential interventions to mitigate these risks.

Open Hardware-based microcontrollers, especially the Arduino platform, have become a comparably easy-to-use tool for rapid prototyping and implementing creative solutions. Such devices in combination with dedicated front-end electronics can offer low-cost alternatives for student projects, slow control and independently operating small-scale instrumentation. The capabilities can be extended to data taking and signal analysis at mid-level rates. Two detector realizations are presented, which cover the readouts of proportional counter tubes and of scintillators or wavelength-shifting fibers with silicon photomultipliers (SiPMs). The SiPMTrigger realizes a small-scale design for coincidence readout of SiPMs as a trigger or veto detector. It consists of a custom mixed signal front-end board featuring signal amplification, discrimination and a coincidence unit for rates of up to 200 kHz. The nCatcher transforms an Arduino Nano to a proportional counter readout with pulse shape analysis: time over threshold measurement and a 10-bit analog-to-digital converter for pulse heights. The device is suitable for low-to-medium-rate environments up to 5 kHz, where a good signal-to-noise ratio is crucial. We showcase the monitoring of thermal neutrons. For data taking and slow control, a logger board is presented that features an SD card and GSM/LoRa interface. [ABSTRACT FROM AUTHOR]