Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 5 de 5
Filter
1.
Eur Arch Otorhinolaryngol ; 278(6): 1869-1877, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1233255

ABSTRACT

PURPOSE: To provide a novel solution to reduce aerosol exposure in the operating room during endoscopic sinus and skull base procedures in the COVID-19 era. METHODS: We have designed a 3D printable midfacial mask that partially seals the nose, while allowing instrumentation during endoscopic transnasal surgery. The mask when connected to a vacuum system creates a constant negative pressure inside it, sucking out aerosols and gases generated during surgical procedures. Its effectiveness was tested using vapour exhalations by a human volunteer and drilling bone in a head model. The physical barrier effect was measured using fluorescein atomization in a head model. RESULTS: The pressure and airflow measured remained negative inside it in all the different situations tested. The mask was capable of completely evacuating human adult exhalation, and was more effective than the hand suction instrument. However, it was as effective as hand suction instrument at preventing aerosol spread from bone drilling. The physical barrier effect achieved a 72% reduction in the splatter created from the fluorescein atomization. CONCLUSIONS: The mask effectively prevented the spread of aerosols and reduced droplet spread during simulated transnasal endoscopic skull base surgery in laboratory conditions. This device has potential benefits in protecting surgical personnel against airborne transmission of COVID-19 and could be useful in reducing chronic exposure to the hazard of surgical smoke.


Subject(s)
COVID-19 , Aerosols , Endoscopy , Humans , SARS-CoV-2 , Skull Base/surgery
2.
Environ Res ; 197: 111096, 2021 06.
Article in English | MEDLINE | ID: covidwho-1163738

ABSTRACT

This study is motivated by the amplified transmission rates of the SAR-CoV-2 virus in areas with high concentrations of fine particulates (PM2.5) as reported in northern Italy and Mexico. To develop a deeper understanding of the contribution of PM2.5 in the propagation of the SAR-CoV-2 virus in the population, the deposition patterns and efficiencies (DEs) of PM2.5 laced with the virus in healthy and asthmatic airways are studied. Physiologically correct 3-D models for generations 10-12 of the human airways are applied to carry out a numerical analysis of two-phase flow for full breathing cycles. Two concentrations of PM2.5 are applied for the simulation, i.e., 30 µg⋅m-3 and 80 µg⋅m-3 for three breathing statuses, i.e., rest, light exercise, and moderate activity. All the PM2.5 injected into the control volume is assumed to be 100% contaminated with the SAR-CoV-2 virus. Skewed air-flow phenomena at the bifurcations are proportional to the Reynolds number at the inlet, and their intensity in the asthmatic airway exceeded that of the healthy one. Upon exhalation, two peak air-flow vectors from daughter branches combine to form one big vector in the parent generation. Asthmatic airway models has higher deposition efficiencies (DEs) for contaminated PM2.5 as compared to the healthy one. Higher DEs arise in the asthmatic airway model due to complex secondary flows which increase the impaction of contaminated PM2.5 on airways' walls.


Subject(s)
Asthma , Lung , Computer Simulation , Humans , Italy , Mexico , Models, Biological , Particulate Matter/toxicity
3.
Proc Natl Acad Sci U S A ; 118(8)2021 02 23.
Article in English | MEDLINE | ID: covidwho-1075324

ABSTRACT

COVID-19 transmits by droplets generated from surfaces of airway mucus during processes of respiration within hosts infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. We studied respiratory droplet generation and exhalation in human and nonhuman primate subjects with and without COVID-19 infection to explore whether SARS-CoV-2 infection, and other changes in physiological state, translate into observable evolution of numbers and sizes of exhaled respiratory droplets in healthy and diseased subjects. In our observational cohort study of the exhaled breath particles of 194 healthy human subjects, and in our experimental infection study of eight nonhuman primates infected, by aerosol, with SARS-CoV-2, we found that exhaled aerosol particles vary between subjects by three orders of magnitude, with exhaled respiratory droplet number increasing with degree of COVID-19 infection and elevated BMI-years. We observed that 18% of human subjects (35) accounted for 80% of the exhaled bioaerosol of the group (194), reflecting a superspreader distribution of bioaerosol analogous to a classical 20:80 superspreader of infection distribution. These findings suggest that quantitative assessment and control of exhaled aerosol may be critical to slowing the airborne spread of COVID-19 in the absence of an effective and widely disseminated vaccine.


Subject(s)
COVID-19/physiopathology , COVID-19/transmission , Exhalation/physiology , Obesity/physiopathology , Aerosols , Age Factors , Animals , Body Mass Index , COVID-19/epidemiology , COVID-19/virology , Cohort Studies , Humans , Mucus/chemistry , Mucus/virology , Obesity/epidemiology , Obesity/virology , Particle Size , Primates , Respiratory System/metabolism , SARS-CoV-2/isolation & purification , Viral Load
4.
Mod Pathol ; 34(3): 522-531, 2021 03.
Article in English | MEDLINE | ID: covidwho-872673

ABSTRACT

Coronavirus disease 2019 (COVID-19) is a novel disease resulting from infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has quickly risen since the beginning of 2020 to become a global pandemic. As a result of the rapid growth of COVID-19, hospitals are tasked with managing an increasing volume of these cases with neither a known effective therapy, an existing vaccine, nor well-established guidelines for clinical management. The need for actionable knowledge amidst the COVID-19 pandemic is dire and yet, given the urgency of this illness and the speed with which the healthcare workforce must devise useful policies for its management, there is insufficient time to await the conclusions of detailed, controlled, prospective clinical research. Thus, we present a retrospective study evaluating laboratory data and mortality from patients with positive RT-PCR assay results for SARS-CoV-2. The objective of this study is to identify prognostic serum biomarkers in patients at greatest risk of mortality. To this end, we develop a machine learning model using five serum chemistry laboratory parameters (c-reactive protein, blood urea nitrogen, serum calcium, serum albumin, and lactic acid) from 398 patients (43 expired and 355 non-expired) for the prediction of death up to 48 h prior to patient expiration. The resulting support vector machine model achieved 91% sensitivity and 91% specificity (AUC 0.93) for predicting patient expiration status on held-out testing data. Finally, we examine the impact of each feature and feature combination in light of different model predictions, highlighting important patterns of laboratory values that impact outcomes in SARS-CoV-2 infection.


Subject(s)
Blood Chemical Analysis , COVID-19/diagnosis , COVID-19/mortality , Decision Support Techniques , Support Vector Machine , Biomarkers/blood , COVID-19/blood , Humans , Predictive Value of Tests , Prognosis , Reproducibility of Results , Retrospective Studies , Risk Assessment , Risk Factors
5.
J Med Internet Res ; 22(9): e23565, 2020 09 25.
Article in English | MEDLINE | ID: covidwho-801719

ABSTRACT

BACKGROUND: Northwell Health, an integrated health system in New York, has treated more than 15,000 inpatients with COVID-19 at the US epicenter of the SARS-CoV-2 pandemic. OBJECTIVE: We describe the demographic characteristics of patients who died of COVID-19, observation of frequent rapid response team/cardiac arrest (RRT/CA) calls for non-intensive care unit (ICU) patients, and factors that contributed to RRT/CA calls. METHODS: A team of registered nurses reviewed the medical records of inpatients who tested positive for SARS-CoV-2 via polymerase chain reaction before or on admission and who died between March 13 (first Northwell Health inpatient expiration) and April 30, 2020, at 15 Northwell Health hospitals. The findings for these patients were abstracted into a database and statistically analyzed. RESULTS: Of 2634 patients who died of COVID-19, 1478 (56.1%) had oxygen saturation levels ≥90% on presentation and required no respiratory support. At least one RRT/CA was called on 1112/2634 patients (42.2%) at a non-ICU level of care. Before the RRT/CA call, the most recent oxygen saturation levels for 852/1112 (76.6%) of these non-ICU patients were at least 90%. At the time the RRT/CA was called, 479/1112 patients (43.1%) had an oxygen saturation of <80%. CONCLUSIONS: This study represents one of the largest reviewed cohorts of mortality that also captures data in nonstructured fields. Approximately 50% of deaths occurred at a non-ICU level of care despite admission to the appropriate care setting with normal staffing. The data imply a sudden, unexpected deterioration in respiratory status requiring RRT/CA in a large number of non-ICU patients. Patients admitted at a non-ICU level of care suffered rapid clinical deterioration, often with a sudden decrease in oxygen saturation. These patients could benefit from additional monitoring (eg, continuous central oxygenation saturation), although this approach warrants further study.


Subject(s)
Coronavirus Infections/mortality , Demography , Pneumonia, Viral/mortality , Adult , Aged , Aged, 80 and over , Betacoronavirus , COVID-19 , Cohort Studies , Female , Heart Arrest/epidemiology , Heart Arrest/mortality , Hospital Mortality , Hospital Rapid Response Team , Hospitalization/statistics & numerical data , Humans , Inpatients/statistics & numerical data , Intensive Care Units , Male , Medical Records , Middle Aged , New York/epidemiology , Oxygen/metabolism , Pandemics , SARS-CoV-2 , Young Adult
SELECTION OF CITATIONS
SEARCH DETAIL