Importance: Initial guidelines recommended prompt endotracheal intubation rather than non-invasive ventilation (NIV) for COVID-19 patients requiring ventilator support. There is insufficient data comparing the impact of intubation versus NIV on patient-centered outcomes of these patients.
Objective: To compare all-cause 30-day mortality for hospitalized COVID-19 patients with respiratory failure who underwent intubation first, intubation after NIV, or NIV only.
Design: Retrospective study of patients admitted in March and April of 2020.
Setting: A teaching hospital in Brooklyn, New York City.
Participants: Adult COVID-19 confirmed patients who required ventilator support (non-invasive ventilation and/or endotracheal intubation) at discretion of treating physician, were included.
Exposures: Patients were categorized into three exposure groups: intubation-first, intubation after NIV, or NIV-only.
Primary Outcome: 30-day all-cause mortality, a predetermined outcome measured by multivariable logistic regression. Data are presented with medians and interquartile ranges, or percentages with 95% confidence intervals, for continuous and categorical variables, respectively. Covariates for the model were age, sex, qSOFA score ≥ 2, presenting oxygen saturation, vasopressor use, and greater than three comorbidities. A secondary multivariable model compared mortality of all patients that received NIV (intubation after NIV and NIV-only) with the intubation-first group.
Results: A total of 222 were enrolled. Overall mortality was 77.5% (95%CI, 72-83%). Mortality for intubation-first group was 82% (95%CI, 73-89%; 75/91), for Intubation after NIV was 84% (95%CI, 70-92%; 37/44), and for NIV-only was 69% (95%CI, 59-78%; 60/87). In multivariable analysis, NIV-only was associated with decreased all-cause mortality (odds ratio [OR]: 0.30, 95%CI, 0.13-0.69). No difference in mortality was observed between intubation-first and intubation after NIV. Secondary analysis found all patients who received NIV to have lower mortality than patients who were intubated only (OR: 0.44, 95%CI, 0.21-0.95).
Conclusions & Relevance: Utilization of NIV as the initial intervention in COVID-19 patients requiring ventilatory support is associated with significant survival benefit. For patients intubated after NIV, the mortality rate is not worse than those who undergo intubation as their initial intervention.
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http://dx.doi.org/10.1016/j.ajem.2021.01.068 | DOI Listing |
Med Intensiva (Engl Ed)
January 2025
Intensive Care Unit, Hospital Universitario Doctor Peset, Av Gaspar Aguilar 90, 46017 Valencia, Spain.
Objective: We aimed to determine predictors of non-invasive ventilation (NIV) failure and validate a nomogram to identify patients at risk of NIV failure.
Design: Observational, analytical study of a retrospective cohort from a single center, compared with an external cohort (March 2020 to August 2021).
Setting: Two intensive care units (ICUs).
Med Intensiva (Engl Ed)
January 2025
Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam Public Health, Amsterdam Cardiovascular Science, Amsterdam Institute for Infection and Immunity, Amsterdam UMC, University of Amsterdam, Vrije Universiteit, Amsterdam, The Netherlands.
Objective: To determine whether the ROX index and its variations can predict the risk of intubation in ICU patients receiving NIV ventilation using large public ICU databases.
Design: Retrospective observational cohort study.
Setting: Patient data was extracted from both the AmsterdamUMCdb and the MIMIC-IV ICU databases, which contained data related to 20,109 and 50,920 unique patients.
Semin Perinatol
December 2024
Department of Women and Children's Health, School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom; Neonatal Intensive Care Unit, University of Patras, Patras, Greece. Electronic address:
Non-invasive ventilation (NIV) is a form of respiratory support provided primarily to preterm born infants in an effort to avoid any endotracheal intubation or as a weaning step following invasive ventilation. In the context of the respiratory distress syndrome of the newborn, NIV could target and partially reverse specific pathophysiological phenomena, by improving alveolar recruitment and establishing adequate functional residual capacity. It can also assist in minimizing lung injury by avoiding excessive pressure delivery, which can be harmful for the developing lung.
View Article and Find Full Text PDFPediatr Neonatol
December 2024
Department of Pediatrics, Faculty of Medicine, University of Medicine and Pharmacy at Ho Chi Minh City, 217 Hong Bang Street District 5, Ho Chi Minh City, 700000, Viet Nam; University Medical Center Ho Chi Minh City, 215 Hong Bang Street District 5, Ho Chi Minh City, 700000, Viet Nam; Neonatal Intensive Care Unit, Children's Hospital 2, 14 Ly Tu Trong Street District 1, Ho Chi Minh City, 700000, Viet Nam. Electronic address:
Background: Invasive mechanical ventilation in very-low-birth-weight infants (VLBWI) was associated with immediate and long-term complications. Nasal high-frequency oscillation (nHFO) has recently become a new non-invasive ventilation (NIV) mode for treating respiratory failure in VLBWI. This study aimed to investigate the safety and efficacy of nHFO as an alternative respiratory support to prevent intubation in VLBWI.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, and Vascular Sciences and Public Health, University of Padova, Via Loredan 18, 35131 Padova, Italy.
: Non-invasive ventilation (NIV) has emerged as a possible first-step treatment to avoid invasive intubation in pediatric intensive care units (PICUs) due to its advantages in reducing intubation-associated risks. However, the timely identification of NIV failure is crucial to prevent adverse outcomes. This study aims to identify predictors of first-attempt NIV failure in PICU patients by testing various machine learning techniques and comparing their predictive abilities.
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