ReviewJournal of personalized medicine2021
The Role of Noninvasive Respiratory Management in Patients with Severe COVID-19 Pneumonia.
Review in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Comparison between high-flow nasal cannula and noninvasive ventilation in COVID-19 patients: a systematic review and meta-analysis.Therapeutic advances in respiratory diseasePooled it
- Efficiency of continuous positive airway pressure and high-flow nasal oxygen therapy in critically ill patients with COVID-19.The Journal of international medical research · 2024Article
- Descriptive account of the first use of the LeVe CPAP System, a new frugal CPAP System, in adult patients with COVID-19 Pneumonitis in Uganda.Tropical medicine and health · 2023Article
- Environmental Contamination by SARS-CoV-2 During Noninvasive Ventilation in COVID-19.Respiratory care · 2023Observational
- Mallampati Score Is an Independent Predictor of Active Oxygen Therapy in Patients with COVID-19.Journal of clinical medicine · 2022Article
- Chest X-ray Does Not Predict the Risk of Endotracheal Intubation and Escalation of Treatment in COVID-19 Patients Requiring Noninvasive Respiratory Support.Journal of clinical medicine · 2022Article
- A breath of relief: High-flow nasal oxygen in a resource-limited setting.African journal of thoracic and critical care medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute hypoxemic respiratory failure is the principal cause of hospitalization, invasive mechanical ventilation and death in severe COVID-19 infection. Nearly half of intubated patients with COVID-19 eventually die. High-Flow Nasal Oxygen (HFNO) and Noninvasive Ventilation (NIV) constitute valuable tools to avert endotracheal intubation in patients with severe COVID-19 pneumonia who do not respond to conventional oxygen treatment. Sparing Intensive Care Unit beds and reducing intubation-related complications may save lives in the pandemic era. The main drawback of HFNO and/or NIV is intubation delay. Cautious selection of patients with severe hypoxemia due to COVID-19 disease, close monitoring and appropriate employment and titration of HFNO and/or NIV can increase the rate of success and eliminate the risk of intubation delay. At the same time, all precautions to protect the healthcare personnel from viral transmission should be taken. In this review, we summarize the evidence supporting the application of HFNO and NIV in severe COVID-19 hypoxemic respiratory failure, analyse the risks associated with their use and provide a path for their proper implementation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.