SynthesisAnaesthesia, critical care & pain medicine2021
Non-invasive oxygenation strategies for respiratory failure with COVID-19: A concise narrative review of literature in pre and mid-COVID-19 era.
Synthesis in Anaesthesia, critical care & pain medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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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
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 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
- Update on the management of acute respiratory failure using non-invasive ventilation and pulse oximetry.Critical care (London, England) · 2023Review
- Assessment of Procedural Pain in Patients with COVID-19 in the Intensive Care Unit.Pain management nursing : official journal of the American Society of Pain Management Nurses · 2022Article
- What is the most adequate non-invasive oxygen support for acute hypoxaemic respiratory failure due to COVID-19?Anaesthesia, critical care & pain medicine · 2021Article
- In-Hospital Mortality of COVID-19 Patients Treated with High-Flow Nasal Oxygen: Evaluation of Biomarkers and Development of the Novel Risk Score Model CROW-65.Life (Basel, Switzerland) · 2021Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The coronavirus disease 2019 (COVID-19) has spread globally and can cause a shortage of medical resources, in particular, mechanical ventilators. High-flow nasal cannula oxygen therapy (HFNC) and non-invasive positive pressure ventilation (NPPV) are frequently used for acute respiratory failure patients as alternatives to invasive mechanical ventilation. They are drawing attention because of a potential role to save mechanical ventilators. However, their effectiveness and risk of viral spread are unclear. The latest network meta-analysis of pre-COVID-19 trials reported that treatment with non-invasive oxygenation strategies was associated with improved survival when compared with conventional oxygen therapy. During the COVID-19 pandemic, a lot of clinical research on COVID-19 related acute respiratory failure has been reported. Several observational studies and small trials have suggested HFNC or NPPV as an alternative of standard oxygen therapy to manage COVID-19 related acute respiratory failure, provided that appropriate infection prevention is applied by health care workers to avoid risks of the virus transmission. Awake proning is an emerging strategy to optimise the management of patients with COVID-19 acute respiratory failure. However, the benefits of awake proning have yet to be assessed in properly designed clinical research. Although HFNC and NPPV are probably effective for acute respiratory failure, the safety data are mostly based on observational and experimental reports. As such, they should be implemented carefully if adequate personal protective equipment and negative pressure rooms are available.
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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.