| Literature DB >> 35420368 |
Tharwat Aisa1, Tidi Hassan2, Ehtesham Khan3, Khaled Algrni4, Muhammed Anwar Malik3.
Abstract
INTRODUCTION: Most of COVID-19 patients present with hypoxemic respiratory failure. Proning is one of the management options proven to improve oxygenation and reduce mortality in non-COVID-19-related acute respiratory distress syndrome. As a response to COVID-19 pandemic surge, a dedicated COVID-19 respiratory ward for the management of mild to moderate ARDS patients who require oxygen therapy, non-invasive ventilation (NIV), or high-flow nasal cannula (HFNC) was established. We adopted a policy of early awake proning in such patients. AIMS: To determine the physiological changes, improvement in oxygenation, the need for intubation, alongside with the duration, tolerance, and adverse effects of awake proning. STUDY DESIGN AND METHODS: Single-center, prospective observational cohort study. All awake, non-intubated, spontaneously breathing patients with COVID-19, and hypoxemic acute respiratory failure requiring oxygen supplementation, NIV, or HFEntities:
Keywords: ARDS; Awake proning; COVID19; Feasibility; Hypoxic respiratory failure
Year: 2022 PMID: 35420368 PMCID: PMC9008294 DOI: 10.1007/s11845-022-03009-7
Source DB: PubMed Journal: Ir J Med Sci ISSN: 0021-1265 Impact factor: 1.568
Baseline characteristics of the patients (n = 50)
| 56.20 (11.91) | |
| 29.46 (3.77) | |
| 8.5 (3.13) | |
| 1.57 (0.78) | |
| 23 (46%) | |
| 27 (54%) | |
| 18 (56%) | |
| 4 (8%) | |
| 6 (12%) | |
| 13 (26%) | |
| 2 (4%) | |
| 2 (4%) | |
| 7 (14%) | |
Data are presented as mean and standard deviation (SD)
BMI body mass index, COPD chronic obstructive pulmonary disease, n number
Effects of awake proning on physiological parameters and oxygenation
| 82% (IQR 72–85) | 93% (IQR 90–94) | 94% (IQR 90–95) | 0.0001 | |
| 10 (1.84) | 11 (1.18) | 11 (1.23) | 0.43 | |
| 38 (4.37) | 31 (4.84) | 30 (4.60) | < 0.0001 | |
| 0.90 (0.11) | 0.67 (0.12) | 0.62 (0.12) | < 0.0001 | |
| 85 (13.76) | 124 (34.08) | 138 (28.01) | < 0.0001 | |
| 132 (9.10) | 130 (7.44) | 129 (8.6) | 0.07 | |
| 71 (9.07) | 70 (6.70) | 69 (6.80) | 0.19 | |
| 100 (7.05) | 94 (8.86) | 93 (10.20) | < 0.0001 | |
| 22 | 20 | 11 | 0.49* |
ANOVA analysis with repeated measures was to assess the changes in parameters overtime. The significant level was set to 0.05
*The P-value is based on chi-square test
Data are presented as mean and standard deviation (SD) or median and interquartile (IQR)