ABSTRACT
High flow nasal oxygen (HFNO) is proven to be effective in non-COVID-19 hypoxemic respiratory failure. In the beginning of the COVID-19 pandemic, HFNO was quickly introduced into daily clinical practice, although the evidence of its effectiveness in COVID-19 was limited. Randomized controlled trials suggest that HFNO has no effect on survival. However, HFNO may lead to less intubations in comparison with conventional oxygen therapy. The evidence of HFNO use in patients with do-not-intubate orders remains very limited. However, in these patients, improvement in comfort could be an important argument to start treatment with HFNO. Additional research is needed to make an evidence based consideration about the clinical use of HFNO in COVID-19 care.
ABSTRACT
Background: The COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among COVID-19 patients could assist decision making in the ICU setting. In this work, we report on the development and validation of a dynamic mortality model specifically for critically ill COVID-19 patients and discuss its potential utility in the ICU. Methods: We collected electronic medical record (EMR) data from 3222 ICU admissions with a COVID-19 infection from 25 different ICUs in the Netherlands. We extracted daily observations of each patient and fitted both a linear (logistic regression) and non-linear (random forest) model to predict mortality within 24 h from the moment of prediction. Isotonic regression was used to re-calibrate the predictions of the fitted models. We evaluated the models in a leave-one-ICU-out (LOIO) cross-validation procedure. Results: The logistic regression and random forest model yielded an area under the receiver operating characteristic curve of 0.87 [0.85; 0.88] and 0.86 [0.84; 0.88], respectively. The recalibrated model predictions showed a calibration intercept of -0.04 [-0.12; 0.04] and slope of 0.90 [0.85; 0.95] for logistic regression model and a calibration intercept of -0.19 [-0.27; -0.10] and slope of 0.89 [0.84; 0.94] for the random forest model. Discussion: We presented a model for dynamic mortality prediction, specifically for critically ill COVID-19 patients, which predicts near-term mortality rather than in-ICU mortality. The potential clinical utility of dynamic mortality models such as benchmarking, improving resource allocation and informing family members, as well as the development of models with more causal structure, should be topics for future research.
ABSTRACT
BACKGROUND: Concerns persist regarding the risk of airborne SARS-CoV-2 transmission by patients with COVID-19 on various modalities of oxygen therapy, such as high-flow nasal cannula (HFNC). AIM: We aimed to compare the presence of airborne RNA in air samples between groups of patients with COVID-19 on different oxygen-delivery systems. We also explored factors that were associated with SARS-CoV-2 RNA positivity in air samples. RESULTS: Air samples were positive for SARS-CoV-2 RNA in three of 39 patients (8%) on HFNC, 0 of 13 (0%) on masks, versus five of 20 (25%) on nasal cannula. Odds ratio for air sample positivity was 0.52 (95% confidence interval (CI) 0.11-2.34) when comparing HFNC vs non-HFNC group, and 5.78 (1.24-27.01) for nasal cannula vs non-nasal cannula group. Patients with positive air samples in comparison with those with negative air samples were sampled earlier after symptoms onset (median: 7 vs 10 days; P=0.04) and had lower Ct values of diagnostic nasopharyngeal samples (median: 22 vs 26; P=0.02). CONCLUSIONS: Air sample positivity was not related to oxygen support device but to viral load. These data suggest that the use of personal protection equipment should be based on risk management according to viral load rather than oxygen support device.
Subject(s)
COVID-19 , Cannula , Humans , Oxygen , RNA, Viral , SARS-CoV-2ABSTRACT
BACKGROUND: The initial aim was to study the effects of face masks worn by recently infected individuals on the airborne spread of SARS-CoV-2, but findings motivated us to proceed with comparing the presence of SARS-CoV-2 in air samples near infected individuals at home with those near infected intensive care unit (ICU) patients. AIM: To assess the presence of SARS-CoV-2 in the air of homes of infected individuals and in ICU rooms of critically ill patients with COVID-19 who were undergoing different forms of potential aerosol-generating medical procedures. METHODS: A high-volume air sampler method was developed that used a household vacuum cleaner with surgical face masks serving as sample filters. SARS-CoV-2 RNA was harvested from these filters and analysed by polymerase chain reaction. Fog experiments were performed to visualize the airflow around the air sampler. Air samples were acquired in close proximity of infected individuals, with or without wearing face masks, in their homes. Environmental air samples remote from these infected individuals were also obtained, plus samples near patients in the ICU undergoing potential aerosol-generating medical procedures. FINDINGS: Wearing a face mask resulted in a delayed and reduced flow of the fog into the air sampler. Face masks worn by infected individuals were found to contain SARS-CoV-2 RNA in 71% of cases. SARS-CoV-2 was detected in air samples regardless of mask experiments. The proportion of positive air samples was higher in the homes (29/41; 70.7%) than in the ICU (4/17; 23.5%) (P < 0.01). CONCLUSION: SARS-CoV-2 RNA could be detected in air samples by using a vacuum cleaner based air sampler method. Air samples in the home environment of recently infected individuals contained SARS-CoV-2 RNA nearly three times more frequently by comparison with those obtained in ICU rooms during potential aerosol-generating medical procedures.