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Most impactful predictors for hyperoxaemia in exacerbation of chronic obstructive pulmonary disease managed by Emergency Medical Services and Emergency Department.
Clinical Respiratory Journal 2019 April
INTRODUCTION: Hyperoxemia in acute exacerbation of chronic obstructive pulmonary disease (AECOPD) leads to adverse outcomes. It remains prevalent in the pre-hospital Emergency Medical Services (EMS) and Emergency Department (ED).
OBJECTIVE: To determine the key predictors for hyperoxemia in AECOPD in EMS and ED.
METHODS: This was a prospective observational study of AECOPD patients in EMS and two EDs. Hyperoxemia was defined as PaO2 > 65 mm Hg (corresponds to SpO2 > 92%). We determined apriori candidate factors in Patient, Organization and Staff domains. Primary outcomes were the key predictors for hyperoxemia. Secondary outcomes were in-hospital mortality and mechanical ventilation rates in hyperoxemic versus non-hyperoxemic groups. We generated a logistic regression model for each domain. We reported the adjusted odds ratios (AORs), 95% CIs and p values. We selected the output factors using AOR ≥2.0 and ≥2.5 for modifiable and non-modifiable factors, respectively. These selected factors were fed into a final model with eventual factors selected based on: threshold AORs as stated above and/or 95% CIs including these AORs.
RESULTS: Three hundred and twenty-six patients were analysed; 60.7% had hyperoxemia. We found three eventual modifiable factors; first, ED SpO2 > 95% [AOR 2.62 (95% CIs: 1.61-4.33); P < 0.001], EMS non-rebreathing mask [AOR 2.01 (95% CIs: 1.06-3.97); P = 0.04]; and ED nasal cannula [AOR 1.69 (95% CIs: 1.05-2.72); P = 0.03]. Secondary outcomes did not differ between groups.
CONCLUSION: We identified three key modifiable predictors. We intend to conduct an interventional study using them to reduce hyperoxemia rate in AECOPD.
OBJECTIVE: To determine the key predictors for hyperoxemia in AECOPD in EMS and ED.
METHODS: This was a prospective observational study of AECOPD patients in EMS and two EDs. Hyperoxemia was defined as PaO2 > 65 mm Hg (corresponds to SpO2 > 92%). We determined apriori candidate factors in Patient, Organization and Staff domains. Primary outcomes were the key predictors for hyperoxemia. Secondary outcomes were in-hospital mortality and mechanical ventilation rates in hyperoxemic versus non-hyperoxemic groups. We generated a logistic regression model for each domain. We reported the adjusted odds ratios (AORs), 95% CIs and p values. We selected the output factors using AOR ≥2.0 and ≥2.5 for modifiable and non-modifiable factors, respectively. These selected factors were fed into a final model with eventual factors selected based on: threshold AORs as stated above and/or 95% CIs including these AORs.
RESULTS: Three hundred and twenty-six patients were analysed; 60.7% had hyperoxemia. We found three eventual modifiable factors; first, ED SpO2 > 95% [AOR 2.62 (95% CIs: 1.61-4.33); P < 0.001], EMS non-rebreathing mask [AOR 2.01 (95% CIs: 1.06-3.97); P = 0.04]; and ED nasal cannula [AOR 1.69 (95% CIs: 1.05-2.72); P = 0.03]. Secondary outcomes did not differ between groups.
CONCLUSION: We identified three key modifiable predictors. We intend to conduct an interventional study using them to reduce hyperoxemia rate in AECOPD.
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