Nebulizer versus metered dose inhaler with space chamber (MDI spacer) for acute asthma and chronic obstructive pulmonary disease exacerbation: attitudes of patients and healthcare providers in the COVID-19 era.

OBJECTIVE: Short-acting bronchodilators for asthma and chronic obstructive pulmonary disease (COPD) exacerbations are commonly delivered by nebulizers although administration using metered dose inhaler with space chamber (MDI spacer) has been shown to be equally efficacious. There are few studies examining patients' and healthcare providers' attitudes on the two administration methods in adults. This study explores patients' and healthcare providers' attitudes on the use of nebulizer versus MDI spacer for acute asthma and COPD exacerbations in adults.Methods: Patients admitted for asthma or COPD exacerbations, doctors, and nurses in a university-affiliated hospital were surveyed from 1 April 2021 to 30 September 2021 regarding their views on the effectiveness, ease of use, preparation and administration, side effects, and infection risk of the two administration methods. RESULTS: Ninety-nine patients, 103 doctors, and 650 nurses completed the survey. 60.6% of patients perceived nebulizer to be more effective. Patients who found nebulizer more comfortable were more likely to prefer nebulizer (OR 43.97, p = 0.01), while those who associated it with a greater infection risk were less likely to prefer nebulizer (OR 0.15, p = 0.03). 49.5% of doctors and 49.1% of nurses perceived nebulizer to be more effective, compared to 10.7% and 34.5%, respectively, for MDI spacer. Effectiveness and patient comfort influenced doctors' and nurses' preference for nebulizer while ease of preparation and administration influenced nurses' preference only. CONCLUSIONS: Patients and healthcare providers perceived nebulizer to be more effective. Factors unique to each group influenced their preference for nebulizer.

A risk prediction score to identify patients at low risk for COVID-19 infection.

Introduction: Singapore's enhanced surveillance programme for COVID-19 identifies and isolates hospitalised patients with acute respiratory symptoms to prevent nosocomial spread. We developed risk prediction models to identify patients with low risk for COVID-19 from this cohort of hospitalised patients with acute respiratory symptoms. Methods: This was a single-centre retrospective observational study. Patients admitted to our institution's respiratory surveillance wards from 10 February to 30 April 2020 contributed data for analysis. Prediction models for COVID-19 were derived from a training cohort using variables based on demographics, clinical symptoms, exposure risks and blood investigations fitted into logistic regression models. The derived prediction models were subsequently validated on a test cohort. Results: Of the 1,228 patients analysed, 52 (4.2%) were diagnosed with COVID-19. Two prediction models were derived, the first based on age, presence of sore throat, dormitory residence, blood haemoglobin level (Hb), and total white blood cell counts (TW), and the second based on presence of headache, contact with infective patients, Hb and TW. Both models had good diagnostic performance with areas under the receiver operating characteristic curve of 0.934 and 0.866, respectively. Risk score cut-offs of 0.6 for Model 1 and 0.2 for Model 2 had 100% sensitivity, allowing identification of patients with low risk for COVID-19. Limiting COVID-19 screening to only elevated-risk patients reduced the number of isolation days for surveillance patients by up to 41.7% and COVID-19 swab testing by up to 41.0%. Conclusion: Prediction models derived from our study were able to identify patients at low risk for COVID-19 and rationalise resource utilisation.