The diagnostic accuracy of spirometry versus peak expiratory flow test for follow-up of adult asthma patients at primary care level.

Background: The asthma burden is growing worldwide, and this is predisposed by environmental and occupational exposures as well as individual risk factors. This study was aimed at a comparison of diagnostic accuracy of spirometry and peak expiratory flow rate (PEFR) in asthma screening of adult patients with lung function abnormalities that present at the level of primary care. Methods: This study was conducted in Shymkent city, South Kazakhstan, the third most populous city of the country with developed industries and high rates of pulmonary diseases. Four hundred and ninety-five adult patients with lung function abnormalities were enrolled in the study and underwent two screening tests (spirometry and PEFR). The diagnosis of asthma was verified by a qualified pulmonologist after performance of screening tests and was based on symptoms, medical history, and laboratory and lung function tests. Results: The sensitivity of spirometry was 0.97 and that of PEFR was 0.95 (p = 0.721), whereas the specificity of spirometry was 0.37 and that of PEFR was 0.28 (p = 0.227). Both tests yielded the same results for the positive predictive value (0.98). The negative predictive value was significantly higher for spirometry versus PEFR (0.23 versus 0.08; p = 0.006). The positive and negative likelihood ratios of the two tests also differed significantly (p = 0.001 and p = 0.006, respectively), whereas the overall accuracy was comparable between the two tests (0.96 for spirometry and 0.94 for PEFR; p = 0.748). Conclusion: Ambulatory PEFR monitoring is non-inferior to the monitoring of the forced expiratory volume in 1 second and could be used for screening purposes on equal grounds with spirometry.

Anticipating the Need for Healthcare Resources Following the Escalation of the COVID-19 Outbreak in the Republic of Kazakhstan.

OBJECTIVES: The lack of advance planning in a public health emergency can lead to wasted resources and inadvertent loss of lives. This study is aimed at forecasting the needs for healthcare resources following the expansion of the coronavirus disease 2019 (COVID-19) outbreak in the Republic of Kazakhstan, focusing on hospital beds, equipment, and the professional workforce in light of the developing epidemiological situation and the data on resources currently available. METHODS: We constructed a forecast model of the epidemiological scenario via the classic susceptible-exposed-infected-removed (SEIR) approach. The World Health Organization's COVID-19 Essential Supplies Forecasting Tool was used to evaluate the healthcare resources needed for the next 12 weeks. RESULTS: Over the forecast period, there will be 104 713.7 hospital admissions due to severe disease and 34 904.5 hospital admissions due to critical disease. This will require 47 247.7 beds for severe disease and 1929.9 beds for critical disease at the peak of the COVID-19 outbreak. There will also be high needs for all categories of healthcare workers and for both diagnostic and treatment equipment. Thus, Republic of Kazakhstan faces the need for a rapid increase in available healthcare resources and/or for finding ways to redistribute resources effectively. CONCLUSIONS: Republic of Kazakhstan will be able to reduce the rates of infections and deaths among its population by developing and following a consistent strategy targeting COVID-19 in a number of inter-related directions.