ABSTRACT
Post-COVID-19 pulmonary sequalae are well-recognized early in the pandemic. Survivorship clinics are crucial for managing at-risk patients. However, it is unclear who requires pulmonary function test (PFT) and when PFTs should be performed. We aim to investigate for whom and how these interval PFTs should be performed. We performed a single-centre, prospective cohort study on COVID-19 survivors between 1st May 2020 to 31st April 2022. These patients were followed up at 6, 9 and 12 months with interval PFT and Short Form-36 (SF-36) Health Survey. Those with PFT defects were offered a computed tomography scan of the thorax. Of the 46 patients recruited, 17 (37%) had severe/critical illness. Compared to those with mild/moderate disease, these patients were more likely to experience DLCO defects (59% versus 17%, p = 0.005) and had lower SF-36 scores (mean physical component summary score of 45 ± 12 versus 52 ± 8, p = 0.046). These differences were most notable at 6 months, compared to the 9- and 12-months intervals. DLCO defects were also associated with older age, raised inflammatory markers and extensive CXR infiltrates. Besides interstitial-like abnormalities, obesity and undiagnosed lung conditions accounted for 39% of the PFT abnormalities. Interval PFTs can be performed earliest 6 months post-COVID-19. Patients with normal tests were unlikely to develop new abnormalities and would not require repeat PFTs. Abnormal PFTs can be followed-up with repeat PFTs 6 monthly until resolution. Non-COVID-19 differentials should be considered for persistent PFT abnormalities.
Subject(s)
Testicular Neoplasms , Critical Illness , Obesity , COVID-19 , Cardiovascular AbnormalitiesABSTRACT
Metal prices have a significant impact on the manufacturing sector. Aluminium as raw material and an essential component of various manufacturing processes have a considerable effect on the cost and price of manufactured items. Therefore, the present study focuses on the influence of aluminium price movements on India's manufacturing sector during the COVID period. The current research is empirical and examines the causal relationship between aluminium prices and the manufacturing index in India during the COVID era. Different methodologies are used to study aluminium price fluctuations. Many earlier studies focused on forecasting aluminium prices, while others looked at the relationship between aluminium and other indices or commodities. The current research uses a quantile regression approach to accomplish the study's objective. Quantile regression is a nonlinear data model that may provide lower or higher results than the conditional mean. This model is appropriate in situations when linearity is not expected. The study's findings are helpful for companies processing or using aluminium in their production processes, all manufacturing industries where aluminium is a crucial component of raw material, and regulators and policymakers working on boosting the aluminium industry and other stakeholders.
ABSTRACT
Background: To assess outcome parameters of using Remdesivir in patients with SARS- COV-2 infection.