Patient flowchart. by Anna D. Ware (19688153)

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Trends of incident opioid users, L-TOT users, and L-TOT discontinuers between 2009 and 2013. by Qian Cai (112039)

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The yearly numerator, denominator and rate of incident opioid users, L-TOT users and L-TOT discontinuers from 2009 to 2019. by Qian Cai (112039)

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Incidence rate ratios of negative binominal regression models for yearly rates of incident opioid users, L-TOT users and L-TOT discontinuers during 2009–2013 and 2015–2019. by Qian Cai (112039)

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Demographic, comorbidity, concurrent drug, and opioid characteristics, among L-TOT users and L-TOT discontinuers between 2009–2019. by Qian Cai (112039)

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Excluded skewed studies. by Solima Sabeel (9545738)

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Reason for exclusion of all 6514 screened articles. by Solima Sabeel (9545738)

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Methodological items for non-randomized studies (MINORS). by Solima Sabeel (9545738)

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Jadad Score of randomized controlled trials. by Solima Sabeel (9545738)

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Summary of randomized controlled trials. by Solima Sabeel (9545738)

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Overall analysis of randomized controlled trials. by Solima Sabeel (9545738)

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Summary table showing analysis of randomized controlled trials stratified based on age groups. by Solima Sabeel (9545738)

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Meta-analysis showing the overall effect of different statin types versus placebo for by Solima Sabeel (9545738)

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Version 2 of the Cochrane risk-of-bias tool for randomized controlled trials. by Solima Sabeel (9545738)

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Analysis of randomized controlled trials stratified based on treatment duration. by Solima Sabeel (9545738)

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Funnel plots of studies included in the meta-analysis assessing by Solima Sabeel (9545738)

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Summary of non-randomized studies. by Solima Sabeel (9545738)

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PRISMA flow diagram of the systematic literature search process. by Solima Sabeel (9545738)

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Newcastle-Ottawa scale. by Solima Sabeel (9545738)

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Detailed information of the observation datasets. by Weidong Ji (129916)

“…Generally speaking, there is no clear linear relationship between scores and the other variables. On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”