Mortality Attributed to COVID-19 in High-Altitude Populations
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Abstract
Woolcott, Orison O., and Richard N. Bergman. Mortality attributed to COVID-19 in high-altitude populations. High Alt Med Biol . 21:409–416, 2020.
Since partial oxygen pressure decreases as altitude increases, environmental hypoxia could worsen Coronavirus Disease 2019 (COVID-19) patient's hypoxemia. We compared COVID-19 mortality at different altitudes.
Methods:
Retrospective analysis of population-level data on COVID-19 deaths was conducted in the United States (1,016 counties) and Mexico (567 municipalities). Mixed-model Poisson regression analysis of the association between altitude and COVID-19 mortality was conducted using individual-level data from 40,168 Mexican subjects with COVID-19, adjusting for multiple covariates.
Results:
Between January 20 and April 13, 2020, mortality rates were higher in U.S. counties located at ≥2,000 m elevation versus those located <1,500 m (12.3 vs. 3.2 per 100,000; p < 0.001). In Mexico, between March 13 and May 13, 2020, mortality rates were higher in municipalities located at ≥2,000 m versus those located <1,500 m (5.3 vs. 3.9 per 100,000; p < 0.001). Among Mexican subjects younger than 65 years, the risk of death was 36% higher in those living at ≥2,000 m versus those living at <1,500 m (adjusted incidence rate ratio [IRR]: 1.36; confidence interval [95% CI], 1.05–1.78; p = 0.022). Among Mexican men, the risk of death was 31% higher at ≥2,000 m versus that at <1,500 m (adjusted IRR: 1.31; 95% CI, 1.03–1.66; p = 0.025). No association between altitude and COVID-19 mortality was found among Mexican women or among Mexican subjects 65 years of age and older.
Conclusions:
Altitude is associated with COVID-19 mortality in men younger than 65 years.
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SciScore for 10.1101/2020.06.10.20128025: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: This study did not require approval or exemption from the Cedars-Sinai Medical Center Institutional Review Board as it involved the analysis of publicly available de-identified data only. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable Since old age and male sex are risk factors linked to COVID-19 mortality (Li et al., 2020; Vincent and Taccone, 2020), we tested for a possible interaction between age and altitude and sex and altitude on the regression models for mortality, pneumonia, and endotracheal intubation. Table 2: Resources
Software and Algorithms Sentences Resources All analyses were performed using … SciScore for 10.1101/2020.06.10.20128025: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: This study did not require approval or exemption from the Cedars-Sinai Medical Center Institutional Review Board as it involved the analysis of publicly available de-identified data only. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable Since old age and male sex are risk factors linked to COVID-19 mortality (Li et al., 2020; Vincent and Taccone, 2020), we tested for a possible interaction between age and altitude and sex and altitude on the regression models for mortality, pneumonia, and endotracheal intubation. Table 2: Resources
Software and Algorithms Sentences Resources All analyses were performed using Stata 14 (StataCorp LP, TX). StataCorpsuggested: (Stata, RRID:SCR_012763)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:A major limitation of the present study include possible misreport of COVID-19 cases and deaths. Underreporting of COVID-19 is a global problem (Krantz and Rao, 2020) as the number of cases largely depend on the number of tests performed and the type of test used. This can introduce bias when comparing incidence rates across populations and overestimate or underestimate the total number of deaths attributed to COVID-19. Likewise, it is possible that the number of reported deaths attributed to COVID-19 does not accurately represent the total of fatal cases. Deaths occurring in nursing homes or private residences could be underreported.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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