LitCovid-sentences  

PMC:7786642 / 29952-32462 JSONTXT 3 Projects

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Id Subject Object Predicate Lexical cue
T248 0-19 Sentence denotes 4.5 Interpretation
T249 20-224 Sentence denotes Compared to the previous studies, our results are the smallest in magnitude, likely because of the high geographical precision that allows more accurate confounding and spatial autocorrelation adjustment.
T250 225-346 Sentence denotes In addition, we report weak evidence of an effect, which could also be due to lack of power and individual exposure data.
T251 347-531 Sentence denotes Nevertheless, as for NO2 we find a high posterior probability of an effect on mortality, we argue that a potential explanation might be the mediation effect of pre-existing conditions.
T252 532-792 Sentence denotes While in our analysis the inclusion of area-level prevalence of hypertension, diabetes and COPD did not change the results, the ecological nature of the pre-existing conditions data does not allow us to account for the mediation effect at the individual level.
T253 793-1024 Sentence denotes Our study focuses on the mortality after contracting SARS-CoV-2, however we cannot rule out individual susceptibility to becoming infected as an explanation to the uncertainty in the effect estimates (Villeneuve and Goldberg 2020).
T254 1025-1144 Sentence denotes Such susceptibility can reflect immunosuppression, leading to later increases in inflammation (Edoardo Conticini et al.
T255 1145-1299 Sentence denotes 2020) and thus worse prognosis, or even disease spread, as recent studies have suggested that PM2.5 can proliferate COVID-19 transmission (Bianconi et al.
T256 1300-1306 Sentence denotes 2020).
T257 1307-1360 Sentence denotes Our analysis captured strong spatial autocorrelation.
T258 1361-1604 Sentence denotes The observed pattern could reflect residual variation from a potential inadequate covariate adjustment (including disease spread), spatial variation of pre-existing conditions, other unknown spatial confounders or a combination from all above.
T259 1605-1853 Sentence denotes In a sensitivity analysis, we observed that the factors associated with disease transmission left the latent field unchanged (Supplemental Material Fig. S21), as did the inclusion of hypertension, diabetes and COPD (Supplemental Material Fig. S33).
T260 1854-2024 Sentence denotes When we restricted the analysis to the pre-lockdown period, the latent field for both pollutants captured London and Birmingham, i.e. the cities with the first outbreaks.
T261 2025-2247 Sentence denotes Considering the above, and the fact that COVID-19 is an infectious disease, we believe that large variation of Fig. 4 is likely due to disease spread, which is not adequately captured in the disease progression covariates.
T262 2248-2510 Sentence denotes Fig. 4 Median posterior spatial relative risk (exponential of the spatial autocorrelation term) and posterior probability that the spatial relative risk is larger than 1 for the models with NO2 and a spatial autocorrelation term and the fully adjusted NO2 model.