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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
241 173-176 Chemical denotes NO2
242 600-603 Chemical denotes NO2
243 1286-1289 Chemical denotes NO2
244 1590-1593 Chemical denotes NO2
245 1663-1666 Chemical denotes NO2
246 1831-1834 Chemical denotes NO2
247 180-188 Disease denotes COVID-19 MESH:C000657245
248 189-198 Disease denotes mortality MESH:D003643
249 231-237 Disease denotes deaths MESH:D003643
250 545-554 Disease denotes mortality MESH:D003643
251 858-866 Disease denotes COVID-19 MESH:C000657245
252 867-876 Disease denotes mortality MESH:D003643
253 922-930 Disease denotes COVID-19 MESH:C000657245
254 931-937 Disease denotes deaths MESH:D003643
255 1159-1167 Disease denotes COVID-19 MESH:C000657245
256 1168-1174 Disease denotes deaths MESH:D003643
257 1240-1248 Disease denotes COVID-19 MESH:C000657245
258 1249-1255 Disease denotes deaths MESH:D003643
259 1452-1458 Disease denotes deaths MESH:D003643
260 1541-1549 Disease denotes COVID-19 MESH:C000657245
261 1550-1559 Disease denotes mortality MESH:D003643
262 1686-1694 Disease denotes COVID-19 MESH:C000657245
263 1695-1701 Disease denotes deaths MESH:D003643
264 1773-1781 Disease denotes COVID-19 MESH:C000657245
265 1782-1791 Disease denotes mortality MESH:D003643

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T189 0-53 Sentence denotes 4.2 Comparison with previous studies focusing on NO2
T190 54-199 Sentence denotes Our study is comparable with previous studies in the US, England and the Netherlands assessing the long-term effect of NO2 in COVID-19 mortality.
T191 200-286 Sentence denotes The study in the US focused on deaths reported by April 29, 2020, using 3122 counties.
T192 287-472 Sentence denotes For the exposure, they calculated the mean of daily concentrations during 2010–2016 as modelled by a previously described ensemble machine learning model (R2 = 0.79) (Di et al., 2019a).
T193 473-519 Sentence denotes They reported a 7.1% (95% Confidence Interval:
T194 520-676 Sentence denotes 1.2%, 13.4%) increase in mortality per 4.5 ppb (1 ppb = 1.25 μg/m3) increase in NO2 after adjusting for confounders and spatial autocorrelation(Liang et al.
T195 677-732 Sentence denotes 2020)(that is approximately 1.3% increase per 1 μg/m3).
T196 733-888 Sentence denotes A study in England, with partly overlapping data as in our analysis, also reported a significant association between NO2 and COVID-19 mortality (p < 0.05).
T197 889-1061 Sentence denotes For the analysis they focused on COVID-19 deaths reported in England up to April 10, 2020, used 317 LTLAs, and did not account for spatial autocorrelation (Travaglio et al.
T198 1062-1068 Sentence denotes 2020).
T199 1069-1216 Sentence denotes The study in the Netherlands using 335 municipalities, mean exposure during 2015–2019 and COVID-19 deaths up to June 5, 2020 reported 0.35 (95% CI:
T200 1217-1419 Sentence denotes 0.04, 0.66) additional COVID-19 deaths for every 1 μg/m3 increase in NO2 after adjusting for confounders and certain spatial controls, such as transmission beyond the Dutch national borders (Cole et al.
T201 1420-1426 Sentence denotes 2020).
T202 1427-1594 Sentence denotes Since the mean number of deaths in their sample is 16.86, the above estimate translates to a 2.0% increase in the COVID-19 mortality for every 1 μg/m3 increase in NO2.
T203 1595-1862 Sentence denotes An ONS report in England using 175 sampling units, 10-year averaged NO2 exposure (PCM) and COVID-19 deaths up to June 12, 2020 found a 0.6% (95% CI: −0.1%, 2.2%) increase in the COVID-19 mortality for every 1 μg/m3 increase in averaged NO2 exposure (Statistics 2020).