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Al-Aly, E. Topol, Science 383, 830\u2013832 (2024)]. These findings are primarily based on cohort studies comparing test-positive COVID-19 patients to controls without known COVID-19 infection, tested or untested [M. Cai, Y. Xie, E. J. Topol, Z. Al-Aly, Nat. Med. 30, 1564\u20131573 (2024)]. However, such comparisons can be biased by the reasons people were tested. Using 14.4 billion insurance claims from 244.7 million US patients, we find that most long-term effects attributed to COVID-19 by unrestricted control designs likely reflect bias due to selective testing of individuals with non-COVID conditions, causing long-term effects of those conditions to be misattributed to COVID-19. We removed this bias by analyzing only tested individuals, comparing test-positive to test-negative patients. Across 614 clinical outcomes followed over 2 y, the test-based design resulted in 83.5% fewer symptoms being attributable to COVID-19 between 30 to 119 d after infection (43 attributable symptoms vs. 262 for the unrestricted control design), a 98.2% reduction at 120 to 359 d (5 vs. 286), and a 100% reduction at 360 to 719 d (0 vs. 369). The unrestricted control design also attributed unrelated outcomes (e.g., firearm injuries) to COVID-19 at a high rate, whereas the testing-based design did not. The test-based control design may modestly underestimate some effects. This study does not indicate that symptoms beyond one year are not genuine but that their attributability to COVID-19 is uncertain.<\/jats:p>","DOI":"10.1073\/pnas.2604414123","type":"journal-article","created":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T17:37:52Z","timestamp":1793122672000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":0,"title":["Revised estimates of types and duration of long COVID symptoms based on claims records from 245 million US patients"],"prefix":"10.1073","volume":"123","author":[{"given":"Hamed","family":"Nilforoshan","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00f54p054","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Computer Science, Stanford 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