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Docta Complutense author Fernández de las Peñas, César author Palacios Ceña, Domingo author Gómez Mayordomo, Víctor author Cuadrado Pérez, María De La Luz author Florencio, Lidiane L. 2023-06-17T08:23:27Z 2023-06-17T08:23:27Z 2021-03-05 Fernández De Las Peñas, C., Palacios Ceña, D., Gómez Mayordomo, V. et al. «Defining Post-COVID Symptoms (Post-Acute COVID, Long COVID, Persistent Post-COVID): An Integrative Classification». International Journal of Environmental Research and Public Health, vol. 18, n.o 5, marzo de 2021, p. 2621. DOI.org (Crossref), https://doi.org/10.3390/ijerph18052621. 1660-4601 10.3390/ijerph18052621 https://hdl.handle.net/20.500.14352/6924 https://doi.org/10.3390/ijerph18052621 https://www.mdpi.com/1660-4601/18/5/2621/htm The pandemic of the coronavirus disease 2019 (COVID-19) has provoked a second pandemic, the “long-haulers”, i.e., individuals presenting with post-COVID symptoms. We propose that to determine the presence of post-COVID symptoms, symptoms should appear after the diagnosis of SARS-CoV-2 infection; however, this situation has some problems due to the fact that not all people infected by SARS-CoV-2 receive such diagnosis. Based on relapsing/remitting nature of post-COVID symptoms, the following integrative classification is proposed: potentially infection related-symptoms (up to 4–5 weeks), acute post-COVID symptoms (from week 5 to week 12), long post-COVID symptoms (from week 12 to week 24), and persistent post-COVID symptoms (lasting more than 24 weeks). The most important topic is to establish the time reference points. The classification also integrates predisposing intrinsic and extrinsic factors and hospitalization data which could promote post-COVID symptoms. The plethora of symptoms affecting multiple systems exhibited by “long-haulers” suggests the presence of different underlying mechanisms. eng Atribución 3.0 España Defining Post-COVID Symptoms (Post-Acute COVID, Long COVID, Persistent Post-COVID): An Integrative Classification journal article URL https://docta.ucm.es/bitstreams/a55e7a52-e962-4001-93af-5b01a1e08a21/download File MD5 e61f91afd49582da84ba9d829d0d10d5 11279980 application/pdf ijerph-18-02621-v2.pdf