Long COVID after breakthrough SARS-CoV-2 infection
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Abstract
The post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection—also referred to as Long COVID—have been described, but whether breakthrough SARS-CoV-2 infection (BTI) in vaccinated people results in post-acute sequelae is not clear. In this study, we used the US Department of Veterans Affairs national healthcare databases to build a cohort of 33,940 individuals with BTI and several controls of people without evidence of SARS-CoV-2 infection, including contemporary ( n = 4,983,491), historical ( n = 5,785,273) and vaccinated ( n = 2,566,369) controls. At 6 months after infection, we show that, beyond the first 30 days of illness, compared to contemporary controls, people with BTI exhibited a higher risk of death (hazard ratio (HR) = 1.75, 95% confidence interval (CI): 1.59, 1.93) and incident post-acute sequelae (HR = 1.50, 95% CI: 1.46, 1.54), including cardiovascular, coagulation and hematologic, gastrointestinal, kidney, mental health, metabolic, musculoskeletal and neurologic disorders. The results were consistent in comparisons versus the historical and vaccinated controls. Compared to people with SARS-CoV-2 infection who were not previously vaccinated ( n = 113,474), people with BTI exhibited lower risks of death (HR = 0.66, 95% CI: 0.58, 0.74) and incident post-acute sequelae (HR = 0.85, 95% CI: 0.82, 0.89). Altogether, the findings suggest that vaccination before infection confers only partial protection in the post-acute phase of the disease; hence, reliance on it as a sole mitigation strategy may not optimally reduce long-term health consequences of SARS-CoV-2 infection. The findings emphasize the need for continued optimization of strategies for primary prevention of BTI and will guide development of post-acute care pathways for people with BTI.
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mRNA-1273 vaccination is associated with a lower incidence of long COVID compared with Ad26.COV2.S (OR 0.87; 95% CI 0.80-0.93).
“Only one study compared (therefore, meta -analyses could not be performed) different types of vaccines (i.e., BNT162b2 vs mRNA-1273 vs Ad26.COV2.S), in which BNT162b2 and mRNA-1273 were associated with lower incidences of long COVID compared to Ad26.COV2.S (OR, 0.86; 95 % CI, 0.800.93 and OR, 0.87; 95 % CI, 0.80-0.93, respectively) whereas no difference was seen between BNT162b2 vs mRNA-1273 (OR,”
From Protective effect of COVID-19 vaccination against long COVID syndrome: A systematic review and meta-analysis (2023) · cites this paper as [16]
The Results section (page unavailable) reports a decreased risk of at least one post-acute sequela among mRNA-1273 recipients, and the Discussion explicitly compares that reduction with Ad26.COV2.S. Our copy does not report the claimed OR of 0.87 or its 95% CI of 0.80–0.93, so the numerical part cannot be verified. (LLM, conf=0.86)
Experimental — accuracy not yet measuredBNT162b2 vaccination is associated with a lower incidence of long COVID compared with Ad26.COV2.S (OR 0.86; 95% CI 0.80-0.93).
“Only one study compared (therefore, meta -analyses could not be performed) different types of vaccines (i.e., BNT162b2 vs mRNA-1273 vs Ad26.COV2.S), in which BNT162b2 and mRNA-1273 were associated with lower incidences of long COVID compared to Ad26.COV2.S (OR, 0.86; 95 % CI, 0.800.93 and OR, 0.87; 95 % CI, 0.80-0.93, respectively) whereas no difference was seen between BNT162b2 vs mRNA-1273 (OR,”
From Protective effect of COVID-19 vaccination against long COVID syndrome: A systematic review and meta-analysis (2023) · cites this paper as [16]
The Results (page not available) report a decreased risk of at least one post-acute sequela among BNT162b2 recipients, and the Discussion explicitly describes greater risk reduction with BNT162b2 than with Ad26.COV2.S. Our copy does not give the claimed OR of 0.86 or 95% CI of 0.80–0.93, so the numerical part is not verified. (LLM, conf=0.88)
Experimental — accuracy not yet measuredNo difference in incidence of long COVID was seen between BNT162b2 and mRNA-1273 vaccination (OR 1.00; 95% CI 0.95-1.05).
“Only one study compared (therefore, meta -analyses could not be performed) different types of vaccines (i.e., BNT162b2 vs mRNA-1273 vs Ad26.COV2.S), in which BNT162b2 and mRNA-1273 were associated with lower incidences of long COVID compared to Ad26.COV2.S (OR, 0.86; 95 % CI, 0.800.93 and OR, 0.87; 95 % CI, 0.80-0.93, respectively) whereas no difference was seen between BNT162b2 vs mRNA-1273 (OR,”
From Protective effect of COVID-19 vaccination against long COVID syndrome: A systematic review and meta-analysis (2023) · cites this paper as [16]
The Results section (page unavailable) reports no statistically significant difference in post-acute sequelae risk between BNT162b2 and mRNA-1273 recipients with breakthrough infections. Our copy does not give the claimed OR of 1.00 or its 95% CI of 0.95–1.05, so those figures cannot be verified. (LLM, conf=0.85)
Experimental — accuracy not yet measuredA nationwide database study revealed that vaccinated patients were less likely to develop long COVID than unvaccinated patients, even in those non-hospitalized.
“A nationwide database study revealed that vaccinated patients were less likely to develop long COVID than unvaccinated patients, even in those non-hospitalized [16].”
From Protective effect of COVID-19 vaccination against long COVID syndrome: A systematic review and meta-analysis (2023) · cites this paper as [16]
Patients with two-dose vaccination were more likely to have pre-existing comorbidities than those without/one-dose vaccination.
“Notably, other studies showed that patients with two-dose vaccination were more likely to have pre-existing comorbidities than those without/one-dose vaccination [16,24,25].”
From Protective effect of COVID-19 vaccination against long COVID syndrome: A systematic review and meta-analysis (2023) · cites this paper as [16]
The Results section on breakthrough infection versus infection without prior vaccination compares post-acute outcomes and says the weighted cohorts had balanced baseline characteristics; it does not report that the vaccinated group had more pre-existing comorbidities. The Methods sections on covariates and statistical analysis identify prior conditions and describe baseline comparisons, but the searched passages do not establish a two-dose versus no-dose/one-dose comorbidity difference (page numbers unavailable). (LLM, conf=0.73)
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Cites
Nalbandian, A., Sehgal, K., Gupta, A., Madhavan, M. V., McGroder, C., Stevens, J. S., Cook, J. R., Nordvig, A. S., Shalev, D., Sehrawat, T. S., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01283-z · Cited by 4,862 · see citing works
Persistent Symptoms in Patients After Acute COVID-19
Carfì, A., Bernabei, R., Landi, F., & for the Gemelli Against COVID-19 Post-Acute Care Study Group (2020) · JAMA · doi:10.1001/jama.2020.12603 · Cited by 4,561 · see citing works
Making Neighborhood-Disadvantage Metrics Accessible — The Neighborhood Atlas
Kind, A. J. H., & Buckingham, W. R. (2018) · New England Journal of Medicine · doi:10.1056/nejmp1802313 · Cited by 3,310 · see citing works
Characterizing long COVID in an international cohort: 7 months of symptoms and their impact
Davis, H. E., Assaf, G. S., McCorkell, L., Wei, H., Low, R. J., Re'em, Y., Redfield, S., Austin, J. P., & Akrami, A. (2021) · eClinicalMedicine · doi:10.1016/j.eclinm.2021.101019 · Cited by 2,881 · see citing works
Taquet, M., Geddes, J. R., Husain, M., Luciano, S., & Harrison, P. J. (2021) · The Lancet Psychiatry · doi:10.1016/s2215-0366(21)00084-5 · Cited by 2,189 · see citing works
High-dimensional characterization of post-acute sequelae of COVID-19
Al-Aly, Z., Xie, Y., & Bowe, B. (2021) · Nature · doi:10.1038/s41586-021-03553-9 · Cited by 1,518 · see citing works
Schneeweiss, S., Rassen, J. A., Glynn, R. J., Avorn, J., Mogun, H., & Brookhart, M. A. (2009) · Epidemiology · doi:10.1097/ede.0b013e3181a663cc · Cited by 1,128 · see citing works
Flagged first, then by citations
Research works printed but not linked: 28
- [2]2. Juthani PV Hospitalisation among vaccine breakthrough COVID-19 infections Lancet Infect. Dis. 2021 21 1485 1486 10.1016/S1473-3099(21)00558-2 34506735 PMC8423430 · DOI
- [3]3. Nixon DF Ndhlovu LC Vaccine breakthrough infections with SARS-CoV-2 variants N. Engl. J. Med. 2021 385 e7 10.1056/NEJMc2107808 34077640 · DOI
- [4]4. Xie Y Xu E Bowe B Al-Aly Z Long-term cardiovascular outcomes of COVID-19 Nat. Med. 2022 28 583 590 10.1038/s41591-022-01689-3 35132265 PMC8938267 · DOI
- [5]5. Bowe, B., Xie, Y., Xu, E. & Al-Aly, Z. Kidney outcomes in Long COVID. J. Am. Soc. Nephrol.32, 2851–2862 (2021) 10.1681/ASN.2021060734 PMC8806085 34470828 · DOI
- [6]6. Xie Y Bowe B Al-Aly Z Burdens of post-acute sequelae of COVID-19 by severity of acute infection, demographics and health status Nat. Commun. 2021 12 6571 10.1038/s41467-021-26513-3 34772922 PMC8589966 · DOI
- [7]7. Xie, Y., Xu, E. & Al-Aly, Z. Risks of mental health outcomes in people with Covid-19: cohort study. BMJ376, e068993 (2022). 10.1136/bmj-2021-068993 PMC8847881 35172971 · DOI
- [8]8. Daugherty SE Risk of clinical sequelae after the acute phase of SARS-CoV-2 infection: retrospective cohort study BMJ 2021 373 n1098 10.1136/bmj.n1098 34011492 PMC8132065 · DOI
- [9]9. Taquet M Incidence, co-occurrence, and evolution of long-COVID features: a 6-month retrospective cohort study of 273,618 survivors of COVID-19 PLoS Med. 2021 18 e1003773 10.1371/journal.pmed.1003773 34582441 PMC8478214 · DOI
- [12]12. Ayoubkhani D Post-covid syndrome in individuals admitted to hospital with covid-19: retrospective cohort study BMJ 2021 372 n693 10.1136/bmj.n693 33789877 PMC8010267 · DOI
- [13]13. Alwan NA The road to addressing Long Covid Science 2021 373 491 493 10.1126/science.abg7113 34326224 · DOI
- [15]15. Xie Y Estimates of all cause mortality and cause specific mortality associated with proton pump inhibitors among US veterans: cohort study BMJ 2019 365 l1580 10.1136/bmj.l1580 31147311 PMC6538974 · DOI
- [16]16. Xie, Y., Bowe, B., Maddukuri, G. & Al-Aly, Z. Comparative evaluation of clinical manifestations and risk of death in patients admitted to hospital with covid-19 and seasonal influenza: cohort study. BMJ371, m4677 (2021). 10.1136/bmj.m4677 PMC7735416 33323357 · DOI
- [17]17. Xie, Y. et al. Comparative effectiveness of sodium-glucose cotransporter 2 inhibitors vs sulfonylureas in patients with type 2 diabetes. JAMA Intern. Med.181, 1043–1053 (2021). 10.1001/jamainternmed.2021.2488 PMC8240007 34180939 · DOI
- [18]18. Cai M Temporal trends in incidence rates of lower extremity amputation and associated risk factors among patients using Veterans Health Administration services from 2008 to 2018 JAMA Netw. Open 2021 4 e2033953 10.1001/jamanetworkopen.2020.33953 33481033 PMC7823225 · DOI
- [19]19. Cai M Bowe B Xie Y Al-Aly Z Temporal trends of COVID-19 mortality and hospitalisation rates: an observational cohort study from the US Department of Veterans Affairs BMJ Open 2021 11 e047369 10.1136/bmjopen-2020-047369 PMC8370839 34400452 · DOI
- [20]20. Bowe B Xie Y Yan Y Al-Aly Z Burden of cause-specific mortality associated with PM2.5 air pollution in the United States JAMA Netw. Open 2019 2 e1915834 10.1001/jamanetworkopen.2019.15834 31747037 PMC6902821 · DOI · Paper page
- [21]21. Bowe, B. et al. Acute kidney injury in a national cohort of hospitalized US veterans with COVID-19. Clin. J. Am. Soc. Nephrol.16, 14–25 (2020). 10.2215/CJN.09610620 PMC7792643 33199414 · DOI
- [22]22. Xie, Y. & Ziyad, A.-A. Risks and burdens of incident diabetes in long COVID-19: a cohort study. Lancet Diabetes Endocrinol.10, 311–321 (2022). 10.1016/S2213-8587(22)00044-4 PMC8937253 35325624 · DOI · Paper page
- [23]23. Spudich S Nath A Nervous system consequences of COVID-19 Science 2022 375 267 269 10.1126/science.abm2052 35050660 · DOI · Paper page
- [26]26. Sharma, A., Oda, G. & Holodniy, M. COVID-19 vaccine breakthrough infections in Veterans Health Administration. Preprint at https://www.medrxiv.org/content/10.1101/2021.09.23.21263864v1 (2021). · DOI
- [28]28. Wei Y Short term exposure to fine particulate matter and hospital admission risks and costs in the Medicare population: time stratified, case crossover study BMJ 2019 367 l6258 10.1136/bmj.l6258 31776122 PMC6880251 · DOI
- [29]29. Aubert CE Best definitions of multimorbidity to identify patients with high health care resource utilization Mayo Clin. Proc. Innov. Qual. Outcomes 2020 4 40 49 10.1016/j.mayocpiqo.2019.09.002 32055770 PMC7011007 · DOI
- [31]31. Olvey EL Clauschee S Malone DC Comparison of critical drug–drug interaction listings: the Department of Veterans Affairs medical system and standard reference compendia Clin. Pharmacol. Ther. 2010 87 48 51 10.1038/clpt.2009.198 19890252 · DOI
- [32]32. Greene M Steinman MA McNicholl IR Valcour V Polypharmacy, drug–drug interactions, and potentially inappropriate medications in older adults with human immunodeficiency virus infection J. Am. Geriatr. Soc. 2014 62 447 453 10.1111/jgs.12695 24576251 PMC4043391 · DOI
- [33]33. Li F Thomas LE Li F Addressing extreme propensity scores via the overlap weights Am. J. Epidemiol. 2019 188 250 257 10.1093/aje/kwy265 30189042 · DOI
- [34]34. Thomas LE Li F Pencina MJ Overlap weighting: a propensity score method that mimics attributes of a randomized clinical trial JAMA 2020 323 2417 2418 10.1001/jama.2020.7819 32369102 · DOI
- [35]35. Lipsitch M Tchetgen Tchetgen E Cohen T Negative controls: a tool for detecting confounding and bias in observational studies Epidemiology 2010 21 383 388 10.1097/EDE.0b013e3181d61eeb 20335814 PMC3053408 · DOI · Paper page
- [36]36. Shi X Miao W Tchetgen ET A selective review of negative control methods in epidemiology Curr. Epidemiol. Rep. 2020 7 190 202 10.1007/s40471-020-00243-4 33996381 PMC8118596 · DOI
Cited by
Sorted by citations
Long COVID: major findings, mechanisms and recommendations
Davis, H. E., McCorkell, L., Vogel, J. M., & Topol, E. J. (2023) · Nature Reviews Microbiology · doi:10.1038/s41579-022-00846-2 · Cited by 4,153 · see citing works
Markov, P. V., Ghafari, M., Beer, M., Lythgoe, K., Simmonds, P., Stilianakis, N. I., & Katzourakis, A. (2023) · Nature Reviews Microbiology · doi:10.1038/s41579-023-00878-2 · Cited by 1,179 · see citing works
Alarming antibody evasion properties of rising SARS-CoV-2 BQ and XBB subvariants
Wang, Q., Iketani, S., Li, Z., Liu, L., Guo, Y., Huang, Y., Bowen, A. D., Liu, M., Wang, M., Yu, J., et al. (2023) · Cell · doi:10.1016/j.cell.2022.12.018 · Cited by 912 · see citing works
Long-term neurologic outcomes of COVID-19
Xu, E., Xie, Y., & Al-Aly, Z. (2022) · Nature Medicine · doi:10.1038/s41591-022-02001-z · Cited by 530 · see citing works
Self-citationNotarte, K. I., Catahay, J. A., Velasco, J. V., Pastrana, A., Ver, A. T., Pangilinan, F. C., Peligro, P. J., Casimiro, M., Guerrero, J. J., Gellaco, M. M. L., et al. (2022) · eClinicalMedicine · doi:10.1016/j.eclinm.2022.101624 · Cited by 480 · see citing works
The neurobiology of long COVID
Monje, M., & Iwasaki, A. (2022) · Neuron · doi:10.1016/j.neuron.2022.10.006 · Cited by 415 · see citing works
Watanabe, A., Iwagami, M., Yasuhara, J., Takagi, H., & Kuno, T. (2023) · Vaccine · doi:10.1016/j.vaccine.2023.02.008 · Cited by 304 · see citing works
Lau, J. J., Cheng, S. M. S., Leung, K., Lee, C. K., Hachim, A., Tsang, L. C. H., Yam, K. W. H., Chaothai, S., Kwan, K. K. H., Chai, Z. Y. H., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02219-5 · Cited by 198 · see citing works
Robinson, D. J., Hanson, K., Jain, A. B., Kichler, J. C., Mehta, G., Melamed, O. C., Vallis, M., Bajaj, H. S., Barnes, T., Gilbert, J., et al. (2023) · Canadian Journal of Diabetes · doi:10.1016/j.jcjd.2023.04.009 · Cited by 73 · see citing works
Chudzik, M., Babicki, M., Kapusta, J., Kałuzińska-Kołat, Ż., Kołat, D., Jankowski, P., & Mastalerz-Migas, A. (2022) · Viruses · doi:10.3390/v14081755 · Cited by 65 · see citing works
- Authors
- Al-Aly, Z., Bowe, B., & Xie, Y.
- Affiliations
- VA St. Louis Health Care System (US)
- Venue
- Nature Medicine
- Published
- 2022-05-25
- Volume
- 28
- Issue
- 7
- Pages
- 1461-1467
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- PMC
- PMC9307472
- OpenAlex
- W4281476185
- Cited by
- 866
- References
- 7
- Citations by year
- 2026: 85 · 2025: 130 · 2024: 217 · 2023: 292 · 2022: 142
- FWCI
- 103.44
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature Medicine (publishedVersion, cc-by)
- Research Square (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Commons@Becker (Washington University School of Medicine) (submittedVersion, cc-by)
- Funders
- U.S. Department of Veterans Affairs
- American Society of Nephrology
- Topics
- Health Sciences › Medicine › Neurology › Long-Term Effects of COVID-19
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Keywords
- long COVID, post-acute sequelae, COVID-19 vaccination, vaccine effectiveness, mortality, cardiovascular complications, coagulopathy, mental health, musculoskeletal disorders, neurological disorders, veterans, post-acute care
- MeSH terms
- COVID-19, SARS-CoV-2, Post-Acute COVID-19 Syndrome, Humans, Nervous System Diseases, Cohort Studies
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