Submitted:
19 December 2025
Posted:
19 December 2025
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Materials and Methods
2.1. Socioeconomic Environment
2.2. Quantification of Long COVID Syndrome Prevalence and Thrombosis
2.4. Statistical Analysis
3. Results
3.1. Long COVID Prevalence and Chronic Treatment with Antihistamines
3.2. Thrombotic Events in the COVID Era by Gender, Polypharmacy, Vaccination and COVID-19 Waves
3.3. Thrombotic Events and Antihistamines
4. Discussion
4.1. Antihistamines and Long COVID
4.2. Antihistamines, Respiratory Viruses and Thrombosis
4.3. Limitations of the Study
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| AntiHm | Antihistamines |
| LC | Long COVID |
| No V | Non-vaccinated |
| Preinf | Previous to the SARS-CoV-2 infection |
| Postinf | Posterior to the SARS-CoV-2 infection |
| Pre Thr | Previous to the thrombosis |
| Post Th | Posterior to the thrombosis |
| CoV | SARS-CoV-2 infection |
| CST | Consorci Sanitari de Terrassa |
References
- O’Mahoney, L.L.; Routen, A.; Gillies, C.; Jenkins, S.A.; Almaqhawi, A.; Ayoubkhani, D.; Banerjee, A.; Brightling, C.; Calvert, M.; Cassambai, S.; et al. The risk of Long Covid symptoms: A systematic review and meta-analysis of controlled studies. Nat. Commun. 2025, 16, 4249. [Google Scholar] [CrossRef]
- 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. Post-acute COVID-19 syndrome. Nat. Med. 2021, 27, 601–615. [Google Scholar] [CrossRef]
- Davis, H.E.; McCorkell, L.; Vogel, J.M.; Topol, E.J. Long COVID: Major findings, mechanisms and recommendations. Nat. Rev. Microbiol. Erratum in Nat. Rev. Microbiol. 2023, 21, 408.. 2023, 21, 133–146. [Google Scholar] [CrossRef]
- Koutsiaris, A.G.; Karakousis, K. Long COVID Mechanisms, Microvascular Effects, and Evaluation Based on Incidence. Life 2025, 15, 887. [Google Scholar] [CrossRef]
- Arévalo-Genicio, A.; García-Arqué, M.C.; Gragea-Nocete, M.; Llistosella, M.; Moro-Casasola, V.; Pérez-Díaz, C.; Puigdellívol-Sánchez, A.; Roca-Puig, R. Long COVID Syndrome Prevalence in 2025 in an Integral Healthcare Consortium in the Metropolitan Area of Barcelona: Persistent and Transient Symptoms. Vaccines 2025, 13, 905. [Google Scholar] [CrossRef] [PubMed]
- Gordon, D.E.; Jang, G.M.; Bouhaddou, M.; Xu, J.; Obernier, K.; White, K.M.; O’Meara, M.J.; Rezelj, V.V.; Guo, J.Z.; Swaney, D.L. A SARS-CoV-2 Protein Interaction Map Reveals Targets for Drug-Repurposing. Nature 2020, 583, 459–468. [Google Scholar] [CrossRef] [PubMed]
- Morán Blanco, J.I.; Alvarenga Bonilla, J.A.; Homma, S.; Suzuki, K.; Fremont-Smith, P.; Villar Gómez de Las Heras, K. Antihistamines and azithromycin as a treatment for COVID-19 on primary health care—A retrospective observational study in elderly patients. Pulm. Pharmacol. Ther. 2021, 67, 101989. [Google Scholar] [CrossRef]
- Bielza, R.; Sanz, J.; Zambrana, F.; Arias, E.; Malmierca, E.; Portillo, L.; Thuissard, I.J.; Lung, A.; Neira, M.; Moral, M.; et al. Clinical Characteristics, Frailty, and Mortality of Residents with COVID-19 in Nursing Homes of a Region of Madrid. J. Am. Med. Dir. Assoc. 2021, 22, 245–252. [Google Scholar] [CrossRef]
- Morán Blanco, J.I.; Alvarenga Bonilla, J.A.; Fremont-Smith, P.; Villar Gómez de Las Heras, K. Antihistamines as an early treatment for COVID-19. Heliyon 2023, 9, e15772. [Google Scholar] [CrossRef] [PubMed]
- Puigdellívol-Sánchez, A.; Juanes-González, M.; Calderón-Valdiviezo, A.; Losa-Puig, H.; Valls-Foix, R.; González-Salvador, M.; Lozano-Paz, C.; Vidal-Alaball, J. COVID-19 in Relation to Chronic Antihistamine Prescription. Microorganisms 2024, 12, 2589. [Google Scholar] [CrossRef]
- Puigdellívol-Sánchez, A.; Juanes-González, M.; Calderón-Valdiviezo, A.I.; Losa-Puig, H.; González-Salvador, M.; León-Pérez, M.; Pueyo-Antón, L.; Franco-Romero, M.; Lozano-Paz, C.; Cortés-Borra, A.; et al. COVID-19 Pandemic Waves and 2024–2025 Winter Season in Relation to Angiotensin-Converting Enzyme Inhibitors, Angiotensin Receptor Blockers and Amantadine. Healthcare (Basel) 2025, 13, 1270. [Google Scholar] [CrossRef] [PubMed]
- CoVariants; Hodcroft, E. Institute of Social and Preventive Medicine University of Bern, Switzerland & SIB Swiss Insitute of 375 Bioinformatics. Available online: https://covariants.org/ (accessed on 30 March 2025).
- Dean, A.G.; Sullivan, K.M.; Soe, M.M. OpenEpi: Open Source Epidemiologic Statistics for Public Health, Versión. Available online: https://www.openepi.com/Menu/OE_Menu.htm (accessed on 30 March 2025).
- Momtazmanesh, S.; Ansari, S.; Izadi, Z.; Shobeiri, P.; Vatankhah, V.; Seifi, A.; Ghiasvand, F.; Bahrami, M.; Salehi, M.; Noorbala, A.A.; Akhondzadeh, S. Effect of famotidine on cognitive and behavioral dysfunctions induced in post-COVID-19 infection: A randomized, double-blind, and placebo-controlled study. J Psychosom Res. 2023, 172, 111389. [Google Scholar] [CrossRef] [PubMed]
- Oh, K.K.; Adnan, M.; Cho, D.H. Network Pharmacology Study to Elucidate the Key Targets of Underlying Antihistamines against COVID-19. Curr. Issues Mol. Biol. 2022, 44, 1597–1609. [Google Scholar] [CrossRef]
- Korinek, M.; Candelas Serra, M.; Abdel Rahman, F.; Dobrovolski, M.; Kuchtiak, V.; Abramova, V.; Fili, K.; Tomovic, E.; Hrcka Krausova, B.; Krusek, J.; Cerny, J.; Vyklicky, L.; Balik, A.; Smejkalova, T. Disease-Associated Variants in GRIN1, GRIN2A and GRIN2B genes: Insights into NMDA Receptor Structure, Function, and Pathophysiology. Physiol Res. 2024, 73, S413–S434. [Google Scholar] [CrossRef]
- Sansom, J.E.; Brooks, J.; Burton, J.L.; Archer, C.B. Effects of H1- and H2-antihistamines on platelet-activating factor and bradykinin-induced inflammatory responses in human skin. Clin Exp Dermatol 1996, 21, 33–37. [Google Scholar] [CrossRef]
- Izquierdo, I.; Casas, L.; Cabrera, S.; Fernandez, A. How to handle off-label prescriptions of rupatadine, a second-generation antihistamine and PAF antagonist: a review. Drugs Context. 2024, 13, 2023–9-5. [Google Scholar] [CrossRef]
- Brennan, C.M.; Nadella, S.; Zhao, X.; Dima, R.J.; Jordan-Martin, N.; Demestichas, B.R.; Kleeman, S.O.; Ferrer, M.; von Gablenz, E.C.; Mourikis, N.; et al. Oral famotidine versus placebo in non-hospitalised patients with COVID-19: A randomised, double-blind,data-intense, phase 2 clinical trial. Gut 2022, 71, 879–888. [Google Scholar] [CrossRef]
- Bunce, P.E.; High, S.M.; Nadjafi, M.; Stanley, K.; Liles, W.C.; Christian, M.D. Pandemic H1N1 influenza infection and vascular thrombosis. Clin Infect Dis 2011, 52, e14–e17. [Google Scholar] [CrossRef]
- Chow, E.J.; Rolfes, M.A.; O’Halloran, A.; Anderson, E.J.; Bennett, N.M.; Billing, L.; et al. Acute Cardiovascular Events Associated With Influenza in Hospitalized Adults: A Cross-sectional Study. Ann Intern Med 2020, 173, 605–613. [Google Scholar] [CrossRef] [PubMed]
- Rubino, R.; Imburgia, C.; Bonura, S.; Trizzino, M.; Iaria, C.; Cascio, A. Thromboembolic Events in Patients with Influenza: A Scoping Review. Viruses 2022, 14, 2817. [Google Scholar] [CrossRef]
- Generalitat de Catalunya. Available online: https://sivic.salut.gencat.cat/ (accessed on 3 December 2025).
- Generalitat de Catalunya. Available online: https://scientiasalut.gencat.cat/bitstream/handle/11351/8851/pidirac_balanç_temporada_gripal_2020_2021.pdf (accessed on 3 December 2025).
- Jacobs, J.W.; Stanek, C.G.; Booth, G.S.; Symeonidis, A.; Shih, A.W.; Allen, E.S.; Gavriilaki, E.; Grossman, B.J.; Pavenski, K.; Moorehead, A.; et al. The seasonal distribution of immune thrombotic thrombocytopenic purpura is influenced by geography: Epidemiologic findings from a multi-center analysis of 719 disease episodes. Am J Hematol. 2024, 99, 2063–2074. [Google Scholar] [CrossRef]
- Javaid, S.S.; Zahid, K.; Ashfaq, H.; Rahman, S.; Shahid, S.; Abbasi, M.B.; Imran, S.; Thada, P.K.; Mengal, A.; Habib, H.; Ullah, M.S.; Kumar, S.; Farooqui, S.K. Seasonal variations in hospitalizations of heart failure patients: a United States nationwide analysis. Minerva Cardiol Angiol Epub ahead of print. 2025. [Google Scholar] [CrossRef]
- Li, L.; Ge, Q.; Sun, S.; Yang, S.; Wei, J.; Sun, Y.; Fan, X.; Liu, J.; Deng, S.; Lisen, L.; Song, Q.; Ding, J.; Wang, S. Association between air pollution-cold wave sequential events and ischaemic stroke incidence among elderly adults in Tianjin, China: a retrospective cohort study. BMJ Open. 2025, 15, e096297. [Google Scholar] [CrossRef]
- Cassavaugh, J.; Longhi, M.S.; Robson, S.C. Impact of Estrogen on Purinergic Signaling in Microvascular Disease. Int J Mol Sci. 2025, 26, 2105. [Google Scholar] [CrossRef]
- Luo, C.; Du, J.; Cuker, A.; Lautenbach, E.; Asch, D.A.; Poland, G.A.; Tao, C.; Chen, Y. Comparability of clinical trials and spontaneous reporting data regarding COVID-19 vaccine safety. Sci Rep. 2022, 12, 10946. [Google Scholar] [CrossRef]
- Anastasiou, T.; Sanidas, E.; Lytra, T.; Mimikos, G.; Gogas, H.; Mantzourani, M. Update on Thromboembolic Events After Vaccination Against COVID-19. Vaccines (Basel). 2025, 13, 833. [Google Scholar] [CrossRef] [PubMed]
- Joy, M.; Agrawal, U.; Fan, X.; Robertson, C.; Anand, S.N.; Ordonez-Mena, J.; Byford, R.; Goudie, R.; Jamie, G.; Kar, D.; Williams, J.; Marsden, G.L.; Tzortziou-Brown, V.; Sheikh, S.A.; Hobbs, F.D.R.; de Lusignan, S. Thrombocytopenic, thromboembolic and haemorrhagic events following second dose with BNT162b2 and ChAdOx1: self-controlled case series analysis of the English national sentinel cohort. Lancet Reg Health Eur. 2023, 32, 100681. [Google Scholar] [CrossRef] [PubMed]
- Khan, G.A.; Huwaikem, M.; Chowdhury, K.; Albugami, H.F.; Ghosh, A. The Role of Sterile Inflammation in Thrombosis: Consequences for Cardiovascular Disease and COVID-19. Mediators Inflamm. 2025, 2025, 8054886. [Google Scholar] [CrossRef]
- Prakash, S.; Choudhury, P.; Bisht, S. Diabetic cardiomyopathy and COVID-19: intersecting pathways and amplified cardiovascular risk. Front Pharmacol. 2025, 16, 1683159. [Google Scholar] [CrossRef] [PubMed]




| No AntiHm | AntiHm | OR No AntiHm/ | p | |||||
| V n inf | inf no LC | LC | % | inf no LC | LC | % | /antiHm | (1-2 tailed) |
| V, inf? ? | 30253 | 26 | 0.1% | 3590 | 11 | 0.3% | ||
| No V, inf? | 13079 | 12 | 0.1% | 1782 | 0.0% | |||
| 1 | ||||||||
| V preinf | 9806 | 51 | 0.5% | 1526 | 12 | 0.8% | 0.66 | 0.09-0.19 |
| V post inf | 3478 | 94 | 2.7% | 556 | 13 | 2.3% | 1.16 | 0.31-0.63 |
| No V | 4786 | 42 | 0.9% | 794 | 6 | 0.8% | 1.16 | 0.36-0.73 |
| 2 | ||||||||
| V preinf | 839 | 7 | 0.8% | 152 | 0.0% | |||
| V post inf | 808 | 34 | 4.2% | 158 | 9 | 5.7% | 0.74 | 0.21-0.42 |
| No V | 485 | 8 | 1.6% | 115 | 2 | 1.7% | 0.95 | 0.48-0.96 |
| ≥3 | ||||||||
| V preinf | 77 | 2 | 2.6% | 18 | 0.0% | |||
| V post inf | 144 | 9 | 6.3% | 22 | 0.0% | |||
| No V | 49 | 5 | 10.2% | 10 | 0.0% |
| Thrombosis | 2020 3-12 | 2021 | 2022 | 2023 | 2024 | 2025 1-3 | No Thrombosis Total general | |
| AntiHm/nT | 13 | 26 | 38 | 34 | 38 | 13 | 10253 | 10415 |
| 0 | 1639 | 1639 | ||||||
| 1 | 1 | 1 | 2005 | 2007 | ||||
| 2-4 | 3 | 9 | 6 | 2 | 10 | 1 | 3878 | 3909 |
| 5-7 | 1 | 4 | 14 | 14 | 13 | 5 | 1629 | 1680 |
| ≥8 | 9 | 12 | 18 | 18 | 14 | 7 | 1102 | 1180 |
| No AntiHm/nT | 243 | 403 | 455 | 495 | 512 | 141 | 179987 | 182236 |
| 0 | 18 | 31 | 23 | 21 | 41 | 28 | 117980 | 118142 |
| 1 | 8 | 9 | 17 | 22 | 33 | 9 | 19556 | 19654 |
| 2-4 | 48 | 88 | 111 | 120 | 159 | 40 | 25608 | 26174 |
| 5-7 | 83 | 117 | 151 | 165 | 145 | 30 | 10639 | 11330 |
| ≥8 | 86 | 158 | 153 | 167 | 134 | 34 | 6204 | 6936 |
| No AntiHm≥1nT | 225 | 372 | 432 | 474 | 471 | 113 | 62007 | 64094 |
| Total general | 256 | 429 | 493 | 529 | 550 | 154 | 190240 | 192651 |
| OR No AntiHm/AntiHm | ||||||||
| 2-4 | 1.5 | 2.8* | 9.0* | 2.4* | ||||
| 5-7 | 4.3* | 1.6 | 1.7* | 1.7 | ||||
| ≥8 | 2.2* | 1.4 | 1.6* | 1.6 | ||||
| No AntiHm ≥1nT |
AntiHm ≥1nT |
||||||
| OR (p) No AntiHm/Antihm |
|||||||
| V pre thr | V post thr | No thr | V pre thr | V post thr | No Thr | ||
| V | 1470 | 324 | 43834 | 123 | 21 | 5923 | |
| V preinf | 343 | 63 | 10376 | 39 | 7 | 1662 | |
| CoV | |||||||
| CoV pre Thr | 260 | 1 | 27 | 1.52 (0.01)* | |||
| CoV post thr | 83 | 62 | 12 | 7 | |||
| CoV No Thr | 10376 | 1662 | |||||
| V postinf | 100 | 60 | 4407 | 9 | 6 | 743 | |
| CoV | |||||||
| CoV pre Thr | 100 | 41 | 9 | 5 | 1.84 (0.03*) | ||
| CoV post thr | 19 | 1 | |||||
| CoV No Thr | 4407 | 743 | |||||
| No CoV | 1027 | 201 | 29051 | 75 | 8 | 3518 | 1.62 (0.00001)* |
| No V | Trh-18466 | Thr-2709 | |||||
| CoV | |||||||
| CoV pre Thr | 52 | 5 | 3.47 (p=0.10) | ||||
| CoV post thr | 20 | 1 | |||||
| CoV No Thr | 5303 | 921 | |||||
| No CoV | |||||||
| No Cov Thr | 221 | 12 | 2.53 (p=0.0006*) | ||||
| No CoV no Thr | 12870 | 1770 | |||||
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