Long COVID’s Gender-Specific Determinants: 3- and 6-Month Evidence from Thai Females During the Delta and Omicron Waves
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Abstract
Objectives: To prospectively identify determinants of Long COVID in Thai females and compare outcomes across the Delta and Omicron periods through structured follow-up assessments at 3 and 6 months post-infection.
Materials and Methods: From May 2021 through June 2022, this prospective cohort study was conducted in Thailand at Thammasat University Hospital and its field hospital. We enrolled 1,484 females aged 18 and older with laboratory-confirmed SARS-CoV-2 infection. Using a standardized questionnaire and trained interviewers to assess Long COVID symptoms, we followed up with participants via telephone interviews at 3- and 6-months post-diagnosis. Multivariable logistic regression was used to identify independent risk factors for Long COVID.
Results: At the 3-month follow-up, 806 participants (54.3%) reported Long COVID symptoms, which persisted in 418 (38.6%) at 6 months. At 3 months, infection during the Omicron-dominant wave (adjusted odds ratio (OR) 1.75, 95% confidence interval (CI): 1.26–2.43) and acute myalgia (adjusted OR 1.52, 95% CI: 1.04–2.22) were significant predictors. At the 6-month follow-up, moderate-to-critical initial illness severity (adjusted OR 2.17, 95% CI: 1.01–4.69) and loss of smell during the acute phase (adjusted OR 1.61, 95% CI: 1.04–2.49) were significant predictors of persistent Long COVID.
Conclusion: In Thai females, determinants for Long COVID shift between 3 and 6 months post-infection. While acute myalgia and the Omicron variant are early predictors, initial illness severity and loss of smell better indicate symptom persistence at 6 months. These findings highlight Long COVID’s dynamic nature and can help identify female patients at higher risk for prolonged symptoms.
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References
Poewe W, Seppi K, Tanner CM, Halliday GM, Brundin P, Volkmann J, et al. Parkinson disease. Nat Rev Dis Primers 2017;3:17013. doi: 10.1038/nrdp.2017.13.
Goldman JG, Litvan I. Mild cognitive impairment in Parkinson’s disease. Minerva Med 2011;102(6):441-59.
Aarsland D, Batzu L, Halliday GM, Geurtsen GJ, Ballard C, Ray Chaudhuri K, et al. Parkinson disease-associated cognitive impairment. Nat Rev Dis Primers 2021;7(1):47. doi: 10.1038/s41572-021-00280-3.
Broeders M, de Bie RM, Velseboer DC, Speelman JD, Muslimovic D, Schmand B. Evolution of mild cognitive impairment in Parkinson disease. Neurology 2013;81(4):346-52. doi: 10.1212/WNL.0b013e31829c5c86.
Goldman JG, Vernaleo BA, Camicioli R, Dahodwala N, Dobkin RD, Ellis T, et al. Cognitive impairment in Parkinson’s disease: a report from a multidisciplinary symposium on unmet needs and future directions to maintain cognitive health. NPJ Parkinsons Dis 2018;4:19. doi: 10.1038/s41531-018-0055-3.
Baiano C, Barone P, Trojano L, Santangelo G. Prevalence and clinical aspects of mild cognitive impairment in Parkinson’s disease: a meta-analysis. Mov Disord 2020;35(1):45-54. doi: 10.1002/mds.27902.
Litvan I, Goldman JG, Tröster AI, Schmand BA, Weintraub D, Petersen RC, et al. Diagnostic criteria for mild cognitive impairment in Parkinson’s disease: movement disorder society task force guidelines. Mov Disord 2012;27(3):349-56. doi: 10.1002/mds.24893.
Lawrence BJ, Gasson N, Loftus AM. Prevalence and subtypes of mild cognitive impairment in parkinson’s disease. Sci Rep 2016;6:33929. doi: 10.1038/srep33929.
Monastero R, Di Fiore P, Ventimiglia GD, Ventimiglia CC, Battaglini I, Camarda R. Prevalence and profile of mild cognitive impairment in Parkinson’s disease. Neurodegener Dis 2012;10(1-4):187-90. doi: 10.1159/000335909.
Aarsland D, Brønnick K, Larsen JP, Tysnes OB, Alves G. Cognitive impairment in incident, untreated Parkinson disease: the Norwegian ParkWest study. Neurology 2009;72(13):1121-6. doi: 10.1212/01.wnl.0000338632.00552.cb.
Yarnall AJ, Breen DP, Duncan GW, Khoo TK, Coleman SY, Firbank MJ, et al. Characterizing mild cognitive impairment in incident Parkinson disease: the ICICLE-PD study. Neurology 2014;82(4):308-16. doi: 10.1212/WNL.0000000000000066.
Hoogland J, Boel JA, de Bie RMA, Geskus RB, Schmand BA, Dalrymple-Alford JC, et al. Mild cognitive impairment as a risk factor for Parkinson’s disease dementia. Mov Disord 2017;32(7):1056-65. doi: 10.1002/mds.27002.
Gonzalez-Latapi P, Bayram E, Litvan I, Marras C. Cognitive impairment in Parkinson’s disease: epidemiology, clinical profile, protective and risk factors. Behav Sci (Basel) 2021;11(5):74. doi: 10.3390/bs11050074.
Bhidayasiri R, Wannachai N, Limpabandhu S, Choeytim S, Suchonwanich Y, Tananyakul S, et al. A national registry to determine the distribution and prevalence of Parkinson’s disease in Thailand: implications of urbanization and pesticides as risk factors for Parkinson’s disease. Neuroepidemiology 2011;37(3-4):222-30. doi: 10.1159/000334440.
Kumar N, Gupta G. Screening of cognitive impairment in early Parkinson’s disease using Montreal Cognitive Assessment (MoCA). J Neurol Sci 2019;405:27-8. doi: 10.1016/j.jns.2019.10.262
Hemrungrojn S, Tangwongchai S, Charoenboon T, Panasawat M, Supasitthumrong T, Chaipresertsud P, et al. Use of the montreal cognitive assessment Thai version to discriminate amnestic mild cognitive impairment from Alzheimer’s disease and healthy controls: machine learning results. Dement Geriatr Cogn Disord 2021;50(2):183-94. doi: 10.1159/000517822.
Stern Y. Cognitive reserve in ageing and Alzheimer’s disease. Lancet Neurol 2012;11(11):1006-12. doi: 10.1016/S1474-4422(12)70191-6.
Kalaria RN, Maestre GE, Arizaga R, Friedland RP, Galasko D, Hall K, et al. Alzheimer’s disease and vascular dementia in developing countries: prevalence, management, and risk factors. Lancet Neurol 2008;7(9):812-26. doi: 10.1016/S1474-4422(08)70169-8.
Xu WL, Atti AR, Gatz M, Pedersen NL, Johansson B, Fratiglioni L. Midlife overweight and obesity increase late-life dementia risk: a population-based twin study. Neurology 2011;76(18):1568-74. doi: 10.1212/WNL.0b013e3182190d09.
Pedditzi E, Peters R, Beckett N. The risk of overweight/obesity in mid-life and late life for the development of dementia: a systematic review and meta-analysis of longitudinal studies. Age Ageing 2016;45(1):14-21. doi: 10.1093/ageing/afv151.
Boyle PA, Buchman AS, Wilson RS, Leurgans SE, Bennett DA. Physical frailty is associated with incident mild cognitive impairment in community-based older persons. J Am Geriatr Soc 2010;58(2):248-55. doi: 10.1111/j.1532-5415.2009.02671.x.
van der Marck MA, Dicke HC, Uc EY, Kentin ZH, Borm GF, Bloem BR, et al. Body mass index in Parkinson’s disease: a meta-analysis. Parkinsonism Relat Disord 2012;18(3):263-7. doi: 10.1016/j.parkreldis.2011.10.016.
Chang KV, Hsu TH, Wu WT, Huang KC, Han DS. Association between sarcopenia and cognitive impairment: a systematic review and meta-analysis. J Am Med Dir Assoc 2016;17(12):1164.e7-15. doi: 10.1016/j.jamda.2016.09.013.
van Uden IW, van der Holst HM, Tuladhar AM, van Norden AG, de Laat KF, Rutten-Jacobs LC, et al. White matter and hippocampal volume predict the risk of dementia in patients with cerebral small vessel disease: the RUN DMC study. J Alzheimers Dis 2016;49(3):863-73. doi: 10.3233/JAD-150573.
