{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T03:42:45Z","timestamp":1790653365986,"version":"4.1.0"},"reference-count":27,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T00:00:00Z","timestamp":1777334400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Economic Development of the Russian Federation","award":["000000C313925P4G0002"],"award-info":[{"award-number":["000000C313925P4G0002"]}]},{"name":"Ivannikov Institute for System Programming of the Russian Academy of Sciences","award":["139-15-2025-011"],"award-info":[{"award-number":["139-15-2025-011"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Background: Post-COVID-19 condition (PCC) affects many survivors, with evidence of sex-specific differences in prevalence and symptom profiles. However, few prediction studies have examined whether sex-stratified models improve prediction or generalize across sexes. This study aimed primarily to develop and compare sex-stratified machine learning models for PCC prediction using routinely available baseline variables, and secondarily to assess cross-sex generalizability and adversarial robustness. Methods: We analyzed a prospective longitudinal cohort of 1006 adults hospitalized with COVID-19 at Sechenov University Hospital Network (Moscow, Russia). Demographics, smoking status, and pre-existing comorbidities were extracted from medical records, and PCC status was assessed at 6-month follow-up. Machine learning models\u2014including classical algorithms and graph-based neural networks\u2014were trained separately for males and females. Cross-sex validation evaluated generalizability, variable importance aided interpretation, and adversarial perturbations assessed model robustness. Results: PCC prevalence was higher in females (53.9%) than males (39.1%). Overall predictive performance was modest across all models, with AUC values ranging approximately 0.50\u20130.61. Graph-based models achieved the highest discrimination, with the best AUC reaching approximately 0.61, while classical approaches provided limited predictive value. Cross-sex validation showed minor asymmetry: models trained on male data performed slightly better on female cases than vice versa. Adversarial testing revealed sensitivity of all models to input perturbations. Conclusions: Demographics and comorbidities alone provide insufficient information for reliable PCC prediction. Modest sex-specific differences in model generalizability suggest distinct, sex-associated PCC phenotypes, but richer multimodal data\u2014including clinical biomarkers, wearable-derived measures, and patient-reported outcomes\u2014will be required to develop clinically useful and equitable predictive models. Sex-stratified approaches should be considered in future post-viral syndrome prediction studies.<\/jats:p>","DOI":"10.3390\/jcm15093367","type":"journal-article","created":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T13:26:41Z","timestamp":1777382801000},"page":"3367","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Sex-Stratified Machine Learning for the Prediction of Post-COVID Condition: A Longitudinal Cohort Study"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1169-5149","authenticated-orcid":false,"given":"Mikhail I.","family":"Krivonosov","sequence":"first","affiliation":[{"name":"ISP RAS Research Center for Trusted Artificial Intelligence, 109004 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ekaterina","family":"Pazukhina","sequence":"additional","affiliation":[{"name":"Centre for Cancer Screening, Prevention and Early Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mikhail","family":"Rumyantsev","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elina","family":"Abdeeva","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dina","family":"Baimukhambetova","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Polina","family":"Bobkova","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yasmin","family":"El-Taravi","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria","family":"Pikuza","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7074-7922","authenticated-orcid":false,"given":"Anastasia","family":"Trefilova","sequence":"additional","affiliation":[{"name":"Academician V.I. Krasnopolsky Moscow Regional Research Institute of Obstetrics and Gynecology (MONIIAG), 22a Pokrovka St., 101000 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aleksandr","family":"Zolotarev","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Margarita","family":"Andreeva","sequence":"additional","affiliation":[{"name":"Centre for Health Services and Policy Research, University of British Columbia, Vancouver, BC V6T 1Z4, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ekaterina","family":"Iakovleva","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3989-2590","authenticated-orcid":false,"given":"Nikolay","family":"Bulanov","sequence":"additional","affiliation":[{"name":"Tareev Clinic of Internal Diseases, Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5999-2150","authenticated-orcid":false,"given":"Sergey","family":"Avdeev","sequence":"additional","affiliation":[{"name":"Clinic of Pulmonology, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7540-1130","authenticated-orcid":false,"given":"Alexey","family":"Zaikin","sequence":"additional","affiliation":[{"name":"ISP RAS Research Center for Trusted Artificial Intelligence, 109004 Moscow, Russia"},{"name":"Institute for Cognitive Neuroscience, University Higher School of Economics, 101000 Moscow, Russia"},{"name":"Department of Mathematics and Women\u2019s Cancer, University College London, London WC1E 6BT, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6512-1629","authenticated-orcid":false,"given":"Valentina","family":"Kapustina","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine No. 1, Institute of Clinical Medicine, Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Victor","family":"Fomin","sequence":"additional","affiliation":[{"name":"Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrey A.","family":"Svistunov","sequence":"additional","affiliation":[{"name":"Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7773-2435","authenticated-orcid":false,"given":"Peter","family":"Timashev","sequence":"additional","affiliation":[{"name":"Institute for Regenerative Medicine, Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4437-9070","authenticated-orcid":false,"given":"Janna G.","family":"Oganezova","sequence":"additional","affiliation":[{"name":"Academician A.P. Nesterov Department of Ophthalmology of the Institute of Clinical Medicine, Pirogov Russian National Research Medical University, 117437 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nina","family":"Avdeenko","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yulia","family":"Ivanova","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lyudmila","family":"Fedorova","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elena","family":"Kondrikova","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Irina","family":"Turina","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Petr","family":"Glybochko","sequence":"additional","affiliation":[{"name":"Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Denis","family":"Butnaru","sequence":"additional","affiliation":[{"name":"Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0194-6389","authenticated-orcid":false,"given":"Oleg","family":"Blyuss","sequence":"additional","affiliation":[{"name":"Centre for Cancer Screening, Prevention and Early Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9652-6856","authenticated-orcid":false,"given":"Daniel","family":"Munblit","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child\u2019s Health, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia"},{"name":"Division of Care in Long Term Conditions, Florence Nightingale Faculty of Nursing, Midwifery and Palliative Care, King\u2019s College London, London WC2R 2LS, UK"},{"name":"Research and Clinical Center for Neuropsychiatry, 119334 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"Sechenov StopCOVID Research Team","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1001\/jama.2020.12603","article-title":"Persistent Symptoms in Patients After Acute COVID-19","volume":"324","author":"Bernabei","year":"2020","journal-title":"JAMA"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1097\/COC.0000000000001005","article-title":"Long COVID in Cancer: A Matched Cohort Study of 1-year Mortality and Long COVID Prevalence Among Patients with Cancer Who Survived an Initial Severe SARS-CoV-2 Infection","volume":"46","author":"Fankuchen","year":"2023","journal-title":"Am. J. Clin. Oncol."},{"key":"ref_3","first-page":"e14357","article-title":"Frequency, signs and symptoms, and criteria adopted for long COVID-19: A systematic review","volume":"75","author":"Martimbianco","year":"2021","journal-title":"Int. J. Clin. Pract."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1001\/jamainternmed.2023.0750","article-title":"Risk Factors Associated with Post-COVID-19 Condition: A Systematic Review and Meta-analysis","volume":"183","author":"Tsampasian","year":"2023","journal-title":"JAMA Intern. Med."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Delfino, C., Poli, M.C., Vial, C., Vial, P.A., Mart\u00ednez, G., Riviotta, A., Arbat, C., Mac-Guire, N., Hoppe, J., and Carvajal, C. (2024). Post-COVID-19 condition: A sex-based analysis of clinical and laboratory trends. Front. Med., 11.","DOI":"10.3389\/fmed.2024.1376030"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1391","DOI":"10.1080\/03007995.2022.2081454","article-title":"Sex differences in sequelae from COVID-19 infection and in long COVID syndrome: A review","volume":"38","author":"Sylvester","year":"2022","journal-title":"Curr. Med. Res. Opin."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Gullo, G., Scaglione, M., Cucinella, G., Riva, A., Coldebella, D., Cavaliere, A.F., Signore, F., Buzzaccarini, G., Spagnol, G., and Lagan\u00e0, A.S. (2022). Congenital Zika Syndrome: Genetic Avenues for Diagnosis and Therapy, Possible Management and Long-Term Outcomes. J. Clin. Med., 11.","DOI":"10.3390\/jcm11051351"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Maranto, M., Zaami, S., Restivo, V., Termini, D., Gangemi, A., Tumminello, M., Culmone, S., Billone, V., Cucinella, G., and Gullo, G. (2023). Symptomatic COVID-19 in Pregnancy: Hospital Cohort Data between May 2020 and April 2021, Risk Factors and Medicolegal Implications. J. Clin. Med., 12.","DOI":"10.3390\/diagnostics13061009"},{"key":"ref_9","unstructured":"Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., and Fergus, R. (2014, January 14\u201316). Intriguing Properties of Neural Networks. Proceedings of the International Conference on Learning Representations (ICLR), Banff, AB, Canada."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"13174","DOI":"10.52202\/068431-0957","article-title":"Increasing confidence in adversarial robustness evaluations","volume":"35","author":"Brendel","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_11","unstructured":"The World Health Organization (2026, March 30). Statement on the Update of WHO\u2019s Working Definitions and Tracking System for SARS-CoV-2 Variants of Concern and Variants of Interest. Available online: https:\/\/www.who.int\/news\/item\/16-03-2023-statement-on-the-update-of-who-s-working-definitions-and-tracking-system-for-sars-cov-2-variants-of-concern-and-variants-of-interest."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1107","DOI":"10.1111\/cea.13997","article-title":"Incidence and risk factors for persistent symptoms in adults previously hospitalized for COVID-19","volume":"51","author":"Munblit","year":"2021","journal-title":"Clin. Exp. Allergy"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/cid\/ciaa1535","article-title":"Stop COVID Cohort: An Observational Study of 3480 Patients Admitted to the Sechenov University Hospital Network in Moscow City for Suspected Coronavirus Disease 2019 (COVID-19) Infection","volume":"73","author":"Munblit","year":"2021","journal-title":"Clin. Infect. Dis."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"e102","DOI":"10.1016\/S1473-3099(21)00703-9","article-title":"A clinical case definition of post-COVID-19 condition by a Delphi consensus","volume":"22","author":"Soriano","year":"2022","journal-title":"Lancet Infect. Dis."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Pazukhina, E., Andreeva, M., Spiridonova, E., Bobkova, P., Shikhaleva, A., El-Taravi, Y., Rumyantsev, M., Gamirova, A., Bairashevskaia, A., and Petrova, P. (2022). Sechenov StopCOVID Research Team Prevalence and risk factors of post-COVID-19 condition in adults and children at 6 and 12 months after hospital discharge: A prospective, cohort study in Moscow (StopCOVID). BMC Med., 20.","DOI":"10.2139\/ssrn.4020142"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1925","DOI":"10.1093\/eurheartj\/ehu207","article-title":"Towards better clinical prediction models: Seven steps for development and an ABCD for validation","volume":"35","author":"Steyerberg","year":"2014","journal-title":"Eur. Heart J."},{"key":"ref_17","first-page":"3","article-title":"Statistical Challenges in the Analysis of Biomarker Data","volume":"Volume 2","author":"Chen","year":"2024","journal-title":"Biostatistics in Biopharmaceutical Research and Development: Clinical Trial Analysis"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Zaikin, A., Sviridov, I., Oganezova, J.G., Menon, U., Gentry-Maharaj, A., Timms, J.F., and Blyuss, O. (2025). Synolitic Graph Neural Networks of High-Dimensional Proteomic Data Enhance Early Detection of Ovarian Cancer. Cancers, 17.","DOI":"10.3390\/cancers17243972"},{"key":"ref_19","unstructured":"Lundberg, S.M., and Lee, S.-I. (2017, January 4\u20139). A unified approach to interpreting model predictions. Proceedings of the 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA."},{"key":"ref_20","unstructured":"Nicolae, M.-I., Sinn, M., Tran, M.N., Buesser, B., Rawat, A., Wistuba, M., Zantedeschi, V., Baracaldo, N., Chen, B., and Ludwig, H. (2018). Adversarial Robustness Toolbox v1. 0.0. arXiv."},{"key":"ref_21","unstructured":"Goodfellow, I.J., Shlens, J., and Szegedy, C. (2015). Explaining and Harnessing Adversarial Examples. International Conference on Learning Representations (ICLR). arXiv."},{"key":"ref_22","unstructured":"Madry, A., Makelov, A., Schmidt, L., Tsipras, D., and Vladu, A. (2018). Towards Deep Learning Models Resistant to Adversarial Attacks. arXiv."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1038\/s41591-021-01292-y","article-title":"Attributes and predictors of long COVID","volume":"27","author":"Sudre","year":"2021","journal-title":"Nat. Med."},{"key":"ref_24","first-page":"9","article-title":"Machine learning models predict long COVID outcomes based on baseline clinical and immunologic factors","volume":"6","author":"Jayavelu","year":"2026","journal-title":"Commun. Med."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5504","DOI":"10.1038\/s41467-023-41541-x","article-title":"Predictors of the post-COVID condition following mild SARS-CoV-2 infection","volume":"14","author":"Reme","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Maranto, M., Gullo, G., Bruno, A., Minutolo, G., Cucinella, G., Maiorana, A., Casuccio, A., and Restivo, V. (2023). Factors Associated with Anti-SARS-CoV-2 Vaccine Acceptance among Pregnant Women: Data from Outpatient Women Experiencing High-Risk Pregnancy. J. Clin. Med., 11.","DOI":"10.3390\/vaccines11020454"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Riemma, G., De Franciscis, P., Tesorone, M., Coppa, E., Schiattarella, A., Billone, V., Lopez, A., Cucinella, G., Gullo, G., and Carotenuto, R.M. (2023). Obstetric and Gynecological Admissions and Hospitalizations in an Italian Tertiary-Care Hospital during COVID-19 Pandemic: A Retrospective Analysis According to Restrictive Measures. J. Clin. Med., 12.","DOI":"10.3390\/jcm12227097"}],"container-title":["Journal of Clinical Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2077-0383\/15\/9\/3367\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T14:01:42Z","timestamp":1777384902000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2077-0383\/15\/9\/3367"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,28]]},"references-count":27,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2026,5]]}},"alternative-id":["jcm15093367"],"URL":"https:\/\/doi.org\/10.3390\/jcm15093367","relation":{},"ISSN":["2077-0383"],"issn-type":[{"value":"2077-0383","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,28]]}}}