Comparative Analysis of Long COVID and Post-Vaccination Syndrome: A Cross-Sectional Study of Clinical Symptoms and Machine Learning-Based Differentiation
Importance. Long COVID is a well documented post viral syndrome, while post vaccination syndrome (PVS) remains poorly characterized. Understanding their similarities and differences is essential for refining diagnostic criteria and developing targeted interventions. This study systematically compares the symptomatology of long COVID and PVS following COVID 19 vaccination, highlighting key distinctions that could inform clinical practice and research. Objective. To assess the clinical characteristics of long COVID and PVS and identify key distinguishing features between the conditions. Design, Setting and Participants. This cross sectional analysis used questionnaire data from the decentralized Yale Listen to Immune, Symptom and Treatment Experiences Now (LISTEN) Study, collected from May 2022 to July 2023. Data analysis occurred between July 2023 and May 2024. A convenience sample of adults (age ≥18 years) with either long COVID or PVS was included. Main Outcomes and Measures. Symptom data were analyzed using clustering techniques to identify groups with shared symptom patterns. A gradient boosted machine learning model was used to determine the most distinguishing symptoms between long COVID and PVS. Results. The long COVID group (n = 441) and PVS group (n = 241) had similar demographic profiles (median age 46 years; 74% vs 80% female, respectively). Participants with long COVID most commonly reported brain fog, altered sense of smell and taste, shortness of breath, fatigue, memory problems, and difficulty speaking. Participants with PVS more frequently reported burning sensations, neuropathy, and numbness. Clustering analysis identified three symptom based subgroups: one enriched for neurological symptoms and PVS; one characterized by multi system symptoms and predominantly long COVID; and one dominated by psychiatric and sleep symptoms, also primarily long COVID. The machine learning model achieved an AUC of 0.79 (95% CI, 0.75 0.82) and highlighted altered sense of smell, cough, burning sensations, and brain fog as key differentiators. Conclusions and Relevance. Although long COVID and PVS share overlapping symptoms, they have distinct clinical profiles, suggesting the possibility of different underlying biological mechanisms. These distinctions may help refine diagnostic criteria, guide personalized treatment strategies, and inform further research into their respective pathophysiology.
### Competing Interest Statement
H.M.K., in the past three years, received options for Element Science and Identifeye and payments from F-Prime for advisory roles. He was a co-founder of and held equity in Hugo Health. He is a co-founder of and holds equity in Refactor Health and ENSIGHT-AI. He is associated with research contracts through Yale University from Janssen, Kenvue, Novartis, and Pfizer. B.B. was partially supported by, and C.C. was supported by, a grant from the Yale-Mayo Clinic Center of Excellence in Regulatory Science and Innovation (CERSI) (U01FD005938). A.I. co-founded RIGImmune, Xanadu Bio and PanV and is a member of the Board of Directors of Roche Holding and Genentech. B.D. reports being a plaintiff in a lawsuit against AstraZeneca alleging breach of contract following her volunteer participation in 2020 in their COVID-19 vaccine clinical trial. She is also a co-chair of REACT19, a non-profit organization offering financial, physical, and emotional support for those suffering from long-term COVID-19 vaccine adverse events. D.H. serves on the Advisory Board of REACT19.
### Funding Statement
This study was funded in part by the Howard Hughes Medical Institute Collaborative COVID-19 Initiative, and in part by Fred Cohen and Carolyn Klebanoff.
### Author Declarations
I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
Yes
The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
The Yale University Institutional Review Board approved the LISTEN study.
I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.
Yes
I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
Yes
I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.
Yes
All data produced in the present study are available upon reasonable request to the corresponding author.