Post-COVID-19 Vaccination and Long COVID: Insights from Patient-Reported Data DOI Creative Commons

Tom Quach,

Mitchell G. Miglis, Lü Tian

и другие.

Vaccines, Год журнала: 2024, Номер 12(12), С. 1427 - 1427

Опубликована: Дек. 18, 2024

COVID-19 vaccinations reduce the severity and number of symptoms for acute SARS-CoV-2 infections may risk developing Long COVID, also known as post-acute sequelae (PASC). Limited heterogenous data exist on how these received after infection might impact trajectory PASC, once persistent have developed. We investigated association post-COVID-19 vaccination with any vaccine(s) PASC in two independent cohorts: a retrospective chart review self-reported from patients (n = 128) seen Stanford Clinic between May 2021 2022 2023 multinational survey assessment individuals 484). Within patient cohort 128), 58.6% 75) were female, 41.4% 53) male; 50% 64) white, 38.3% 49) non-white. A total 60.2% 77) reported no change their vaccination, 17.2% 22) improved symptoms, 22.7% 29) worsened symptoms. In 484), 380 U.S., 104 outside U.S.; 88.4% 428) 11.6% 56) 88.8% 430) 11.2% 54) The distribution vaccine effects was 20.2% 98), 60.5% effect 293), 19.2% 93). both cohorts, demographic features, including age, sex, race/ethnicity, not significantly associated post-vaccination symptom changes. There non-significant difference median dates among different outcomes. BMI significant improvement (p 0.026) cohort, while history booster doses < 0.001) cohort. Most did report changes overall following onset. Further research is needed to better understand relationship PASC.

Язык: Английский

Improving entity recognition using ensembles of deep learning and fine-tuned large language models: A case study on adverse event extraction from VAERS and social media DOI

Yiming Li,

Deepthi Viswaroopan,

William He

и другие.

Journal of Biomedical Informatics, Год журнала: 2025, Номер unknown, С. 104789 - 104789

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

3
Mapping vaccine names in clinical trials to vaccine ontology using cascaded fine-tuned domain-specific language models DOI Creative Commons
Jianfu Li, Yiming Li,

Yuanyi Pan

и другие.

Journal of Biomedical Semantics, Год журнала: 2024, Номер 15(1)

Опубликована: Авг. 9, 2024

Vaccines have revolutionized public health by providing protection against infectious diseases. They stimulate the immune system and generate memory cells to defend targeted Clinical trials evaluate vaccine performance, including dosage, administration routes, potential side effects.

Язык: Английский

Процитировано

7
Systematic collection, annotation, and pattern analysis of viral vaccines in the VIOLIN vaccine knowledgebase DOI Creative Commons
Anthony Huffman, Mamta Gautam,

Arya Gandhi

и другие.

Frontiers in Cellular and Infection Microbiology, Год журнала: 2025, Номер 15

Опубликована: Фев. 7, 2025

Viral vaccines have been proven significant in protecting us against viral diseases such as COVID-19. To better understand and design vaccines, it is critical to systematically collect, annotate, analyse various identify enriched patterns from these vaccines. We collected experimentally verified the literature, manually annotated, stored information VIOLIN vaccine database. The annotated included basic names, pathogens diseases, components, formulations, their induced host responses. Enriched were identified our systematical analysis of antigens. A total 2,847 95 species (including 72 RNA 23 DNA species) collected, These used 542 taxonomical found viruses covered by target different life cycle stages (e.g., entry, assembly, exit, immune evasion) top ranked human, animal HPV antigen proteins also show up virion locations HRSV Both structural non-structural for development. Protective antigens tend a protegenicity score >85% based on Vaxign-ML calculation, which measures predicted suitability use. While adhesins still significantly higher chances being protective antigens, only 21.42% be adhesins. Furthermore, Gene Ontology (GO) enrichment using customized Fisher's exact test many entry into cell, DNA/RNA/ATP/ion binding, suppression type 1 interferon-mediated signaling pathway. associated entities relations are ontologically modeled represented Vaccine (VO). web interface was developed support user friendly queries knowledgebase, insightful patterns.

Язык: Английский

Процитировано

1
Impact of climate change on vaccine responses and inequity DOI
Kai Zhang, Yifang Dang,

Yiming Li

и другие.

Nature Climate Change, Год журнала: 2024, Номер 14(12), С. 1216 - 1218

Опубликована: Ноя. 15, 2024

Язык: Английский

Процитировано

6
Exploring Temporal and Spatial Characteristics of Serious Adverse Event Reports Following COVID-19 Bivalent Vaccines DOI Creative Commons
Yiming Li, Wei Tao, Yifang Dang

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Март 3, 2025

Abstract Background To mitigate the spread of variants such as Omicron in COVID-19 pandemic, development and utilization bivalent vaccines have become essential. However, an expected subset individuals may experience serious adverse events (AE) after receiving vaccine. Methods In this research, we conducted in-depth analysis data obtained from Centers for Disease Control Prevention (CDC) Vaccine Adverse Event Reporting System (VAERS) to evaluate safety administered between 9/15/2022 9/1/2023. The Standard Federal Regions were used region partitions. broaden our understanding post-vaccination AE, performed temporal investigate trends Top 10 reported AE all event reports. We also examined similarity across diverse regions within United States. Results Our findings indicated that a relatively stably decreasing trend was observed over time, with four peaks December 2022, February 2023, Mar 2023 April 2023. terms spatial analysis, middle northern exhibited higher rates AEs associated An obvious similar pattern is (III, IV, V, VI, VII). Conclusion Overall, research underscores ongoing need vigilant post-licensure vaccine monitoring, emphasizing continuous surveillance essential upholding effectiveness vaccines.

Язык: Английский

Процитировано

0
Exploring Associations Between COVID-19 Bivalent Vaccines and Their Related Adverse Events: A Correlational Study DOI Creative Commons
Yiming Li, Wei Tao, Sori Kim Lundin

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Март 10, 2025

Abstract Introduction COVID-19, a global health crisis, prompted rapid vaccine development. Bivalent vaccines by Pfizer-BioNTech and Moderna target both original Omicron strains. Despite vaccination efforts, the persistence of adverse events underscores importance ongoing safety monitoring. Method We collected COVID-19 bivalent event reports from Vaccine Adverse Event Reporting System (VAERS) (September 15, 2022, to September 1, 2023). The Medical Dictionary for Regulatory Activities (MedDRA) categorized reported symptoms into corresponding concepts. Statistical analyses included zero-truncated Poisson regression estimating symptom rates, logistic identifying risk factors, Spearman correlation assessing non-parametric relationships between in different Organ Classes (SOCs). Results Our analysis identified significant correlations SOCs. Notably, positive (ρ = 0.3) linked Infections (SOC 1) with Respiratory disorders 13), while negative (ρ=-0.3) connected Investigations 23) Injury 24). Zero-truncated modeling estimated an average 6.179 per individual, varying age, gender, vaccine. Gender age significantly influence associated vaccines. Females generally experienced higher odds most SOCs compared males, except cardiac product-related issues. Older adults showed likelihood across various SOCs, children adolescents had distinct susceptibility patterns. Additionally, Pfizer were mainly immune skin primarily metabolic Conclusion In conclusion, our study aligned self-reported items widely-accepted medical terminology rigorously analyzed following using advanced statistical methods. findings provide crucial insights, guiding evidence-based strategies interventions safety.

Язык: Английский

Процитировано

0
Enhancing Relation Extraction for COVID-19 Vaccine Shot-Adverse Event Associations with Large Language Models DOI Creative Commons

Yiming Li,

Deepthi Viswaroopan,

William He

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Март 17, 2025

Objective The rapid evolution of the COVID-19 virus has led to development different vaccine shots, each designed combat specific variants and enhance overall efficacy. While vaccines have been crucial in controlling spread virus, they can also cause adverse events (AEs). Understanding these relationships is vital for safety monitoring surveillance. Methods In our study, we collected data from Vaccine Adverse Event Reporting System (VAERS) social media platforms (Twitter Reddit) extract between shots events. dataset comprised 771 relation pairs, enabling a comprehensive analysis event patterns. We employed state-of-the-art GPT models, including GPT-3.5 GPT-4, alongside traditional models such as Recurrent Neural Networks (RNNs) BioBERT, relationships. Additionally, used two sets post-processing rules further refine extracted relations. Evaluation metrics precision, recall, F1-score were assess performance extracting accurately. Results most commonly reported AEs following primary series include arm soreness, fatigue, headache, while spectrum boosters more diverse. extraction, fine-tuned with Sentence-based Relation Identification achieved highest precision 0.94 perfect recall 1, resulting an impressive F1 score 0.97. Conclusion This study advances biomedical informatics by showing how large language deep learning VAERS media. These findings improve clinical practice enhancing understanding post-vaccination symptoms. precedent future research natural processing informatics, potential applications pharmacovigilance decision-making.

Язык: Английский

Процитировано

0
A case of autosomal dominant polycystic kidney disease with systemic lupus erythematosus developing after SARS-CoV-2 vaccination DOI Creative Commons

K. Miyauchi,

Joichi Usui, Tatsuya Shimizu

и другие.

CEN Case Reports, Год журнала: 2025, Номер unknown

Опубликована: Май 20, 2025

Язык: Английский

Процитировано

0
VaxBot-HPV: a GPT-based chatbot for answering HPV vaccine-related questions DOI Creative Commons

Yiming Li,

Jianfu Li, Manqi Li

и другие.

JAMIA Open, Год журнала: 2024, Номер 8(1)

Опубликована: Дек. 26, 2024

Abstract Objective Human Papillomavirus (HPV) vaccine is an effective measure to prevent and control the diseases caused by HPV. However, widespread misinformation hesitancy remain significant barriers its uptake. This study focuses on development of VaxBot-HPV, a chatbot aimed at improving health literacy promoting vaccination uptake providing information answering questions about HPV vaccine. Methods We constructed knowledge base (KB) for which consists 451 documents from biomedical literature web sources extracted 202 question-answer pairs KB 39 generated GPT-4 training testing purposes. To comprehensively understand capabilities potential GPT-based chatbots, 3 models were involved in this study: GPT-3.5, GPT-4. The evaluation criteria included answer relevancy faithfulness. Results VaxBot-HPV demonstrated superior performance faithfulness compared baselines. For test KB, it achieved score 0.85 0.97. Similarly, attained scores 0.96 GPT-generated questions. Discussion demonstrates effectiveness fine-tuned large language healthcare, outperforming generic GPT accuracy relevance. Fine-tuning mitigates hallucinations misinformation, ensuring reliable while allowing dynamic tailored responses. specific fine-tuning, includes context addition pairs, enables provide explanations reasoning behind answers, enhancing transparency user trust. Conclusions underscores importance leveraging fine-tuning techniques chatbots healthcare applications, with implications medical education public communication.

Язык: Английский

Процитировано

3
Post-COVID-19 Vaccination and Long COVID: Insights from Patient-Reported Data DOI Creative Commons

Tom Quach,

Mitchell G. Miglis, Lü Tian

и другие.

Vaccines, Год журнала: 2024, Номер 12(12), С. 1427 - 1427

Опубликована: Дек. 18, 2024

COVID-19 vaccinations reduce the severity and number of symptoms for acute SARS-CoV-2 infections may risk developing Long COVID, also known as post-acute sequelae (PASC). Limited heterogenous data exist on how these received after infection might impact trajectory PASC, once persistent have developed. We investigated association post-COVID-19 vaccination with any vaccine(s) PASC in two independent cohorts: a retrospective chart review self-reported from patients (n = 128) seen Stanford Clinic between May 2021 2022 2023 multinational survey assessment individuals 484). Within patient cohort 128), 58.6% 75) were female, 41.4% 53) male; 50% 64) white, 38.3% 49) non-white. A total 60.2% 77) reported no change their vaccination, 17.2% 22) improved symptoms, 22.7% 29) worsened symptoms. In 484), 380 U.S., 104 outside U.S.; 88.4% 428) 11.6% 56) 88.8% 430) 11.2% 54) The distribution vaccine effects was 20.2% 98), 60.5% effect 293), 19.2% 93). both cohorts, demographic features, including age, sex, race/ethnicity, not significantly associated post-vaccination symptom changes. There non-significant difference median dates among different outcomes. BMI significant improvement (p 0.026) cohort, while history booster doses < 0.001) cohort. Most did report changes overall following onset. Further research is needed to better understand relationship PASC.

Язык: Английский

Процитировано

1