Adverse Effects of COVID-19 Vaccination: Machine Learning and Statistical Approach to Identify and Classify Incidences of Morbidity and Postvaccination Reactogenicity

Abstract

Good vaccine safety and reliability are essential for successfully countering infectious disease spread. A small but significant number of adverse reactions to COVID-19 vaccines have been reported. Here, we aim to identify possible common factors in such adverse reactions to enable strategies that reduce the incidence of such reactions by using patient data to classify and characterise those at risk. We examined patient medical histories and data documenting postvaccination effects and outcomes. The data analyses were conducted using a range of statistical approaches followed by a series of machine learning classification algorithms. In most cases, a group of similar features was significantly associated with poor patient reactions. These included patient prior illnesses, admission to hospitals and SARS-CoV-2 reinfection. The analyses indicated that patient age, gender, taking other medications, type-2 diabetes, hypertension, allergic history and heart disease are the most significant pre-existing factors associated with the risk of poor outcome. In addition, long duration of hospital treatments, dyspnoea, various kinds of pain, headache, cough, asthenia, and physical disability were the most significant clinical predictors. The machine learning classifiers that are trained with medical history were also able to predict patients with complication-free vaccination and have an accuracy score above 90%. Our study identifies profiles of individuals that may need extra monitoring and care (e.g., vaccination at a location with access to comprehensive clinical support) to reduce negative outcomes through classification approaches.

Lymphadenopathy post‐COVID‐19 vaccination with increased FDG uptake may be falsely attributed to oncological disorders: A systematic review

“…Approximately 4.2% of the individuals who took the Moderna vaccine developed lymphadenopathy in one cohort study 41 . In two cohort studies in which participants took either the Pfizer or Moderna vaccine (unspecified), 1.9% of the individuals developed lymphadenopathy 43 . Additionally, in another cohort 1.0% of the individuals who took the AstraZeneca vaccine developed lymphadenopathy 48 (Figure 4A).…”

“…Tables 1 and 2 summarize the summed percentages of individuals who developed lymphadenopathy out of the total individuals in cohort studies without control, cohort studies with control, and RTCs 21–57 …”

“…Tables and summarize the types of the included studies 21–57 . The results from our search yielded 24 case series/reports, 7 cohort studies without control (Table ), 21–51 3 cohort studies with controls, and 3 randomized control trials (RCT) (Table ) 52–57 . Two of the cohort studies without control were conducted in the USA and two in Israel.…”

“…Tables and summarize the demographic and clinical data extracted from the included studies 21–57 . Table 1 summarizes the findings of the studies without control including cohort studies, case series, and case reports.…”

Heart Rate Variability in Subjects with Severe Allergic Background Undergoing COVID-19 Vaccination

“…The side effects of vaccination were amplified by the media, increasing vaccine hesitancy from the beginning of the vaccination campaign, and governments introduced measures to undermine misinformation and encourage vaccination. Scientific research has currently been focused on hypersensitivity reactions and the characteristics of subjects who may develop them [ 4 , 5 ]. Hypersensitivity reactions are an exaggerated and inappropriate immunological response to an allergen typically characterized by skin, respiratory, and/or cardiovascular involvement [ 6 ].…”