Pattern of self-reported adverse events related to COVID-19 vaccines in Saudi Arabia: A nationwide study
Bibliographic record
Abstract
Background Vaccination against coronavirus disease 2019 (COVID-19) is the most effective way to end the pandemic. Any development of adverse events (AEs) from various vaccines should be reported. We therefore aimed to explore major and minor AEs among vaccinated individuals in Saudi Arabia. Methods This is a nationwide report based on the Saudi Arabian Ministry of Health (MOH) registry. It included those who received COVID-19 vaccines from 17th December 2020 to 31st December 2021. The study included spontaneous self-reported adverse effects to COVID-19 vaccines where the study participants used a governmental mobile app (Sehhaty) to report their AEs following vaccination using a checklist option that included a selection of side-effects. The primary outcome was to determine AEs reported within 14 days of vaccination which included injection site itching, pain, reaction, redness, swelling, anxiety, dizziness, fever, headache, hoarseness, itchiness, loss of consciousness, nausea, heartburn, sleep disruption, fatigue, seizures, anaphylaxis, shortness of breath, wheezing, swelling of lips, face, and throat, loss of consciousness, and admissions into the intensive care unit (ICU). Results The study included a total number of 28,031 individuals who reported 71,480 adverse events (AEs); which were further classified into minor and major adverse events including ICU admissions post vaccination. Of the reported AEs, 38,309 (53. 6%) side-effects were reported following Pfizer-BioNTech, 32,223 (45%) following Oxford-AstraZeneca, and 948 (1.3%) following Moderna. The following reported AEs were statistically significant between the different vaccine types: shortness of breath\difficulty of breathing, dizziness, fever above 39°C, headache, hoarseness, injection site reactions, itchiness, nausea, sleep disruption, fatigue, wheezing, swelling of lips/face and\or throat, and loss of consciousness (p-value < 0.05). Fever and seizure were the only statistically significant AEs amongst the number of vaccine doses received (p-value < 0.05). Ten ICU admissions were reported in the 14 days observation period post-COVID-19 vaccination with the following diagnoses: acute myocardial infarction, pneumonia, atherosclerosis, acute respiratory failure, intracranial hemorrhage, grand mal seizure, Guillain-Barré syndrome, abnormal blood gas levels, and septic shock. Conclusion This study demonstrated that the most prevalent SARS-CoV-2 vaccine side-effects among adults in Saudi Arabia were mild in nature. This information will help reduce vaccine hesitancy and encourage further mass vaccination to combat the COVID-19 pandemic, especially as booster doses are now available. Further studies are warranted to obtain a better understanding of the association between risk factors and the experiencing of side-effects post vaccination.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".