New Onset of Type 1 Diabetes Mellitus Post-COVID-19 Vaccine
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with an increased morbidity and mortality worldwide. Coronavirus disease 2019 (COVID-19) vaccines have shown high efficacy in preventing the infection but with many possible side effects such as hyperglycemia. New-onset diabetes mellitus (DM) and severe metabolic complications have been reported post-vaccination. Here we report a 45-year-old woman who came to the hospital complaining of polyurea, polydipsia, and weight loss 3 weeks after the first activation dose of COVID-19 vaccine. Her hemoglobin A1c (HbA1c) upon presentation was 9% without any prior history of DM. She was diagnosed with type 1 diabetes mellitus (T1DM), as the anti-glutamic acid decarboxylase (GAD) antibody was positive and complicated during follow-up with diabetic ketoacidosis (DKA). This is the first case in Saudi Arabia suggesting that the COVID-19 RNA-based vaccines might cause new onset of T1DM, complicated by late DKA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".