Thyrotoxic Periodic Paralysis in the Post-COVID Era: A Case Report with Literature Review
Bibliographic record
Abstract
Thyrotoxic Periodic Paralysis (TPP) is an acute potentially lethal emergency in patients with hyperthyroidism who present with sudden muscle weakness and hypokalemia. It is commonly precipitated by high carbohydrate or high salt content meals, strenuous exercise, stress, trauma, glucocorticoids, epinephrine, alcohol, or respiratory infections. COVID-19 infection or vaccination may represent a novel trigger for TPP. Furthermore, COVID-19 infection or vaccination may incite inflammatory processes leading to thyrotoxicosis, which can manifest as TPP. While COVID-19 causing subacute thyroiditis, euthyroid sick syndrome, Hashimoto’s disease, or Graves’ disease have been well documented in the literature; there have only been six case reports of post-COVID-19 TPP. Notably, all cases thus far have been restricted to male patients, and there is paucity of literature from North America. The purpose of this paper is to outline the first case of post-COVID-19 TPP in a female patient, who presented to the emergency department with acute paralysis and severe hypokalemia (2.2 mmol/L) three months after COVID-19 infection. Investigations in the emergency department showed thyrotoxicosis. She was treated with potassium replacement, which improved her paralysis. Subsequent investigations revealed severe hyperthyroidism from Graves’ disease, which is currently managed with metoprolol and methimazole. Her hyperthyroidism improved without recurrent hypokalemia or paralysis. In addition, we outline the epidemiology, pathophysiology, precipitants, and management of TPP, with a particular focus on COVID-19 infection or vaccination precipitating TPP. We discuss post-COVID-19 TPP cases thus far described in the literature. Knowing that North American COVID-19 infection waves lagged Asia, we could anticipate additional future TPP cases.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".