Bibliographic record
Abstract
We are presenting a first ever published report in the English literature in a patient presenting with adverse effects of an FDA-banned medicine, Reumofan, which has been marketed to treat rheumatism, joint pain, arthritis and neuralgia. It contains undisclosed traces of dexamethasone, diclofenac and methocarbamol. Some of these adverse effects include hypertension, adrenal insufficiency, gastrointestinal bleeding and sudden death. Our patient presented with progressively worsening edema affecting upper and lower extremities, abdominal wall and face. He was ruled out for venous thrombosis, and his cardiac catheterization and transthoracic echocardiogram exhibited no evidence of heart failure. His edema was successfully treated with diuresis during his hospitalization and on follow-up visit, he was found to be adrenally insufficient and hypotensive on discontinuation of Reumofan. This case illustrates the severe adverse effects that can occur as a result of Reumofan use in a patient using this medicine to treat debilitating joint pain and reinforces the importance of a thorough medication history. J Endocrinol Metab. 2014;4(3):78-80 doi: http://dx.doi.org/10.14740/jem216w
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".