Bibliographic record
Abstract
We present the case of a man in his 70s who developed acute confusion from hypertensive encephalopathy triggered by indomethacin. He was recently prescribed indomethacin, a non-steroidal anti-inflammatory drug (NSAID) for headaches. However, his headaches were in the context of worsening hypertension that was treated with trandolapril. The use of indomethacin consequently worsened his underlying condition. On presentation to the emergency department, his blood pressure was 190/110 mmHg. Bloodwork including electrolytes, glucose, metabolic studies, renal and liver function were within normal limits; infectious workup including blood and urine cultures subsequently returned negative; and brain computed tomography and magnetic resonance imaging revealed no acute process to explain his presentation. Indomethacin was discontinued and the patient's hypertension was treated with amlodipine. Both his confusion and underlying headaches resolved as his blood pressure normalized. The patient was diagnosed with hypertensive encephalopathy triggered by indomethacin. NSAID use can trigger blood pressure decompensation, especially in patients with underlying hypertension; this effect is particularly pronounced in patients treated with anti-hypertensive medications that inhibit the renin-angiotensin-aldosterone (RAS) system. Symptomatic treatment with NSAIDs is not without potential harm; it is important to carefully consider a patient's underlying diagnosis, indication for therapy and risk for adverse effects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".