Case Report: Segmental Arterial Mediolysis, a Rare Cause of Hypertension
Bibliographic record
Abstract
RATIONALE: The differential diagnosis for hypertension with elevated plasma renin is broad. This case illustrates one of the rarer, and therefore underrecognized, causes of high renin hypertension. PRESENTING CONCERNS OF THE PATIENT: A 41-year-old man with a medical history significant for multiple ischemic strokes and dyslipidemia presented for assessment of decreased renal function and resistant hypertension. His initial workup for secondary causes of hypertension was remarkable for an elevated plasma renin and normal aldosterone. Further investigation with computed tomography (CT) angiography was performed, which demonstrated multiple bilateral renal aneurysms and infarcts. DIAGNOSES: After ruling out other potential causes of bilateral renal aneurysms and infarcts, a diagnosis of segmental arterial mediolysis (SAM) was made. INTERVENTIONS: Optimization of antihypertensive regimen, counseling regarding regular home blood pressure monitoring, and smoking cessation. OUTCOMES: The patient achieved excellent blood pressure control, stable renal function, and had no further strokes or other vascular events. TEACHING POINTS: Our case demonstrates the importance of considering SAM in the diagnosis of hypertension with elevated plasma renin and as a vasculitis mimic. It also highlights the importance of considering renal vascular imaging in the workup of resistant hypertension.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| 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".