Case Report: Atheroembolic renal disease in a 72‐year‐old patient through coronary intervention after myocardial infarction
Bibliographic record
Abstract
Cholesterol embolization or atheroembolic renal disease (AERD) is an often underdiagnosed issue in patients featuring a prevalent risk profile. It is a multisystemic disease with progressive renal insufficiency due to foreign body reaction of cholesterol crystals flushed into a small vessel system of the kidneys from the arteriosclerotic plaques. The most common setting in which it occurs is iatrogenic after vascular catheterization and less frequent spontaneously. Typical clinical symptoms are delayed impairment of renal function, cutaneous manifestations such as livedo reticularis or purple toes with persistingly palpable arterial pulse, myalgia, systemic symptoms such as weight loss and fever, and abdominal and neurological symptoms. Diagnosis is generally made by clinical appearance, risk profile, and interval of time from intervention; a definitive diagnosis can only be made by renal biopsy. Even though the exact incidence is not known because most patients do not undergo biopsy due to older age, comorbidity, and other explanations for loss of renal function, it is estimated to be 4% after vascular intervention. Patient and renal outcome is dependent on comorbidity, risk profile, and preexisting chronic kidney disease (CKD). About 30% of patients are estimated to require maintenance dialysis and these patients have a high risk of death within 24 months after the first renal replacement therapy. Prognosis is also influenced by severity. The case reported is a 72-year-old male patient with preexisting CKD stage 3 undergoing percutaneous coronary intervention after myocardial infarction and consecutive AERD with typical clinical appearance 6 weeks after the event.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".