The Challenge of Diagnosing Atheroembolic Renal Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Atheroembolic renal disease (AERD) is caused by showers of cholesterol crystals released by eroded atherosclerotic plaques. Embolization may occur spontaneously or after angiographic/surgical procedures. We sought to determine clinical features and prognostic factors of AERD. METHODS AND RESULTS: Incident cases of AERD were enrolled at multiple sites and followed up from diagnosis until dialysis and death. Diagnosis was based on clinical suspicion, confirmed by histology or ophthalmoscopy for all spontaneous forms and for most iatrogenic cases. Cox regression was used to model time to dialysis and death as a function of baseline characteristics, AERD presentation (acute/subacute versus chronic renal function decline), and extrarenal manifestations. Three hundred fifty-four subjects were followed up for an average of 2 years. They tended to be male (83%) and elderly (60% >70 years) and to have cardiovascular diseases (90%) and abnormal renal function at baseline (83%). AERD occurred spontaneously in 23.5% of the cases. During the study, 116 patients required dialysis, and 102 died. Baseline comorbidities, ie, reduced renal function, presence of diabetes, history of heart failure, acute/subacute presentation, and gastrointestinal tract involvement, were significant predictors of event occurrence. The risk of dialysis and death was 50% lower among those receiving statins. CONCLUSIONS: Clinical features of AERD are identifiable. These make diagnosis possible in most cases. Prognosis is influenced by disease type and severity.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it