A Prospective Observational Survey on the Long-Term Effect of LDL Apheresis on Drug-Resistant Nephrotic Syndrome
Bibliographic record
Abstract
BACKGROUND/AIMS: LDL apheresis (LDL-A) is used for drug-resistant nephrotic syndrome (NS) as an alternative therapy to induce remission by improvement of hyperlipidemia. Several clinical studies have suggested the efficacy of LDL-A for refractory NS, but the level of evidence remains insufficient. A multicenter prospective study, POLARIS (Prospective Observational Survey on the Long-Term Effects of LDL Apheresis on Drug-Resistant Nephrotic Syndrome), was conducted to evaluate its clinical efficacy with high-level evidence. METHODS: Patients with NS who showed resistance to primary medication for at least 4 weeks were prospectively recruited to the study and treated with LDL-A. The long-term outcome was evaluated based on the rate of remission of NS 2 years after treatment. Factors affecting the outcome were also examined. RESULTS: A total of 58 refractory NS patients from 40 facilities were recruited and enrolled as subjects of the POLARIS study. Of the 44 subjects followed for 2 years, 21 (47.7%) showed remission of NS based on a urinary protein (UP) level <1.0 g/day. The UP level immediately after LDL-A and the rates of improvement of UP, serum albumin, serum creatinine, eGFR, and total and LDL cholesterol after the treatment session significantly affected the outcome. CONCLUSIONS: Almost half of the cases of drug-resistant NS showed remission 2 years after LDL-A. Improvement of nephrotic parameters at termination of the LDL-A treatment was a predictor of a favorable outcome.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".