Rapid Progression of Focal Segmental Glomerulosclerosis in Patients with High-Risk APOL1 Genotypes
Bibliographic record
Abstract
BACKGROUND: FSGS is a heterogeneous diagnosis with a guarded prognosis. Polymorphisms in the apolipoprotein L1 ( APOL1 ) gene are associated with developing FSGS and faster progression to kidney failure in affected patients. Better understanding the natural history of patients with FSGS and APOL1 risk alleles is essential to improve patient care and support the design and interpretation of interventional studies. The objective of this study was to evaluate the quantitative association between APOL1 and kidney disease progression and the interaction with other clinical and laboratory factors. METHODS: CureGN cohort study participants with biopsy diagnosis of FSGS, regardless of self-identified race, were included. The exposure of interest was two APOL1 risk alleles (high risk) versus zero to one risk alleles (low risk). The primary outcome was eGFR slope categorized as rapid progressor (eGFR slope ≤-5 ml/min per year), intermediate progressor (slope between 0 and -5), or nonprogressor (slope ≥0). Multivariable ordinal logistic and linear regressions were used for adjusted analyses. Missing data were addressed using multiple imputation. RESULTS: Of 650 participants, 476 (73%) had genetic testing, among whom 87 (18%) were high risk. High-risk participants were more likely to have lower median eGFR (62 [interquartile range, 36-81] versus low-risk participants 76 ml/min per 1.73 m 2 [interquartile range, 44-106]; P <0.01). In adjusted analysis, the odds of more rapid progression of eGFR was 2.75 times higher (95% confidence interval, 1.67 to 4.53; P <0.001) in the high-risk versus low-risk groups. CONCLUSIONS: In patients with FSGS, high-risk APOL1 genotype is the predominant factor associated with more rapid loss of kidney function.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".