Treatment with Glucocorticoids or Calcineurin Inhibitors in Primary FSGS
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: In primary FSGS, calcineurin inhibitors have primarily been studied in patients deemed resistant to glucocorticoid therapy. Few data are available about their use early in the treatment of FSGS. We sought to estimate the association between choice of therapy and ESRD in primary FSGS. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We used an inception cohort of patients diagnosed with primary FSGS by kidney biopsy between 1980 and 2012. Factors associated with initiation of therapy were identified using logistic regression. Time-dependent Cox models were performed to compare time to ESRD between different therapies. RESULTS: In total, 458 patients were studied (173 treated with glucocorticoids alone, 90 treated with calcineurin inhibitors with or without glucocorticoids, 12 treated with other agents, and 183 not treated with immunosuppressives). Tip lesion variant, absence of severe renal dysfunction (eGFR≥30 ml/min per 1.73 m(2)), and hypoalbuminemia were associated with a higher likelihood of exposure to any immunosuppressive therapy. Only tip lesion was associated with initiation of glucocorticoids alone over calcineurin inhibitors. With adjusted Cox regression, immunosuppressive therapy with glucocorticoids and/or calcineurin inhibitors was associated with better renal survival than no immunosuppression (hazard ratio, 0.49; 95% confidence interval, 0.28 to 0.86). Calcineurin inhibitors with or without glucocorticoids were not significantly associated with a lower likelihood of ESRD compared with glucocorticoids alone (hazard ratio, 0.42; 95% confidence interval, 0.15 to 1.18). CONCLUSIONS: The use of immunosuppressive therapy with calcineurin inhibitors and/or glucocorticoids as part of the early immunosuppressive regimen in primary FSGS was associated with improved renal outcome, but the superiority of calcineurin inhibitors over glucocorticoids alone remained unproven.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".