Bibliographic record
Abstract
Lupus Nephritis (LN) is a common and severe manifestation of systemic lupus erythematosus (SLE), impacting up to 40% of SLE patients. Despite advancements in understanding the pathogenesis of LN, outcomes have not significantly improved since the early 2000s. LN patients face higher mortality, emphasizing the importance of achieving disease remission. Screening for nephritis involves regular monitoring, especially within the first 5 years of SLE diagnosis. Monitoring includes urinalysis, serum creatinine, and immune serology. Kidney biopsy remains the gold standard for LN diagnosis and classification, providing crucial information for treatment decisions. The standard of care involves hydroxychloroquine for all LN patients, with immunosuppressive treatments tailored to the histologic class. The recently approved medications, belimumab and voclosporin, offer additional therapeutic alternatives. Approximately 20% of LN patients exhibit features of thrombotic microangiopathy, warranting anticoagulation. Optimizing glucocorticoid dosing is recommended, favouring lower doses to minimize adverse effects. Lifelong monitoring is essential, as flares can occur at any point, emphasizing the need for continued immunosuppression. Given the lack of renal response in 30–60% of patients, the addition of combination therapies, such as calcineurin inhibitors or belimumab, should be considered. Duration of treatment is crucial, considering the progressive loss of podocytes and nephron function, which may lead to chronic kidney disease. Regular monitoring, maintenance immunosuppression, and lifestyle modifications contribute to preventing flares and improving long-term outcomes for LN patients.
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.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.010 |
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".