Serial renal biopsy in systemic lupus erythematosus.
Bibliographic record
Abstract
OBJECTIVE: To examine the role of sequential renal biopsies in patients with systemic lupus erythematosus (SLE), with regard to indications, morphologic change over time, and the clinical utility of repeat biopsies. METHODS: Patients with repeat renal biopsies were identified from the University of Toronto Lupus Clinic Database and their biopsies were reviewed blindly by a committee, using the WHO classification as well as activity and chronicity indices. Reasons for obtaining biopsy were documented, and therapeutic decisions following repeat biopsy were tabulated. RESULTS: Fifty-seven patients (49 F/9 M) had at least 2 renal biopsies between 1970 and 1994. The mean interval between biopsies was 4.2 years. The major reason for obtaining the first biopsy was disease diagnosis (32/57), while the majority of repeat biopsies were performed to discern the cause of increasing proteinuria (45/57). A comparison of the WHO classification of initial and repeat biopsies showed evolution to another class in 23 instances, but more commonly a change within a class was seen. A decrease in proliferative lesions (classes III and IV and subsets of V) was noted on repeat biopsies. The chronicity index increased significantly (p = 0.0001) and the activity index decreased (p = 0.064) between biopsies. Seventy-seven percent of patients had a change in treatment based on biopsy results. CONCLUSION: The major reason for repeat renal biopsy in patients with SLE was proteinuria. Renal morphology in patients with SLE can change with time, particularly in terms of chronicity and activity features. Repeat biopsies in patients with SLE appear to have clinical utility.
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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".