Clinical Outcomes and Clinico-pathological Correlations in Lupus Nephritis with Kidney Biopsy Showing Thrombotic Microangiopathy
Bibliographic record
Abstract
OBJECTIVE: Renal thrombotic microangiopathy (TMA) is an uncommon pathological finding in lupus nephritis (LN), and its clinical significance remains to be defined. METHODS: Twenty-four patients with lupus nephritis (LN) and renal TMA were selected from a retrospective review of 677 biopsy-proven LN patients, and compared with 48 LN controls without TMA (1:2 ratio) matched according to demographics and treatments. RESULTS: Renal TMA was noted in 3.5% of kidney biopsies of LN. TMA was associated with a higher prevalence of anti-Ro (45.8% vs 18.8%; p = 0.016), higher Systemic Lupus Erythematosus Disease Activity Index scores (21.4 ± 8.5 vs 10.8 ± 2.3; p < 0.001), lower estimated glomerular filtration rate (eGFR; 16.8 ± 11.7 ml/min vs 77.8 ± 28.6 ml/min; p < 0.001), and a higher percentage of patients who required dialysis (37.5% vs 2.1%; p < 0.001) at the time of kidney biopsy. Activity and chronicity indices [median (range)] were higher in the TMA group [11 (2-19) and 3 (1-8), respectively, compared with 7 (0-15) and 1 (0-3) in controls; p = 0.004 and p < 0.001; respectively]. Patients with TMA showed inferior 5-year renal survival and higher incidence of chronic kidney disease at last followup (70% and 66.6%, respectively, compared with 95% and 29.2% in controls; p = 0.023 and 0.002, respectively). The TMA group also showed lower median eGFR compared with controls [50.1 (IQR 7-132) ml/min vs 85.0 (IQR 12-147) ml/min; p = 0.003]. Five-year patient survival rate was similar between the 2 groups (87% and 98% in TMA and control group, respectively; p = 0.127). CONCLUSION: TMA in kidney biopsy was associated with more severe clinical and histological activity, and significantly inferior longterm renal outcome in LN.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".