The role of plasma exchange in treating post-transplant focal segmental glomerulosclerosis: A systematic review and meta-analysis of 77 case-reports and case-series
Bibliographic record
Abstract
BACKGROUND: Evidence on the role of plasma exchange for treating recurrent post-transplant focal segmental glomerulosclerosis (FSGS) comes largely from individual cases and uncontrolled series. We conducted a systematic review and meta-analysis to estimate the remission rate after treatment with plasma exchange, and to determine if remission varied with patient or treatment characteristics. METHODS: We searched MEDLINE, EMBASE, Science Citation Index Expanded, and the Conference Proceedings Citation Index (Science and BIOSIS) for studies of patients with post-transplant recurrent FSGS who were treated with plasma exchange after recurrence (1950-2012). Of 678 studies screened, 77 met our inclusion criteria: 34 case reports (45 patients) and 43 case series (378 patients). We extracted patient-level data from each study and used random-effects models to calculate remission, defined as proteinuria <3.5 g/day (partial) or <0.5 g/day (complete). RESULTS: The overall remission rate in 423 patients with outcome data was 71 % (95 % CI: 66 % to 75 %). In 235 patients with data on age, remission was similar for adults and children: 69.1 % (95 % CI: 59.6 % to 77.2 %) and 70.2 % (95 % CI: 61.1 % to 77.9 %). Males were more likely to achieve remission (OR = 2.85; 95 % CI: 1.44 to 5.62) and patients treated within 2 weeks of recurrence showed a trend towards higher likelihood of remission (OR = 2.16; 95 % CI: 0.93 to 5.01). Proteinuria >7 g/day at recurrence was inversely associated with remission (OR = 0.43; 95 % CI: 0.19 to 0.97). Age and type of kidney transplant (living vs. deceased) did not associate with remission. CONCLUSION: In this systematic review of patients with recurrent post-transplant FSGS, 71 % of patients achieved full or partial remission after treatment with plasma exchange; however, extensive missing data and lack of a control group limit any conclusions on causality.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.024 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".