Review of Glomerular Diseases: Focal Segmental Glomerulosclerosis (FSGS) and Minimal Change Disease (MCD)
Bibliographic record
Abstract
Purpose: Idiopathic focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) are chronic glomerulopathies which may compromise patients’ quality of life, and for which there is no cure. This literature review aimed to summarize our current understanding of the pathophysiology, clinical characteristics, and best available treatment for the two conditions in order to outline a consolidated treatment protocol and identify future research considerations. Methods: PubMed was systematically searched by a single reviewer in order to identify primary studies pertaining to the diagnosis, treatment and classification of FSGS and MCD. Additionally, a hand search of UpToDate was conducted to glean further information about the best available evidence as summarized for clinician use. Relevant information was extracted and synthesized. Results: Primary FSGS and MCD result from distinct pathogenic mechanisms, hypothesized to involve kidney injury via immune dysregulation. Patients require a kidney biopsy for diagnostic purposes. First-line treatment involves glucocorticoids (i.e. prednisone), although patients’ responsiveness may be inconsistent; second-line treatment is immunotherapy. Conclusion: This review summarized clinically-important information about FSGS and MCD, and emphasized the need for further research in the field of clinical nephrology. Large scale trials such as the Cure Glomerulonephropathy should be conducted to gather information about the affected population.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".