Synthetic ACTH for Treatment of Glomerular Diseases: A Case Series
Bibliographic record
Abstract
RATIONALE: Synthetic adrenocorticotropic hormone (Tetracosactide) has been used in the treatment of refractory glomerular diseases. Literature surrounding the use of this medication is limited to small case series and there is conflicting data on the rate of adverse events associated with this medication. PRESENTING CONCERNS OF THE PATIENT: Glomerulonephritis not in remission after at least 6 months of treatment with conservative care. Stable doses of concurrent immunosuppression were permitted. DIAGNOSES: Membranous nephropathy, IgA nephropathy, minimal change disease, and focal and segmental glomerulosclerosis. INTERVENTION: Intramuscular synthetic adrenocorticotropic hormone (Tetracosactide, Synacthen Depot) with doses of either 1 mg weekly or 1 mg twice weekly. OUTCOMES: Five of 12 patients had at least a partial remission with Tetracosactide. Median time to response was 6 months for responders. Five of the 12 patients had adverse events documented, 2 of which led to treatment discontinuation. No patients with focal and segmental glomerulosclerosis responded to treatment. LESSONS LEARNED: Higher rate of adverse events than previously reported with synthetic adrenocorticotropic hormone and uncertain treatment efficacy.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".