Glomerulonephritis during Mycobacterium tuberculosis infection: scoping review
Bibliographic record
Abstract
INTRODUCTION: People with Tuberculosis (TB) infection may present with glomerulonephritis (GN). The range of presentations, renal pathologies, and clinical outcomes are uncertain. Whether clinical features that establish if GN etiology is medication or TB related, and possible benefits of immunosuppression remain uncertain. METHODS: A scoping review was completed, searching MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Web of Science and Conference Abstracts from Inception to December, 2023. The study population included patients with TB infection who developed GN and underwent renal biopsy. All data regarding presentation, patient characteristics, renal pathology, management of TB and GN, and outcomes were summarized. RESULTS: There were 62 studies identified, with 130 patients. These cases included a spectrum of presentations including acute kidney injury, nephrotic syndrome and hypertension, and a range of 10 different renal pathology diagnoses. Cases that included immunosuppression and outcomes ranged from complete remission to long-term dialysis dependence. The presence of granulomas (4/4, 100%), anti-glomerular basement membrane disease (3/3, 100%), amyloidosis (75/76, 98.7%), and focal segmental glomerulosclerosis (2/2, 100%) were specific for GN being TB-infection related. On the other hand, minimal change disease was specific for anti-TB therapy related (7/7, 100%). While patients with more aggressive forms of GN commonly were prescribed immunosuppression, this study was unable to confirm efficacy. Only rifampin or isoniazid were implicated in drug-associated GN. DISCUSSION: This study provides a clear rationale for renal biopsy in patients with TB and GN, and outlines predictors for the GN etiology. Thus, this study establishes key criteria to optimize diagnosis and management of patients with TB and GN.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| 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".