A Case of Proteinuria Associated With Thrombotic Microangiopathy in a Patient With Sickle Cell Disease
Bibliographic record
Abstract
Introduction: Thrombotic microangiopathy (TMA) causes renal dysfunction. Classic causes include thrombotic thrombocytopenic purpura, atypical haemolytic uremic syndrome, pregnancy, malignancy, drugs, transplant, autoimmune disease, infection, malignant hypertension, antiphospholipid (APLA) syndrome. We describe the case of patient with SCD with TMA shown on renal biopsy when evaluated for proteinuria. Case Description: A 25 year-old male with SCD (HbSS) had proteinuria (1+ on dipstick, urine PCR of 212 mg/mmol, 24-hour protein of 2.75 g) with normal renal function (creatinine 83μmol/L) on screening. He had no known renal disease, diabetes, or nephrotoxic medications (including no NSAIDs). Routine blood-work was unremarkable, aside from baseline haemolytic indices. Autoimmune, vasculitis and infectious workup was negative. Morphological review was done to confirm schistocytes were not being mistaken for sickled RBC. Renal biopsy showed changes suggestive of SCN/hypertension (Fig 1a), and TMA (Fig 1b). Work-up for TMA causes was negative - normal ADAMTS13 levels (>98%), negative blood cultures, and no APLA antibodies. Genetic studies did not show any TMA pathogenic variants in complement or coagulation genes. The TMA was thus attributed to SCD in the absence of acute pain episodes.Fig 1a:: Glomerulomegaly with arteriolar hyalinosis.Fig 1b:: Arteriole with intimal fibrinDiscussion: Case reports describe SCD-associated TMA, but these are in the setting of vaso-occlusive pain episodes, which are hypothesized to trigger TMA. Our case of SCD-associated TMA, without a pain crisis, is thus novel and proposes that SCD itself may be a secondary cause of renal TMA. Our case highlights the importance of renal biopsy for patients with SCD and proteinuria to identify if entities aside from SCN are contributory. Patients with SCD-associated TMA have responded to plasma exchange and/or RBC exchange transfusion in the setting of a pain crisis. Whether patients like ours, presenting outside a pain crisis, also respond to these therapies remains to be studied.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".