Recurrent heparin‐induced thrombocytopenia due to heparin rinsing before priming the machine in a hemodialysis patient: A case report
Bibliographic record
Abstract
Abstract Heparin has remained the most commonly used anticoagulant for patients undergoing hemodialysis. It is usually safe to use but can have severe adverse effects in some cases. Heparin‐induced thrombocytopenia (HIT) is a life‐threatening complication of exposure to heparin. It results from an autoantibody directed against endogenous platelet factor 4 (PF4) in complex with heparin, which activates platelets and can cause catastrophic arterial and venous thromboses. Here, we present the case of an 80‐year‐old woman with a recent diagnosis of chronic renal failure who developed acute HIT (platelet count nadir, 15 × 109/L) on day 7 of hemodialysis performed with routine heparin anticoagulation, who despite subsequent heparin‐free hemodialysis (with argatroban and warfarin) developed recurrent HIT (complicated by acute cerebral infarction) on day 11 that we attributed to “rinsing” of the circuit with heparin‐containing saline (3,000 units of unfractionated heparin, with subsequent saline washing) performed pre‐dialysis as per routine. After stopping heparin rinsing, the platelet count recovered completely, without further thrombotic or other sequelae. Our experience indicates that for patients with acute HIT, besides the well‐known practice of using non‐heparin anticoagulation during dialysis and avoiding heparin “locking” of dialysis catheters, it is also important to avoid inadvertent rinsing of the circuit with heparin during preparation for hemodialysis.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| 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".