The Total Pentad: a Case Report of Thrombotic Thrombocytopenic Purpura Presenting as an Acute Cerebrovascular Accident
Bibliographic record
Abstract
Thrombotic Thrombocytopenic Purpura (TTP) is a rare blood-coagulation disorder that causes extensive thrombus formation within the blood vessels. Diagnosis of the disorder is made on the basis of identification of some or all of five clinical features, described as the typical “pentad”: thrombocytopenia, microangiopathic hemolytic anemia, fluctuating neurological symptoms, renal failure, and fever. We report the case of a middle aged female who presented to an urban teaching hospital emergency department. Her initial symptoms of TTP were subtle, making it difficult to achieve a definitive early diagnosis. Awareness of the disorder allowed us to follow through on monitoring for the pentad during the initial period of hospitalization and facilitated the diagnosis, which led to prompt and appropriate treatment. The patient made a complete and sustained recovery. Since prompt institution of plasmapheresis is essential to recovery, we share this case in order to increase the possibility that TTP will be considered in the differential diagnosis of patients presenting with all or part of the total pentad.
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) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".