Unfractionated Heparin in SARS-CoV-2 Pneumonia: Ischemic Stroke Case Report
Bibliographic record
Abstract
Thromboembolism is a known phenomenon in patients with Coronavirus disease 2019 (COVID-19). Recent investigations have revealed that a significant proportion of those hospitalized with severe COVID-19 demonstrate clinical and laboratory markers compatible with hypercoagulability, which is differentiated from disseminated intravascular coagulation (DIC), termed COVID-associated coagulopathy. Additionally, there is increasing concern for development of acute ischemic stroke because of this hypercoagulable state. We present a patient with COVID-19 pneumonia who was managed with unfractionated heparin (UFH) infusion and developed a large ischemic infarct shortly after cessation of the infusion. In retrospect, the patient's coagulation parameters were consistent with overt DIC, although some of these parameters are easily masked by the effects of UFH. These findings emphasize the importance of anticoagulation as well as its careful discontinuation, as failure to do so may result in a significant thromboembolic event.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.002 |
| 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".