Isolated immune thrombocytopenic purpura in a young adult Covid-19 patient.
Bibliographic record
Abstract
OBJECTIVE: Patients with Covid-19 can have different symptoms, ranging from asymptomatic patients to various grades of respiratory failure, caused by typical interstitial pneumonia, cardiac involvement or neurological symptoms. PATIENTS AND METHODS: In April 2020, we focused our attention on a young woman with diffused purpura on her lower extremities, with no respiratory, cardiac or neurological symptoms. A complete blood analysis showed us a severe thrombocytopenia. We excluded other possible causes of thrombocytopenic purpura such as hematological (lymphocyte subsets), hepatological disease or splenomegaly. On autoimmune screening, we found Isolated immune thrombocytopenic purpura in a young adult Covid-19 patient positivity of anti-nuclear antibody (ANA) with a centrosome pattern and extractable nuclear antigens (ENA) and connective tissue disease screen resulted positive but none of the included specific antigens results positive, probably due to an aspecific antibody reaction. The wide variability of COVID disease presentation may be due to a personal different immune response to the virus. CONCLUSIONS: The immune response against the virus is crucial in the evolution and understanding of COVID-19 disease but it has still to be fully understood.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".