Management of <scp>CLL</scp> patients early in the <scp>COVID</scp>‐19 pandemic: An international survey of <scp>CLL</scp> experts
Bibliographic record
Abstract
infection has been detected in 55% (6/11) of cases: two had contacts with COVID-19 positive subjects, and four had occupational exposure (three are nurses working in hospital or assisted living facilities). Three patients were asymptomatic. One patient (#3 in supplementary information) was admitted for high fever and bone marrow hypoplasia, lymphopenia, and agranulocytosis (on treatment with deferiprone) and tested positive at the third swab. Six out of 11 were hospitalized, but no one required mechanical ventilation. The patient with more severe symptoms who required more intensive ventilation support with continuous positive airway pressure (CPAP) has a history of diffuse large B-cell lymphoma, treated with chemotherapy in the previous year, currently in complete remission. Of the six people admitted to the hospital, only three received supposedly specific treatment for COVID-19: one hydroxychloroquine (HCQ), one HCQ plus ritonavir/darunavir, and one HCQ plus anakinra. Patient #3 did not receive HCQ due to concomitant therapy with amiodarone and an increased risk of life-threatening arrhythmia. The clinical course ranged from 10 to 29 days. Ten patients have clinically recovered and are on a daily remote phone call follow-up. Splenectomy which was present in 8/11 patients did not seem to affect the clinical course. Of note, except for the patient with myelosuppression, no increase in blood requirement was observed. When luspatercept treatment was halted in the NTDT patient, hemoglobin fell from 110 to 82 g/L, a value similar to the pre-luspatercept period. Neither death nor severe SARS or signs of cytokines storm were observed in these 11 subjects, which may be surprising, taking into account the mean age and the presence of severe comorbidities. Our data, although preliminary, do not indicate increased severity of COVID-19 in TS. A larger number of cases needs to be collected to define the impact of this new infection and its outcome in these fragile patients.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".