Concurrent use of hydroxyurea and deferasirox in Californians with sickle cell disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: When patients with sickle cell disease have appropriate indications, they can be prescribed hydroxyurea (HU) and deferasirox (DFX) concurrently despite little knowledge about how the two medications interact. We wished to analyze whether there was evidence of adverse interaction between HU and DFX when taken simultaneously and hypothesized that those who took both drugs together had similar clinical complications when compared to those who took only one or neither drug. METHODS: We conducted this retrospective cohort investigation between 2009 and 2016 of persons with SCD in the California Sickle Cell Data Collection Program, a validated database of Californians with SCD a statewide. People in the database who took HU and DFX simultaneously for at least 3 months as compared to those who took either HU or DFX alone or to matched persons who took neither drug were eligible. RESULTS: We identified 104 people who were prescribed both HU and DFX concurrently, 877 who were prescribed HU only, and 314 who were prescribed DFX only during the study period. We identified 416 matched controls who took neither HU nor DFX. People who took both HU and DFX concurrently had similar rates of ED and inpatient encounters and had similar rates and distribution of adverse effects compared to those who took either HU or DFX alone or took neither drug. CONCLUSION: Three months of concurrent use of DFX and HU appears safe, but further studies are required to better understand the safety and effectiveness of this medication combination. (Funded by CDC, CDC Foundation, and others).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".