Pregnancy outcomes in patients with chronic myeloid leukemia treated with imatinib mesylate: short report from a developing country
Bibliographic record
Abstract
Treatment of chronic myeloid leukemia (CML) is challenging in patients who want to conceive. We followed 809 patients with CML treated with imatinib mesylate (IM). We observed outcomes in 90 pregnancies from 61 patients (21 females, 40 males) who conceived while on IM. Information was obtained on duration of exposure to IM, pregnancy termination and congenital abnormalities. Hematologic and cytogenetic responses were also recorded. Twenty-eight pregnancies occurred among females, while 62 were reported from male patients. Among female patients, 19 (67.9%) pregnancies were uneventful while six (21.4%) ended in adverse events. Only 12 (57%) females reported their pregnancies. Three (4.4%) adverse events were reported from male patients. Pregnancy is an important part of life in our young patients due to cultural and societal pressures. It is paramount to counsel pregnant patients to switch to drugs with no adverse effect on the developing fetus. However, lack of communication is a major factor preventing physicians from counseling patients about conception.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".