Neurodevelopment in children exposed in utero to cyclosporine and azathioprine following maternal renal transplant: preliminary results
Bibliographic record
Abstract
Background Cyclosporine and azathioprine are the most commonly used drugs to prevent rejection of transplanted organs. Pregnancy following renal transplantation can be associated with risks for both the mother and the fetus, therefore it is essential to study the reproductive safety of these drugs. Objectives To evaluate the prenatal effects of cyclosporine and azathioprine on children's neurodevelopment following maternal renal transplant, and to compare to control children. Study design Prospective cohort with matched controls. Methods Exposed children were assessed using the Wechsler Preschool and Primary Scales of Intelligence–Revised, the Wechsler Intelligence Scale for Children-III, the Developmental Neuropsychological Assessment, the Preschool Language Scale-III, and the Clinical Evaluation of Language Fundamentals-III. The preliminary results of the exposed children were compared to standard norms. Results Currently, the 20 exposed children (age 3 to13 years) were not significantly different from the norms on Global, Verbal, and Performance IQ (103 + 15; 105 + 16; and 101 + 14 respectively). The exposed children appear to have language scores (Total 112 + 8; Expressive 111 + 10; and Auditory 112 + 7) in the upper range of the norms. Conclusion These preliminary results are reassuring and may contribute to informed decision making, by pregnant women and health professionals. Clinical Pharmacology & Therapeutics (2004) 75, P74–P74; doi: 10.1016/j.clpt.2003.11.278
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".