Prospective Evaluation of Kidney Function in Long-Term Survivors of Pediatric CNS Tumors
Bibliographic record
Abstract
Purpose: Numerous acute effects of chemotherapeutics on kidney function are well described. However, data on the long-term effects of chemotherapy in the growing population of childhood central nervous system (CNS) tumor survivors is limited. We aimed to evaluate the kidney function of a cohort of long-term CNS tumor survivors treated with different standard chemotherapeutic regimens. Methods: Patients treated for a CNS tumor were prospectively evaluated up to 12 years after completion of their therapy. Examination of kidney function was performed during routine follow-up visits. Blood pressure and blood and urine parameters were analyzed for kidney function evaluation. Glomerular function was assessed by calculating the estimated glomerular filtration rate (eGFR), tubular functions were analyzed by measuring serum electrolytes, bicarbonate and phosphate reabsorption, and proteinuria was assessed by calculating the protein/creatinine ratio and phosphate reabsorption. Results: None of the 65 patients evaluated suffered from clinically relevant kidney impairment (eGFR < 90 mL/min/L, 73 m2). There was no association between chemotherapy dose and eGFR. Only two patients showed mild signs of tubulopathy and 11 patients were diagnosed with elevated blood pressure. Conclusion: With adequate supportive measures, such as sufficient hydration according to chemotherapy protocol guidelines, as well as avoidance or close monitoring of additional nephrotoxic medication, impaired kidney function is rare in CNS tumor survivors treated with standard chemotherapy. Nonetheless, long-term follow-up is essential for early detection of mild impairment of kidney function.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".