Association between AKI during Cisplatin Therapy in Children with CKD and Hypertension at 12 and 36 Months after Therapy End
Bibliographic record
Abstract
Background: Cisplatin (CisP) may cause acute kidney injury (AKI) in children treated for cancer. Predicting post-CisP chronic kidney disease (CKD) or elevated blood pressure or hypertension (≥eBP) remains elusive. We determined: 1) adjusted associations of AKI during CisP therapy with CKD and ≥eBP at 12 and 36 months(M) post-therapy end; 2) whether CKD and ≥eBP at 3M are associated with CKD and ≥eBP at 12 and 36M after CisP therapy end. Methods: Multicenter prospective study of children treated with CisP followed throughout therapy and for 36M post-therapy end. Exclusion: pre-existing kidney conditions. Urine, blood, BP collected at 3, 12, and 36M post-CisP therapy. Exposures: a) serum creatinine (SCr)-AKI any time during CisP therapy, per KDIGO; b) severe electrolyte-defined AKI (eAKI) during CisP therapy per National Cancer Institute (NCI) v4.0 criteria; c) composite AKI (SCr-AKI and severe eAKI); d) presence of CKD or ≥eBP at 3M post-CisP therapy end. Outcomes at 12 and 36M post-CisP therapy: a) CKD (per KDIGO); b)≥eBP (per AAP guidelines); c) composite of CKD or ≥eBP. Analysis: 1) multiple logistic regression (MLR) to evaluate AKI – outcome association (stepwise covariate selection); 2) MLR to evaluate association between 3M and 12M/36M outcomes (for AKI interaction). Results: Table shows prevalence of CKD and ≥eBP at 12 and 36M. Patients with SCr-AKI, eAKI and composite AKI were more likely to have ≥eBP at 12M. CKD or ≥eBP at 3M did not predict outcome presence at 12 and 36M (Table 1). However, patients with vs. without CKD at 12M were 4.8 times more likely to have CKD at 36M (Table 1). Conclusion: HTN and CKD were common at 12 and 36M post-CisP therapy. AKI during therapy was associated with ≥eBP at 12M, but the presence of kidney or BP outcomes at 3M did not predict later CKD or HTN. Novel methods to predict kidney health outcomes and interventions to reduce AKI during therapy should be investigated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".