Adverse Long-Term Outcomes following AKI in Hospitalized Children: A Meta-Analysis
Bibliographic record
Abstract
Background: Acute kidney injury (AKI) is common during pediatric hospitalizations and is associated with adverse short-term outcomes. However, long-term outcomes among survivors of pediatric AKI remain uncertain. We performed a systematic review to determine the risk of long-term outcomes following an episode of AKI. Methods: We conducted a systematic literature search in EMBASE, PubMed, and Web of Science for studies reporting adverse events at least three months following AKI defined using standardized definitions in participants aged <18 year. We excluded studies if they reported outcomes in children with obstructive lesions, renal vascular disorder (i.e HUS), or solid organ transplantations. Random effect meta-analyses were performed to calculate pooled estimates. Results: Of 12817 records identified through our initial search, 38 studies (14892 participants) were included in the final analysis. Pooled cumulative incidence of participants with CKD, mortality, proteinuria, and hypertension was 16% (95% CI: 12 to 19), 6% (3 to 8), 19% (11 to 26) and 13% (10 to 17) respectively, following an episode of AKI. Only 24 studies with follow up period ranging from 6 months to 15 years included a comparator group of patients without AKI. The odds of developing CKD was higher among children with AKI as compared to those without AKI (OR: 1.57, 95% CI: 1.05 to 2.35; Figure 1). Mortality was also higher after AKI (OR: 1.84, 95% CI: 1.28 to 2.63). There was no significant association between AKI and proteinuria (OR: 1.13, 0.63 to 2.03) or hypertension (OR: 1.27, 0.75 to 2.15) at follow up. Conclusion: Children with AKI are at a higher risk of developing long-term CKD and mortality. These findings support enhanced surveillance of kidney function after an episode of AKI, with the aim of improving long-term kidney and patient survival.Pooled odds ratio of chronic kidney disease
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.055 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".