Neurocognitive and Educational Outcomes in Children and Adolescents with CKD
Bibliographic record
Abstract
Background and objectives Poor cognition can affect educational attainment, but the extent of neurocognitive impairment in children with CKD is not well understood. This systematic review assessed global and domain-specific cognition and academic skills in children with CKD and whether these outcomes varied with CKD stage. Design, setting, participants, & measurements Electronic databases were searched for observational studies of children with CKD ages 21 years old or younger that assessed neurocognitive or educational outcomes. Risk of bias was assessed using a modified Newcastle–Ottawa scale. We used random effects models and expressed the estimates as mean differences with 95% confidence intervals stratified by CKD stage. Results Thirty-four studies (25 cross-sectional, n =2095; nine cohort, n =991) were included. The overall risk of bias was high because of selection and measurement biases. The global cognition (full-scale intelligence quotient) of children with CKD was classified as low average. Compared with the general population, the mean differences (95% confidence intervals) in full-scale intelligence quotient were −10.5 (95% confidence interval, −13.2 to −7.72; all CKD stages, n =758), −9.39 (95% confidence interval, −12.6 to −6.18; mild to moderate stage CKD, n =582), −16.2 (95% confidence interval, −33.2 to 0.86; dialysis, n =23), and −11.2 (95% confidence interval, −17.8 to −4.50; transplant, n =153). Direct comparisons showed that children with mild to moderate stage CKD and kidney transplants scored 11.2 (95% confidence interval, 2.98 to 19.4) and 10.1 (95% confidence interval, −1.81 to 22.0) full-scale intelligence quotient points higher than children on dialysis. Children with CKD also had lower scores than the general population in executive function and memory (verbal and visual) domains. Compared with children without CKD, the mean differences in academic skills ( n =518) ranged from −15.7 to −1.22 for mathematics, from −9.04 to −0.17 for reading, and from −14.2 to 2.53 for spelling. Conclusions Children with CKD may have low-average cognition compared with the general population, with mild deficits observed across academic skills, executive function, and visual and verbal memory. Limited evidence suggests that children on dialysis may be at greatest risk compared with children with mild to moderate stage CKD and transplant recipients.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".