Social Deprivation and Incidence of Pediatric Kidney Failure in France
Bibliographic record
Abstract
Introduction: Approximately 8 per million children and young adults aged < 20 years initiate kidney replacement therapy (KRT) per year in France. We hypothesize that social deprivation could be a determinant of childhood-onset kidney failure. The objective of this study was to estimate the incidence of pediatric KRT in France according to the level of social deprivation. Methods: All patients < 20 years who initiated KRT from 2010 to 2015 in metropolitan France were included. Data were collected from the comprehensive French registry of KRT French Renal Epidemiology and Information network (REIN). We used a validated ecological index to assess social deprivation, the 2011 French version of the European Deprivation Index (EDI). We estimated the age standardized incidence rates according to the quintiles of EDI using direct standardization and incidence rate ratio using Poisson regression. Results: We included 672 children with kidney failure (58.6% males, 30.7% with glomerular or vascular disease, 43.3% starting KRT between 11 and 17 years). 38.8% were from the most deprived areas (quintile 5 of EDI). The age standardized incidence rate increased with quintile of EDI, from 5.45 (95% confidence interval [CI] = 4.25-6.64) per million children per year in the least deprived quintile to 8.46 (95% CI = 7.41-9.51) in the most deprived quintile of EDI (incidence rates ratio Q5 vs. Q1 1.53-fold; 95% CI = 1.18-2.01). Conclusion: This study showed that even in a country with a universal health care system, there is a strong association between the incidence of pediatric KRT and social deprivation showing that social health inequalities appear from KRT initiation. This study highlights the need to look further into social inequalities in the earliest stage of chronic kidney disease (CKD).
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".