Comorbidities in Chronic Pediatric Peritoneal Dialysis Patients: A Report of the International Pediatric Peritoneal Dialysis Network
Bibliographic record
Abstract
UNLABELLED: BACKGROUND, OBJECTIVES, AND METHODS: Hospitalization and mortality rates in pediatric dialysis patients remain unacceptably high. Although studies have associated the presence of comorbidities with an increased risk for death in a relatively small number of pediatric dialysis patients, no large-scale study had set out to describe the comorbidities seen in pediatric dialysis patients or to evaluate the impact of those comorbidities on outcomes beyond the newborn period. In the present study, we evaluated the prevalence of comorbidities in a large international cohort of pediatric chronic peritoneal dialysis (CPD) patients from the International Pediatric Peritoneal Dialysis Network registry and began to assess potential associations between those comorbidities and hospitalization rates and mortality. RESULTS: Information on comorbidities was available for 1830 patients 0 - 19 years of age at dialysis initiation. Median age at dialysis initiation was 9.1 years [interquartile range (IQR): 10.9], median follow-up for calculation of hospitalization rates was 15.2 months (range: 0.2 - 80.9 months), and total follow-up time in the registry was 2095 patient-years. At least 1 comorbidity had been reported for 602 of the patients (32.9%), with 283 (15.5%) having cognitive impairment; 230 (12.6%), motor impairment; 167 (9.1%), cardiac abnormality; 76 (4.2%), pulmonary abnormality; 212 (11.6%), ocular abnormality; and 101 (5.5%), hearing impairment. Of the 150 patients (8.2%) that had a defined syndrome, 85% had at least 1 nonrenal comorbidity, and 64% had multiple comorbidities. The presence of at least 1 comorbidity was associated with a higher hospitalization rate [hospital days per 100 observation days: 1.7 (IQR: 5.8) vs 1.2 (IQR: 3.9), p = 0.001] and decreased patient survival (4-year survival rate: 73% vs 90%, p < 0.0001). CONCLUSIONS: Nearly one third of pediatric CPD patients in a large international cohort had at least 1 comorbidity, and multiple comorbidities were frequently reported among patients with a defined syndrome. Preliminary analysis suggests an association between comorbidity and poor outcome in those patients. As this powerful international registry matures, further multivariate analyses will be important to more clearly define the impact of comorbidities on hospitalization rates and mortality in pediatric CPD patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".