Evaluation of Levocarnitine Use in Pediatric Patients Undergoing Peritoneal Dialysis
Bibliographic record
Abstract
Background: Patients with ESRD undergoing peritoneal dialysis (PD) experience significant L-carnitine loss, altering acyl/free carnitine ratio (AFCR). Secondary carnitine deficiency manifests in clinical complications such as EPO-resistant anemia, intradialytic hypotension, cardiomyopathy, and skeletal muscle weakness. The efficacy of L-carnitine supplementation in reversing deficiency remains unclear and few studies have evaluated its use in PD, limiting evidence-based recommendations. This quality improvement study investigated L-carnitine supplementation in the pediatric PD population. Methods: Retrospective chart review (2018–2024) was completed for 20 PD patients (2–17 years) receiving intraperitoneal L-carnitine in varying monthly doses (500 mg, 750 mg, or 1000 mg). Patients were evaluated pre-treatment, monthly during treatment, and post-treatment at their final visit. Carnitine deficiency was defined as AFCR>0.4. The primary outcome was correction of AFCR, classified as ‘improvement’ and measured by a lower post-treatment AFCR compared to pre-treatment. Secondary outcomes included anemia presence measured by hemoglobin levels and erythropoietin-stimulating agent (ESA) doses. Statistical analyses included one-way ANOVA, t-tests, and Chi-Squared tests. Results: 9/20 patients (45%) showed improvement, 10/20 (50%) worsened as seen by increased AFCR, and 1 (5%) showed no change (p=0.8). Mean duration of treatment was 13.7±7.7 months and was significantly associated with improvement (p<0.001). Improved patients received similar mean L-carnitine (28.8 vs 20.7mg/kg) and ESA doses to worsened patients (p=0.2, p=0.8, p=0.4). An association between L-carnitine dose and post-AFCR was seen (p<0.001), as well as a significant decrease between pre- and post-AFCR in improved patients (p=0.003). Age was associated with L-carnitine dose and improvement, whereby patients ages <=10 years received higher weight-adjusted doses than patients ages 11-17 (p=0.09). Treatment duration was strongly associated with hemoglobin levels in all patients (p<0.001). Conclusion: L-carnitine supplementation in higher doses and for longer duration was associated with improvement in 45% of patients, as evidenced by lower post-treatment AFCRs. Further research and larger sample size are required to determine whether correction of AFCR is beneficial against associated complications.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".