Short-term effects of nocturnal haemodialysis on carnitine metabolism
Bibliographic record
Abstract
BACKGROUND: Functional carnitine deficiency [as indicated by an abnormal acyl-carnitine/free-carnitine (AC:FC) ratio] is commonly seen in patients with end-stage renal disease (ESRD), resulting in significant clinical detriments including anaemia, cardiomyopathy and muscle weakness. Nocturnal haemodialysis (NHD) (5-6 sessions per week, 8 h per treatment) has been reported to reverse several surrogate markers of uraemia. Conversely, as a consequence of increased dialysis dose, NHD may have the potential to aggravate plasma nutrient deficiencies. Our objective was to determine the effects of NHD on plasma free-carnitine levels and carnitine metabolism. METHODS: We conducted an observational cohort study with a before and after design. Nine ESRD patients (age: 47 +/- 3; mean +/- SEM) were studied. Routine biochemical, haemodynamic and carnitine metabolic products were analysed at baseline while on conventional haemodialysis and 2 months post-conversion to NHD. Free-carnitine and total-carnitine levels were generated by colorimetric assays. The difference between total- and free-carnitine concentrations was estimated to be the acyl-carnitine level. Paired t-test was used to ascertain statistical significance. RESULTS: After conversion to NHD, there was a significant increase in urea clearance in all patients. Plasma free-carnitine levels fell from 26.54 +/- 2.99 to 15.6 +/- 2.34 micromol/l (P < 000.1). A similar reduction in plasma acyl-carnitine levels was observed (from 13.22 +/- 1.34 to 6.24 +/- 1.20 micromol/l (P < 0.001)). The AC:FC ratio improved from 0.51 +/- 0.03 to 0.39 +/- 0.03 (P < 0.005) (Normal < 0.25). CONCLUSION: NHD is associated with an improvement in AC:FC ratio. Further research is needed to examine the longitudinal clinical impact of this metabolic correction and to examine whether this effect is sustained.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".