A composite score of protein-energy nutritional status predicts mortality in haemodialysis patients no better than its individual components
Bibliographic record
Abstract
BACKGROUND: Protein-energy wasting is tightly associated with mortality in haemodialysis patients. An expert panel of the International Society of Renal Nutrition and Metabolism (ISRNM) has published a consensus on the parameters that define protein-energy nutritional status and posed the question, 'which scoring system most effectively predicts outcome?' The aim of our study was therefore to develop a composite score of protein-energy nutritional status (cPENS) and to assess its prediction of all-cause mortality. METHODS: We used the data of 560 haemodialysis patients participating in the CONvective TRAnsport STudy (CONTRAST). All participants were followed for occurrence of death. Internationally recommended nutritional targets were used as components of the cPENS, including the subjective global assessment (target score ≥ 6), albumin (≥ 4.0 g/dL), normalized protein nitrogen appearance (≥ 0.8 g/kg/day), cholesterol (≥ 100 mg/dL), creatinine (≥ 10 mg/dL) and BMI (> 23 kg/m(2)). A Cox regression model was used to analyse the relation between different cPENS variants and mortality. RESULTS: The median follow-up time was 1.4 years (max 4.2). One hundred and five patients (19%) died. A cPENS variant based on albumin, BMI, creatinine and the nPNA yielded the strongest relation with mortality (hazard ratio 0.63, 95% confidence interval 0.54-0.74, P < 0.001), after adjustments for confounders. Some of the individual parameters of the cPENS, notably albumin and creatinine, were related to mortality with similar strength and magnitude. CONCLUSIONS: In conclusion, albumin reflects mortality risk similarly to multiple nutritional parameters combined. This questions the clinical value of the proposed diagnostic criteria for protein-energy wasting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".