Association of malnutrition–inflammation complex and responsiveness to erythropoiesis-stimulating agents in long-term hemodialysis patients
Bibliographic record
Abstract
BACKGROUND: Protein-energy wasting, inflammation and refractory anemia are common in long-term hemodialysis patients. A decreased responsiveness to erythropoiesis-stimulating agents (ESA) is often the cause of the refractory anemia. We hypothesized that the malnutrition-inflammation complex is an independent predictor of decreased responsiveness to ESAs in hemodialysis patients. METHODS: This cohort study of 754 hemodialysis patients was examined for an association between inflammatory and nutritional markers, including the malnutrition-inflammation score (MIS) and responsiveness to ESA. Cubic spline models were fitted to verify found associations. RESULTS: The mean (±SD) age of patients was 54 ± 15 years, 53% were diabetic and 32% blacks. MIS was worse in the highest quartile of ESAs responsiveness index (ERI, ESA dose divided by hemoglobin) when compared with 1st quartile (6.5 ± 4.5 versus 4.4 ± 3.4; P < 0.001). Both C-reactive protein (log CRP) (β = 0.19) and interleukin-6 (log IL-6) (β = 0.32) were strong and independent predictors of ERI using multivariate linear regression. Serum albumin (β = -0.30) and prealbumin levels (β = -0.14) were inversely associated with ERI. Each 1 SD higher MIS, higher CRP and lower albumin were associated with 86, 44 and 97% higher likelihood of having highest versus three lowest ERI quartiles in fully adjusted models [odds ratio (and 95% confidence interval) of 1.86 (1.31-2.85), 1.44 (1.08-1.92) and 1.97 (1.41-2.78)], respectively. Cubic splines confirmed the continuous and incremental nature of these associations. CONCLUSIONS: Malnutrition-inflammation complex is an incremental predictor of poor responsiveness to ESAs in hemodialysis patients. Further studies are needed to assess whether modulating inflammatory or nutritional processes can improve anemia management.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".