Serum Fructosamine and Glycated Albumin and Risk of Mortality and Clinical Outcomes in Hemodialysis Patients
Bibliographic record
Abstract
OBJECTIVE: Assays for serum total glycated proteins (fructosamine) and the more specific glycated albumin may be useful indicators of hyperglycemia in dialysis patients, either as substitutes or adjuncts to standard markers such as hemoglobin A1c, as they are not affected by erythrocyte turnover. However, their relationship with long-term outcomes in dialysis patients is not well described. RESEARCH DESIGN AND METHODS: We measured fructosamine and glycated albumin in baseline samples from 503 incident hemodialysis participants of a national prospective cohort study, with enrollment from 1995-1998 and median follow-up of 3.5 years. Outcomes were all-cause and cardiovascular disease (CVD) mortality and morbidity (first CVD event and first sepsis hospitalization) analyzed using Cox regression adjusted for demographic and clinical characteristics, and comorbidities. RESULTS: Mean age was 58 years, 64% were white, 54% were male, and 57% had diabetes. There were 354 deaths (159 from CVD), 302 CVD events, and 118 sepsis hospitalizations over follow-up. Both fructosamine and glycated albumin were associated with all-cause mortality; adjusted HR per doubling of the biomarker was 1.96 (95% CI 1.38-2.79) for fructosamine and 1.40 (1.09-1.80) for glycated albumin. Both markers were also associated with CVD mortality [fructosamine 2.13 (1.28-3.54); glycated albumin 1.55 (1.09-2.21)]. Higher values of both markers were associated with trends toward a higher risk of hospitalization with sepsis [fructosamine 1.75 (1.01-3.02); glycated albumin 1.39 (0.94-2.06)]. CONCLUSIONS: Serum fructosamine and glycated albumin are risk factors for mortality and morbidity in hemodialysis 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".