Macrocytosis may be associated with mortality in chronic hemodialysis patients: a prospective study
Bibliographic record
Abstract
BACKGROUND: Macrocytosis occurs in chronic hemodialysis (CHD) patients; however, its significance is unknown. The purpose of this study was to establish the prevalence and distribution of macrocytosis, to identify its clinical associations and to determine if macrocytosis is associated with mortality in stable, chronic hemodialysis patients. METHODS: We conducted a single-centre prospective cohort study of 150 stable, adult CHD patients followed for nine months. Macrocytosis was defined as a mean corpuscular volume (MCV) > 97 fl. We analyzed MCV as a continuous variable, in tertiles and using a cutoff point of 102 fl. RESULTS: The mean MCV was 99.1 ± 6.4 fl, (range 66-120 fl). MCV was normally distributed. 92 (61%) of patients had an MCV > 97 fl and 45 (30%) > 102 fl. Patients were not B12 or folate deficient in those with available data and three patients with an MCV > 102 fl had hypothyroidism. In a logistic regression analysis, an MCV > 102 fl was associated with a higher Charlson-Age Comorbidity Index (CACI) and higher ratios of darbepoetin alfa to hemoglobin (Hb), [(weekly darbepoetin alfa dose in micrograms per kg body weight / Hb in g/L)*1000]. There were 23 deaths at nine months in this study. Unadjusted MCV > 102 fl was associated with mortality (HR 3.24, 95% CI 1.42-7.39, P = 0.005). Adjusting for the CACI, an MCV > 102 fl was still associated with mortality (HR 2.47, 95% CI 1.07-5.71, P = 0.035). CONCLUSIONS: Macrocytosis may be associated with mortality in stable, chronic hemodialysis patients. Future studies will need to be conducted to confirm this finding.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".