The Role of Older Age in Normocytic Anaemia in Type 2 Diabetes Mellitus
Bibliographic record
Abstract
BACKGROUND: Older age has a significant association with anaemia. However, this has not been adequately investigated in the context of specific comorbidities such as Type 2 Diabetes Mellitus (T2DM). OBJECTIVES: To investigate the role of age in Normocytic Anaemia (NCA) and the adverse outcomes of NCA in T2DM. METHODS: Patients with NCA, either unexplained or related to Chronic Kidney Disease (CKD), were recruited from a diabetic clinic over six months. Anaemia was defined as a haemoglobin(Hb) < 130g/l for men and <120g/l for women. The relevant data were obtained by interviewing patients and review of medical records. Patients were followed for 12 months for pre-defined adverse outcomes. RESULTS: Of the 354 patients assessed, 203 were included (mean age 63.12 ± 13.62 years, males 49.8%). The prevalence of NCA was 24% (49). Older age had a significant univariate association with NCA (p < 0.001) and this remained significant (adjusted Odds Ratio (OR) 1.24, 95% CI 1.16- 5.29) after adjusting for estimated Glomerular Filtration Rate (eGFR) < 60ml/min/1.73m2, albuminuria and other potential confounders. Adjusting for eGFR as a continuous variable also confirmed this significant association (OR1.15, 95% CI 1.10-7.01). In the subgroup of patients aged ≥ 75 years, only older age was significantly associated with NCA. The incidence of all-cause mortality and composite cardiovascular/cerebrovascular events was similar in the anaemic and nonanaemic groups. CONCLUSION: NCA is common in T2DM and has a significant association with older age independent of CKD. The anaemia is mild in most patients and appears to have a benign course.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".