Effect of anaemia on mortality, cardiovascular hospitalizations and end‐stage renal disease among patients with chronic kidney disease
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To determine whether an independent association exists between anaemia and chronic kidney disease (CKD) outcomes in a quasi-incidence cohort when patients' most recent laboratory values are considered. METHODS: We conducted a dynamic, retrospective cohort study among patients with incident CKD in a large health maintenance organization administrative data set. CKD was defined by two estimated glomerular filtration rates (eGFR). We measured the absolute rates for all-cause mortality, cardiovascular hospitalizations and end-stage renal disease. RESULTS: Our completed cases Cox regression model followed 5885 patients with both CKD and haemoglobin measures. For patients with the most severe anaemia (haemoglobin <10.5 g/dL), we estimated an increased rate of mortality (hazard ratio (HR)=5.27, CI 4.37-6.35), cardiovascular hospitalizations (HR=2.18, CI 1.76-2.70) and end-stage renal disease (HR=5.46, CI 3.38-8.82) when compared with patients who were not anaemic; the HR reflect time-varying haemoglobins and eGFR. CONCLUSION: Anaemia is a predictor of excess mortality, excess cardiovascular hospitalizations and excess end-stage renal disease even when the progression of CKD is considered by controlling for time-varying eGFR values.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it