Medical Costs of Untreated Anemia in Elderly Patients with Predialysis Chronic Kidney Disease
Bibliographic record
Abstract
The objective of this study was to quantify the incremental medical costs that are associated with untreated anemia among elderly patients with predialysis chronic kidney disease (CKD). An analysis of claims and laboratory data between January 1999 and February 2005 was conducted. Inclusion criteria were age >/=65 yr, two or more hemoglobin readings, one or more claims for CKD, and two or more GFR values of <60 ml/min per 1.73 m(2) (stages 3 to 5 CKD). Patients were excluded when they had cancer or lupus, had received organ transplantation, or were treated for anemia. An open-cohort design was used to classify patients' observation periods into anemia and nonanemia. Both univariate and multivariate analyses were conducted to compare periods of anemia and nonanemia for average monthly medical costs; the latter was adjusted for age, gender, GFR, diabetes, hypertension, liver cirrhosis, coronary artery disease, myocardial infarction, and left ventricular hypertrophy. A subset analysis of patients with moderate CKD (stage 3) was conducted. A total of 2001 patients were identified. Untreated anemia was associated with a significant increase in medical costs, with an unadjusted incremental monthly cost of $1089 (P < 0.0001) and a cost ratio of 1.8:1 relative to nonanemia. After controlling for covariates, untreated anemia remained significantly associated with a cost increase (adjusted incremental monthly cost $503; cost ratio 1.4:1; P < 0.0001). Similar significant cost burden was observed in the subset of patients with moderate CKD. The retrospective observational design may be more susceptible to bias than a randomized, controlled trial. This large study, which was based on real-life practice data, demonstrated that untreated anemia in elderly patients with predialysis CKD was associated with a significant increase in medical costs.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".