Association of Serum Phosphorus Level With Anemia in Kidney Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: Anemia and mineral and bone disorders (MBD) are both important and common complications in kidney transplant recipients. Studies in patients with chronic kidney disease indicated a possible independent association of higher serum phosphorus with anemia, but similar associations have not been examined in kidney transplant recipients. We hypothesized that higher serum phosphorus is associated with anemia independent of other components of MBD. METHODS: We examined the association of serum phosphorus with hemoglobin level and the prevalence of anemia in a prevalent cohort of 992 kidney transplant recipients in a single outpatient transplant center. Associations were examined in linear and logistic regression models with adjustment for demographic and comorbid conditions for various known risk factors of anemia, including measures of iron deficiency, inflammation, and components of MBD including serum levels of 25(OH) vitamin D, parathyroid hormone, and fibroblast growth factor 23. RESULTS: In multivariable adjusted regression models, a 1 standard deviation (0.8 mg/dL) higher serum phosphorus level was associated with 0.26 g/dL lower blood hemoglobin concentration (95% confidence intervals -0.36 to -0.15, P<0.001) and with an odds ratio for anemia of 1.77 (95% confidence intervals 1.33-2.37, P<0.001). These associations were consistent across the entire spectrum of the physiologic serum phosphorus concentration and were more accentuated in patients with lower estimated glomerular filtration rate. CONCLUSIONS: Higher serum phosphorus is independently associated with anemia in kidney transplant recipients.
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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 | 0.000 |
| 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 | 0.001 |
| 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".