Retrospective review of bone mineral metabolism management in end-stage renal disease patients wait-listed for renal transplant
Bibliographic record
Abstract
Anna Chavlovski,1 Greg A Knoll,1–3 Timothy Ramsay,4 Swapnil Hiremath,1–3 Deborah L Zimmerman1–31University of Ottawa, 2Ottawa Hospital, 3Kidney Research Centre, Ottawa Hospital Research Institute, 4Ottawa Methods Centre, Ottawa, ON, CanadaBackground: In patients with end-stage renal disease, use of vitamin D and calcium-based phosphate binders have been associated with progression of vascular calcification that might have an impact on renal transplant candidacy. Our objective was to examine management of mineral metabolism in patients wait-listed for renal transplant and to determine the impact on cardiac perfusion imaging.Methods: Data was collected retrospectively on patients wait-listed for a renal transplant (n = 105), being either active (n = 73) and on hold (n = 32). Demographic data, medications, serum concentrations of calcium, phosphate, parathyroid hormone, and cardiac perfusion imaging studies were collected from the electronic health record. Chi-square and Student’s t-tests were used to compare active and on-hold patients as appropriate. Logistic regression was used to examine variables associated with worsening cardiac imaging studies.Results: The wait-listed patients were of mean age 56 ± 14 years and had been on dialysis for 1329 ± 867 days. On-hold patients had received a significantly greater total dose of calcium (2.35 ± .94 kg versus 1.49 ± 1.52 kg; P = 0.02) and were more likely to have developed worsening cardiovascular imaging studies (P = 0.03). Total doses of calcium and calcitriol were associated with worsening cardiovascular imaging studies (P = 0.05).Conclusion: Patients on hold on the renal transplant waiting list received higher total doses of calcium. A higher total dose of calcium and calcitriol was also associated with worsening cardiovascular imaging. Time on dialysis before transplant has been associated with worse post-transplant outcomes, and it is possible that the total calcium and calcitriol dose received contributed to these inferior outcomes.Keywords: dialysis, calcium, cardiac, transplantation
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".