Substitute treatment and replacement in chronic kidney disease: peritoneal dialysis, hemodialysis and transplant.
Bibliographic record
Abstract
Chronic dialysis replacement treatments or renal transplants are instituted when the patient's glomerular filtration rate, measured by 24-h urine endogenous creatinine clearance, is <10-15 ml/mm and, as the The National Kidney Foundation Kidney Disease Outcomes Quality Initiative (NKF KDOQI), European and Canadian guidelines point out, when one or two of the following complications occur: "uremic toxicity" symptoms, significant fluid retention that does not respond to loop diuretics, hyperkalemia, chronic anemia (hemoglobin <8 g), metabolic acidosis or acute pulmonary edema. In all patients for whom transplant is indicated, a selected live donor must be sought or, in the absence of contraindications, the patient should be registered with the national cadaver donation waiting list. While waiting for the transplant, patients will be on a chronic dialysis program. There is no national registry of patients undergoing chronic dialysis; only indirect data from the Mexican Kidney Foundation and the dialysis industry are available. However, it is estimated that 40,000-50,000 people are under this treatment and the numbers grow by 11% every year. Overall, it is thought that for every patient receiving chronic dialysis, there is one more patient who dies without access to therapy. Hemodialysis units must comply with the Official Hemodialysis Standard and the General Health Council Hemodialysis Unit Quality Assessment Form.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".