Bibliographic record
Abstract
Hyperphosphatemia is a well recognized risk factor for cardiovascular mortality in dialysis patients. Despite advanced technology and regular and efficient dialysis treatment the prevalence of hyperphosphatemia is still high. The goal of normalization of serum phosphorus (iP) levels can only be reached by optimization of dialysis prescription in combination with individualized dietary and medical strategies. Due to the unique characteristics of intradialytic iP kinetics, dialysis treatment time and frequency are the most effective factors governing intradialytic iP removal. Although the combination of diffusive and convective removal by hemodiafiltration allows a further increase in iP mass removal, a neutral phosphorus balance without dietary restrictions and the use of phosphate binders has only be achieved by daily nocturnal hemodialysis. Strict dietary phosphate restriction bears the risk of inadequate protein intake and the development of protein/calorie malnutrition. Although phosphate binders (PB) can effectively lower serum iP levels into the normal range, this is rarely achieved in clinical practice probably due to inadequate relation of PB dose to dietary phosphorus intake. Developing methods to enable patients to self-adjust phosphate binder dose to individual meal phosphate content, similar to adjusting insulin dose to carbohydrate intake, may lead to further improvements in phosphate management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".