Volume Control in Hemodialysis Patients
Bibliographic record
Abstract
Cardiovascular disease is the main cause of the high mortality of dialysis patients and is largely due to poor control of blood pressure. Establishing and maintaining normal extracellular volume (ECV) is required to achieve normotension. The dry weight concept links ECV and blood pressure by a simple clinical relationship. Dry weight is the ideal postdialysis weight that allows a constantly normal blood pressure to be maintained without using antihypertensive medications. Maintenance of normal ECV requires control of salt intake to reduce interdialytic weight gain ( i.e., saline overload) combined with the diffusive and convective removal of salt and water from the body during dialysis sessions. Several problems are to be faced when using the dry weight method. Clinical evaluation must take into account the following confounding factors: weight varies with nutrition, clinical symptoms are unspecific and sometimes discordant, and there is a lag time between ECV and blood pressure changes. On the other hand, achievement of dry weight is hampered by dialysis times that are too short (and weight gains that are too high), by antihypertensive medications, and by poor heart conditions. A longer session time allows for a slower, easier, and more comfortable ultrafiltration.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".