Toward green dialysis: Focus on water savings
Bibliographic record
Abstract
Hemodialysis is one of the most water and energy-hungry medical procedures, and thus represents a clear opportunity where improvements should be made concerning the consumption and wastage of water. Three levels were investigated on which there are potential savings: the precise adjustment of water production according to specific needs, the reuse of reverse osmosis rejected water, and finally the huge volumes of post-patient dialysate effluent. The "AURAL" (Association pour l'Utilisation du Rein Artificiel à Lyon), main unit in Lyon, was the site of investigation for this study, which cares for 173 chronic hemodialysis patients. Evaluation of the 3 levels described earlier was undertaken on this particular building, and on the water treatment currently used. Volumes of produced water can be improved by different hydraulic systems or by adjusting the pure water conductivity used for dialysis. Concerning the reject water, reuse for building sanitation became the focus of further attention. The technical feasibility, volume of saved water, and applicable work costs were considered. The results suggest that out of a possible 2834 m(3)/year of reject water, 1200 m(3)/year may be reused and return on investment recovered within 5.8 years. Finally, the reprocessing and feasibility of reuse of dialysate effluent were investigated. Initial calculations show that although technical solutions are available, such processing of the wastewater production is not profitable in the short term. Regarding the significant prior authorization and risk management analysis necessary for such a project, this avenue was pursued no further. From the perspective of a "green dialysis," the reuse of reject water into sanitation is both viable and profitable in our unit, and must be the next step of our project. More widely, improvements can be made by defining a more precise range of pure water conductivity for dialysis and by applying reuse water project to new or to be renovated units.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".