Provision and quality of dialysis services in <scp>L</scp>ibya
Bibliographic record
Abstract
Dialysis is entirely funded by the public health care sector in Libya. Access to treatment is unrestricted for citizens but there is a lack of local information and no renal registry to gather national data. This cross-sectional study aimed to investigate dialysis provision and practice in Libyan dialysis facilities in 2009. A structured interview regarding dialysis capacity, staffing and methods of assessment of dialysis patients, and infection control measures was conducted with the medical directors of all 40 dialysis centers and 28 centers were visited. A total of 2417 adult patients were receiving maintenance dialysis in 40 centers, giving a population prevalence of approximately 624 per million. Most dialysis units were located in the northern part of the country and only 12.5% were free-standing units. Only three centers offered peritoneal dialysis. One hundred ninety-two hemodialysis rooms hosted 713 functioning hemodialysis stations, giving a ratio of one machine to 3.4 patients. Around half of centers operated only two dialysis shifts per day. Nephrologist/internist to patient ratio was 1:40 and nurse to patient ratio was 1:3.7. We found a wide variation in monitoring of dialysis patients, with dialysis adequacy assessed only in a minority. Separate rooms were allocated for chronic viral infection seropositive patients in 92.5% of the units. In general, the provision of dialysis is adequate but several areas for improvement have been identified, including a need for implementation of guidelines, recruitment of more nephrologists, and the development of more cost-effective alternatives such as peritoneal dialysis and 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".