UK Renal Registry 18th Annual Report: Chapter 12 Epidemiology of Reported Infections amongst Patients Receiving Dialysis for Established Renal Failure in England 2013 to 2014: a Joint Report from Public Health England and the UK Renal Registry
Bibliographic record
Abstract
From 1st May 2013 to 30th April 2014 there were 35 episodes of Methicillin resistant Staphylococcus aureus (MRSA) bacteraemia in established renal failure patients on dialysis. This is now fairly stable year-on-year equating to a rate of 0.15 episodes per 100 dialysis patient years, following an initial decline in rates from 4.0 episodes per 100 dialysis patient years in 2005 when reporting began. Methicillin sensitive Staphylococcus aureus (MSSA) bacteraemia rates were slightly higher this year at 2.23 per 100 dialysis patient years (compared with 1.59 episodes per 100 dialysis patient years last year) with 526 episodes of blood stream infection reported. In 2005, the first year this was reported, there were 1,114 MSSA bacteraemias in 54 centres. There were 247 Clostridium difficile infection episodes with a rate of 1.05 per 100 dialysis patient years, slightly higher than last year at 0.55 episodes per 100 dialysis patient years. Escherichia coli infections occurred at a rate of 1.49 per 100 dialysis patient years, very similar to the rate reported last year (1.32 episodes per 100 dialysis patient years). This report has utilised a new methodology to identify cases, linking all established renal failure cases known to the UK Renal Registry (UKRR) with all infections reported to Public Health England and avoids the need for the local microbiology team to flag the patient as a renal patient. This may have increased the reliability of diagnosis at the UKRR level. In each infection for which access data were collected, the presence of a central venous catheter appeared to correlate with increased risk.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".