Urinary tract infections in hemodialysis patients—The controversy of antimicrobial drug urine concentrations
Bibliographic record
Abstract
BACKGROUND: Major infectious diseases societies recommend the use of antimicrobials that achieve high-urinary concentrations to treat urinary tract infection (UTI), which is a concept of little relevance to the oliguric and anuric hemodialysis (HD) dependent population. Outcome studies in this population are more relevant, but unfortunately scarce. We sought to investigate the impact of different antimicrobials on clinical and microbiologic outcomes in HD dependent population. METHODS: A retrospective observational study conducted at our quaternary care hospital between May 2015 and December 2019. We included all HD dependent adults diagnosed with UTIs. Our primary end points were clinical and microbiologic cure. Our secondary end points were 90-day recurrence and mortality. RESULTS: . Thirty-six subjects of the sample (64.3%) were anuric. Ninety-one percent of the patients achieved clinical cure. Out of those who had repeat cultures, 90.7% achieved microbiologic cure. Clinical and microbiologic cure rates were not significantly different between the oliguric and anuric groups. The 90-day recurrence rate was 11.1% and mortality was 19%, none of them was related to UTI. CONCLUSION: Our findings demonstrate high rate of clinical and microbiologic cure in the treatment of oliguric and anuric HD dependent patients. We suggest that drug development and treatment societies to consider clinical and microbiologic outcomes in conjunction with achievable urinary concentration when making recommendations for the treatment of UTI.
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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 | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".