Use of cranberry products does not appear to be associated with a significant reduction in incidence of recurrent urinary tract infections
Bibliographic record
Abstract
Commentary on: Jepson RG, Williams G, Craig JC. Cranberries for preventing urinary tract infections. Cochrane Database Syst Rev 2012;10:CD001321.[OpenUrl][1][PubMed][2] Urinary tract infections (UTIs) represent a considerable healthcare burden, with important consequences in terms of morbidity and cost. Preventive measures are limited, not always dramatically effective1 and associated with a concerning increase in the resistance profile of common pathogens to different antibiotics. Thus, there is considerable interest in alternative prophylactic interventions. Among these, cranberry products (CP) are often recommended and utilised. The study by Jepson and colleagues updates a previous analysis on the use of CP for this purpose. The authors conducted a systematic review and meta-analysis (SR/MA) of pertinent literature identified by a comprehensive search strategy with an in-depth assessment of randomised and quasi-randomised trials of CP (vs placebo and non-placebo controls) in preventing UTIs. Two investigators independently evaluated and extracted information on methods, participants, interventions … [1]: {openurl}?query=rft.jtitle%253DCochrane%2Bdatabase%2Bof%2Bsystematic%2Breviews%2B%2528Online%2529%26rft.stitle%253DCochrane%2BDatabase%2BSyst%2BRev%26rft.aulast%253DJepson%26rft.auinit1%253DR.%2BG.%26rft.volume%253D10%26rft.spage%253DCD001321%26rft.epage%253DCD001321%26rft.atitle%253DCranberries%2Bfor%2Bpreventing%2Burinary%2Btract%2Binfections.%26rft_id%253Dinfo%253Apmid%252F23076891%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=23076891&link_type=MED&atom=%2Febmed%2F18%2F5%2F181.atom
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.010 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".