Regular drinking of cranberry-lingonberry juice concentrate reduced recurrent urinary tract infections in women
Bibliographic record
Abstract
Kontiokari T, Sundqvist K, Nuutinen M , et al. Randomised trial of cranberry-lingonberry juice and Lactobacillus GG drink for the prevention of urinary tract infections in women. BMJ2001 Jun 30; 322 : 1571 –3 [OpenUrl][1][Abstract/FREE Full Text][2] QUESTION: Does regular drinking of cranberry-lingonberry juice concentrate or Lactobacillus GG drink reduce recurrence of urinary tract infections (UTIs) in women? Randomised {allocation concealed}*, blinded (outcome assessor), controlled trial with 12 months of follow up. Student health service at the University of Oulu and occupational health centre for the staff of Oulu University Hospital, Finland. 150 women (mean age 30 y) who had a UTI caused by Escherichia coli (≥105 colony forming units [cfu]/ml in clean voided midstream urine) and were not taking any antimicrobial prophylaxis. Follow up at 12 months was 91%. 50 women were allocated to receive 50 ml of cranberry-lingonberry juice concentrate (7.5 g cranberry concentrate and 1.7 g … [1]: {openurl}?query=rft.jtitle%253DBMJ%26rft.stitle%253DBMJ%26rft.aulast%253DKontiokari%26rft.auinit1%253DT.%26rft.volume%253D322%26rft.issue%253D7302%26rft.spage%253D1571%26rft.epage%253D1571%26rft.atitle%253DRandomised%2Btrial%2Bof%2Bcranberry-lingonberry%2Bjuice%2Band%2BLactobacillus%2BGG%2Bdrink%2Bfor%2Bthe%2Bprevention%2Bof%2Burinary%2Btract%2Binfections%2Bin%2Bwomen%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmj.322.7302.1571%26rft_id%253Dinfo%253Apmid%252F11431298%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/ijlink?linkType=ABST&journalCode=bmj&resid=322/7302/1571&atom=%2Febnurs%2F5%2F2%2F43.atom
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".