Literature Review of Ascorbic Acid, Cranberry, and D-mannose for Urinary Tract Infection Prophylaxis in Older People
Bibliographic record
Abstract
Background Urinary tract infections (UTIs) are the most prevalent infections in older patients with the potential for morbidity and mortality. Antibiotics are not generally recommended for UTI prophylaxis in this population. There is interest among the public and health providers to try over-the-counter products, such as cranberry, D-mannose, and vitamin C. The objective of this analysis was to review the literature for the efficacy and tolerability of these supplements in older individuals. Methods A literature review was conducted on PubMed using the search terms urinary tract infection or UTI, prevention/prophylaxis, cranberry, D-mannose, vitamin C/ascorbic acid. Few studies were conducted among older people; therefore, the authors included studies of all adults who had recurrent UTIs or were at increased risk of UTIs. Level (quality) of evidence were determined using the ACC/AHA Clinical Practice Guideline Recommendation Classification System. Results A total of 24 studies were included. This review captured all studies in previous reviews as well as recent publications. The authors determined that there were limited data for D-mannose and vitamin C, and randomized data for cranberry as defined by the classification system. Conclusions The three supplements reviewed appear not to be strongly supported by clinical data. For those who are interested in trying these products despite the lack of robust evidence for clinical efficacy, it may be helpful to know that the studies included in this review did not identify any clinically important signs of harm, to the extent that safety data were documented and reported.
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
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".