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Record W4385294483 · doi:10.4140/tcp.n.2023.315

Literature Review of Ascorbic Acid, Cranberry, and D-mannose for Urinary Tract Infection Prophylaxis in Older People

2023· review· en· W4385294483 on OpenAlexaff
Grace Y. Song, Mira Koro, Vivian Leung, Gabriel Loh

Bibliographic record

VenueThe Senior Care Pharmacist · 2023
Typereview
Languageen
FieldMedicine
TopicUrinary Tract Infections Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineAscorbic acidGuidelineUrinary systemTolerabilityIntensive care medicineClinical trialPopulationInternal medicineAdverse effectEnvironmental healthPathology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.782
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.395
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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