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Record W4387598437 · doi:10.12968/bjon.2023.32.18.s8

Risk factors for urinary tract infections associated with lower quality of life among intermittent catheter users

2023· article· en· W4387598437 on OpenAlexaff
Márcio Augusto Averbeck, Michael Kennelly, Nikesh Thiruchelvam, Charalampos Konstantinidis, Emmanuel Chartier‐Kastler, Andrei V. Krassioukov, Malene Hornbak, Lotte Neergaard Jacobsen, Rikke Vaabengaard, Sabrina Islamoska

Bibliographic record

VenueBritish Journal of Nursing · 2023
Typearticle
Languageen
FieldMedicine
TopicUrinary Tract Infections Management
Canadian institutionsGF Strong Rehabilitation CentreUniversity of British ColumbiaInternational Collaboration On Repair DiscoveriesVancouver Coastal Health
Fundersnot available
KeywordsMedicineUrineUrinary systemQuality of life (healthcare)Internal medicineResidual urineRelative riskCatheterRisk factorIntensive care medicineSurgeryConfidence intervalNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Evidence shows that intermittent catheterisation (IC) for bladder emptying is linked to urinary tract infections (UTIs) and poor quality of life (QoL). AIM: To investigate the association between UTI risk factors and QoL and patient-reported UTIs respectively. METHODS: A survey was distributed to IC users from 13 countries. FINDINGS: Among 3464 respondents, a significantly poorer QoL was observed when experiencing blood in the urine, residual urine, bowel dysfunction, recurrent UTIs, being female, and applying withdrawal techniques. A lower UTI risk was found when blood was not apparent in urine (RR: 0.63; 95% CI: 0.55-0.71), the bladder was perceived empty (RR: 0.83; 95% CI: 0.72-0.96), not having bowel dysfunction (RR: 0.86; 95% CI: 0.76-0.98), and being male (RR: 0.70; 95% CI: 0.62-0.79). CONCLUSION: This study underlines the importance of risk factors and their link to QoL and UTIs, highlighting the need for addressing symptoms before UTIs become problematic.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.332
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations10
Published2023
Admission routes1
Has abstractyes

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