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Record W2888756773 · doi:10.22374/jeleu.v1i1.6

A Prospective Audit of Urinary Tract Infection Incidence Following the use of Endosheath® for Flexible Cystoscopy

2018· article· en· W2888756773 on OpenAlexvenueno aff
Omar Al-Mula Abed, Shaun Trecarten, Shahid Islam, Ananda Kumar Dhanasekaran

Bibliographic record

VenueJournal of Endoluminal Endourology · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMedical Device Sterilization and Disinfection
Canadian institutionsnot available
Fundersnot available
KeywordsCystoscopyMedicineBacteriuriaUrinary systemIncidence (geometry)UrinalysisUrineProspective cohort studyAntibioticsSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Introduction Objectives To assess the incidence of bacteriuria and urinary tract infection following use of Endosheath®, and to assess patient comfort and satisfaction post-procedure. Patients and Methods One hundred thirty-five patients undergoing Endosheath® flexible cystoscopy (FC) were prospectively identified. Patients were excluded if pre-procedure urinalysis or symptoms suggested infection. Those who underwent FC were asked to provide a urine sample 72 hours post-procedure, assessing for bacterial culture and sensitivity. Patients completed a questionnaire assessing comfort, pain and whether they would recommend the procedure to others if required. Results Of the 135 patients, 117 patients returned their post-procedure samples and processed. Thirteen (11.1%) of the urine cultures samples were positive. Four (3.4%) of this 13 patients had symptoms of urinary tract infection (UTI) and were treated with antibiotics. One hundred and seven (79%) patients found the procedure comfortable and 104 (77%) patients would recommend the procedure to others. Conclusions Flexible Cystoscopy utilising Endosheath® appears to have comparable incidence of bacteriuria and UTI post procedure compared with standard FC, and is well tolerated by most patients.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.042
GPT teacher head0.310
Teacher spread0.268 · 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 designBench or experimental
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".

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Citations1
Published2018
Admission routes1
Has abstractyes

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