The Unintended Deleterious Consequences of the ‘Routine’ Urinalysis

Bush, Larry M.; Vazquez-Pertejo, Maria T.

doi:10.1016/j.amjmed.2016.08.014

Cited by 3 publications

(4 citation statements)

References 5 publications

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“…High quality studies have also demonstrated that treatment of asymptomatic bacteriuria increases risk of antibiotic resistance as opposed to decreasing the frequency of symptomatic infections in females. 23 Our study has demonstrated that a large resistance pattern to trimethoprim exists, in keeping with recent literature findings. Considering this, the use of trimethoprim as a first-line antibiotic in national guidance will undoubtedly continue to exacerbate this situation.…”

Section: Discussionsupporting

confidence: 92%

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Bacteriuria resistance patterns and the suitability of urinalysis as an initial diagnostic tool in a post-antibiotic era

Taktak

Gall

Dyer

2021

Therapeutic Advances in Urology

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Aims: Urinalysis is used as a first-line investigation throughout healthcare to indicate bacteriuria and guide treatment of potential urinary tract infections. In light of rising bacterial multi-resistance, we aim to analyse its diagnostic accuracy, determine its usefulness in a present-day setting and evaluate current antibiotic resistance patterns across a Trust population. Methods: A retrospective case series of 712 paired urinalysis and urine culture results was obtained over a 1-month period. Sensitivity, specificity and diagnostic accuracy were calculated, and resistance profiles of commonly used Trust antibiotics assessed using statistical analysis. Results: A high false negative rate of nitrites on urinalysis, with sensitivity of 38.4%, was found. Leucocyte sensitivity was 87.6% and specificity 39.7%, with no improvement in diagnostic accuracy seen when combining both. Positive urine culture growth demonstrated a substantial resistance pattern to trimethoprim of 48%, compounded by a statistically significant correlation with gentamicin resistance ( p < 0.0001). Conclusion: Our study has highlighted a reduced accuracy of urinalysis compared with previous literature, questioning its usefulness in the real world. We have consolidated growing published trends doubting the efficacy of trimethoprim, revealing co-existing resistance patterns between commonly used antibiotics. This will have implications for future antibiotic-prescribing protocols and requires further research to ensure guidelines are progressive in consciously managing this growing concern in modern-day healthcare.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Bacteriuria resistance patterns and the suitability of urinalysis as an initial diagnostic tool in a post-antibiotic era

Taktak

Gall

Dyer

2021

Therapeutic Advances in Urology

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“…Since low back pain can relate to multiple potential diagnoses/labels, creating a complete definition can be challenging (13,14). Finally, urinalysis is often cited and investigated as a potential low-value service in some circumstances, and some studies have investigated its use in claims data (15)(16)(17). We include it as an example here to demonstrate the application's utility for investigating diagnosis codes associated with a more generally used pathology test.…”

Section: Diseases [Icd] Codes)mentioning

confidence: 99%

Health service research definition builder: An R Shiny application for exploring diagnosis codes associated with services reported in routinely collected health data

Chalmers

Gopinath

Elshaug

2022

Preprint

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Many administrative health data-based studies define patient cohorts using procedure and diagnosis codes. The impact these criteria have on a study's final cohort is not always transparent to co-investigators or other audiences if access to the research data is restricted. We developed a SAS and R Shiny interactive research support tool which generates and displays the diagnosis code summaries associated with a selected medical service or procedure. This allows non-analyst users to interrogate claims data and groupings of reported diagnosis codes. The SAS program uses a tree classifier to find associated diagnosis codes with the service claims compared against a matched, random sample of claims without the service. Claims are grouped based on the overlap of these associated diagnosis codes. The Health Services Research (HSR) Definition Builder Shiny application uses this input to create interactive table and graphics, which updates estimated claim counts of the selected service as users select inclusion and exclusion criteria. This tool can help researchers develop preliminary and shareable definitions for cohorts for administrative health data research. It allows an additional validation step of examining frequency of all diagnosis codes associated with a service, reducing the risk of incorrect included or omitted codes from the final definition. In our results, we explore use of the application on three example services in 2016 US Medicare claims for patients aged over 65: knee arthroscopy, spinal fusion procedures and urinalysis. Readers can access the application at https://kelsey209.shinyapps.io/hsrdefbuilder/ and the code at https://github.com/kelsey209/hsrdefbuilder.

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“…Since low back pain can relate to multiple potential diagnoses/labels, creating a complete definition can be challenging [ 13 , 14 ]. Finally, urinalysis is often cited and investigated as a potential low-value service in some circumstances, and some studies have investigated its use in claims data [ 15 – 17 ]. We include it as an example here to demonstrate the application’s utility for investigating diagnosis codes associated with a more generally used pathology test.…”

Section: Introductionmentioning

confidence: 99%

Health service research definition builder: An R Shiny application for exploring diagnosis codes associated with services reported in routinely collected health data

2023

View full text Add to dashboard Cite

Many administrative health data-based studies define patient cohorts using procedure and diagnosis codes. The impact these criteria have on a study’s final cohort is not always transparent to co-investigators or other audiences if access to the research data is restricted. We developed a SAS and R Shiny interactive research support tool which generates and displays the diagnosis code summaries associated with a selected medical service or procedure. This allows non-analyst users to interrogate claims data and groupings of reported diagnosis codes. The SAS program uses a tree classifier to find associated diagnosis codes with the service claims compared against a matched, random sample of claims without the service. Claims are grouped based on the overlap of these associated diagnosis codes. The Health Services Research (HSR) Definition Builder Shiny application uses this input to create interactive table and graphics, which updates estimated claim counts of the selected service as users select inclusion and exclusion criteria. This tool can help researchers develop preliminary and shareable definitions for cohorts for administrative health data research. It allows an additional validation step of examining frequency of all diagnosis codes associated with a service, reducing the risk of incorrect included or omitted codes from the final definition. In our results, we explore use of the application on three example services in 2016 US Medicare claims for patients aged over 65: knee arthroscopy, spinal fusion procedures and urinalysis. Readers can access the application at https://kelsey209.shinyapps.io/hsrdefbuilder/ and the code at https://github.com/kelsey209/hsrdefbuilder.

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The Unintended Deleterious Consequences of the ‘Routine’ Urinalysis

Cited by 3 publications

References 5 publications

Bacteriuria resistance patterns and the suitability of urinalysis as an initial diagnostic tool in a post-antibiotic era

Bacteriuria resistance patterns and the suitability of urinalysis as an initial diagnostic tool in a post-antibiotic era

Health service research definition builder: An R Shiny application for exploring diagnosis codes associated with services reported in routinely collected health data

Health service research definition builder: An R Shiny application for exploring diagnosis codes associated with services reported in routinely collected health data

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