ArticleScandinavian journal of primary health care2025
Comparing visual and automated urine dipstick analysis in a general practice population.
Article in Scandinavian journal of primary health care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- An Interpretable SERS-AI Platform for Rapid and Quantitative Diagnosis of Polymicrobial UTIs: Powered by Positively Charged Plasmonic Nanoparticles and Attention-Based Deep Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Diagnostic test accuracy of dipstick urinalysis in clean catch urine for urinary tract infection in febrile infants presenting to emergency departments: a post-hoc analysis of the FIDO study.EClinicalMedicine · 2025Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionUrinary symptoms constitute the primary reason for female patients to consult their general practitioner. The urinary dipstick test serves as a cornerstone for diagnosing urinary tract infections (UTIs), yet traditional visual interpretation may be subject to variability. Automated devices for dipstick urinalysis are routinely used as alternatives, yet the evidence regarding their accuracy remains limited. Therefore we aimed to compare concordance between visual and automated urinary dipstick interpretation and determine their test characteristics for the prediction of bacteriuria. MATERIAL AND
methodsWe conducted a prospective validation study including urine samples originating from adult patients in general practice that were sent to the Maastricht Medical Centre + for urinary culture. Urinary dipstick tests were performed on each sample, which were interpreted visually and automatically. We calculated Cohen's κ and percentage agreement and used 2 × 2 tables to calculate test characteristics.
resultsWe included 302 urine samples. Visual and automated analysis showed almost perfect agreement (κ = 0.82 and κ = 0.86, respectively) for both nitrite and leukocyte esterase, but moderate agreement for erythrocytes (κ = 0.51). Interpretation of clinically relevant (nitrite and/or leukocyte esterase positive) samples showed almost perfect agreement (κ = 0.88). Urinary dipsticks show similar test characteristics with urinary culture as gold standard, with sensitivities of 0.92 and 0.91 and specificities of 0.37 and 0.41 for visual and automated interpretation respectively.
conclusionAutomated and visual dipstick analysis show near perfect agreement and perform similarly in predicting bacteriuria. However, automated analysis requires maintenance and occasionally measurement errors can occur.
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