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Urine drug testing is frequently used in clinical, employment, educational, and legal settings and misinterpretation of test results can result in significant adverse consequences for the individual who is being tested. Advances in drug testing technology combined with a rise in the number of novel misused substances present challenges to clinicians to appropriately interpret urine drug test results. Authors searched PubMed and Google Scholar to identify published literature written in English between 1946 and 2016, using urine drug test, screen, false-positive, false-negative, abuse, and individual drugs of abuse as key words. Cited references were also used to identify the relevant literature. In this report, we review technical information related to detection methods of urine drug tests that are commonly used and provide an overview of false-positive/false-negative data for commonly misused substances in the following categories: cannabinoids, central nervous system (CNS) depressants, CNS stimulants, hallucinogens, designer drugs, and herbal drugs of abuse. We also present brief discussions of alcohol and tricyclic antidepressants as related to urine drug tests, for completeness. The goal of this review was to provide a useful tool for clinicians when interpreting urine drug test results and making appropriate clinical decisions on the basis of the information presented.

Key Points UTIs are increasingly caused by multidrug-resistant organisms as a result of the overuse of empirical, broad-spectrum antibiotic therapy Antimicrobial susceptibility, determined by the phenotypic response to antibiotic exposure, is key for clinical decision making for treating the wide variety of uropathogens and identifying resistance markers Existing technologies (such as PCR, fluorescence in situ hybridization, and mass spectrometry) and new technologies (such as droplet microfluidic and biosensor platforms) need to focus on direct urine testing to expedite objective diagnoses Integrated biosensor–microfluidic platforms have the most potential for point-of-care testing, as they facilitate direct urine analysis and can encompass all assay steps in a compact device New technologies are a key step towards improved antimicrobial stewardship Timely and accurate identification and determination of the antimicrobial susceptibility of uropathogens is central to the management of UTIs and antimicrobial stewardship. In this Review, Davenport and colleagues discuss emerging technologies including biosensors, microfluidics, and other integrated platforms that could improve UTI diagnosis and treatment choice. Timely and accurate identification and determination of the antimicrobial susceptibility of uropathogens is central to the management of UTIs. Urine dipsticks are fast and amenable to point-of-care testing, but do not have adequate diagnostic accuracy or provide microbiological diagnosis. Urine culture with antimicrobial susceptibility testing takes 2–3 days and requires a clinical laboratory. The common use of empirical antibiotics has contributed to the rise of multidrug-resistant organisms, reducing treatment options and increasing costs. In addition to improved antimicrobial stewardship and the development of new antimicrobials, novel diagnostics are needed for timely microbial identification and determination of antimicrobial susceptibilities. New diagnostic platforms, including nucleic acid tests and mass spectrometry, have been approved for clinical use and have improved the speed and accuracy of pathogen identification from primary cultures. Optimization for direct urine testing would reduce the time to diagnosis, yet these technologies do not provide comprehensive information on antimicrobial susceptibility. Emerging technologies including biosensors, microfluidics, and other integrated platforms could improve UTI diagnosis via direct pathogen detection from urine samples, rapid antimicrobial susceptibility testing, and point-of-care testing. Successful development and implementation of these technologies has the potential to usher in an era of precision medicine to improve patient care and public health.

Abstract Introduction/Objective Traditionally, urinalysis encompasses the chemical analysis of urine by dipstick and manual microscopy for formed elements. High specimen volume and varying subjectivity among individuals performing microscopic analysis make the practice both imprecise and inefficient. Implementation of Sysmex UN- Series™Automated Urinalysis (Sysmex Corporation, Kobe, Japan) fulfilled our need for automation, addressing both issues at hand. Automated urinalysis offers a solution for laboratories to meet the growing demand for faster result turn around times(TAT) with ever increasing specimen volumes. We expect greater sensitivity and reproducibility in terms of comparison to manual microscopy, as well as quicker TAT with the change in methodology. Methods/Case Report Using both unpreserved and preserved urine tubes, a macroscopic comparative study between Clinitek Advantus(manual) and Clinitek Novus (automated) methods was carried out on 141 urines with greater than 60 abnormal patients. Similarly, a microscopic study between the laboratory’s manual microscopy procedure and the Sysmex UF-5000 was carried out on 112 urines with greater than 60 abnormal patients. RBCs, WBCs, Epithelial cells were evaluated under high power field(40X); casts and crystals were evaluated under lower power field(10X). The Reference Range Interval for both chemical and microscopic was verified using 44 normal patient specimens. The quantified values are converted to high and low power field (hpf/lpf), analogous to the current system in the laboratory. Results (if a Case Study enter NA) Most parameters had >90% agreement between manual and automated method. Parameters falling below 90% were checked to see if discrepancies fell within 1 degree. Automated system is more sensitive than manual and our average TAT for urinalysis dropped 50%. Conclusion The automated urinalysis technology enabled us to focus only on samples requiring intervention based on pathological criteria, resulting in reduced overall TAT and workload burden, and improved consistency in reporting across specimens.

Human urine samples are non-invasive, readily available, and contain several components that can provide useful indicators of the health status of patients. Hence, urine is a desirable and important template to aid in the diagnosis of common clinical conditions. Conventional methods such as dipstick tests, urine culture, and urine microscopy are commonly used for urinalysis. Among them, the dipstick test is undoubtedly the most popular owing to its ease of use, low cost, and quick response. Despite these advantages, the dipstick test has limitations in terms of sensitivity, selectivity, reusability, and quantitative evaluation of diseases. Various biosensor technologies give it the potential for being developed into point-of-care (POC) applications by overcoming these limitations of the dipstick test. Here, we present a review of the biosensor technologies available to identify urine-based biomarkers that are typically detected by the dipstick test and discuss the present limitations and challenges that future development for their translation into POC applications for urinalysis.

Background Proteinuria screening is recommended for patients with hypertension to screen for kidney disease and identify those at elevated risk for cardiovascular disease. However, screening rates among hypertensive patients are low. Home testing strategies may be useful in improving proteinuria screening adherence. Methods We conducted an individual-level, randomized trial at 55 primary care clinic sites in the Geisinger Health System to evaluate the effectiveness of a strategy using home smartphone urinalysis test (Dip.io) to complete proteinuria screening in previously unscreened non-diabetic patient portal users with hypertension. All patients received an educational letter and a standing urinalysis lab order, and then were randomized to control (usual care) or intervention. Intervention arm participants were invited to complete proteinuria screening with a mailed home smartphone urinalysis test. Co-primary outcomes were completion of proteinuria screening and number of albuminuria cases (albumin/creatinine ratio [ACR] ≥ 30 mg/g or protein/creatinine ratio ≥ 150 mg/g) at the end of 3 months. We also evaluated patient satisfaction with the home test, and compliance with recommendations for patients with newly detected albuminuria. Results A total of 999 patients were randomized to intervention or control. Out of 499 patients assigned to the intervention arm, 253 were reached by phone, and 69/97 (71.1%) consented patients completed the home test. Overall, the intervention increased proteinuria screening completion (28.9% vs. 18.0%; p  < 0.001) with no effect on the number of albuminuria cases (4 vs. 4) although only 6/57 (10.5%) patients with trace or 1+ urine dipstick protein had a follow-up quantitative test. Among the 55 patients who completed a survey after the home test, 89% preferred testing at home rather than the physician’s office. Conclusions A strategy using a home urinalysis smartphone test increased proteinuria screening rates in previously unscreened patients with hypertension and may be useful in increasing rates of proteinuria screening compliance. Future studies should evaluate use of home testing kits to screen for and confirm albuminuria, and determine whether improving early detection of kidney disease can improve future kidney health. Trial registration Clinical Trial Registry: NCT03470701 (First posted 3/20/2018) https://clinicaltrials.gov/ct2/show/NCT03470701 . This study was retrospectively registered.

Chronic kidney disease (CKD) is usually diagnosed using the estimated glomerular filtration rate (eGFR) or kidney damage markers. The urine dipstick test is a widely used screening tool for albuminuria, a CKD marker. Although the urine albumin:creatinine ratio (ACR) has advantages over the dipstick test in sensitivity and quantification of levels, the two methods have not been compared in the general population. A total of 20,759 adults with urinalysis data in the Korea National Health and Nutrition Examination Survey 2011-2014 were examined. CKD risk categories were created using a combination of eGFR and albuminuria. Albuminuria was defined using an ACR cutoff of 30 mg/g or 300 mg/g and a urine dipstick cutoff of trace or 1+. The EQ-5D index was used for the health outcome. Prevalence estimates of ACR ≥30 mg/g and >300 mg/g vs dipstick ≥trace and ≥1+ in adults aged ≥20 years were 7.2% and 0.9% vs 9.1% and 1.2%, respectively. For ACR ≥30 mg/g detection, the sensitivity, specificity, and positive/negative predictive values of dipstick ≥trace were 43.6%, 93.6%, 34.6%, and 95.5%, respectively. When risk categories created based on dipstick cutoffs were compared with those based on ACR cutoffs, 10.4% of the total population was reclassified to different risk categories, with only 3.9% reclassified to the same CKD category. Akaike information criterion values were lower, and non-fatal disease burdens of CKD were larger, in models predicting EQ-5D index using ACR-based categories compared to those using dipstick-based categories, even after adjusting for confounders. In conclusion, the urine dipstick test had poor sensitivity and high false-discovery rates for ACR ≥30 mg/g detection, and classified a large number of individuals into different CKD risk categories compared with ACR-based categories. Therefore, ACR assessments in CKD screening appear beneficial for a more accurate prediction of worse quality of life.

To evaluate the feasibility of a novel point-of-care test (POCT) management strategy including phase contrast microscopy for bacteriuria and urinary dipsticks for erythrocytes to guide antibiotic prescribing in women with suspected uncomplicated urinary tract infection (uUTI) in general practice. Pilot cluster randomised controlled trial in 20 general practices in Germany. Practices were assigned 1:1 to POCT-guided management or usual care. All urine samples were sent for urine culture. Follow-up over 28 days involved symptom diaries, telephone interviews, and medical record review. Primary outcomes were recruitment and retention rates. Secondary outcomes included total and inappropriate antibiotic use, symptom duration and burden, recurrent and upper UTIs, re-consultations, and diagnostic accuracy of microscopy versus urine culture. Mixed-effects models accounted for clustering. Over 8 months, 157 women were recruited (90 intervention, 67 control), median of 7.5 patients per practice (range 1-15). Participant retention at day 28 was 75%. Baseline characteristics were well balanced. Antibiotic use was similar in both groups: 77% (intervention) vs. 79% (control) at initial consultation. The mean number of antibiotic courses over 28 days was 0.96 (intervention) vs. 1.00 (control), with no indication of reduced prescribing. Phase-contrast microscopy showed limited diagnostic accuracy, especially for ruling out infection (negative predictive value 46%). Exploratory analyses suggested that if GPs had access to urine culture results at the point of care, antibiotic prescribing in the intervention group could have been higher than in routine care. The POCT-guided management approach for suspected uUTIs is feasible but presents implementation and methodological challenges. Recruitment varied across sites and was lower in the control group practices, highlighting the risk of differential recruitment. Retention was below the expected 80%, indicating the need for efficient follow-up strategies in future trials. Explorative analyses suggest that simply adding diagnostic information may not support antibiotic stewardship. Novel POCTs should be carefully assessed for their influence on prescribing before routine use. Trial registration: ClinicalTrials.gov NCT05667207.

Background Urine sediment analysis is a cornerstone of diagnostic testing. This study evaluates FUS-3000 Plus, an automated urine sediment analyzer using advanced imaging and artificial intelligence, to assess its technical performance and diagnostic accuracy for routine clinical use. Methods The study analyzed 98 urine samples for chemical parameters (pH, protein, blood, leukocyte esterase, and nitrite) and 76 samples for particle analysis (red blood cells [RBCs], white blood cells, epithelial cells, crystals, bacteria) by both FUS-3000 Plus and sediMAX™, the current laboratory analyzer in use. Additionally, 139 samples were tested for glucosuria and proteinuria, with results compared to the Cobas C702. Carry-over, precision, and linearity were assessed by internal quality controls in accordance with Clinical and Laboratory Standards Institute protocols. Accuracy was further evaluated using external quality controls. Results FUS-3000 Plus demonstrated strong agreement with sediMAX for nitrites, protein, and leukocyte esterase (kappa values >0.5) and correlated well with the Cobas C702 for glucosuria and proteinuria. However, discrepancies were observed in glucosuria detection, with some samples yielding inaccurate results even during external quality control assessments. A carry-over effect for RBCs required a rinse step after highly concentrated samples. Precision was acceptable (CV: 3%–11%), and Bland–Altman plots showed strong agreement for formed elements (correlation >0.95). However, the analyzer had reduced accuracy in bacteriuria detection. Conclusion FUS-3000 Plus is a reliable tool for routine urinalysis, excelling in particle classification. However, improvements are needed in bacteriuria detection and minimizing carry-over effects. Future research should explore its ability to identify additional cellular elements and its diagnostic utility in diverse clinical populations.