Point-of-care tests for urinary tract infections to reduce antimicrobial resistance: a systematic review and conceptual economic model

Health Technol Assess. 2024 Nov;28(77):1-109. doi: 10.3310/PTMV8524.

Abstract

Background: Urinary tract infections are diagnosed by general practitioners based on symptoms, dipstick tests in some and laboratory urine culture. Patients may be given inappropriate antibiotics. Point-of-care tests can diagnose urinary tract infection in near-patient settings quicker than standard culture. Some can identify the causative pathogen or antimicrobial sensitivity.

Objective: To assess whether point-of-care tests for people with suspected urinary tract infection have the potential to be clinically effective and cost-effective to the NHS.

Design: Systematic review and conceptual economic model.

Results: Two randomised controlled trials evaluated Flexicult Human (one against standard care; one against ID Flexicult). One trial found no evidence of a difference between groups in concordant antibiotic use (odds ratio 0.84, 95% confidence interval 0.58 to 1.20), and the other found no difference in appropriate antibiotic prescribing (odds ratio 1.44, 95% confidence interval 1.03 to 1.99). Compared with standard care, Flexicult was associated with reduced antibiotic prescribing at initial consultation (odds ratio 0.56, 95% confidence interval 0.35 to 0.88). No difference was found for other outcomes. Sixteen studies reported test accuracy data. Most were rated as being at unclear or high risk of bias. We identified data on three rapid tests (results < 40 minutes). Lodestar DX (n = 1) had good sensitivity (86%, 95% confidence interval 74% to 99%) and specificity (88%, 95% confidence interval 83% to 94%) for detecting Escherichia coli. Uriscreen (n = 4) had modest summary sensitivity (74%, 95% confidence interval 59% to 84%) and specificity (64%, 95% confidence interval 41% to 82%). UTRiPLEX (n = 1) had poor sensitivity (21%) and good specificity (94%). Twelve studies evaluated culture-based tests (results 24 hours). Laboratory-based studies found Dipstreak (n = 2) and Uricult (n = 1) to be highly accurate, but there were limitations with these studies. Uricult Trio (n = 3) had more modest summary sensitivity (73%, 95% confidence interval 63% to 82%) and specificity (70%, 95% confidence interval 52% to 84%). Summary sensitivity for Flexicult Human (n = 4) and ID Flexicult (n = 2) was 79% (95% confidence interval 72% to 85%) and 89% (95% confidence interval 84% to 93%). Summary specificity was 67% (95% confidence interval 30% to 90%) and 70% (95% confidence interval 52% to 84%). Caution is needed in interpreting findings because of heterogeneity and limited data. Five studies evaluated technical performance (Flexicult Human, n = 3; Uricult Trio, n = 2). Limited data suggested that they are easier to use and interpret than standard culture. A conceptual economic model estimated the cost-effectiveness of point-of-care tests for urinary tract infection diagnosis, pathogen identification and antimicrobial sensitivity testing. Sensitivity and specificity of tests were informed by the clinical effectiveness review. Studies identified by the review were screened for evidence on treatment efficacy, costs and utility data; only two studies provided relevant evidence. A pragmatic search identified eight cost-effectiveness studies that provided further evidence. A decision tree comparing point-of-care tests in a mixed population (Lodestar DX vs. Flexicult Human) and in women with uncomplicated urinary tract infection (Lodestar DX vs. Flexicult Human vs. ID Flexicult) was implemented. The available input data were too limited for the results to be meaningful.

Conclusion and future work: More research is required to determine whether point-of-care tests for urinary tract infection have the potential to be clinically effective and cost-effective to the NHS. Rapid tests such as Astrego PA-100 system and Lodestar DX appear promising, but data are very limited.

Study registration: This study is registered as PROSPERO CRD42022383889.

Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135710) and is published in full in Health Technology Assessment; Vol. 28, No. 77. See the NIHR Funding and Awards website for further award information.

Keywords: ANTI-BACTERIAL AGENTS; DIAGNOSTIC TEST ACCURACY; ECONOMIC MODEL; META-ANALYSIS; SYSTEMATIC REVIEW; URINARY TRACT INFECTIONS.

Plain language summary

Urine infections are very common but can be difficult to diagnose. A GP will diagnose a urine infection based on symptoms, and sometimes they will send a urine sample to the lab. The GP will usually give antibiotics before knowing the lab test results (which can take up to a week). Some people will be given the wrong antibiotics, and some will be given antibiotics unnecessarily. New ‘rapid tests’ can be done in the GP surgery or pharmacy and will quickly tell (some in just a few minutes) whether someone has a urine infection. Some tests can also tell which bug is causing the infection and which antibiotics will work best. We wanted to know whether using ‘rapid tests’ to diagnose urine infections means that more people are correctly diagnosed, diagnosed more quickly, and treated with the right antibiotics more quickly. We also wanted to know whether these tests are a good use of NHS money. We reviewed existing research and developed an economic (cost) model. There is very little information available on these ‘rapid tests’. Tests were only looked at by a few studies each, and the people studied were different. Rapid tests that can detect a urine infection in under 40 minutes showed promise, but there were not enough data to know whether they are a good use of NHS money. More studies are needed to answer this question and to determine whether results vary across different populations.

Publication types

  • Systematic Review
  • Review

MeSH terms

  • Anti-Bacterial Agents* / therapeutic use
  • Cost-Benefit Analysis*
  • Drug Resistance, Bacterial
  • Humans
  • Models, Economic
  • Point-of-Care Systems / economics
  • Point-of-Care Testing / economics
  • State Medicine
  • Technology Assessment, Biomedical
  • United Kingdom
  • Urinary Tract Infections* / diagnosis
  • Urinary Tract Infections* / drug therapy

Substances

  • Anti-Bacterial Agents