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Diagnostic Accuracy of Point-of-Care Tests for Detecting Albuminuria: A Systematic Review and Meta-analysisDiagnostic Accuracy of Point-of-Care Tests for Detecting Albuminuria

Malcolm P. McTaggart, PhD; Ronald G. Newall, PhD; Jennifer A. Hirst, MSc; Clare R. Bankhead, DPhil; Edmund J. Lamb, PhD; Nia W. Roberts, MSc(Econ); and Christopher P. Price, PhD
[+] Article and Author Information

From East Kent Hospitals University NHS Foundation Trust, Canterbury, and University of Oxford, Oxford, United Kingdom.

Disclaimer: The views expressed are those of the authors and do not necessarily represent the views of the National Health Service, the National Institute for Health Research, or the Department of Health.

Financial Support: Ms. Roberts and Professor Price are supported by the National Institute for Health Research Diagnostic Evidence Co-operative Oxford at Oxford Health NHS Foundation Trust.

Disclosures: None. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M13-2331.

Requests for Single Reprints: Christopher P. Price, PhD, Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, United Kingdom.

Current Author Addresses: Dr. McTaggart: Department of Clinical Biochemistry, Royal Shrewsbury Hospital, Mytton Oak Road, Shrewsbury SY3 8XQ, United Kingdom.

Dr. Newall: 63 Highover Park, Amersham HP7 0BP, United Kingdom.

Ms. Hirst, Dr. Bankhead, and Professor Price: Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, United Kingdom.

Dr. Lamb: Clinical Biochemistry, East Kent Hospitals University NHS Foundation Trust, Kent and Canterbury Hospital, Ethelbert Road, Canterbury CT1 3NG, United Kingdom.

Ms. Roberts: Bodleian Health Care Libraries, Knowledge Centre, ORC Research Building, Old Road Campus, Headington, Oxford OX3 7DQ, United Kingdom.

Author Contributions: Conception and design: M.P. McTaggart, R.G. Newall, E.J. Lamb, C.P. Price.

Analysis and interpretation of the data: M.P. McTaggart, R.G. Newall, J.A. Hirst, C.R. Bankhead, E.J. Lamb, C.P. Price.

Drafting of the article: M.P. McTaggart, R.G. Newall, E.J. Lamb, C.P. Price.

Critical revision of the article for important intellectual content: M.P. McTaggart, R.G. Newall, J.A. Hirst, C.R. Bankhead, E.J. Lamb, C.P. Price.

Final approval of the article: M.P. McTaggart, R.G. Newall, J.A. Hirst, C.R. Bankhead, E.J. Lamb, N.W. Roberts, C.P. Price.

Provision of study materials or patients: M.P. McTaggart.

Statistical expertise: J.A. Hirst, C.R. Bankhead.

Administrative, technical, or logistic support: M.P. McTaggart, N.W. Roberts.

Collection and assembly of data: M.P. McTaggart, R.G. Newall, E.J. Lamb, N.W. Roberts, C.P. Price.


Ann Intern Med. 2014;160(8):550-557. doi:10.7326/M13-2331
Text Size: A A A

Background: Experts recommend screening for albuminuria in patients at risk for kidney disease.

Purpose: To systematically review evidence about the diagnostic accuracy of point-of-care (POC) tests for detecting albuminuria in individuals for whom guidelines recommend such detection.

Data Sources: Cochrane Library, EMBASE, Medion database, MEDLINE, and Science Citation Index from 1963 through 5 December 2013; hand searches of other relevant journals; and reference lists.

Study Selection: Cross-sectional studies, published in any language, that compared the accuracy of machine-read POC tests of urinary albumin–creatinine ratio with that of laboratory measurement.

Data Extraction: Two independent reviewers extracted study data and assessed study quality using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2) tool.

Data Synthesis: Sixteen studies (n = 3356 patients) that evaluated semiquantitative or quantitative POC tests and used random urine samples collected in primary or secondary ambulatory care settings met inclusion criteria. Pooling results from a bivariate random-effects model gave sensitivity and specificity estimates of 76% (95% CI, 63% to 86%) and 93% (CI, 84% to 97%), respectively, for the semiquantitative test. Sensitivity and specificity estimates for the quantitative test were 96% (CI, 78% to 99%) and 98% (CI, 93% to 99%), respectively. The negative likelihood ratios for the semiquantitative and quantitative tests were 0.26 (CI, 0.16 to 0.40) and 0.04 (CI, 0.01 to 0.25), respectively.

Limitation: Accuracy estimates were based on data from single-sample urine measurement, but guidelines require that diagnosis of albuminuria be based on at least 2 of 3 samples collected in a 6-month period.

Conclusion: A negative semiquantitative POC test result does not rule out albuminuria, whereas quantitative POC testing meets required performance standards and can be used to rule out albuminuria.

Primary Funding Source: None.

Figures

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Appendix Figure 1.

Summary of evidence search and selection.

After the literature search, titles and abstracts were screened by 2 independent investigators with arbitration by 2 other investigators. Full-text versions of retained articles were obtained, and a further round of selection was performed. Data were extracted from the remaining articles. QUADAS-2 = Quality Assessment of Diagnostic Accuracy Studies 2.

*Appendix Table 3 provides reasons for exclusion.

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Appendix Figure 2.

Bar charts for QUADAS-2 analysis.

Risk of bias (left) and applicability concerns (right) were assessed by 2 independent investigators using a QUADAS-2 questionnaire across the domains shown, with arbitration on disagreements by a third investigator. QUADAS-2 = Quality Assessment of Diagnostic Accuracy Studies 2.

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Figure 1.

Forest plots for the semiquantitative test.

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Figure 2.

Forest plots for the semiquantitative test with a clinical operator.

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Figure 3.

Forest plots for the semiquantitative test with a laboratory operator.

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Appendix Figure 3.

HSROC curve plots for semiquantitative test.

Plots for laboratory operators (left) and clinical operators (right) are shown. HSROC = hierarchical summary receiver-operating characteristic.

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Figure 4.

Forest plots for the quantitative test.

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Appendix Figure 4.

HSROC curve plot for quantitative assay studies.

HSROC = hierarchical summary receiver-operating characteristic.

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Appendix Figure 5.

Likelihood ratio scattergram for semiquantitative test.

LLQ = left lower quadrant; LR− = negative likelihood ratio; LR+ = positive likelihood ratio; LUQ = left upper quadrant; RLQ = right lower quadrant; RUQ = right upper quadrant.

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Appendix Figure 6.

Likelihood ratio scattergram for quantitative test.

LLQ = left lower quadrant; LR− = negative likelihood ratio; LR+ = positive likelihood ratio; LUQ = left upper quadrant; RLQ = right lower quadrant; RUQ = right upper quadrant.

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