Validating the prediction of lower urinary tract infection in primary care: sensitivity and specificity of urinary dipsticks and clinical scores in women

doi:10.3399/bjgp10X514747

Br J Gen Pract. 2010 July 1; 60(576): 495–500.

PMCID: PMC2894378

Validating the prediction of lower urinary tract infection in primary care: sensitivity and specificity of urinary dipsticks and clinical scores in women

Paul Little, MD, FRCGP, MRCP, Professor

Community Clinical Sciences Division (CCS), Southampton University, Southampton

Kate Rumsby, BA

Community Clinical Sciences Division (CCS), Southampton University, Southampton

Rachel Jones^*

Community Clinical Sciences Division (CCS), Southampton University, Southampton

^*The authors would like to dedicate this paper to Dr Rachel Jones who recently died unexpectedly

Greg Warner, MA, MRCGP, DCH, DRCOG, DSEM, GP

Nightingale Surgery, Romsey

Michael Moore, BMed Sci, MSc, MRCP, MRCGP, GP

Three Swans Surgery, Salisbury

J Andrew Lowes, BSc, MRCP, FRCPath

Southampton Health Protection Agency Laboratory, Southampton

Helen Smith, MSc, MD, MRCGP, FFPHM, Professor

Community Clinical Sciences Division (CCS), Southampton University, Southampton

Catherine Hawke, Public Health Physician

Hastings and St Leonard Primary Care Trust, St Leonards-on-Sea

Geraldine Leydon, Senior Research Fellow

Community Clinical Sciences Division (CCS), Southampton University, Southampton

Mark Mullee, MSc, CStat

Community Clinical Sciences Division (CCS), Southampton University, Southampton

Address for correspondence Professor P Little, University of Southampton, Aldermoor Health Centre, Aldermoor Close, Southampton, SO16 5ST. E-mail: p.little/at/soton.ac.uk

This article has been cited by other articles in PMC.

Abstract

Background

Dipsticks are one of the most commonly used near-patient tests in primary care, but few clinical or dipstick algorithms have been rigorously developed.

Aim

To confirm whether previously documented clinical and dipstick variables and algorithms predict laboratory diagnosis of urinary tract infection (UTI).

Design of study

Validation study.

Setting

Primary care.

Method

A total of 434 adult females with suspected lower UTI had bacteriuria assessed using the European Urinalysis Guidelines.

Results

Sixty-six per cent of patients had confirmed UTI. The predictive values of nitrite, leucocyte esterase (+ or greater), and blood (haemolysed trace or greater) were confirmed (independent multivariate odds ratios = 5.6, 3.5, and 2.1 respectively). The previously developed dipstick rule — based on presence of nitrite, or both leucocytes and blood — was moderately sensitive (75%) but less specific (66%; positive predictive value [PPV] 81%, negative predictive value [NPV] 57%). Predictive values were improved by varying the cut-off point: NPV was 76% for all three dipstick results being negative; the PPV was 92% for having nitrite and either blood or leucocyte esterase. Urine offensive smell was not found to be predictive in this sample; for a clinical score using the remaining three predictive clinical features (urine cloudiness, dysuria, and nocturia), NPV was 67% for none of the features, and PPV was 82% for three features.

Conclusion

A clinical score is of limited value in increasing diagnostic precision. Dipstick results can modestly improve diagnostic precision but poorly rule out infection. Clinicians need strategies to take account of poor NPVs.

Keywords: algorithms, clinical scoring; diagnosis, urinary tract infection; primary care; urinalysis

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