PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-2 (2)
 

Clipboard (0)
None

Select a Filter Below

Journals
Authors
more »
Year of Publication
Document Types
1.  Validating the prediction of lower urinary tract infection in primary care: sensitivity and specificity of urinary dipsticks and clinical scores in women 
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.
doi:10.3399/bjgp10X514747
PMCID: PMC2894378  PMID: 20594439
algorithms, clinical scoring; diagnosis, urinary tract infection; primary care; urinalysis
2.  Developing clinical rules to predict urinary tract infection in primary care settings: sensitivity and specificity of near patient tests (dipsticks) and clinical scores 
Background
Suspected urinary tract infection (UTI) is one of the most common presentations in primary care. Systematic reviews have not documented any adequately powered studies in primary care that assess independent predictors of laboratory diagnosis.
Aim
To estimate independent clinical and dipstick predictors of infection and to develop clinical decision rules.
Design of study
Validation study of clinical and dipstick findings compared with laboratory testing.
Setting
General practices in the south of England.
Method
Laboratory diagnosis of 427 women with suspected UTI was assessed using European urinalysis guidelines. Independent clinical and dipstick predictors of diagnosis were estimated.
Results
UTI was confirmed in 62.5% of women with suspected UTI. Only nitrite, leucocyte esterase (+ or greater), and blood (haemolysed trace or greater) independently predicted diagnosis (adjusted odds ratios 6.36, 4.52, 2.23 respectively). A dipstick decision rule, based on having nitrite, or both leucocytes and blood, was moderately sensitive (77%) and specific (70%); positive predictive value (PPV) was 81% and negative predictive value (NPV) was 65%. Predictive values were improved by varying the cut-off point: NPV was 73% for all three dipstick results being negative, and PPV was 92% for having nitrite and either blood or leucocyte esterase. A clinical decision rule, based on having two of the following: urine cloudiness, offensive smell, and dysuria and/or nocturia of moderate severity, was less sensitive (65%) (specificity 69%; PPV 77%, NPV 54%). NPV was 71% for none of the four clinical features, and the PPV was 84% for three or more features.
Conclusions
Simple decision rules could improve targeting of investigation and treatment. Strategies to use such rules need to take into account limited negative predictive value, which is lower than expected from previous research.
PMCID: PMC1874525  PMID: 16882379
clinical scoring algorithms; diagnosis, urinary tract infection; dipsticks

Results 1-2 (2)