Abstract
Purpose Up to 50% of urinary tract infections (UTIs) in young children are missed in primary care. Urine culture is essential for diagnosis, but urine collection is often difficult. Our aim was to derive and internally validate a two-step clinical rule using (1) symptoms and signs to select children for urine collection; and (2) symptoms, signs and dipstick testing to guide antibiotic treatment.
Methods We recruited acutely unwell children <5 years from 233 primary care sites across England and Wales. Index tests were parent reported symptoms; clinician reported signs; urine dipstick results; and clinician opinion of UTI likelihood (‘clinical diagnosis’) prior to dipstick and culture). The reference standard was microbiologically confirmed UTI cultured from a clean catch urine sample. We calculated sensitivity, specificity and area under the receiver operator characteristic (AUROC) curve of coefficient-based (graded severity) and points-based (dichotomised) symptom/sign logistic regression models and internally validated the AUROC using bootstrapping.
Results 3036 children provided urines and culture results were available for 2740 (90%). Of these 60 (2.2%) were positive: ‘clinical diagnosis’ was 46.6% sensitive with AUROC of 0.77. Previous UTI, increasing pain/crying on passing urine, increasingly smelly urine, absence of severe cough, increasing clinician impression of severe illness, abdominal tenderness on examination and normal ear examination were associated with UTI. The validated coefficient (points) based model AUROCs were 0.87 (0.86), increasing to 0.90 (0.90) by adding dipstick nitrites, leucocytes and blood.
Conclusions A symptoms and signs based clinical rule is superior to clinician diagnosis and performs well for identifying young children for non-invasive urine sampling. Dipstick results add further diagnostic value for empiric antibiotic treatment.
Methods We recruited acutely unwell children <5 years from 233 primary care sites across England and Wales. Index tests were parent reported symptoms; clinician reported signs; urine dipstick results; and clinician opinion of UTI likelihood (‘clinical diagnosis’) prior to dipstick and culture). The reference standard was microbiologically confirmed UTI cultured from a clean catch urine sample. We calculated sensitivity, specificity and area under the receiver operator characteristic (AUROC) curve of coefficient-based (graded severity) and points-based (dichotomised) symptom/sign logistic regression models and internally validated the AUROC using bootstrapping.
Results 3036 children provided urines and culture results were available for 2740 (90%). Of these 60 (2.2%) were positive: ‘clinical diagnosis’ was 46.6% sensitive with AUROC of 0.77. Previous UTI, increasing pain/crying on passing urine, increasingly smelly urine, absence of severe cough, increasing clinician impression of severe illness, abdominal tenderness on examination and normal ear examination were associated with UTI. The validated coefficient (points) based model AUROCs were 0.87 (0.86), increasing to 0.90 (0.90) by adding dipstick nitrites, leucocytes and blood.
Conclusions A symptoms and signs based clinical rule is superior to clinician diagnosis and performs well for identifying young children for non-invasive urine sampling. Dipstick results add further diagnostic value for empiric antibiotic treatment.
Original language | English |
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Pages (from-to) | 325-336 |
Number of pages | 12 |
Journal | Annals of Family Medicine |
Volume | 14 |
Issue number | 4 |
DOIs | |
Publication status | Published - 11 Jul 2016 |
Keywords
- Urinary Tract Infections
- Primary Care
- Pediatrics
- Diagnosis
- Anti-Bacterial Agents
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Dr Kate Birnie
- Bristol Medical School (PHS) - Senior Research Fellow
- Bristol Population Health Science Institute
Person: Academic , Member
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Professor Alastair D Hay
- Bristol Population Health Science Institute
- Health Protection Research Unit (HPRU)
- Bristol Medical School (PHS) - Professor of Primary Care
- Infection and Immunity
- Centre for Academic Primary Care
Person: Academic , Member