scholarly journals Predicting the use of antibiotics after initial symptomatic treatment of an uncomplicated urinary tract infection: analyses performed after a randomised controlled trial

BMJ Open ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. e035074
Author(s):  
Ingvild Vik ◽  
Ibrahimu Mdala ◽  
Marianne Bollestad ◽  
Gloria Cristina Cordoba ◽  
Lars Bjerrum ◽  
...  

ObjectiveTo predict antibiotic use after initial treatment with ibuprofen using data from a randomised controlled trial comparing ibuprofen to pivmecillinam in the treatment of women with symptoms of an uncomplicated urinary tract infection (UTI).Setting16 sites in a primary care setting in Norway, Sweden and Denmark.ParticipantsData from 181 non-pregnant women aged 18–60 presenting with symptoms of uncomplicated UTI, initially treated with ibuprofen.MethodsUsing the least absolute shrinkage and selection operator logistic regression model, we conducted analyses to see if baseline information could help us predict which women could be treated with ibuprofen without risking treatment failure and which women should be recommended antibiotics.ResultsOf the 143 women included in the final analysis, 77 (53.8%) recovered without antibiotics and 66 (46.2 %) were subsequently prescribed antibiotics. In the unadjusted binary logistic regression, the number of days with symptoms before inclusion (<3 days) and feeling moderately unwell or worse (≥4 on a scale of 0–6) were significant predictors for subsequent antibiotic use. In the adjusted model, no predictors were significantly associated with subsequent antibiotic use. The area under the curve of the final model was 0.66 (95% CI: 0.57 to 0.74).ConclusionWe did not find any baseline information that significantly predicted the use of antibiotic treatment. Identifying women who need antibiotic treatment to manage their uncomplicated UTI is still challenging. Larger data sets are needed to develop models that are more accurate.Trial registration numberClinicalTrials.gov (NCT01849926).

BMJ ◽  
2015 ◽  
pp. h6544 ◽  
Author(s):  
Ildikó Gágyor ◽  
Jutta Bleidorn ◽  
Michael M Kochen ◽  
Guido Schmiemann ◽  
Karl Wegscheider ◽  
...  

BMJ ◽  
2010 ◽  
Vol 340 (feb05 1) ◽  
pp. c199-c199 ◽  
Author(s):  
P Little ◽  
M V Moore ◽  
S Turner ◽  
K Rumsby ◽  
G Warner ◽  
...  

2021 ◽  
pp. BJGP.2021.0359
Author(s):  
Gail Hayward ◽  
Sam Mort ◽  
Ly-mee Yu ◽  
Merryn Voysey ◽  
Margaret Glogowska ◽  
...  

Background: Urine collection devices (UCD) are being marketed and used in clinical settings to reduce urine sample contamination, despite inadequate supporting evidence. Aim: To determine whether UCDs, compared to standardised instructions for urine sample collection, reduce the proportion of contaminated samples. Design, Setting: Single blind randomised controlled trial in UK Primary care. Method: Women aged ≥ 18 years presenting to with symptoms attributable to urinary tract infection (UTI) were randomised (1:1:1) to use either a Peezy UCD, a Whizaway Midstream UCD, or standardised verbal instructions (SVI) for midstream sample collection. The primary outcome was the proportion of urine samples reported as contaminated by microbiology laboratory analysis. Results: 1264 women (Peezy n=424; Whizaway n=421; SVI n=419) were randomised between 5/10/16 and 20/8/18. 90 women were excluded from the primary analysis due to ineligibility or lack of primary outcome data, leaving 1174 (n=381; n=390; n=403) for intention-to-treat analysis. The proportion of contaminated samples was 26.5% with the Peezy, 28.2% Whizaway, and 29% SVI (relative risk (RR) Peezy v SVI 0.91 [95% Confidence Interval (CI) 0.76 to 1.09] (P = 0.32); Whizaway v SI 0.98 [95% CI 0.97 to 1.20] (P = 0.82)). There were 100 (25.3%) device failures with Peezy and 35 (8.8%) with Whizaway UCDs; the proportion of contaminated samples was similar after device failure samples were excluded. Conclusion: Neither Peezy nor Whizaway UCDs reduced sample contamination when used by women presenting to primary care with suspected UTI. Their use cannot be recommended for this purpose in this setting.


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