Incidence and Diagnostic Yield of Repeat Urine Culture in Hospitalized Patients: an Opportunity for Diagnostic Stewardship

Abstract

There is limited knowledge on the incidence, diagnostic yield, and cost associated with inappropriate repeat urine cultures. The factors that affect repeat urine culturing practices are not well understood. We conducted a retrospective study of adult inpatients who had ≥1 urine culture performed during their hospitalization between January 2015 and February 2018. We analyzed the proportion of inappropriate repeat urine cultures performed <48 h after the index culture. We defined an inappropriate repeat urine culture to be a repeat urine culture performed following a negative index culture or a repeat urine specimen obtained from the same urinary catheter. Overall, 28,141 urine cultures were performed on 21,306 patients. There were 2,060 (7.3%) urine cultures repeated in <48 h. Of these, 1,120 (54.4%) urine cultures were inappropriate. Predictors for inappropriate repeat urine cultures included collection of the initial urine sample for culture in the emergency department (adjusted odds ratio [aOR], 5.65; 95% confidence interval [CI], 4.70 to 6.78), male gender (aOR, 1.61; 95% CI, 1.42 to 1.84), congestive heart failure (aOR, 1.20; 95% CI, 1.03 to 1.38), and a longer hospital stay (aOR, 1.01 per day; 95% CI, 1.00 to 1.01). A patient with an index urine culture obtained from an indwelling catheter (aOR, 0.65; 95% CI, 0.53 to 0.80) was less likely to have an inappropriate repeat culture. Among 1,120 negative index urine cultures, only 4.7% of repeat cultures were positive for bacteriuria. The estimated laboratory charges for inappropriate repeat urine cultures were $16,800 over the study period. Among inpatients, over half of all urine cultures repeated in <48 h were inappropriate. This offers an opportunity for diagnostic stewardship and optimization of antimicrobial use.

Urinary Infections in a Hospital Unit in Central Portugal – 5-Year Analysis

“…4.1% of the individuals in the sample were taking antibiotics at the time of collecting urine for urine culture, which goes against good microbiological practices, as the presence of the drug in the body leads to changes in the flora and leads to difficulties in identification microbiology at laboratory level. It may also be a factor that leads to the inability to identify the microorganism present in urine, requiring repeat collections and new laboratory procedures, with a consequent increase in diagnostic time and costs [29]. However, considering that more than 60% of these people were hospitalized, antibiotics will be clinically advised, even possibly for other pathologies, and the urinary infection may have been subsequent and, as we saw previously, even resulted from a procedure associated with healthcare.…”

Machine learning-assisted decision-support models to better predict patients with calculous pyonephrosis

“…The relevant laboratory parameters included preoperative peripheral white blood cell (WBC) counts, preoperative peripheral neutrophil counts, serum C-reactive protein (CRP), urine leukocyte counts, urine nitrite, and urine culture results. Urine culture with a single microorganism growth of 10 5 colony forming units (CFU)/mL for a sterile midstream urine sample and 10 4 CFU/mL for a catheterized sample were considered positive results (20). The CT attenuation value [Hounsfield units (HU)] of renal pelvis urine was obtained and calculated automatically from picture archiving and communication systems (PACS) (13).…”

Diagnostic Stewardship Protocol to Reduce Urine Contamination: A Quality Improvement Project

“…DSPs are becoming more widespread and have been used to develop methods to lower contamination rates. 8 Sum Foong et al 9 used a DSP to evaluate UC reordering within the first 48 hours of a patient admission and found that 54.4% of repeat UCs were done inappropriately, and, of those, only 4.7% yielded any additional benefit due to contamination. Dolan and Cornish 6 evaluated the use of a multidisciplinary team to formulate a 3-step preanalytical protocol aimed at reducing urine contamination and found that such interventions aimed at improving specimen collection, handling, and labeling practices significantly reduced both contamination rates and financial costs.…”