Asymptomatic Bacteriuria and Pyuria in Premenopausal Women

Type 1 fimbrial phase variation in multidrug-resistant asymptomatic uropathogenic Escherichia coli clinical isolates upon adherence to HTB-4 cells

The adherence of bladder uroepithelial cells, subsequent expression, and regulation of type 1 fimbrial genes (key mediator of attachment) in clinical multidrug-resistant uropathogenic Escherichia coli (MDR-UPECs) isolated from individuals with asymptomatic bacteriuria (ABU) remain unexplored till date. Therefore, this study aimed to investigate the underlying molecular mechanisms associated with the adherence of clinical MDR-ABU-UPECs to human a uroepithelial cell line (HTB-4), both in the absence and presence of D-Mannose. These investigations focused on phase variation, expression, and regulation of type 1 fimbriae and were compared to a prototype ABU-strain (E. coli 83972) and symptomatic MDR-UPECs. Discordant to the ABU prototype strain, MDR-ABU-UPECs exhibited remarkable adhesive capacity that was significantly reduced after D-mannose exposure, fairly like the MDR symptomatic UPECs. The type 1 fimbrial phase variation, determined by the fim switch analysis, asserted the statistically significant incidence of "both OFF and ON" orientation among the adherent MDR-ABU-UPECs with a significant reduction in phase-ON colonies post-D-mannose exposure, akin to the symptomatic ones. This was indicative of an operative and alternating type 1 fimbrial phase switch. The q-PCR assay revealed a coordinated action of the regulatory factors; H-NS, IHF, and Lrp on the expression of FimB and FimE recombinases, which further controlled the function of fimH and fimA genes in ABU-UPECs, similar to symptomatic strains. Therefore, this study is the first of its kind to provide an insight into the regulatory crosstalk of different cellular factors guiding the adhesion of ABU-UPECs to the host. Additionally, it also advocated for the need to accurately characterize ABU-UPECs.

Predictive performance of urinalysis for urine culture results according to causative microorganisms: an integrated analysis with artificial intelligence

Urinary tract infections (UTIs) are pervasive and prevalent in both community and hospital settings. Recent trends in the changes of the causative microorganisms in these infections could affect the effectiveness of urinalysis (UA). We aimed to evaluate the predictive performance of UA for urinary culture test results according to the causative microorganisms. In addition, UA results were integrated with artificial intelligence (AI) methods to improve the predictive power. A total of 360,376 suspected UTI patients were enrolled from two university hospitals and one commercial laboratory. To ensure broad model applicability, only a limited range of clinical data available from commercial laboratories was used in the analyses. Overall, 53,408 (14.8%) patients were identified as having a positive urine culture. Among the UA tests, the combination of leukocyte esterase and nitrite tests showed the highest area under the curve (AUROC, 0.766; 95% CI, 0.764-0.768) for predicting urine culture positivity but performed poorly for Gram-positive bacteriuria (0.642; 0.637-0.647). The application of an AI model improved the predictive power of the model for urine culture results to an AUROC of 0.872 (0.870-0.875), and the model showed superior performance metrics not only for Gram-negative bacteriuria (0.901; 0.899-0.902) but also for Gram-positive bacteriuria (0.745; 0.740-0.749) and funguria (0.872; 0.865-0.879). As the prevalence of non-Escherichia coli-caused UTIs increases, the performance of UA in predicting UTIs could be compromised. The addition of AI technologies has shown potential for improving the predictive performance of UA for urine culture results.IMPORTANCEUA had good performance in predicting urine culture results caused by Gram-negative bacteria, especially for Escherichia coli and Pseudomonas aeruginosa bacteriuria, but had limitations in predicting urine culture results caused by Gram-positive bacteria, including Streptococcus agalactiae and Enterococcus faecalis. We developed and externally validated an AI model incorporating minimal demographic information of patients (age and sex) and laboratory data for UA, complete blood count, and serum creatinine concentrations. The AI model exhibited improved performance in predicting urine culture results across all the causative microorganisms, including Gram-positive bacteria, Gram-negative bacteria, and fungi.

From pre-test and post-test probabilities to medical decision making

BACKGROUND

A central goal of modern evidence-based medicine is the development of simple and easy to use tools that help clinicians integrate quantitative information into medical decision-making. The Bayesian Pre-test/Post-test Probability (BPP) framework is arguably the most well known of such tools and provides a formal approach to quantify diagnostic uncertainty given the result of a medical test or the presence of a clinical sign. Yet, clinical decision-making goes beyond quantifying diagnostic uncertainty and requires that that uncertainty be balanced against the various costs and benefits associated with each possible decision. Despite increasing attention in recent years, simple and flexible approaches to quantitative clinical decision-making have remained elusive.

METHODS

We extend the BPP framework using concepts of Bayesian Decision Theory. By integrating cost, we can expand the BPP framework to allow for clinical decision-making.

RESULTS

We develop a simple quantitative framework for binary clinical decisions (e.g., action/inaction, treat/no-treat, test/no-test). Let p be the pre-test or post-test probability that a patient has disease. We show thatr ∗ = ( 1 - p ) / p represents a critical value called a decision boundary. In terms of the relative cost of under- to over-acting, r ∗ represents the critical value at which action and inaction are equally optimal. We demonstrate how this decision boundary can be used at the bedside through case studies and as a research tool through a reanalysis of a recent study which found widespread misestimation of pre-test and post-test probabilities among clinicians.

CONCLUSIONS

Our approach is so simple that it should be thought of as a core, yet previously overlooked, part of the BPP framework. Unlike prior approaches to quantitative clinical decision-making, our approach requires little more than a hand-held calculator, is applicable in almost any setting where the BPP framework can be used, and excels in situations where the costs and benefits associated with a particular decision are patient-specific and difficult to quantify.

Using the Sysmex UF-4000 urine flow cytometer for rapid diagnosis of urinary tract infection in the clinical microbiological laboratory

BACKGROUND

Urinary tract infections are responsible for a significant worldwide disease burden. Performing urine culture is time consuming and labor intensive. Urine flow cytometry might provide a quick and reliable method to screen for urinary tract infection.

METHODS

We analyzed routinely collected urine samples received between 2020 and 2022 from both inpatients and outpatients. The UF-4000 urine flow cytometer was implemented with an optimal threshold for positivity of ≥100 bacteria/μL. We thereafter validated the prognostic value to detect the presence of urinary tract infection (UTI) based on bacterial (BACT), leukocyte (WBC), and yeast-like cell (YLC) counts combined with the bacterial morphology (UF gram-flag).

RESULTS

In the first phase, in 2019, the UF-4000 was implemented using 970 urine samples. In the second phase, between 2020 and 2022, the validation was performed in 42,958 midstream urine samples. The UF-4000 screen resulted in a 37% (n = 15,895) decrease in performed urine cultures. Uropathogens were identified in 18,673 (69%) positively flagged urine samples. BACT > 10.000/μL combined with a gram-negative flag had a >90% positive predictive value for the presence of gram-negative uropathogens. The absence of gram-positive flag or YLC had high negative predictive values (99% and >99%, respectively) and are, therefore, best used to rule out the presence of gram-positive bacteria or yeast. WBC counts did not add to the prediction of uropathogens.

CONCLUSION

Implementation of the UF-4000 in routine practice decreased the number of cultured urine samples by 37%. Bacterial cell counts were highly predictive for the presence of UTI, especially when combined with the presence of a gram-negative flag.

From Pre-test and Post-test Probabilities to Medical Decision Making

Background

A central goal of modern evidence-based medicine is the development of simple and easy to use tools that help clinicians integrate quantitative information into medical decision-making. The Bayesian Pre-test/Post-test Probability (BPP) framework is arguably the most well known of such tools and provides a formal approach to quantify diagnostic uncertainty given the result of a medical test or the presence of a clinical sign. Yet, clinical decision-making goes beyond quantifying diagnostic uncertainty and requires that that uncertainty be balanced against the various costs and benefits associated with each possible decision. Despite increasing attention in recent years, simple and flexible approaches to quantitative clinical decision-making have remained elusive.

Methods

We extend the BPP framework using concepts of Bayesian Decision Theory. By integrating cost, we can expand the BPP framework to allow for clinical decision-making.

Results

We develop a simple quantitative framework for binary clinical decisions (e.g., action/inaction, treat/no-treat, test/no-test). Let p be the pre-test or post-test probability that a patient has disease. We show that r * = ( 1 - p ) / p represents a critical value called a decision boundary. In terms of the relative cost of under- to over-acting, r * represents the critical value at which action and inaction are equally optimal. We demonstrate how this decision boundary can be used at the bedside through case studies and as a research tool through a reanalysis of a recent study which found widespread misestimation of pre-test and post-test probabilities among clinicians.

Conclusions

Our approach is so simple that it should be thought of as a core, yet previously overlooked, part of the BPP framework. Unlike prior approaches to quantitative clinical decision-making, our approach requires little more than a hand-held calculator, is applicable in almost any setting where the BPP framework can be used, and excels in situations where the costs and benefits associated with a particular decision are patient-specific and difficult to quantify.

The Prevalence and Association of Different Uropathogens Detected by M-PCR with Infection-Associated Urine Biomarkers in Urinary Tract Infections

Background

Many emerging uropathogens are currently identified by multiplex polymerase chain reaction (M-PCR) in suspected UTI cases. Standard urine culture (SUC) has significantly lower detection rates, raising questions about whether these organisms are associated with UTIs and truly cause inflammation.

Objective

To determine if microbes detected by M-PCR were likely causative of UTI by measuring inflammatory biomarkers in the urine of symptomatic patients.

Design Setting and Participants

Midstream voided urine was collected from subjects ≥60 years presenting to urology clinics with symptoms of UTI (n = 1132) between 01/2023 and 05/2023. Microbe detection was by M-PCR and inflammation-associated biomarker (neutrophil gelatinase-associated lipocalin, interleukin 8, and interleukin 1β) was by enzyme-linked immunosorbent assay. Biomarker positivity was measured against individual and groups of organisms, E. coli and non-E. coli cases, emerging uropathogens, monomicrobial and polymicrobial cases.

Outcome Measurements and Statistical Analysis

Distributions were compared using 2-sample Wilcoxon Rank Sum test with 2-tailed p-values < 0.05 considered statistically significant.

Results and Limitations

M-PCR was positive in 823 (72.7%) specimens with 28 of 30 (93%) microorganisms/groups detected. Twenty-six of twenty-eight detected microorganisms/groups (93%) had ≥2 biomarkers positive in >66% of cases. Both non-E. coli cases and E. coli cases had significant biomarker positivity (p < 0.05). Limitations were that a few organisms had low prevalence making inferences about their individual significance difficult.

Conclusion

The majority of microorganisms identified by M-PCR were associated with active inflammation measured by biomarker positivity, indicating they are likely causative of UTIs in symptomatic patients. This includes emerging uropathogens frequently not detected by standard urine culture.

Diagnostic and antibiotic stewardship lessons: an outpatient assessment of symptomatic reflex urinalysis ordering accuracy using an electronic best-practice alert

BACKGROUND

It is not well known how reliably clinicians order reflex urinalysis to microscopy and culture (rUA-cx) for outpatient urinary tract infection (UTI) workup. Antibiotic appropriateness cannot be fully appreciated until the prevalence of UTIs and asymptomatic bacteriuria (ASB) are realized.

OBJECTIVE

This quality improvement study has two major aims, first to determine UTI symptom accuracy for rUA-cx ordering and second, to confirm UTI and ASB cases by integrating rUA-cx and cascaded urinalysis results. Antibiotic utilization and diagnostic coding were secondarily linked to UTIs and ASB.

METHODS

An electronic best-practice alert informed the ordering of two rUA-cx options: symptomatic- rUA-cx specifically for dysuria, frequency, urgency, costovertebral pain, suprapubic pain or fever versus non-specific-rUA-cx for vague complaints. UTI symptoms were verified by chart review. Confirmed UTI was defined as a significant culture with UTI symptoms and ASB as a significant culture without UTI symptoms.

RESULTS

rUA-cx (2065) were prospectively collected over 6 months from female patients at risk for uncomplicated UTIs. Symptomatic-rUA-cx and non-specific-rUA-cx were associated with UTI symptoms for 53% (809/1527) and 20% (107/538), respectively. Overall, 44% (916/2065) of all rUA-cx had UTI symptoms. rUA-cx were overordered by a factor of 9 (2065/225) for every confirmed UTI. The UTI-to-ASB relative ratio was 2.6 (225/86). Regarding UTI-relevant antibiotics, 39% (214/553) were appropriately associated with UTI whereas only 22% (74/339) of inappropriate antibiotics were captured by the ASB definition, underestimating the problem 4-fold.

CONCLUSIONS

UTI and ASB remain challenging to categorize despite a meticulous method that applied acceptable criteria.

Elevated UTI Biomarkers in Symptomatic Patients with Urine Microbial Densities of 10,000 CFU/mL Indicate a Lower Threshold for Diagnosing UTIs

The literature lacks consensus on the minimum microbial density required for diagnosing urinary tract infections (UTIs). This study categorized the microbial densities of urine specimens from symptomatic UTI patients aged ≥ 60 years and correlated them with detected levels of the immune response biomarkers neutrophil gelatinase-associated lipocalin (NGAL), interleukin-8 (IL-8), and interleukin-1-beta (IL-1β). The objective was to identify the microbial densities associated with significant elevation of these biomarkers in order to determine an optimal threshold for diagnosing symptomatic UTIs. Biobanked midstream voided urine samples were analyzed for microbial identification and quantification using standard urine culture (SUC) and multiplex-polymerase chain reaction (M-PCR) testing, while NGAL, IL-8, and IL-1β levels were measured via enzyme-linked immunosorbent assay (ELISA). NGAL, IL-8, and IL-1β levels were all significantly elevated at microbial densities ≥ 10,000 cells/mL when measured via M-PCR (p < 0.0069) or equivalent colony-forming units (CFUs)/mL via SUC (p < 0.0104) compared to samples with no detectable microbes. With both PCR and SUC, a consensus of two or more elevated biomarkers correlated well with microbial densities > 10,000 cells/mL or CFU/mL, respectively. The association between ≥10,000 cells and CFU per mL with elevated biomarkers in symptomatic patients suggests that this lower threshold may be more suitable than 100,000 CFU/mL for diagnosing UTIs.

Current Pyuria Cutoffs Promote Inappropriate Urinary Tract Infection Diagnosis in Older Women

BACKGROUND

Pre-existing lower urinary tract symptoms (LUTS), cognitive impairment, and the high prevalence of asymptomatic bacteriuria (ASB) complicate the diagnosis of urinary tract infection (UTI) in older women. The presence of pyuria remains the cornerstone of UTI diagnosis. However, >90% of ASB patients have pyuria, prompting unnecessary treatment. We quantified pyuria by automated microscopy and flowcytometry to determine the diagnostic accuracy for UTI and to derive pyuria thresholds for UTI in older women.

METHODS

Women ≥65 years with ≥2 new-onset LUTS and 1 uropathogen ≥104 colony-forming units (CFU)/mL were included in the UTI group. Controls were asymptomatic and classified as ASB (1 uropathogen ≥105 CFU/mL), negative culture, or mixed flora. Patients with an indwelling catheter or antimicrobial pretreatment were excluded. Leukocyte medians were compared and sensitivity-specificity pairs were derived from a receiver operating characteristic curve.

RESULTS

We included 164 participants. UTI patients had higher median urinary leukocytes compared with control patients (microscopy: 900 vs 26 leukocytes/µL; flowcytometry: 1575 vs 23 leukocytes/µL; P < .001). Area under the curve was 0.93 for both methods. At a cutoff of 264 leukocytes/µL, sensitivity and specificity of microscopy were 88% (positive and negative likelihood ratio: 7.2 and 0.1, respectively). The commonly used cutoff of 10 leukocytes/µL had a poor specificity (36%) and a sensitivity of 100%.

CONCLUSIONS

The degree of pyuria can help to distinguish UTI in older women from ASB and asymptomatic controls with pyuria. Current pyuria cutoffs are too low and promote inappropriate UTI diagnosis in older women. Clinical Trials Registration. International Clinical Trials Registry Platform: NL9477 (https://trialsearch.who.int/Trial2.aspx?TrialID=NL9477).

Building a nomogram plot based on the nanopore targeted sequencing for predicting urinary tract pathogens and differentiating from colonizing bacteria

Background

The identification of uropathogens (UPBs) and urinary tract colonizing bacteria (UCB) conduces to guide the antimicrobial therapy to reduce resistant bacterial strains and study urinary microbiota. This study established a nomogram based on the nanopore-targeted sequencing (NTS) and other infectious risk factors to distinguish UPB from UCB.

Methods

Basic information, medical history, and multiple urine test results were continuously collected and analyzed by least absolute shrinkage and selection operator (LASSO) regression, and multivariate logistic regression was used to determine the independent predictors and construct nomogram. Receiver operating characteristics, area under the curve, decision curve analysis, and calibration curves were used to evaluate the performance of the nomogram.

Results

In this study, the UPB detected by NTS accounted for 74.1% (401/541) of all urinary tract microorganisms. The distribution of ln(reads) between UPB and UCB groups showed significant difference (OR = 1.39; 95% CI, 1.246-1.551, p < 0.001); the reads number in NTS reports could be used for the preliminary determination of UPB (AUC=0.668) with corresponding cutoff values being 7.042. Regression analysis was performed to determine independent predictors and construct a nomogram, with variables ranked by importance as ln(reads) and the number of microbial species in the urinary tract of NTS, urine culture, age, urological neoplasms, nitrite, and glycosuria. The calibration curve showed an agreement between the predicted and observed probabilities of the nomogram. The decision curve analysis represented that the nomogram would benefit clinical interventions. The performance of nomogram with ln(reads) (AUC = 0.767; 95% CI, 0.726-0.807) was significantly better (Z = 2.304, p-value = 0.021) than that without ln(reads) (AUC = 0.727; 95% CI, 0.681-0.772). The rate of UPB identification of nomogram was significantly higher than that of ln(reads) only (χ^2 = 7.36, p-value = 0.009).

Conclusions

NTS is conducive to distinguish uropathogens from colonizing bacteria, and the nomogram based on NTS and multiple independent predictors has better prediction performance of uropathogens.

Urinalysis exhibits excellent predictive capacity for the absence of urinary tract infection

OBJECTIVES

To assess predictive value of urinalysis for negative urine culture and absence of urinary tract infection, re-evaluate the microbial growth threshold for positive urine culture result, and describe antimicrobial resistance features. Urine culture is associated with 27% of U.S. hospitalizations, and unnecessary antibiotic prescription is a main antibiotic resistance contributor.

SUBJECTS AND METHODS

Urinalyses with urine culture from women ages 18-49 from 2013 to 2020 were studied. Clinically-diagnosed urinary tract infection (CUTI) was defined as 1) uropathogen growth, 2) documented diagnosis of urinary tract infection, and 3) antibiotic prescription. Sensitivity, specificity, and diagnostic predictive values were used to assess urinalysis performance in predicting isolation of a uropathogen by culture and in detection of CUTI.

RESULTS

12,252 urinalyses were included. 41% of urinalyses were associated with positive urine culture and 1287 (10.5%) with CUTI. Negative urinalysis exhibited high predictive accuracy for negative urine culture (specificity 90.3%, PPV 87.3%) and absence of CUTI (specificity 92.2%, PPV 97.4%). 24% of patients not meeting the CUTI definition were still prescribed antibiotics. 22% of cultures associated with CUTI exhibited growth less than 100,000 CFU/ml. Escherichia coli was implemented as causing 70% of CUTIs, and 4.2% of these produced an extended spectrum beta-lactamase.

CONCLUSIONS

Negative urinalysis exhibits high predictive accuracy for absence of CUTI. A reporting threshold of 10,000 CFU/ml is more clinically appropriate than a 100,000 CFU/ml cutpoint. Reflex culture based on urinalysis results could complement clinical judgement and improve laboratory and antibiotic stewardship in pre-menopausal women.

Persistent Escherichia coli infection in renal tubular cells enhances calcium oxalate crystal-cell adhesion by inducing ezrin translocation to apical membranes via Rho/ROCK pathway

Recent evidence has suggested that recurrent urinary tract infection (UTI) can cause not only infection stones but also metabolic stones (e.g., those containing calcium oxalate monohydrate or COM). However, precise mechanisms underlying UTI-induced metabolic stones remained unknown. In this study, Escherichia coli, the most common bacterium found in recurrent UTI was used to establish the in vitro model for persistent infection of renal epithelial cells. The promoting effects of persistent E. coli infection on kidney stone formation were validated by COM crystal-cell adhesion assay, followed by immunofluorescence study for changes in surface expression of the known COM crystal receptors. Among the five receptors examined, only ezrin had significantly increased level on the surface of persistently infected cells without change in its total level. Such translocation of ezrin to apical membranes was confirmed by Western blotting of apical membrane and cytosolic fractions and confocal microscopic examination. Additionally, persistent infection increased phosphorylation (Thr567) of ezrin. However, all of these changes induced by persistent E. coli infection were significantly inhibited by small-interfering RNA (siRNA) specific for ezrin or a Rho-associated kinase (ROCK)-specific inhibitor (Y-27632). In summary, this study provides a piece of evidence demonstrating that persistent infection by E. coli, one of the non-urease-producing bacteria, may contribute to COM metabolic stone formation by translocation of ezrin to apical membranes, thereby promoting COM crystal-cell adhesion. Such ezrin translocation was mediated via Rho/ROCK signaling pathway. These findings may, at least in part, explain the pathogenic mechanisms underlying recurrent UTI-induced metabolic kidney stone disease.

The Five Ds of Outpatient Antibiotic Stewardship for Urinary Tract Infections

Urinary tract infections (UTI) are one of the most common indications for antibiotic prescriptions in the outpatient setting. Given rising rates of antibiotic resistance among uropathogens, antibiotic stewardship is critically needed to improve outpatient antibiotic use, including in outpatient clinics (primary care and specialty clinics) and emergency departments. Outpatient clinics are in general a neglected practice area in antibiotic stewardship programs, yet most antibiotic use in the United States is in the outpatient setting. This article provides a comprehensive review of antibiotic stewardship strategies for outpatient UTI in the adult population, with a focus on the "five Ds" of stewardship for UTI, including right diagnosis, right drug, right dose, right duration, and de-escalation. Stewardship interventions that have shown success for improving prescribing for outpatient UTI are discussed, including diagnostic stewardship strategies, such as reflex urine cultures, computerized decision support systems, and modified reporting of urine culture results. Among the many challenges to achieving stewardship for UTI in the outpatient setting, some of the most important are diagnostic uncertainty, increasing antibiotic resistance, limitations of guidelines, and time constraints of stewardship personnel and front-line providers. This article presents a stewardship framework, built on current evidence and expert opinion, that clinicians can use to guide their own outpatient management of UTI.

Preoperative bacteriuria positivity on urinalysis increases wound complications in primary total hip arthroplasty regardless of the urine culture result

BACKGROUND

Current evidence does not recommend screening urine culture and curing asymptomatic bacteriuria (ASB) before joint arthroplasty. The bacteriuria count on pre-operative urinalysis is a more common clinical parameter. We aimed to investigate whether the bacteriuria count on preoperative urinalysis can increase postoperative wound complications in primary total hip arthroplasty (THA).

METHODS

We conducted a retrospective study that included patients who underwent primary THA in our institution from 2012 to 2018. We obtained preoperative urinalysis results before THA during the same hospitalization and identified patients with abnormal urinalysis. Receiver operating characteristic (ROC) curves were first generated to evaluate the predicted value of leukocyte esterase (LE), nitrite, bacteriuria, and pyuria in the urinalysis for superficial wound infection. Then, all included patients were divided into two groups according to the preoperative urinalysis: a bacteriuria-positive group and a bacteriuria-negative group. The primary outcome was the superficial wound infection rate within 3 months postoperatively, and the secondary outcomes included wound leakage, prosthetic joint infection (PJI), pulmonary infection, urinary tract infection (UTI), readmission rate within 3 months postoperatively, and length of stay (LOS) during hospitalization. We utilized univariable analyses to compare the outcomes between the two groups. A multivariable logistic regression model was generated to explore the potential association between bacteriuria and the risk of superficial wound infection, wound leakage, and readmission rate controlling for baseline values.

RESULTS

A total of 963 patients were included in the study. One hundred sixty patients had abnormal urinalysis. The AUCs for LE, nitrite, bacteriuria, and pyuria were 0.507 (95% confidence interval (CI), 0.315 to 0.698), 0.551 (0.347 to 0.756), 0.675 (0.467 to 0.882), and 0.529 (0.331 to 0.728), respectively. Bacteriuria was diagnostically superior to LE, nitrite, and pyuria. Among the 963 patients, 95 had a positive bacteriuria on preoperative urinalysis, and only 9 (9.5%) had a positive urine culture. Compared with the bacteriuria-negative group, the bacteriuria-positive group had a higher superficial wound infection rate (4.2% vs. 0.6%, P = 0.008), higher wound leakage rate (11.6% vs. 4.5%, P = 0.007), higher readmission rate (5.3% vs. 1.3%, P = 0.015) within 3 months postoperatively and longer LOS (6.19 ± 2.89 days vs. 5.58 ± 2.14 days, P = 0.011). After adjustment, the bacteriuria-positive group had a significantly increased risk of superficial wound infection (OR = 7.587, 95%CI: 2.002 to 28.755, P = 0.003), wound leakage (OR = 3.044, 95%CI: 1.461 to 6.342, P = 0.003), and readmission (OR = 4.410, 95%CI: 1.485 to 13.097, P = 0.008).

CONCLUSION

Preoperative bacteriuria positivity on urinalysis significantly increased the risk of postoperative wound complications, readmission, and LOS in primary THA regardless of the result of the urine culture. Urinalysis is a fast and cost-acceptable test whose advantages have been underestimated.

LEVEL OF EVIDENCE

Level III, observational study.

Envisioning Future UTI Diagnostics

Urinary tract infections (UTIs) are among the most common bacterial infections in the United States and are a major driver of antibiotic use - both appropriate and inappropriate - across healthcare settings. UTI treatment has become complex due to antibacterial resistance; one quarter of urinary tract isolates of Escherichia coli in the United States in 2017 were resistant to fluoroquinolones and one third to trimethoprimsulfamethoxazole (1), agents with historically predictable activity against E. coli. As a result, more broad-spectrum antibiotics are being used to treat UTIs, contributing to selection of further antibiotic resistance.