Adult urinary tract infection

Recurrent Cystitis in Women-A Real-World Analysis of Bacteria Spectrum and Resistance Situation for Calculated Therapy

Recurrent cystitis in women represents an everyday challenge; however, little to no data regarding this population are available. This study aimed to evaluate this collective with respect to a rational calculated antibiotic therapy. Urine cultures and antibiograms from a urological office were retrospectively evaluated from patient data collected between January 2017 and June 2019. The evaluation was conducted using SPSS ©. In total, 84 female patients, who were aged between 18 and 87 years old (median 60 years), suffered from recurrent cystitis. Escherichia coli was found in 53.9% of cases, Staphylococcus aureus and enterococci were each found in 6.7%, and Proteus spp. and Streptococcus agalactiae were each found in 5.6%. The resistance levels to ciprofloxacin (CIP), trimethoprim-sulfamethoxazole (TRS), nitrofurantoin (NIT), and nitroxoline (NOX) were 18.2%, 30.7%, 16.1%, and 12.5% in the tested cases, respectively. Regarding E. coli, resistance to CIP, TRS, and NIT was found in 17.8%, 25%, and 4.2% of the tested cases, and no resistance to NOX was found. The resistance level to CIP was in a tolerable range of <20% in the overall cohort and the E. coli subgroup. More than a quarter of the bacteria were resistant to TRS. The low resistance rates for NIT and NOX are remarkable, promoting the use of these substances if they are not yet used.

Point-of-Care Pathogen Testing Using Photonic Crystals and Machine Vision for Diagnosis of Urinary Tract Infections

Urinary tract infections (UTIs) caused by bacterial invasion can lead to life-threatening complications, posing a significant health threat to more than 150 million people worldwide. As a result, there is need for accurate and rapid diagnosis of UTIs to enable more effective treatment. Described here is an intelligent diagnostic system constructed for bacterial detection using an immunobiosensor, signal-amplification biochip, and image processing algorithm based on machine vision. This prototype can quickly detect bacteria by collection of enhanced luminescence enabled by the photonic crystals integrated into the biochip. By use of a machine vision algorithm, the very small luminescence signals are analyzed to provide a low detection limit and wide dynamic range. This sensor system can offer an affordable, accessible, and user-friendly digital diagnostic solution, possibly suitable for wearable technology, that could improve treatment of this challenging disease.

[Recurrent and catheter-associated urinary tract infections : Prophylaxis and prevention]

Urinay tract infection (UTI) as one of the most frequent bacterial infections in humans is of utmost relevance. Because of the rising prevalence of antimicrobial resistance, urinalysis should always include urine culture and a resistogram in order to avoid an unspecific selection and overuse of antibiotics. Prevention of recurrent UTI must first of all rule out predisposing uropathogenic conditions. Nowadays, a great variety of drugs, behavioral, and supportive treatment options can effectively minimize UTI recurrence. The growing importance of vaccines (immunotherapy), probiotics (lactobacilli), and standardized herbal preparations meets the need of reducing antibiotic use and the development of antimicrobial resistance. Around 80% of all nosocomial UTIs (nUTIs) are associated with indwelling urinary catheters. It is estimated that up to 70% of all nUTIs occurring in Germany may be avoided by using appropriate preventative measures. Therefore, profound knowledge about the basics of catheter-associated nUTIs and the correct management of urinary catheters are of utmost individual and socioeconomic importance.

Comparison of antibiotic resistance patterns in collections of Escherichia coli and Proteus mirabilis uropathogenic strains

Escherichia coli and Proteus mirabilis are important urinary tract pathogens. The constant increase in the antibiotic resistance of clinical bacterial strains has become an important clinical problem. The aim of this study was to compare the antibiotic resistance of 141 clinical (Sweden and Poland) and 42 laboratory (Czech Republic) P.mirabilis strains and 129 clinical (Poland) uropathogenic E. coli strains. The proportion of unique versus diverse patterns in Swedish clinical and laboratory P. mirabilis strain collections was comparable. Notably, a similar proportion of unique versus diverse patterns was observed in Polish clinical P. mirabilis and E. coli strain collections. Mathematical models of the antibiotic resistance of E. coli and P. mirabilis strains based on Kohonen networks and association analysis are presented. In contrast to the three clinical strain collections, which revealed complex associations with the antibiotics tested, laboratory P. mirabilis strains provided simple antibiotic association diagrams. The monitoring of antibiotic resistance patterns of clinical E. coli and P. mirabilis strains plays an important role in the treatment procedures for urinary tract infections and is important in the context of the spreading drug resistance in uropathogenic strain populations. The adaptability and flexibility of the genomes of E. coli and P.mirabilis strains are discussed.