ArticleInfection and drug resistance2022
Predictive Value of a Quick Pitt Bacteremia Score for Prognosis of Patients with Bloodstream Infection Secondary to Urinary Tract Infection: A Retrospective Cohort Study.
Article in Infection and drug resistance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 10 citations in OpenAlex.
- Urinary bacterial count as a predictor of concomitant bacteremia in adults with community-acquired Enterobacterales urinary tract infections.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Article
- Bacteremia complicating urinary tract infections in hospitalized patients in a tertiary care hospital in Palestine, retrospective study.BMC infectious diseases · 2026Article
- Clinical characteristics and risk factors ofFrontiers in microbiology · 2026Article
- Construction and validation of a predictive in-hospital mortality nomogram in patients with staphylococcus aureus bloodstream infection.Scientific reports · 2025Article
- Personalized machine learning-based prognostic model for ICU-acquired bloodstream infections.Frontiers in cellular and infection microbiology · 2025Article
- Species Distribution, Typical Clinical Features and Risk Factors for Poor Prognosis of Super-Elderly Patients with Bloodstream Infection in China.Infection and drug resistance · 2024Article
- A predictive model for the identification of the risk of sepsis in patients with Gram-positive bacteria in the intensive care unit.Journal of thoracic disease · 2023Article
- Antimicrobial Peptides Demonstrate Activity against Resistant Bacterial Pathogens.Infectious disease reports · 2023Review
- Prediction of 30-Day Mortality Using the Quick Pitt Bacteremia Score in Hospitalized Patients withInfection and drug resistance · 2023Article
- Acute kidney injury should not be neglected - optimization of quick Pitt bacteremia score for predicting mortality in critically ill patients with bloodstream infection: a retrospective cohort study.Therapeutic advances in infectious diseaseArticle
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7 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Purpose: To analyze the effect of a quick Pitt bacteremia score (qpitt) on the prognosis of patients with bloodstream infection (BSI) secondary to urinary tract infection (UTI) and to further explore its use in aiding appropriate selection of initial antibiotic treatment. Methods: Medical records of patients with BSIs secondary to UTIs who were admitted to our hospital from January 2018 to December 2020 were retrospectively collected. To screen for independent risk factors, logistic analysis was conducted on statistically significant variables. The receiver operating characteristic (ROC) curve was drawn with prognosis and death as the state variables to evaluate the predictive value. Patients were grouped by qpitt 2-point cutoff, to explore the impact of initial antimicrobial treatment regimens on poor prognosis and death in different subgroups. Poor prognosis was defined as a hospital length of stay (HLOS) ≥14 days or death within 28 days from BSI onset (ie, 28-day death). Results: A total of 266 patients were included in this study. In BSIs secondary to UTIs, we observed a pathogenic composition of 77.44% Gram-negative bacteria, 19.55% Gram-positive bacteria, and 3.01% fungi. The qpitt had poor predictive value for poor prognosis [area under ROC (AUROC) = 0.653, p < 0.001], while it had a high predictive value for death (AUROC = 0.890, p < 0.001). For patients with a qpitt ≥2, the poor prognosis and death rates of patients who were initially treated with carbapenem antibiotics were lower (p < 0.01). In comparison, initial treatment with carbapenem antibiotics had no significant effect on prognosis and death rates in patients with qpitt <2 (p > 0.1). Conclusion: The qpitt is highly predictive for death in patients with BSIs secondary to UTIs and can be used to inform first-line antibiotic treatment strategy.
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