Identifying key blood markers for bacteremia in elderly patients: insights into bacterial pathogens

Frontiers in Cellular and Infection Microbiology, Journal Year: 2025, Volume and Issue: 14

Published: Jan. 16, 2025

This study aimed to assess the distribution of bacteremia pathogens in elderly patients, examine impact gender on pathogen distribution, and evaluate predictive value routine blood parameters for diagnosing bacteremia. A retrospective analysis was conducted 151 patients (≥60 years old) admitted Fuding Hospital, Fujian University Traditional Chinese Medicine between October 2022 June 2023. Comprehensive tests cultures were performed. The diagnostic efficacy parameters, including white cell (WBC), neutrophil-to-lymphocyte ratio (NLR), platelet-lymphocyte (PLR), red width (RDW), evaluated using receive operating characteristic (ROC) curve analysis. Patients categorized into either culture-positive group (82 cases) or culture-negative (69 according culture results. No significant differences age found groups. primary bacterial Escherichia coli, Klebsiella pneumoniae Streptococcus. Elderly female demonstrated a significantly higher positivity rate E. coli compared their male counterparts (P = 0.021). areas under ROC (AUC) four as follows: WBC, 0.851 (95% confidence interval (CI) 0.790 - 0.912); NLR, 0.919 CI 0.875 0.963); PLR, 0.609 0.518 0.700); RDW 0.626 0.563 0.717). identified predominant pathogenic microorganism causing elderly, with among patients. Routine (WBC, RDW) potential

Language: Английский

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Zebrafish: A trending model for gut-brain axis investigation

Aquatic Toxicology, Journal Year: 2024, Volume and Issue: 270, P. 106902 - 106902

Published: March 17, 2024

Language: Английский

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Random forest differentiation of Escherichia coli in elderly sepsis using biomarkers and infectious sites

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: June 5, 2024

Abstract This study addresses the challenge of accurately diagnosing sepsis subtypes in elderly patients, particularly distinguishing between Escherichia coli (E. coli) and non- E. infections. Utilizing machine learning, we conducted a retrospective analysis 119 employing random forest model to evaluate clinical biomarkers infection sites. The demonstrated high diagnostic accuracy, with an overall accuracy 87.5%, impressive precision recall rates 93.3% respectively. It identified sites, platelet distribution width, reduced count, procalcitonin levels as key predictors. achieved F1 Score 90.3% area under receiver operating characteristic curve 88.0%, effectively differentiating subtypes. Similarly, logistic regression least absolute shrinkage selection operator underscored significance infectious methodology shows promise for enhancing diagnosis contributing advancement medicine field diseases.

Language: Английский

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Seasonal variation in intravenous broad-spectrum antimicrobial use in Japan from 2018 to 2023

Journal of Infection and Chemotherapy, Journal Year: 2025, Volume and Issue: unknown, P. 102636 - 102636

Published: Jan. 1, 2025

Language: Английский

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Clinical presentation and antibiotic resistance trends of Escherichia coli isolated from clinical samples in South India: A two-year study (2022–2023)

Infection Disease & Health, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

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Urinary tract infections and antimicrobial susceptibility: A retrospective trend analysis of uropathogens in women in Accra, Ghana (2019–2022)

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(4), P. e0321293 - e0321293

Published: April 4, 2025

Urinary tract infections (UTIs) remain a significant public health concern, with evolving patterns in prevalence and antimicrobial resistance. This retrospective study, conducted at the Greater Accra Regional Hospital Accra, Ghana, analyzed 11,280 urine cultures obtained exclusively from female patients 2019 to 2022 assess trends UTI burden, stratified by age month, susceptibility patterns. In all, pathogens were isolated 4475 (39.67%) of samples tested. Of total number uropathogens isolated, majority them bacterial (94.21%), an increasing proportion fungal infections, specifically candida species (5.79%). Irrespective year, highest consistently recorded month May, while individuals aged ≥ 90 years exhibited greatest odds infection 2020 (aOR: 1.88, p = 0.039). Escherichia coli (30.51%) Staphylococcus aureus (15.16%) most prevalent Gram-negative Gram-positive pathogens, respectively. Antimicrobial testing revealed declining antibiotic effectiveness over time, notable exceptions for gentamicin (97.4% against Enterococcus spp.) ofloxacin (82.9% spp.). Alarmingly, antibiotics rates below 20% 2022, underscoring growing resistance challenge. These findings, drawn key healthcare facility Ghana’s capital, highlight dynamic nature UTIs urgent need targeted interventions, optimized stewardship, continuous monitoring improve patient outcomes.

Language: Английский

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Machine Learning Analysis of Biomarkers and Infectious Sites in Elderly Sepsis: Distinguishing Escherichia coli from Non-Escherichia coli Infections with a Random Forest Model

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: March 6, 2024

Abstract This study examines the challenge of accurately diagnosing sepsis subtypes in elderly patients, focusing on distinguishing between Escherichia coli and non-E. infections. Utilizing machine learning, we conducted a retrospective analysis 119 employing Random Forest model to evaluate clinical biomarkers infection sites. The demonstrated high diagnostic accuracy, with an overall accuracy 87.5%, impressive precision recall rates 93.3% respectively. It identified site, Platelet Distribution Width (PDW), platelet count, Procalcitonin (PCT) levels as key predictors, while logistic regression underscored significance smoking. Achieving F1 Score 90.3% ROC AUC 88.0%, our effectively differentiates subtypes. methodology offers potential for enhancing diagnosis, improving patient outcomes, contributing advancement medicine field infectious diseases.

Language: Английский

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Prevalence and antibiotic resistance profile of UTI-causing uropathogenic bacteria in diabetics and non-diabetics at the Maternity and Children Hospital in Jeddah, Saudi Arabia

Frontiers in Microbiology, Journal Year: 2024, Volume and Issue: 15

Published: Nov. 28, 2024

One of the most prevalent and recurrent infectious diseases that can range from moderate to fatal is urinary tract infection (UTI). Broad-spectrum antibiotics are only management strategy for UTIs in ambulators hospital stays. Due ongoing emergence antibiotic resistance among uropathogens, there a need proper selection empirical therapy against UTIs. This study aimed compare etiological profiles susceptibility patterns between diabetic non-diabetic UTI female patients Maternity Children Hospital Jeddah, Saudi Arabia.

Language: Английский

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