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1.
Isr Med Assoc J ; 26(5): 299-303, 2024 May.
Artículo en Inglés | MEDLINE | ID: mdl-38736345

RESUMEN

BACKGROUND: Group A Streptococcus (GAS) is the predominant bacterial pathogen of pharyngitis in children. However, distinguishing GAS from viral pharyngitis is sometimes difficult. Unnecessary antibiotic use contributes to unwanted side effects, such as allergic reactions and diarrhea. It also may increase antibiotic resistance. OBJECTIVES: To evaluate the effect of a machine learning algorithm on the clinical evaluation of bacterial pharyngitis in children. METHODS: We assessed 54 children aged 2-17 years who presented to a primary healthcare clinic with a sore throat and fever over 38°C from 1 November 2021 to 30 April 2022. All children were tested with a streptococcal rapid antigen detection test (RADT). If negative, a throat culture was performed. Children with a positive RADT or throat culture were considered GAS-positive and treated antibiotically for 10 days, as per guidelines. Children with negative RADT tests throat cultures were considered positive for viral pharyngitis. The children were allocated into two groups: Group A streptococcal pharyngitis (GAS-P) (n=36) and viral pharyngitis (n=18). All patients underwent a McIsaac score evaluation. A linear support vector machine algorithm was used for classification. RESULTS: The machine learning algorithm resulted in a positive predictive value of 80.6 % (27 of 36) for GAS-P infection. The false discovery rates for GAS-P infection were 19.4 % (7 of 36). CONCLUSIONS: Applying the machine-learning strategy resulted in a high positive predictive value for the detection of streptococcal pharyngitis and can contribute as a medical decision aid in the diagnosis and treatment of GAS-P.


Asunto(s)
Aprendizaje Automático , Faringitis , Infecciones Estreptocócicas , Streptococcus pyogenes , Humanos , Faringitis/microbiología , Faringitis/diagnóstico , Niño , Proyectos Piloto , Infecciones Estreptocócicas/diagnóstico , Infecciones Estreptocócicas/tratamiento farmacológico , Preescolar , Masculino , Femenino , Streptococcus pyogenes/aislamiento & purificación , Adolescente , Sistemas de Apoyo a Decisiones Clínicas , Antibacterianos/uso terapéutico , Antibacterianos/administración & dosificación , Enfermedad Aguda , Diagnóstico Diferencial , Algoritmos
2.
Pathogens ; 13(3)2024 Feb 24.
Artículo en Inglés | MEDLINE | ID: mdl-38535544

RESUMEN

Urinary tract infections (UTIs) in childhood are common and are associated with considerable acute morbidity and long-term complications. The need for updated data to optimize empiric antibiotic therapy is crucial. We aimed to investigate the pathogens causing pediatric community acquired UTIs, their correlation with demographic characteristics, and trends in their antimicrobial resistance. This nationwide cross-sectional study included all 53,203 children (<18 years) diagnosed with UTI in community outpatient clinics in the following selected years: 2007, 2011, 2015, 2019 and 2021. Escherichia coli (E. coli) (82.1%) was the most common uropathogen, followed by Enterobacter, Klebsiella, Proteus, Pseudomonas, and Enterococcus species. The bacterial distribution displayed statistically significant (p < 0.0001) gender- and sector-specific patterns with a higher relative prevalence of non-E. coli UTI in Jewish and males. The rate of extended-spectrum beta-lactamase-positive E. coli increased substantially and significantly (p < 0.001) from only 6.1% in 2007 to 25.4% in 2021. Most non-E. coli uropathogens exhibited resistance to commonly used empiric antibiotics for UTIs in children. These findings are significant in guiding optimal empiric antibiotic treatment for pediatric community acquired UTIs. The resistance of uropathogens to antimicrobials is region- and time-dependent. Therefore, the periodic and local assessment of antibiotic resistance trends is essential to update guidelines and provide the most appropriate antibacterial therapy for children with UTIs.

3.
Harefuah ; 156(2): 68-70, 2017 Feb.
Artículo en Hebreo | MEDLINE | ID: mdl-28551890

RESUMEN

INTRODUCTION: Kaplan Medical Center (KMC) provides medical services to about 1 million Israeli citizens. The southern plain region is one of the leading areas in terms of population growth in Israel and as a result, the demand for medical services is constantly on the rise. The workload at KMC is tremendous; over 140,000 referrals to the emergency department with a 6% increase each year. Bed occupancy in the internal wards is above 120% on average per year (the highest in Israel) and ambulatory care referrals are rising at an overwhelming pace. Nonetheless, even under such a burden, this hospital deals with medical quality on a daily basis. Medical quality in KMC can be evaluated in many ways. The hospital is an academic institute, affiliated to the Hebrew University Medical School in Jerusalem, educates medical students, employs interns and residents in dozens of wards and is accredited on behalf of the JCI. One cannot talk about quality without conducting research. Clinical research is a foundation stone in the hospital. Research is performed by both residents and specialists with no time set aside for that matter (as opposed to the USA), based on the understanding that you cannot provide high standards of care without investigating, understanding, innovating, developing and providing advanced evidence-based treatments. In this current issue of "Harefuah" we present original and review articles written by KMC's physicians, which reflect a sample of the diverse research activity being conducted in the hospital.


Asunto(s)
Atención a la Salud , Hospitales Públicos/normas , Calidad de la Atención de Salud , Humanos , Israel , Médicos , Facultades de Medicina , Estudiantes de Medicina
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