Mycobacterium avium is the most common pathogen in children presenting as non-tuberculous mycobacterial lymphadenitis. In Sweden non-tuberculous mycobacterial infection is a notifiable disease. The goal of our study was to determine the annual incidence of M. avium infection in Swedish children, 1998-2003, and describe clinical features related to age and treatment of children with M. avium lymphadenitis. To do this, we retrospectively analysed patient records of 162 children less than 7 y of age from the entire country with culture-verified M. avium disease. The incidence of M. avium infection in Sweden was lower in 2000-2003 than in 1998-1999. Young children (

Download full-text PDF

Source
http://dx.doi.org/10.1080/00365540701840088DOI Listing

Publication Analysis

Top Keywords

clinical features
8
mycobacterium avium
8
non-tuberculous mycobacterial
8
incidence avium
8
avium infection
8
avium
6
children
6
features incidence
4
incidence mycobacterium
4
avium infections
4

Similar Publications

Background: The anti-melanoma differentiation-associated gene 5 (anti-MDA5) antibody-positive dermatomyositis is known for its association with rapidly progressive interstitial lung disease (RP-ILD) and ulcerative skin lesions, often presenting with or without muscle involvement. The aim of this study was to identify distinct clinical and laboratory features that could be used to evaluate disease progression in an ethnically diverse cohort of anti-MDA5 dermatomyositis patients at a U.S.

View Article and Find Full Text PDF

Background: Urinary tract infection (UTI) is a frequent health-threatening condition. Early reliable diagnosis of UTI helps to prevent misuse or overuse of antibiotics and hence prevent antibiotic resistance. The gold standard for UTI diagnosis is urine culture which is a time-consuming and also an error prone method.

View Article and Find Full Text PDF

A machine learning model accurately identifies glycogen storage disease Ia patients based on plasma acylcarnitine profiles.

Orphanet J Rare Dis

January 2025

Laboratory of Metabolic Diseases, Department of Laboratory Medicine, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Postbus, Groningen, 30001 - 9700 RB, the Netherlands.

Background: Glycogen storage disease (GSD) Ia is an ultra-rare inherited disorder of carbohydrate metabolism. Patients often present in the first months of life with fasting hypoketotic hypoglycemia and hepatomegaly. The diagnosis of GSD Ia relies on a combination of different biomarkers, mostly routine clinical chemical markers and subsequent genetic confirmation.

View Article and Find Full Text PDF

Background: Patients supported by extracorporeal membrane oxygenation (ECMO) are at a high risk of brain injury, contributing to significant morbidity and mortality. This study aimed to employ machine learning (ML) techniques to predict brain injury in pediatric patients ECMO and identify key variables for future research.

Methods: Data from pediatric patients undergoing ECMO were collected from the Chinese Society of Extracorporeal Life Support (CSECLS) registry database and local hospitals.

View Article and Find Full Text PDF

Objectives: To construct a prediction model based on deep learning (DL) and radiomics features of diffusion weighted imaging (DWI), and clinical variables for evaluating TP53 mutations in endometrial cancer (EC).

Methods: DWI and clinical data from 155 EC patients were included in this study, consisting of 80 in the training set, 35 in the test set, and 40 in the external validation set. Radiomics features, convolutional neural network-based DL features, and clinical variables were analyzed.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!