2023
Machine learning to predict bacteriologic confirmation of Mycobacterium tuberculosis in infants and very young children
Smith J, Milligan K, McCarthy K, Mchembere W, Okeyo E, Musau S, Okumu A, Song R, Click E, Cain K. Machine learning to predict bacteriologic confirmation of Mycobacterium tuberculosis in infants and very young children. PLOS Digital Health 2023, 2: e0000249. PMID: 37195976, PMCID: PMC10191346, DOI: 10.1371/journal.pdig.0000249.Peer-Reviewed Original ResearchMicrobial confirmationTB diseaseYoung childrenNoninvasive procedureLarge prospective cohortCases of tuberculosisChest X-rayDiagnosis of tuberculosisClinical decision makingBacteriologic confirmationHousehold contactsTB infectionProspective cohortRadiologic factorsPaucibacillary natureClinical similaritiesDiagnostic cohortClinical diseaseChildhood diseasesInvasive proceduresNovel biomarkersTuberculosisClinical researchM. tuberculosisDisease
2022
Clinical and Radiologic Factors Associated With Detection of Mycobacterium tuberculosis in Children Under 5 Years old Using Invasive and Noninvasive Sample Collection Techniques—Kenya
Smith J, Song R, McCarthy K, Mchembere W, Click E, Cain K. Clinical and Radiologic Factors Associated With Detection of Mycobacterium tuberculosis in Children Under 5 Years old Using Invasive and Noninvasive Sample Collection Techniques—Kenya. Open Forum Infectious Diseases 2022, 9: ofac560. PMID: 36386048, PMCID: PMC9664973, DOI: 10.1093/ofid/ofac560.Peer-Reviewed Original ResearchSpecimen collection techniquesRadiologic factorsYoung childrenProspective cohort studyFine-needle aspirationHistory of exposurePublic health concernCritical public health concernBacteriologic confirmationAirway compressionCervical lymphadenopathyRadiological factorsCohort studyPediatric tuberculosisTB casesPresumptive tuberculosisClinical managementImmunologic evidenceNeedle aspirationPositive specimenDiagnostic testingTuberculosisLogistic regressionHealth concernMycobacterium tuberculosis