2019
Machine Learning to Predict Outcomes in Patients with Acute Gastrointestinal Bleeding: A Systematic Review
Shung D, Simonov M, Gentry M, Au B, Laine L. Machine Learning to Predict Outcomes in Patients with Acute Gastrointestinal Bleeding: A Systematic Review. Digestive Diseases And Sciences 2019, 64: 2078-2087. PMID: 31055722, DOI: 10.1007/s10620-019-05645-z.Peer-Reviewed Original ResearchConceptsClinical risk scoreUpper gastrointestinal bleedingGastrointestinal bleedingOutcomes of mortalityRisk scoreSystematic reviewOvert gastrointestinal bleedingAcute gastrointestinal bleedingPrognosis Studies toolRisk of biasFull-text studiesCurrent risk assessment toolsRisk assessment toolHospital stayHemostatic interventionRisk stratificationInclusion criteriaPrognostic performanceHigh riskIndependent reviewersConference abstractsLower riskMedian AUCPatientsMortality
2015
Factors impacting physicians’ decisions to prevent variceal hemorrhage
Yan K, Bridges J, Augustin S, Laine L, Garcia-Tsao G, Fraenkel L. Factors impacting physicians’ decisions to prevent variceal hemorrhage. BMC Gastroenterology 2015, 15: 55. PMID: 25934271, PMCID: PMC4423490, DOI: 10.1186/s12876-015-0287-1.Peer-Reviewed Original ResearchConceptsEndoscopic variceal ligationEradication of varicesLiver diseaseFirst variceal bleedMore daysSpecific treatment attributesLatent class analysisMechanism of actionVariceal bleedVariceal hemorrhageLarge varicesVariceal ligationPhysician characteristicsTreatment preferencesTreatment characteristicsTreatment attributesGroup 2Side effectsPrevention strategiesClass analysisVaricesPatientsPhysiciansDistinct subgroupsStandardized patients