2023
Trends in Upper Gastrointestinal Bleeding in Patients on Primary Prevention Aspirin: A Nationwide Emergency Department Sample Analysis, 2016-2020
Li D, Laine L, Shung D. Trends in Upper Gastrointestinal Bleeding in Patients on Primary Prevention Aspirin: A Nationwide Emergency Department Sample Analysis, 2016-2020. The American Journal Of Medicine 2023, 136: 1179-1186.e1. PMID: 37696350, PMCID: PMC10841721, DOI: 10.1016/j.amjmed.2023.08.010.Peer-Reviewed Original ResearchConceptsUpper gastrointestinal bleedingGastrointestinal bleedingRed blood cell transfusionNationwide Emergency Department SamplePrimary cardiovascular preventionRecent guideline recommendationsBlood cell transfusionProportion of hospitalizationsEmergency Department SampleMedicare reimbursementInternational Statistical ClassificationRelated Health ProblemsCardiovascular preventionCell transfusionOlder patientsHospital admissionCommon etiologyGuideline recommendationsMajor complicationsUlcer diseaseEndoscopic interventionRevision codesAppropriate indicationsRecent guidelinesCardiovascular disease
2021
Neural network predicts need for red blood cell transfusion for patients with acute gastrointestinal bleeding admitted to the intensive care unit
Shung D, Huang J, Castro E, Tay JK, Simonov M, Laine L, Batra R, Krishnaswamy S. Neural network predicts need for red blood cell transfusion for patients with acute gastrointestinal bleeding admitted to the intensive care unit. Scientific Reports 2021, 11: 8827. PMID: 33893364, PMCID: PMC8065139, DOI: 10.1038/s41598-021-88226-3.Peer-Reviewed Original ResearchConceptsAcute gastrointestinal bleedingRed blood cell transfusionBlood cell transfusionGastrointestinal bleedingHigh-risk patientsCell transfusionRed blood cellsPatient cohortIntensive Care III (MIMIC-III) critical care databaseIntensive care unit staySevere acute gastrointestinal bleedingPacked red blood cellsBlood cellsCommon gastrointestinal causesLaboratory test featuresTime-updated dataIntensive care unitValidation patient cohortCritical care databaseLarge urban hospitalMedical Information MartInternal validation setGastrointestinal causesUnit stayCare unit
2019
Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal Bleeding
Shung DL, Au B, Taylor RA, Tay JK, Laursen SB, Stanley AJ, Dalton HR, Ngu J, Schultz M, Laine L. Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal Bleeding. Gastroenterology 2019, 158: 160-167. PMID: 31562847, PMCID: PMC7004228, DOI: 10.1053/j.gastro.2019.09.009.Peer-Reviewed Original ResearchConceptsUpper gastrointestinal bleedingHospital-based interventionsComposite endpointScoring systemRockall scoreGastrointestinal bleedingClinical riskConsecutive unselected patientsLow-risk patientsClinical scoring systemRisk-scoring systemExternal validation cohortCharacteristic curve analysisInternal validation setOutpatient managementUnselected patientsValidation cohortEmergency departmentMedical CenterGreater AUCPatientsAbstractTextCurve analysisEndpointAUCMachine 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