2020
Active Surveillance of the Implantable Cardioverter-Defibrillator Registry for Defibrillator Lead Failures
Resnic F, Majithia A, Dhruva S, Ssemaganda H, Robbins S, Marinac-Dabic D, Hewitt K, Ohno-Machado L, Reynolds M, Matheny M. Active Surveillance of the Implantable Cardioverter-Defibrillator Registry for Defibrillator Lead Failures. Circulation Cardiovascular Quality And Outcomes 2020, 13: e006105. PMID: 32283971, PMCID: PMC7360169, DOI: 10.1161/circoutcomes.119.006105.Peer-Reviewed Original ResearchConceptsICD RegistryLead failureActive surveillanceNational Cardiovascular Data Registry ICD RegistryImplantable Cardioverter-Defibrillator RegistryPrimary safety end pointPropensity-matched survival analysisRate of freedomSafety end pointLead failure rateLong-term safetySignificant patient harmDefibrillator lead failureEarly lead failureMonitoring of safetyComparator patientsContemporary ICDLead survivalMeaningful differencesOutcome ascertainmentFailure rateNew ICDPatient harmPatientsSurvival analysis
2017
A risk prediction score for acute kidney injury in the intensive care unit
Malhotra R, Kashani K, Macedo E, Kim J, Bouchard J, Wynn S, Li G, Ohno-Machado L, Mehta R. A risk prediction score for acute kidney injury in the intensive care unit. Nephrology Dialysis Transplantation 2017, 32: 814-822. PMID: 28402551, DOI: 10.1093/ndt/gfx026.Peer-Reviewed Original ResearchConceptsAcute kidney injuryIntensive care unitAcute risk factorsRisk score modelICU admissionKidney injuryCare unitValidation cohortKidney diseaseRisk factorsTest cohortTreatment of AKIAtherosclerotic coronary vascular diseaseMulticenter prospective cohort studyGlobal Outcomes criteriaChronic kidney diseaseHigh-risk patientsProspective cohort studyChronic liver diseaseCongestive heart failureTime of screeningCoronary vascular diseaseRisk prediction scoreEarly therapeutic interventionExternal validation cohort
2012
An improved model for predicting postoperative nausea and vomiting in ambulatory surgery patients using physician-modifiable risk factors
Sarin P, Urman R, Ohno-Machado L. An improved model for predicting postoperative nausea and vomiting in ambulatory surgery patients using physician-modifiable risk factors. Journal Of The American Medical Informatics Association 2012, 19: 995-1002. PMID: 22582204, PMCID: PMC3534465, DOI: 10.1136/amiajnl-2012-000872.Peer-Reviewed Original ResearchConceptsAmbulatory surgery dataExperimental modelNon-modifiable patient characteristicsApfel risk scoreAmbulatory surgery patientsGood calibrationLogistic regression modelsAmbulatory surgery casesPONV prophylaxisPostoperative nauseaFrequent complicationPatient characteristicsSurgery patientsAnesthetic techniqueAmbulatory surgeryPatient riskRisk factorsSurgery casesAnaesthetic practiceRisk scoreAcademic centersSurgery dataPractice improvementNauseaVomiting
2004
Prediction of mortality in an Indian intensive care unit
Nimgaonkar A, Karnad D, Sudarshan S, Ohno-Machado L, Kohane I. Prediction of mortality in an Indian intensive care unit. Intensive Care Medicine 2004, 30: 248-253. PMID: 14727015, DOI: 10.1007/s00134-003-2105-4.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAPACHEFemaleHospital MortalityHumansIndiaIntensive Care UnitsLogistic ModelsMaleMiddle AgedProbabilityProspective StudiesConceptsNeural networkIndian data setAPACHE IIArtificial neural network modelBack-propagation algorithmNeural network modelAnalysis of informationDay 1 APACHE II scoreIndian Intensive Care UnitsNetwork modelAPACHE II equationAPACHE II systemAPACHE II scoreIntensive care unitRisk of deathPrediction of mortalityNetworkHosmer-Lemeshow statisticData setsLogistic regression modelsHospital outcomesII scoreCare unitUniversity HospitalConsecutive admissions
2003
No-reflow is an independent predictor of death and myocardial infarction after percutaneous coronary intervention
Resnic F, Wainstein M, Lee M, Behrendt D, Wainstein R, Ohno-Machado L, Kirshenbaum J, Rogers C, Popma J, Piana R. No-reflow is an independent predictor of death and myocardial infarction after percutaneous coronary intervention. American Heart Journal 2003, 145: 42-46. PMID: 12514653, DOI: 10.1067/mhj.2003.36.Peer-Reviewed Original ResearchConceptsPercutaneous coronary interventionPostprocedural myocardial infarctionStrong independent predictorMyocardial infarctionIndependent predictorsSodium nitroprussideInhospital outcomesCoronary interventionClinical outcomesSaphenous vein graft interventionIntracoronary vasodilator therapyVein graft interventionAdministration of verapamilAcute myocardial infarctionRate of deathInhospital mortalityVasodilator therapyCardiogenic shockBaseline demographicsGraft interventionUnstable anginaAdverse eventsConsecutive patientsIntracoronary verapamilInfarction
2001
Simplified risk score models accurately predict the risk of major in-hospital complications following percutaneous coronary intervention
Resnic F, Ohno-Machado L, Selwyn A, Simon D, Popma J. Simplified risk score models accurately predict the risk of major in-hospital complications following percutaneous coronary intervention. The American Journal Of Cardiology 2001, 88: 5-9. PMID: 11423050, DOI: 10.1016/s0002-9149(01)01576-4.Peer-Reviewed Original ResearchMeSH KeywordsAngioplasty, Balloon, CoronaryCardiopulmonary BypassCoronary DiseaseFemaleHospital MortalityHumansLogistic ModelsMaleMiddle AgedMyocardial InfarctionNeural Networks, ComputerPostoperative ComplicationsPredictive Value of TestsPrognosisProspective StudiesRisk AssessmentRisk FactorsROC CurveConceptsPercutaneous coronary interventionRisk score modelHospital complicationsCoronary interventionScore modelGlycoprotein IIb/IIIa antagonistsIIb/IIIa antagonistsMultiple logistic regression modelBedside risk stratificationCombined end pointUse of stentsMultiple logistic modelLogistic regression modelsBypass surgeryRisk stratificationSingle centerDecreased riskMyocardial infarctionRisk factorsComplicationsInterventional proceduresEnd pointLogistic regressionLogistic modelROC curve