2022
Investigation of hypertension and type 2 diabetes as risk factors for dementia in the All of Us cohort
Nagar S, Pemu P, Qian J, Boerwinkle E, Cicek M, Clark C, Cohn E, Gebo K, Loperena R, Mayo K, Mockrin S, Ohno-Machado L, Ramirez A, Schully S, Able A, Green A, Zuchner S, Jordan I, Meller R. Investigation of hypertension and type 2 diabetes as risk factors for dementia in the All of Us cohort. Scientific Reports 2022, 12: 19797. PMID: 36396674, PMCID: PMC9672061, DOI: 10.1038/s41598-022-23353-z.Peer-Reviewed Original ResearchConceptsAssociation of hypertensionPrevalence of dementiaType 2 diabetesRisk factorsUS populationRace/ethnicityHigh prevalenceLarge observational cohort studyMultivariable logistic regression modelRisk factor modificationObservational cohort studyT2D risk factorsInvestigation of hypertensionAssociation of T2DOdds of dementiaRace/ethnicity groupsAssociation of sexCross-sectional analysisLogistic regression modelsWorld Health OrganizationElectronic health recordsConcurrent hypertensionModifiable comorbiditiesCohort studyFinal cohort
2017
A Predictive Model for Extended Postanesthesia Care Unit Length of Stay in Outpatient Surgeries
Gabriel R, Waterman R, Kim J, Ohno-Machado L. A Predictive Model for Extended Postanesthesia Care Unit Length of Stay in Outpatient Surgeries. Anesthesia & Analgesia 2017, 124: 1529-1536. PMID: 28079580, DOI: 10.1213/ane.0000000000001827.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAge FactorsAgedAged, 80 and overAmbulatory Surgical ProceduresAnesthesiaChildChild, PreschoolCritical CareFemaleForecastingHumansHypertensionInfantInfant, NewbornIntensive Care UnitsLength of StayLogistic ModelsMaleMiddle AgedModels, StatisticalObesity, MorbidPostoperative CareRisk FactorsROC CurveYoung AdultConceptsPACU lengthPostanesthesia care unit lengthPrimary anesthesia typePostanesthesia care unitHosmer-Lemeshow testLogistic regression modelsAnesthesia typeMorbid obesityCare unitHL testOutpatient surgeryOutpatient procedureSingle institutionHigher oddsNonsignificant P valuesStayPatientsSurgical specialtiesROC curveGood calibrationCharacteristic curveExcellent discriminationAUC valuesP-valueBackward elimination
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 ResearchConceptsNeural 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
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
2000
Major complications after angioplasty in patients with chronic renal failure: a comparison of predictive models.
Lacson R, Ohno-Machado L. Major complications after angioplasty in patients with chronic renal failure: a comparison of predictive models. AMIA Annual Symposium Proceedings 2000, 457-61. PMID: 11079925, PMCID: PMC2243840.Peer-Reviewed Original ResearchConceptsPercutaneous transluminal coronary angioplastyEnd-stage renal diseaseChronic renal failureMajor complicationsRenal failureCongestive heart failurePatient risk factorsTransluminal coronary angioplastyLogistic regression modelsCoronary angioplastyHeart failureRenal diseasePoor outcomeMyocardial infarctionRisk factorsPrior historyPresence of shockComplicationsLogistic regressionPatientsDiscriminatory abilityDemographic characteristicsAngioplastyRegression modelsStandard logistic regression modelDevelopment and evaluation of models to predict death and myocardial infarction following coronary angioplasty and stenting.
Resnic F, Popma J, Ohno-Machado L. Development and evaluation of models to predict death and myocardial infarction following coronary angioplasty and stenting. AMIA Annual Symposium Proceedings 2000, 690-3. PMID: 11079972, PMCID: PMC2243827.Peer-Reviewed Original ResearchConceptsPercutaneous coronary interventionMyocardial infarctionPost-procedural myocardial infarctionMajor acute complicationsRisk-scoring systemRisk of deathMultivariate logistic regressionRisk score modelRisk-scoring modelLogistic regression modelsAcute complicationsCoronary angioplastyCoronary interventionClinical practiceInfarctionScoring systemInterventional cardiologyLogistic regressionRisk modelClinical implementationRisk deathDeathScore modelReasonable discriminationRegression modelsUsing electronic data to predict the probability of true bacteremia from positive blood cultures.
Wang S, Kuperman G, Ohno-Machado L, Onderdonk A, Sandige H, Bates D. Using electronic data to predict the probability of true bacteremia from positive blood cultures. AMIA Annual Symposium Proceedings 2000, 893-7. PMID: 11080013, PMCID: PMC2243892.Peer-Reviewed Original ResearchConceptsPositive blood culturesClinical prediction ruleBlood culturesTreatment decisionsTrue bacteremiaCulture resultsPositive blood culture resultsPrediction rulePaper chart reviewProbability of bacteremiaBlood culture resultsInfectious disease expertsAppropriate treatment decisionsLogistic regression modelsRevalidation studyChart reviewDisease expertsOne-year periodBacteremiaPhysiciansRegression modelsTrue positivesPatientsHospitalHousestaff