2017
A Novel Risk Score to Predict the Need for Nutrition Support After Cardiac Surgery
Ohkuma R, Crawford T, Brown P, Grimm J, Magruder J, Kilic A, Suarez-Pierre A, Snyder S, Wood J, Schneider E, Sussman M, Whitman G. A Novel Risk Score to Predict the Need for Nutrition Support After Cardiac Surgery. The Annals Of Thoracic Surgery 2017, 104: 1306-1312. PMID: 28625392, DOI: 10.1016/j.athoracsur.2017.03.013.Peer-Reviewed Original ResearchConceptsPostoperative nutrition supportNutrition supportCardiac surgeryNS scoresAdult cardiac surgery patientsMultivariable logistic regression modelingEarly postoperative nutritionMalnutrition-related morbidityCardiac surgery patientsNovel risk scoreRelative odds ratioLogistic regression modelingTiming of initiationPostoperative nutritionSurgery patientsDerivation cohortIndependent predictorsPredictive screening toolMultivariable analysisValidation cohortC-statisticOdds ratioHigh riskRisk scorePatients
2013
Reliability adjustment
Hashmi Z, Dimick J, Efron D, Haut E, Schneider E, Zafar S, Schwartz D, Cornwell E, Haider A. Reliability adjustment. Journal Of Trauma And Acute Care Surgery 2013, 75: 166-172. PMID: 23940864, PMCID: PMC3989535, DOI: 10.1097/ta.0b013e318298494f.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedBenchmarkingCause of DeathDatabases, FactualFemaleHospital MortalityHumansInjury Severity ScoreMaleMiddle AgedOutcome Assessment, Health CareQuality ImprovementReproducibility of ResultsRisk AdjustmentSurvival AnalysisTrauma CentersUnited StatesWounds and InjuriesWounds, NonpenetratingWounds, PenetratingYoung AdultConceptsRisk-adjusted mortality ratesInjury Severity ScoreLow-volume centersMortality rateNational Trauma Data Bank 2010National Trauma Data BankReliability adjustmentHierarchical logistic regression modelingPatients 16 yearsRisk-adjusted mortalityTrauma Data BankNumber of patientsLogistic regression modelingHospital performance assessmentRisk adjustment methodsTrauma centerSeverity scoreVolume centersMortality ratioWorst quintileInterfacility variation