2024
External Validation of an Electronic Health Record-Based Diagnostic Model for Histological Acute Tubulointerstitial Nephritis.
Moledina D, Shelton K, Menez S, Aklilu A, Yamamoto Y, Kadhim B, Shaw M, Kent C, Makhijani A, Hu D, Simonov M, O'Connor K, Bitzel J, Thiessen-Philbrook H, Wilson F, Parikh C. External Validation of an Electronic Health Record-Based Diagnostic Model for Histological Acute Tubulointerstitial Nephritis. Journal Of The American Society Of Nephrology 2024 PMID: 39500309, DOI: 10.1681/asn.0000000556.Peer-Reviewed Original ResearchJohns Hopkins HospitalAcute tubulointerstitial nephritisValidation cohortKidney biopsyTubulointerstitial nephritisDiagnosis of acute tubulointerstitial nephritisProportion of biopsiesElectronic health recordsAnalyzed patientsDevelopment cohortBaseline prevalenceAccurate diagnosisBiopsyCohortHealth recordsClinician's abilityDiagnostic modelPotential predictorsNephritisAssess discriminationKidneyAUCHematuria Cancer Risk Score with Ultrasound Informs Cystoscopy Use in Patients with Hematuria
Tan W, Ahmad A, Zhou Y, Nathan A, Ogunbo A, Gbolahan O, Kallam N, Smith R, Khalifeh M, Tan W, Cohen D, Volanis D, Walter F, Sasieni P, Kamat A, Kelly J. Hematuria Cancer Risk Score with Ultrasound Informs Cystoscopy Use in Patients with Hematuria. European Urology Oncology 2024, 8: 87-93. PMID: 38811250, DOI: 10.1016/j.euo.2024.05.005.Peer-Reviewed Original ResearchCancer risk scoreRenal bladder ultrasoundTa bladder cancerUrinary tract cancerRisk scoreValidation cohortBladder cancerHealth care cost savingsBladder ultrasoundDiagnosis of urinary tract cancerInvasive proceduresDevelopment cohortIdentification of cancerSuspicion of bladder cancerSecondary careIndependent validation cohortReceiver operating characteristic curveUK hospitalsArea under the receiver operating characteristic curveOutcome measuresTriage of patientsConsecutive patientsPatient cohortCystoscopyHematuria
2023
Development and validation of a novel score to predict brain death after out-of-hospital cardiac arrest
Kitlen E, Kim N, Rubenstein A, Keenan C, Garcia G, Khosla A, Johnson J, Miller P, Wira C, Greer D, Gilmore E, Beekman R. Development and validation of a novel score to predict brain death after out-of-hospital cardiac arrest. Resuscitation 2023, 192: 109955. PMID: 37661012, DOI: 10.1016/j.resuscitation.2023.109955.Peer-Reviewed Original ResearchConceptsHospital cardiac arrestBrain deathCardiac arrestOptimal cutEtiology of arrestDeath risk scoreNon-shockable rhythmOperator characteristic curveHours of arrestCenter cohortIndependent predictorsSulcal effacementUnResponsiveness (FOUR) scoreValidation cohortDevelopment cohortMAIN OUTCOMEHigh riskRisk scoreAcademic centersNovel scoreOHCACohortInternal validationRadiology reportsCharacteristic curveA Multiclass Radiomics Method–Based WHO Severity Scale for Improving COVID-19 Patient Assessment and Disease Characterization From CT Scans
Henao J, Depotter A, Bower D, Bajercius H, Todorova P, Saint-James H, de Mortanges A, Barroso M, He J, Yang J, You C, Staib L, Gange C, Ledda R, Caminiti C, Silva M, Cortopassi I, Dela Cruz C, Hautz W, Bonel H, Sverzellati N, Duncan J, Reyes M, Poellinger A. A Multiclass Radiomics Method–Based WHO Severity Scale for Improving COVID-19 Patient Assessment and Disease Characterization From CT Scans. Investigative Radiology 2023, 58: 882-893. PMID: 37493348, PMCID: PMC10662611, DOI: 10.1097/rli.0000000000001005.Peer-Reviewed Original ResearchConceptsCOVID-19 positive patientsClinical Progression ScaleLung lesionsLesion modelDisease severityGround-glass opacitiesCOVID-19 patientsRadiologist assessmentExpert thoracic radiologistsMulticenter cohortPleural effusionDisease extentRetrospective studyDevelopment cohortPatient assessmentTomography scanCT scanSeverity ScalePatient's diseaseTissue lesionsThoracic radiologistsLesionsPatientsRadiomics modelRadiomic features
2022
Development and validation of a prediction model for persistent functional impairment among older ICU survivors
Ferrante LE, Murphy TE, Leo‐Summers L, O'Leary JR, Vander Wyk B, Pisani MA, Gill TM. Development and validation of a prediction model for persistent functional impairment among older ICU survivors. Journal Of The American Geriatrics Society 2022, 71: 188-197. PMID: 36196998, PMCID: PMC9870848, DOI: 10.1111/jgs.18075.Peer-Reviewed Original ResearchConceptsPersistent functional impairmentICU hospitalizationFunctional impairmentValidation cohortICU admissionDevelopment cohortOlder Intensive Care Unit SurvivorsIntensive care unit survivorsOlder adultsOlder ICU survivorsMonths of dischargeHigh-risk survivorsCommunity-living participantsGood calibrationHospital lengthICU survivorsCritical illnessMedian agePrior hospitalizationFunctional recoveryNational HealthProbable dementiaHospitalizationHigh riskDepressive symptomsActuarial Prediction Versus Clinical Prediction of Exits From a National Supported Housing Program
Byrne T, Tsai J. Actuarial Prediction Versus Clinical Prediction of Exits From a National Supported Housing Program. American Journal Of Orthopsychiatry 2022, 92: 217-223. PMID: 35025573, PMCID: PMC10687831, DOI: 10.1037/ort0000603.Peer-Reviewed Original ResearchConceptsClinical judgmentLogistic regressionClinical predictionService utilization historiesBehavioral health diagnosesMultivariable prediction modelPositive predictive valueHUD-VASHSupported housing programsDevelopment cohortValidation cohortPredictive valueSociodemographic characteristicsClinician ratingsHealth diagnosisCohortSupportive housing programCase managersPermanent supportive housingCharacteristic curveVeteransSupportive housingPresent studyPremature exitUtilization history
2021
Composite Metric for Benchmarking Site Performance in Transcatheter Aortic Valve Replacement
Desai ND, O’Brien S, Cohen DJ, Carroll J, Vemulapalli S, Arnold SV, Forrest JK, Thourani VH, Kirtane AJ, O’Neil B, Manandhar P, Shahian DM, Badhwar V, Bavaria JE. Composite Metric for Benchmarking Site Performance in Transcatheter Aortic Valve Replacement. Circulation 2021, 144: 186-194. PMID: 33947202, DOI: 10.1161/circulationaha.120.051456.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAortic Valve StenosisDisease ManagementFemaleHealth Care SurveysHumansMalePatient Reported Outcome MeasuresPostoperative ComplicationsPrognosisRegistriesReproducibility of ResultsSeverity of Illness IndexTranscatheter Aortic Valve ReplacementTreatment OutcomeUnited StatesConceptsTranscatheter aortic valve replacementAortic valve replacementValve replacementSerious complicationsCardiology Transcatheter Valve Therapy RegistryThoracic Surgeons/American CollegeTranscatheter Valve Therapy RegistryAcute kidney injuryRetrospective cohort studyRisk-adjusted mortalityRisk-adjusted outcomesQuality of careSingle outcome measureComposite risk modelPerivalvular regurgitationTAVR outcomesKidney injuryPeriprocedural complicationsPerivalvular leakCohort studyAortic stenosisDevelopment cohortOutcome measuresAmerican CollegeComplicationsPredicting In-Hospital Mortality in Patients Undergoing Percutaneous Coronary Intervention
Castro-Dominguez YS, Wang Y, Minges KE, McNamara RL, Spertus JA, Dehmer GJ, Messenger JC, Lavin K, Anderson C, Blankinship K, Mercado N, Clary JM, Osborne AD, Curtis JP, Cavender MA. Predicting In-Hospital Mortality in Patients Undergoing Percutaneous Coronary Intervention. Journal Of The American College Of Cardiology 2021, 78: 216-229. PMID: 33957239, DOI: 10.1016/j.jacc.2021.04.067.Peer-Reviewed Original ResearchConceptsPercutaneous coronary interventionHospital mortalityQuality improvement effortsCoronary interventionDevelopment cohortValidation cohortRisk-standardized mortality ratesHospital risk-standardized mortality ratesBedside risk scoreHigh-risk patientsIn-Hospital MortalityHospital mortality riskRisk of mortalityLevel of consciousnessProcedural urgencyCathPCI RegistryClinical presentationRisk cohortRisk stratificationCardiovascular instabilityCardiac arrestMortality riskRisk scoreClinical acuityClinical relevance
2020
Development and validation of a 30-day mortality index based on pre-existing medical administrative data from 13,323 COVID-19 patients: The Veterans Health Administration COVID-19 (VACO) Index
King JT, Yoon JS, Rentsch CT, Tate JP, Park LS, Kidwai-Khan F, Skanderson M, Hauser RG, Jacobson DA, Erdos J, Cho K, Ramoni R, Gagnon DR, Justice AC. Development and validation of a 30-day mortality index based on pre-existing medical administrative data from 13,323 COVID-19 patients: The Veterans Health Administration COVID-19 (VACO) Index. PLOS ONE 2020, 15: e0241825. PMID: 33175863, PMCID: PMC7657526, DOI: 10.1371/journal.pone.0241825.Peer-Reviewed Original ResearchConceptsCharlson Comorbidity IndexVeterans Health AdministrationVACO IndexValidation cohortMedical administrative dataDevelopment cohortSARS-CoV-2 testing resultsMortality indexICD-10 diagnosis codesUS Veterans Health AdministrationSARS-CoV-2 infectionPre-existing medical conditionsCOVID-19 mortality riskPeripheral vascular diseaseCOVID-19 patientsCOVID-19 infectionCOVID-19 mortalitySARS-CoV-2Administrative dataLogistic regression modelsRace/ethnicityCohort subgroupsComorbidity indexOverall mortalityComorbid conditionsABC score: a new risk score that accurately predicts mortality in acute upper and lower gastrointestinal bleeding: an international multicentre study
Laursen SB, Oakland K, Laine L, Bieber V, Marmo R, Redondo-Cerezo E, Dalton HR, Ngu J, Schultz M, Soncini M, Gralnek I, Jairath V, Murray IA, Stanley AJ. ABC score: a new risk score that accurately predicts mortality in acute upper and lower gastrointestinal bleeding: an international multicentre study. Gut 2020, 70: 707-716. PMID: 32723845, DOI: 10.1136/gutjnl-2019-320002.Peer-Reviewed Original ResearchConceptsLower gastrointestinal bleedingABC scoreLower riskHigher ABC scoresGastrointestinal bleedingRisk scoreMortality rateHospital mortality rateInternational cohort studyManagement of patientsNew risk scoreInternational multicentre studyLower ABC scoreLGIB patientsUGIB patientsComorbidity scoreCohort studyMulticentre studyBlood testsValidation cohortDevelopment cohortLGIBUGIBHigh riskPatients
2019
Development and Validation of a Risk Prediction Model for Cesarean Delivery After Labor Induction
Danilack VA, Hutcheon JA, Triche EW, Dore DD, Muri JH, Phipps MG, Savitz DA. Development and Validation of a Risk Prediction Model for Cesarean Delivery After Labor Induction. Journal Of Women's Health 2019, 29: 656-669. PMID: 31657668, PMCID: PMC8935479, DOI: 10.1089/jwh.2019.7822.Peer-Reviewed Original ResearchConceptsLabor inductionCesarean deliveryHistory of herpesTerm labor inductionInternal validationExcessive fetal growthBetter risk stratificationExternal validation cohortVariables gestational ageRisk prediction modelStart of inductionRisk stratificationTime of inductionDevelopment cohortValidation cohortMaternal ageFetal growthMaternal raceMedical indicationsWoman's riskU.S. hospitalsCharacteristic curveHospitalCohortInductionMAP(ASH): A new scoring system for the prediction of intervention and mortality in upper gastrointestinal bleeding
Redondo‐Cerezo E, Vadillo‐Calles F, Stanley AJ, Laursen S, Laine L, Dalton HR, Ngu JH, Schultz M, Jiménez‐Rosales R. MAP(ASH): A new scoring system for the prediction of intervention and mortality in upper gastrointestinal bleeding. Journal Of Gastroenterology And Hepatology 2019, 35: 82-89. PMID: 31359521, DOI: 10.1111/jgh.14811.Peer-Reviewed Original ResearchConceptsUpper gastrointestinal bleedingGastrointestinal bleedingEndoscopic interventionGlasgow-Blatchford scoreSystolic blood pressureNew scoring systemBlatchford scoreProspective databaseBlood pressureRisk stratificationValidation cohortDevelopment cohortOriginal cohortEmergency roomMental statusRisk scoreClinical practiceFair discriminationScoring systemPatientsMortalityCohortNew scoreInterventionBleedingDevelopment and validation of a haematuria cancer risk score to identify patients at risk of harbouring cancer
Tan W, Ahmad A, Feber A, Mostafid H, Cresswell J, Fankhauser C, Waisbrod S, Hermanns T, Sasieni P, Kelly J, Khetrapal P, Baker H, Sridhar A, Lamb B, Ocampo F, McBain H, Baillie K, Middleton K, Watson D, Knight H, Maher S, Rane A, Pathmanathan B, Harmathova A, Hellawell G, Pelluri S, Pati J, Cossons A, Scott C, Madaan S, Bradfield S, Wakeford N, Dann A, Cook J, Cornwell M, Mills R, Thomas S, Reyner S, Vallejera G, Adeniran P, Masood S, Whotton N, Dent K, Pearson S, Hatton J, Newton M, Heeney E, Green K, Evans S, Rogers M, Gupwell K, Whiteley S, Brown A, McGrath J, Lunt N, Hill P, Sinclair A, Paredes‐Guerra A, Holbrook B, Ong E, Wardle H, Wilson D, Bayles A, Fennelly R, Tribbeck M, Ames K, Davies M, Taylor J, Edmunds E, Moore J, Mckinley S, Nolan T, Speed A, Tunnicliff A, Fossey G, Williams A, George M, Hutchins I, Einosas R, Richards A, Henderson A, Appleby B, Kehoe L, Gladwell L, Drakeley S, Davies J, Krishnan R, Roberts H, Main C, Jain S, Dumville J, Wilkinson N, Taylor J, Thomas F, Goulden K, Vinod C, Green E, Waymont C, Rogers J, Grant A, Carter V, Heap H, Lomas C, Cooke P, Scarratt L, Hodgkiss T, Johnstone D, Johnson J, Allsop J, Rothwell J, Connolly K, Cherian J, Ridgway S, Coulding M, Savill H, Mccormick J, Clark M, Collins G, Jewers K, Keith S, Bowen G, Hargreaves J, Riley K, Srirangam S, Rees A, Williams S, Dukes S, Goffe A, Dawson L, Mistry R, Chadwick J, Cocks S, Hull R, Loftus A, Baird Y, Moore S, Greenslade S, Margalef J, Chadbourn I, Harris M, Hicks J, Clitheroe P, Connolly S, Hodgkinson S, Haydock H, Sinclair A, Storr E, Cogley L, Natale S, Lovegrove W, Slack K, Nash D, Smith K, Walsh J, Guerdette A, Hill M, Payne D, Taylor B, Sinclair E, Perry M, Debbarma M, Hewitt D, Sriram R, Power A, Cannon J, Devereaux L, Thompson A, Atkinson K, Royle L, Madine J, MacLean K, Sarpong R, Brew‐Graves C, Williams N. Development and validation of a haematuria cancer risk score to identify patients at risk of harbouring cancer. Journal Of Internal Medicine 2019, 285: 436-445. PMID: 30521125, PMCID: PMC6446724, DOI: 10.1111/joim.12868.Peer-Reviewed Original ResearchConceptsCancer risk scoreNational Institute for Health and Clinical Excellence guidelinesRisk scoreInvestigation of haematuriaPhysician decision-makingAge-specific thresholdsValidation cohortExcellence guidelinesUK hospitalsAmerican Urological Association guidelinesNational guidelinesImprove patientNo significant overfittingImprove patient selectionUpper tract cancerLack of consensusAssociation guidelinesSmoking historySwiss patientsCohortPatient ageDevelopment cohortPatient selectionGuidelinesHaematuria
2018
Accuracy of electronic health record data for the diagnosis of chronic obstructive pulmonary disease in persons living with HIV and uninfected persons
Crothers K, Rodriguez CV, Nance RM, Akgun K, Shahrir S, Kim J, Hoo G, Sharafkhaneh A, Crane HM, Justice AC. Accuracy of electronic health record data for the diagnosis of chronic obstructive pulmonary disease in persons living with HIV and uninfected persons. Pharmacoepidemiology And Drug Safety 2018, 28: 140-147. PMID: 29923258, PMCID: PMC6309326, DOI: 10.1002/pds.4567.Peer-Reviewed Original ResearchMeSH KeywordsAdministration, InhalationAge FactorsAlgorithmsBronchodilator AgentsCohort StudiesData AccuracyData Interpretation, StatisticalDrug PrescriptionsElectronic Health RecordsFemaleHIV InfectionsHumansInternational Classification of DiseasesLogistic ModelsMaleMiddle AgedNebulizers and VaporizersPrevalencePulmonary Disease, Chronic ObstructiveRisk FactorsSmokingSpirometryConceptsChronic obstructive pulmonary diseaseICD-9 codesObstructive pulmonary diseaseElectronic health record dataHealth record dataPulmonary diseaseHIV-Associated Lung Emphysema (EXHALE) studyIntegrated Clinical Systems cohortVeterans Aging Cohort StudyHIV uninfected personsAIDS Research NetworkAging Cohort StudyRecord dataEHR dataReceiver-operating curveCohort studyRespiratory symptomsHIV statusUninfected personsClinical variablesDevelopment cohortClinical indicationsSpirometry dataSpirometryUninfected individuals
2014
Predicting Hematoma Expansion After Primary Intracerebral Hemorrhage
Brouwers HB, Chang Y, Falcone GJ, Cai X, Ayres AM, Battey TW, Vashkevich A, McNamara KA, Valant V, Schwab K, Orzell SC, Bresette LM, Feske SK, Rost NS, Romero JM, Viswanathan A, Chou S, Greenberg SM, Rosand J, Goldstein JN. Predicting Hematoma Expansion After Primary Intracerebral Hemorrhage. JAMA Neurology 2014, 71: 158-164. PMID: 24366060, PMCID: PMC4131760, DOI: 10.1001/jamaneurol.2013.5433.Peer-Reviewed Original ResearchConceptsPrimary intracerebral hemorrhageIndependent validation cohortIntracerebral hemorrhageHematoma expansionValidation cohortHigh riskPrediction scoreUrban academic medical centerBaseline ICH volumeWarfarin sodium useProspective cohort studyAcute intracerebral hemorrhageMultivariable logistic regressionTomography angiography spot signComputed tomography angiography spot signAcademic medical centerPredictors of expansionCohort studyMultivariable analysisDevelopment cohortICH volumeC-statisticClinical trialsIndividualized treatmentMAIN OUTCOME
2003
Burden of Illness Score for Elderly Persons
Inouye SK, Bogardus ST, Vitagliano G, Desai MM, Williams CS, Grady JN, Scinto JD. Burden of Illness Score for Elderly Persons. Medical Care 2003, 41: 70-83. PMID: 12544545, DOI: 10.1097/00005650-200301000-00010.Peer-Reviewed Original ResearchMeSH KeywordsAge FactorsAgedAged, 80 and overCohort StudiesComorbidityCost of IllnessFemaleFollow-Up StudiesForecastingGeriatric AssessmentHealth StatusHospitalizationHospitals, TeachingHumansMaleMortalityPneumoniaProbabilityProportional Hazards ModelsRisk AdjustmentRisk FactorsSeverity of Illness IndexSex FactorsSurvival AnalysisTime FactorsConceptsGroup IHazard ratioIllness scoresOverall mortalityC-statisticElderly personsHospitalized older personsHigh-risk diagnosesRisk adjustment indexProspective cohortValidation cohortDevelopment cohortUniversity HospitalPhysiologic abnormalitiesRisk factorsFunctional impairmentRisk groupsMedicine serviceMortality predictionMortality rateGroup IICohortOlder personsFinal modelGroup III
2002
Development and Validation of a Risk‐Adjustment Index for Older Patients: The High‐Risk Diagnoses for the Elderly Scale
Desai MM, Bogardus ST, Williams CS, Vitagliano G, Inouye SK. Development and Validation of a Risk‐Adjustment Index for Older Patients: The High‐Risk Diagnoses for the Elderly Scale. Journal Of The American Geriatrics Society 2002, 50: 474-481. PMID: 11943043, DOI: 10.1046/j.1532-5415.2002.50113.x.Peer-Reviewed Original ResearchConceptsRisk adjustment indexDevelopment cohortElderly ScaleRisk diagnosisProspective cohort studyGeneral medical patientsGeneral medicine serviceUniversity Teaching HospitalCox proportional hazardsCharacteristic curve analysisComparable patientsCohort studyOlder patientsStrength of associationDischarge diagnosisMedical patientsValidation cohortRisk groupsTeaching hospitalInitial cohortMortality riskSeparate cohortMedicine serviceMortality ratePatients
1999
The Combined Effects of Baseline Vulnerability and Acute Hospital Events on the Development of Functional Dependence Among Community-Living Older Persons
Gill T, Williams C, Tinetti M. The Combined Effects of Baseline Vulnerability and Acute Hospital Events on the Development of Functional Dependence Among Community-Living Older Persons. The Journals Of Gerontology Series A 1999, 54: m377-m383. PMID: 10462171, DOI: 10.1093/gerona/54.7.m377.Peer-Reviewed Original ResearchConceptsCommunity-living older personsValidation cohortDevelopment cohortOlder personsBaseline vulnerabilityHospital eventsPopulation-based cohort studyAcute care hospital admissionsCommunity-living personsHigh-risk groupSkilled nursing facilitiesYears of ageCohort studyHospital admissionPrimary outcomeComparable personsNew disabilityDaily livingNursing facilitiesCohortCognitive statusHigh-vulnerability groupPrecipitating eventsPhysical performanceAdmission
1997
A Predictive Model for ADL Dependence in Community‐Living Older Adults Based on a Reduced Set of Cognitive Status Items
Gill T, Williams C, Richardson E, Berkman L, Tinetti M. A Predictive Model for ADL Dependence in Community‐Living Older Adults Based on a Reduced Set of Cognitive Status Items. Journal Of The American Geriatrics Society 1997, 45: 441-445. PMID: 9100712, DOI: 10.1111/j.1532-5415.1997.tb05168.x.Peer-Reviewed Original ResearchConceptsADL dependenceDevelopment cohortValidation cohortPresence of impairmentsPopulation-based cohort studyMini-Mental State Examination (MMSE) itemCommunity-living older adultsCommunity-living personsSelf-reported ADLOlder person's riskYears of ageCohort studyResearch nursesMultivariable analysisRisk groupsBaseline interviewInitial cohortStratified subjectsSeparate cohortCohortPerson's riskGeneral communityOlder adultsCognitive AssessmentComparable subjects
1993
A predictive index for functional decline in hospitalized elderly medical patients
Inouye S, Wagner D, Acampora D, Horwitz R, Cooney L, Hurst L, Tinetti M. A predictive index for functional decline in hospitalized elderly medical patients. Journal Of General Internal Medicine 1993, 8: 645-652. PMID: 8120679, DOI: 10.1007/bf02598279.Peer-Reviewed Original ResearchMeSH KeywordsActivities of Daily LivingAgedAged, 80 and overChi-Square DistributionCohort StudiesConnecticutFemaleGeriatric AssessmentHospital Bed Capacity, 500 and overHospitals, UniversityHumansLikelihood FunctionsMaleMultivariate AnalysisPrevalenceProportional Hazards ModelsProspective StudiesReproducibility of ResultsRisk FactorsSingle-Blind MethodConceptsFunctional declineRisk factorsMedical patientsValidation cohortDevelopment cohortHospitalized elderly medical patientsIndependent baseline risk factorsLow social activity levelNumber of RFsPredictive indexBaseline risk factorsGeneral medical wardsProspective cohort studyGeneral medical patientsHigh-risk groupUniversity Teaching HospitalElderly medical patientsRisk stratification systemNursing home placementRate of deathSocial activity levelsComparable patientsCohort studyElderly patientsMedical wards
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply