2024
A Multicenter Evaluation of the Impact of Therapies on Deep Learning-based Electrocardiographic Hypertrophic Cardiomyopathy Markers
Dhingra L, Sangha V, Aminorroaya A, Bryde R, Gaballa A, Ali A, Mehra N, Krumholz H, Sen S, Kramer C, Martinez M, Desai M, Oikonomou E, Khera R. A Multicenter Evaluation of the Impact of Therapies on Deep Learning-based Electrocardiographic Hypertrophic Cardiomyopathy Markers. The American Journal Of Cardiology 2024 PMID: 39581517, DOI: 10.1016/j.amjcard.2024.11.028.Peer-Reviewed Original ResearchCleveland Clinic FoundationHypertrophic cardiomyopathyMedian follow-up periodHypertrophic cardiomyopathy therapyMonitoring treatment responseFollow-up periodImpact of therapyAtlantic Health SystemLack of improvementOral alternativePost-SRTMedical therapyTreatment responseMulticenter evaluationInterventricular septumPercutaneous reductionMavacamtenTherapyPatientsClinic FoundationPoint-of-care monitoringECGECG imagesScoresHealth systemValidating International Classification of Diseases Code (ICD) 10th Revision Algorithms for Accurate Identification of Pulmonary Embolism
Bikdeli B, Khairani C, Bejjani A, Lo Y, Mahajan S, Caraballo C, Jimenez J, Krishnathasan D, Zarghami M, Rashedi S, Jimenez D, Barco S, Secemsky E, Klok F, Hunsaker A, Aghayev A, Muriel A, Hussain M, Appah-Sampong A, Lu Y, Lin Z, Mojibian H, Aneja S, Khera R, Konstantinides S, Goldhaber S, Wang L, Zhou L, Monreal M, Piazza G, Krumholz H, Investigators P. Validating International Classification of Diseases Code (ICD) 10th Revision Algorithms for Accurate Identification of Pulmonary Embolism. Journal Of Thrombosis And Haemostasis 2024 PMID: 39505153, DOI: 10.1016/j.jtha.2024.10.013.Peer-Reviewed Original ResearchDischarge codesInternational ClassificationICD-10Yale New Haven Health SystemPositive predictive valueMass General Brigham hospitalsAccuracy of ICD-10ICD-10 codesPulmonary embolismHealth systemImage codingElectronic databasesF1 scorePre-specified protocolExcellent positive predictive valueIndependent physiciansHighest F1 scoreIdentification of pulmonary embolismAcute pulmonary embolismSecondary codePE codesScoresIdentified PERevised algorithm
2020
Quality of informed consent documents among US. hospitals: a cross-sectional study
Spatz ES, Bao H, Herrin J, Desai V, Ramanan S, Lines L, Dendy R, Bernheim SM, Krumholz HM, Lin Z, Suter LG. Quality of informed consent documents among US. hospitals: a cross-sectional study. BMJ Open 2020, 10: e033299. PMID: 32434934, PMCID: PMC7247389, DOI: 10.1136/bmjopen-2019-033299.Peer-Reviewed Original ResearchConceptsInformed consent documentsHOSPITAL scoreUS hospitalsMean hospital scoresRetrospective observational studyConsent documentsCross-sectional studyEight-item instrumentService patientsElective proceduresProcedure typeObservational studySurgical proceduresMedicare feeHospitalHospital qualityMeasure scoresInformed consentMost hospitalsSpearman correlationScoresFace validityIndependent ratersOutcomesStakeholder feedback
2018
Accurate estimation of cardiovascular risk in a non-diabetic adult: detecting and correcting the error in the reported Framingham Risk Score for the Systolic Blood Pressure Intervention Trial population
Warner F, Dhruva SS, Ross JS, Dey P, Murugiah K, Krumholz HM. Accurate estimation of cardiovascular risk in a non-diabetic adult: detecting and correcting the error in the reported Framingham Risk Score for the Systolic Blood Pressure Intervention Trial population. BMJ Open 2018, 8: e021685. PMID: 30037874, PMCID: PMC6059296, DOI: 10.1136/bmjopen-2018-021685.Peer-Reviewed Original ResearchConceptsSystolic Blood Pressure Intervention TrialFramingham risk scoreCardiovascular riskRisk scoreStudy populationStudy participantsNon-diabetic adultsTotal study populationHigh-risk populationClinical trial dataClinical trial sitesTrial populationIntervention trialsRisk populationsNew England JournalIndependent investigatorsTrial dataSecondary analysisSPRINT trialSPRINT dataTrialsRiskScoresParticipantsPopulationIdentifying county characteristics associated with resident well-being: A population based study
Roy B, Riley C, Herrin J, Spatz ES, Arora A, Kell KP, Welsh J, Rula EY, Krumholz HM. Identifying county characteristics associated with resident well-being: A population based study. PLOS ONE 2018, 13: e0196720. PMID: 29791476, PMCID: PMC5965855, DOI: 10.1371/journal.pone.0196720.Peer-Reviewed Original ResearchConceptsCounty-level factorsClinical careCross-sectional studyQuality of lifeBetter health outcomesMulti-dimensional assessmentHealth outcomesBeing IndexGallup-Sharecare WellUS residentsCareCounty characteristicsSurvey participantsResident wellUS countiesScoresCounty equivalentsAssessmentFactorsCohort
2017
Impact of Telemonitoring on Health Status
Jayaram NM, Khariton Y, Krumholz HM, Chaudhry SI, Mattera J, Tang F, Herrin J, Hodshon B, Spertus JA. Impact of Telemonitoring on Health Status. Circulation Cardiovascular Quality And Outcomes 2017, 10: e004148. PMID: 29237746, PMCID: PMC5776725, DOI: 10.1161/circoutcomes.117.004148.Peer-Reviewed Original ResearchConceptsKansas City Cardiomyopathy QuestionnaireUsual careHealth statusHeart failureKCCQ overall summary scoreRecent heart failure hospitalizationDisease-specific health statusKCCQ overall summaryHeart failure hospitalizationWeeks of dischargeRandomized clinical trialsOverall summary scoreKCCQ scoresNoninvasive TelemonitoringFailure hospitalizationBaseline characteristicsSecondary outcomesTreatment armsClinical trialsSummary scoresPatientsSubscale scoresCareHospitalizationScores
2015
Do Non-Clinical Factors Improve Prediction of Readmission Risk? Results From the Tele-HF Study
Krumholz HM, Chaudhry SI, Spertus JA, Mattera JA, Hodshon B, Herrin J. Do Non-Clinical Factors Improve Prediction of Readmission Risk? Results From the Tele-HF Study. JACC Heart Failure 2015, 4: 12-20. PMID: 26656140, PMCID: PMC5459404, DOI: 10.1016/j.jchf.2015.07.017.Peer-Reviewed Original ResearchConceptsReadmission ratesPatient-reported informationHeart failureHealth statusReadmission riskC-statisticRisk scorePsychosocial variablesMedical record abstractionWeeks of dischargeReadmission risk modelNon-clinical factorsCandidate risk factorsReadmission risk predictionRecord abstractionClinical variablesPatient interviewsMedical recordsRisk factorsPatientsPsychosocial informationPsychosocial characteristicsTelephone interviewsRisk predictionScores
2005
Performance of the Thrombolysis in Myocardial Infarction (TIMI) ST-elevation myocardial infarction risk score in a national cohort of elderly patients
Rathore SS, Weinfurt KP, Foody JM, Krumholz HM. Performance of the Thrombolysis in Myocardial Infarction (TIMI) ST-elevation myocardial infarction risk score in a national cohort of elderly patients. American Heart Journal 2005, 150: 402-410. PMID: 16169316, PMCID: PMC2790534, DOI: 10.1016/j.ahj.2005.03.069.Peer-Reviewed Original ResearchConceptsThirty-day mortality rateTIMI scoreElderly patientsMortality rateRisk scoreMyocardial Infarction (TIMI) risk scoreHigh TIMI scoreMyocardial Infarction (TIMI) scoreCommunity-based cohortReperfusion therapyTrial cohortPrognostic discriminationTrial populationNational cohortModest discriminationPatientsUS hospitalsSTEMICohortScore discriminationScoresThrombolysis