2023
Cardiometabolic disease and obesity patterns differentially predict acute kidney injury after total joint replacement: a retrospective analysis
Leis A, Mathis M, Kheterpal S, Zawistowski M, Mukherjee B, Pace N, O'Reilly-Shah V, Smith J, Karvonen-Gutierrez C. Cardiometabolic disease and obesity patterns differentially predict acute kidney injury after total joint replacement: a retrospective analysis. British Journal Of Anaesthesia 2023, 131: 37-46. PMID: 37188560, PMCID: PMC10308436, DOI: 10.1016/j.bja.2023.04.001.Peer-Reviewed Original ResearchConceptsOdds of acute kidney injuryAcute kidney injuryCardiometabolic diseasesNon-Hispanic blacksGroup of hospitalsKidney injuryCardiometabolic patternTotal joint arthroplasty complicationsObesity statusObesity patternsIncreased oddsDisease co-occurrenceIncreased odds of AKIRetrospective analysisRisk of postoperative acute kidney injuryLatent class analysisLatent classesPostoperative acute kidney injuryRisk of acute kidney injuryRisk factorsDifferential riskTotal joint replacementMetabolic syndromeObesityPostoperative AKI risk
2019
Does Information on Blood Heavy Metals Improve Cardiovascular Mortality Prediction?
Wang X, Mukherjee B, Park S. Does Information on Blood Heavy Metals Improve Cardiovascular Mortality Prediction? Journal Of The American Heart Association 2019, 8: e013571. PMID: 31631727, PMCID: PMC6898859, DOI: 10.1161/jaha.119.013571.Peer-Reviewed Original ResearchMeSH KeywordsAgedBiomarkersCadmiumCardiovascular DiseasesFemaleHumansLeadMaleMercuryMiddle AgedPredictive Value of TestsRisk FactorsConceptsCardiovascular diseaseNational Health and Nutrition Examination SurveyHealth and Nutrition Examination SurveyRisk factorsStudy sampleCardiovascular disease risk factorsCardiovascular disease mortalityCardiovascular disease risk assessmentImprove CVD risk predictionC-statisticNutrition Examination SurveyCardiovascular mortality predictionCVD risk predictionCox modelBlood markersExamination SurveyPrecision healthRisk scorePairwise interaction termsBlood metalsIntegrated discrimination improvementRisk predictionReclassification improvementMortality predictionInteraction terms
2017
Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES
Park S, Zhao Z, Mukherjee B. Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES. Environmental Health 2017, 16: 102. PMID: 28950902, PMCID: PMC5615812, DOI: 10.1186/s12940-017-0310-9.Peer-Reviewed Original ResearchConceptsEnvironmental risk scoreBayesian kernel machine regressionNational Health and Nutrition Examination SurveyHealth and Nutrition Examination SurveyRisk scoreAssociated with odds ratiosNutrition Examination SurveyAssociated with systolicExamination SurveyMulti-pollutant approachKernel machine regressionPollutant mixturesSD increaseEpidemiological researchDiastolic blood pressureMortality outcomesOdds ratioBayesian additive regression treesDisease endpointsHealth endpointsCumulative riskPositive associationEnvironmental exposuresIntermediate markersCardiovascular disease
2015
Extreme Air Pollution Conditions Adversely Affect Blood Pressure and Insulin Resistance
Brook R, Sun Z, Brook J, Zhao X, Ruan Y, Yan J, Mukherjee B, Rao X, Duan F, Sun L, Liang R, Lian H, Zhang S, Fang Q, Gu D, Sun Q, Fan Z, Rajagopalan S. Extreme Air Pollution Conditions Adversely Affect Blood Pressure and Insulin Resistance. Hypertension 2015, 67: 77-85. PMID: 26573709, PMCID: PMC4830086, DOI: 10.1161/hypertensionaha.115.06237.Peer-Reviewed Original ResearchConceptsFine particulate matterParticulate matterAmbient fine particulate matterSD increaseAssociated with worsening insulin resistanceBlack carbon levelsBlack carbon exposurePublic health warningsAir pollutionBeijing metropolitan areaBlack carbonHealth warningsAssociated with rangeCardiometabolic healthCarbon levelsDiastolic blood pressureExposure windowsCardiometabolic diseasesHealth effectsNonsmoking adultsMetabolic syndromeDeveloping world todayCarbon exposureSystolic blood pressure elevationHealth
2013
Cardiovascular Depression in Rats Exposed to Inhaled Particulate Matter and Ozone: Effects of Diet-Induced Metabolic Syndrome
Wagner J, Allen K, Yang H, Nan B, Morishita M, Mukherjee B, Dvonch J, Spino C, Fink G, Rajagopalan S, Sun Q, Brook R, Harkema J. Cardiovascular Depression in Rats Exposed to Inhaled Particulate Matter and Ozone: Effects of Diet-Induced Metabolic Syndrome. Environmental Health Perspectives 2013, 122: 27-33. PMID: 24169565, PMCID: PMC3888573, DOI: 10.1289/ehp.1307085.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBlood PressureCardiovascular DiseasesEnvironmental MonitoringHeart RateMaleMetabolic SyndromeOzoneParticulate MatterRatsRats, Sprague-DawleyConceptsHFrD ratsBlood pressureND ratsHeart rateMetabolic syndromeHR variabilityFasting levels of blood glucoseNormal dietMale Sprague-Dawley ratsParticulate matterAssociated with cardiovascular morbidityCardiovascular depressionAir pollutionSprague-Dawley ratsDiet-induced metabolic syndromeElevated fasting levelsToxicity of air pollutantsFine particulate matterHigh-fructose dietLevels of blood glucoseInhalable particulate matterLevels of ozoneInduce MetSCardiovascular morbidityExaggerated BP