Featured Publications
Predicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learning
Kucukkaya A, Zeevi T, Chai N, Raju R, Haider S, Elbanan M, Petukhova-Greenstein A, Lin M, Onofrey J, Nowak M, Cooper K, Thomas E, Santana J, Gebauer B, Mulligan D, Staib L, Batra R, Chapiro J. Predicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learning. Scientific Reports 2023, 13: 7579. PMID: 37165035, PMCID: PMC10172370, DOI: 10.1038/s41598-023-34439-7.Peer-Reviewed Original ResearchThe Dead Donor Rule, Reversibility and Donor Wishes
Batra R, Latham S. The Dead Donor Rule, Reversibility and Donor Wishes. The American Journal Of Bioethics 2023, 23: 31-32. PMID: 36681919, DOI: 10.1080/15265161.2022.2159581.Peer-Reviewed Original ResearchPrediction of Death after Terminal Extubation, the Machine Learning Way
Huang J, Shung D, Burman T, Krishnaswamy S, Batra R. Prediction of Death after Terminal Extubation, the Machine Learning Way. Journal Of The American College Of Surgeons 2022, 235: s95-s96. DOI: 10.1097/01.xcs.0000896548.82546.55.Peer-Reviewed Original ResearchOutcomes of Simultaneous Liver‐Kidney Transplantation Using Kidneys of Deceased Donors With Acute Kidney Injury
Batra RK, Ariyamuthu VK, MacConmara MP, Gupta G, Gungor AB, Tanriover B. Outcomes of Simultaneous Liver‐Kidney Transplantation Using Kidneys of Deceased Donors With Acute Kidney Injury. Liver Transplantation 2022, 28: 983-997. PMID: 35006615, DOI: 10.1002/lt.26406.Peer-Reviewed Original ResearchConceptsSimultaneous liver-kidney transplantationDeath-censored graft failureAcute kidney injuryLiver-kidney transplantationDeceased donorsKidney injuryGraft failureSCr levelsMultivariable Cox proportional hazards modelsTerminal serum creatinine levelTransplantation Network registry dataCox proportional hazards modelShorter cold ischemia timeCause graft failureGood organ qualitySerum creatinine levelsCold ischemia timeInternational consensus guidelinesProportional hazards modelLiver transplantCreatinine levelsPrimary outcomeStudy cohortIschemia timeKidney diseaseThe use of nondirected donor organs in living donor liver transplantation: Perspectives and guidance
Fox AN, Liapakis A, Batra R, Bittermann T, Emamaullee J, Emre S, Genyk Y, Han H, Jackson W, Pomfret E, Raza M, Rodriguez‐Davalos M, Gold S, Samstein B, Shenoy A, Taner T, Roberts JP, Group T. The use of nondirected donor organs in living donor liver transplantation: Perspectives and guidance. Hepatology 2022, 75: 1579-1589. PMID: 34859474, DOI: 10.1002/hep.32260.Peer-Reviewed Original ResearchFrailty, an Imperfect ICU Rationing Criterion
Batra RK, Latham SR. Frailty, an Imperfect ICU Rationing Criterion. The American Journal Of Bioethics 2021, 21: 69-71. PMID: 34710005, DOI: 10.1080/15265161.2021.1980142.Peer-Reviewed Original ResearchNeural network predicts need for red blood cell transfusion for patients with acute gastrointestinal bleeding admitted to the intensive care unit
Shung D, Huang J, Castro E, Tay JK, Simonov M, Laine L, Batra R, Krishnaswamy S. Neural network predicts need for red blood cell transfusion for patients with acute gastrointestinal bleeding admitted to the intensive care unit. Scientific Reports 2021, 11: 8827. PMID: 33893364, PMCID: PMC8065139, DOI: 10.1038/s41598-021-88226-3.Peer-Reviewed Original ResearchConceptsAcute gastrointestinal bleedingRed blood cell transfusionBlood cell transfusionGastrointestinal bleedingHigh-risk patientsCell transfusionRed blood cellsPatient cohortIntensive Care III (MIMIC-III) critical care databaseIntensive care unit staySevere acute gastrointestinal bleedingPacked red blood cellsBlood cellsCommon gastrointestinal causesLaboratory test featuresTime-updated dataIntensive care unitValidation patient cohortCritical care databaseLarge urban hospitalMedical Information MartInternal validation setGastrointestinal causesUnit stayCare unitMachine Learning Models for Prediction of Posttreatment Recurrence in Early-Stage Hepatocellular Carcinoma Using Pretreatment Clinical and MRI Features: A Proof-of-Concept Study.
Iseke S, Zeevi T, Kucukkaya AS, Raju R, Gross M, Haider SP, Petukhova-Greenstein A, Kuhn TN, Lin M, Nowak M, Cooper K, Thomas E, Weber MA, Madoff DC, Staib L, Batra R, Chapiro J. Machine Learning Models for Prediction of Posttreatment Recurrence in Early-Stage Hepatocellular Carcinoma Using Pretreatment Clinical and MRI Features: A Proof-of-Concept Study. American Journal Of Roentgenology 2022, 220: 245-255. PMID: 35975886, PMCID: PMC10015590, DOI: 10.2214/ajr.22.28077.Peer-Reviewed Original ResearchConceptsEarly-stage hepatocellular carcinomaLiver transplantHepatocellular carcinomaImaging featuresPosttreatment recurrenceOrgan allocationMean AUCLiver transplant eligibilityPretreatment clinical characteristicsPretreatment MRI examinationsKaplan-Meier analysisKaplan-Meier curvesClinical characteristicsImaging surveillanceTherapy allocationTransplant eligibilityUnderwent treatmentClinical parametersRetrospective studyUnpredictable complicationMRI dataConcept studyPoor survivalClinical impactPretreatment MRIClinical and Ethical Framework for Liver Retransplantation Using Living Donor Grafts: A Western Perspective
Batra RK, Mulligan DC. Clinical and Ethical Framework for Liver Retransplantation Using Living Donor Grafts: A Western Perspective. Liver Transplantation 2022, 28: 760-762. PMID: 34931433, DOI: 10.1002/lt.26395.Peer-Reviewed Original ResearchInactive status is an independent predictor of liver transplant waitlist mortality and is associated with a transplant centers median meld at transplant
Merola J, Gan G, Stewart D, Noreen S, Mulligan D, Batra R, Haakinson D, Deng Y, Kulkarni S. Inactive status is an independent predictor of liver transplant waitlist mortality and is associated with a transplant centers median meld at transplant. PLOS ONE 2021, 16: e0260000. PMID: 34793524, PMCID: PMC8601542, DOI: 10.1371/journal.pone.0260000.Peer-Reviewed Original ResearchConceptsDonor service areasWaitlist mortalityTransplant centersMedian MELDHigh mortalityStatus changesLiver transplant waitlist mortalityDeceased donor transplantsInactive statusTransplant probabilityInactive patientsMELD scoreDonor transplantsHazard ratioIndependent predictorsTransplant ratesCare coordinationMortalityPatientsTransplantLevel cohortsTertileSignificant differencesCohortMELDMeaningful Residual Function, Permanence and Brain Death
Batra R, Latham S. Meaningful Residual Function, Permanence and Brain Death. AJOB Neuroscience 2023, 14: 269-271. PMID: 37682666, DOI: 10.1080/21507740.2023.2243891.Peer-Reviewed Original ResearchCurrent status: meeting the regulatory goals of your liver transplant program.
Batra RK, Mulligan DC. Current status: meeting the regulatory goals of your liver transplant program. Current Opinion In Organ Transplantation 2021, 26: 146-151. PMID: 33650996, DOI: 10.1097/mot.0000000000000869.Peer-Reviewed Original ResearchDeep learning–assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver
Oestmann PM, Wang CJ, Savic LJ, Hamm CA, Stark S, Schobert I, Gebauer B, Schlachter T, Lin M, Weinreb JC, Batra R, Mulligan D, Zhang X, Duncan JS, Chapiro J. Deep learning–assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver. European Radiology 2021, 31: 4981-4990. PMID: 33409782, PMCID: PMC8222094, DOI: 10.1007/s00330-020-07559-1.Peer-Reviewed Original ResearchConceptsNon-HCC lesionsHepatocellular carcinomaHCC lesionsAtypical imagingGrading systemLI-RADS criteriaAtypical imaging featuresPrimary liver cancerTypical hepatocellular carcinomaAtypical hepatocellular carcinomaContrast-enhanced MRISensitivity/specificityLiver transplantMethodsThis IRBRetrospective studyLiver malignanciesImaging featuresLiver cancerAtypical featuresConclusionThis studyLesionsMRIClinical applicationCarcinomaImage-based diagnosisThe Ethical Challenges of Stem Cell Therapy in Vascular Disorders
Batra R. The Ethical Challenges of Stem Cell Therapy in Vascular Disorders. 2020, 105-113. DOI: 10.1007/978-3-030-56954-9_4.Peer-Reviewed Original ResearchStem cell researchCell researchModern medicineReligious thinkersEthical conflictsEthical debateEthical challengesCultural controversyHuman beingsInevitable clashPolitical controversyFuturistic potentialBioethicsControversial debateDebateHuman cloneClinical medicineBiological conceptsControversyEthicistsPhilosophersBeneficenceEthicsReligionThinkersLiver Transplantation in the Time of COVID19: Barriers and Ethical Considerations for Management and Next Steps
Jaffe A, Schilsky ML, Deshpande R, Batra R. Liver Transplantation in the Time of COVID19: Barriers and Ethical Considerations for Management and Next Steps. Hepatology Communications 2020, 4: 1242-1256. PMID: 32838103, PMCID: PMC7361607, DOI: 10.1002/hep4.1568.Peer-Reviewed Original ResearchEnd-stage liver diseaseLiver transplantLiver transplantationLiver diseaseVirus severe acute respiratory syndrome coronavirus 2Severe acute respiratory syndrome coronavirus 2Acute respiratory syndrome coronavirus 2Respiratory syndrome coronavirus 2Syndrome coronavirus 2Critical care bedsLife-saving procedureHealth care systemCorona Virus DiseasePosttransplant recipientsCoronavirus 2Transplant programsTumor controlBlood productsCOVID19 infectionCare bedsPatientsStaff contactTransplantCare systemDiseaseINACTIVE STATUS CHANGE IS AN INDEPENDENT PREDICTOR OF WAITLIST MORTALITY AND DISPROPORTIONATELY IMPACTS PATIENTS IN DONOR SERVICE AREAS WITH A HIGHER MEDIAN MELD AT TRANSPLANT
Batra R, Noreen S, Stewart D, Haakinson D, Gan G, Deng Y, Mulligan D, Kulkarni S. INACTIVE STATUS CHANGE IS AN INDEPENDENT PREDICTOR OF WAITLIST MORTALITY AND DISPROPORTIONATELY IMPACTS PATIENTS IN DONOR SERVICE AREAS WITH A HIGHER MEDIAN MELD AT TRANSPLANT. Transplantation 2020, 104: s213-s213. DOI: 10.1097/01.tp.0000699484.39814.91.Peer-Reviewed Original ResearchPROOF-OF-CONCEPT USE OF MACHINE LEARNING TO PREDICT TUMOR RECURRENCE OF EARLY-STAGE HEPATOCELLULAR CARCINOMA BEFORE THERAPY USING BASELINE MAGNETIC RESONANCE IMAGING
Batra R, Kuecuekkaya A, Zeevi T, Raju R, Chai N, Haider S, Elbanan M, Petukhova A, Lin ,, Onofrey J, Nowak M, Cooper K, Thomas E, Gebauer B, Staib L, Chapiro J. PROOF-OF-CONCEPT USE OF MACHINE LEARNING TO PREDICT TUMOR RECURRENCE OF EARLY-STAGE HEPATOCELLULAR CARCINOMA BEFORE THERAPY USING BASELINE MAGNETIC RESONANCE IMAGING. Transplantation 2020, 104: s43-s44. DOI: 10.1097/01.tp.0000698472.65040.1e.Peer-Reviewed Original ResearchUtility of Liver Transplantation Within the Bounds of Non-futility
Batra R. Utility of Liver Transplantation Within the Bounds of Non-futility. Current Transplantation Reports 2020, 7: 187-193. DOI: 10.1007/s40472-020-00288-w.Peer-Reviewed Original ResearchOutcomes of Kidney Transplantation Utilizing Kidneys From High (>85%) Kidney Donor Profile Index (KDPI) Donors.
Boyle S, Batra R, Heilman R, Chakkera H, Khamash H, Huskey J, Moss A, Katariya N, Hewitt W, Reddy K. Outcomes of Kidney Transplantation Utilizing Kidneys From High (>85%) Kidney Donor Profile Index (KDPI) Donors. Transplantation 2014, 98: 134. DOI: 10.1097/00007890-201407151-00412.Peer-Reviewed Original Research
2024
Liver Transplant Costs and Activity After United Network for Organ Sharing Allocation Policy Changes
Ahmed O, Doyle M, Abouljoud M, Alonso D, Batra R, Brayman K, Brockmeier D, Cannon R, Chavin K, Delman A, DuBay D, Finn J, Fridell J, Friedman B, Fritze D, Ginos D, Goldberg D, Halff G, Karp S, Kohli V, Kumer S, Langnas A, Locke J, Maluf D, Meier R, Mejia A, Merani S, Mulligan D, Nibuhanupudy B, Patel M, Pelletier S, Shah S, Vagefi P, Vianna R, Zibari G, Shafer T, Orloff S. Liver Transplant Costs and Activity After United Network for Organ Sharing Allocation Policy Changes. JAMA Surgery 2024, 159: 939-947. PMID: 38809546, PMCID: PMC11137658, DOI: 10.1001/jamasurg.2024.1208.Peer-Reviewed Original Research