Cristiana Baloescu, MD, MPH
Assistant Professor of Emergency MedicineDownloadHi-Res Photo
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Appointments
Emergency Medicine
Primary
About
Titles
Assistant Professor of Emergency Medicine
Biography
Cristiana Baloescu graduated from the Yale Emergency Medicine Residency Program in 2017. She completed medical school at Dartmouth Geisel School of Medicine in 2013. During residency, she conducted research in disaster preparedness, applications of machine learning in point-of-care ultrasound interpretation, and served as the resident director of medical student education. After graduating from residency, she pursued further training in point-of-care ultrasound fellowship, as well as a Masters degree in public health at Yale. Her goal is to advance the field of point-of-care ultrasound, establish programs in developing countries. She is from Bucharest, Romania, and attended Wesleyan College in Macon, GA. An avid international travel, she met her husband, also a physician-scientist, during an academic exchange program in Germany.
Appointments
Emergency Medicine
Assistant ProfessorPrimary
Other Departments & Organizations
- Emergency Medicine
- Emergency Ultrasound
- Yale Medicine
Education & Training
- MPH
- Yale School of Public Health (2022)
- Resident
- Yale New Haven Hospital (2017)
- MD
- Geisel School of Medicine at Dartmouth (2013)
- BA
- Wesleyan College, Biology, Chemistry (2013)
Research
Overview
Current research projects include investigating software applications providing a quantitative assessment of interstitial fluid on lung point-of-care ultrasound and whether this corresponds to degree of clinical disease severity, automated estimation of ejection fraction on point-of-care echo clips.
I am also currently developing research studies in point-of-care ultrasound guided nerve blocks.
If you are a medical student looking for a research project to get involved with, please email me for details.
ORCID
0000-0001-7012-1260
Research at a Glance
Yale Co-Authors
Frequent collaborators of Cristiana Baloescu's published research.
Publications Timeline
A big-picture view of Cristiana Baloescu's research output by year.
Christopher L Moore, MD
Rachel Liu, BAO, MBBCh, FACEP, FAIUM
Andrew Ulrich, MD
Arjun Venkatesh, MD, MBA, MHS
Donald Wright, MD, MHS
Melissa Shaw
14Publications
182Citations
Publications
2024
Deep-learning generated B-line score mirrors clinical progression of disease for patients with heart failure
Baloescu C, Chen A, Varasteh A, Hall J, Toporek G, Patil S, McNamara R, Raju B, Moore C. Deep-learning generated B-line score mirrors clinical progression of disease for patients with heart failure. The Ultrasound Journal 2024, 16: 42. PMID: 39283362, PMCID: PMC11405569, DOI: 10.1186/s13089-024-00391-4.Peer-Reviewed Original ResearchConceptsB-line scoreComposite congestion scoreCongestion scoreHeart failureSeverity scoreB-linesCongestive heart failurePatients suspectedPulmonary congestionLung zonesClinical progressionRothman IndexClinical assessmentDisease severityPatientsPresence of artifactsEvaluate changesLungDetect fluidUltrasound experienceMixed effects modelsScoresDiseaseInterstitial spaceUltrasound systemPatient Factors Associated with Unplanned Sedation after Intra-articular Lidocaine for Shoulder Dislocation
Wright D, Sherak R, Seo L, Parhar A, Baloescu C. Patient Factors Associated with Unplanned Sedation after Intra-articular Lidocaine for Shoulder Dislocation. JEM Reports 2024, 3: 100093. DOI: 10.1016/j.jemrpt.2024.100093.Peer-Reviewed Original ResearchConceptsIntra-articular lidocaineIV sedationAdverse eventsShoulder dislocationRate of procedural complicationsRetrospective observational cohort studyQuantity of opioidsAcute anterior shoulder dislocationED length of stayAnterior shoulder dislocationObservational cohort studyPatient-level factorsMultivariate logistic regressionShoulder dislocation reductionAcademic hospital systemLength of stayAssociated with greater ratesComplication rateProcedural complicationsAdult patientsProspective studyUnivariate analysisIntravenous sedationCohort studyED lengthSpatiotemporal Deep Learning-Based Cine Loop Quality Filter for Handheld Point-of-Care Echocardiography
Mukaddim R, Mackay E, Gessert N, Erkamp R, Sethuraman S, Sutton J, Bharat S, Jutras M, Baloescu C, Moore C, Raju B. Spatiotemporal Deep Learning-Based Cine Loop Quality Filter for Handheld Point-of-Care Echocardiography. IEEE Transactions On Ultrasonics Ferroelectrics And Frequency Control 2024, PP: 1-1. PMID: 38700961, DOI: 10.1109/tuffc.2024.3396796.Peer-Reviewed Original ResearchConceptsOptical flow framesHigh-quality framesLow-quality framesNeural network architectureDeep learning modelsInput framesFrame levelEcho framesNetwork architectureSpatiotemporal deep learning modelCNN modelTemporal informationLV borderLearning modelsTest datasetSpatial informationFlow frameCNNImage qualityPoint-of-careQuantification algorithmHandheldAutomated quantification algorithmImage artifactsImage interpretationEmergency Physician-performed Echocardiogram in Non-ST Elevation Acute Coronary Syndrome Patients Requiring Coronary Intervention
Tan T, Wright D, Baloescu C, Lee S, Moore C. Emergency Physician-performed Echocardiogram in Non-ST Elevation Acute Coronary Syndrome Patients Requiring Coronary Intervention. Western Journal Of Emergency Medicine 2024, 0: 9-16. PMID: 38205979, PMCID: PMC10777186, DOI: 10.5811/westjem.60508.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsConceptsPresence of RWMARegional wall motion abnormalitiesCoronary interventionEmergency departmentEmergency physiciansElevation acute coronary syndrome patientsNew regional wall motion abnormalitiesNon-ST elevation acute coronary syndrome patientsAcute coronary syndrome patientsRetrospective observational cohort studyEarly coronary interventionDiagnostic coronary angiographyCoronary artery bypassCoronary syndrome patientsObservational cohort studyActivation criteriaIdentification of patientsWall motion abnormalitiesCare transthoracic echocardiographyMeeting inclusion criteriaED electrocardiogramArtery bypassSame admissionAdult patientsCohort study
2023
Development and interobserver reliability of a rating scale for lung ultrasound pathology in lower respiratory tract infection
Baloescu C, Chen A, Schnittke N, Hicks B, Zhu M, Kaili M, Shupp J, Chan D, Malia L, Coneybeare D, Gregory K, Kessler D, Raju B, Moore C. Development and interobserver reliability of a rating scale for lung ultrasound pathology in lower respiratory tract infection. WFUMB Ultrasound Open 2023, 1: 100006. DOI: 10.1016/j.wfumbo.2023.100006.Peer-Reviewed Original ResearchCitationsAltmetricConceptsLower respiratory tract infectionsRespiratory tract infectionsIntraclass correlation coefficientTract infectionsUltrasound pathologiesRating ScaleSonographic findingsInter-rater reliabilityExpert consensusPleural line abnormalitiesGood inter-rater reliabilityAverage intraclass correlation coefficientSeverity Rating ScalePleural effusionLung aerationSeverity ScaleFourth subsetInterobserver reliabilityCine clipsInfectionUltrasound expertsScanning protocolPathologyB-linesCOVID-19Machine Learning Algorithm Detection of Confluent B-Lines
Baloescu C, Rucki A, Chen A, Zahiri M, Ghoshal G, Wang J, Chew R, Kessler D, Chan D, Hicks B, Schnittke N, Shupp J, Gregory K, Raju B, Moore C. Machine Learning Algorithm Detection of Confluent B-Lines. Ultrasound In Medicine & Biology 2023, 49: 2095-2102. PMID: 37365065, DOI: 10.1016/j.ultrasmedbio.2023.05.016.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsTwo‐ Versus 8‐Zone Lung Ultrasound in Heart Failure: Analysis of a Large Data Set Using a Deep Learning Algorithm
Baloescu C, Chen A, Varasteh A, Toporek G, McNamara R, Raju B, Moore C. Two‐ Versus 8‐Zone Lung Ultrasound in Heart Failure: Analysis of a Large Data Set Using a Deep Learning Algorithm. Journal Of Ultrasound In Medicine 2023, 42: 2349-2356. PMID: 37255051, DOI: 10.1002/jum.16262.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsHeart failureLung ultrasoundBland-Altman plot analysisSubgroup analysisUltrasound protocolMore lung zonesProspective observational studyReal-world clinical useB-linesAdult patientsLung zonesObservational studyClinical useScanning protocolVideo loopsPatientsPlot analysisRate severityUltrasoundAverage severitySeverityScoresTwo- VersusFailureSeverity informationEmergency Department Point‐of‐Care Echocardiography and Lung Ultrasound in Predicting COVID‐19 Severity
Baloescu C, Weingart G, Moore C. Emergency Department Point‐of‐Care Echocardiography and Lung Ultrasound in Predicting COVID‐19 Severity. Journal Of Ultrasound In Medicine 2023, 42: 1841-1850. PMID: 36840721, DOI: 10.1002/jum.16205.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsLeft ventricular ejection fractionPleural line abnormalitiesSevere COVID-19Emergency departmentSevere COVIDPOCUS findingsCOVID-19Decreased LVEFEmergency department pointHypoxemic respiratory failureRetrospective cohort studyAdult ED patientsRight ventricular dilationVentricular ejection fractionWeeks of presentationSevere clinical courseCOVID-19 severityLung POCUSRespiratory failureCohort studyCare echocardiographyClinical courseDisease courseEjection fractionHospital admission
2022
Effect of Point-of-Care Ultrasound on Clinical Outcomes in Low-Resource Settings: A Systematic Review
Baloescu C, Parhar A, Liu R, Wanjiku GW. Effect of Point-of-Care Ultrasound on Clinical Outcomes in Low-Resource Settings: A Systematic Review. Ultrasound In Medicine & Biology 2022, 48: 1711-1719. PMID: 35786524, DOI: 10.1016/j.ultrasmedbio.2022.04.221.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsResource-limited settingsLow-resource settingsCare ultrasoundPre-specified primary outcomesEffects of POCUSFree-text termsPrimary outcomeClinical outcomesMedical Subject HeadingsPatient outcomesDifferential diagnosisPatient managementObservational studyMethodological qualityClinical utilityHigh riskElectronic databasesSystematic reviewPatient careFinal reviewPatient diagnosisPOCUSDiagnosisValuable interventionText terms
2021
Interobserver Agreement and Correlation of an Automated Algorithm for B‐Line Identification and Quantification With Expert Sonologist Review in a Handheld Ultrasound Device
Moore CL, Wang J, Battisti AJ, Chen A, Fincke J, Wang A, Wagner M, Raju B, Baloescu C. Interobserver Agreement and Correlation of an Automated Algorithm for B‐Line Identification and Quantification With Expert Sonologist Review in a Handheld Ultrasound Device. Journal Of Ultrasound In Medicine 2021, 41: 2487-2495. PMID: 34964489, DOI: 10.1002/jum.15935.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsIntraclass correlation coefficientHandheld ultrasound deviceB-linesAdult emergency department patientsPathologic lung conditionsEmergency department patientsUltrasound deviceDepartment patientsLung conditionsClinical studiesInterobserver agreementWeighted KappaUltrasound expertsPatientsCountMultiple settingsKappaUnique subjectsDyspnea
Clinical Care
Overview
Clinical Specialties
Emergency Medicine
Board Certifications
Emergency Medicine
- Certification Organization
- AB of Emergency Medicine
- Original Certification Date
- 2018
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