2025
The International Society of Nephrology Collaborative Quality Framework to Support Safe and Effective Dialysis Provision in Resource-Challenged Settings
Davies S, Naicker S, Liew A, Vachharajani T, Pecoits-Filho R, Jha V, Finkelstein F, Harris D. The International Society of Nephrology Collaborative Quality Framework to Support Safe and Effective Dialysis Provision in Resource-Challenged Settings. Kidney International Reports 2025, 10: 663-672. DOI: 10.1016/j.ekir.2024.11.1366.Peer-Reviewed Original ResearchCatastrophic healthcare expenditureContinuous quality improvementQuality frameworkHealthcare commissionersPatient safetyLack of resourcesSub-optimal qualityHealthcare expendituresIterative reviewResource-challenged settingsInequitable accessQuality improvementResource settingsDialysis provisionDialysis planningProvidersExternal validationInternational SocietyPatient groupPolicy makersEffective treatmentHealthcarePatientsSetsFunders
2024
International multi-institutional external validation of preoperative risk scores for 30-day in-hospital mortality in paediatric patients
Tangel V, Hoeks S, Stolker R, Brown S, Pryor K, de Graaff J, Committee M, Pace N, Domino K, Muehlschlegel J, Kheterpal S, Vaughan M, Mathis M, Jiang S, Obembe S, Freundlich R, Schonberger R, Kim D. International multi-institutional external validation of preoperative risk scores for 30-day in-hospital mortality in paediatric patients. British Journal Of Anaesthesia 2024, 133: 1222-1233. PMID: 39477712, DOI: 10.1016/j.bja.2024.09.003.Peer-Reviewed Original ResearchConceptsSurgical risk scoresPediatric risk assessmentArea under the receiver operating characteristic curveIn-hospital mortalityRisk scoreMulticenter Perioperative Outcomes GroupPreoperative risk scoreDecision curve analysisReceiver operating characteristic curvePhysical status scoreExternal validationAssess model discriminationRisk prediction scoreASA physical status scoreClinical decision-makingPaediatric patientsLow probability of mortalityDutch hospitalsOutcome groupPatient-specific risk scoresPrimary outcomeClustering of casesCurve analysisStatus scoreCharacteristic curveBrain-phenotype predictions of language and executive function can survive across diverse real-world data: Dataset shifts in developmental populations
Adkinson B, Rosenblatt M, Dadashkarimi J, Tejavibulya L, Jiang R, Noble S, Scheinost D. Brain-phenotype predictions of language and executive function can survive across diverse real-world data: Dataset shifts in developmental populations. Developmental Cognitive Neuroscience 2024, 70: 101464. PMID: 39447452, PMCID: PMC11538622, DOI: 10.1016/j.dcn.2024.101464.Peer-Reviewed Original ResearchBrain-phenotype associationsConnectome-based predictive modelingBrain-behavior associationsPrediction of languagePhiladelphia Neurodevelopmental CohortHealthy Brain NetworkClinical symptom burdenFMRI taskHuman Connectome ProjectExecutive functionBehavioral measuresDevelopmental populationsNeurodevelopmental CohortBrain networksDevelopmental sampleConnectome ProjectResearch settingsGeneralizabilitySymptom burdenExternal validationFMRIClinical settingAssociationEthnic minority representationTaskRadiomics-driven personalized radiotherapy for primary and recurrent tumors: A general review with a focus on reirradiation
Beddok A, Orlhac F, Rozenblum L, Calugaru V, Créhange G, Dercle L, Nioche C, Thariat J, Marin T, El Fakhri G, Buvat I. Radiomics-driven personalized radiotherapy for primary and recurrent tumors: A general review with a focus on reirradiation. Cancer/Radiothérapie 2024, 28: 597-602. PMID: 39406602, DOI: 10.1016/j.canrad.2024.09.002.Peer-Reviewed Original ResearchPersonalized radiotherapyTumor localizationTreatment planningMedian AUCImaging modalitiesRisk of recurrenceHead and neckImprove treatment precisionPredicting clinical outcomesOptimal treatment planQuantitative imaging biomarkersRecurrent tumorsApplication of radiomicsRecurrent cancerClinical radiotherapyExternal validationClinical outcomesRadiotherapyReirradiationLack of external validationMEDLINE searchTreatment precisionImaging biomarkersImaging protocolTumorPower and reproducibility in the external validation of brain-phenotype predictions
Rosenblatt M, Tejavibulya L, Sun H, Camp C, Khaitova M, Adkinson B, Jiang R, Westwater M, Noble S, Scheinost D. Power and reproducibility in the external validation of brain-phenotype predictions. Nature Human Behaviour 2024, 8: 2018-2033. PMID: 39085406, DOI: 10.1038/s41562-024-01931-7.Peer-Reviewed Original ResearchHuman Connectome ProjectAdolescent Brain Cognitive Development StudyConnectome ProjectCognitive Development StudyPhiladelphia Neurodevelopmental CohortHealthy Brain NetworkStructural connectivity dataMatrix reasoningWorking memoryAnxiety/depression symptomsAttention problemsNeurodevelopmental CohortBrain networksBrain-phenotype associationsEffect sizeConnectivity dataExternal validationRelated processesValidation studySample sizeBrain ProjectDevelopment studiesTraining sample sizeGeneralizability of modelsExternal samplesAn Updated Simplified Severity Scale for Age-Related Macular Degeneration Incorporating Reticular Pseudodrusen Age-Related Eye Disease Study Report Number 42
Agrón E, Domalpally A, Chen Q, Lu Z, Chew E, Keenan T, Groups A. An Updated Simplified Severity Scale for Age-Related Macular Degeneration Incorporating Reticular Pseudodrusen Age-Related Eye Disease Study Report Number 42. Ophthalmology 2024, 131: 1164-1174. PMID: 38657840, PMCID: PMC11416341, DOI: 10.1016/j.ophtha.2024.04.011.Peer-Reviewed Original ResearchAge-Related Eye Disease StudyProgression to late AMDReticular pseudodrusenLate AMDFive-year ratesProgression rateAge-related macular degenerationSeverity ScaleEye Disease StudyClinical trial cohortIncrease prognostic accuracyPost hoc analysisMacular degenerationAREDS2Prognostic accuracyTrial cohortRisk featuresHoc analysisRisk categorizationPseudodrusenAge-relatedBaselineDisease StudyRiskExternal validationRisk Score for Long-Term Survival and Major Adverse Cardiovascular and Cerebrovascular Events After Coronary Artery Bypass Grafting Surgery
Dokollari A, Rosati F, Muneretto C, Amabile A, Pernoci M, Gemelli M, Hassanabad A, Sicouri S, Sicouri N, Yamashita Y, Baudo M, Bonacchi M, Cabrucci F, Bacchi B, Ghorpade N, Shah A, Coku L, Cameli M, Mandoli G, Kjelstrom S, Montone G, Wertan M, Ramlawi B, DiMagli A, Sutter F. Risk Score for Long-Term Survival and Major Adverse Cardiovascular and Cerebrovascular Events After Coronary Artery Bypass Grafting Surgery. The American Journal Of Cardiology 2024, 225: 10-21. PMID: 38608800, DOI: 10.1016/j.amjcard.2024.03.039.Peer-Reviewed Original ResearchIsolated coronary artery bypass graftingCoronary artery bypass graftingRisk scoreLong-term survivalCoronary risk scoreFollow-upExternal validationAll-cause mortalityCoronary artery bypass graft surgeryArtery bypass graft surgeryAfrican American ethnicityAll-causeBypass graft surgeryArtery bypass graftingLong-term mortalityYear follow-upPredictive risk scoreRisk score modelAmerican ethnicityGraft surgeryBypass graftingCerebrovascular eventsRisk predictorsMyocardial infarctionBootstrap cross-validationAutomated MRI liver segmentation for anatomical segmentation, liver volumetry, and the extraction of radiomics
Gross M, Huber S, Arora S, Ze’evi T, Haider S, Kucukkaya A, Iseke S, Kuhn T, Gebauer B, Michallek F, Dewey M, Vilgrain V, Sartoris R, Ronot M, Jaffe A, Strazzabosco M, Chapiro J, Onofrey J. Automated MRI liver segmentation for anatomical segmentation, liver volumetry, and the extraction of radiomics. European Radiology 2024, 34: 5056-5065. PMID: 38217704, PMCID: PMC11245591, DOI: 10.1007/s00330-023-10495-5.Peer-Reviewed Original ResearchMagnetic resonance imagingRadiomics feature extractionLiver volumetryIntraclass correlation coefficientRadiomic featuresLiver segmentationAutomated liver volumetryHepatocellular carcinoma patientsMann-Whitney U testAutomated liver segmentationManual segmentationQuantitative imaging biomarkersCarcinoma patientsRetrospective studyInstitutional databaseAnatomical localizationClinical relevanceManual volumetryMann-WhitneyU testExternal validationInternal test setImaging biomarkersInclusion criteriaResultsIn total
2023
Paths Forward for Clinicians Amidst the Rise of Unregulated Clinical Decision Support Software: Our Perspective on NarxCare
Buonora M, Axson S, Cohen S, Becker W. Paths Forward for Clinicians Amidst the Rise of Unregulated Clinical Decision Support Software: Our Perspective on NarxCare. Journal Of General Internal Medicine 2023, 39: 858-862. PMID: 37962733, PMCID: PMC11043299, DOI: 10.1007/s11606-023-08528-2.Peer-Reviewed Original ResearchClinical decision support toolClinical decision support softwareHealthcare institutionsOpioid prescribingOverdose epidemicPatient encountersIndividual cliniciansPatient careProprietary formulaRigorous external validationCliniciansWider implementationExternal validationPrescribingPotential harmSufficient evidencePublic healthDecision support softwareDecision support toolSpecific actionsMortalityCareTime and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging
Pieszko K, Shanbhag A, Singh A, Hauser M, Miller R, Liang J, Motwani M, Kwieciński J, Sharir T, Einstein A, Fish M, Ruddy T, Kaufmann P, Sinusas A, Miller E, Bateman T, Dorbala S, Di Carli M, Berman D, Dey D, Slomka P. Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging. Npj Digital Medicine 2023, 6: 78. PMID: 37127660, PMCID: PMC10151323, DOI: 10.1038/s41746-023-00806-x.Peer-Reviewed Original ResearchAcute coronary syndromeMajor adverse cardiovascular eventsMyocardial perfusion imagingCause deathAdverse cardiovascular eventsModifiable risk factorsPrediction of deathPersonalized risk assessmentCardiovascular eventsCoronary syndromeClinical featuresPrognostic valueRisk factorsExternal cohortStandard clinical interpretationPerfusion imagingAbnormality measuresCardiac perfusionTime pointsPatients' explanationsClinical interpretationExternal validationDeathPatientsRisk assessmentDevelopment and external validation of machine learning algorithms for postnatal gestational age estimation using clinical data and metabolomic markers
Hawken S, Ducharme R, Murphy M, Olibris B, Bota A, Wilson L, Cheng W, Little J, Potter B, Denize K, Lamoureux M, Henderson M, Rittenhouse K, Price J, Mwape H, Vwalika B, Musonda P, Pervin J, Chowdhury A, Rahman A, Chakraborty P, Stringer J, Wilson K. Development and external validation of machine learning algorithms for postnatal gestational age estimation using clinical data and metabolomic markers. PLOS ONE 2023, 18: e0281074. PMID: 36877673, PMCID: PMC9987787, DOI: 10.1371/journal.pone.0281074.Peer-Reviewed Original ResearchConceptsGestational ageCord blood dataClinical dataBlood dataMetabolomic markersEarly pregnancy ultrasoundHeel-prick blood sampleProspective birth cohortMultivariable linear regressionBlood sample dataExternal validationGestational age estimationRetrospective cohortPregnancy ultrasoundHeel prickExternal cohortIndependent cohortBlood samplesBirth cohortNewbornsPostnatal gestational age estimationCohortUltrasound estimatesInternal model validationLow-income countriesIdentifying Depression Early in Adolescence: assessing the performance of a risk score for future onset of depression in an independent Brazilian sample
Cunha G, Caye A, Pan P, Fisher H, Pereira R, Ziebold C, Bressan R, Miguel E, Salum G, Rohde L, Kohrt B, Mondelli V, Kieling C, Gadelha A. Identifying Depression Early in Adolescence: assessing the performance of a risk score for future onset of depression in an independent Brazilian sample. Brazilian Journal Of Psychiatry 2023, 45: 242-248. PMID: 37126861, PMCID: PMC10288471, DOI: 10.1590/1516-4446-2022-2775.Peer-Reviewed Original Research
2022
NS-HGlio: A generalizable and repeatable HGG segmentation and volumetric measurement AI algorithm for the longitudinal MRI assessment to inform RANO in trials and clinics
Abayazeed A, Abbassy A, Müeller M, Hill M, Qayati M, Mohamed S, Mekhaimar M, Raymond C, Dubey P, Nael K, Rohatgi S, Kapare V, Kulkarni A, Shiang T, Kumar A, Andratschke N, Willmann J, Brawanski A, De Jesus R, Tuna I, Fung S, Landolfi J, Ellingson B, Reyes M. NS-HGlio: A generalizable and repeatable HGG segmentation and volumetric measurement AI algorithm for the longitudinal MRI assessment to inform RANO in trials and clinics. Neuro-Oncology Advances 2022, 5: vdac184. PMID: 36685009, PMCID: PMC9850874, DOI: 10.1093/noajnl/vdac184.Peer-Reviewed Original ResearchHigh-grade gliomasNeuro-Oncology criteriaResidual tumor volumeTreatment response monitoringIntraclass correlation coefficientMRI assessmentTreatment responseTumor volumeResponse assessmentRadiation planningTumor tissueInternal validationResponse monitoringGBM datasetsMRIExternal validationVolumetric measurementsEDDice similarity coefficientExternal validation of yonsei nomogram predicting chronic kidney disease development after partial nephrectomy: An international, multicenter study
Raheem A, Landi I, Alowidah I, Capitanio U, Montorsi F, Larcher A, Derweesh I, Ghali F, Mottrie A, Mazzone E, De Naeyer G, Campi R, Sessa F, Carini M, Minervini A, Raman J, Rjepaj C, Kriegmair M, Autorino R, Veccia A, Mir M, Claps F, Choi Y, Ham W, Santok G, Tadifa J, Syling J, Furlan M, Simeone C, Bada M, Celia A, Carrión D, Bazan A, Ruiz C, Malki M, Barber N, Hussain M, Micali S, Puliatti S, Ghaith A, Hagras A, Ghoneem A, Eissa A, Alqahtani A, Rumaih A, Alwahabi A, Alenzi M, Pavan N, Traunero F, Antonelli A, Porcaro A, Illiano E, Costantini E, Rha K. External validation of yonsei nomogram predicting chronic kidney disease development after partial nephrectomy: An international, multicenter study. International Journal Of Urology 2022, 30: 308-317. PMID: 36478459, DOI: 10.1111/iju.15108.Peer-Reviewed Original ResearchConceptsNew-onset CKDCKD stageChronic kidney disease developmentExternal validationCKD stage ICT1 renal massesKidney disease developmentPreoperative eGFRPatient ageConsecutive patientsMulticenter studyTumor sizePartial nephrectomyRenal massesProgression rateGood calibration propertiesStage IProgression probabilityPatientsNomogramIndividual riskCKDDisease developmentEGFRMedian valuePrediction of Distant Metastases After Stereotactic Body Radiation Therapy for Early Stage NSCLC: Development and External Validation of a Multi-Institutional Model
Gao S, Jin L, Meadows H, Shafman T, Gross C, Yu J, Aerts H, Miccio J, Stahl J, Mak R, Decker R, Kann B. Prediction of Distant Metastases After Stereotactic Body Radiation Therapy for Early Stage NSCLC: Development and External Validation of a Multi-Institutional Model. Journal Of Thoracic Oncology 2022, 18: 339-349. PMID: 36396062, DOI: 10.1016/j.jtho.2022.11.007.Peer-Reviewed Original ResearchConceptsStereotactic body radiation therapyEarly-stage NSCLCBody radiation therapyDistant metastasisStage NSCLCRadiation therapyHigh-risk patient subgroupsExternal validationPatient-level riskMulti-institutional databaseTime-dependent areaGray regression modelsRandom survival forest modelDM riskSystemic therapyPatient subgroupsIndividualized riskNSCLCPatientsDM ratesDiscriminatory performanceRandom survival forestTherapyInternal validationGood calibrationA Novel Machine Learning-Based Point-Score Model as a Non-Invasive Decision-Making Tool for Identifying Infected Ascites in Patients with Hydropic Decompensated Liver Cirrhosis: A Retrospective Multicentre Study
Würstle S, Hapfelmeier A, Karapetyan S, Studen F, Isaakidou A, Schneider T, Schmid R, von Delius S, Gundling F, Triebelhorn J, Burgkart R, Obermeier A, Mayr U, Heller S, Rasch S, Lahmer T, Geisler F, Chan B, Turner P, Rothe K, Spinner C, Schneider J. A Novel Machine Learning-Based Point-Score Model as a Non-Invasive Decision-Making Tool for Identifying Infected Ascites in Patients with Hydropic Decompensated Liver Cirrhosis: A Retrospective Multicentre Study. Antibiotics 2022, 11: 1610. PMID: 36421254, PMCID: PMC9686825, DOI: 10.3390/antibiotics11111610.Peer-Reviewed Original ResearchDecompensated liver cirrhosisInfected ascitesLiver cirrhosisPredictive valueHigh negative predictive valueRetrospective multicentre studySimilar predictive valuePre-test probabilityEpisodes of patientsFurther external validationNegative predictive valuePositive predictive valuePromising non-invasive approachLaboratory featuresMulticentre studyProspective studyAscitesCirrhosisPatientsNon-invasive approachClinical routineLASSO regression modelExternal validationAbdominocentesisRegression modelsDerivation and Validation of a Brief Emergency Department-Based Prediction Tool for Posttraumatic Stress After Motor Vehicle Collision
Jones C, An X, Ji Y, Liu M, Zeng D, House S, Beaudoin F, Stevens J, Neylan T, Clifford G, Jovanovic T, Linnstaedt S, Germine L, Bollen K, Rauch S, Haran J, Storrow A, Lewandowski C, Musey P, Hendry P, Sheikh S, Punches B, Lyons M, Kurz M, Swor R, McGrath M, Hudak L, Pascual J, Seamon M, Datner E, Harris E, Chang A, Pearson C, Peak D, Merchant R, Domeier R, Rathlev N, O'Neil B, Sergot P, Sanchez L, Bruce S, Miller M, Pietrzak R, Joormann J, Barch D, Pizzagalli D, Sheridan J, Smoller J, Harte S, Elliott J, Koenen K, Ressler K, Kessler R, McLean S. Derivation and Validation of a Brief Emergency Department-Based Prediction Tool for Posttraumatic Stress After Motor Vehicle Collision. Annals Of Emergency Medicine 2022, 81: 249-261. PMID: 36328855, PMCID: PMC11181458, DOI: 10.1016/j.annemergmed.2022.08.011.Peer-Reviewed Original ResearchConceptsMotor vehicle collisionsPosttraumatic stress symptomsValidation cohortSubstantial posttraumatic stress symptomsStress symptomsVehicle collisionsRisk-stratify individualsClinical decision support toolEmergency department patientsPersistent posttraumatic stress symptomsPreventive intervention trialNumber of EDsEase of administrationDerivation cohortPrimary outcomeDepartment patientsIntervention trialsBaseline healthHigh riskSymptomsCohortExternal validationPsychological recoveryDiscriminative abilityPosttraumatic stressP2.12-03 External Validation of a Novel CT-Based Prognostic Radiomic Signature in Patients with Metastatic NSCLC in SWOG S0819 Phase III Randomized Trial
Dercle L, Gomez D, Zhao B, Kelly K, Herbst R, Redman M, Gandara D, Schwartz L. P2.12-03 External Validation of a Novel CT-Based Prognostic Radiomic Signature in Patients with Metastatic NSCLC in SWOG S0819 Phase III Randomized Trial. Journal Of Thoracic Oncology 2022, 17: s152. DOI: 10.1016/j.jtho.2022.07.251.Peer-Reviewed Original ResearchDevelopment and validation of the age-associated dementia policy (AgeD-Pol) computer simulation model in the USA and Europe
Hyle E, Foote J, Shebl F, Qian Y, Reddy K, Mukerji S, Wattananimitgul N, Viswanathan A, Schwamm L, Pandya A, Freedberg K. Development and validation of the age-associated dementia policy (AgeD-Pol) computer simulation model in the USA and Europe. BMJ Open 2022, 12: e056546. PMID: 35793913, PMCID: PMC9260808, DOI: 10.1136/bmjopen-2021-056546.Peer-Reviewed Original ResearchConceptsAge-associated dementiaKaiser Permanente Northern CaliforniaCumulative incidenceAAD incidenceInternal validationLifetime cumulative incidenceSex-stratified dataExternal validationFramingham Heart StudyCohort studyRotterdam StudyRotterdam cohortDisease burdenDisease progressionOutcome measuresHeart StudyDATA SOURCESACT cohortAdult ChangesCohort dataNatural historyCohortMortalityHealth systemIncidenceMo1160: EXTERNAL VALIDATION OF A PREDICTIVE MODEL DETERMINING RISK OF NEOPLASTIC PROGRESSION OF BARRETT'S ESOPHAGUS IN A COHORT OF UNITED STATES VETERANS
Nguyen T, Thrift A, Ketwaroo G, Du X, Novelo L, George R, Rosen D, El-Serag H. Mo1160: EXTERNAL VALIDATION OF A PREDICTIVE MODEL DETERMINING RISK OF NEOPLASTIC PROGRESSION OF BARRETT'S ESOPHAGUS IN A COHORT OF UNITED STATES VETERANS. Gastroenterology 2022, 162: s-719. DOI: 10.1016/s0016-5085(22)61693-7.Peer-Reviewed Original Research
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