2022
DKA Prevention and Insulin Pumps: Lessons Learned From a Large Pediatric Pump Practice
Doyle EA, Weinzimer SA, Tamborlane W. DKA Prevention and Insulin Pumps: Lessons Learned From a Large Pediatric Pump Practice. The Science Of Diabetes Self-Management And Care 2022, 48: 476-482. PMID: 36129121, DOI: 10.1177/26350106221125699.Peer-Reviewed Original ResearchConceptsContinuous glucose monitorHigher A1C levelsA1c levelsDKA eventsInsulin pumpPump usersPump-treated patientsRetrospective chart reviewPediatric endocrinology practiceType 1 diabetesInsulin pump usersConcurrent illnessDKA preventionPump patientsDiabetes durationDKA episodesMean A1CChart reviewEndocrinology practiceDKA ratesDKA severityMean ageInsulin omissionMost episodesPatientsA Pilot randomized trial to examine effects of a hybrid closed-loop insulin delivery system on neurodevelopmental and cognitive outcomes in adolescents with type 1 diabetes
Reiss AL, Jo B, Arbelaez AM, Tsalikian E, Buckingham B, Weinzimer SA, Fox LA, Cato A, White NH, Tansey M, Aye T, Tamborlane W, Englert K, Lum J, Mazaika P, Foland-Ross L, Marzelli M, Mauras N. A Pilot randomized trial to examine effects of a hybrid closed-loop insulin delivery system on neurodevelopmental and cognitive outcomes in adolescents with type 1 diabetes. Nature Communications 2022, 13: 4940. PMID: 36042217, PMCID: PMC9427757, DOI: 10.1038/s41467-022-32289-x.Peer-Reviewed Original ResearchConceptsHybrid closed-loop insulin delivery systemStandard care groupType 1 diabetesClosed-loop insulin delivery systemWhite matter volumeCare groupPrimary outcomeInsulin delivery systemsMatter volumeFractional anisotropyCognitive AssessmentRigorous glucose controlDiagnosis of T1DClosed-loop groupBetter diabetes controlDiabetes care groupsConcept pilot studyYears of ageAcademic medical centerFunctional brain activityCortical surface areaMonths study durationRandomized participantsDiabetes controlGlucose controlLived experience of CamAPS FX closed loop system in youth with type 1 diabetes and their parents
Hood KK, Garcia‐Willingham N, Hanes S, Tanenbaum ML, Ware J, Boughton CK, Allen JM, Wilinska ME, Tauschmann M, Denvir L, Thankamony A, Campbell F, Wadwa RP, Buckingham BA, Davis N, DiMeglio LA, Mauras N, Besser REJ, Ghatak A, Weinzimer SA, Fox DS, Kanapka L, Kollman C, Sibayan J, Beck RW, Hovorka R, Consortium T. Lived experience of CamAPS FX closed loop system in youth with type 1 diabetes and their parents. Diabetes Obesity And Metabolism 2022, 24: 2309-2318. PMID: 35837984, PMCID: PMC9804666, DOI: 10.1111/dom.14815.Peer-Reviewed Original ResearchCambridge hybrid closed-loop algorithm in children and adolescents with type 1 diabetes: a multicentre 6-month randomised controlled trial
Ware J, Boughton CK, Allen JM, Wilinska ME, Tauschmann M, Denvir L, Thankamony A, Campbell FM, Wadwa RP, Buckingham BA, Davis N, DiMeglio LA, Mauras N, Besser REJ, Ghatak A, Weinzimer SA, Hood KK, Fox DS, Kanapka L, Kollman C, Sibayan J, Beck RW, Hovorka R, Consortium D, Hovorka R, Acerini C, Thankamony A, Allen J, Boughton C, Dovc K, Dunger D, Ware J, Musolino G, Tauschmann M, Wilinska M, Hayes J, Hartnell S, Slegtenhorst S, Ruan Y, Haydock M, Mangat J, Denvir L, Kanthagnany S, Law J, Randell T, Sachdev P, Saxton M, Coupe A, Stafford S, Ball A, Keeton R, Cresswell R, Crate L, Cripps H, Fazackerley H, Looby L, Navarra H, Saddington C, Smith V, Verhoeven V, Bratt S, Khan N, Moyes L, Sandhu K, West C, Wadwa R, Alonso G, Forlenza G, Slover R, Towers L, Berget C, Coakley A, Escobar E, Jost E, Lange S, Messer L, Thivener K, Campbell F, Yong J, Metcalfe E, Allen M, Ambler S, Waheed S, Exall J, Tulip J, Buckingham B, Ekhlaspour L, Maahs D, Norlander L, Jacobson T, Twon M, Weir C, Leverenz B, Keller J, Davis N, Kumaran A, Trevelyan N, Dewar H, Price G, Crouch G, Ensom R, Haskell L, Lueddeke L, Mauras N, Benson M, Bird K, Englert K, Permuy J, Ponthieux K, Marrero-Hernandez J, DiMeglio L, Ismail H, Jolivette H, Sanchez J, Woerner S, Kirchner M, Mullen M, Tebbe M, Besser R, Basu S, London R, Makaya T, Ryan F, Megson C, Bowen-Morris J, Haest J, Law R, Stamford I, Ghatak A, Deakin M, Phelan K, Thornborough K, Shakeshaft J, Weinzimer S, Cengiz E, Sherr J, Van Name M, Weyman K, Carria L, Steffen A, Zgorski M, Sibayan J, Beck R, Borgman S, Davis J, Rusnak J, Hellman A, Cheng P, Kanapka L, Kollman C, McCarthy C, Chalasani S, Hood K, Hanes S, Viana J, Lanning M, Fox D, Arreaza-Rubin G, Eggerman T, Green N, Janicek R, Gabrielson D, Belle S, Castle J, Green J, Legault L, Willi S, Wysham C. Cambridge hybrid closed-loop algorithm in children and adolescents with type 1 diabetes: a multicentre 6-month randomised controlled trial. The Lancet Digital Health 2022, 4: e245-e255. PMID: 35272971, DOI: 10.1016/s2589-7500(22)00020-6.Peer-Reviewed Original ResearchConceptsClosed-loop groupInsulin pump therapyType 1 diabetesControl groupBaseline HbAUsual carePump therapyClosed-loop insulin deliverySuboptimal glucose controlPediatric diabetes centersKey inclusion criteriaClosed-loop insulin delivery systemPrimary endpointBlock randomisationDiabetes CenterGlucose controlInsulin delivery systemsInclusion criteriaPrimary analysisTherapyInsulin deliveryMonthsG pumpHbADiabetesCongenital hyperinsulinism in infancy and childhood: challenges, unmet needs and the perspective of patients and families
Banerjee I, Raskin J, Arnoux JB, De Leon DD, Weinzimer SA, Hammer M, Kendall DM, Thornton PS. Congenital hyperinsulinism in infancy and childhood: challenges, unmet needs and the perspective of patients and families. Orphanet Journal Of Rare Diseases 2022, 17: 61. PMID: 35183224, PMCID: PMC8858501, DOI: 10.1186/s13023-022-02214-y.Peer-Reviewed Original ResearchConceptsBlood glucose monitoringBetter outcomesUnmet needGlucose monitoringLimited treatment optionsLong-term developmental outcomesPerspectives of patientsCare of newbornsKey clinical challengeAdverse eventsSignificant morbidityPersistent hypoglycemiaTreatment optionsNeurological damageSpecialized careSpecialized centersCommon causeCurrent treatmentClinical challengeCongenital hyperinsulinismEarly diagnosisEffective treatmentNeurocognitive impairmentNew therapiesPatients
2021
Youth and parent preferences for an ideal AP system: It is all about reducing burden
Commissariat PV, Roethke LC, Finnegan JL, Guo Z, Volkening LK, Butler DA, Dassau E, Weinzimer SA, Laffel LM. Youth and parent preferences for an ideal AP system: It is all about reducing burden. Pediatric Diabetes 2021, 22: 1063-1070. PMID: 34324772, PMCID: PMC8530854, DOI: 10.1111/pedi.13252.Peer-Reviewed Original ResearchPredictors of Time-in-Range (70–180 mg/dL) Achieved Using a Closed-Loop Control System
Schoelwer MJ, Kanapka LG, Wadwa RP, Breton MD, Ruedy KJ, Ekhlaspour L, Forlenza GP, Cobry EC, Messer LH, Cengiz E, Jost E, Carria L, Emory E, Hsu LJ, Weinzimer SA, Buckingham BA, Lal RA, Oliveri MC, Kollman CC, Dokken BB, Cherñavvsky DR, Beck RW, DeBoer MD, Gonder-Frederick L, Robic J, Voelmle M, Conschafter K, Morris K, Barnett C, Carr K, Hellmann J, Kime M, Todd Alonso G, Slover R, Berget C, Towers L, Lange S, Buckingham B, Maahs D, Lal R, Ekhlaspour L, Norlander L, Hood K, Town M, Weir C, Smith K, Hsu L, Shinksy D, Viana J, Cengiz E, Weinzimer S, Weyman K, Carria L, Zgorski M, Ruedy K, Beck R, Borgman S, Rusnak J, Kanapka L, Kollman C, Murphy C, Arreza-Rubin G, Green N, Kovatchev B, Brown S, Anderson S, Breton M, Laffel L, Pinsker J, Levy C, Kudva Y, Wadwa R, Buckingham B, Doyle III F, Renard E, Cobelli C, Reznik Y, Arreza-Rubin G, Lum J, Beck R, Ruedy K, Janicek R, Gabrielson D. Predictors of Time-in-Range (70–180 mg/dL) Achieved Using a Closed-Loop Control System. Diabetes Technology & Therapeutics 2021, 23: 475-481. PMID: 33689454, PMCID: PMC8252894, DOI: 10.1089/dia.2020.0646.Peer-Reviewed Original ResearchConceptsGlycemic controlLower TIROptimal glycemic controlType 1 diabetesPredictors of timeGreater improvementClinical characteristicsClinical predictorsFourth quartileMore insulinBody weightGlucose monitor dataExtension phaseMultivariate modelBolusStrongest predictorContinuous glucose monitor dataQuartileInsulinPredictorsChildrenParticipantsT1D.T1DDiabetesImpact of Type 1 Diabetes in the Developing Brain in Children: A Longitudinal Study.
Mauras N, Buckingham B, White NH, Tsalikian E, Weinzimer SA, Jo B, Cato A, Fox LA, Aye T, Arbelaez AM, Hershey T, Tansey M, Tamborlane W, Foland-Ross LC, Shen H, Englert K, Mazaika P, Marzelli M, Reiss AL. Impact of Type 1 Diabetes in the Developing Brain in Children: A Longitudinal Study. Diabetes Care 2021, 44: 983-992. PMID: 33568403, PMCID: PMC7985430, DOI: 10.2337/dc20-2125.Peer-Reviewed Original ResearchConceptsType 1 diabetesBrain volumeControl subjectsTotal brain volume differencesEarly-onset type 1 diabetesAge-matched control subjectsIntelligence quotientCognitive scoresWhite matter volumeBrain volume differencesContinuous glucose monitoringDiabetes groupFull-scale intelligence quotientDiabetes complicationsDiabetes controlTotal brainVerbal intelligence quotientDiabetesMatter volumeSensor glucoseCognitive testingGlucose monitoringMixed-effects modelsBrainGroup differencesInnovative features and functionalities of an artificial pancreas system: What do youth and parents want?
Commissariat PV, Volkening LK, Butler DA, Dassau E, Weinzimer SA, Laffel LM. Innovative features and functionalities of an artificial pancreas system: What do youth and parents want? Diabetic Medicine 2021, 38: e14492. PMID: 33290599, PMCID: PMC9196947, DOI: 10.1111/dme.14492.Peer-Reviewed Original ResearchExtended Use of the Control-IQ Closed-Loop Control System in Children With Type 1 Diabetes.
Kanapka LG, Wadwa RP, Breton MD, Ruedy KJ, Ekhlaspour L, Forlenza GP, Cengiz E, Schoelwer MJ, Jost E, Carria L, Emory E, Hsu LJ, Weinzimer SA, DeBoer MD, Buckingham BA, Oliveri M, Kollman C, Dokken BB, Cherñavvsky D, Beck RW. Extended Use of the Control-IQ Closed-Loop Control System in Children With Type 1 Diabetes. Diabetes Care 2021, 44: 473-478. PMID: 33355258, PMCID: PMC7818334, DOI: 10.2337/dc20-1729.Peer-Reviewed Original ResearchConceptsType 1 diabetesChildren 6Sensor-augmented pump therapyWeeks of useDiabetic ketoacidosisDays of useGlycemic controlSAP groupSevere hypoglycemiaPump therapyClinical trialsPercentage of timeCLC groupMean TIRDiabetesFurther evaluationCohortRCTsDlWeeksChildrenDaysExtended useParticipantsKetoacidosis
2020
Insulin dose optimization using an automated artificial intelligence-based decision support system in youths with type 1 diabetes
Nimri R, Battelino T, Laffel LM, Slover RH, Schatz D, Weinzimer SA, Dovc K, Danne T, Phillip M. Insulin dose optimization using an automated artificial intelligence-based decision support system in youths with type 1 diabetes. Nature Medicine 2020, 26: 1380-1384. PMID: 32908282, DOI: 10.1038/s41591-020-1045-7.Peer-Reviewed Original ResearchConceptsType 1 diabetesInsulin dose adjustmentPhysician armDose adjustmentAcademic diabetes centerInsulin pump settingsPrimary efficacy measureSevere adverse eventsTarget glucose rangeInsulin pump therapyNon-inferiority trialArtificial intelligence-based decision support systemAdverse eventsInsulin titrationDiabetes CenterEfficacy measuresPump therapyPercentage of timePercentage of readingsGlucose levelsSix monthsContinuous glucose monitoring devicesDiabetesInsulin pumpGlucose monitoring devicesA Randomized Trial of Closed-Loop Control in Children with Type 1 Diabetes
Breton MD, Kanapka LG, Beck RW, Ekhlaspour L, Forlenza GP, Cengiz E, Schoelwer M, Ruedy KJ, Jost E, Carria L, Emory E, Hsu LJ, Oliveri M, Kollman CC, Dokken BB, Weinzimer SA, DeBoer MD, Buckingham BA, Cherñavvsky D, Wadwa RP. A Randomized Trial of Closed-Loop Control in Children with Type 1 Diabetes. New England Journal Of Medicine 2020, 383: 836-845. PMID: 32846062, PMCID: PMC7920146, DOI: 10.1056/nejmoa2004736.Peer-Reviewed Original ResearchConceptsType 1 diabetesSensor-augmented insulin pumpClosed-loop groupGlucose levelsMedian percentageTarget rangeInsulin pumpInsulin deliveryParallel-group trialYears of ageContinuous glucose monitoringDiabetic ketoacidosisPrimary outcomeSevere hypoglycemiaHemoglobin levelsRandomized trialsGlycemic outcomesPercentage of timeChildren 6Control groupType 1DiabetesMean percentageGlucose monitoringTrialsBrain Function Differences in Children With Type 1 Diabetes: A Functional MRI Study of Working Memory
Foland-Ross LC, Tong G, Mauras N, Cato A, Aye T, Tansey M, White NH, Weinzimer SA, Englert K, Shen H, Mazaika PK, Reiss AL, Tsalikian E, Tansey M, Coffey J, Cabbage J, Salamat S, Bisbee R, Mauras N, Fox L, Cato A, Englert K, Sikes K, Ewen T, Bird K, Buckingham B, Wilson D, Aye T, Kingman R, Weinzimer S, Tamborlane W, Ambrosino J, Steffen A, Weyman K, Zgorski M, White N, Arbelaez A, Levandoski L, Starnes A, Hershey T, Reiss A, Foland-Ross L, Marzelli M, Mazaika P, Tong G, Sperling M, Becker D, Cleary P, Greenbaum C, Moran A. Brain Function Differences in Children With Type 1 Diabetes: A Functional MRI Study of Working Memory. Diabetes 2020, 69: 1770-1778. PMID: 32471809, PMCID: PMC7372069, DOI: 10.2337/db20-0123.Peer-Reviewed Original ResearchConceptsType 1 diabetesImproved glycemic controlBrain function differencesFunctional MRI studyGreater modulationDiabetes groupGlycemic controlFrontoparietal cortexMRI studiesControl groupDiabetesType 1Functional MRICompensatory mechanismsEarly onsetBrain activationVisuospatial Working Memory TaskChildrenN-back taskMemory functionEarly ageMemory abilityWorking Memory TaskFuture studiesActivation
2018
Impact of Early Diabetic Ketoacidosis on the Developing Brain
Aye T, Mazaika PK, Mauras N, Marzelli MJ, Shen H, Hershey T, Cato A, Weinzimer SA, White NH, Tsalikian E, Jo B, Reiss AL, Group D, Tsalikian E, Tansey M, Coffey J, Cabbage J, Salamati S, Mauras N, Fox L, Cato A, Englert K, Sikes K, Buckingham B, Wilson D, Aye T, Caswell K, Ambers E, Weinzimer S, Tamborlane W, Steffen A, Weyman K, Zgorski M, Ambrosino J, White N, Arbelaez A, Levandoski L, Starnes A, Hershey T, Reiss A, Barnea-Goraly N, Marzelli M, Mazaika P, Peng D, Beck R, Kollman C, Ruedy K, Winer K, Sperling M, Becker D, Cleary P, Greenbaum C, Moran A. Impact of Early Diabetic Ketoacidosis on the Developing Brain. Diabetes Care 2018, 42: dc181405. PMID: 30573652, PMCID: PMC6385695, DOI: 10.2337/dc18-1405.Peer-Reviewed Original ResearchType 1 Diabetes in Children and Adolescents: A Position Statement by the American Diabetes Association
Chiang JL, Maahs DM, Garvey KC, Hood KK, Laffel LM, Weinzimer SA, Wolfsdorf JI, Schatz D. Type 1 Diabetes in Children and Adolescents: A Position Statement by the American Diabetes Association. Diabetes Care 2018, 41: dci180023. PMID: 30093549, PMCID: PMC6105320, DOI: 10.2337/dci18-0023.Peer-Reviewed Original ResearchPredictive Low-Glucose Suspend Reduces Hypoglycemia in Adults, Adolescents, and Children With Type 1 Diabetes in an At-Home Randomized Crossover Study: Results of the PROLOG Trial
Forlenza GP, Li Z, Buckingham BA, Pinsker JE, Cengiz E, Wadwa RP, Ekhlaspour L, Church MM, Weinzimer SA, Jost E, Marcal T, Andre C, Carria L, Swanson V, Lum JW, Kollman C, Woodall W, Beck RW. Predictive Low-Glucose Suspend Reduces Hypoglycemia in Adults, Adolescents, and Children With Type 1 Diabetes in an At-Home Randomized Crossover Study: Results of the PROLOG Trial. Diabetes Care 2018, 41: dc180771. PMID: 30089663, DOI: 10.2337/dc18-0771.Peer-Reviewed Original ResearchConceptsType 1 diabetesSAP armPredictive low glucose suspendSensor-augmented pump therapyNew insulin delivery systemsRandomized Crossover StudySevere hypoglycemic eventsGlucose concentrationMin/dayMean glucose concentrationLow glucose suspendBasal-IQRebound hyperglycemiaSlim X2Glycemic controlPrimary outcomeCrossover studyMedian timeCrossover trialHypoglycemic eventsPump therapyInsulin delivery systemsPercentage of timeHypoglycemiaDiabetes
2016
Altered Integration of Structural Covariance Networks in Young Children With Type 1 Diabetes
Hosseini SM, Mazaika P, Mauras N, Buckingham B, Weinzimer SA, Tsalikian E, White NH, Reiss AL, Network F. Altered Integration of Structural Covariance Networks in Young Children With Type 1 Diabetes. Human Brain Mapping 2016, 37: 4034-4046. PMID: 27339089, PMCID: PMC5053865, DOI: 10.1002/hbm.23293.Peer-Reviewed Original ResearchConceptsEarly-onset T1DStructural covariance networksYoung childrenNeurocognitive deficitsType 1 diabetes mellitusCovariance networksBrain networksFrequent chronic diseasesHum Brain MappRegional gray matterGlycemic controlDiabetes mellitusGlucose dysregulationNeural insultsHealthy controlsLarge-scale brain networksChronic diseasesBulk of evidenceNeuroanatomical changesT1DWhite matterGray matterBrain developmentGraph theoretical analysisT1D.Compensatory Hyperconnectivity in Developing Brains of Young Children With Type 1 Diabetes
Saggar M, Tsalikian E, Mauras N, Mazaika P, White NH, Weinzimer S, Buckingham B, Hershey T, Reiss AL. Compensatory Hyperconnectivity in Developing Brains of Young Children With Type 1 Diabetes. Diabetes 2016, 66: 754-762. PMID: 27702833, PMCID: PMC5319714, DOI: 10.2337/db16-0414.Peer-Reviewed Original ResearchConceptsControl subjectsIntrinsic connectivityAge-matched control subjectsYoung childrenBrain intrinsic connectivityResting-state functional MRI dataType 1 diabetesSeed-based analysisCognitive functioningBlood glucoseSustained dysregulationOverall group differencesLarge multisite studyT1DYounger ageFunctional MRI dataCognitive deficitsType 1Cognitive functionObserved positive associationDiabetesMultisite studyCompensatory roleGroup differencesBrain
2015
Variations in Brain Volume and Growth in Young Children With Type 1 Diabetes
Mazaika PK, Weinzimer SA, Mauras N, Buckingham B, White NH, Tsalikian E, Hershey T, Cato A, Aye T, Fox L, Wilson DM, Tansey MJ, Tamborlane W, Peng D, Raman M, Marzelli M, Reiss AL. Variations in Brain Volume and Growth in Young Children With Type 1 Diabetes. Diabetes 2015, 65: 476-485. PMID: 26512024, PMCID: PMC4747456, DOI: 10.2337/db15-1242.Peer-Reviewed Original ResearchConceptsEarly-onset type 1 diabetesType 1 diabetesBlood glucose levelsWhite matter volumeGlucose levelsMatter volumeTime pointsBrain volumeAge-matched control subjectsCortical gray matter volumeMeasures of hyperglycemiaMean HbA1c levelCurrent treatment guidelinesManagement of diabetesRapid brain maturationGray matter volumeTime of scanCortical surface areaHbA1c levelsTreatment guidelinesControl subjectsGlycemic variationsLongitudinal time pointsBrain maturationDiabetes
2014
Longitudinal Assessment of Neuroanatomical and Cognitive Differences in Young Children With Type 1 Diabetes: Association With Hyperglycemia
Mauras N, Mazaika P, Buckingham B, Weinzimer S, White NH, Tsalikian E, Hershey T, Cato A, Cheng P, Kollman C, Beck RW, Ruedy K, Aye T, Fox L, Arbelaez AM, Wilson D, Tansey M, Tamborlane W, Peng D, Marzelli M, Winer KK, Reiss AL. Longitudinal Assessment of Neuroanatomical and Cognitive Differences in Young Children With Type 1 Diabetes: Association With Hyperglycemia. Diabetes 2014, 64: 1770-1779. PMID: 25488901, PMCID: PMC4407847, DOI: 10.2337/db14-1445.Peer-Reviewed Original ResearchConceptsWhite matter growthControl subjectsAge-matched control subjectsType 1 diabetesHigh-resolution structural MRIWhite matter areasWhite matter volumeYoung childrenContinuous glucose monitoringGray matter regionsNondiabetic childrenChronic hyperglycemiaExecutive function scoresFunction scoresGlucose variabilityMatter volumeChildren ages 4Comprehensive neurocognitive testsBrain regionsLongitudinal assessmentType 1Structural MRIHyperglycemiaDiabetesMatter regions