MultinationalHomeUse ofClosed-Loop Control Is Safe and EffectiveDiabetes Care 2016;39:1143–1150 | DOI: 10.2337/dc15-2468

OBJECTIVE

To evaluate the efficacy of a portable, wearable, wireless artificial pancreas sys-tem (the Diabetes Assistant [DiAs] running the Unified Safety System) on glucosecontrol at home in overnight-only and 24/7 closed-loop control (CLC) modes inpatients with type 1 diabetes.

RESEARCH DESIGN AND METHODS

At six clinical centers in four countries, 30 participants 18–66 years old with type 1diabetes (43% female, 96% non-Hispanic white, median type 1 diabetes duration19 years, median A1C 7.3%) completed the study. The protocol included a 2-weekbaseline sensor-augmented pump (SAP) period followed by 2 weeks of overnight-only CLC and 2 weeks of 24/7 CLC at home. Glucose control during CLC wascompared with the baseline SAP.

RESULTS

Glycemic control parameters for overnight-only CLCwere improved during the night-time period comparedwith baseline for hypoglycemia (time<70mg/dL, primary endpoint median 1.1% vs. 3.0%; P < 0.001), time in target (70–180 mg/dL: 75% vs. 61%;P < 0.001), and glucose variability (coefficient of variation: 30% vs. 36%; P < 0.001).Similar improvements for day/night combined were observed with 24/7 CLC com-pared with baseline: 1.7% vs. 4.1%, P < 0.001; 73% vs. 65%, P < 0.001; and 34% vs.38%, P < 0.001, respectively.

CONCLUSIONS

CLC running ona smartphone (DiAs) in the home environmentwas safe and effective.Overnight-only CLC reduced hypoglycemia and increased time in range overnight andincreased time in range during the day; 24/7 CLC reduced hypoglycemia and in-creased time in range both overnight and during the day. Compared with over-night-only CLC, 24/7 CLCprovided additional hypoglycemiaprotection during theday.

In the past decade, the diabetes community has seen unprecedented advances inartificial pancreas (AP) technology, which moved from short-term inpatient studiesto long-term trials at home using wireless, portable, wearable AP systems. A com-prehensive review of the early developments in the AP field and of the first inpatientclosed-loop control (CLC) studies can be found in a Perspectives in Diabetes articleby Cobelli, Renard, and Kovatchev (1), and several recent reviews highlight addi-tional progress in this field (2–6). A notable achievement in AP technology was theintroduction of the first portable, wearable AP platformdthe Diabetes Assistant(DiAs) (7)ddeveloped by our group at the University of Virginia (UVA) and firsttested in outpatient trials in Italy and in France in October 2011 (8). DiAs was builtusing an Android smart phone as a computational hub and included an AP graphical

1University of Virginia, Charlottesville, VA2Jaeb Center for Health Research, Tampa, FL3WilliamSansumDiabetesCenter, SantaBarbara,CA4University of Padova, Padova, Italy5Department of Endocrinology, Diabetes, andNutrition and INSERM1411 Clinical InvestigationCenter, Montpellier University Hospital, andUMR CNRS 5203/INSERM U1191, Institute ofFunctional Genomics, University of Montpellier,Montpellier, France6Division of Pediatric Endocrinology and Diabe-tes, Department of Pediatrics, Stanford Univer-sity School of Medicine, Stanford, CA7Jesse Z and Sara Lea Shafer Institute of Endo-crinology and Diabetes, National Center forChildhood Diabetes, Schneider Children’s Medi-cal Center of Israel, and Sackler Faculty of Med-icine, Tel Aviv University, Petah Tikva, Israel8Department of Chemical Engineering, Universityof California, Santa Barbara, Santa Barbara, CA9Harvard John A. Paulson School of Engineering andApplied Sciences,HarvardUniversity, Cambridge,MA10TypeZero Technologies, LLC, Charlottesville, VA

Corresponding author: Roy W. Beck, rbeck@jaeb.org.

Received 13 November 2015 and accepted 16March 2016.

Clinical trial reg. no.NCT02137512, clinicaltrials.gov.

This article contains Supplementary Data onlineat http://care.diabetesjournals.org/lookup/suppl/doi:10.2337/dc15-2468/-/DC1.

*A full listing of the members of the Control toRange Study Group is included in the APPENDIX.

© 2016 by the American Diabetes Association.Readersmayuse this article as longas thework isproperly cited, the use is educational and not forprofit, and the work is not altered.

See accompanying articles, pp. 1123,1127, 1135, 1151, 1161, 1168, 1175,and 1180.

Stacey M. Anderson,1 Dan Raghinaru,2

Jordan E. Pinsker,3 Federico Boscari,4

Eric Renard,5 Bruce A. Buckingham,6

Revital Nimri,7 Francis J. Doyle III,8,9

Sue A. Brown,1 Patrick Keith-Hynes,1,10

Marc D. Breton,1 Daniel Chernavvsky,1

Wendy C. Bevier,3 Paige K. Bradley,3

Daniela Bruttomesso,4 Simone Del Favero,4

Roberta Calore,4 Claudio Cobelli,4

AngeloAvogaro,4 Anne Farret,5 JeromePlace,5

Trang T. Ly,6 Satya Shanmugham,6

Moshe Phillip,7 Eyal Dassau,8,9

Isuru S. Dasanayake,8 Craig Kollman,2

John W. Lum,2 Roy W. Beck,2 and

Boris Kovatchev,1 for the Control to Range

Study Group*

Diabetes Care Volume 39, July 2016 1143

ARTIFIC

IALPANCREA

S

user interface designed for the patient (9)and a web-based remote monitoring sys-tem for use by the study team (10). Thedefining characteristic of DiAs is its capa-bility to switch between different modesof operation, depending on patient pref-erence and signal availability (7,9).Using DiAs as the medical platform,

we previously tested and validated twomodular closed-loop algorithms (theUnified Safety System [USS], developedat UVA, and the Modular Model Predic-tive Control, developed by the interna-tional AP study group) in gradually lessstructured and less monitored settings,following a pathway to achieve eventualregulatory approval (11). This pathwayincluded several feasibility and safetytrials in hotel settings (8,12,13), summercamp studies testing DiAs in childrenwith diabetes (14,15), and the recentlycompleted overnight (16) and 42-hdinner-overnight (17) trials of CLC athome. Here, we describe the first longer-term use of DiAs–USS Virginia at homeusing a completely wireless and portable,wearable AP system. The goal of this studywas to provide safety and efficacy data forthe DiAs–USS Virginia AP system in thehome environment with the aim of sup-porting preliminary data for the nextstep in the development pathwaydalarge-scale clinical trial to establish CLCas a viable treatment modality for type 1diabetes.

RESEARCH DESIGN AND METHODS

The protocol, conducted at six clinicalcenters in the U.S., Italy, France, and Israel,was approved by each institutional orindependent review board, and writ-ten informed consent was obtainedfrom each participant. An independentData and Safety Monitoring Boardprovided oversight. The study is listed onwww.clinicaltrials.gov (clinical trial reg.no. NCT02137512). Details of the proto-col are available online (http://www.clinicaltrials.gov/ct2/show/NCT02137512);key aspects are summarized herein.Major eligibility criteria included age

18–69 years, type 1 diabetes duration ofat least 1 year, use of an insulin pump forat least 6 months, A1C,10.0%, continu-ous access to internet, cell phone service,and a computer at home. Additional eli-gibility criteria included commitmentfrom a companion living with the partici-pant to take part in all training activities,to be knowledgeable of the participant’s

location at all times, and to be availableto provide assistance when the systemwas used at night. Exclusions includeddiabetic ketoacidosis or severehypoglyce-mia with seizure or loss of consciousnessin the prior 12 months and hypoglycemiaunawareness defined as a score of $3on a 0–7 scale by a Clarke HypoglycemiaUnawareness Questionnaire. Other exclu-sions included the presence of one of avariety of medical conditions, laboratoryabnormalities, or medications that wereconsidered to affect study participation.

Closed-Loop SystemThe CLC system included the followingcomponents: 1) DiAs, a smart-phonemedical platform; 2) Dexcom G4 Platinumconnected to DiAs via continuous glucosemonitor (CGM) receiver andUSB-Bluetoothrelay hardware (SmartLoop LLC; New York,NY); 3) Roche Accu-Chek insulin pumpconnected to DiAs via wireless Blue-tooth; 4) remote monitoring server con-nected to DiAs via 3G or local Wi-Finetwork; and 5) modular CLC algorithmrunning on DiAs, which is of control-to-range class.

In this trial, DiAs operated in the fol-lowing modes.

Sensor-Only Mode

This is the default mode any time theDiAs is connected with a CGM but hasno connection with the insulin pump. Inthis mode, the pump operates in itsstandard open-loop (OL) manner whileDiAs provides hypo- and hyperglycemiaalerts implemented as traffic-light sig-nals (green/yellow/red light) (9) anddata transfer to a server for remotemonitoring and diagnostics (10).

Pump Mode or OL Control Mode

In this mode, the DiAs control algo-rithms are not active, and the systemdelivers the normal basal rates as pro-grammed in the DiAs insulin profile set-tings. Pump mode also tracks insulin onboard and allows the user to issue mealand correction boluses. If DiAs loses com-munication with the pump, DiAs will re-vert to either sensor-only mode (if a CGMis connected) or stopped mode (if noCGM is connected) and the insulinpumpwill revert to the patient’s preprog-rammed basal rates within 30 min.

CLC Mode

The algorithms deployed in the USS Vir-ginia use a modular architecture (18,19)composed of the safety supervision (20),

hyperglycemia mitigation, and basalrate modules. Insulin corrections are ad-ministered by the hyperglycemia mitiga-tionmodule if glucose levels are predictedto exceed the upper limit of a presetglucose range, e.g., 180 mg/dL, and themodule is designed to maintain glucosebetween 70 and 180 mg/dL during theday. The basal ratemodule is designed toslide its glucose target from 160 mg/dLduring the daytime down to 120 mg/dLby wake-up time in the morning (15,16).The system uses as a base the patient’sunderlying insulin pump parameters.Meals are announced using the DiAsmeal screen (9), and uponmeal announce-ment the system recommends premealboluses.

Safety Mode

This is a variant of CLC mode in whichonly the safety supervision module (20)is active so that the system can reduceinsulin to prevent hypoglycemia butcannot exceed OL basal insulin delivery.Per protocol, this mode was to be usedwhenever the participant was driving,exercising, or performing any poten-tially dangerous activity.

Participants were asked to remain inCLC whenever feasible and permitted byprotocol but were able to switch topump or sensor mode as needed. Partic-ipants were instructed to perform fin-gerstick blood glucose checks afterhypo- or hyperglycemia red light alertsand to treat with carbohydrate or correc-tive insulin as specified in a participantuser guide. Manual correction boluses inthe absence of any traffic light alertswerepermitted, but participants were encour-aged to rely on automated insulin dosingwhenever feasible. Home use of the sys-tem included all the activities of normaldaily living, including eating, going towork, sleeping, exercising, etc.

Study ProtocolDepending on the participant’s currentexperience with CGM use (17 of the 30enrolled were active CGM users at en-rollment), the participant initially spent0–3 weeks using CGM at home followedby a 2-week period at home using boththe study pump and CGM. This 2-weekperiod of sensor-augmented pump(SAP) therapy at home was consideredthe baseline period to be comparedwiththe 2 weeks of overnight-only CLC sys-tem use and 2 weeks of a 24 h per dayand 7 days per week (24/7) CLC system

1144 Multinational Home Closed-Loop Control Diabetes Care Volume 39, July 2016

use at home. After this baseline SAP pe-riod, participants and study companionscompleted a 12-h training session withthe DiAs system in OL control (OLC)mode in either a clinical or transitionalnonclinical setting. The participant pro-ceeded to use the DiAs in OLC modefor a 1-week period at home. Upon com-pletion, the participant and companionreturned to the clinic or transitionalnonclinical setting such as a hotel for a48-h training session of use of the DiAsin CLC and safety modes. The partici-pants then completed 3–5 days of trialuse of DiAs in overnight-only CLC fol-lowed by 2 weeks of overnight-only CLCuse at home, a 3- to 5-day trial period ofDiAs in 24/7 CLC mode, and 2 weeks of24/7 CLC use at home. During the periodsof at-home CLC use, remote safety mon-itoring was available to clinical staff whofollowed specific guidelines for interven-ing and contacting a participant or com-panion should there be a technical issueor safety concern. As an additional safetyprecaution, participants also were con-tacted daily by study staff during the 3-to 5-day trial periods of CLC use at home.Adverse event reporting included any

untoward medical occurrence or unex-pected occurrence in a study participantincluding severe hypoglycemia (whichwas defined as an event that requiredassistance of another person to adminis-ter oral carbohydrate, glucagon, or otherresuscitative actions), hyperglycemia re-sulting in ketoacidosis, and any study ordevice-related event.

Statistical MethodsThe primary outcome was CGM sensorglucose percent time,70 mg/dL, whichwas computed separately for each ofthe three 2-week study phases. Thetwo primary comparisons were thechange from baseline in the percenttime ,70 mg/dL during overnight-onlyCLC and during 24/7 CLC. A sample sizeof N = 30 participants was estimated toprovide;85% power to detect a 33% re-duction in the percent time ,70 mg/dLduring the 24/7 CLC compared with base-line SAP, assuming a two-tailed pairedt test and a type I error of 5%.Safety and basic system performance

analyses included all participants. Effi-cacy glycemic analyses excluded oneparticipant for whom baseline datawere unavailable due to a broken CGMreceiver, leaving N = 29 included in

analysis. Similarly, insulin analyses ex-cluded one participant for whom base-line pump data were lost, leaving N = 29included in analysis. Downloaded CGMreadings during times when DiAs wasinactive or not receiving data duringthe overnight CLC (7% of the totaldata) and 24/7 CLC (4% of the totaldata) were excluded from the analysis(results were similar when using allCGM receiver data from the two CLCphases). Paired t tests for normally dis-tributed metrics or the signed-rank testfor skewed distributions were used tocompare baseline versus overnight-only CLC and baseline SAP versus 24/7CLC overall and separately by daytime(0700–2300 h) and nighttime (2300–0700 h).Paired t tests to compare overnight-onlyCLC versus 24/7 CLC were added as posthoc analyses.

No adjustment was made for multiplecomparisons. All P values are two tailed,and analyses were performed using SAS9.4 software.

RESULTS

Characteristics of the 30 participantswere as follows: median age 44 years(ranged 18–66), 57%male, 96%Caucasian,median BMI 25 kg/m2 (interquartile range[IQR] 23, 27), median type 1 diabetesduration 19 years (IQR 13, 28), mediantotal daily units of insulin per kg 0.57 (IQR0.42, 0.72), and median A1C 7.3% (IQR7.1, 7.7) (Supplementary Table 1). All par-ticipants completed the full 2 weeks ofboth the overnight-only and 24/7 phases.

Nighttime (2300–0700 h) sensor glu-cose metrics were significantly improvedduring overnight-only CLC comparedwithbaseline. Median time ,70 mg/dL drop-ped from 3.0% during baseline to 1.1%during overnight-only CLC (P , 0.001)(Table 1 and Fig. 1); median time in tar-get, 70–180 mg/dL, increased from 61 to75% (P , 0.001); median time .180mg/dL dropped from 37 to 24% (P ,0.001); mean glucose dropped from 163to 150 mg/dL (P = 0.002) (Fig. 2); andmedian coefficient of variation droppedfrom 36 to 30% (P , 0.001). Sensor glu-cose metrics (day and night pooled) alsowere improvedduring the24/7 CLCphasecompared with baseline SAP. Mediantime,70 mg/dL dropped from 4.1% dur-ing baseline SAP to 1.7% during 24/7 CLC(P , 0.001) (Table 1 and Figs. 1 and 3),median time in target 70–180 mg/dLincreased from 65 to 73% (P , 0.001),

median time .180 mg/dL dropped from32 to 25% (P = 0.001), and median coef-ficient of variation dropped from 38 to34% (P , 0.001). Mean glucose was notsignificantly different (157 vs. 153 mg/dL;P = 0.14). Daytime hypoglycemia, time inrange, hyperglycemia, and coefficient ofvariation also were improved during 24/7CLC (P # 0.02) (Table 1). Results forother glucose metrics are shown inSupplementary Table 2.

Similarly, nighttime sensor glucosemetrics were significantly improved dur-ing the 24/7 CLC phase compared withbaseline SAP. Nighttime median time,70 mg/dL dropped from 3.0% duringbaseline to 0.4% during 24/7 CLC (P ,0.001) (Table 1 and Fig. 1); median timein target, 70–180 mg/dL, increased from61 to 72% (P , 0.001); median time.180 mg/dL dropped from 37 to 27%(P , 0.001); mean glucose droppedfrom 163 to 154 mg/dL (P = 0.03) (Fig.2); and median coefficient of variationdropped from 36 to 32%; (P , 0.001).

Trends toward improved time inrange 70–180 mg/dL were observedeven for participants who already hadgood control ($65% in range) at base-line (Fig. 3, Supplementary Table 3, andSupplementary Fig. 1). Among the 14participants with baseline time in range$65%, the median improvement foroverall daytime and nighttime was 5%during overnight-only CLC and 2% dur-ing 24/7 CLC. Corresponding median im-provements for the 15 participants withbaseline time in range ,65% were 12%and 13%, respectively.

In a post hoc analysis, daytime mediantime,70 mg/dL, which was 3.2% duringovernight-only CLC, was further reducedto 2.3% during 24/7 CLC (P, 0.001) (Ta-ble 1 and Figs. 1 and 2). Daytime meanglucose; median time in target, 70–180mg/dL; and median time .180 mg/dLwere not significantly different (P = 0.07,0.49, and 0.61 respectively) comparing24/7 CLC and overnight-only CLC.

For nighttime only, the median totaldelivered insulin was 1.26 units/h (IQR1.04, 1.61) during baseline SAP, 1.28units/h (IQR 0.95, 1.59) during over-night-only CLC, and 1.23 units/h (IQR0.94, 1.75) during 24/7 CLC. For overalldaytime and nighttime, themedian totaldelivered insulin was 1.78 units/h (IQR1.56, 2.07), 1.74 units/h (IQR 1.53, 2.22),and 1.83 units/h (IQR 1.46, 2.38), re-spectively (Supplementary Fig. 2).

care.diabetesjournals.org Anderson and Associates 1145

There were no cases of severe hypo-glycemia, diabetic ketoacidosis, or otherserious adverse events during the trial.

The system performed well in termsof connectivity with the CGM sensor anddelivery of recommended amounts ofinsulin (Supplementary Table 4), al-though participants were instructed onhow to reconnect devices to the DiAs, asthis was needed on some occasions.

At the conclusion of the study, partici-pants completed a questionnaire regard-ing their experience with the DiAs–USSVirginia. In general, the experience wasreported as positive. Suggestions for im-provements or enhancements in the sys-tem are summarized in SupplementaryAppendix A.

CONCLUSIONS

In this study, we demonstrated that glu-cose control was significantly improvedduring both overnight-only and 24/7CLC compared with baseline SAP. Inthe overnight period, this includedboth an increased time in range and areduction in hypoglycemia. The controlstrategy of tightening the glucose targetovernight from a starting point of160 mg/dL down to 120 mg/dL 3 h laterensures that the algorithm is less ag-gressive when the effect of insulin is an-ticipated to be greatest overnight andmore aggressive once steady state isachieved and the insulin resistance as-sociated with the dawn phenomenon isoccurring (16). Hence, even though par-ticipants received more insulin between0100 and 0500 h during CLC relativeto baseline SAP, it was dosed in a mannerthat reduced hyperglycemia but did not sig-nificantly contribute to hypoglycemia.

The inclusion of 2 weeks each of over-night-only CLC and 24/7 CLC interven-tions allowed us to assess whetherthere was an incremental benefit to us-ing the closed-loop system 24/7 versusduring the overnight period alone. De-spite the challenges of normal daily liv-ing, overnight-only and 24/7 CLC wereboth superior to SAP in terms of glucosetime in range during the day and over24 h. While many early adopters of aclosed-loop system will use the system24/7, we envision that there will beothers who will prefer to use the systemonly at night. Hence, it is clinically rele-vant that overnight-only CLC providedbenefit in overall glycemia, not only inthe overnight period when algorithmic

Table

1—Effica

cyandsa

fety

outcomes(N

=29participants*)

Overall(day

andnight)

Nightonly(230

0–07

00h)

Day

only(070

0–23

00h)

Baseline

Overnight-onlyCLC

24/7

CLC

Baseline

Overnight-onlyCLC

24/7

CLC

Baseline

Overnight-onlyCLC

24/7

CLC

Totalsen

sorhours,m

edian*

335

336

336

115

113

112

217

219

218

Timespen

t,70

mg/dL,%,m

edian(IQR)

4.1(2.0,7

.8)

2.6(1.6,3

.6)

1.7(1.1,2

.7)

3.0(1.1,6

.3)

1.1(0.2,1

.6)

0.4(0.2,1

.7)

4.6(2.0,7

.0)

3.2(2.1,4

.6)

2.3(1.3,3

.0)

Pvs.baseline

NA

0.002

,0.001

NA

,0.00

1,0.001

NA

0.10

,0.001

Pvs.nightCLC†

NA

NA

,0.001

NA

NA

0.31

NA

NA

,0.001

Timein

range

70–18

0mg/dL,%,m

edian(IQR)

65(59,

69)

73(65,

78)

73(68,

76)

61(53,

73)

75(69,

80)

72(65,

80)

65(61,

71)

70(65,

77)

72(69,

78)

Pvs.baseline

NA

,0.001

,0.001

NA

,0.00

1,0.001

NA

0.001

,0.001

Pvs.nightCLC†

NA

NA

0.91

NA

NA

0.20

NA

NA

0.49

Sensorglucose,m

g/dL,mean6

SD15

76

1814

96

1215

36

1216

36

2315

06

1215

46

1315

46

1914

86

1515

26

14Pvs.baseline

NA

0.009

0.14

NA

0.00

20.03

NA

0.07

0.54

Pvs.nightCLC†

NA

NA

0.06

NA

NA

0.18

NA

NA

0.07

Glucose

coefficien

tofvariation,%,m

edian(IQR)

38(34,

41)

35(33,

37)

34(31,

37)

36(32,

40)

30(29,

34)

32(27,

36)

38(34,

42)

37(34,

39)

35(31,

37)

Pvs.baseline

NA

0.005

,0.001

NA

,0.00

1,0.001

NA

0.13

,0.001

Pvs.nightCLC†

NA

NA

0.02

NA

NA

0.52

NA

NA

,0.001

SD,m

g/dL,med

ian(IQR)

61(53,

69)

52(48,

58)

51(47,

55)

61(50,

69)

47(42,

51)

48(40,

58)

58(53,

65)

55(49,

60)

53(47,

54)

Pvs.baseline

NA

,0.001

,0.001

NA

,0.00

1,0.001

NA

0.02

,0.001

Pvs.nightCLC†

NA

NA

0.41

NA

NA

0.12

NA

NA

0.06

Timespen

t.18

0mg/dL,%,m

edian(IQR)

32(25,

36)

24(20,

31)

25(22,

28)

37(24,

45)

24(19,

28)

27(19,

34)

31(23,

35)

23(19,

32)

25(21,

29)

Pvs.baseline

NA

,0.001

0.001

NA

,0.00

1,0.001

NA

0.02

0.02

Pvs.nightCLC†

NA

NA

0.26

NA

NA

0.11

NA

NA

0.61

NA,n

otapplicab

le.*O

neparticipan

twas

excluded

dueto

missingbaselineCGM

data.†Po

sthoccomparisonofovernight-onlyCLC

vs.24

/7CLC.

1146 Multinational Home Closed-Loop Control Diabetes Care Volume 39, July 2016

insulin modulation and predictive alertswere active, but also the following daywhen the user was back in OLC mode.The majority of this effect occurred inthe morning hours (i.e., 0700–1100 h),likely the result of an improved fastingglucose value prior to breakfast insulindosing and perhaps also improved con-trol of hepatic glucose output afterovernight CLC use. Alternatively, someof the improvement might have comefrom the user being more engagedwith DiAs than with SAPdi.e., monitor-ing DiAs more closely than traditionalSAP sensor and pump. In the currentstudy for the overnight-only CLC arm,DiAs was manually switched to CLC atbedtime and the system automaticallyreverted to OLC mode at 0700 h for OLtherapy during the day. This contrastswith the methodology of Brown et al.(16) and Kropff et al. (21) who usedDiAs–USS Virginia for overnight-onlyCLC and then transitioned to the Accu-Chek Spirit Combo plus Dexcom G4 Plat-inum (without DiAs) for OLC during theday. These investigators also observedimproved daytime and 24-h glucosecontrol with the overnight-only CLCsystem compared with SAP despite theabsence of DiAs for OLC during theday, suggesting that there may be ben-eficial physiologic effects imparted by

overnight CLC that are independentfrom any additional benefit of the DiAsplatform. Indeed, other investigatorsusing overnight-only CLC have reportedsimilar results. Thabit et al. (22) re-ported a beneficial effect from overnight-only CLC use in children and adolescentsthat extended over the full 24-h period,and Hovorka et al. (23) found that overnight-only CLC resulted in lower glucose levelsfor 3.5 h after stopping CLC. The longesthome study that demonstrated this car-ryover effect was performed by Nimriet al. (24) using MD-Logic overnight-only CLC for 6 weeks and showing a10 mg/dL reduction in the averagedaytime glucose levels with signifi-cantly lower insulin levels comparedwith SAP.

Similar to our results, other groupsusing overnight-only CLC comparedwith SAP at home have demonstratedincreased time in range and reducedtime in hypoglycemia in the overnightperiod (16,21–24). In contrast to theadult-only population of the currentstudy, three of these investigations in-cluded both adolescents and adultswith type 1 diabetes (22–24). Bihormo-nal 24/7 CLC was evaluated in an inpa-tient facility as well as a diabetes campsetting for three consecutive nightswhere participants were randomized

to different sequences of single-hormoneCLC, bihormonal CLC, and conven-tional insulin pump therapy (i.e., OLC)(25–27). Bihormonal CLC resulted incomparable time in euglycemia com-pared with single-hormone CLC andless time spent in hypoglycemia (,4.0mmol/L or 72 mg/dL) compared withOL and single-hormone CLC (25–27).Leelarathna et al. (28) evaluated 8days of SAP or CLC insulin delivery inrandom order in 17 adults with type 1diabetes. During the home phase, thepercentage of time with glucose in thetarget range was significantly higherduring CLC compared with SAP. How-ever, contrary to the current study,time spent below target was compara-ble between 24/7 CLC and SAP. Possibledifferences likely come from the algo-rithm designdin our case, the algo-rithm is equipped with a dedicatedsafety system specifically responsiblefor the prevention of hypoglycemia.

In the current study, hypoglycemia,70 mg/dL was reduced in the over-night period by overnight-only CLC andin both the day and night periods by24/7 CLC compared with SAP. However,overnight-only CLC did not reduce hypo-glycemia ,70 mg/dL during the daywhen the control algorithms were inac-tive. Hence, 24/7 closed loop offers an

Figure 1—Time,70 mg/dL (A), between 70 and 180 mg/dL (B), and.180 mg/dL (D) and mean glucose (C) by study phase. Bottom and top of eachbox denote the 25th and 75th percentile, respectively; the horizontal line inside each box denotes themedian, and the dot denotes themean. N = 29participants; 1 participant was excluded owing to missing baseline CGM data. Night CLC, overnight-only CLC.

care.diabetesjournals.org Anderson and Associates 1147

additional benefit of hypoglycemia pro-tection during times of system use duringthe day. Hyperglycemia defined as timespent .180 mg/dL was reduced both atnight and during the day by both over-night-only and 24/7 CLC compared withSAP. Although a significant reduction indaytime hyperglycemia was seen withCLC, daytime meal challenges continueto be an obstacle for tight daytime glu-cose control with CLC. This is not unex-pected given the mismatch in insulinactivity and meal carbohydrate absorp-tion with the current insulin analogs.The home environment provided typi-

cal daily challenges of real-life. Some ofthe predicted distractions included workand school schedules, children, travel,and a variety of meal and exercise sched-ules. However, certain aspects of thefunctionality and performance of the sys-tem in the home environment were notpredictable at the outset, such as how thesystem would perform when changingfrom Wi-Fi to 3G, during daylight saving

time, or when system anomalies causedunexpected date and time changes. In thecase of the DiAs–USS Virginia, fail-safemodes allowed the insulin pump to inde-pendently resume preprogrammed basalrates in the event of any failure of theDiAs or the control modules and an alertwas sent to a physician.

One of themajor differences betweenthis trial and many previous outpatientinvestigations of CLC is that the systemused was completely portable and wire-less, giving participants freedom to carryon their normal activities. Full wirelessconnectivity will continue to be an im-portant feature of CLC, as the equip-ment burden without it would bemuch more cumbersome to the userand may limit applications of use. Fortu-nately, additional rapid advancementsin the CGM field have occurred in thepast year and the Dexcom G5 transmit-ter will be able to directly communicatewith a cell phone for future iterations ofDiAs-AP systems.

As part of a multinational, multicenterstudy, we tested our system in a diversegroup of patients with type 1 diabetesover a wide range of ages, duration ofdiabetes, baseline A1C, BMI, total dailyinsulin, and eating schedules (e.g., Euro-pean vs. American mealtimes) and dem-onstrated that the system is safe andeffective across borders. Baseline A1Cwas reasonably good (median 7.3%);hence, extrapolation of these results topopulations with suboptimal control isnot possible. Since our hybrid AP systemis initialized with the participant’s base-line pump parameters, only participantswho were actively using predefinedpump parameters were eligible. By de-sign, participants with A1C $10% wereexcluded, as poor baseline diabetes con-trol may be indicative of either noncom-pliance with the present insulin pumptherapy or problematic pump settingsat baseline. Adaptive AP systems andAP systems using an initial optimizationof the pump parameters may be less de-pendent on baseline pump parametersand allow for participation of individualswith initial A1C.10%. For those peoplewith baseline A1C of ;7%, a threefoldreduction in hypoglycemia offers asafety layer and reassurance, whileautomated insulin delivery may allevi-ate the psychological burden of inten-sive treatment. In general, patients ingood control would be one of the sub-groups to benefit most from CLC owingto its power to reduce hypoglycemiawithout compromising A1C. For thosewith higher baseline A1C values, the APsystem should aim to reduce A1C with-out increasing the occurrence of hypo-glycemia. Both of these populationsare being studied in an upcoming largetrial.

Since this was the first use of DiAs–USS Virginia outside of a research setting,safety measures included self-monitoringof blood glucose (SMBG) testing seventimes daily and the inclusion of onlythose participants with preserved hypo-glycemia awareness. The imposed fin-gerstick schedule may have resulted inincreased postprandial insulin correctiondosing above baseline, although thiswould be anticipated to be similar inboth the control and experimentalarms, as the fingerstick schedule wassimilar in each. Future studies shouldnot impose this type of monitoringschedule, as current CGM technology is

Figure 2—Twenty-four-hour CGM sensor glucose comparing baseline with overnight-only CLC (A) and24/7 CLC (B). N = 29 participants; 1 participant was excluded owing to missing baseline CGM data.Bottom and top curves denote the 25th and 75th percentile, respectively, and the curves with dots ortriangles denote the median. As seen in the two dashed-line rectangles, 24/7 CLC (B) consistentlyimproveddaytimehypoglycemia frombaseline comparedwithovernight-onlyCLC (B comparedwithA).

1148 Multinational Home Closed-Loop Control Diabetes Care Volume 39, July 2016

sufficiently accurate to catch impendinghypo- and hyperglycemia events, andthe Dexcom G5 Mobile has alreadyachieved a replacement claim in Europe.Additionally, patients using AP systemsat home are not likely to continuewith this degree of SMBG testing inthe long run. AP systems should be eval-uated for performance using the mini-mum number of SMBG tests required tomaintain CGM calibration, as this willlikely be the fewest SMBG tests em-ployed by users of commercial AP sys-tems at home.A limitation of the current study is the

lack of a randomized crossover design ofSAP, overnight-only CLC, and 24/7 CLC.However, the primary goal was to pro-vide evidence of the safety and efficacyof such a wireless and portable systemin the home environment. The futureplanned large-scale trial will use a ran-domized parallel-group design poweredfor A1C reduction.In conclusion, use of a completely por-

table andwireless hybrid AP system in thehome environment increases time inrange and reduces hypoglycemia whenthe closed-loop system is active. Longerstudies are needed to further establishsafety, clinical outcomes over time, us-ability, and system adaptation. Addi-tional studies in children, those withhypoglycemia unawareness, and those

with suboptimal control are presentlyongoing.

Acknowledgments. The authors thank StephenPatek (Department of Systems & InformationEngineering, University of Virginia) for his contribu-tion to the design of the control algorithm used inthe study, and the authors recognize the efforts ofthe participants and their families and thank them.Funding. This project was supported by grantsfrom the JDRF (22-2011-649 and 17-2013-509).CGMs and sensors were purchased at a bulkdiscount price from Dexcom (San Diego, CA).Insulin pumps and home glucose meters wereprovided to the study by Roche Diabetes Care,Inc. (Indianapolis, IN). Home ketone meters andtest strips were provided by Abbott DiabetesCare, Inc. S.M.A. and B.A.B. report grants fromthe JDRF. R.N. reports grants from the JDRFduring the conduct of the study. F.J.D. III reportsgrants from the JDRF and grants from theNational Institutes of Health (NIH) during theconduct of the study. S.A.B. reports grants fromthe JDRF during the conduct of the study. M.P.reports grants from the JDRF during the conductof the study. E.D. reports grants from the JDRFand grants from the NIH during the conduct ofthe study. R.W.B. reports grants from the JDRFduring the conduct of the study.

The companies had no involvement in thedesign, conduct, or analysis of the trial or themanuscript preparation.Duality of Interest. S.M.A. reports grants fromMedtronic, personal fees from Senseonics, andgrants from InSpark outside the submittedwork.F.B. reports personal fees from Roche Diagnos-tics outside the submitted work. E.R. reportspersonal fees from A. Menarini Diagnostics,personal fees from Cellnovo, personal fees

from Abbott, personal fees from Eli Lilly, per-sonal fees from Johnson & Johnson, personalfees from Medtronic, personal fees from NovoNordisk, personal fees from Sanofi, personalfees from Roche Diagnostics, and grant/material support fromDexcomandRocheDiagnos-tics outside the submittedwork. B.A.B. reports sup-port from Roche Diagnostics, Dexcom, and Abbottduring the conduct of the study; personal fees fromMedtronic; personal fees from Sanofi; personalfees from Tandem Diabetes Care; personal feesfrom Novo Nordisk; and grant support from Med-tronic and Dexcom outside the submitted work.R.N. reports support fromDreaMedDiabetes outsidethe submitted work. F.J.D. III reports personal feesfromAGC and personal fees fromAnimas Corpora-tion outside the submitted work. S.A.B. reportsgrants from Animas Corporation and grants fromMedtronic outside the submitted work. P.K.-H. re-ports a submitted patent for a Unified Platform ForMonitoring And Control Of Blood Glucose Levels InDiabetic Patients that is pending to TypeZero Tech-nologies, LLC; reports being a researcher at UVAwho developed the DiAs AP system used duringthe conduct of the study; and reports that he isnow a founder and full-time employee at TypeZeroTechnologies, which has licensed this technologyand IP from UVA and is currently engaged in com-mercializing a related system. M.D.B. reports sup-port from TypeZero Technologies LLC, grants andpersonal fees fromRoche, grants and personal feesfrom Sanofi, personal fees fromBayer, and supportfrom InSpark outside the submitted work, has pat-ent 8,585,593 issued, patent 8,562,587 issued, pat-ent 20150018633 pending, patent 20130116649pending, patent 20120078067 pending, and patent20100249561 pending. D.B. reports personal feesfromRocheDiagnostics, personal fees from Eli Lilly,personal fees from LifeScan, personal fees fromAbbott, and personal fees from Sanofi outsidethe submitted work. C.C. has patent B9 PCT/US2008/082063 issued. M.P. reports personalfees from Sanofi and personal fees fromMedtronicoutside the submitted work. E.D. reports personalfees from AGC and personal fees from Animas Cor-poration outside the submitted work. C.K. reportsgrants from JDRF during the conduct of the study.R.W.B. reports support from Animas Corporation,TandemDiabetesCare, andBigfootBiomedicalout-side the submitted work. B.K. reports grants fromBecton, Dickinson and Company; grants fromSanofi; and personal fees from Sanofi outside thesubmitted work. In addition, B.K. has patent8,562,587, 22 October 2013, with royalties paidto Animas Corporation; patent PCT/US12/43883,July 2012, licensed to TypeZero Technologies; andpatent PCT/US12/43910, June 2012, licensed toTypeZero Technologies and is a shareholder inTypeZeroTechnologies.Nootherpotential conflictsof interest relevant to this article were reported.Author Contributions. The Jaeb Center forHealth Research had full access to all of thedata in the study and takes responsibility for theintegrity of the data and the accuracy of the dataanalysis. The study was designed and conductedby the Control to Range Study Group. Theauthors (writing group) collectively wrote themanuscript and vouch for the data. S.M.A. wasthe protocol chair for the study; wrote theabstract, introduction, and discussion; and con-tributed to the editing of the entire manuscript.J.E.P., F.B., E.R., B.A.B., R.N., S.A.B., D.C., W.C.B.,

Figure 3—Participant-level overall (day and night) time ,70 mg/dL and time in range (70–180mg/dL) by baseline and study phase. N = 29 participants; 1 participant was excluded owing tomissing baseline CGM data. A: Time,70 mg/dL during overnight-only CLC by baseline. B: Time,70 mg/dL during 24/7 CLC by baseline. C: Time in range during overnight-only CLC by baseline.D: Time in range during 24/7 CLC by baseline.

care.diabetesjournals.org Anderson and Associates 1149

P.K.B., D.B., S.D.F., R.C., C.C., A.A., A.F., J.P., T.T.L.,and S.S. researched data, contributed to discus-sion, and reviewed and edited the manuscript.F.J.D. III, P.K.-H., M.D.B., M.P., E.D., I.S.D., andC.K. contributed to discussion and reviewed andedited the manuscript. S.M.A., D.R., J.W.L., R.W.B.,and B.K. wrote the manuscript, contributed to dis-cussion, and reviewed and edited the manu-script. P.K.-H. was the chief engineer of theDiAs AP platform. M.D.B. and B.K. designedthe CLC algorithm. S.M.A. is the guarantor ofthis work and, as such, had full access to all thedata in the study and takes responsibility forthe integrity of the data and the accuracy ofthe data analysis.

AppendixThe Control to Range Study Group is as follows.Clinical Centers. UVA: Stacey M. Anderson(site principal investigator [PI] and protocolchair), Boris Kovatchev (study PI), Sue A. Brown(coinvestigator [I]), Marc Breton (I and engineer[E]), PatrickKeith-Hynes (I andE),AntoineRobert(E), Daniel Chernavvsky (coordinator [C]), MaryOliveri (C), Benton Mize (E), Molly McElwee (C),Christian Wakeman (other personnel position[O]), and Sandra Foster (O). Division of Pediat-ric Endocrinology and Diabetes, Stanford Uni-versity, Stanford, CA: Bruce A. Buckingham (sitePI), Trang T. Ly (I), Daniel DeSalvo (I), SatyaShanmugham (C), Marques Delacruz (O), ElianaFrank (O), and Sarah Hanes (O). William SansumDiabetes Center: Jordan E. Pinsker (site PI),Kristin Castorino (I), Alex Morf (I), Wendy Bevier(C), and Paige Bradley (C). Department of Chem-ical Engineering, University of California, SantaBarbara: Francis J.Doyle III (sitePI), EyalDassau (Iand E), and Isuru S. Dasanayake (E). University ofPadova: Claudio Cobelli (site PI), Angelo Avogaro(I), Daniela Bruttomesso (I), Federico Boscari (I),Simone Del Favero (E, I, and C), and RobertaCalore (E). Jesse Z and Sara Lea Shafer Instituteof Endocrinology and Diabetes: Moshe Phillip(site PI), Revital Nimri (I), Avivit Brener (I), AlonFarfel (I), Sharon De-Mol (I), EranMel (I), NaamaFisch (I), Rachel Belo (I), MarieMouler (I), RachelBelo (I), Ido Muller (C), Alona Hamou (C), OrnaHermon(C),Galit Shiovitch-Mantzuri (O), ShaharMiller (E), and Ortal Shelah (E). Department ofEndocrinology, Diabetes, and Nutrition andINSERM 1411 Clinical Investigation Center,Montpellier University Hospital, and UMRCNRS 5203/INSERM U1191, Institute of Func-tional Genomics, University of Montpellier:Eric Renard (site PI), Anne Farret (I), JeromePlace (E and C), Emeline Vachey (C), and AminaBenkhelifa (O).Coordinating Center. Jaeb Center for HealthResearch: Roy W. Beck (site PI), John Lum (I),Craig Kollman (biostatistician [B]), Dan Raghi-naru (B), Judy Sibayan (C), Nelly M. Njeru (C),Barvan Alvarado (O), Denny Figuerres (E), andCarlos Murphy (O).Data and Safety Monitoring Board. John C.Pickup (chair), Irl Hirsch, and Howard Wolpert.

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