Real-time continuous glucose monitoring in adults with type 1 diabetes and impaired hypoglycaemia awareness or severe hypoglycaemia treated with multiple daily insulin injections (HypoDE): a multicentre, randomised controlled trial
www.thelancet.com Published online February 16, 2018
Lutz Heinemann, Guido Freckmann, Dominic Ehrmann, Gabriele Faber-Heinemann, Stefania Guerra, Delia Waldenmaier, Norbert Hermanns
ABSTRACT
Summary
Background
The effectiveness of real-time continuous glucose monitoring (rtCGM) in avoidance of hypoglycaemia
among high-risk individuals with type 1 diabetes treated with multiple daily insulin injections (MDI) is unknown. We
aimed to ascertain whether the incidence and severity of hypoglycaemia can be reduced through use of rtCGM in
these individuals.
Methods
The HypoDE study was a 6-month, multicentre, open-label, parallel, randomised controlled trial done at
12 diabetes practices in Germany. Eligible participants had type 1 diabetes and a history of impaired hypoglycaemia awareness or severe hypoglycaemia during the previous year. All participants wore a masked rtCGM system for 28 days and were then randomly assigned to 26 weeks of unmasked rtCGM (Dexcom G5 Mobile system) or to the control group (continuing with self-monitoring of blood glucose). Block randomisation with 1:1 allocation was done centrally, with the study site as the stratifying variable. Masking of participants and study sites was not possible. Control participants wore a masked rtCGM system during the follow-up phase (weeks 22–26). The primary outcome was the baseline-adjusted number of hypoglycaemic events (defined as glucose ≤3·0 mmol/L for ≥20 min) during the follow-up phase. The full dataset analysis comprised participants who wore the rtCGM system during the baseline and follow-up phases. The intention-to-treat analysis comprised all randomised participants.
This trial is registered with ClinicalTrials.gov, number NCT02671968.
Findings
Between March 4, 2016, and Jan 12, 2017, 149 participants were randomly assigned (n=74 to the control group;
n=75 to the rtCGM group) and 141 completed the follow-up phase (n=66 in the control group, n=75 in the rtCGM
group). The mean number of hypoglycaemic events per 28 days among participants in the rtCGM group was reduced from 10·8 (SD 10·0) to 3·5 (4·7); reductions among control participants were negligible (from 14·4 [12·4] to 13·7 [11·6]). Incidence of hypoglycaemic events decreased by 72% for participants in the rtCGM group (incidence rate ratio 0·28 [95% CI 0·20–0·39], p<0·0001). 18 serious adverse events were reported: seven in the control group, ten in the rtCGM group, and one before randomisation. No event was considered to be related to the investigational device.
Interpretation
Usage of rtCGM reduced the number of hypoglycaemic events in individuals with type 1 diabetes
treated by MDI and with impaired hypoglycaemia awareness or severe hypoglycaemia.
Discussion
The results of this multicentre randomised study in
individuals with type 1 diabetes treated with MDI and
with impaired hypoglycaemia awareness or severe
hypoglycaemia show that the number of hypoglycaemic
events can be markedly reduced by use of rtCGM
compared with reliance on SMBG.
Other measures of
biochemical hypoglycaemia or markers of future
hypoglycaemic risk, such as percentage of hypoglycaemic
values and the LBGI, were also significantly improved in
the rtCGM group. Additionally, use of rtCGM lowered the
frequency of clinical severe hypoglycaemia
and reduced glycaemic variability. Importantly, the slight improvement
in HbA1c values in the rtCGM group and the similar
HbA1c values between both study groups indicate that
hypoglycaemia reduction was not achieved at the expense
of a deterioration of overall glycaemic control. These
findings show that use of rtCGM can effectively address
problematic hypoglycaemia in individuals with type 1
diabetes treated by MDI.
According to recent international consensus recommendations,
a rtCGM reading below a threshold of
3.0 mmol/L (<54 mg/dL) for at least 15 mins is considered
a hypoglycaemic event.23 Glucose concentrations below
this threshold cause severe neuroglycopenic dysfunction
of the brain that limits the ability to self-treat.24 This
dysfunction not only increases the risk of severe
hypoglycaemia24 but is also associated with hazards in
daily life if it occurs during potentially dangerous activities
such as driving or while operating machines.1 In the
absence of third-party assistance, severe hypoglycaemia
has a high probability of resulting in a life-threatening
condition such as a coma or seizure. Thus, a reduction in
the frequency of hypoglycaemic episodes requiring any
third-party assistance could also be protective against
further deterioration of severe hypoglycaemia resulting in
coma or seizure.25
We found no difference in the incidence of severe
hypoglycaemia requiring medical assistance for recovery.
This result indicates that, despite use of rtCGM, a
subgroup of participants had a persistently elevated
hypoglycaemia risk.6 Because these events are rare, this
study might not have had sufficient statistical power to
detect differences within this subgroup of participants
with severe hypoglycaemia.26
We noted no relevant difference in the self-reported
hypoglycaemia unawareness score between study groups.
This observation corroborates findings from other studies,
which showed a reduction in the incidence of severe
hypoglycaemia but no difference in hypoglycaemia
unawareness scores.3,4 Self-reported unawareness might
be a good predictor of future hypoglycaemia in epidemiological
studies,15 but it is less suited to measure the
physiological effect of hypoglycaemia avoidance on
hypoglycaemia-associated autonomic failure in the context
of rtCGM.
Glycaemic variability was also reduced by use of
rtCGM. This result indicates that rtCGM participants
achieved a more stable glucose profile than did
participants in the control group, which is also a
protective factor against hypoglycaemia.27 As reported,
rtCGM participants showed a significant reduction in
glycaemic variability, from 39.3% at baseline to 34.1% at
follow-up; glycaemic variability less than 36% is
considered stable.23
Patient-reported outcomes showed a positive effect of
rtCGM use on hypoglycaemia-related distress and on
satisfaction with glucose monitoring systems. No effects
were seen on fear of hypoglycaemia and overall diabetesrelated
distress or self-reported health status. This
result indicates that use of rtCGM specifically affected
participants’ satisfaction with this method for glucose
monitoring and participants’ hypoglycaemia-related distress.
Findings from the most recent studies that investigated
use of rtCGM exclusively in individuals with type 1
diabetes treated by MDI were similar to the results
reported here. In the GOLD study,12 an open-label
crossover randomised trial, use of rtCGM was associated
with a notably lower percentage of time participants
spent in the hypoglycaemic range (<3.0 mmol/L)
compared with conventional treatment with SMBG
(0.79% vs 1.89%). Similar differences in the percentage
of time spent with glucose concentrations less than
3.3 mmol/L were observed in the DIAMOND trial13
among rtCGM users compared with SMBG users
(1.4% vs 2.7%, p=0.002).
Conversely, the hypoglycaemic outcomes reported in
the IN CONTROL trial3 and the sensor-augmented CSII
study by Ly and colleagues4 were less robust. For
example, the percentage of glucose values less than or
equal to 3.9 mmol/L was notably higher among rtCGM
users in the sensor-augmented study4 (4.2%) and the
IN CONTROL study3 (6.8%) than in our study (median
1.6%; IQR 0.9–3.7). Glycaemic variability was also
higher with use of rtCGM in the IN CONTROL study
than in our study (39.5% vs 34.1%). However, there
are substantial differences between the three studies.
Whereas the HypoDE study included only participants
treated by MDI, 44% of participants in the IN CONTROL
study and 100% of those in the study by Ly and
colleagues used CSII therapy. The differences in these
findings might also be a consequence of demographic
differences; duration of diabetes within the
IN CONTROL population was 10 years longer than
in the HypoDE study population. The analytical
performance of different rtCGM systems used in these
studies might also be an important contributor to
these findings. Nevertheless, considering that rtCGM
combined with CSII is the most expensive choice
of therapy in type 1 diabetes, the finding that
MDI combined with rtCGM has similar effects
on hypoglycaemia could have significant healtheconomic
implications. Therefore, head-to-head studies
with MDI and CSII combined with rtCGM are
clearly needed.
A key strength of the HypoDE study is that we only
enrolled individuals with type 1 diabetes treated by MDI
and with impaired hypoglycaemia awareness or severe
hypoglycaemia. As discussed earlier, this population has
not been well studied in previous trials. Thus, this study
provided evidence of the significant effect of rtCGM on
problematic hypoglycaemia in individuals treated by
MDI. Findings from a recent study comparing outcomes
of rtCGM in participants treated with MDI or CSII28 and
comparative effectiveness research29 suggest that the
combination of CSII and rtCGM has an unexpectedly
limited ability to reduce hypoglycaemia. A further
strength of the HypoDE study is that the glycaemic
outcomes related to rtCGM could be confirmed by
SMBG measurements, thus excluding the possibility
that these outcomes were an artifact. Absence of external
validation of the rtCGM results was a major criticism of
the IN CONTROL study.30
Some limitations should also be considered. First,
neither participants nor study personnel could be
masked to the intervention. Second, participants were
required to wear their rtCGM device 85% of the time
during the baseline phase to continue in the study. This
requirement might have resulted in selection bias,
which could potentially limit the generalisability of our
findings to all high-risk individuals with type 1 diabetes.
The use of SMBG data to assess the effect of rtCGM on
glycaemic outcomes could also be problematic since
the control group might have tested blood glucose
several times during one hypoglycaemic event. This
repeated testing might have biased the effect of SMBG
on hypoglycaemia-related outcomes. Additionally, the
frequency of SMBG was substantially different during
the follow-up period between the groups, which
necessitated the use of a post-randomisation covariate.
The absence of adjustment for multiplicity for
secondary outcomes can be regarded as another
limitation.
In summary, our findings indicate that individuals
with type 1 diabetes treated by MDI and with impaired
hypoglycaemia awareness or severe hypoglycaemia can
minimise both biochemical and clinical hypoglycaemia
through use of rtCGM without compromising overall
glycaemic control. Since the majority of individuals
with type 1 diabetes are treated by MDI, this finding has
high clinical relevance.
__________________________
A randomized controlled pilot study of continuous glucose monitoring and flash glucose monitoring in
people with Type 1 diabetes and impaired awareness of hypoglycaemia
Reddy, N. Jugnee, A. El Laboudi, E. Spanudakis, S. Anantharaja and N. Oliver
Diabetic Medicine 5 December 2017
Abstract
Aim
Hypoglycaemia in Type 1 diabetes is associated with mortality and morbidity, especially where awareness of
hypoglycaemia is impaired. Clinical pathways for access to continuous glucose monitoring (CGM) and flash glucose monitoring technologies are unclear. We assessed the impact of CGM and flash glucose monitoring in a high-risk group of people with Type 1 diabetes.
Methods
A randomized, non-masked parallel group study was undertaken. Adults with Type 1 diabetes using a
multiple-dose insulin-injection regimen with a Gold score of ≥ 4 or recent severe hypoglycaemia were recruited.
Following 2 weeks of blinded CGM, they were randomly assigned to CGM (Dexcom G5) or flash glucose monitoring (Abbott Freestyle Libre) for 8 weeks. The primary outcome was the difference in time spent in hypoglycaemia (below 3.3 mmol/l) from baseline to endpoint with CGM versus flash glucose monitoring.
Results Some 40 participants were randomized to CGM (n = 20) or flash glucose monitoring (n = 20). The
participants (24 men, 16 women) had a median (IQR) age of 49.6 (37.5–63.5) years, duration of diabetes of 30.0 (21.0–36.5) years and HbA1c of 56 (48–63) mmol/mol [7.3 (6.5–7.8)%]. The baseline median percentage time < 3.3 mmol/l was 4.5% in the CGM group and 6.7% in the flash glucose monitoring. At the end-point the percentage time < 3.3 mmol/l was 2.4%, and 6.8% respectively (median between group difference 4.3%, P = 0.006). Time spent in hypoglycaemia at all thresholds, and hypoglycaemia fear, were different between groups, favouring CGM.
Conclusion
CGM more effectively reduces time spent in hypoglycaemia in people with Type 1 diabetes and impaired
awareness of hypoglycaemia compared with flash glucose monitoring
Clinical Trial Registry No: NCT03028220)
Discussion
The results from this randomized parallel group pilot study
suggest that an 8-week intervention with CGM has a greater
benefit in reducing time in hypoglycaemia compared with flash
glucose monitoring in people with Type 1 diabetes and
impaired awareness of hypoglycaemia. Both CGM and flash
glucosemonitoring improvedHbA1c and percentage time spent
in glucose target (3.9–7.8 and 3.9–10 mmol/l) over 8 weeks.
Finally, within- and between-group improvements in overall
hypoglycaemia fear and the worry sub-scale of the hypoglycaemia
fear survey were seen with CGM. Awareness of
hypoglycaemia remained unchanged with both glucose monitoring
devices.
This is the first direct comparator study of continuous
glucose recording technologies assessing glucose outcomes
and aimed to provide supporting evidence for clinical
pathways implementing CGM and flash glucose monitoring
technologies. Around 25% of people with Type 1 diabetes
have impaired awareness of hypoglycaemia, and the associations
with severe hypoglycaemia confer a burden of
mortality and morbidity. The data from this study suggest
that alerts and alarms are important for this high-risk group,
and that evidence-based clinical pathways must include a
measure of hypoglycaemia awareness prior to implementing
monitoring technologies where flash glucose monitoring may
not be first choice. A measure of hypoglycaemia awareness is
already included in the National Institute for Health and
Care Excellence (NICE) guideline for Type 1 diabetes in
adults [18]. In the IMPACT study [16] flash glucose
monitoring reduced time in hypoglycaemia, a finding we
have not replicated, but IMPACT excluded people with
impaired awareness of hypoglycaemia and recruited participants
with a lower mean HbA1c. These differences in the
population recruited may further indicate the importance of
selecting the appropriate technology for individuals with
Type 1 diabetes.
We did not see an improvement in self-reported awareness
of hypoglycaemia measured by Gold score with either CGM
or flash glucose monitoring. The lack of improvement in
Gold score with CGM is consistent with findings seen in the
IN CONTROL study [15] and in a retrospective audit [19].
The HypoCOMPaSS study showed that restoration of
hypoglycaemia awareness can be achieved, but that selfmonitoring
capillary blood glucose and CGM have an
equivalent effect on impaired awareness of hypoglycaemia
[20]. However, the study designs and technologies implemented
differ, and further research is warranted to explore
the impacts of technology as an adjunct to education in
people with Type 1 diabetes and impaired awareness of
hypoglycaemia. A limitation to evaluating the Gold score
after the use of CGM or flash glucose monitoring is that it is
a subjective score and therefore does not distinguish whether
those who restored their hypoglycaemia awareness had true
recurrence of hypoglycaemia awareness from symptoms or
whether the glucose monitoring was providing ‘electronic
awareness’ by seeing the glucose trace falling or hearing the
alarms with CGM.
Our study is limited by small numbers and a short followup
period, but the population and study design are comparable
with previous reports in highly selected high-risk
groups. The baseline estimate of glucose data was derived
from blinded CGM in both groups, but the final glucose data
was derived from either CGM or flash glucose monitoring.
Therefore, a further limitation is the comparison between
CGM and FGM data, where accuracy may not be equivalent,
so glucose outcomes may not be directly comparable.
This applies when evaluating the difference from baseline to
endpoint within the flash glucose monitoring group and
when comparing the two groups. However, the devices were
used in line with license and the relative published accuracies,
expressed as a mean absolute difference, are between
11% and 13% for real-world use [21–24]. Another limitation
of our study is that stratification at randomization was
based on HbA1c alone and does not consider other factors
such as age, gender and diabetes duration. It is also
important to note that the reported times within range
reported are not independent (for example the percentage
time spent < 3.3mmol outcome includes percentage time
spent < 2.8 mmol/l). We recognize that the inclusion of
participants with severe hypoglycaemia and a Gold score of
< 4 makes the study population heterogeneous as those five
participants with a Gold score of < 4 may not have impaired
awareness of hypoglycaemia. This is a limitation, but these
participants belong to a high-risk population and were
randomized in an equal distribution (two in the CGM group
and five in the flash glucose monitoring group). The strength
of the study lies in its novelty and the clearly defined
homogeneous group of those at highest risk of challenging
hypoglycaemia.
A new consensus for reporting hypoglycaemia in studies as
< 3.0 mmol/l was recently recommended by The International
Hypoglycaemia Study Group [25], but this was not the
case at the time of study design. The percentage time spent at
glucose < 3.0 mmol/l was therefore not a predetermined
study outcome in this study, but when analysed post hoc the
baseline vs. endpoint values were (3.1 vs. 1.5) and (4.7 vs.
5.0) in the CGM group and flash glucose monitoring group
respectively and there was a significant difference in median
change from baseline between groups (P = 0.004), suggesting
benefit with CGM.
The uptake of flash glucose monitoring has been striking
but, as yet, the technology has not been widely incorporated
into clinical guidelines where its role has been unclear. The
IMPACT study selected a specific group of people with
HbA1c values close to target and showed no change in HbA1c
but a reduction in time spent in hypoglycaemia compared
with self-monitoring of capillary blood glucose [16]. This
study adds to the IMPACT and DIAMOND studies and
suggests that CGM is preferable to flash glucose monitoring
for people with Type 1 diabetes using a multiple-dose
injection regimen with HbA1c values above target, and for
those with challenging hypoglycaemia.
One possible mechanism for the findings in our study is the
impact of alerts and alarms on behaviour and it is striking to
note that, alongside a reduction in exposure to hypoglycaemia,
we have demonstrated a reduction in hypoglycaemia
fear and worry. The changes to hypoglycaemia fear should
be confirmed in a larger study with a more heterogeneous
population.
Conclusion
In summary, our pilot data suggest that CGM has a
greater beneficial impact on hypoglycaemia outcomes
than flash glucose monitoring for people with impaired
hypoglycaemia awareness. Additionally, CGM has a
beneficial impact on hypoglycaemia fear, one of the
major barriers to optimal glucose control. The data
suggest that careful assessment of hypoglycaemia awareness
is critical to selecting the appropriate glucose
monitoring technology and that evidence-based clinical
pathways for monitoring should be different for people
with impaired awareness.
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