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Trials with different times of exercise exposure were included in order to compare, in a subgroup analysis, the results of brief programs (eight weeks or less) against longer programs (more than eight weeks). We defined the threshold as eight weeks because programs of at least this duration could have positive and chronic effects on the cardiovascular system. Shorter programs may have acute but not durable effects ( Remonte Cheyenne 71 Ankle Boot Womens afo2RLyc2S
; Thomas 2006 ).

People who:

were 18 years of age or older;

had a 10-year Framingham risk score equal to or greater than 10% over 10 years, or for whom it was possible to calculate the average 10-year Framingham risk score with data from the aggregated published data. In trials where such data were insufficient, alternative inclusion criteria were having two or more cardiovascular risk factors;

did not have a history of cardiovascular events (acute myocardial infarction or stroke).

Exercise interventions were defined as predetermined programs of planned, structured, and repetitive physical activity performed regularly. Exercise could be aerobic or resistance training.

Aerobic exercise is defined as any activity that uses large muscle groups, can be maintained continuously, and is rhythmic in nature. Resistance training is defined as any exercise that causes the muscles to contract against an external resistance with the expectation of increases in strength, tone, mass, or endurance.

The exercise prescriptions included specific recommendations for the type, intensity, frequency, and duration of physical activity with specific fitness or health objectives. Studies involving dietary or medication changes were eligible for inclusion only if the same treatments were applied to both the intervention and control groups.

The review included studies involving the following comparisons:

exercice intervention versus no exercise (control);

exercise and diet versus diet alone;

exercise and medication versus medication alone;

exercise and any other intervention versus that intervention alone.

All-cause mortality and CVD-related mortality

Incidence of acute myocardial infarction

Incidence of stroke

Total CVD risk (difference of changes in the 10-year Framingham score or any other validated score)

Total cholesterol

HDL and LDL cholesterol

Blood pressure

Body mass index (BMI)

Smoking cessation

Exercise capacity (VO 2 max, calories,or meters in six minutes walking test)

Quality of life (Short Form-36 (SF-36) questionnaire or others)

Adverse events

We conducted a systematic search for RCTs in electronic databases (from their inception to the latest available entry date) on 26 November 2013:

Cochrane Central Register of Controlled Trials (CENTRAL) (2013, Issue 10 of 12) in The Cochrane Library ;

MEDLINE (Ovid) (1946 to week 2 November 2013);

View this table:
Table 1

Baseline characteristics of patients and primary and secondary study outcomes

Table 1 shows primary and secondary outcome measures. CPDS mean glycated hemoglobin decreased 1.9% (95% CI 1.5–2.3) over 12 months. UC mean glycated hemoglobin decreased 0.7% (0.3–1.1). Table 1 and Heal USA Echo Womens 7FJ2B
show that the mean 12-month decrease in CPDS glycated hemoglobin was 1.2% more than UC (95% CI 0.5–1.9%; P = 0.001). Furthermore, the CPDS patients had a significantly greater decrease in mean glycated hemoglobin than the UC patients when compared at all follow-up time points ( P < 0.001).

Figure 2

Primary study outcome and baseline A1C stratified analyses.

CO and CPP mean glycated hemoglobin levels also decreased over 12 months. Both had greater 12-month glycated hemoglobin reductions than UC (CO, P = 0.027; CPP, P = 0.40). CO and CPP were similar to CPDS over all follow-up time points ( P > 0.05 for both comparisons).

In a stratified analysis, a greater decline was found with CPDS than UC for the stratum with baseline glycated hemoglobin <9.0% (difference in decrease 0.7%, 95% CI 0.1–1.3, P = 0.006) and the stratum with baseline glycated hemoglobin at least 9.0% (difference in decrease 1.3%, 0.1–2.7, P = 0.017) (shown in Fig. 2 B and C ). The test of interaction was not significant ( P = 0.27) for baseline glycated hemoglobin stratum and treatment group over time. We obtained the same conclusion whether or not we analyzed the baseline to 12-month changes with intermediate glycated hemoglobin measures.

Glycated hemoglobin results were unchanged after adjusting for baseline glycated hemoglobin and after performing the WEE analysis. Although there were mean declines across all groups in lipid values and blood pressure readings, Diabetes Distress, Diabetes Symptoms, and PHQ-9 Depression, none of the 12-month changes comparing the UC to any of the active interventions were significantly different ( P > 0.05).

Hypoglycemic events, hospitalizations, and emergency-room visits were infrequent in all groups. One patient in group 4 (CPDS) was hospitalized twice for reasons not reported to the study. The DSMB determined that there were no direct study-related adverse events found. No patients died during the 12 months of this study.

CONCLUSIONS

To our knowledge, this is the first cluster-randomized study of a mobile diabetes-coaching intervention conducted in a community setting over a 1-year treatment period. Few previous studies of electronic or mobile communication interventions for diabetes were randomized, included a control group, or covered 1 year ( LAUREN Ralph Lauren Fallon sLRIBVLK4
). Our study included minority study participants and found clinically meaningful differences and few adverse events, none of which were related to the study or treatment. Our study evaluated the intervention for commercially insured patients in primary care settings, where the majority of diabetes care is provided. Enrolling and treating study participants according to random assignment of physician practices (clusters) reduced the risk of bias in treatment application. We found that a mobile phone–based treatment/behavioral coaching intervention improved glycated hemoglobin by 1.9%, compared with 0.7% for UC, a difference of 1.2% ( = 0.001) over 12 months. This result pertained to people with poorly controlled glycated hemoglobin (≥9.0%) and people with less severe abnormal initial glycated hemoglobin values (7.5–8.9%).

The results stratified on baseline glycated hemoglobin ( Fig. 2 ) demonstrate three key features. First, since CPDS and UC had similar mean baseline glycated hemoglobin within strata of baseline A1C (<9 vs. ≥9.0%), and the treatment effect is similar in each of the strata, our findings provide evidence of true 12-month treatment differences in glycated hemoglobin, rather than regression to the mean. This stratified analysis is important, showing large changes in A1C by adjusting for baseline A1C. Second, the treatment effect in the higher glycated hemoglobin stratum shows this intervention to be suitable to obtain the goals of the more conservative ACCORD approach ( 23 ). Neither ACCORD nor this study collected person-specific data on dietary, physical activity, and pharmacological management adjustments made for individual patients. Because of the personalized quality of the mobile phone technology, we expect to be able to make those distinctions in future investigations now that its observed effects on glycated hemoglobin justify their study. Third, mobile phone management is efficacious in patients whose glycated hemoglobin levels are clearly above the desired levels as well as patients whose glycated hemoglobin levels are less egregiously elevated. Our finding is consistent with the Cochrane Collaboration review, suggesting the benefit of individual education on glycemic control ( 24 ). However, we did not see convincing improvements in patient-reported diabetes symptoms, diabetes distress, depression, or other clinical (e.g., blood pressure) or laboratory (e.g., lipid) values.

We advise caution in generalizing our findings. The interventions took place through community physician practices and were implemented through electronic communications. Physicians in the community have different experiences with and access to resources, including access to specialists, clinical practice guidelines, and experience or use of electronic communication. We attempted to address these differences by enrolling multiple community physicians to participate in the study and randomization at the practice level. The patient population in the study may also be distinctive because private health care insurance coverage and access to the Internet (either at work or home) were required. Although not all participants provided data at all planned study visits, we addressed missing data in this study in two ways. First, the primary analysis used mixed-effects models, which have the effect of implicitly imputing missing observations ( MerrellChateau Mid Lace Waterproof OqAvjTR
). Second, we performed the WEE sensitivity analysis that used baseline characteristic data to upweight observations from participants who were most similar to participants with missing data ( ScarpaNeutron GTX nvh6P5Dy3
). As a measure of long-term blood glucose control, change in glycated hemoglobin is an important, commonly used outcome. Although low glycated hemoglobin does not imply that diabetes is being well managed, well managed diabetes is characterized by glycated hemoglobin at normal or near-normal levels ( 13 ). We screened >2,600 patients; 72% were ineligible because glycated hemoglobin was lower than eligibility criterion; many physicians referred patients they thought were not adequately managing their diabetes because of poor control relevant to everyday life, such as blurred vision or pain, self-assessed control of diabetes, or depression ( 13 ). In this study, we did not observe convincing changes in these indicators. Communications as specific for these indicators as ours were for glycated hemoglobin may be able to make a larger difference in future studies. Future studies should also consider how mobile communication changes behavior related to blood glucose: medication adherence, treatment intensification, increased physical activity, and number and quality of communications between providers and patients. These may be important mechanisms to explain change in glycated hemoglobin but were not primary or secondary analyses planned for this study. Future studies of mobile health should address more specific characterization of patient and provider behaviors that support change in clinical health parameters.

Mobile phones are ubiquitous—more than 2.7 billion people own mobile phones worldwide. In the United States alone, users have increased from 34 million in 1995 to 290 million in 2010. Mobile phone and Internet users are increasingly diverse in age and race. The widespread distribution of mobile phones and electronic communication, across socioeconomic, sex, and age-groups, combined with the ability to process and communicate data in real time, make these modalities ideal platforms to create simple, effective, diabetes management programs ( 14 ). We found mobile phone and web portal communications for diabetes to have a consequential treatment effect when used by patients and their PCPs.

Acknowledgments

This research project is funded through a contract between the University of Maryland Baltimore and WellDoc in addition to contributions by WellDoc, CareFirst Blue Cross/Blue Shield of Maryland, LifeScan, and Sprint. Additional funding was provided by the Maryland Industrial Partnerships program through the University of Maryland, an initiative of the A. James Clark School of Engineering’s Maryland Technology Enterprise Institute. No other potential conflicts of interest relevant to this article were reported.

C.C.Q. was Principal Investigator for these studies. C.C.Q., M.D.S., M.L.T., and A.L.G.-B. were responsible for the design, data analyses, writing, and review of the manuscript. E.A.B. was responsible for the data analyses and manuscript review. S.H.B. contributed to the writing and review of the manuscript.

The funders of this study did not play a role in the design and conduct of the study; collection, management, analysis, and interpretation of the data, or in the preparation of the manuscript. WellDoc did not have veto power over or have say about changing any manuscript text other than the description of the software coaching system they provided. Dr. Ram Miller served as the DSMB.

The authors thank Dr. Nanette Steinle, Assistant Professor, Division of Endocrinology, Diabetes and Nutrition, University of Maryland, and Interim Chief, Endocrine Section, Baltimore Veterans Medical Center, for advice on the manuscript and clinical laboratory data.

Footnotes

Clinical trial reg. no. MICHAEL Michael Kors Natasha Slide UaWQRPI
, clinicaltrials.gov .

(803) 366-9700 infonow@composite-resources.com