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A Randomized, Controlled Trial of an Automated Wireless Messaging System for Diabetes
Abstract
Aggressive management of blood glucose reduces future diabetes-related complications, but this is difficult to achieve.
This randomized, controlled study tested the effect of using a wireless two-way pager-based automated messaging system to improve diabetes control through facilitated self-management. The system sent health-related messages to patients, with automatic forwarding of urgent patient responses to the health care team.
Participants in both the experimental (pager) and the control groups experienced an average hemoglobin A1c decrease of 0.1-0.3%. More patients in the pager group were normotensive, and more felt that their health care was better by the end of the study. A total of 79% of participants enjoyed using the pager, and 68% wanted to continue using the system.
Utilizing a wireless, automated messaging system in clinical practice is a feasible, low-cost, interactive way to facilitate diabetes self-management, which is acceptable to patients. While providing a convenient way for patients and providers to communicate, this system can support automated recording and ready retrieval of these real-time interactions.
... An example message would be, "It's time to take your medication". Eleven studies include the use of one-way Prompts/Cues (Boker, Feetham, Armstrong, Purcell, & Jacobe, 2012;Boland et al., 2014;Garofalo et al., 2016;Harris, Lehavot, & Huh, 2010;Katalenich, Shi, & Liu, 2015;Leu, Norris, Hummel, Isaac, & Brogan, 2005;Moore, Poquette, & Casaletto, 2015;Nundy, Dick, Solomon, & Peek, 2013;Nundy et al., 2014;Park, Howie-Esquivel, Chung, & Dracup, 2014;Park, Howie-Esquivel, Whooley, & Dracup, 2015;Simoni, Huh, & Frick, 2009;Spoelstra, Given, & Sikorskii, 2016;Wald, Bestwick, Raiman, Brendell, & Wald, 2014;Yard, Huh, King, & Simoni, 2011). However, the inclusion of this BCT did not have a consistent effect on medication adherence outcomes with only five of these reporting improvements in medication adherence. ...
... Examples included in this review were blood pressure (BP) or blood glucose (BG) home testing. Completing this self-testing was coded as the Biofeedback BCT and was incorporated into 12 of our included studies (Aikens, Rosland, et al., 2015;Aikens, Trivedi, Aron, et al., 2015;Bove et al., 2013;Katalenich et al., 2015;Leu et al., 2005;Magid, Ho, & Olson, 2011;Nelson, Mulvaney, Gebretsadik, Ho, et al., 2016;Nundy et al., 2013Nundy et al., , 2014Piette, Striplin, & Marinec, 2015;Piette et al., 2000;Shane-McWhorter, Lenert, & Petersen, 2014;Vollmer, Owen-Smith, & Tom, 2014). Where self-testing required the use of a device (e.g. ...
... As these self-monitoring records were not submitted directly, we classified this BCT as delivered through a non-digital component. However, digital communication was used to Prompt/Cue completion of the self-testing behavior and monitor its completion in five studies (Katalenich et al., 2015;Leu et al., 2005;Magid et al., 2011;Nundy et al., 2013Nundy et al., , 2014Shane-McWhorter et al., 2014), although examining the impact on the self-testing behavior itself was not within the scope of this review. ...
Purpose:
Around half of prescribed medications for long-term conditions are not taken as directed. Automated two-way digital communication, such as text messaging and interactive voice response technology, could deliver interventions to improve medication adherence, and subsequently health. However, exploration of how such interventions may improve medication adherence is limited. This review aimed to explore how automated two-way digital communication can improve medication taking with or without using non-digital intervention components, such as phone calls with healthcare professionals.
Methods:
A theory-informed narrative synthesis systematic review. Several databases were searched including CINAHL, Embase, Medline, and Web of Science using key words relating to 'medication adherence' and digital communication technologies. The Behavior Change Technique (BCT) coding using the BCT Taxonomy V1 and the Behavior Change Wheel were used to identify BCTs delivered within the included interventions.
Results:
A total of 3,018 records were screened with 43 study reports included in the review. Four medication-taking behaviors: taking medication, obtaining medication, self-testing, and asking for support were identified as targets for behavior change within the included interventions. Most BCTs within the digital communication component aimed to increase motivation for medication adherence, with non-digital intervention components included to address other medication taking barriers, such as physical and psychological capability.
Conclusion:
Automated two-way digital communication can detect barriers to medication adherence by monitoring performance of the taking medication behavior. Monitoring outcomes from taking medication may increase reflective motivation to take medicines. Addressing physical opportunity to taking medication by facilitating the behavior obtaining medication may also increase adherence.
... Critical to the success of this is the ability to personalise and tailor content to an individual's needs (Weitzel et al, 2007;Bewick et al, 2008;Kypri et al, 2014). The use of digital technology to provide, extend and reinforce substance use treatment has been identified in several cohorts including cannabis-smoking young people (Shrier et al, 2014), alcoholusing college students (Weitzel et al, 2007) and tobacco smokers looking to quit in the UK, New Zealand and Norway (Rodgers et al, 2005;Fjeldsoe et al, 2009;Whittaker et al, 2009), although research has not always indicated behaviour change as an outcome (Leu et al, 2005;Franklin et al, 2006). ...
Background
The use of digital technology in health and social care is developing rapidly. It is promoted in UK policy and research which suggests varied results surrounding its implementation and outcomes.
Introduction
This article aimed to test the implementation and outcomes of a short messaging service sent to a dedicated phone. The target cohort were drug treatment clients in two sites in Northern England.
Materials and methods
Through staff focus groups and interviews with a small cohort of clients, the implementation and perceptions of the system were examined.
Results
A total of 19 participants were recruited to site 1 (15 male, 4 female, average age=37.7 years) and 12 participants were recruited to site 2 (9 male, 3 female, average age=40.3 years). One outcome that was of interest was wellbeing in treatment which, in this study, was described as an overall sense of feeling better rather than just focusing on the rehabilitation aspect of the programme. Other outcomes included: the successful completion of treatment and for clients to report and instance of a relapse/re-presentation.
Discussion
The system shows some evidence of its ‘social actor’ role; however, its implementation was hindered by staff citing that it called for increased resources. For future implementation, the use of clients' own phones may be considered which may help to embed the system more fully in recovery planning and targeting clients at a different treatment stage.
Conclusions
Despite some indications of positive results for clients and a perception that the system may have value as an addition to existing clinical interventions, more evaluation is required to determine whether this system can be implemented in a drug treatment setting.
... Ongoing monitoring of glucose is arguably the most critical aspect of self-care in diabetes, as it triggers subsequent self-care behaviours based on its results [3,42]. However, while awareness of sugar levels is likely to trigger immediate actions to address hypo-or hyperglycemia, it may not always translate into improved self-care [43], so assessment of motivation for all three focal behaviours is preferable. ...
Purpose:
There is a need for improved measurement of motivation for diabetes self-care. The Elaborated Intrusion Theory of Desire offers a coherent framework for understanding and identifying the cognitive-affective events that constitute the subjective experience of motivation and may therefore inform the development of such an instrument. Recent research has shown the resultant Motivation Thought Frequency scale (MTF) to have a stable factor structure (Intensity, Incentives Imagery, Self-Efficacy Imagery, Availability) when applied to physical activity, excessive snacking or alcohol use in the general population. The current study aimed to confirm the four-factor structure of the MTF for glucose testing, physical activity and healthy eating in people with type 2 diabetes. Associations with self-reports of concurrent diabetic self-care behaviours were also examined.
Method:
Confirmatory factor analyses tested the internal structure, and multiple regressions assessed the scale's relationship with concurrent self-care behaviours. The MTF was completed by 340 adults with type 2 diabetes, and 237 from that sample also reported self-care behaviours. Separate MTFs assessed motivation for glucose testing, physical activity and healthy eating. Self-care was assessed using questions from the Summary of Diabetes Self-Care Activities.
Results:
The MTF for each goal achieved an acceptable fit on all indices after selected errors within factors were allowed to intercorrelate. Intensity and Self-Efficacy Imagery provided the strongest and most consistent correlations with relevant self-care behaviours.
Conclusion:
Results provide preliminary support for the MTF in a diabetes sample. Testing of its sensitivity to change and its predictive utility over time is needed.
... No significant differences were found in 14 studies (34%, 14/41), and mixed results were observed in 11 (27%). Multimedia Appendix 2 provides an overview of the methods and outcomes of these studies [18,23,27,30,33,35,39,42,43,45,46,48,49,[52][53][54][55][57][58][59][60][61][65][66][67][68][69][70][71][72][73][74][75][76][77][78][79][80][81][82][83]. ...
Adherence to chronic disease management is critical to achieving improved health outcomes, quality of life, and cost-effective health care. As the burden of chronic diseases continues to grow globally, so does the impact of non-adherence. Mobile technologies are increasingly being used in health care and public health practice (mHealth) for patient communication, monitoring, and education, and to facilitate adherence to chronic diseases management.
We conducted a systematic review of the literature to evaluate the effectiveness of mHealth in supporting the adherence of patients to chronic diseases management ("mAdherence"), and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among patients and health care providers.
We searched PubMed, Embase, and EBSCO databases for studies that assessed the role of mAdherence in chronic disease management of diabetes mellitus, cardiovascular disease, and chronic lung diseases from 1980 through May 2014. Outcomes of interest included effect of mHealth on patient adherence to chronic diseases management, disease-specific clinical outcomes after intervention, and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among target end-users.
In all, 107 articles met all inclusion criteria. Short message service was the most commonly used mAdherence tool in 40.2% (43/107) of studies. Usability, feasibility, and acceptability or patient preferences for mAdherence interventions were assessed in 57.9% (62/107) of studies and found to be generally high. A total of 27 studies employed randomized controlled trial (RCT) methods to assess impact on adherence behaviors, and significant improvements were observed in 15 of those studies (56%). Of the 41 RCTs that measured effects on disease-specific clinical outcomes, significant improvements between groups were reported in 16 studies (39%).
There is potential for mHealth tools to better facilitate adherence to chronic disease management, but the evidence supporting its current effectiveness is mixed. Further research should focus on understanding and improving how mHealth tools can overcome specific barriers to adherence.
Background:
With the continuous and enormous spread of mobile technologies, mHealth has evolved as a new subfield of eHealth. While eHealth is broadly focused on information and communication technologies, mHealth seeks to explore more into mobile devices and wireless communication. Since mobile phone penetration has exceeded other infrastructure in low and middle-income countries (LMICs), mHealth is seen as a promising component to provide pervasive and patient-centered care.
Objectives:
The aim of our research work for this paper is to examine the mHealth literature to identify application areas, target diseases, and mHealth service and technology types that are most appropriate for LMICs.
Methods:
Based on the 2011 WHO mHealth report, a combination of search terms, all including the word "mHealth", was identified. A literature review was conducted by searching the PubMed and IEEE Xplore databases. Articles were included if they were published in English, covered an mHealth solution/intervention, involved the use of a mobile communication device, and included a pilot evaluation study. Articles were excluded if they did not provide sufficient detail on the solution covered or did not focus on clinical efficacy/effectiveness. Cross-referencing was also performed on included articles.
Results:
842 articles were retrieved and analyzed, 255 of which met the inclusion criteria. North America had the highest number of applications (n=74) followed by Europe (n=50), Asia (n=44), Africa (n=25), and Australia (n=9). The Middle East (n=5) and South America (n=3) had the least number of studies. The majority of solutions addressed diabetes (n=51), obesity (n=25), CVDs (n=24), HIV (n=18), mental health (n=16), health behaviors (n=16), and maternal and child's health (MCH) (n=11). Fewer solutions addressed asthma (n=7), cancer (n=5), family health planning (n=5), TB (n=3), malaria (n=2), chronic obtrusive pulmonary disease (COPD) (n=2), vision care (n=2), and dermatology (n=2). Other solutions targeted stroke, dental health, hepatitis vaccination, cold and flu, ED prescribed antibiotics, iodine deficiency, and liver transplantation (n=1 each). The remainder of solutions (n=14) did not focus on a certain disease. Most applications fell in the areas of health monitoring and surveillance (n=93) and health promotion and raising awareness (n=88). Fewer solutions addressed the areas of communication and reporting (n=11), data collection (n=6), tele-medicine (n=5), emergency medical care (n=3), point of care support (n=2), and decision support (n=2). The majority of solutions used SMS messaging (n=94) or mobile apps (n=71). Fewer used IVR/phone calls (n=8), mobile website/email (n=5), videoconferencing (n=2), MMS (n=2), or video (n=1) or voice messages (n=1). Studies were mostly RCTs, with the majority suffering from small sample sizes and short study durations. Problems addressed by solutions included travel distance for reporting, self-management and disease monitoring, and treatment/medication adherence.
Conclusions:
SMS and app solutions are the most common forms of mHealth applications. SMS solutions are prevalent in both high and LMICs while app solutions are mostly used in high income countries. Common application areas include health promotion and raising awareness using SMS and health monitoring and surveillance using mobile apps. Remaining application areas are rarely addressed. Diabetes is the most commonly targeted medical condition, yet remains deficient in LMICs.
Objective: To reveal the effects of consumer-oriented health information technologies (CHITs) on patient outcomes in diabetes management over time through systematic review and meta-analysis.
Methods: We searched 5 electronic databases (from database inception to July 2016) for studies that reported on randomized controlled trials examining the effects of CHITs on glycemic control and other patient outcomes in diabetes management. Data were analyzed using either meta-analysis or a narrative synthesis approach.
Results: Eighty randomized controlled trial studies, representing 87 individual trials, were identified and included for analysis. Overall, the meta-analysis showed that the use of CHITs resulted in significant improvement in glycemic control compared to usual care (standardized mean difference = −0.31%, 95% confidence interval −0.38 to −0.23, P < .001) in patients with diabetes. Specifically, improvement in glycemic control was significant at intervention durations of 3, 6, 8, 9, 12, 15, 30, and 60 months, while no significant differences were found at other time points reported. The narrative synthesis provided mixed effects of CHITs on other clinical, psychosocial, behavioral, and knowledge outcomes.
Conclusions: The use of CHITs appears to be more effective than usual care in improving glycemic control for patients with diabetes. However, their effectiveness did not remain consistent over time and in other patient outcomes. Further efforts are required to examine long-term effects of CHITs and to explore factors that can moderate the effects over time.
Background
We developed a patient-centered, smartphone-based, diabetes care system (PSDCS). This study aims to test the feasibility of glycosylated hemoglobin (HbA1c) reduction with the PSDCS.
Methods
This study was a single-arm pilot study. The participants with type 2 diabetes mellitus were instructed to use the PSDCS, which integrates a Bluetooth-connected glucometer, digital food diary, and wearable physical activity monitoring device. The primary end point was the change in HbA1c from baseline after a 12-week intervention.
Results
Twenty-nine patients aged 53.9±9.1 years completed the study. HbA1c and fasting plasma glucose levels decreased significantly from baseline (7.7%±0.7% to 7.1%±0.6%, P<0.0001; 140.9±39.1 to 120.1±31.0 mg/dL, P=0.0088, respectively). The frequency of glucose monitoring correlated with the magnitude of HbA1c reduction (r=–0.57, P=0.0013). The components of the diabetes self-care activities, including diet, exercise, and glucose monitoring, were significantly improved, particularly in the upper tertile of HbA1c reduction. There were no severe adverse events during the intervention.
Conclusion
A 12-week application of the PSDCS to patients with inadequately controlled type 2 diabetes resulted in a significant HbA1c reduction with tolerable safety profiles; these findings require confirmation in a future randomized controlled trial.
Background:
We developed a patient-centered, smartphone-based, diabetes care system (PSDCS). This study aims to test the feasibility of glycosylated hemoglobin (HbA1c) reduction with the PSDCS.
Methods:
This study was a single-arm pilot study. The participants with type 2 diabetes mellitus were instructed to use the PSDCS, which integrates a Bluetooth-connected glucometer, digital food diary, and wearable physical activity monitoring device. The primary end point was the change in HbA1c from baseline after a 12-week intervention.
Results:
Twenty-nine patients aged 53.9±9.1 years completed the study. HbA1c and fasting plasma glucose levels decreased significantly from baseline (7.7%±0.7% to 7.1%±0.6%, P<0.0001; 140.9±39.1 to 120.1±31.0 mg/dL, P=0.0088, respectively). The frequency of glucose monitoring correlated with the magnitude of HbA1c reduction (r=-0.57, P=0.0013). The components of the diabetes self-care activities, including diet, exercise, and glucose monitoring, were significantly improved, particularly in the upper tertile of HbA1c reduction. There were no severe adverse events during the intervention.
Conclusion:
A 12-week application of the PSDCS to patients with inadequately controlled type 2 diabetes resulted in a significant HbA1c reduction with tolerable safety profiles; these findings require confirmation in a future randomized controlled trial.
Background:
Telemedicine (TM) is the use of telecommunication systems to deliver health care at a distance. It has the potential to improve patient health outcomes, access to health care and reduce healthcare costs. As TM applications continue to evolve it is important to understand the impact TM might have on patients, healthcare professionals and the organisation of care.
Objectives:
To assess the effectiveness, acceptability and costs of interactive TM as an alternative to, or in addition to, usual care (i.e. face-to-face care, or telephone consultation).
Search methods:
We searched the Effective Practice and Organisation of Care (EPOC) Group's specialised register, CENTRAL, MEDLINE, EMBASE, five other databases and two trials registers to June 2013, together with reference checking, citation searching, handsearching and contact with study authors to identify additional studies.
Selection criteria:
We considered randomised controlled trials of interactive TM that involved direct patient-provider interaction and was delivered in addition to, or substituting for, usual care compared with usual care alone, to participants with any clinical condition. We excluded telephone only interventions and wholly automatic self-management TM interventions.
Data collection and analysis:
For each condition, we pooled outcome data that were sufficiently homogenous using fixed effect meta-analysis. We reported risk ratios (RR) and 95% confidence intervals (CI) for dichotomous outcomes, and mean differences (MD) for continuous outcomes.
Main results:
We included 93 eligible trials (N = 22,047 participants), which evaluated the effectiveness of interactive TM delivered in addition to (32% of studies), as an alternative to (57% of studies), or partly substituted for usual care (11%) as compared to usual care alone.The included studies recruited patients with the following clinical conditions: cardiovascular disease (36), diabetes (21), respiratory conditions (9), mental health or substance abuse conditions (7), conditions requiring a specialist consultation (6), co morbidities (3), urogenital conditions (3), neurological injuries and conditions (2), gastrointestinal conditions (2), neonatal conditions requiring specialist care (2), solid organ transplantation (1), and cancer (1).Telemedicine provided remote monitoring (55 studies), or real-time video-conferencing (38 studies), which was used either alone or in combination. The main TM function varied depending on clinical condition, but fell typically into one of the following six categories, with some overlap: i) monitoring of a chronic condition to detect early signs of deterioration and prompt treatment and advice, (41); ii) provision of treatment or rehabilitation (12), for example the delivery of cognitive behavioural therapy, or incontinence training; iii) education and advice for self-management (23), for example nurses delivering education to patients with diabetes or providing support to parents of very low birth weight infants or to patients with home parenteral nutrition; iv) specialist consultations for diagnosis and treatment decisions (8), v) real-time assessment of clinical status, for example post-operative assessment after minor operation or follow-up after solid organ transplantation (8) vi), screening, for angina (1).The type of data transmitted by the patient, the frequency of data transfer, (e.g. telephone, e-mail, SMS) and frequency of interactions between patient and healthcare provider varied across studies, as did the type of healthcare provider/s and healthcare system involved in delivering the intervention.We found no difference between groups for all-cause mortality for patients with heart failure (16 studies; N = 5239; RR:0.89, 95% CI 0.76 to 1.03, P = 0.12; I(2) = 44%) (moderate to high certainty of evidence) at a median of six months follow-up. Admissions to hospital (11 studies; N = 4529) ranged from a decrease of 64% to an increase of 60% at median eight months follow-up (moderate certainty of evidence). We found some evidence of improved quality of life (five studies; N = 482; MD:-4.39, 95% CI -7.94 to -0.83; P < 0.02; I(2) = 0%) (moderate certainty of evidence) for those allocated to TM as compared with usual care at a median three months follow-up. In studies recruiting participants with diabetes (16 studies; N = 2768) we found lower glycated haemoglobin (HbA1c %) levels in those allocated to TM than in controls (MD -0.31, 95% CI -0.37 to -0.24; P < 0.00001; I(2)= 42%, P = 0.04) (high certainty of evidence) at a median of nine months follow-up. We found some evidence for a decrease in LDL (four studies, N = 1692; MD -12.45, 95% CI -14.23 to -10.68; P < 0.00001; I(2 =) 0%) (moderate certainty of evidence), and blood pressure (four studies, N = 1770: MD: SBP:-4.33, 95% CI -5.30 to -3.35, P < 0.00001; I(2) = 17%; DBP: -2.75 95% CI -3.28 to -2.22, P < 0.00001; I(2) = 45% (moderate certainty evidence), in TM as compared with usual care.Seven studies that recruited participants with different mental health and substance abuse problems, reported no differences in the effect of therapy delivered over video-conferencing, as compared to face-to-face delivery. Findings from the other studies were inconsistent; there was some evidence that monitoring via TM improved blood pressure control in participants with hypertension, and a few studies reported improved symptom scores for those with a respiratory condition. Studies recruiting participants requiring mental health services and those requiring specialist consultation for a dermatological condition reported no differences between groups.
Authors' conclusions:
The findings in our review indicate that the use of TM in the management of heart failure appears to lead to similar health outcomes as face-to-face or telephone delivery of care; there is evidence that TM can improve the control of blood glucose in those with diabetes. The cost to a health service, and acceptability by patients and healthcare professionals, is not clear due to limited data reported for these outcomes. The effectiveness of TM may depend on a number of different factors, including those related to the study population e.g. the severity of the condition and the disease trajectory of the participants, the function of the intervention e.g., if it is used for monitoring a chronic condition, or to provide access to diagnostic services, as well as the healthcare provider and healthcare system involved in delivering the intervention.
This article describes the development of a diabetes attitude scale (DAS) that was designed to measure the attitudes of health-care professionals (HCPs). The DAS was developed through the efforts of a national panel of diabetes experts. The panel developed a 60-item scale that was pilot tested and reduced to a 50-item scale. The 50-item scale was then mailed to a national sample of HCPs with an interest in diabetes. The surveys were returned by 633 nurses, 322 dietitians, 116 physicians, and 67 others totaling 1138 returns (a return rate of 54%). The returned surveys were analyzed, and a 31-item DAS composed of 8 subscales resulted. Evidence for the reliability and validity of the 31-item DAS along with the instrument itself are included in this study.
New treatments for HIV can improve immune functioning and decrease mortality. However, lapses in adherence may render these complex regimens ineffective. Sixty-three men and 9 women on highly active antiretroviral therapy completed measures of medication adherence, psychological characteristics, and barriers to adherence. HIV viral load, a health outcome measure of virus amount present in blood, was also obtained. The sample was 36% African American and 56% Caucasian, with 35% reporting disability. Nearly one third of patients had missed medication doses in the past 5 days, and 18% had missed doses weekly over the past 3 months. Frequency of missed doses was strongly related to detectable HIV viral loads. Depression, side-effect severity, self-efficacy, and social support distinguished patients with good and poor adherence. Barriers also varied with adherence level. Implications for interventions promoting HIV treatment adherence are discussed.
Failure to adhere to complex antiretroviral regimens can lead to resistance and treatment failure among HIV-positive persons. In this study of the feasibility of an automated two-way messaging system to improve adherence, participants received multiple short daily messages designed to remind, educate, encourage adherence, and solicit responses concerning side effects and self-reported adherence. Twenty-five participants remained in the study for a median of 208 days, receiving 17,440 messages and replying to 14,677 (84%). Participants reported missing one or more doses on 36% of 743 queries and reported medication side effects on 26% of 729 queries. Participants expressed high satisfaction with the messaging system and reported that it helped with medication adherence. The study suggests that it is feasible to use an automated wireless two-way messaging system to communicate with HIV-positive patients over an extended period of time.
The medical care system is not very effective in modifying health behavior of individuals, in particular, ensuring patient compliance with medication regimens, healthy diets, regular physical activity, and regular health screening, and in the avoidance of substance abuse. Telephone-Linked Care (TLC) is a telecommunications technology that enables computer-controlled telephone counseling with patients in their homes. It has been applied to the task of improving a number of different health behaviors. Randomized controlled studies suggest that use of the system for as little as 3 months is associated with improvement in adherence to medication regimens, dietary change in hypercholesterolemia, and increased physical activity among sedentary individuals. Future work involves applying the technology to other important health behaviors, optimally using health behavior theory in the system design, targeting use of TLC to the most appropriate patient groups, incorporating new computer and telecommunications technology into the system, and interfacing TLC into the health care delivery system.
To report the progress (after 9-year follow-up) of a study designed to determine whether improved glucose control in patients with newly diagnosed non-insulin-dependent diabetes mellitus (NIDDM) is effective in reducing the incidence of clinical complications.
A multicenter, randomized, controlled trial of different therapies for NIDDM. After initial diet therapy, 4209 asymptomatic patients who remained hyperglycemic (fasting plasma glucose levels, 6.0 to 15.0 mmol/L) were assigned to either a conventional therapy policy, primarily with diet alone, or to an intensive therapy policy, aiming for fasting plasma glucose levels of less than 6.0 mmol/L, with assignment to primary therapy with sulfonylurea or insulin (which increased insulin supply) or metformin (which enhanced insulin sensitivity).
All three modes of pharmacologic therapy in the intensively treated group-sulfonylurea, insulin, and metformin-had similar efficacy in reducing the fasting plasma glucose and glycated hemoglobin levels. Over 9 years, patients assigned to intensive therapy with sulfonylurea or insulin had lower fasting plasma glucose levels (median, 7.3 and 9.0 mmol/L, respectively) than patients assigned to conventional therapy. Regardless of the assigned therapy, however, the fasting plasma glucose and hemoglobin A1c levels increased, and maintaining near-normal glycemia was, in general, not feasible. Even insulin therapy did not achieve the therapeutic goal of near-normal glycemia because of the difficulty in treating marked hyperglycemia and the risk for hypoglycemic episodes. Nine years after the diagnosis of diabetes, 29% of the patients had had a diabetes-related clinical end point, 20% had had a macrovascular complication, and 9% had had a microvascular complication.
A report will be published in 1998 after a median duration from randomization of 11 years (range, 6 to 20 years) with an 81% power at a 1% level of significance of detecting whether the obtained improvement in glucose control causes a 15% decrease or increase in the incidence of major complications and whether any specific therapy is advantageous or disadvantageous.
