Diabetes mellitus is a chronic illness that requires continuing medical care and ongoing patient self-management education and support to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires multifactorial risk reduction strategies beyond glycemic control. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes.
These standards of care are intended to provide clinicians, patients, researchers, payers, and other interested individuals with the components of diabetes care, general treatment goals, and tools to evaluate the quality of care. Although individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. Specifically titled sections of the standards address children with diabetes, pregnant women, and people with prediabetes. These standards are not intended to preclude clinical judgment or more extensive evaluation and management of the patient by other specialists as needed. For more detailed information about management of diabetes, refer to references ( 1 &#; 3 ).
The recommendations included are screening, diagnostic, and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A large number of these interventions have been shown to be cost-effective ( 4 ). A grading system ( Table 1 ), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.
These standards of care are revised annually by the ADA&#;s multidisciplinary Professional Practice Committee, incorporating new evidence. For the current revision, committee members systematically searched Medline for human studies related to each subsection and published since 1 January . Recommendations (bulleted at the beginning of each subsection and also listed in the &#;Executive Summary: Standards of Medical Care in Diabetes&#;&#;) were revised based on new evidence or, in some cases, to clarify the prior recommendation or match the strength of the wording to the strength of the evidence. A table linking the changes in recommendations to new evidence can be reviewed at http://professional.diabetes.org/CPR . As is the case for all position statements, these standards of care were reviewed and approved by the Executive Committee of ADA&#;s Board of Directors, which includes health care professionals, scientists, and lay people.
Feedback from the larger clinical community was valuable for the revision of the standards. Readers who wish to comment on the &#;Standards of Medical Care in Diabetes&#;&#; are invited to do so at http://professional.diabetes.org/CPR .
Members of the Professional Practice Committee disclose all potential financial conflicts of interest with industry. These disclosures were discussed at the onset of the standards revision meeting. Members of the committee, their employer, and their disclosed conflicts of interest are listed in the &#;Professional Practice Committee for the Clinical Practice Recommendations&#; table (see p. S109). The ADA funds development of the standards and all its position statements out of its general revenues and does not use industry support for these purposes.
Some patients cannot be clearly classified as type 1 or type 2 diabetic. Clinical presentation and disease progression vary considerably in both types of diabetes. Occasionally, patients who otherwise have type 2 diabetes may present with ketoacidosis. Similarly, patients with type 1 diabetes may have a late onset and slow (but relentless) progression of disease despite having features of autoimmune disease. Such difficulties in diagnosis may occur in children, adolescents, and adults. The true diagnosis may become more obvious over time.
Other specific types of diabetes due to other causes, e.g., genetic defects in β-cell function, genetic defects in insulin action, diseases of the exocrine pancreas (such as cystic fibrosis), and drug- or chemical-induced (such as in the treatment of HIV/AIDS or after organ transplantation)
Since there is preanalytical and analytical variability of all the tests, it is also possible that when a test whose result was above the diagnostic threshold is repeated, the second value will be below the diagnostic cut point. This is least likely for A1C, somewhat more likely for FPG, and most likely for the 2-h PG. Barring a laboratory error, such patients are likely to have test results near the margins of the threshold for a diagnosis. The health care professional might opt to follow the patient closely and repeat the testing in 3&#;6 months.
On the other hand, if two different tests are available in an individual and the results are discordant, the test whose result is above the diagnostic cut point should be repeated, and the diagnosis is made based on the confirmed test. That is, if a patient meets the diabetes criterion of the A1C (two results &#;6.5%) but not the FPG (<126 mg/dL or 7.0 mmol/L), or vice versa, that person should be considered to have diabetes.
As with most diagnostic tests, a test result diagnostic of diabetes should be repeated to rule out laboratory error, unless the diagnosis is clear on clinical grounds, such as a patient with a hyperglycemic crisis or classic symptoms of hyperglycemia and a random plasma glucose &#;200 mg/dL. It is preferable that the same test be repeated for confirmation, since there will be a greater likelihood of concurrence in this case. For example, if the A1C is 7.0% and a repeat result is 6.8%, the diagnosis of diabetes is confirmed. However, if two different tests (such as A1C and FPG) are both above the diagnostic thresholds, the diagnosis of diabetes is also confirmed.
The established glucose criteria for the diagnosis of diabetes (FPG and 2-h PG) remain valid as well ( Table 2 ). Just as there is less than 100% concordance between the FPG and 2-h PG tests, there is no perfect concordance between A1C and either glucose-based test. Analyses of the National Health and Nutrition Examination Survey (NHANES) data indicate that, assuming universal screening of the undiagnosed, the A1C cut point of &#;6.5% identifies one-third fewer cases of undiagnosed diabetes than a fasting glucose cut point of &#;126 mg/dL (7.0 mmol/L) ( 11 ), and numerous studies have confirmed that at these cut points the 2-h OGTT value diagnoses more screened people with diabetes ( 12 ). However, in practice, a large portion of the diabetic population remains unaware of its condition. Thus, the lower sensitivity of A1C at the designated cut point may well be offset by the test&#;s greater practicality, and wider application of a more convenient test (A1C) may actually increase the number of diagnoses made.
Epidemiological datasets show a similar relationship for A1C to the risk of retinopathy as has been shown for the corresponding FPG and 2-h PG thresholds. The A1C has several advantages to the FPG and OGTT, including greater convenience (since fasting is not required), evidence to suggest greater preanalytical stability, and less day-to-day perturbations during periods of stress and illness. These advantages must be balanced by greater cost, the limited availability of A1C testing in certain regions of the developing world, and the incomplete correlation between A1C and average glucose in certain individuals. In addition, HbA 1c levels may vary with patients&#; race/ethnicity ( 7 , 8 ). Some have posited that glycation rates differ by race (with, for example, African Americans having higher rates of glycation), but this is controversial. A recent epidemiological study found that, when matched for FPG, African Americans (with and without diabetes) indeed had higher A1C than whites, but also had higher levels of fructosamine and glycated albumin and lower levels of 1,5 anhydroglucitol, suggesting that their glycemic burden (particularly postprandially) may be higher ( 9 ). Epidemiological studies forming the framework for recommending use of the A1C to diagnose diabetes have all been in adult populations. Whether the cut point would be the same to diagnose children or adolescents with type 2 diabetes is an area of uncertainty ( 3 , 10 ). A1C inaccurately reflects glycemia with certain anemias and hemoglobinopathies. For patients with an abnormal hemoglobin but normal red cell turnover, such as sickle cell trait, an A1C assay without interference from abnormal hemoglobins should be used (an updated list is available at www.ngsp.org/interf.asp ). For conditions with abnormal red cell turnover, such as pregnancy, recent blood loss or transfusion, or some anemias, the diagnosis of diabetes must employ glucose criteria exclusively.
In , an International Expert Committee that included representatives of the ADA, the International Diabetes Federation (IDF), and the European Association for the Study of Diabetes (EASD) recommended the use of the A1C test to diagnose diabetes, with a threshold of &#;6.5% ( 6 ), and the ADA adopted this criterion in ( 5 ). The diagnostic test should be performed using a method that is certified by the NGSP and standardized or traceable to the Diabetes Control and Complications Trial (DCCT) reference assay. Although point-of-care (POC) A1C assays may be NGSP certified, proficiency testing is not mandated for performing the test, so use of these assays for diagnostic purposes could be problematic.
Hence, it is reasonable to consider an A1C range of 5.7&#;6.4% as identifying individuals with prediabetes. As is the case for individuals found to have IFG and IGT, individuals with an A1C of 5.7&#;6.4% should be informed of their increased risk for diabetes as well as CVD and counseled about effective strategies to lower their risks (see Section IV). As with glucose measurements, the continuum of risk is curvilinear, so that as A1C rises, the risk of diabetes rises disproportionately ( 15 ). Accordingly, interventions should be most intensive and follow-up particularly vigilant for those with A1Cs above 6.0%, who should be considered to be at very high risk.
As is the case with the glucose measures, several prospective studies that used A1C to predict the progression to diabetes demonstrated a strong, continuous association between A1C and subsequent diabetes. In a systematic review of 44,203 individuals from 16 cohort studies with a follow-up interval averaging 5.6 years (range 2.8&#;12 years), those with an A1C between 5.5 and 6.0% had a substantially increased risk of diabetes with 5-year incidences ranging from 9 to 25%. An A1C range of 6.0&#;6.5% had a 5-year risk of developing diabetes between 25 to 50% and relative risk (RR) 20 times higher compared with an A1C of 5.0% ( 15 ). In a community-based study of black and white adults without diabetes, baseline A1C was a stronger predictor of subsequent diabetes and cardiovascular events than was fasting glucose ( 16 ). Other analyses suggest that an A1C of 5.7% is associated with diabetes risk similar to that in the high-risk participants in the Diabetes Prevention Program (DPP) ( 17 ).
Individuals with IFG and/or IGT have been referred to as having prediabetes, indicating the relatively high risk for the future development of diabetes. IFG and IGT should not be viewed as clinical entities in their own right but rather risk factors for diabetes as well as cardiovascular disease (CVD). IFG and IGT are associated with obesity (especially abdominal or visceral obesity), dyslipidemia with high triglycerides and/or low HDL cholesterol, and hypertension.
In and , the Expert Committee on Diagnosis and Classification of Diabetes Mellitus ( 13 , 14 ) recognized an intermediate group of individuals whose glucose levels, although not meeting criteria for diabetes, are nevertheless too high to be considered normal. These persons were defined as having impaired fasting glucose (IFG) (FPG levels 100 mg/dL [5.6 mmol/L] to 125 mg/dL [6.9 mmol/L]) or impaired glucose tolerance (IGT) (2-h values in the OGTT of 140 mg/dL [7.8 mmol/L] to 199 mg/dL [11.0 mmol/L]). It should be noted that the World Health Organization (WHO) and a number of other diabetes organizations define the cutoff for IFG at 110 mg/dL (6.1 mmol/L).
For many illnesses, there is a major distinction between screening and diagnostic testing. However, for diabetes, the same tests would be used for &#;screening&#; as for diagnosis. Diabetes may be identified anywhere along a spectrum of clinical scenarios ranging from a seemingly low-risk individual who happens to have glucose testing, to a higher-risk individual whom the provider tests because of high suspicion of diabetes, to the symptomatic patient. The discussion herein is primarily framed as testing for diabetes in those without symptoms. The same assays used for testing for diabetes will also detect individuals with prediabetes.
Testing to detect type 2 diabetes and prediabetes in asymptomatic people should be considered in adults of any age who are overweight or obese (BMI &#;25 kg/m 2 ) and who have one or more additional risk factors for diabetes ( Table 4 ). In those without these risk factors, testing should begin at age 45. (B)
Because of the need for follow-up and discussion of abnormal results, testing should be carried out within the health care setting. Community screening outside a health care setting is not recommended because people with positive tests may not seek, or have access to, appropriate follow-up testing and care. Conversely, there may be failure to ensure appropriate repeat testing for individuals who test negative. Community screening may also be poorly targeted; i.e., it may fail to reach the groups most at risk and inappropriately test those at low risk (the worried well) or even those already diagnosed.
The appropriate interval between tests is not known ( 30 ). The rationale for the 3-year interval is that false negatives will be repeated before substantial time elapses, and there is little likelihood that an individual will develop significant complications of diabetes within 3 years of a negative test result. In the modeling study, repeat screening every 3 or 5 years was cost-effective ( 19 ).
The A1C, FPG, or the 2-h OGTT are appropriate for testing. It should be noted that the tests do not necessarily detect diabetes in the same individuals. The efficacy of interventions for primary prevention of type 2 diabetes ( 23 &#; 29 ) has primarily been demonstrated among individuals with IGT, not for individuals with isolated IFG or for individuals with specific A1C levels.
Recommendations for testing for diabetes in asymptomatic, undiagnosed adults are listed in Table 4 . Testing should be considered in adults of any age with BMI &#;25 kg/m 2 and one or more of the known risk factors for diabetes. In addition to the listed risk factors, certain medications, such as glucocorticoids and antipsychotics ( 20 ), are known to increase the risk of type 2 diabetes. There is compelling evidence that lower BMI cut points suggest diabetes risk in some racial and ethnic groups. In a large multiethnic cohort study, for an equivalent incidence rate of diabetes conferred by a BMI of 30 kg/m 2 in whites, the BMI cutoff value was 24 kg/m 2 in South Asians, 25 kg/m 2 in Chinese, and 26 kg/m 2 in African Americans ( 21 ). Disparities in screening rates, not explainable by insurance status, are highlighted by evidence that despite much higher prevalence of type 2 diabetes, non-Caucasians in an insured population are no more likely than Caucasians to be screened for diabetes ( 22 ). Because age is a major risk factor for diabetes, testing of those without other risk factors should begin no later than age 45 years.
Type 2 diabetes is frequently not diagnosed until complications appear, and approximately one-fourth of all people with diabetes in the U.S. may be undiagnosed. The effectiveness of early identification of prediabetes and diabetes through mass testing of asymptomatic individuals has not been proven definitively, and rigorous trials to provide such proof are unlikely to occur. In a large randomized controlled trial (RCT) in Europe, general practice patients between the ages of 40&#;69 years were screened for diabetes and then randomly assigned by practice to routine care of diabetes or intensive treatment of multiple risk factors. After 5.3 years of follow-up, CVD risk factors were modestly but significantly more improved with intensive treatment. Incidence of first CVD event and mortality rates were not significantly different between groups ( 18 ). This study would seem to add support for early treatment of screen-detected diabetes, as risk factor control was excellent even in the routine treatment arm and both groups had lower event rates than predicted. The absence of a control unscreened arm limits the ability to definitely prove that screening impacts outcomes. Mathematical modeling studies suggest that screening independent of risk factors beginning at age 30 years or age 45 years is highly cost-effective (<$11,000 per quality-adjusted life-year gained) ( 19 ).
Prediabetes and diabetes meet established criteria for conditions in which early detection is appropriate. Both conditions are common, increasing in prevalence, and impose significant public health burdens. There is a long presymptomatic phase before the diagnosis of type 2 diabetes is usually made. Relatively simple tests are available to detect preclinical disease. Additionally, the duration of glycemic burden is a strong predictor of adverse outcomes, and effective interventions exist to prevent progression of prediabetes to diabetes (see Section IV) and to reduce risk of complications of diabetes (see Section VI).
The incidence of type 2 diabetes in adolescents has increased dramatically in the last decade, especially in minority populations ( 31 ), although the disease remains rare in the general pediatric population ( 32 ). Consistent with recommendations for adults, children and youth at increased risk for the presence or the development of type 2 diabetes should be tested within the health care setting ( 33 ). The recommendations of the ADA consensus statement &#;Type 2 Diabetes in Children and Adolescents,&#; with some modifications, are summarized in Table 5 .
Testing to detect type 2 diabetes and prediabetes should be considered in children and adolescents who are overweight and who have two or more additional risk factors for diabetes ( Table 5 ). (E)
Generally, people with type 1 diabetes present with acute symptoms of diabetes and markedly elevated blood glucose levels, and some cases are diagnosed with life-threatening ketoacidosis. Evidence from several studies suggests that measurement of islet autoantibodies in relatives of those with type 1 diabetes identifies individuals who are at risk for developing type 1 diabetes. Such testing, coupled with education about symptoms of diabetes and follow-up in an observational clinical study, may allow earlier identification of onset of type 1 diabetes and lessen presentation with ketoacidosis at time of diagnosis. This testing may be appropriate in those who have relatives with type 1 diabetes, in the context of clinical research studies (see, for example, http://www.diabetestrialnet.org ). However, widespread clinical testing of asymptomatic low-risk individuals cannot currently be recommended, as it would identify very few individuals in the general population who are at risk. Individuals who screen positive should be counseled about their risk of developing diabetes and symptoms of diabetes, followed closely to prevent development of diabetic ketoacidosis, and informed about clinical trials. Clinical studies are being conducted to test various methods of preventing type 1 diabetes in those with evidence of autoimmunity. Some interventions have demonstrated modest efficacy in slowing β-cell loss early in type 1 diabetes ( 34 , 35 ), and further research is needed to determine whether they may be effective in preventing type 1 diabetes.
Because some cases of GDM may represent pre-existing undiagnosed type 2 diabetes, women with a history of GDM should be screened for diabetes 6&#;12 weeks postpartum, using nonpregnant OGTT criteria. Because of their prepartum treatment for hyperglycemia, use of the A1C for diagnosis of persistent diabetes at the postpartum visit is not recommended ( 44 ). Women with a history of GDM have a greatly increased subsequent risk for diabetes ( 45 ) and should be followed up with subsequent screening for the development of diabetes or prediabetes, as outlined in Section II. Lifestyle interventions or metformin should be offered to women with a history of GDM who develop prediabetes, as discussed in Section IV. In the prospective Nurses&#; Health Study II, risk of subsequent diabetes after a history of GDM was significantly lower in women who followed healthy eating patterns. Adjusting for BMI moderately, but not completely, attenuated this association ( 46 ).
The American College of Obstetricians and Gynecologists announced in that they continue to recommend use of prior diagnostic criteria for GDM ( 43 ). Several other countries have adopted the new criteria, and a report from the WHO on this topic is pending at the time of publication of these standards. The National Institutes of Health is planning to hold a consensus development conference on this topic in .
Admittedly, there are few data from randomized clinical trials regarding therapeutic interventions in women who will now be diagnosed with GDM based on only one blood glucose value above the specified cut points (in contrast to the older criteria that stipulated at least two abnormal values). However, there is emerging observational and retrospective evidence that women diagnosed with the new criteria (even if they would not have been diagnosed with older criteria) have increased rates of poor pregnancy outcomes similar to those of women with GDM by prior criteria ( 39 , 40 ). Expected benefits to these pregnancies and offspring are inferred from intervention trials that focused on women with more mild hyperglycemia than identified using older GDM diagnostic criteria and that found modest benefits ( 41 , 42 ). The frequency of follow-up and blood glucose monitoring for these women is not yet clear, but likely to be less intensive than for women diagnosed by the older criteria. It is important to note that 80&#;90% of women in both of the mild GDM studies (whose glucose values overlapped with the thresholds recommended herein) could be managed with lifestyle therapy alone.
These new criteria will significantly increase the prevalence of GDM, primarily because only one abnormal value, not two, is sufficient to make the diagnosis. The ADA recognizes the anticipated significant increase in the incidence of GDM diagnosed by these criteria and is sensitive to concerns about the &#;medicalization&#; of pregnancies previously categorized as normal. These diagnostic criteria changes are being made in the context of worrisome worldwide increases in obesity and diabetes rates, with the intent of optimizing gestational outcomes for women and their babies.
GDM carries risks for the mother and neonate. The Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study ( 37 ), a large-scale (&#;25,000 pregnant women) multinational epidemiological study, demonstrated that risk of adverse maternal, fetal, and neonatal outcomes continuously increased as a function of maternal glycemia at 24&#;28 weeks, even within ranges previously considered normal for pregnancy. For most complications, there was no threshold for risk. These results have led to careful reconsideration of the diagnostic criteria for GDM. After deliberations in &#;, the International Association of Diabetes and Pregnancy Study Groups (IADPSG), an international consensus group with representatives from multiple obstetrical and diabetes organizations, including ADA, developed revised recommendations for diagnosing GDM. The group recommended that all women not known to have prior diabetes undergo a 75-g OGTT at 24&#;28 weeks of gestation. Additionally, the group developed diagnostic cut points for the fasting, 1-h, and 2-h plasma glucose measurements that conveyed an odds ratio for adverse outcomes of at least 1.75 compared with women with the mean glucose levels in the HAPO study. Current screening and diagnostic strategies, based on the IADPSG statement ( 38 ), are outlined in Table 6 .
For many years, GDM was defined as any degree of glucose intolerance with onset or first recognition during pregnancy ( 13 ), whether or not the condition persisted after pregnancy, and not excluding the possibility that unrecognized glucose intolerance may have antedated or begun concomitantly with the pregnancy. This definition facilitated a uniform strategy for detection and classification of GDM, but its limitations were recognized for many years. As the ongoing epidemic of obesity and diabetes has led to more type 2 diabetes in women of childbearing age, the number of pregnant women with undiagnosed type 2 diabetes has increased ( 36 ). Because of this, it is reasonable to screen women with risk factors for type 2 diabetes ( Table 4 ) for diabetes at their initial prenatal visit, using standard diagnostic criteria ( Table 2 ). Women with diabetes found at this visit should receive a diagnosis of overt, not gestational, diabetes.
People with prediabetes often have other cardiovascular risk factors, such as obesity, hypertension, and dyslipidemia. Assessing and treating these risk factors is an important aspect of reducing cardiometabolic risk. In the DPP and DPPOS, cardiovascular event rates have been very low, perhaps due to appropriate management of cardiovascular risk factors in all arms of the study ( 56 ).
Based on the results of clinical trials and the known risks of progression of prediabetes to diabetes, persons with an A1C of 5.7&#;6.4%, IGT, or IFG should be counseled on lifestyle changes with goals similar to those of the DPP (7% weight loss and moderate physical activity of at least 150 min/week). Regarding drug therapy for diabetes prevention, metformin has a strong evidence base and demonstrated long-term safety ( 53 ). For other drugs, issues of cost, side effects, and lack of persistence of effect in some studies ( 54 ) require consideration. Metformin was less effective than lifestyle modification in the DPP and DPPOS, but may be cost-saving over a 10-year period ( 51 ). It was as effective as lifestyle modification in participants with a BMI of at least 35 kg/m 2 , but not significantly better than placebo than those over age 60 years ( 23 ). In women in the DPP with a history of GDM, metformin and intensive lifestyle modification led to an equivalent 50% reduction in the risk of diabetes ( 55 ). Metformin therefore might reasonably be recommended for very high-risk individuals (those with a history of GDM, the very obese, and/or those with more severe or progressive hyperglycemia).
RCTs have shown that individuals at high risk for developing type 2 diabetes (those with IFG, IGT, or both) can significantly decrease the rate of onset of diabetes with particular interventions ( 23 &#; 29 ). These include intensive lifestyle modification programs that have been shown to be very effective (&#;58% reduction after 3 years) and use of the pharmacological agents metformin, α-glucosidase inhibitors, orlistat, and thiazolidinediones, each of which has been shown to decrease incident diabetes to various degrees. Follow-up of all three large studies of lifestyle intervention has shown sustained reduction in the rate of conversion to type 2 diabetes, with 43% reduction at 20 years in the Da Qing study ( 47 ), 43% reduction at 7 years in the Finnish Diabetes Prevention Study (DPS) ( 48 ), and 34% reduction at 10 years in the U.S. Diabetes Prevention Program Outcomes Study (DPPOS) ( 49 ). A cost-effectiveness model suggested that lifestyle interventions as delivered in the DPP are cost-effective ( 50 ), and actual cost data from the DPP and DPPOS confirm that lifestyle interventions are highly cost-effective ( 51 ). Group delivery of the DPP intervention in community settings has the potential to be significantly less expensive while still achieving similar weight loss ( 52 ).
Metformin therapy for prevention of type 2 diabetes may be considered in those with IGT (A), IFG (E), or an A1C of 5.7&#;6.4% (E), especially for those with BMI >35 kg/m 2 , aged <60 years, and women with prior GDM. (A)
Patients with IGT (A), IFG (E), or an A1C of 5.7&#;6.4% (E) should be referred to an effective ongoing support program targeting weight loss of 7% of body weight and increasing physical activity to at least 150 min/week of moderate activity such as walking.
A complete medical evaluation should be performed to classify the diabetes, detect the presence of diabetes complications, review previous treatment and risk factor control in patients with established diabetes, assist in formulating a management plan, and provide a basis for continuing care. Laboratory tests appropriate to the evaluation of each patient&#;s medical condition should be performed. A focus on the components of comprehensive care ( Table 7 ) will assist the health care team to ensure optimal management of the patient with diabetes.
The management plan should be formulated as a collaborative therapeutic alliance among the patient and family, the physician, and other members of the health care team. A variety of strategies and techniques should be used to provide adequate education and development of problem-solving skills in the various aspects of diabetes management. Implementation of the management plan requires that the goals and treatment plan are individualized and take patient preferences into account. The management plan should recognize diabetes self-management education (DSME) and ongoing diabetes support as an integral component of care. In developing the plan, consideration should be given to the patient&#;s age, school or work schedule and conditions, physical activity, eating patterns, social situation and cultural factors, and presence of complications of diabetes or other medical conditions.
People with diabetes should receive medical care from a team that may include physicians, nurse practitioners, physician&#;s assistants, nurses, dietitians, pharmacists, and mental health professionals with expertise and a special interest in diabetes. It is essential in this collaborative and integrated team approach that individuals with diabetes assume an active role in their care.
Two primary techniques are available for health providers and patients to assess the effectiveness of the management plan on glycemic control: patient self-monitoring of blood glucose (SMBG) or interstitial glucose, and A1C.
A trial comparing CGM plus insulin pump to SMBG plus multiple injections of insulin in adults and children with type 1 diabetes showed significantly greater improvements in A1C with &#;sensor-augmented pump&#; therapy ( 68 , 69 ), but this trial did not isolate the effect of CGM itself. Overall, meta-analyses suggest that compared with SMBG, CGM lowers A1C by &#;0.26% ( 70 ). Altogether, these data suggest that, in appropriately selected patients who are motivated to wear it most of the time, CGM reduces A1C. The technology may be particularly useful in those with hypoglycemia unawareness and/or frequent episodes of hypoglycemia, although studies as yet have not shown significant reductions in severe hypoglycemia ( 70 ). CGM forms the underpinning for the development of pumps that suspend insulin delivery when hypoglycemia is developing and for the burgeoning work on &#;artificial pancreas&#; systems.
Real-time CGM through the measurement of interstitial glucose (which correlates well with plasma glucose) is available. These sensors require calibration with SMBG, and the latter are still recommended for making acute treatment decisions. CGM devices have alarms for hypo- and hyperglycemic excursions. A 26-week randomized trial of 322 type 1 diabetic patients showed that adults aged &#;25 years using intensive insulin therapy and CGM experienced a 0.5% reduction in A1C (from &#;7.6 to 7.1%) compared with usual intensive insulin therapy with SMBG ( 66 ). Sensor use in children, teens, and adults to age 24 years did not result in significant A1C lowering, and there was no significant difference in hypoglycemia in any group. Importantly, the greatest predictor of A1C lowering in this study for all age-groups was frequency of sensor use, which was lower in younger age-groups. In a smaller RCT of 129 adults and children with baseline A1C <7.0%, outcomes combining A1C and hypoglycemia favored the group utilizing CGM, suggesting that CGM is also beneficial for individuals with type 1 diabetes who have already achieved excellent control ( 67 ).
Because the accuracy of SMBG is instrument and user dependent ( 63 ), it is important to evaluate each patient&#;s monitoring technique, both initially and at regular intervals thereafter. Optimal use of SMBG requires proper review and interpretation of the data, both by the patient and provider. Among patients who checked their blood glucose at least once daily, many reported taking no action when results were high or low ( 64 ). In one study of insulin-naïve patients with suboptimal initial glycemic control, use of structured SMBG (a paper tool to collect and interpret 7-point SMBG profiles over 3 days at least quarterly) reduced A1C by 0.3% more than in an active control group ( 65 ). Patients should be taught how to use SMBG data to adjust food intake, exercise, or pharmacological therapy to achieve specific goals, and the ongoing need for and frequency of SMBG should be re-evaluated at each routine visit.
The evidence base for SMBG for patients with type 2 diabetes on noninsulin therapy is somewhat mixed. Several randomized trials have called into question the clinical utility and cost-effectiveness of routine SMBG in non&#;insulin-treated patients ( 58 &#; 60 ). A recent meta-analysis suggested that SMBG reduced A1C by 0.25% at 6 months ( 61 ), while a Cochrane review concluded that the overall effect of SMBG in such patients is small up to 6 months after initiation and subsides after 12 months ( 62 ).
The frequency and timing of SMBG should be dictated by the particular needs and goals of the patient. SMBG is especially important for patients treated with insulin to monitor for and prevent asymptomatic hypoglycemia and hyperglycemia. Most patients with type 1 diabetes and others on intensive insulin regimens (MDI or insulin pump therapy) should do SMBG at least prior to meals and snacks, occasionally postprandially, at bedtime, prior to exercise, when they suspect low blood glucose, after treating low blood glucose until they are normoglycemic, and prior to critical tasks such as driving. For many patients, this will require testing 6&#;8 times daily, although individual needs may be greater. Although there are few rigorous studies, a database study of almost 27,000 children and adolescents with type 1 diabetes showed that, after adjustment for multiple confounders, increased daily frequency of SMBG was significantly associated with lower A1C (&#;0.2% per additional test per day, leveling off at five tests per day) and with fewer acute complications ( 57 ). The optimal frequency of SMBG for patients on nonintensive regimens, such as those with type 2 diabetes on basal insulin, is not known, although a number of studies have used fasting SMBG for patient or provider titration of the basal insulin dose.
Major clinical trials of insulin-treated patients that demonstrated the benefits of intensive glycemic control on diabetes complications have included SMBG as part of multifactorial interventions, suggesting that SMBG is a component of effective therapy. SMBG allows patients to evaluate their individual response to therapy and assess whether glycemic targets are being achieved. Results of SMBG can be useful in preventing hypoglycemia and adjusting medications (particularly prandial insulin doses), medical nutrition therapy (MNT), and physical activity.
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Although the evidence for A1C lowering is less strong in children, teens, and younger adults, CGM may be helpful in these groups. Success correlates with adherence to ongoing use of the device. (C)
Patients on multiple-dose insulin (MDI) or insulin pump therapy should do SMBG at least prior to meals and snacks, occasionally postprandially, at bedtime, prior to exercise, when they suspect low blood glucose, after treating low blood glucose until they are normoglycemic, and prior to critical tasks such as driving. (B)
For patients in whom A1C/eAG and measured blood glucose appear discrepant, clinicians should consider the possibilities of hemoglobinopathy or altered red cell turnover, and the options of more frequent and/or different timing of SMBG or use of CGM. Other measures of chronic glycemia such as fructosamine are available, but their linkage to average glucose and their prognostic significance are not as clear as is the case for A1C.
In the ADAG trial, there were no significant differences among racial and ethnic groups in the regression lines between A1C and mean glucose, although there was a trend toward a difference between African/African American participants and Caucasian ones. A small study comparing A1C to CGM data in type 1 diabetic children found a highly statistically significant correlation between A1C and mean blood glucose, although the correlation (r = 0.7) was significantly lower than in the ADAG trial ( 79 ). Whether there are significant differences in how A1C relates to average glucose in children or in African American patients is an area for further study. For the time being, the question has not led to different recommendations about testing A1C or to different interpretations of the clinical meaning of given levels of A1C in those populations.
Table 8 contains the correlation between A1C levels and mean plasma glucose levels based on data from the international A1C-Derived Average Glucose (ADAG) trial utilizing frequent SMBG and CGM in 507 adults (83% Caucasian) with type 1, type 2, and no diabetes ( 77 ). The ADA and the American Association for Clinical Chemistry have determined that the correlation (r = 0.92) is strong enough to justify reporting both an A1C result and an estimated average glucose (eAG) result when a clinician orders the A1C test. The table in pre- versions of the &#;Standards of Medical Care in Diabetes&#; describing the correlation between A1C and mean glucose was derived from relatively sparse data (one 7-point profile over 1 day per A1C reading) in the primarily Caucasian type 1 diabetic participants in the DCCT ( 78 ). Clinicians should note that the numbers in the table are now different, as they are based on &#;2,800 readings per A1C in the ADAG trial.
The A1C test is subject to certain limitations. Conditions that affect erythrocyte turnover (hemolysis, blood loss) and hemoglobin variants must be considered, particularly when the A1C result does not correlate with the patient&#;s clinical situation ( 63 ). In addition, A1C does not provide a measure of glycemic variability or hypoglycemia. For patients prone to glycemic variability (especially type 1 diabetic patients or type 2 diabetic patients with severe insulin deficiency), glycemic control is best judged by the combination of results of self-monitoring and the A1C. The A1C may also serve as a check on the accuracy of the patient&#;s meter (or the patient&#;s reported SMBG results) and the adequacy of the SMBG testing schedule.
Because A1C is thought to reflect average glycemia over several months ( 63 ) and has strong predictive value for diabetes complications ( 71 , 72 ), A1C testing should be performed routinely in all patients with diabetes, at initial assessment and then as part of continuing care. Measurement approximately every 3 months determines whether patient&#;s glycemic targets have been reached and maintained. For any individual patient, the frequency of A1C testing should be dependent on the clinical situation, the treatment regimen used, and the judgment of the clinician. Some patients with stable glycemia well within target may do well with testing only twice per year, while unstable or highly intensively managed patients (e.g., pregnant type 1 diabetic women) may be tested more frequently than every 3 months. The availability of the A1C result at the time that the patient is seen (POC testing) has been reported in small studies to result in increased intensification of therapy and improvement in glycemic control ( 73 , 74 ). However, two recent systematic reviews and meta-analyses found no significant difference in A1C between POC and laboratory A1C usage ( 75 , 76 ).
Lowering A1C to below or around 7% has been shown to reduce microvascular complications of diabetes and if implemented soon after the diagnosis of diabetes is associated with long-term reduction in macrovascular disease. Therefore, a reasonable A1C goal for many nonpregnant adults is <7%. (B)
Providers might reasonably suggest more stringent A1C goals (such as <6.5%) for selected individual patients, if this can be achieved without significant hypoglycemia or other adverse effects of treatment. Appropriate patients might include those with short duration of diabetes, long life expectancy, and no significant CVD. (C)
Less stringent A1C goals (such as <8%) may be appropriate for patients with a history of severe hypoglycemia, limited life expectancy, advanced microvascular or macrovascular complications, extensive comorbid conditions, and those with long-standing diabetes in whom the general goal is difficult to attain despite DSME, appropriate glucose monitoring, and effective doses of multiple glucose-lowering agents including insulin. (B)
Hyperglycemia defines diabetes, and glycemic control is fundamental to the management of diabetes. The DCCT (71), a prospective RCT of intensive versus standard glycemic control in patients with relatively recently diagnosed type 1 diabetes, showed definitively that improved glycemic control is associated with significantly decreased rates of microvascular (retinopathy and nephropathy) and neuropathic complications. Follow-up of the DCCT cohorts in the Epidemiology of Diabetes Interventions and Complications (EDIC) study (80,81) demonstrated persistence of these microvascular benefits in previously intensively treated subjects, even though their glycemic control approximated that of previous standard arm subjects during follow-up.
The Kumamoto Study (82) and UK Prospective Diabetes Study (UKPDS) (83,84) confirmed that intensive glycemic control was associated with significantly decreased rates of microvascular and neuropathic complications in patients with type 2 diabetes. Long-term follow-up of the UKPDS cohorts showed persistence of the effect of early glycemic control on most microvascular complications (85).
Subsequent trials in patients with more long-standing type 2 diabetes, designed primarily to look at the role of intensive glycemic control on cardiovascular outcomes, also confirmed a benefit, although more modest, on onset or progression of microvascular complications. The Veterans Affairs Diabetes Trial (VADT) showed significant reductions in albuminuria with intensive (achieved median A1C 6.9%) compared with standard glycemic control, but no difference in retinopathy and neuropathy (86,87). The Action in Diabetes and Vascular Disease: Preterax and Diamicron MR Controlled Evaluation (ADVANCE) study of intensive versus standard glycemic control in type 2 diabetes found a statistically significant reduction in albuminuria, but not in neuropathy or retinopathy, with an A1C target of <6.5% (achieved median A1C 6.3%) compared with standard therapy achieving a median A1C of 7.0% (88). Analyses from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial have shown lower rates of onset or progression of early-stage microvascular complications in the intensive glycemic control arm compared with the standard arm (89,90).
Epidemiological analyses of the DCCT and UKPDS (71,72) demonstrate a curvilinear relationship between A1C and microvascular complications. Such analyses suggest that, on a population level, the greatest number of complications will be averted by taking patients from very poor control to fair or good control. These analyses also suggest that further lowering of A1C from 7 to 6% is associated with further reduction in the risk of microvascular complications, albeit the absolute risk reductions become much smaller. Given the substantially increased risk of hypoglycemia (particularly in those with type 1 diabetes, but also in the recent type 2 diabetes trials), the concerning mortality findings in the ACCORD trial (91), and the relatively much greater effort required to achieve near-normoglycemia, the risks of lower glycemic targets may outweigh the potential benefits on microvascular complications on a population level. However, selected individual patients, especially those with little comorbidity and long life expectancy (who may reap the benefits of further lowering of glycemia below 7%), may, based on provider judgment and patient preferences, adopt more intensive glycemic targets (e.g., an A1C target <6.5%) as long as significant hypoglycemia does not become a barrier.
CVD, a more common cause of death in populations with diabetes than microvascular complications, is less clearly impacted by levels of hyperglycemia or the intensity of glycemic control. In the DCCT, there was a trend toward lower risk of CVD events with intensive control, and in 9-year post-DCCT follow-up of the EDIC cohort participants previously randomized to the intensive arm had a significant 57% reduction in the risk of nonfatal myocardial infarction (MI), stroke, or CVD death compared with those previously in the standard arm (92). The benefit of intensive glycemic control in this type 1 diabetic cohort has recently been shown to persist for several decades (93).
In type 2 diabetes, there is evidence that more intensive treatment of glycemia in newly diagnosed patients may reduce long-term CVD rates. During the UKPDS trial, there was a 16% reduction in cardiovascular events (combined fatal or nonfatal MI and sudden death) in the intensive glycemic control arm that did not reach statistical significance (P = 0.052), and there was no suggestion of benefit on other CVD outcomes such as stroke. However, after 10 years of follow-up, those originally randomized to intensive glycemic control had significant long-term reductions in MI (15% with sulfonylurea or insulin as initial pharmacotherapy, 33% with metformin as initial pharmacotherapy) and in all-cause mortality (13% and 27%, respectively) (85).
Three more recent large trials (ACCORD, ADVANCE, and VADT) suggested no significant reduction in CVD outcomes with intensive glycemic control in participants who had more advanced type 2 diabetes than UKPDS participants. All three of these trials were conducted in participants with more long-standing diabetes (mean duration 8&#;11 years) and either known CVD or multiple cardiovascular risk factors. Details of these three studies are reviewed extensively in an ADA position statement (94).
The ACCORD study enrolled participants with either known CVD or two or more major cardiovascular risk factors and randomized them to intensive glycemic control (goal A1C <6%) or standard glycemic control (goal A1C 7&#;8%). The glycemic control comparison was halted early due to the finding of an increased rate of mortality in the intensive arm compared with the standard arm (1.41% vs. 1.14% per year; HR 1.22; 95% CI 1.01&#;1.46), with a similar increase in cardiovascular deaths. This increase in mortality in the intensive glycemic control arm was seen in all prespecified patient subgroups. The primary outcome of ACCORD (nonfatal MI, nonfatal stroke, or cardiovascular death) was nonsignificantly lower in the intensive glycemic control group due to a reduction in nonfatal MI, both when the glycemic control comparison was halted and all participants transitioned to the standard glycemic control intervention (91), and at completion of the planned follow-up (95).
Exploratory analyses of the mortality findings of ACCORD (evaluating variables including weight gain, use of any specific drug or drug combination, and hypoglycemia) were reportedly unable to identify a clear explanation for the excess mortality in the intensive arm (91). The ACCORD investigators subsequently published additional epidemiological analyses showing no increase in mortality in the intensive arm participants who achieved A1C levels below 7% nor in those who lowered their A1C quickly after trial enrollment. In fact, although there was no A1C level at which intensive arm participants had significantly lower mortality than standard arm participants, the highest risk for mortality was observed in intensive arm participants with the highest A1C levels (96).
The role of hypoglycemia in the excess mortality findings was also complex. Severe hypoglycemia was significantly more likely in participants randomized to the intensive glycemic control arm. However, excess mortality in the intensive versus standard arms was only significant for participants with no severe hypoglycemia, and not for those with one or more episodes. Severe hypoglycemia was associated with excess mortality in either arm, but the association was stronger in those randomized to the standard glycemic control arm (97). Unlike the case with the DCCT trial, where lower achieved A1C levels were related to significantly increased rates of severe hypoglycemia, in ACCORD every 1% decline in A1C from baseline to 4 months into the trial was associated with a significant decrease in the rate of severe hypoglycemia in both arms (96).
The primary outcome of ADVANCE was a combination of microvascular events (nephropathy and retinopathy) and major adverse cardiovascular events (MI, stroke, and cardiovascular death). Intensive glycemic control (to a goal A1C <6.5% vs. treatment to local standards) significantly reduced the primary end point. However, this was due to a significant reduction in the microvascular outcome, primarily development of macroalbuminuria, with no significant reduction in the macrovascular outcome. There was no difference in overall or cardiovascular mortality between the intensive compared with the standard glycemic control arms (88).
The VADT randomized participants with type 2 diabetes uncontrolled on insulin or maximal-dose oral agents (median entry A1C 9.4%) to a strategy of intensive glycemic control (goal A1C <6.0%) or standard glycemic control, with a planned A1C separation of at least 1.5%. The primary outcome of the VADT was a composite of CVD events. The cumulative primary outcome was nonsignificantly lower in the intensive arm (86). An ancillary study of the VADT demonstrated that intensive glycemic control significantly reduced the primary CVD outcome in individuals with less atherosclerosis at baseline (assessed by coronary calcium) but not in persons with more extensive baseline atherosclerosis (98). A post hoc analysis showed a complex relationship between duration of diabetes before glycemic intensification and mortality: mortality in the intensive vs. standard glycemic control arm was inversely related to duration of diabetes at the time of study enrollment. Those with diabetes duration less than 15 years had a mortality benefit in the intensive arm, while those with duration of 20 years or more had higher mortality in the intensive arm (99).
The evidence for a cardiovascular benefit of intensive glycemic control primarily rests on long-term follow-up of study cohorts treated early in the course of type 1 and type 2 diabetes and subset analyses of ACCORD, ADVANCE, and VADT. A group-level meta-analysis of the latter three trials suggests that glucose lowering has a modest (9%) but statistically significant reduction in major CVD outcomes, primarily nonfatal MI, with no significant effect on mortality. However, heterogeneity of the mortality effects across studies was noted, precluding firm summary measures of the mortality effects. A prespecified subgroup analysis suggested that major CVD outcome reduction occurred in patients without known CVD at baseline (HR 0.84, 95% CI 0.74&#;0.94) (100). Conversely, the mortality findings in ACCORD and subgroup analyses of the VADT suggest that the potential risks of intensive glycemic control may outweigh its benefits in some patients, such as those with very long duration of diabetes, known history of severe hypoglycemia, advanced atherosclerosis, and advanced age/frailty. Certainly, providers should be vigilant in preventing severe hypoglycemia in patients with advanced disease and should not aggressively attempt to achieve near-normal A1C levels in patients in whom such a target cannot be safely and reasonably easily achieved. Severe or frequent hypoglycemia is an absolute indication for the modification of treatment regimens, including setting higher glycemic goals. Many factors, including patient preferences, should be taken into account when developing a patient&#;s individualized goals (101).
Recommended glycemic goals for many nonpregnant adults are shown in Table 9. The recommendations are based on those for A1C values, with listed blood glucose levels that appear to correlate with achievement of an A1C of <7%. The issue of pre- versus postprandial SMBG targets is complex (102). Elevated postchallenge (2-h OGTT) glucose values have been associated with increased cardiovascular risk independent of FPG in some epidemiological studies. In diabetic subjects, some surrogate measures of vascular pathology, such as endothelial dysfunction, are negatively affected by postprandial hyperglycemia (103). It is clear that postprandial hyperglycemia, like preprandial hyperglycemia, contributes to elevated A1C levels, with its relative contribution being higher at A1C levels that are closer to 7%. However, outcome studies have clearly shown A1C to be the primary predictor of complications, and landmark glycemic control trials such as the DCCT and UKPDS relied overwhelmingly on preprandial SMBG. Additionally, an RCT in patients with known CVD found no CVD benefit of insulin regimens targeting postprandial glucose compared with those targeting preprandial glucose (104). A reasonable recommendation for postprandial testing and targets is that for individuals who have premeal glucose values within target but have A1C values above target, monitoring postprandial plasma glucose (PPG) 1&#;2 h after the start of the meal and treatment aimed at reducing PPG values to <180 mg/dL may help lower A1C.
Table 9
Summary of glycemic recommendations for many nonpregnant adults with diabetes
A1C <7.0%* Preprandial capillary plasma glucose 70&#;130 mg/dL* (3.9&#;7.2 mmol/L) Peak postprandial capillary plasma glucose&#; <180 mg/dL* (<10.0 mmol/L) &#;*Goals should be individualized based on: duration of diabetes age/life expectancy comorbid conditions known CVD or advanced microvascular complications hypoglycemia unawareness individual patient considerations &#; More or less stringent glycemic goals may be appropriate for individual patients &#; Postprandial glucose may be targeted if A1C goals are not met despite reaching preprandial glucose goals A1C <7.0%* Preprandial capillary plasma glucose 70&#;130 mg/dL* (3.9&#;7.2 mmol/L) Peak postprandial capillary plasma glucose&#; <180 mg/dL* (<10.0 mmol/L) &#;*Goals should be individualized based on: duration of diabetes age/life expectancy comorbid conditions known CVD or advanced microvascular complications hypoglycemia unawareness individual patient considerations &#; More or less stringent glycemic goals may be appropriate for individual patients &#; Postprandial glucose may be targeted if A1C goals are not met despite reaching preprandial glucose goals View LargeGlycemic goals for children are provided in Section VIII.A.1.a. As regards goals for glycemic control for women with GDM, recommendations from the Fifth International Workshop-Conference on Gestational Diabetes Mellitus (105) were to target maternal capillary glucose concentrations of:
preprandial: &#;95 mg/dL (5.3 mmol/L), and either:
1-h postmeal: &#;140 mg/dL (7.8 mmol/L) or
2-h postmeal: &#;120 mg/dL (6.7 mmol/L)
For women with pre-existing type 1 or type 2 diabetes who become pregnant, a recent consensus statement (106) recommended the following as optimal glycemic goals, if they can be achieved without excessive hypoglycemia:
premeal, bedtime, and overnight glucose 60&#;99 mg/dL (3.3&#;5.4 mmol/L)
peak postprandial glucose 100&#;129 mg/dL (5.4&#;7.1 mmol/L)
A1C <6.0%
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Based on this review, the studies that showed more satisfactory results in healing diabetic wounds were those who applied energy densities in the range of 3-5 J/cm2, power densities equal to or below 0.2 W/cm2 and continuous emission. The He-Ne laser with a wavelength of 632.8 nm was used more often.
consisted of bibliographic searching the databases Bireme, SciELO, PubMed/Medline and Lilacs by using the keywords related to the topic. Were selected from these keywords, papers discussing the use of laser on wounds associated with diabetes, published in the period -, in Portuguese or English.
To determine the most effective parameter in healing wounds related to diabetes mellitus, as well as the most widely used type of laser.
The article discusses the results of a literature review on the application of low intensity laser therapy on the healing of wounds associated diabetes mellitus in the last 10 years.
Diabetes mellitus (DM) comprises a set of metabolic diseases resulting from changes in the secretion and/or action of insulin produced by the pancreas. Its main feature is the hyperglycemia associated with dysfunction of various systems, such as cardiovascular, renal and nervous.1
After tissue injury, scarring occurs through four phases: hemostasis, inflammation, proliferation and remodeling. These phases involve a cascade of events that will add and promote the repair of the lesion. The action of growth factors such as VEGF (Vascular Endothelial Growth Factor), FGF (fibroblast growth factor) and TGF-β (Transforming Growth Factor β) is essential since it stimulates fibroblast proliferation and collagen, as well as the neovascularization, important for scar formation. When any of these components is changed, there is a commitment of tissue repair and the wound becomes chronic. 2
In diabetic subjects, there is an endothelial dysfunction, which alters the performance of these cells, such as the proliferation, migration and angiogenesis ability, hampering the consolidation of this process. 3 This dysregulation, associated with the presence of neuropathy and consequent reduction in sensitivity, predisposes the emergence of ulcers. 4
The deficiency in the wound healing process is a complex problem not only for the diabetic patient and family, but also for the government, since the high-risk of the existing infection may culminate in the patient's limb and own life impairment, burdening the system with social security expenses. 5-6
Due to this dysfunction, several studies have been conducted aiming to assist in wound healing of patients and to reduce morbidity and mortality caused by them. Among the reported therapeutic methods, there is the Low Level Laser Therapy (LLLT).
The low level laser therapy is considered an effective therapeutic method in wound healing when certain factors are properly observed, such as dosage, power input, time and interval between sessions. 7 It promotes the reduction of the inflammatory phase, favoring the angiogenesis and the production of extracellular matrix components, as well as its organization.8-9
In addition to reducing the lesion area and accelerating the healing process, laser therapy has the advantage of being easily administered. These benefits assist in promoting patient quality of life and minimizing possible complications. 10-11
Research conducted in vitro and in vivo, aiming at wound healing by LLLT, have different protocols. The types of low intensity lasers often found in the literature are Helium and Neon (He-Ne), Gallium-Aluminum-Arsenide (GaAlAs) Aluminum-Gallium-Indium-Phosphorous (AlGaInP) and Gallium-Arsenide (GaAs).12 Parameters such as energy density, power, wave shape and length, beam and application time show wide divergence between studies. Dosage appears as one of the most disparate, ranging from 0.04 to 30 J/cm2.12,13
The densities used can often be inappropriate for the phase in which the wound is. In wound healing in diabetes, different doses will promote the stimulation or inhibition of this process. Thus, it is important to note, among the most commonly used protocols, which ones proved to be beneficial, so the effectiveness of photostimulation is not compromised. 14
The random use of these parameters for the same purpose highlights the need for standardization in laser therapy. The objective of this study, therefore, was to check the most effective parameter in the healing of wounds associated with diabetes mellitus, as well as the most commonly used type of laser.
For more information, please visit Low Level Laser Therapy For Hyperglycemia.