Diffferent Readings From Cgm Vs. Traditional Glucose Monitor

Cureus. 2019 Sep; xi(9): e5634.

Continuous Glucose Monitoring Versus Cocky-monitoring of Claret Glucose in Type 2 Diabetes Mellitus: A Systematic Review with Meta-analysis

Monitoring Editor: Alexander Muacevic and John R Adler

Rajesh Naidu Janapala

^ane Internal Medicine, Icahn School of Medicine at Mountain Sinai/Queens Hospital Center, New York, United states of america

Joseph South Jayaraj

ⁱⁱ Internal Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

Nida Fathima

ⁱⁱ Internal Medicine, California Found of Behavioral Neurosciences and Psychology, Fairfield, USA

Tooba Kashif

² Internal Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

Norina Usman

^three Internal Medicine, Veterans Affairs Palo Alto Wellness Intendance System - Stanford University Schoolhouse of Medicine, Palo Alto, Us

Amulya Dasari

² Internal Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

Nusrat Jahan

² Internal Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, U.s.a.

Issac Sachmechi

^ane Internal Medicine, Icahn School of Medicine at Mount Sinai/Queens Hospital Center, New York, USA

Received 2019 Aug 26; Accustomed 2019 Sep 12.

Abstract

Every eleventh adult has diabetes, and every third has prediabetes. Over 95% of diabetics are of type ii. It is well established that diabetes doubles the run a risk of eye disease and stroke autonomously from increasing the risk of microvascular complications. Hence, strict glycemic control is necessary. Even so, it increases the risk of hypoglycemia, especially in patients with longstanding diabetes. Continuous glucose monitors (CGM) utilize a sensor to continuously measure out the glucose levels in the interstitial fluid every 10 seconds and gives out hateful values every five minutes. CGMs are emerging tools in the management of type 2 diabetes. The prime objective of this review is to notice out if there is plenty supporting bear witness, suggesting that continuous glucose monitoring is more effective than cocky-monitoring of claret glucose (SMBG) in type ii diabetes. We conducted a systematic literature search in Medline (PubMed) looking for any studies addressing our objective. It is observed that in that location is a varying level of evidence supporting that employing a CGM can reduce glycated hemoglobin (HbA1c), hypoglycemic events, and increment patient satisfaction. However, some studies reported no significant benefits. This systematic review with meta-analysis concludes that the use of CGM in blazon two diabetes mellitus (T2DM) is benign, as it significantly reduces HbA1c compared to the usual method of SMBG. The pooled mean difference in HbA1c was -0.25 (-0.45, -0.06) and statistically significant (at p = 0.01) when comparing CGM to SMBG.

Keywords: continuous glucose monitor, blazon 2 diabetes mellitus, self-monitoring of blood glucose, real-fourth dimension glucose monitoring, fourth dimension in range, glucose variability

Introduction

The International Diabetes Federation estimates that one in every eleven adults has diabetes accounting for almost 425 million diabetics in the earth [1]. While the Center for Disease Control and Prevention states that the United States solitary has 30 million diabetics (of whom 95% are type 2 diabetics) and 90 million prediabetics [2]. Autonomously from being the leading crusade of chronic kidney illness, lower-limb amputations, and adult-onset blindness, diabetes also doubles the risk of having heart disease or stroke. Diabetes is the 7th leading cause of death in the U.s.. The financial burden of diagnosed diabetes is projected as $327 billion yearly, which is going to increment exponentially equally the population is aging and living longer than before.

The Benefits of Continuous glucose monitor (CGM) in type ane diabetic (T1DM) patients when compared to routine glucose testing have been very well established by many studies and are now a vital tool in their diabetes management. However, the benefits of CGM in type 2 diabetics (T2DM) are not well established, and its usage is limited. Every bit nearly of the T2DM patients are elderly, their diabetes management is a challenge due to the co-existence of multiple comorbidities and polypharmacy. Although glycated hemoglobin (HbA1c) is a gold standard marker to assess glycemic control and a well-established marker correlating with increased complications, CGM gives the power to make the diabetes management personalized [3-4]. Though it is well demonstrated that bringing down HbA1c to <7% past an intensive glycemic control decreases the take a chance of microvascular complications, it is associated with an increased adventure of hypoglycemia [5]. With increasing accuracy and features such as hypoglycemia alarms and trends, CGMs tin reduce the hazard of astringent hypoglycemic events. Through this review, nosotros wanted to know if there is enough show to support the efficacy of CMG over self-monitoring of blood glucose (SMBG) in patients with T2DM.

In this commodity, we discussed what is already known, not known, and the emerging trends in the usage of CGM in patients with T2DM. We also discussed the emerging parameters of claret glucose measurements that will potentially supersede HbA1c in guiding treatment decisions. We conducted a meta-analysis compiling data from different studies to know if CGM usage tin effectively reduce HbA1c in T2DM patients.

Materials and methods

In this trial, we conducted a thorough and systematic literature search in MEDLINE (PubMed) through a combination of both Mesh terms and keywords. The following tabular array details the search strategy (Table ​ 1). The search terms were separately developed by 2 authors individually and combined to perform a comprehensive search of relevant literature from the last ten years. Studies were screened for inclusion and exclusion criteria, as mentioned below. The following figure (Figure ​ ane) summarizes the flow of search trial through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) menses diagram [6].

Table ane

Search words and their combined results

MeSh, medical subject headings

Population(P):	Article hits
"Diabetes Mellitus"[Mesh] OR "Diabetes Mellitus, Blazon two"[Mesh]	405131
AND
Intervention(I):
(("continuous glucose monitoring"[All Fields] OR "CGM"[All Fields]) OR "real-fourth dimension glucose monitoring"[All Fields]) OR (continuous [All Fields] AND "measurement"[All Fields]) AND ("glucose"[MeSH Terms] OR "glucose"[All Fields])	4406
AND
Comparison(C):
(("Blood Glucose Self-Monitoring"[Mesh] OR "self glucose monitoring"[All Fields]) OR (intermittent[All Fields] AND ("claret glucose cocky-monitoring"[MeSH Terms] OR ("blood"[All Fields] AND "glucose"[All Fields] AND "self-monitoring"[All Fields]) OR ("blood glucose cocky-monitoring"[All Fields]) OR ("self"[All Fields] AND "claret"[All Fields] AND "glucose"[All Fields] AND "monitoring"[All Fields]) OR ("self blood glucose monitoring"[All Fields])) OR "Home glucose monitoring"[All Fields]	6313
AND
Outcomes(O):
((((((((("Glycated Hemoglobin A"[Mesh] OR "hemoglobin A1c"[All Fields]) OR "HbA1c"[All Fields]) OR "Hypoglycemia"[Mesh]) OR "Hypoglycemic episodes"[All Fields]) OR "Hypoglycemic episode"[All Fields]) OR "low blood glucose"[All Fields]) OR "ease of use"[All Fields]) OR "convenient"[All Fields]) OR "convenience"[All Fields]) OR "user-friendly"[All Fields]	175204
Final Search results:	628

Summary of study period (PRISMA menstruation diagram)

PRISMA = preferred reporting items for systematic reviews and meta-analyses, RCT = randomised controlled trial, n = number of results

Inclusion

1. Studies that compare CGM of blood glucose to SMBG (or other routine methods for monitoring hyperglycemia) in T2DM patient (≥xix years of age)

2. Studies that measure out HbA1c as an outcome and has a baseline mean HbA1c ≥6.v%

iii. Articles that are in English or other languages if a translated version in English language is readily available.

Exclusion

i. Studies involving significant women

2. In-patient population

Statistical assay

The statistical analysis is planned to be carried out with Review Manage v.3 (RevMan 5.3). The master outcome to be measured in this review is the deviation of mean HbA1c in the CGM group compared to the SMBG group at the finish of the studies. In a randomized command trial, it is causeless that difference in concluding mean measurements volition on average exist the identical estimate of the departure in mean alter measurements. Heterogeneity volition exist determined by I² static. I² 50% or more is regarded equally substantial heterogeneity among the studies. A stock-still-effect model will be used to combine the private study results if heterogeneity is depression (<20 %) or else the random-effects model will exist used.

Results

Information extraction and quality appraisal

Information extracted from the randomised control trials (RCT) from our literature search are shown in Tabular array ​ two.

Table 2

Data extracted from the RCTs

n = full number of subjects, I = number of subjects in the intervention group (CGM grouping), C = number of subjects in the command group (SMBG group), RCT = randomised command trial

[vii-11]

	Starting time author/Year of publication	Study population	Study Duration	CGM usage duration	Outcomes compared to command group			Limitations
					HbA1c	Hypoglycemia	Ease of apply/ Quality of life
i	Brook RW et al., 2017	north=158 I=79 C=79	24 Weeks/six months	Daily usage for 24 weeks	The adjusted difference in mean alter for CGM group and control group is  -0.3% [95% CI, -0.5% to 0.0%]; P = 0.022)	Did not differ meaningfully in measured hypoglycemia	Did not differ meaningfully in Quality of life measures. However, the CGM group had high satisfaction with use of CGM	Study duration. CGM-measured hypoglycemia was extremely low at baseline, which express the ability to assess the issue of CGM on reducing hypoglycemia.
2	Yoo HJ et al., 2008	north = 65  I =  32 C = 33	12 weeks/ three months	Monthly three days at a time for three months	Significantly reduced (ix.1 ± 1.0% to 8.0 ± ane.2% vs. 8.7 ± 0.7% to viii.3 ± 1.1%, respectively; P = 0.004)	No pregnant difference between the groups	Significant reduction in total daily calorie intake, weight, body mass index (BMI), and postprandial glucose level, and a significant increase in total practice time per week.	Small study population and short written report duration
iii	Ehrhardt NM et al., 2011 and Vigersky RA et al., 2012	northward = 100   I = l C = fifty	12 weeks of intervention and 52-calendar week long term follow upwards	12 weeks of intermittent usage	Pregnant decrease in hateful, unadjusted HbA1c at end of 12 weeks of intermittent CGM usage (one.0% vs0.5%) and sustained at week 40(0.8%vs 0.2%)  (P = 0.04). Average, statistically adapted Pass up of          -0.48% (p = .006)	Not assessed	No difference in Weight, Claret pressure, and The Problem Areas in Diabetes (PAID) scores.	Small study population, a slight variation in baseline characteristics (age)
four	Sato J et al., 2016	north = 34  I = 17 C = 17	Eight months	Four to five days of usage on three separate occasions	No pregnant difference in the change of HbA1c at the end of the study	Fourth dimension spent in hypoglycemia was virtually goose egg in both groups both at baseline and at the end of the study. Hence the difference between the groups was not appreciated.	Based on changes in Diabetes Handling Satisfaction Questionnaire (DTSQ) scores, No significant improvement in patient satisfaction.	pocket-size sample size
five	Cosson E et al., 2009	n = 25  I = 11 C = 14	three months	48 hrs.	significantly reduced (mean: –0.63±0.34%; P= 0.05 vs –0.31±0.29%; P= 0.eighteen, respectively)	No significant difference betwixt the groups	Most patients reported no or mild pain, while mixed reporting on bothersome of the device due to its bulkiness.	Pocket-sized study population and curt study duration

Quality assessment was washed in duplicate past two authors independently for all the RCTs using the latest revised Cochrane Risk-of-Bias (RoB) tool for randomized trials [thirteen]. The summary of the risk of bias for the vi randomized trials is shown illustratively in Figure ​ 2. During the quality assessment, whatsoever discrepancy between the authors was solved after word with a 3rd writer. Five of the six studies shown to have a low run a risk of bias, while one study proved to have some concerns [7-12]. A systemic review from our search was assessed for quality with the AMSTAR checklist [14]. All other studies were evaluated for their quality using report type-specific Disquisitional Appraisal Checklist from Joanna Briggs Constitute (JBI) [15]. Each questionnaire has ten-11 questions. Each question was given one point. A study scoring five or fewer points was considered having a high take chances of bias.

Illustrative summary of RoB of the RCTs

RoB = Adventure-of-bias, RCT = randomized command trials

All the studies were thoroughly comprehended, and their relevant historical bibliographic references were searched for all pertinent information. Later excluding studies that accept data only from T1DM patients and including studies that take data from only T2DM patients or mixed population (only with subgroup data and analysis for T2DM), resulted in six RCTs. Ii of these studies reported information for the same written report at unlike time points (1 after the intervention and some other one after long term follow-up without intervention) [9-10]. Hence, only five studies were included in the meta-analysis.

The five RCTs studied 382 T2DM patients that met our written report criteria with 189 patients being in the CGM grouping and 193 in the control group. However, in a report, three subjects in the intervention group and five subjects in the control grouping dropped out and were not included in that studies' final analysis [8]. Hence, our meta-assay has 374 total T2DM patients, which include 186 in the CGM group and 188 in the SMBG group. The studies lasted in a range of three to eight months in duration. The baseline HbA1c levels ranged between 6.ix% to 12%. Moreover, the cumulative hateful HbA1c for all the five RCTs was eight.53% (0.91) at baseline, indicating poorly controlled diabetes.

Meta-assay

Cumulative assay of the data from all 5 RCTs was washed using RevMan 5 tool. The fixed-upshot model was used to combine the results as the heterogeneity was very low (I² = 0%), suggesting minimal variation across studies. The cumulative analysis of data from all the five RCTs showed that CGM usage in T2DM patients decreased HbA1c past 0.25% (with a 95% conviction interval between 0.45 and 0.06) compared to SMBG (p = 0.01). The pooled mean difference in Hba1c was -0.25 (-0.45, -0.06) with statistical significance of (p = 0.01) comparing CGM to SMBG. A woods plot illustrating the aforementioned is shown in the figure (Effigy ​ 3). The funnel plot (Figure ​ 4) shows that no publication bias was observed.

Mean deviation of HbA1c between CGM and SMBG groups at the end of respective studies and their pooled analysis

CGM = continuous glucose monitoring, SMBG = self-monitoring of blood glucose, SD = standard deviation, CI = confidence interval

Funnel plot for the five RCTs comparing CGM to SMBG in T2DM

MD = mean deviation, SE = standard error, RCTs = randomized control trials, CGM = continuous glucose monitor, SMBG = self-monitoring of blood glucose, T2DM = type 2 diabetes mellitus

Discussion

CGMs are the latest tools in the management of diabetes. The first CGM was approved by the Food and Drug Administration in 1999. Since then they kept evolving from a big device with concrete wires to the sensor to present-days virtually painless small sensors that communicate wirelessly with their receivers. Current commercially bachelor CGMs comes with different features and functions, but the main idea is that they have a sensor that is usually attached to the skin either over the abdomen or back of the arms. The tip of the sensor lies in the interstitial fluid measuring interstitial glucose level every ten seconds, then giving out an average reading every five minutes and up to 288 readings in a day, which is then transmitted to the receiver or smartphone wirelessly.

This review discusses all the aspects of CGM in type the diabetics that nosotros came through our literature review. The CGM group or intervention group was compared to a control group that was using either an SMBG with multiple finger sticks or other routine methods. Most studies emphasized on the following areas when measuring the outcome of using CGM in T2DM patients. These include HbA1c, hypoglycemia, glucose variability, and patient satisfaction.

HbA1c

Alter in the HbA1c was the primary outcome in most of the studies that focused on CGM usage in T2DM. Most studies take demonstrated a reduction in HbA1c with the utilise of CGM when compared to the controls [7-10,13,16,17]. Yet, a study washed in a university hospital in Japan and published in 2016 demonstrated no meaning change in HbA1c when compared to command [11]. It is noted that the study sample size was very small compared to other studies. In our meta-assay, the analysis of pooled information from 5 RCTs showed that CGM was more effective in reducing HbA1c (mean departure of -0.25 and 95% confidence interval between -0.45and -0.06) compared to SMBG with a statistical significance of more than 95% (p = 0.01). The cumulative hateful HbA1c of the 5 RCTs was 8.53% (0.91) at the baseline, indicates that CGM was effective in T2DM patients with poorly controlled diabetes. It was observed that 14 days of CGM usage provided a reasonable guess of mean glucose, fourth dimension in range, and hyperglycemia measures for 3 months [xviii]. Collecting information for additional days did not prove to improve correlation to standard glucose metrics like HbA1c and hateful glucose. Twelve weeks of intermittent usage of Real Time-CGM (RT-CGM) has shown non but to reduce HbA1c but also the effect was sustained at week xl, even after the discontinuation of CGM at 12 weeks [10]. This demonstrated that even short-term usage of CGM was beneficial, which might be due to the constant feedback of nutrition-related glucose variations resulting in patients becoming more aware of what foods to choose. This feedback mechanism leads to good for you lifestyle modification, which is very much needed in patients with T2DM.

Hypoglycemia

Hypoglycemic episodes could become a prime indication for choosing CGM by intendance providers in the management of their patient's diabetes. Tighter glycemic control is express past events of Hypoglycemia. Long-standing diabetes leads to peripheral neuropathy and can reduce hypoglycemic awareness in the elderly. It is observed that in the elderly with diabetes, hypoglycemia is a more common crusade for hospitalization than hyperglycemia [19]. It besides increases the risk of mortality.

Studies demonstrated that CGMs detected a significantly college number of hypoglycemic events than the SMBG or symptomatic hypoglycemia [xx-23]. It is noticed that the hypoglycemic episodes were predominantly nocturnal [17,21,22,24]. Hence, naturally, they volition go unnoticed by the patient or patient'due south partner, which makes the timely rescue challenging and increases the risk of mortality. CGMs with alarms to extreme glycemic excursions help in detecting impending severe hypoglycemic episodes and helps accept timely action. Notwithstanding, information technology is noted that some studies accept shown that CGM data did not differ significantly from the controls], which may be explained by the fact that these populations could exist relatively good for you with bottom glycemic excursions [seven,10,12]. Therefore, these studies have insufficient ability in detecting a significant difference between the groups.

Glucose variability and time in range

HbA1c and SMBG tin accurately approximate the mean glucose values, just they lack the ability to look for glycemic excursions. It is observed that most hyperglycemia occurs post postprandially while nearly hypoglycemia occurs during the dark, which is missed by T2DM patients who routinely do finger pricks in the morning time and earlier meals. On the other hand, HbA1c just correlates with mean blood glucose levels leaving out extreme values. Additionally, studies have reported that obesity could falsely evidence low HbA1c [25].

Extensive glycemic data yielded past the CGMs can assistance overcome the above limitations. They tin report the time spent in specific glycemic ranges in a day. That is, they can written report the amount of time spent with glycemic levels ≤lxx mg/dl, between 70 and 180mg/dl and ≥180 mg/dl. Even custom glycemic ranges tin can be set to personalize the direction. The emerging new parameter in diabetes management is Time in Range (TIR). Studies accept demonstrated that CGM usage helped in increasing the fourth dimension spent in TIR and decrease in fourth dimension spent in hypoglycemia and hyperglycemia [7,ten,26]. As of at present, there is no standardized range for TIR, merely the most acceptable range is between 70 and 180 mg/dl below 70 mg/dl is regarded as hypoglycemia and above 180 mg/dl as hyperglycemia. Efforts are being made to standardize the CGM metrics, including TIR, in establishing the goals for diabetes management. American Diabetic Association has presented recommendations for TIR in Type 1 and two diabetics as betwixt lxx and 180 mg/dl in June 2019 [27].

Patient satisfaction

Patient satisfaction is one of the critical aspects that decide if the CGM tin can be used in daily life. Dissimilar the HbA1c (which is washed one time in three months) or SMBG (which is performed once or twice daily in virtually blazon 2 diabetics), a CGM device is attached to a patient's trunk throughout the day for vii to xiv days or more. Unless the patients are satisfied with the accurateness, usability, and the benefits of the device, they might not be motivated to wear them. Surprisingly, one report reported very high compliance with CGM usage; almost 97% of the subjects used information technology for six or more days per week for half dozen months. A satisfaction survey at the finish of the trial indicated very high satisfaction with CGM [26]. Some other studies also demonstrated similarly high satisfaction [seven,28].

One study observed that in that location was a significant reduction in daily calorie intake, trunk mass index, postprandial glucose levels, and increased practice time per week in patients using CGM for three sequent days within three months [x]. Real-time glucose data might serve equally a motivational tool for patients, as they receive real-fourth dimension feedback on their diet and exercise, encouraging them to adopt a healthy lifestyle in the long term. Still, some studies reported no pregnant difference in weight, blood force per unit area, Problem Areas in Diabetes (PAID) scores, or patient satisfaction [viii-9,11].

Personal and professional CGM devices

CGM devices can be classified equally professional CGM devices and personal CGM devices. Personal CGM devices display real-time glucose measurements to patients. Which helps patients understand the furnishings of diet and lifestyle on their blood glucose levels. CGMs can act as a motivational tool and besides guide medication dosage in patients using insulin. They as well alert patients to extreme glucose excursions. Professional CGM devices are blinded to patients. They provide retrospective data which is mainly used by healthcare providers in making necessary changes to the patient's diabetes regimen. They are worn by the patient generally for a menstruation of seven days, and and so the data is downloaded by the healthcare provider. Professional CGM has demonstrated that information technology improves both glycemic command and cost outcomes in patients over a wide range of baseline therapies [17,29]. One study noticed that professional CGM devices provided the maximal do good for patients with a baseline HbA1c level of 7% or above [17]. Currently, CGM devices are expensive and are not covered past about insurance providers for T2DM. Yet, professional CGM devices can be price-effective and user-friendly. Thus, they can be potentially incorporated into principal care.

Limitations of CGM devices

Like any other tool in managing diabetes CGM devices too suffer from some limitations. Currently, the about limiting gene for its integration into routine diabetic care is the cost. CGM devices are expensive and prescription but. The initial cost may exceed over $m for the device, and a monthly supply of sensors may cost over $300. Some of the devices need a fingerstick glucose test done to calibrate the CGM device frequently. This may be annoying for patients as they cannot rely on the CGM data itself, especially with extreme readings. However, the current generation of CGM devices are improving in accuracy and are mill calibrated; hence, they do not need end-user calibration. 1 of the prime number reasons for adopting CGM devices for some patients is to manage their hypoglycemia. However, information technology is to be noted that CGM devices evidence increasingly inaccurate results at depression glucose ranges. Unlike finger stick tests where the glucose levels are measured in capillary blood, CGM devices measure it in the interstitial fluid. There is a time lag of 5 to 20 minutes before the vascular and interstitial glucose levels equilibrate. Hence, they can be unreliable at times, especially during rapid fluctuations. Some people may experience uncomfortable to wear a device that is stuck on their skin all the fourth dimension. Lastly, Personal CGM devices might not be beneficial only by wearing them, without any insight and motivation to make lifestyle modifications in line with the feedback from the real-time glycemic data.

Limitations of this review

This review has many limitations. Chiefly, the literature search was conducted but in ane electronic database, Medline (PubMed) database. Some relevant and disquisitional studies that are not PubMed indexed might have been missed. Studies published in other than the English language (except if their translated version is readily available) accept not been reviewed. No detailed sensitivity assay is performed due to the pocket-size sample size of the studies. No explicit cost-benefit or brunt has been studied in this review.

Conclusions

The benefits of CGM in T1DM patients have been well established. Yet, relatively few studies accept been conducted in T2DM patients, and nearly of them are of less than six months in elapsing. Although a significant corporeality of evidence suggests that the usage of CGM in the management of T2DM is associated with benefits of reduction in HbA1c (from our meta-analysis) especially in poorly controlled T2DM patients, the sample size and study durations are as well small to generalize the results. We meet the need for RCTs with larger sample sizes and longer durations to institute the above beneficial effects. The metrics of CGM take to exist standardized so that they tin be widely adopted into clinical practice. Guidelines for the indication of a CGM in T2DM take to be established.

Notes

The content published in Cureus is the result of clinical feel and/or inquiry past contained individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of information or conclusions published herein. All content published inside Cureus is intended only for educational, inquiry and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional person. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors accept declared that no competing interests exist.

Human Ethics

Consent was obtained by all participants in this study

Animal Ethics

Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue.

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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822918/

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