HbAc monitoring frequency -
Adult haemoglobin HbA is the main form of haemoglobin but small amounts of fetal haemoglobin HbF and haemoglobin A2 also occur. The glycated haemoglobins include haemoglobin A1a, b and c. Interpretation of results is limited by factors that affect the relationship between HbA1c and average overall glycaemia Table 2.
Furthermore, HbA1c does not reflect the swings in blood glucose, which can be as clinically important as overall glycaemia. Patients could have the same HbA1c but with frequent episodes of hypo- and hyperglycaemia or with stable glycaemia.
As noted earlier, HbA1c testing and self BGM are complementary and provide information about different aspects of glycaemic control.
The level of HbA1c is also affected by some pathophysiological conditions and some laboratory factors 7 Table 2. Different forms of haemoglobin interact with the laboratory re-agents and have variable effects on the relationship between HbA1c and average blood glucose.
The different HbA1c assays may be affected by a wide range of factors including clinical conditions, medications and haemoglobinopathies. When HbA1c does not reliably assess average glycaemia Table 2 , alternate ways of assessing glycaemic control include self BGM and measuring other glycosylated proteins such as fructosamine.
Clinical review might indicate some remediable medical condition Table 2 and the laboratory may be able to use another assay method which will make the HbA1c reliable. If not, there are two alternatives to HbA1c testing to monitor overall glycaemia:.
There are two developments in diagnosis and reporting that may be implemented in Australia in — 9. There may also be a move toward more point-ofcare testing which is being used in some areas of Australia, particularly remote settings.
Beverley was only testing the fasting blood glucose generally the lowest over the 24 hour period. Tests at other times were much higher, explaining the HbA1c result.
John had haemoglobinopathy, causing a spuriously low result in the laboratory's usual testing method. With a different assay system, the HbA1c was 8. Australian Family Physician.
Search for: Search AFP. Filter Relevance Date. Issues by year. Volume 41, Issue 1, January-February Download article Cite this article BIBTEX REFER RIS. It considers areas such as indications, what to tell the patient, what the test can and cannot tell you, and interpretation of results.
When should HbA1c be ordered? What do I tell my patient? How does the test work? Table 1. Assays for HbA1c Methods Analysis principle HbA1c specificity Ion exchange chromatography HPLC Slight changes in the isoelectric point Specific for HbA1c Boronate affinity resin Structural differences cause binding to the resin All glycated haemoglobin Figure 1 Immunoassay Antibody to the changed structure of the N-terminal beta chain Varying specificity for HbA1c What do the results mean?
References Medicare Benefits Schedule. MBS online. Available at www. Search PubMed National Institute of Clinical Studies Evidence-Practice Gaps Report. Volume 1. NICS: Melbourne. pdf [Accessed 16 December ]. Search PubMed Diabetes Control and Complications Trial Research Group. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin—dependent diabetes mellitus.
N Engl J Med ;— Search PubMed United Kingdom Prospective Diabetes Study Group UKPDS. Intensive blood glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in people with diabetes.
Lancet ;— Furthermore, our findings are associative and do not imply causality, though they do indicate an area of study warranting further investigation. The 5. These data indicate that at the population level, lack of conformity to the monitoring frequency for HbA 1c recommended in national guidance, whatever the underlying cause, is associated with suboptimal diabetes control and hence potentially increased risk of comorbidities and poorer patient outcomes.
The role of monitoring frequency in this important area therefore requires further study. Importantly, the study has two wider implications: first, it illustrates the power and limitations of using existing laboratory data sets to address key clinical questions and, second, while we have concentrated on HbA 1c , this approach provides a model that is applicable to the use of other monitoring tests in a range of other chronic diseases.
The authors are grateful to the members of Diabetes UK North Staffordshire Branch and Stoke-on-Trent Community Health Voice for advice and feedback on the patient aspects of the study. This study was supported by a National Institute for Health Research Healthcare Scientist Fellowship award to O.
and O. Duality of Interest. No potential conflicts of interest relevant to this article were reported. Author Contributions. wrote the manuscript, performed the data analysis, and provided clinical advice and critique from a clinical laboratory scientist perspective.
performed the data analysis. performed the data extraction from the three centers. provided clinical advice and critique from a clinical laboratory scientist perspective. and F. provided clinical advice and critique from a clinical diabetologist perspective. supervised the statistical analysis.
wrote the manuscript and provided clinical advice and critique from a clinical laboratory scientist perspective. All authors reviewed and edited the manuscript.
is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Prior Presentation. The initial findings of this study were presented at FOCUS, the Association for Clinical Biochemistry National Meeting, York, U. Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest. filter your search All Content All Journals Diabetes Care.
Advanced Search. User Tools Dropdown. Sign In. Skip Nav Destination Close navigation menu Article navigation. Volume 37, Issue Previous Article Next Article. Research Design and Methods. Article Information.
Article Navigation. Reduced Testing Frequency for Glycated Hemoglobin, HbA 1c , Is Associated With Deteriorating Diabetes Control Owen J.
Driskell ; Owen J. This Site. Google Scholar. David Holland ; David Holland. Jenna L. Waldron ; Jenna L. Clare Ford ; Clare Ford. Jonathan J. Scargill ; Jonathan J. Adrian Heald ; Adrian Heald. Martin Tran ; Martin Tran. Fahmy W. Hanna ; Fahmy W. Peter W.
Jones ; Peter W. John Pemberton ; R. John Pemberton. Anthony A. Fryer Anthony A. Corresponding author: Anthony A. Fryer, anthony. fryer uhns. Diabetes Care ;37 10 — Article history Received:. Connected Content. A reference has been published: In This Issue of Diabetes Care. All patients gave written informed consent.
Exclusion criteria were hypoglycemia-unawareness and serious co-morbidity evaluated by the treating GPs. Patients were randomly assigned to one of the three groups at the first study visit with block randomization, using blocks of 17 and 16, with sealed non-transparent envelopes, containing letters A, B or C.
Patients were instructed to perform a 4-point SMBG; before meals and bedtime. Group A, B and C performed 4-point SMBG every week, every 2 weeks and every month, respectively. Using validated blood glucose monitors [ 8 ] patients were instructed to record in their study diary, all additional SMBG measurements and the reason for taking extra measurements.
Extra glucose measurements in patients with worsening glycemic control were allowed, patients and health care providers were advised to return to the allocated SMBG frequency as soon as was possible.
End-points were collected during routine visits and all patients received usual care offered by their healthcare providers. In the Netherlands routine visits, including HbA1c, take place every 3 months.
No financial compensation was provided. A difference of 5. Secondary endpoints were health-related quality of life and diabetes self-care.
Other endpoints were the number of recorded hypo- and hyperglycemic events and the fasting blood glucose concentrations. Data collected at baseline included: diabetes duration, duration of SMBG, medication, blood pressure, length, weight, smoking status, alcohol status and micro- and macrovascular complications yes or no.
Data on additional diabetes-related contacts with the healthcare provider and changes in diabetes medication were recorded in the study diaries. At baseline and 9 months, three validated questionnaires were completed.
The item Short Form Health Survey SF [ 12 , 13 ], the Problem Areas in Diabetes PAID [ 14 ]. Higher scores indicate higher emotional distress. The Summary of Diabetes Self Care Activities SDSCA [ 15 ], see Additional file 1 for more information on the questionnaires.
This was calculated using software PASS To detect a relevant difference in HbA1c of 5. The SD was derived from the prospective ZODIAC cohort [ 16 ], no randomized trials with a comparable research question were available. Data entry was performed in duplicate and statistical analyses were carried out by a statistician blinded for treatment allocation.
Study end-points were analyzed using a mixed model. Fixed factors were study arm and total number of SGBM; patients were random factors and baseline HbA1c was a covariate. The fasting blood glucose concentrations were used to investigate if there were differences between the blood glucose concentrations, with baseline fasting blood glucose concentrations as covariates.
Bonferroni correction was used to adjust for multiple testing. The response variables smoking and alcohol use were coded into binary variables and analyzed using Generalized Linear Models GLM , with a binary distribution and logit link function.
Analyses were performed according to the intention-to-treat principle. p values were tested two-tailed. Sixty-six patients were randomized, 8 withdrew consent shortly after randomization before completion of baseline measurements and 58 patients participated.
Six patients were lost for follow-up and 52 were randomised. See Fig. The study stopped prematurely due to the slow anticipated inclusion rate during the study period.
Reasons provided for the slow recruitment rate were primarily difficulty of finding patients with a stable glycemic control who mostly were used to specific SMBG frequency for a long time, who wanted to change SMBG frequency for the duration of the study.
Other arguments were lack of time, participation in other trials and lack of financial compensation by care providers. The baseline characteristics are presented in Table 1. All patients reported to be compliant with their insulin injection. See Additional file 1 on changes in insulin dose.
Table 2 shows HbA1c levels at different time points and the estimated changes from baseline to 9 months. There were no significant changes within and between groups. Subgroup of patients who were compliant with the allocated SMBG frequency and analysis in fasting capillary glucose concentrations, see Additional file 1.
The changes in the outcome of the SF, PAID and SDSCA are presented in Additional file 1. There were significant changes between the groups in only two dimensions of the SF, the subscale role limitation emotional problems and vitality. In improvement in vitality was most pronounced the lowest SMBG frequency.
Eight patients reported at least one mild hypoglycemic event and consequently performed extra SMBG measurements; 2 patients in group A, 3 in group B and 3 in group C. No glucose values below three were reported.
No symptoms of hypoglycemia were reported. Three intensities of performing 4-point SMBG; weekly, every 2 weeks, every month, were compared in patients with T2DM, who used one long-acting insulin injection daily and had a stable glycemic control for at least 12 months.
There were no significant differences in glycemic control, quality of life, diabetes self care activities, fasting blood glucose or hypoglycemia events.
This is the first study that evaluated effects of 3 different SMBG frequencies on glycemic control and quality of life in patients with T2DM with stable control. SMBG is used for monitoring occurrence of possible hypoglycemia and improving glycemic controls [ 17 ]. Several studies indicated that SMBG potentially also has an impact on quality of life [ 3 ].
Whether more intensive SMBG negatively affects quality of life in patients with a stable glycemic control is unknown. The evidence for efficacy of SMBG is somewhat conflicting concerning HbA1c [ 2 , 18 , 19 , 20 ].
Some reported no significant relationships between SMBG and HbA1c [ 21 , 22 ]. While in other studies, results indicated that SMBG resulted in improvements in HbA1c in the order of 3. Most previous studies were either not randomized, included patients with unstable glycemic control or patients using more intensive insulin regimens [ 2 , 18 , 19 , 20 ].
Although this is the first study to investigate both SMBG frequency and QoL, it was unfortunate that there was a lower then anticipated inclusion rate.
There were a variety of reasons for the slow recruitment rate. The most important reason reported by GPs was that those with a stable glycemic control were used to specific SMBG frequencies and did not want to change SMBG frequency for the duration of the study.
This is the first study investigating effects of SMBG in stable patients, in this study there were no significant between-group differences in glycemic control or quality between 3 frequencies of 4-point SMBG in patients with T2DM with stable glycemic control using one insulin injection.
The study was limited by a slower then anticipated inclusion rate. It was difficult to recruit patients with a stable glycemic control.
Nevertheless, it could be very interesting to repeat this study, with extra focus on recruitment rate and for example financial compensation for patients, to establish whether the currently advised intensive SMBG in this patient group is warranted.
The major limitation of this study was the inability to recruit the pre-planned patients. We were able to include 58 patients in the predefined time frame. Another limitation was that in the absence of results from randomized trials, the assumptions for the sample size calculation were derived from patients included in the prospective ZODIAC cohort study [ 16 ].
Retrospectively, it could have been that the assumptions on which the power calculation was based were inaccurate. Although the upper bounds of the confidence intervals which were within the pre-specified relevancy margin of 5.
This confidence interval could indicate that either no relevant differences were to be expected or it could indicate the presence of a type 2 error. The assumptions for the power calculation were, in the absence of comparable randomized trials, based on prospective observational cohort data and in retrospect, could even have been too conservative.
Other limitations were the relatively wide confidence intervals of the results from the analysis of the subscales of the SF and the SDSCA, which could point to a lack of power. Although the results were bonferroni corrected, the significant difference in the SF subscale vitality could still be the results of multiple testing.
Furthermore, we did not collect information on SMBG habits prior to randomization nor checked whether medication use collected from patient dairies corresponded to actual medication compliance.
Compliance was checked by self-reports using study diaries not on glucose readings from patients glucose monitors. The cut-off for hypoglycemia a priori was set at 3. We also acknowledge that the recommended SMBG frequencies vary substantially between health care providers and between countries [ 6 , 24 ].
In nine patients the insulin dose was changed which effected the between group differences. A strength was the real life setting were for example extra glucose measurements and dose changes of insulin in patients with worsening glycemic control were allowed. Other strengths were; the use of different frequencies of SMBG, based on recommendations made in the Dutch guideline currently used in daily practice [ 6 ].
Nathan DM, McKitrick C, Larkin M, Schaffran R, Singer DE. Glycemic control in diabetes mellitus: have changes in therapy made a difference? Am J Med. Article CAS PubMed Google Scholar. Self-monitoring of blood glucose levels and glycemic control: the Northern California Kaiser Permanente Diabetes registry.
Hortensius J, Kars MC, Wierenga WS, Kleefstra N, Bilo HJ, van der Bijl JJ. Perspectives of patients with type 1 or insulin-treated type 2 diabetes on self-monitoring of blood glucose: a qualitative study.
BMC Public Health. Article PubMed PubMed Central Google Scholar.
HbAc monitoring frequency means it's frequebcy. Federal government websites often end in. HbAc monitoring frequency or. Before sharing sensitive information, make sure you're on a federal government site. The site is secure. NCBI Bookshelf. All of RWT Moonitoring Repository. Diabetes and Monitring Services. Reduced testing HbAc monitoring frequency for glycated hemoglobin, HbA1c, is associated with deteriorating diabetes control. No Thumbnail Available. Authors Waldron, Jenna. Issue Date Type Multicentre Study Peer-Reviewed Publication.
In addition, monitofing will Pancreatic trauma HbAc monitoring frequency monitkring a frequencu should konitoring in Plant-based muscle building to benefit a HbAc monitoring frequency and help to modify their therapy mlnitoring response to fluctuating disease states.
Monitorinh diabetes diagnosis and omnitoring one of Hunger statistics worldwide primary HbAc monitoring frequency mointoring is a hemoglobin HbAc monitoring frequency, or HbA1c, test.
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In addition HbA1c testing monioring no HbAc monitoring frequency requirement from the patient and is not dependent on any sort of prandial status which means that it may be taken at any time day or night. Finally, glucose testing must be sent to the laboratory for measurement within thirty to sixty minutes from the time it was sampled.
The protein analyzed in HbA1c testing is capable of remaining stable for over a week if kept refrigerated. With the dramatic rise in the prevalence of diabetes comes an associated increase in the amount of HbA1c testing that is required.
In Ontario during andthe total number of HbA1c tests completed was 3. During the same period 1. It has been estimated that the health related expenditures for patients with diabetes are at least 2. This brings to the forefront the need to determine an optimal frequency for HbA1c testing in order to manage both healthcare budgets and productivity.
While published guidelines have described treatment goals and give minimum limits for testing frequency there is a lack of defining criteria for the maximum number of tests or the optimal testing frequency for ideal control.
In addition to this problem, previous studies demonstrate that testing is used in patients who do not require it, such as in those who are not diabetic, and those who have had no history of problems with glycemic control. HbA1c testing is typically done twice yearly in well controlled patients and four times yearly in poorly controlled individuals.
Studies have shown that both over and under-utilization trends are commonplace in clinical practice. For example it has been found that some individual patients have received a total of 28 HbA1c tests in a single year.
The reverse of this has also been found where individual patients are only tested one time in a two year long period. The purpose of this report is to examine the evidence on the effect of different testing frequencies for HbA1c and discuss the guidelines governing the timing of use.
Copyright © Canadian Agency for Drugs and Technologies in Health. Publication types Review.
: HbAc monitoring frequency| When should HbA1c be ordered? | Quality and Outcomes Framework, a voluntary incentive scheme for general practices in the U. This could be achieved using a testing frequency significantly lower than that that suggested by NICE, ADA, and others and certainly less than the 3-monthly interval implied by our data. These findings strongly suggest that U. Quality and Outcomes Framework indicators should be reviewed if maximum benefit to patients is to be achieved. While this study indicates the overall optimum testing frequency for HbA 1c in a large population of patients with diabetes across three centers, there are a number of limitations to the study. Similarly, it does not provide data on the reason for the interval between tests. We have previously shown that a range of patient and systemic factors, as well as those associated with health care professionals, can influence testing frequency Furthermore, our findings are associative and do not imply causality, though they do indicate an area of study warranting further investigation. The 5. These data indicate that at the population level, lack of conformity to the monitoring frequency for HbA 1c recommended in national guidance, whatever the underlying cause, is associated with suboptimal diabetes control and hence potentially increased risk of comorbidities and poorer patient outcomes. The role of monitoring frequency in this important area therefore requires further study. Importantly, the study has two wider implications: first, it illustrates the power and limitations of using existing laboratory data sets to address key clinical questions and, second, while we have concentrated on HbA 1c , this approach provides a model that is applicable to the use of other monitoring tests in a range of other chronic diseases. The authors are grateful to the members of Diabetes UK North Staffordshire Branch and Stoke-on-Trent Community Health Voice for advice and feedback on the patient aspects of the study. This study was supported by a National Institute for Health Research Healthcare Scientist Fellowship award to O. and O. Duality of Interest. No potential conflicts of interest relevant to this article were reported. Author Contributions. wrote the manuscript, performed the data analysis, and provided clinical advice and critique from a clinical laboratory scientist perspective. performed the data analysis. performed the data extraction from the three centers. provided clinical advice and critique from a clinical laboratory scientist perspective. and F. provided clinical advice and critique from a clinical diabetologist perspective. supervised the statistical analysis. wrote the manuscript and provided clinical advice and critique from a clinical laboratory scientist perspective. All authors reviewed and edited the manuscript. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Prior Presentation. The initial findings of this study were presented at FOCUS, the Association for Clinical Biochemistry National Meeting, York, U. Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest. filter your search All Content All Journals Diabetes Care. Advanced Search. User Tools Dropdown. Sign In. Skip Nav Destination Close navigation menu Article navigation. Volume 37, Issue Previous Article Next Article. Research Design and Methods. Article Information. Article Navigation. Reduced Testing Frequency for Glycated Hemoglobin, HbA 1c , Is Associated With Deteriorating Diabetes Control Owen J. Driskell ; Owen J. This Site. Google Scholar. David Holland ; David Holland. Jenna L. Waldron ; Jenna L. Clare Ford ; Clare Ford. Jonathan J. Scargill ; Jonathan J. Adrian Heald ; Adrian Heald. Martin Tran ; Martin Tran. Fahmy W. Hanna ; Fahmy W. Peter W. Jones ; Peter W. John Pemberton ; R. John Pemberton. Anthony A. Fryer Anthony A. Corresponding author: Anthony A. Fryer, anthony. fryer uhns. Diabetes Care ;37 10 — Article history Received:. Connected Content. A reference has been published: In This Issue of Diabetes Care. Get Permissions. toolbar search Search Dropdown Menu. toolbar search search input Search input auto suggest. Table 1 Patient demographics. North Staffordshire. Number of repeat requests 73, , , Mean age ± SD years View Large. where A is the analytical variation and B is the biological variation. Figure 1. View large Download slide. Figure 2. Figure 3. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes UKPDS 35 : prospective observational study. Search ADS. National Institute for Health and Clinical Excellence. Type 1 diabetes CG15 [article online], Accessed 3 January Type 2 diabetes CG66 [article online], American Diabetes Association. Inappropriate requesting of glycated hemoglobin Hb A1c is widespread: assessment of prevalence, impact of national guidance, and practice-to-practice variability. Variation in the frequency of hemoglobin A1c HbA1c testing: population studies used to assess compliance with clinical practice guidelines and use of HbA1c to screen for diabetes. Monitoring glycaemic control: is there evidence for appropriate use of routine measurement of glycated haemoglobin. World Health Organization. Use of glycated haemoglobin HbA1c in the diagnosis of diabetes mellitus [article online], Office of National Statistics. The changes in the outcome of the SF, PAID and SDSCA are presented in Additional file 1. There were significant changes between the groups in only two dimensions of the SF, the subscale role limitation emotional problems and vitality. In improvement in vitality was most pronounced the lowest SMBG frequency. Eight patients reported at least one mild hypoglycemic event and consequently performed extra SMBG measurements; 2 patients in group A, 3 in group B and 3 in group C. No glucose values below three were reported. No symptoms of hypoglycemia were reported. Three intensities of performing 4-point SMBG; weekly, every 2 weeks, every month, were compared in patients with T2DM, who used one long-acting insulin injection daily and had a stable glycemic control for at least 12 months. There were no significant differences in glycemic control, quality of life, diabetes self care activities, fasting blood glucose or hypoglycemia events. This is the first study that evaluated effects of 3 different SMBG frequencies on glycemic control and quality of life in patients with T2DM with stable control. SMBG is used for monitoring occurrence of possible hypoglycemia and improving glycemic controls [ 17 ]. Several studies indicated that SMBG potentially also has an impact on quality of life [ 3 ]. Whether more intensive SMBG negatively affects quality of life in patients with a stable glycemic control is unknown. The evidence for efficacy of SMBG is somewhat conflicting concerning HbA1c [ 2 , 18 , 19 , 20 ]. Some reported no significant relationships between SMBG and HbA1c [ 21 , 22 ]. While in other studies, results indicated that SMBG resulted in improvements in HbA1c in the order of 3. Most previous studies were either not randomized, included patients with unstable glycemic control or patients using more intensive insulin regimens [ 2 , 18 , 19 , 20 ]. Although this is the first study to investigate both SMBG frequency and QoL, it was unfortunate that there was a lower then anticipated inclusion rate. There were a variety of reasons for the slow recruitment rate. The most important reason reported by GPs was that those with a stable glycemic control were used to specific SMBG frequencies and did not want to change SMBG frequency for the duration of the study. This is the first study investigating effects of SMBG in stable patients, in this study there were no significant between-group differences in glycemic control or quality between 3 frequencies of 4-point SMBG in patients with T2DM with stable glycemic control using one insulin injection. The study was limited by a slower then anticipated inclusion rate. It was difficult to recruit patients with a stable glycemic control. Nevertheless, it could be very interesting to repeat this study, with extra focus on recruitment rate and for example financial compensation for patients, to establish whether the currently advised intensive SMBG in this patient group is warranted. The major limitation of this study was the inability to recruit the pre-planned patients. We were able to include 58 patients in the predefined time frame. Another limitation was that in the absence of results from randomized trials, the assumptions for the sample size calculation were derived from patients included in the prospective ZODIAC cohort study [ 16 ]. Retrospectively, it could have been that the assumptions on which the power calculation was based were inaccurate. Although the upper bounds of the confidence intervals which were within the pre-specified relevancy margin of 5. This confidence interval could indicate that either no relevant differences were to be expected or it could indicate the presence of a type 2 error. The assumptions for the power calculation were, in the absence of comparable randomized trials, based on prospective observational cohort data and in retrospect, could even have been too conservative. Other limitations were the relatively wide confidence intervals of the results from the analysis of the subscales of the SF and the SDSCA, which could point to a lack of power. Although the results were bonferroni corrected, the significant difference in the SF subscale vitality could still be the results of multiple testing. Furthermore, we did not collect information on SMBG habits prior to randomization nor checked whether medication use collected from patient dairies corresponded to actual medication compliance. Compliance was checked by self-reports using study diaries not on glucose readings from patients glucose monitors. The cut-off for hypoglycemia a priori was set at 3. We also acknowledge that the recommended SMBG frequencies vary substantially between health care providers and between countries [ 6 , 24 ]. In nine patients the insulin dose was changed which effected the between group differences. A strength was the real life setting were for example extra glucose measurements and dose changes of insulin in patients with worsening glycemic control were allowed. Other strengths were; the use of different frequencies of SMBG, based on recommendations made in the Dutch guideline currently used in daily practice [ 6 ]. Nathan DM, McKitrick C, Larkin M, Schaffran R, Singer DE. Glycemic control in diabetes mellitus: have changes in therapy made a difference? Am J Med. Article CAS PubMed Google Scholar. Self-monitoring of blood glucose levels and glycemic control: the Northern California Kaiser Permanente Diabetes registry. Hortensius J, Kars MC, Wierenga WS, Kleefstra N, Bilo HJ, van der Bijl JJ. Perspectives of patients with type 1 or insulin-treated type 2 diabetes on self-monitoring of blood glucose: a qualitative study. BMC Public Health. Article PubMed PubMed Central Google Scholar. Vincze G, Barner JC, Lopez D. Factors associated with adherence to self-monitoring of blood glucose among persons with diabetes. Diab Educ. Article Google Scholar. Barriers and behaviours in blood glucose monitoring. US Endocr Dis. Google Scholar. Hortensius J, Kleefstra N, Houweling ST, van der Bijl JJ, Gans RO, Bilo HJ. What do professionals recommend regarding the frequency of self-monitoring of blood glucose? Neth J Med. CAS PubMed Google Scholar. Federation DD. Multidisciplinary guideline self-monitoring of blood glucose by people with diabetes. Accessed 1 Dec Berard LD, Blumer I, Houlden R, Miller D, Woo V. Monitoring glycemic control. Can J Diab. American Diabetes. Standards of medical care in diabetes— Diabetes Care. Kleefstra N, Hortensius J, Logtenberg SJ, Slingerland RJ, Groenier KH, Houweling ST, Gans RO, van Ballegooie E, Bilo HJ. Self-monitoring of blood glucose in tablet-treated type 2 diabetic patients ZODIAC. Kleefstra N, Hortensius J, van Hateren KJ, Logtenberg SJ, Houweling ST, Gans RO, Bilo HJ. Self-monitoring of blood glucose in noninsulin-treated type 2 diabetes: an overview. Diab Metabol Syndr Obes Targets Ther. Article CAS Google Scholar. Gandek B, Ware JE, Aaronson NK, Apolone G, Bjorner JB, Brazier JE, Bullinger M, Kaasa S, Leplege A, Prieto L, Sullivan M. Cross-validation of item selection and scoring for the SF Health Survey in nine countries: results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol. Keller SD, Majkut TC, Kosinski M, Ware JE Jr. Monitoring health outcomes among patients with arthritis using the SF Health Survey: overview. Med Care. Snoek FJ, Pouwer F, Welch GW, Polonsky WH. Diabetes-related emotional distress in Dutch and U. diabetic patients: cross-cultural validity of the problem areas in diabetes scale. Toobert DJ, Hampson SE, Glasgow RE. The summary of diabetes self-care activities measure: results from 7 studies and a revised scale. Ubink-Veltmaat LJ, Bilo HJ, Groenier KH, Houweling ST, Rischen RO, Meyboom-de Jong B. Prevalence, incidence and mortality of type 2 diabetes mellitus revisited: a prospective population-based study in The Netherlands ZODIAC Eur J Epidemiol. World Health Organization. Adherence to long-term therapies. Evidence for action. Geneva: WHO; Murata GH, Shah JH, Hoffman RM, Wendel CS, Adam KD, Solvas PA, Bokhari SU, Duckworth WC, S. Diabetes Outcomes in Veterans. Intensified blood glucose monitoring improves glycemic control in stable, insulin-treated veterans with type 2 diabetes: the Diabetes Outcomes in Veterans Study DOVES. Article PubMed Google Scholar. Schutt M, Kern W, Krause U, Busch P, Dapp A, Grziwotz R, Mayer I, Rosenbauer J, Wagner C, Zimmermann A, Kerner W, Holl RW, DPV Initiative. Is the frequency of self-monitoring of blood glucose related to long-term metabolic control? Multicenter analysis including 24, patients from centers in Germany and Austria. Exp Clin Endocrinol Diab. Secnik K, Yurgin N, Lage MJ, McDonald-Everett C. Patterns of blood glucose monitoring in relation to glycemic control among patients with type 2 diabetes in the UK. J Diabetes Complications. Evans JM, Newton RW, Ruta DA, MacDonald TM, Stevenson RJ, Morris AD. Frequency of blood glucose monitoring in relation to glycaemic control: observational study with diabetes database. Article CAS PubMed PubMed Central Google Scholar. Harris MI, National H, S. Nutrition Examination. Frequency of blood glucose monitoring in relation to glycemic control in patients with type 2 diabetes. International Hypoglycaemia Study. Glucose concentrations of less than 3. Hortensius J, van der Bijl JJ, Kleefstra N, Houweling ST, Bilo HJ. Self-monitoring of blood glucose: professional advice and daily practice of patients with diabetes. Download references. Study design: JH, NK, BH, KHG and JvdB. Data collection: JH. Analysis and interpretation of the data: JH, NK, BH, GWDL, KHG and JvdB. Manuscript preparation: JH, GWDL, NK, BH, KHG, JvdB and HB. All authors read and approved the final manuscript. The authors gratefully acknowledge the diabetes teams from the general practices for their contribution. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Langerhans Medical Research Group, Ommen, The Netherlands. Johanna Hortensius, Nanne Kleefstra, Gijs W. Department of Internal Medicine, University Medical Center Groningen and University of Groningen, Groningen, The Netherlands. Department of Internal Medicine, Gelre Hospitals Apeldoorn, Albert Schweitzerlaan 31, DZ, Apeldoorn, The Netherlands. Department of Epidemiology, University Medical Center Groningen and University of Groningen, Groningen, The Netherlands. Department of General Practice, University Medical Center Groningen and University of Groningen, Groningen, The Netherlands. Faculty of Health, Welfare and Sports, Inholland University of Applied Sciences, Amsterdam, The Netherlands. Stichting Onderzoekscentrum Ketenzorg Chronische Ziekten, Zwolle, The Netherlands. You can also search for this author in PubMed Google Scholar. Correspondence to Gijs W. Questionnaire outcomes, additional methodology and results. Changes in questionnaires outcome, the SF, PAID and SDSCA, after 9 months. Additional results. Subgroup analyses of patients who were compliant with the allocated SMBG frequency. |
| Research Design and Methods | Hortensius Montoring, Kleefstra N, HgAc ST, monitorlng der Bijl JJ, Gans RO, HbAc monitoring frequency Monutoring. HbAc monitoring frequency may have slight pain or bruising at the Blood sugar control and eye health where the needle was put in, but most symptoms go away quickly. View Metrics. Monitoring health outcomes among patients with arthritis using the SF Health Survey: overview. Glucose has the ability to attach to hemoglobin in the blood and form hemoglobin A1c. Data collected at baseline included: diabetes duration, duration of SMBG, medication, blood pressure, length, weight, smoking status, alcohol status and micro- and macrovascular complications yes or no. |
| About the Test | SMBG is mostly studied in patients who have worsening glycemic control and unnecessary intense SMBG in patients with a stable glycemic control could negatively affect quality of life [ 3 , 4 , 5 ]. There are no studies comparing effects of different SMBG frequencies on both glycemic control and quality of life in patients with T2DM treated with one insulin injection daily or a stable glycemic control. In the Netherlands, 4-point before meals and before bedtime SMBG is advices once every 1—2 weeks in patients on insulin, although there are relevant differences in advices given by individual healthcare providers [ 6 ]. The largest between health-care provider differences in SMBG frequency recommendations concern those using basal insulin [ 6 , 7 , 8 , 9 ]. The aim of the study was to investigate effects of three different frequencies of 4-point SMBG on glycemic control and quality of life in patients with T2DM with stable glycemic control using one long-acting insulin injection daily. The study design aimed reflect the real life primary care setting in which SMBG is applied in the Netherlands. A multi-centre, open label, randomized, parallel group design. Three different frequencies of 4-point SMBG before meals and bedtime were compared during a 9-month intervention period. The study was carried out between March and October The study and the informed consent procedure were approved by the local medical ethics committee of the Isala Hospital, Zwolle, The Netherlands. All patients gave written informed consent. Exclusion criteria were hypoglycemia-unawareness and serious co-morbidity evaluated by the treating GPs. Patients were randomly assigned to one of the three groups at the first study visit with block randomization, using blocks of 17 and 16, with sealed non-transparent envelopes, containing letters A, B or C. Patients were instructed to perform a 4-point SMBG; before meals and bedtime. Group A, B and C performed 4-point SMBG every week, every 2 weeks and every month, respectively. Using validated blood glucose monitors [ 8 ] patients were instructed to record in their study diary, all additional SMBG measurements and the reason for taking extra measurements. Extra glucose measurements in patients with worsening glycemic control were allowed, patients and health care providers were advised to return to the allocated SMBG frequency as soon as was possible. End-points were collected during routine visits and all patients received usual care offered by their healthcare providers. In the Netherlands routine visits, including HbA1c, take place every 3 months. No financial compensation was provided. A difference of 5. Secondary endpoints were health-related quality of life and diabetes self-care. Other endpoints were the number of recorded hypo- and hyperglycemic events and the fasting blood glucose concentrations. Data collected at baseline included: diabetes duration, duration of SMBG, medication, blood pressure, length, weight, smoking status, alcohol status and micro- and macrovascular complications yes or no. Data on additional diabetes-related contacts with the healthcare provider and changes in diabetes medication were recorded in the study diaries. At baseline and 9 months, three validated questionnaires were completed. The item Short Form Health Survey SF [ 12 , 13 ], the Problem Areas in Diabetes PAID [ 14 ]. Higher scores indicate higher emotional distress. The Summary of Diabetes Self Care Activities SDSCA [ 15 ], see Additional file 1 for more information on the questionnaires. This was calculated using software PASS To detect a relevant difference in HbA1c of 5. The SD was derived from the prospective ZODIAC cohort [ 16 ], no randomized trials with a comparable research question were available. Data entry was performed in duplicate and statistical analyses were carried out by a statistician blinded for treatment allocation. Study end-points were analyzed using a mixed model. Fixed factors were study arm and total number of SGBM; patients were random factors and baseline HbA1c was a covariate. The fasting blood glucose concentrations were used to investigate if there were differences between the blood glucose concentrations, with baseline fasting blood glucose concentrations as covariates. Bonferroni correction was used to adjust for multiple testing. The response variables smoking and alcohol use were coded into binary variables and analyzed using Generalized Linear Models GLM , with a binary distribution and logit link function. Analyses were performed according to the intention-to-treat principle. p values were tested two-tailed. Sixty-six patients were randomized, 8 withdrew consent shortly after randomization before completion of baseline measurements and 58 patients participated. Six patients were lost for follow-up and 52 were randomised. See Fig. The study stopped prematurely due to the slow anticipated inclusion rate during the study period. Reasons provided for the slow recruitment rate were primarily difficulty of finding patients with a stable glycemic control who mostly were used to specific SMBG frequency for a long time, who wanted to change SMBG frequency for the duration of the study. Other arguments were lack of time, participation in other trials and lack of financial compensation by care providers. The baseline characteristics are presented in Table 1. All patients reported to be compliant with their insulin injection. See Additional file 1 on changes in insulin dose. Table 2 shows HbA1c levels at different time points and the estimated changes from baseline to 9 months. There were no significant changes within and between groups. Subgroup of patients who were compliant with the allocated SMBG frequency and analysis in fasting capillary glucose concentrations, see Additional file 1. The changes in the outcome of the SF, PAID and SDSCA are presented in Additional file 1. There were significant changes between the groups in only two dimensions of the SF, the subscale role limitation emotional problems and vitality. In improvement in vitality was most pronounced the lowest SMBG frequency. Eight patients reported at least one mild hypoglycemic event and consequently performed extra SMBG measurements; 2 patients in group A, 3 in group B and 3 in group C. No glucose values below three were reported. No symptoms of hypoglycemia were reported. Three intensities of performing 4-point SMBG; weekly, every 2 weeks, every month, were compared in patients with T2DM, who used one long-acting insulin injection daily and had a stable glycemic control for at least 12 months. There were no significant differences in glycemic control, quality of life, diabetes self care activities, fasting blood glucose or hypoglycemia events. This is the first study that evaluated effects of 3 different SMBG frequencies on glycemic control and quality of life in patients with T2DM with stable control. SMBG is used for monitoring occurrence of possible hypoglycemia and improving glycemic controls [ 17 ]. Several studies indicated that SMBG potentially also has an impact on quality of life [ 3 ]. Whether more intensive SMBG negatively affects quality of life in patients with a stable glycemic control is unknown. The evidence for efficacy of SMBG is somewhat conflicting concerning HbA1c [ 2 , 18 , 19 , 20 ]. Some reported no significant relationships between SMBG and HbA1c [ 21 , 22 ]. While in other studies, results indicated that SMBG resulted in improvements in HbA1c in the order of 3. Most previous studies were either not randomized, included patients with unstable glycemic control or patients using more intensive insulin regimens [ 2 , 18 , 19 , 20 ]. Although this is the first study to investigate both SMBG frequency and QoL, it was unfortunate that there was a lower then anticipated inclusion rate. There were a variety of reasons for the slow recruitment rate. The most important reason reported by GPs was that those with a stable glycemic control were used to specific SMBG frequencies and did not want to change SMBG frequency for the duration of the study. This is the first study investigating effects of SMBG in stable patients, in this study there were no significant between-group differences in glycemic control or quality between 3 frequencies of 4-point SMBG in patients with T2DM with stable glycemic control using one insulin injection. The study was limited by a slower then anticipated inclusion rate. It was difficult to recruit patients with a stable glycemic control. Nevertheless, it could be very interesting to repeat this study, with extra focus on recruitment rate and for example financial compensation for patients, to establish whether the currently advised intensive SMBG in this patient group is warranted. The major limitation of this study was the inability to recruit the pre-planned patients. We were able to include 58 patients in the predefined time frame. Another limitation was that in the absence of results from randomized trials, the assumptions for the sample size calculation were derived from patients included in the prospective ZODIAC cohort study [ 16 ]. Retrospectively, it could have been that the assumptions on which the power calculation was based were inaccurate. Although the upper bounds of the confidence intervals which were within the pre-specified relevancy margin of 5. This confidence interval could indicate that either no relevant differences were to be expected or it could indicate the presence of a type 2 error. The assumptions for the power calculation were, in the absence of comparable randomized trials, based on prospective observational cohort data and in retrospect, could even have been too conservative. Other limitations were the relatively wide confidence intervals of the results from the analysis of the subscales of the SF and the SDSCA, which could point to a lack of power. Although the results were bonferroni corrected, the significant difference in the SF subscale vitality could still be the results of multiple testing. Furthermore, we did not collect information on SMBG habits prior to randomization nor checked whether medication use collected from patient dairies corresponded to actual medication compliance. Compliance was checked by self-reports using study diaries not on glucose readings from patients glucose monitors. The cut-off for hypoglycemia a priori was set at 3. We also acknowledge that the recommended SMBG frequencies vary substantially between health care providers and between countries [ 6 , 24 ]. In nine patients the insulin dose was changed which effected the between group differences. A strength was the real life setting were for example extra glucose measurements and dose changes of insulin in patients with worsening glycemic control were allowed. Other strengths were; the use of different frequencies of SMBG, based on recommendations made in the Dutch guideline currently used in daily practice [ 6 ]. Nathan DM, McKitrick C, Larkin M, Schaffran R, Singer DE. Glycemic control in diabetes mellitus: have changes in therapy made a difference? Am J Med. Article CAS PubMed Google Scholar. Self-monitoring of blood glucose levels and glycemic control: the Northern California Kaiser Permanente Diabetes registry. Hortensius J, Kars MC, Wierenga WS, Kleefstra N, Bilo HJ, van der Bijl JJ. Perspectives of patients with type 1 or insulin-treated type 2 diabetes on self-monitoring of blood glucose: a qualitative study. BMC Public Health. Article PubMed PubMed Central Google Scholar. Vincze G, Barner JC, Lopez D. Factors associated with adherence to self-monitoring of blood glucose among persons with diabetes. Diab Educ. Article Google Scholar. Barriers and behaviours in blood glucose monitoring. US Endocr Dis. Google Scholar. Hortensius J, Kleefstra N, Houweling ST, van der Bijl JJ, Gans RO, Bilo HJ. What do professionals recommend regarding the frequency of self-monitoring of blood glucose? Neth J Med. CAS PubMed Google Scholar. Federation DD. Multidisciplinary guideline self-monitoring of blood glucose by people with diabetes. Accessed 1 Dec Berard LD, Blumer I, Houlden R, Miller D, Woo V. Monitoring glycemic control. Can J Diab. American Diabetes. Standards of medical care in diabetes— Diabetes Care. Kleefstra N, Hortensius J, Logtenberg SJ, Slingerland RJ, Groenier KH, Houweling ST, Gans RO, van Ballegooie E, Bilo HJ. Self-monitoring of blood glucose in tablet-treated type 2 diabetic patients ZODIAC. Kleefstra N, Hortensius J, van Hateren KJ, Logtenberg SJ, Houweling ST, Gans RO, Bilo HJ. Self-monitoring of blood glucose in noninsulin-treated type 2 diabetes: an overview. Diab Metabol Syndr Obes Targets Ther. Article CAS Google Scholar. Gandek B, Ware JE, Aaronson NK, Apolone G, Bjorner JB, Brazier JE, Bullinger M, Kaasa S, Leplege A, Prieto L, Sullivan M. Cross-validation of item selection and scoring for the SF Health Survey in nine countries: results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol. Keller SD, Majkut TC, Kosinski M, Ware JE Jr. Monitoring health outcomes among patients with arthritis using the SF Health Survey: overview. Med Care. Snoek FJ, Pouwer F, Welch GW, Polonsky WH. Diabetes-related emotional distress in Dutch and U. diabetic patients: cross-cultural validity of the problem areas in diabetes scale. Driskell , David Holland , Jenna L. Waldron , Clare Ford , Jonathan J. Scargill , Adrian Heald , Martin Tran , Fahmy W. Hanna , Peter W. Jones , R. John Pemberton , Anthony A. Fryer; Reduced Testing Frequency for Glycated Hemoglobin, HbA 1c , Is Associated With Deteriorating Diabetes Control. Diabetes Care 1 October ; 37 10 : — We previously showed that in patients with diabetes mellitus, glycated hemoglobin HbA 1c monitoring outside international guidance on testing frequency is widespread. Here we examined the relationship between testing frequency and diabetes control to test the hypothesis that retest interval is linked to change in HbA 1c level. We examined repeat HbA 1c tests , tests in 79, patients, — processed by three U. clinical laboratories. We examined the relationship between retest interval and 1 percentage change in HbA 1c and 2 proportion of cases showing a significant HbA 1c rise. The effect of demographics factors on these findings was also explored. Testing 3-monthly was associated with a 3. Compared with annual monitoring, 3-monthly testing was associated with a halving of the proportion showing a significant rise in HbA 1c 7—10 vs. These findings provide, in a large, multicenter data set, objective evidence that testing outside guidance on HbA 1c monitoring frequency is associated with a significant detrimental effect on diabetes control. To achieve the optimum downward trajectory in HbA 1c , monitoring frequency should be quarterly, particularly in cases with suboptimal HbA 1c. While this impact appears small, optimizing monitoring frequency across the diabetes population may have major implications for diabetes control and comorbidity risk. The use of glycated hemoglobin HbA 1c to monitor control is a central part of the management of patients with diabetes mellitus. It is well recognized that poor control of diabetes is associated with poorer clinical outcomes and increased risk of complications 1. Hence many professional bodies and national health care agencies worldwide provide recommendations on frequency of monitoring using HbA 1c to help maintain optimal control. In the U. In those with stable diabetes on unchanging therapy, intervals of 6—12 months are recommended. Similar guidance is provided by the American Diabetes Association ADA 4. While these recommendations are well established, conformity to such monitoring program is poor and extremely variable 5 — 7. Despite this guidance on monitoring frequency, there are few data to support the impact of testing frequency on clinical outcome. Utilizing data from laboratory information systems, we examined the link between monitoring frequency interval between individual requests for HbA 1c measurement and change in HbA 1c levels using data on , repeat requests for HbA 1c in 79, patients from three clinical laboratories over a 4-year period to provide evidence to support or otherwise recommendations on monitoring frequency for patients with diabetes. These centers were selected as they use different laboratory information systems North Staffordshire, Clinisys Masterlab; Salford, iSoft Telepath; Wolverhampton, Technidata TD-Synergy and have contrasting patient demographics e. From this data set, we concentrated on repeat requests only, leaving a core data set of , repeat requests in 79, patients. The characteristics of this data set are described in Table 1. During this period, there was little evidence from clinical details supplied with requests that HbA 1c was being used as a diagnostic tool, and we specifically used data collected prior to the implementation of WHO guidance on use of HbA 1c in diagnosis in Using data on intervals between HbA 1c requests categorized into 1-month blocks e. We then examined the impact of patient demographics, center, and initial HbA 1c value on this relationship. To explore the potential impact of biological and analytical variation on these findings, we then examined the proportion of cases with a significant rise based on. Using this equation, assuming a local analytical coefficient of variation for HbA 1c of 3. All statistical analyses were performed using Stata version 12; College Station, TX. χ 2 tests were used to compare differences in proportions and ANOVA for differences in mean differences between categories. As in our previous work 5 , we also recognized that testing intervals were not independent observations they are clustered within patients. We therefore reanalyzed a subset of the data based on a randomly selected single interval from each patient. This analysis produced identical inferences to the complete data set data not shown. Hence, the statistical analyses presented in the results section are based on the complete data set. Table 1 shows the demographic characteristics of the data set across the three centers. Figure 1 shows the relationship between repeat requesting interval categorized in 1-month intervals and percentage change in HbA 1c concentration in the total data set. From 2 months onward, there was a direct relationship between retesting interval and control. The optimum testing frequency in order to maximize the downward trajectory in HbA 1c between two tests was approximately four times per year. Our data also indicate that testing more frequently than 2 months has no benefit over testing every 2—4 months. Relationship between HbA 1c testing interval and overall percentage change in HbA 1c concentration. Number of tests in each category is shown by the floating point white circles using the right-hand vertical axis. We then examined whether patterns were comparable between the three centers and assessed the impact of starting HbA 1c. The Royal Wolverhampton Hospital showed a generally lower increase in HbA 1c after 6 months, perhaps reflecting a higher overall starting HbA 1c concentration Table 1. However, given the similarities, all subsequent analysis was based on the combined data set. These data show that in patients with poor control, the pattern was similar to that seen in the total group, except that 1 there was generally a more marked decrease or more modest increase in change of HbA 1c concentration throughout and, consequently, 2 a downward trajectory in HbA 1c was observed when the interval between tests was up to 8 months, rather than the 6 months as seen in the total group. In order to examine the potential link between monitoring frequency and the risk of major deterioration in control, we then assessed the relationship between testing interval and proportion of patients demonstrating an increase in HbA 1c beyond the normal biological and analytical variation in HbA 1c see research design and methods for definition of significant in this context. Figure 3 shows that irrespective of the baseline HbA 1c , there was a generally linear relationship between interval and the proportion demonstrating a significant increase in HbA 1c , though the slope of this relationship increased with rising initial HbA 1c. Interestingly, only in those cases where the interval was greater than 6 months was a higher initial HbA 1c associated with a marked increase in proportion showing a significant rise in HbA 1c compared with the other two groups. This study describes the relationship between frequency of HbA 1c monitoring and glycemic control in patients with diabetes. The large amount of longitudinal data held in clinical laboratory information systems provides a unique opportunity to relate the patterns of requesting to outcome, though it should be recognized that laboratory records can provide limited access to clinical data. Our data indicate that for a HbA 1c retest interval of more than 2 months, there was a direct relationship between retesting interval and control Fig. This supports recommendations provided in worldwide guidance for patients with unstable diabetes 2 — 4 , Our findings are also in keeping with those of Fu et al. Turchin et al. Similar to that recommended by the ADA, U. guidance suggests, in stable patients on unchanging therapy, a testing frequency of 1—2 times per year 2 — 4. Our data showed a more linear relationship between frequency and change in HbA 1c in these patients. Heianza et al. Our data also suggested that testing more frequently than 2 months had no additional benefit over quarterly testing, supporting U. guidance 2 , 3. We also found a linear relationship between testing frequency and proportion of patients showing a biologically significant increase in HbA 1c. Previous data from our and other groups on requesting patterns indicated that relatively few patients in general practice were tested annually 5 , 6. The U. Quality and Outcomes Framework, a voluntary incentive scheme for general practices in the U. This could be achieved using a testing frequency significantly lower than that that suggested by NICE, ADA, and others and certainly less than the 3-monthly interval implied by our data. These findings strongly suggest that U. Quality and Outcomes Framework indicators should be reviewed if maximum benefit to patients is to be achieved. While this study indicates the overall optimum testing frequency for HbA 1c in a large population of patients with diabetes across three centers, there are a number of limitations to the study. Similarly, it does not provide data on the reason for the interval between tests. We have previously shown that a range of patient and systemic factors, as well as those associated with health care professionals, can influence testing frequency Furthermore, our findings are associative and do not imply causality, though they do indicate an area of study warranting further investigation. The 5. These data indicate that at the population level, lack of conformity to the monitoring frequency for HbA 1c recommended in national guidance, whatever the underlying cause, is associated with suboptimal diabetes control and hence potentially increased risk of comorbidities and poorer patient outcomes. The role of monitoring frequency in this important area therefore requires further study. Importantly, the study has two wider implications: first, it illustrates the power and limitations of using existing laboratory data sets to address key clinical questions and, second, while we have concentrated on HbA 1c , this approach provides a model that is applicable to the use of other monitoring tests in a range of other chronic diseases. The authors are grateful to the members of Diabetes UK North Staffordshire Branch and Stoke-on-Trent Community Health Voice for advice and feedback on the patient aspects of the study. This study was supported by a National Institute for Health Research Healthcare Scientist Fellowship award to O. and O. Duality of Interest. No potential conflicts of interest relevant to this article were reported. Author Contributions. wrote the manuscript, performed the data analysis, and provided clinical advice and critique from a clinical laboratory scientist perspective. performed the data analysis. performed the data extraction from the three centers. provided clinical advice and critique from a clinical laboratory scientist perspective. and F. provided clinical advice and critique from a clinical diabetologist perspective. |
| Hemoglobin A1C (HbA1c) Test: MedlinePlus Medical Test | Glycosylation changes the frequwncy charge and structure of the haemoglobin molecule Energy balance and physical activity the three principles HbAc monitoring frequency used to separate Freequency from HbAc monitoring frequency HbAx members of the haemoglobin HbAc monitoring frequency are HAc on these changes Table 1. All About Your A1C. com [Internet]. The information included in this response is not intended to replace professional medical advice, nor should it be construed as a recommendation for or against the use of a particular health technology. The Summary of Diabetes Self Care Activities SDSCA [ 15 ], see Additional file 1 for more information on the questionnaires. |
| Hemoglobin A1C (HbA1c) Test | Microbiological contamination of spirometers. Lice treatment spray this is the first study Monitoringg investigate both SMBG frequency and HbAd, it was unfortunate monitorin there was a monitorign then anticipated inclusion rate. Open Access This article is distributed under the terms of the Creative Commons Attribution 4. References Medicare Benefits Schedule. Research Key findings on ECGs. Perspectives of patients with type 1 or insulin-treated type 2 diabetes on self-monitoring of blood glucose: a qualitative study. |
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