Monitoring glycaemic control in patients with diabetes mellitus

Sodi, Ravinder; McKay, Kim; Dampetla, Srilatha; Pappachan, Joseph M

doi:10.1136/bmj.k4723

Cited by 11 publications

(9 citation statements)

References 13 publications

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“…25 HbA1c is used to monitor long-term glycemic control as it correlates well with the average blood glucose levels 90 to 120 days before measurement. 25 There is, however, no consensus regarding its role in predicting adverse outcomes in joint arthroplasty surgery. 29 Iorio et al 16 reported similar HbA1c levels in the infected diabetic patients (mean HbA1c, 7.2%; range, 5.1%-11.7%) and the noninfected diabetic patients (mean HbA1c 6.92%; range, 4.7-15.1) in their study of 3468 patients who underwent 4241 primary or revision total hip arthroplasty or total knee arthroplasty, and they concluded that HbA1c levels are not reliable in predicting the risk of infection after total joint arthroplasty.…”

Section: Discussionmentioning

confidence: 99%

“…18 Good glycemic control is integral in diabetic treatment and control of its related complications. 25 HbA1c is used to monitor long-term glycemic control as it correlates well with the average blood glucose levels 90 to 120 days before measurement. 25 There is, however, no consensus regarding its role in predicting adverse outcomes in joint arthroplasty surgery.…”

Section: Discussionmentioning

confidence: 99%

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Results of Hallux Valgus Surgery in Diabetic Patients With Good Glycemic Control

et al. 2020

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Background: Literature is sparse on whether diabetes affects outcomes of hallux valgus surgery. With the rising global prevalence of diabetes and diabetes being an independent predictor of poorer outcomes, particularly in foot and ankle surgery, we aimed to investigate the impact of diabetes on the outcomes of hallux valgus surgery. Methods: We conducted a retrospective comparative cohort study of prospectively collected registry data of 951 feet in 721 patients who underwent surgery for symptomatic hallux valgus between 2007 and 2015 at our institution. All patients with diabetes were identified and matched with patients without diabetes for age, sex, and body mass index in a 1:2 ratio to construct the matched cohorts for analysis. Glycemic control in the diabetic cohort was assessed using preoperative HbA1c. The primary outcome measure was complication rates. Secondary outcomes were (1) deformity correction using the hallux valgus and intermetatarsal angles; (2) patient-reported outcomes using visual analog scale (VAS) for pain, Short Form–36 (SF-36) Physical and Mental Health subscales, and American Orthopaedic Foot & Ankle Society (AOFAS) scores; (3) patient satisfaction; and (4) reoperation rates up to 2 years postoperatively. Forty diabetic patients were identified and matched to 80 nondiabetic patients. Although matching was only performed for age, sex, and body mass index, the diabetic and the nondiabetic cohorts were also similar in hallux valgus severity, preoperative scores, and types of procedures performed. Results: The mean preoperative HbA1c in our diabetic cohort was 7.1%. Both the diabetic and nondiabetic cohorts showed excellent AOFAS and VAS scores with no differences in degree of deformity correction, complication profiles, reoperation rates, outcome scores, and satisfaction at both 6 months and 2 years postoperatively. Conclusion: We believe stringent patient selection was key to reduced complication rates and good outcomes in diabetic patients. Well-selected diabetic patients remain suitable candidates for hallux valgus surgery. Level of Evidence: Level III, retrospective comparative study.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Results of Hallux Valgus Surgery in Diabetic Patients With Good Glycemic Control

et al. 2020

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“…2,3 Glycaemic control is typically measured through either fingerpick blood sugar readings or glycosylated haemoglobin levels (Hba1c). 4 The glycosylated haemoglobin value (Hba1c) reports the amount of glucose bound to haemoglobin molecules, and represents an average of blood sugar control over the preceding 6 weeks prior to the test being taken. 4 There are not "normal values" for Hba1c as such, however the Hba1c value can be used in both the diagnosis of T2DM and monitoring of all types diabetes (although less useful in monitoring gestational diabetes mellitus -GDM.…”

Section: Introductionmentioning

confidence: 99%

Association between glycosylated haemoglobin and outcomes for patients discharged from hospital with diabetes: A health informatics approach

et al. 2021

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Aims/Objectives Extensive research considers associations between inpatient glycaemic control and outcomes during hospital admission; this cautions against overly tight glycaemic targets. Little research considers glycaemic control following hospital discharge. This is despite a clear understanding that people with diabetes are at increased risk of negative outcomes, following discharge. We evaluate absolute and relative Hba1c values, and frequency of Hba1c monitoring, on readmission and mortality rates for people discharged from hospital with diabetes. Methods All discharges (n = 46,357) with diabetes from a major tertiary referral centre over 3 years were extracted, including biochemistry data. We conducted an evaluation of association between Hba1c, mortality and readmission, statistical significance and standardised Cohen’s D effect size calculations. Results 399 patients had a Hba1c performed during their admission. 3,138 patients had a Hba1c within 1 year of discharge. Mean average Hba1c for readmissions was 57.82 vs 60.39 for not readmitted (p = 0.009, Cohen’s D 0.28). Mean average number of days to Hba1c testing in readmitted was 97 vs 113 for those not readmitted (p = 0.00006, Cohen’s D 0.39). Further evaluation of mortality outcomes, cohorts of T1DM and T2DM and association of relative change in Hba1c was performed. Conclusions Lower Hba1c values following discharge from hospital are significantly associated with increased risk of readmission, as is a shorter duration until testing. Similar patterns observed for mortality. Findings particularly prominent for T1DM. Further research needed to consider underlying causation and design of appropriate risk stratification models.

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“…The CPC and CPC+ provide practices with a robust learning system, including actionable data feedback to guide their decision-making 5. Since it is widely known that adequate monitoring of diabetes-related health outcomes is tremendously important to reduce the risk of diabetes complications6–8 both CPC and CPC+ support monitoring of people with type 2 diabetes through health technology data.…”

Section: Introductionmentioning

confidence: 99%

Association between GP participation in a primary care group and monitoring of biomedical and lifestyle target indicators in people with type 2 diabetes: a cohort study (ELZHA cohort-1)

et al. 2020

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ObjectiveWhether care group participation by general practitioners improves delivery of diabetes care is unknown. Using ‘monitoring of biomedical and lifestyle target indicators as recommended by professional guidelines’ as an operationalisation for quality of care, we explored whether (1) in new practices monitoring as recommended improved a year after initial care group participation (aim 1); (2) new practices and experienced practices differed regarding monitoring (aim 2).DesignObservational, real-life cohort study.SettingPrimary care registry data from Eerstelijns Zorggroep Haaglanden (ELZHA) care group.ParticipantsAim 1:From six new practices (n=538 people with diabetes) that joined care group ELZHA in January 2014, two practices (n=211 people) were excluded because of missing baseline data; four practices (n=182 people) were included.Aim 2:From all six new practices (n=538 people), 295 individuals were included. From 145 experienced practices (n=21 465 people), 13 744 individuals were included.ExposureCare group participation includes support by staff nurses on protocolised diabetes care implementation and availability of a system providing individual monitoring information. ‘Monitoring as recommended’ represented minimally one annual registration of each biomedical (HbA1c, systolic blood pressure, low-density lipoprotein) and lifestyle-related target indicator (body mass index, smoking behaviour, physical exercise).Primary outcome measuresAim 1:In new practices, odds of people being monitored as recommended in 2014 were compared with baseline (2013).Aim 2:Odds of monitoring as recommended in new and experienced practices in 2014 were compared.ResultsAim 1:After 1-year care group participation, odds of being monitored as recommended increased threefold (OR 3.00, 95% CI 1.84 to 4.88, p<0.001).Aim 2:Compared with new practices, no significant differences in the odds of monitoring as recommended were found in experienced practices (OR 1.21, 95% CI 0.18 to 8.37, p=0.844).ConclusionsWe observed a sharp increase concerning biomedical and lifestyle monitoring as recommended after 1-year care group participation, and subsequently no significant difference between new and experienced practices—indicating that providing diabetes care within a collective approach rapidly improves registration of care.

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Monitoring glycaemic control in patients with diabetes mellitus

Cited by 11 publications

References 13 publications

Results of Hallux Valgus Surgery in Diabetic Patients With Good Glycemic Control

Results of Hallux Valgus Surgery in Diabetic Patients With Good Glycemic Control

Association between glycosylated haemoglobin and outcomes for patients discharged from hospital with diabetes: A health informatics approach

Association between GP participation in a primary care group and monitoring of biomedical and lifestyle target indicators in people with type 2 diabetes: a cohort study (ELZHA cohort-1)

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