Project description:BackgroundCancer and Diabetes Mellitus (DM) are leading causes of death worldwide and the prevalence of both is escalating. People with co-morbid cancer and DM have increased morbidity and premature mortality compared with cancer patients with no DM. The reasons for this are likely to be multifaceted but will include the impact of hypo/hyperglycaemia and diabetes therapies on cancer treatment and disease progression. A useful step toward addressing this disparity in treatment outcomes is to establish the impact of cancer treatment on diabetes control.AimThe aim of this review is to identify and analyse current evidence reporting glycaemic control (HbA1c) during and after cancer treatment.MethodsSystematic searches of published quantitative research relating to comorbid cancer and type 2 diabetes mellitus were conducted using databases, including Medline, Embase, PsychINFO, CINAHL and Web of Science (February 2017). Full text publications were eligible for inclusion if they: were quantitative, published in English language, investigated the effects of cancer treatment on glycaemic control, reported HbA1c (%/mmols/mol) and included adult populations with diabetes. Means, standard deviations and sample sizes were extracted from each paper; missing standard deviations were imputed. The completed datasets were analysed using a random effects model. A mixed-effects analysis was undertaken to calculate mean HbA1c (%/mmols/mol) change over three time periods compared to baseline.ResultsThe available literature exploring glycaemic control post-diagnosis was mixed. There was increased risk of poor glycaemic control during this time if studies of surgical treatment for gastric cancer are excluded, with significant differences between baseline and 12 months (p < 0.001) and baseline and 24 months (p = 0.002).ConclusionWe found some evidence to support the contention that glycaemic control during and/or after non-surgical cancer treatment is worsened, and the reasons are not well defined in individual studies. Future studies should consider the reasons why this is the case.

Project description:IntroductionThis study investigated glycaemic control in individuals with type 1 (T1D) or type 2 diabetes (T2D) 6 months after initiating fast-acting insulin aspart (faster aspart) in a real-world setting.MethodsThis was a single-arm, observational study using extracted patient data from the IBM® Explorys® database (USA) for individuals with T1D or T2D initiating faster aspart (at least one prescription of faster aspart) in the study period 1 January 2018 to 27 October 2020. Clinical characteristics, including age, body mass index, and baseline HbA1c, were extracted, as well as recorded events of hypoglycaemia. The primary endpoint was the change in HbA1c from baseline to 6 months.ResultsA total of 787 individuals were included; 36.6% of these individuals had T1D and 63.4% had T2D (of whom 46.9% were new users of rapid-acting insulin when initiating faster aspart [T2D new users] and 53.1% were switching from another rapid-acting insulin to faster aspart [T2D switchers]). For individuals with T1D, T2D new users, or T2D switchers, estimated mean change in HbA1c from baseline to 6 months was - 0.20% (95% CI - 0.53, 0.14; p = 0.252), - 1.00% (95% CI - 1.34, - 0.67; p < 0.0001), and - 0.70% (95% CI - 1.06, - 0.35; p = 0.0001), respectively. In the baseline HbA1c > 8.5% subgroup, there was a significant estimated decrease in HbA1c from baseline to 6 months in individuals with T1D (- 1.2% [95% CI - 1.80, - 0.60]; p = 0.0001) or T2D (- 0.6% [95% CI - 0.92, - 0.35]; p < 0.0001). Event rates of hypoglycaemia after 12 months were 0.68, 0.38, and 0.59 events/year for individuals with T1D, T2D new users, and T2D switchers, respectively.ConclusionUS IBM® Explorys® data demonstrated a clinically relevant reduction in HbA1c 6 months after initiating faster aspart treatment for individuals with T2D, but not T1D overall, although patients with baseline HbA1c > 8.5% had significant HbA1c reductions regardless of diabetes type.

Project description:Aims/hypothesisThe aim of this work was to examine whether glycaemic control has improved in those with type 1 diabetes in Scotland between 2004 and 2016, and whether any trends differed by sociodemographic factors.MethodsWe analysed records from 30,717 people with type 1 diabetes, registered anytime between 2004 and 2016 in the national diabetes database, which contained repeated measures of HbA1c. An additive mixed regression model was used to estimate calendar time and other effects on HbA1c.ResultsOverall, median (IQR) HbA1c decreased from 72 (21) mmol/mol [8.7 (4.1)%] in 2004 to 68 (21) mmol/mol (8.4 [4.1]%) in 2016. However, all of the improvement across the period occurred in the latter 4 years: the regression model showed that the only period of significant change in HbA1c was 2012-2016 where there was a fall of 3 (95% CI 1.82, 3.43) mmol/mol. The largest reductions in HbA1c in this period were seen in children, from 69 (16) mmol/mol (8.5 [3.6]%) to 63 (14) mmol/mol (7.9 [3.4]%), and adolescents, from 75 (25) mmol/mol (9.0 [4.4]%) to 70 (23) mmol/mol (8.6 [4.3]%). Socioeconomic status (according to Scottish Index of Multiple Deprivation) affected the HbA1c values: from the regression model, the 20% of people living in the most-deprived areas had HbA1c levels on average 8.0 (95% CI 7.4, 8.9) mmol/mol higher than those of the 20% of people living in the least-deprived areas. However this difference did not change significantly over time. From the regression model HbA1c was on average 1.7 (95% CI 1.6, 1.8) mmol/mol higher in women than in men. This sex difference did not narrow over time.Conclusions/interpretationIn this high-income country, we identified a modest but important improvement in HbA1c since 2012 that was most marked in children and adolescents. These changes coincided with national initiatives to reduce HbA1c including an expansion of pump therapy. However, in most people, overall glycaemic control remains far from target levels and further improvement is badly needed, particularly in those from more-deprived areas.

Project description:Diabetes mellitus (DM) is a well-known risk factor for atrial fibrillation (AF), but the mechanism(s) by which DM affects AF prevalence remains unclear. This study aims to evaluate the impact of diabetes mellitus severity (expressed as its known duration), antihyperglycemic treatment regimen and glycaemic control on AF prevalence. From the representative sample of 3014 participants (mean age 77.5, 49.1% female) from the cross-sectional NOMED-AF study, 881 participants (mean age 77.6 ± 0.25, 46.4% female) with concomitant DM were involved in the analysis. AF was screened using a telemonitoring vest for a mean of 21.9 ± 9.1 days. The mean DM duration was 12 ± 0.35 years, but no significant impact of DM timespan on AF prevalence was observed. No differences in the treatment pattern (oral medication vs insulin vs both oral + insulin) among the study population with and without AF were shown (p = 0.106). Metabolic control reflected by HbA1c levels showed no significant association with AF and silent AF prevalence (p = 0.635; p = 0.094). On multivariate analyses, age (Odds Ratio (OR) 1.35, 95%CI: 1.18-1.53, p < 0.001), p = 0.042), body mass index (BMI; OR 1.043, 95%CI: 1.01-1.08, p = 0.027) and LDL < 100 mg/dl (OR 0.64, 95%CI: 0.42-0.97, p = 0.037) were independent risk factors for AF prevalence, while age (OR 1.45, 95%CI: 1.20-1.75, p < 0.001), LDL < 100 mg/dl (OR 0.43, 95%CI 0.23-0.82, p = 0.011), use of statins (OR 0.51, 95%CI: 0.28-0.94, p = 0.031) and HbA1c ≤ 6.5 (OR 0.46, 95%CI: 0.25-0.85, p = 0.013) were associated with silent AF prevalence. Diabetes duration, diabetic treatment pattern or metabolic control per se did not significantly impact the prevalence of AF, including silent AF detected by prospective continuous monitoring. Independent predictors of AF were age, BMI and low LDL levels, with statins and HbA1c ≤ 6.5 being additional independent predictors for silent AF.Trial registration: NCT03243474.

Project description:The objective of the present study was to establish if individuals with Diabetes Mellitus (DM2) and periodontal diseases (gingivitis or periodontitis) presented an increase in the concentration of modified LDL (moLDL) and what is the influence of periodontal treatment on the decrease of moLDL particles with consequent improvement in the parameters of DM2. Twenty-four diabetic patients with periodontitis (Group 1) and twenty-four diabetic patients with gingivitis (Group 2) were followed up for a period of 12 months. Group 1 was treated with periodontal debridement, and Group 2 received supra-gingival scaling and prophylaxis. In both groups, periodontal clinical parameters: probing depth (PD), clinical attachment level (CAL), gingival resection (GR), bleeding on probing index (BOP) and plaque index; inflammatory serum markers (glycemia, A1c, total cholesterol, HDL-cholesterol (HDL-c), LDL-cholesterol (LDL-c), triglycerides and hs-CRP) and oxidized LDL (oxLDL) were measured at baseline, t = 6 and t = 12 months after treatment. Solutions of LDL were analyzed using the nonlinear optical Z-Scan and optical absorption techniques. The periodontal clinical parameters showed significant improvement (p < 0.05) in both Group after 12 months. For both groups, total cholesterol, HDL-c, LDL-c, triglycerides and A1c levels did not show significant reductions after periodontal therapy. hs-CRP levels in Group 1 presented a significant reduction after 12 months. The glycemic rate and the oxLDL concentrations did not show significant differences as a function of time. The optical measurements of LDL solutions revealed an improvement of the LDL-c quality in both groups. Periodontal debridement was able to improve periodontal parameters and the quality of LDL-c in diabetic patients but without changes in the oxLDL concentration in both groups. Considering the clinical relevance, the reduction of infectious and inflammatory sites present in the oral cavity through periodontal therapy may help with the control and prevention of hyperglycemia and precursors of cardiovascular diseases.

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Treatment of periodontal disease for glycaemic control in people with diabetes mellitus.

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