OBJECTIVE -To estimate the absolute and relative risk of cardiovascular disease (CVD) in patients with type 1 diabetes in the U.K.RESEARCH DESIGN AND METHODS -Subjects with type 1 diabetes (n ϭ 7,479) and five age-and sex-matched subjects without diabetes (n ϭ 38,116) and free of CVD at baseline were selected from the General Practice Research Database (GPRD), a large primary care database representative of the U.K. population. Incident major CVD events, comprising myocardial infarction, acute coronary heart disease death, coronary revascularizations, or stroke, were captured for the period 1992-1999.RESULTS -The hazard ratio (HR) for major CVD was 3.6 (95% CI 2.9 -4.5) in type 1 diabetic men compared with those without diabetes and 7.7 (5.5-10.7) in women. Increased HRs were found for acute coronary events (3.0 and 7.6 in type 1 diabetic men and women, respectively, versus nondiabetic subjects), coronary revascularizations (5.0 in men, 16.8 in women), and for stroke (3.7 in men, 4.8 in women). Type 1 diabetic men aged 45-55 years had an absolute CVD risk similar to that of men in the general population 10 -15 years older, with an even greater difference in women.CONCLUSIONS -Despite advances in care, these data show that absolute and relative risks of CVD remain extremely high in patients with type 1 diabetes. Women with type 1 diabetes continue to experience greater relative risks of CVD than men compared with those without diabetes. Diabetes Care 29:798 -804, 2006

Dyspnea (shortness of breath, breathlessness) is a major and disabling symptom of heart and lung disease. The representation of dyspnea in the cerebral cortex is unknown. In the first study designed to explore the central neural structures underlying perception of dyspnea, we evoked the perception of severe 'air hunger' in healthy subjects by restraining ventilation below spontaneous levels while holding arterial oxygen and carbon dioxide levels constant. PET revealed that air hunger activated the insular cortex. The insula is a limbic structure also activated by visceral stimuli, temperature, taste, nausea and pain. Like dyspnea, such perceptions underlie behaviors essential to homeostasis and survival.

Aims  Under‐reporting of diabetes on death certificates contributes to the unreliable estimates of mortality as a result of diabetes. The influence of obesity on mortality in Type 2 diabetes is not well documented. We aimed to study mortality from diabetes and the influence of obesity on mortality in Type 2 diabetes in a large cohort selected from the General Practice Research Database (GPRD). Methods  A cohort of 44 230 patients aged 35–89 years in 1992 with Type 2 diabetes was identified. A comparison group matched by year of birth and sex with no record of diabetes at any time was identified (219 797). Hazards ratios (HRs) for all‐cause mortality during the period January 1992 to October 1999 were calculated using the Cox Proportional Hazards Model. The effects of body mass index (BMI), smoking and duration of diabetes on all‐cause mortality amongst people with diabetes was assessed (n = 28 725). Results  The HR for all‐cause mortality in Type 2 diabetes compared with no diabetes was 1.93 (95% CI 1.89–1.97), in men 1.77 (1.72–1.83) and in women 2.13 (2.06–2.20). The HR decreased with increasing age. In the multivariate analysis in diabetes only, the HR for all‐cause mortality amongst smokers was 1.50 (1.41–1.61). Using BMI 20–24 kg/m2 as the reference range, for those with a BMI 35–54 kg/m2 the HR was 1.43 (1.28–1.59) and for those with a BMI 15–19 kg/m2 the HR was 1.38 (1.18–1.61). Conclusions  Patients with Type 2 diabetes have almost double the mortality rate compared with those without. The relative risk decreases with age. In people with Type 2 diabetes, obesity and smoking both contribute to the risk of all‐cause mortality, supporting doctrines to stop smoking and lose weight.

Evidence before this studyWe have searched PubMed and Scopus from 1990-2017, to identify relevant studies that contain terms for older people; all-cause mortality; glycaemic control; glycaemic variability (with synonyms). We also identified current international guidelines for older people. Overall, the data on optimal glycaemic targets for older people are scant, particularly from prospective studies. In terms of the association between glycaemic control and mortality in older populations the finding have suggested a 'J' shaped distribution in that relationship, although the point at which a significant mortality hazard is observed at the lower end of the glycaemic range has varied between studies. In terms of glycaemic variability, it has been identified that longer term variations in glycaemic control are associated with mortality risk. However, these analyses have not been graduated for magnitude or direction of variability. In addition, previous analyses have not considered the impact of low HbA1c levels, which are associated with mortality risk independent of diabetes intervention. Added value of this studyIn this large population study we are the first group to consider both glycaemic control and glycaemic variability together. We have also employed a new metric for variability which considers exposure to clinically significant changes in glycaemic control. This metric enabled us to assess the direction of change as well as the overall variability. Integrating glycaemic control and variability in our modelling enabled us to consider the importance of stability as a potential factor in understanding the mortality hazard in this population. Additional nuances to our analysis include: consideration of low HbA1c values; higher levels of granularity compared to previous studies in terms of glycaemic thresholds, with 0.5%(5.5mmol/l) HbA1c increments; consideration of gender differences; and the distinction between those who develop diabetes in midlife and those who develop it in older age. Implications of all the available evidenceOur data suggest that we may need to rethink how we consider glycaemic targets in the older diabetes population, in a number of ways: firstly, that variability expresses significant hazard in older people; secondly, that variability may be independent of diabetes therapies and may be related to other factors related to aging; thirdly, stability seems to attenuate hazard in medium to higher ranges of glycaemic control; and finally, there may be some important gender differences in relation to glycaemic control and hazard which are not considered in current guidelines. Therefore, while we recognise that observational data can often raise more questions than answers; we would advocate that we reconsider glycaemic control not simply as a target to direct therapeutic management, but as an important piece of information in relation to assessing individual risk. Perhaps in the past we have been too polarised in our view of glycaemia as purely indicative of optimal control, rather than as a p...

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Aims/hypothesis Risk estimates for stroke in patients with diabetes vary. We sought to obtain reliable risk estimates for stroke and the association with diabetes, comorbidity and lifestyle in a large cohort of type 2 diabetic patients in the UK. Materials and methods Using the General Practice Research Database, we identified all patients who had type 2 diabetes and were aged 35 to 89 years on 1 January 1992. We also identified five comparison subjects without diabetes and of the same age and sex. Hazard ratios (HRs) for stroke between January 1992 and October 1999 were calculated, and the association with age, sex, body mass index, smoking, hypertension, atrial fibrillation and duration of diabetes was investigated. Results The absolute rate of stroke was 11.91 per 1,000 person-years (95% CI 11.41-12.43) in people with diabetes (n=41,799) and 5.55 per 1,000 person-years (95% CI 5.40-5.70) in the comparison group (n=202,733). The ageadjusted HR for stroke in type 2 diabetic compared with non-diabetic subjects was 2.19 (95% CI 2.09-2.32) overall, 2.08 (95% CI 1.94-2.24) in men and 2.32 (95% CI 2.16-2.49) in women. The increase in risk attributable to diabetes was highest among young women (HR 8.18; 95% CI 4.31-15.51) and decreased with age. No investigated comorbidity or lifestyle characteristic emerged as a major contributor to risk of stroke. Conclusions/interpretation This study provides risk estimates for stroke for an unselected population from UK general practice. Patients with type 2 diabetes were at an increased risk of stroke, which decreased with age and was higher in women. Additional risk factors for stroke in type 2 diabetic patients included duration of diabetes, smoking, obesity, atrial fibrillation and hypertension.

BackgroundIncreasing numbers of patients with type 2 diabetes mellitus are progressing to insulin therapy, and despite its potency many such individuals still have suboptimal glycaemic control. Insulin initiation and intensification is now often conducted by Practice Nurses and General Practitioners in many parts of the UK. Therefore, gaining insight into perspectives of patients and primary care clinicians is important in determining self-management and engagement with insulin. A thematic synthesis of studies was conducted exploring the views and experiences of people with type 2 diabetes and of healthcare professionals on insulin use and management in the context of primary care.MethodsProtocol based systematic searches of electronic databases (CINAHL, Cochrane Library, EMBASE, MEDLINE, PsycINFO, and Web of Science) were performed on 1 October 2014 and updated on 31 March 2015, to identify studies that identified the views and experiences of adults with type 2 diabetes or primary care clinicians on the use of insulin in the management of type 2 diabetes. Studies meeting the review inclusion criteria were critically appraised using the CASP qualitative research checklist or Barley’s checklist for survey designs. A thematic synthesis was then conducted of the collected studies.ResultsThirty-four studies were selected. Of these, 12 used qualitative interviews (nine with patients and three with healthcare professionals) and 22 were survey based (14 with patients, three with healthcare professionals, and five with both). Twelve key themes were identified and formed three domains, patient perceptions, healthcare professional perceptions, and health professional-patient relationships. The patient-centred themes were: insulin-related beliefs, social influences, psychological factors, hypoglycaemia, and therapy barriers. The clinician-related themes were: insulin skills of general practitioners, healthcare integration, healthcare professional-perceived barriers, hypoglycaemia, and explanations for adherence. Healthcare professional-patient relationship themes were drawn from the perspectives of patients and from clinicians.ConclusionsThis review reveals multiple barriers to optimal insulin use in primary care at both the patient and healthcare professional levels. These barriers indicate the need for multimodal interventions to: improve the knowledge and competencies of primary care professionals in insulin use; provide more effective patient education and self-management support; and introduce integrated insulin support systems.Electronic supplementary materialThe online version of this article (10.1186/s12875-018-0753-2) contains supplementary material, which is available to authorized users.

Aims To determine the effectiveness of self-audit tools designed to detect miscoding, misclassification and misdiagnosis of diabetes in primary care. MethodsWe developed six searches to identify people with diabetes with potential classification errors. The search results were automatically ranked from most to least likely to have an underlying problem. Eight practices with a combined population of 72 000 and diabetes prevalence 2.9% (n = 2340) completed audit forms to verify whether additional information within the patients' medical record confirmed or refuted the problems identified. ResultsThe searches identified 347 records, mean 42 per practice. Pre-audit 20% (n = 69) had Type 1 diabetes, 70% (n = 241) had Type 2 diabetes, 9% (n = 30) had vague codes that were hard to classify, 2% (n = 6) were not coded and one person was labelled as having gestational diabetes. Of records, 39.2% (n = 136) had important errors: 10% (n = 35) had coding errors; 12.1% (42) were misclassified; and 17.0% (59) misdiagnosed as having diabetes. Thirty-two per cent (n = 22) of people with Type 2 diabetes (n = 69) were misclassified as having Type 1 diabetes; 20% (n = 48) of people with Type 2 diabetes (n = 241) did not have diabetes; of the 30 patients with vague diagnostic terms, 50% had Type 2 diabetes, 20% had Type 1 diabetes and 20% did not have diabetes. Examples of misdiagnosis were found in all practices, misclassification in seven and miscoding in six.Conclusions Volunteer practices successfully used these self-audit tools. Approximately 40% of patients identified by computer searches (5.8% of people with diabetes) had errors; misdiagnosis is commonest, misclassification may affect treatment options and miscoding in omission from disease registers and the potential for reduced quality of care.