The relationship between generic and diabetes specific psychological factors and glycaemic control in adults with type 1 diabetes.

259 adults with type 1 diabetes completed measure of anxiety, depression and diabetes specific distress, HbA1c from medical records. Anxiety not depression predicted HbA1c, this association was mediated by illness specific cognitions. Targeting illness specific cognitions may be more productive than treatment of general dysphoria in type 1 diabetes.

The prevalence of depression and anxiety in adults with Type 1 diabetes.

AIM: The aim of the present study was to determine the prevalence of anxiety and depression in a large UK group of people with Type 1 diabetes. METHODS: Patients aged 16-60 years were invited to complete self-report questionnaires when they attended outpatient clinic appointments. HbA(1c) was recorded from the clinic database. RESULTS: Analysis was based on 273 complete questionnaires. The mean scores for both anxiety (mean 6.4, sd 4.5) and depression (mean 3.4, sd 3.5) were consistent with normative data. Females reported significantly higher mean anxiety than males, although neither reached the criterion for 'caseness'. Significant differences to the norm were observed for the percentages reporting moderate to severe levels of depression in males (chi(2) = 6.44; d.f. = 2; P = 0.04) and moderate to severe levels of anxiety in females (chi(2) = 7.47; d.f. = 2; P = 0.02). HbA(1c) was positively correlated with HADS scores (anxiety r = 0.2, P = 0.001, depression r = 0.14, P = 0.02). CONCLUSIONS: While there is no significant difference in the mean anxiety or depression in this cohort compared with those reported for a non-diabetic, healthy population, the results suggest that there is an increased prevalence of clinically relevant anxiety in females and of depression in males with Type 1 diabetes when compared with the normative data.

Influence of alcohol on cognitive performance during mild hypoglycaemia; implications for Type 1 diabetes.

AIMS: Alcohol and hypoglycaemia independently affect cognitive function. This may be relevant for insulin-treated diabetic patients who drive motor vehicles. The aim of this study was to examine the effect of mild hypoglycaemia (2.8 mmol/l) with modest alcohol intoxication (levels below UK driving limits) on intellectual performance in patients with Type 1 diabetes. METHODS: A hyperinsulinaemic glucose clamp (60 mU/m2) was used to study 17 subjects [age 35 +/- 8 years, HbA1c 8.1 +/- 1.4% (mean +/- sd)] on four occasions: (A) euglycaemia (4.5 mmol/l) with placebo, (B) euglycaemia with alcohol, (C) hypoglycaemia (2.8 mmol/l) with placebo, and (D) hypoglycaemia with alcohol. Cognitive performance was assessed using four-choice reaction time (4CRT, primary outcome), measurements of general intellectual skills [trail making B (TMB) and digit symbol substitution (DSST)], and visual information processing [visual change detection (VCD)]. A test related to driving performance (hazard perception) was also used. RESULTS: In experiments B and D the average blood alcohol level was 43 mg/dl. This was associated with deterioration in 4CRT [+ 35 ms [95% confidence interval (CI) 20, 50]] and TMB, whereas hypoglycaemia without alcohol increased 4CRT only [+ 39 ms (95% CI 5, 73)]. However, when alcohol was combined with hypoglycaemia, there was marked deterioration in all the cognitive function tests [4CRT 74 ms (95% CI 35, 113), TMB, DSST and VCD]. Hazard perception was not affected. The effect of alcohol was no different in euglycaemia than in hypoglycaemia, i.e. there was no interaction. Whereas hypoglycaemia did not reduce the likelihood that the subjects would drive, alcohol did. CONCLUSIONS: The cumulative effect of alcohol and hypoglycaemia on cognitive function together has implications for driving in patients with Type 1 diabetes. Both independently impair cognitive function and together the effects are additive. Patients with Type 1 diabetes should be educated about hypoglycaemia and driving and should avoid alcohol completely if planning to drive.

Use of the Internet to optimize self-management of type 1 diabetes: preliminary experience with DiasNet.

Six patients with type 1 diabetes participated in a pilot trial. Their median age was 36 years (range 29-61) and the median duration of diabetes was 10 years (range 3-29). They were asked to enter, from their home or work PC, blood glucose values, insulin doses and a food diary. From the data entered, a computer model generated a simulation of the blood glucose concentration for the data collection period. It could then suggest alternative insulin doses (or regimes), or meal sizes, to reduce the risk of hypo- and hyperglycaemia. During a six-month study, patients entered a median of five sets of data (range two to eight). Feedback from participants revealed that while the system was helpful, difficulties with data entry hindered its use. Information gained from this exercise is shaping further development of the system.

Performance of a continuous glucose monitoring system during controlled hypoglycaemia in healthy volunteers.

It has been suggested that the continuous glucose monitoring system may be a useful tool for detecting unrecognised hypoglycaemia, especially at times when finger prick testing is difficult or impossible (e.g., at night). Studies suggest that subcutaneous glucose levels closely mimic blood glucose levels with a lag time of only a few minutes. However, no studies have been published to show how well the sensor performs during sustained or in recovery from hypoglycaemia. This study involved using a hyperinsulinaemic glucose clamp (60 mU/m2) in nine healthy volunteers. Each subject had two sensors inserted the day before the study. Blood glucose levels were maintained at euglycaemia for the first 60 min, then decreased to 45 mg/dL (2.5 mmol/L) for 60 min, and finally restored to euglycaemia. Blood glucose measurements were compared with interstitial values recorded by the sensor. Sensor profiles showed acceptable agreement with blood glucose levels at each of the three plateaus with a correlation coefficient of 0.79, slope of 0.85, and mean absolute error of 7%. The sensor drop closely matched the drop in blood glucose, but the recovery from hypoglycaemia was delayed by an average of 26 min. Continuous glucose sensing provides a useful means of detecting unrecognised hypoglycaemia in type 1 diabetes, although the duration of hypoglycaemia may be overestimated.

Preventing glycaemic excursions in diabetic patients requiring percutaneous endoscopic gastrostomy (PEG) feeding after a stroke.

AIMS AND METHODS: Enteral feeding for diabetic patients with a stroke is often associated with hyperglycaemia and/or hypoglycaemia, which can adversely influence neurological recovery. We have developed a structured enteral feeding programme aimed at establishing 'normal' feeding patterns and avoiding marked glycaemic excursions. RESULTS: Of 332 consecutive patients admitted to an acute stroke unit, 20 of 41 diabetic patients required PEG feeding. Over the initial 24-48 h, patients had 22- h feeds with continuous intravenous infusion of soluble insulin. Thereafter, they were established on three feeds per day. Soluble insulin was given prior to each feed with isophane insulin at 2200 h. Average duration of feed was 13 +/- 8 days with an achieved glucose level of 8.7 +/- 2.5 (mean +/- SD) mmol/l associated with 0.8 episodes of biochemical hypoglycaemia (< 3 mmol/l) each week. CONCLUSIONS: A structured enteral feeding programme for PEG-fed diabetic patients can improve the quality of care with avoidance of marked glycaemic excursions.

DiasNet--a diabetes advisory system for communication and education via the internet.

Intensive diabetes treatment can lead to a substantial reduction of the rate of the complications associated with diabetes. However, a number of patients may have poor control despite specialist care, and this along with devolution of care to non-specialists suggests that alternative interventions should be developed. The present paper describes an Internet based system where more emphasis is put on patient empowerment, the keywords being education and communication. The DiasNet system is based on a well documented decision support system, Dias, designed for use by clinicians. The scope of DiasNet has been widened from being used by clinicians to give advice on insulin dose, to also being used by patients as a tool for education and communication. Patients can experiment with their own data, adjusting insulin doses or meal sizes. In this way different therapeutic and dietary alternatives can be tried out, allowing the patient to gain experience in achieving glycaemic control. DiasNet is implemented in JAVA according to the client/server principle, enabling a new way of communication between patient and clinician: in case of any problems, the patient simply phones the clinician, who immediately, using his or her office PC, can take a look at the data the patient has entered.

The effect of evening alcohol consumption on next-morning glucose control in type 1 diabetes.

OBJECTIVE: Alcohol is associated with acute hypoglycemia in patients with type 1 diabetes. After drinking alcohol in the evening, delayed hypoglycemia has also been described, although its cause is unknown. We performed a controlled study to investigate this phenomenon. RESEARCH DESIGN AND METHODS: We admitted six men with type 1 diabetes (aged 19-51 years, HbA(1c) 7.0-10.3%) on two occasions, from 5:00 P.M. to 12:00 noon the following day. They received regular insulin injections before standardized meals, at 6:00 P.M. and 8:00 A.M., and a basal insulin infusion (0.15 mU x kg(-1) x min(-1)) from 11:00 P.M. They drank either dry white wine (0.75 g/kg alcohol) or mineral water at 9:00 P.M. over 90 min. Blood glucose, alcohol, insulin, cortisol, growth hormone, and glucagon levels were measured. RESULTS: Blood ethanol reached a mean (SEM) peak of 19.1 (1.2) mmol/l and was undetectable by 8:00 A.M. There were no significant differences in evening or overnight blood glucose levels between the studies. In the morning, fasting and postprandial blood glucose levels were significantly lower after consumption of wine (postprandial peak 8.9 [1.7] vs. 15 [1.5] mmol/l, P < 0.01), and from 10:00 A.M., five subjects required treatment for hypoglycemia (nadir 1.9-2.9 mmol/l). None of the subjects had hypoglycemia after consumption of water. After consumption of wine, growth hormone secretion was significantly reduced between midnight and 4:00 A.M. (area under the curve 2.1 [1.1] vs. 6.5 [2.1] microg. l(-1) x h(-1), P = 0.04). There were no differences in insulin or other hormone levels. CONCLUSIONS: In type 1 diabetes, moderate consumption of alcohol in the evening may predispose patients to hypoglycemia after breakfast the next morning. This is associated with reduced nocturnal growth hormone secretion. Patients should be informed of this risk and advised regarding appropriate preventative measures.

Impaired absorption and omission of insulin: a novel method of detection using the diabetes advisory system computer model.

The Diabetes Advisory System (DIAS) is a decision-support program developed to assist insulin dose adjustment in type 1 diabetes. In this paper, we show how it might be used to identify impaired absorption or omission of insulin in patients with poorly controlled blood glucose. An evaluation of glucose results from four outpatients with persistent hyperglycemia is presented (age 19-48 years with type 1 diabetes for 13-18 years of duration, HbA1c 9.4-13.6%). Each had completed a 4-day record of blood glucose (BG, pre-meal and bedtime), dietary (carbohydrate) intake, and insulin doses (with injection sites). From these data, DIAS modeled a glucose profile (simulated glucose, SG) for the same period. Qualitative assessments were made of differences between BG and SG, and selective reduction or complete removal of insulin doses where BG >> SG. Large improvements in modeling were attributed to either impaired absorption or omission of insulin. Confirmation of these problems was sought from the patients by detailed consultation and physical examination. Impaired insulin absorption was suspected in two patients, both having significant injection site abnormalities. Insulin omission was suspected in the other two subjects. Both had normal injection sites, and one admitted to missing doses. Following retraining, data from three patients showed noticeable improvements in overall modeling as well as glucose control. Using DIAS in the evaluation of patients with type 1 diabetes may highlight previously unrecognized injection site abnormalities or insulin dose omission. This could assist rational optimization of insulin therapy in cases of persistently poor glucose control.

Reducing hospital inpatient length of stay for patients with diabetes.

AIMS: To ascertain the effect of routine review by a diabetes nurse advisor on length of stay for medical and surgical inpatients with diabetes. METHODS: Inpatients with diabetes were identified prospectively from January 1997 until December 1998 (792 in 1997 and 819 in 1998). A new post of diabetes nurse advisor was introduced in January 1998 to optimize diabetes management. Length of stay was calculated retrospectively from hospital computer records. RESULTS: Median length of stay in 1997 was 11 days in medicine and 8 days in surgery. In 1998, the nurse advisor made 1936 visits to 819 patients; median length of stay fell to 8 days in medicine and 5 days in surgery (P < 0.001). Bed occupancy by patients with diabetes fell from 6.8 to 4.0%. Mean length of stay across the hospital remained unchanged. CONCLUSIONS: The introduction of a ward-based diabetes nurse advisor was associated with significant reductions in length of stay in inpatients with diabetes. Since this study was not a randomized study, other factors may have contributed to this change. However, the consistency of the reduction across specialities suggests the post itself had an important effect.

What do patients with diabetes know about their tablets?

AIMS: To assess knowledge about oral hypoglycaemic agents amongst patients with diabetes and non-specialist healthcare professionals. METHOD: An anonymous questionnaire was used in two centres to assess knowledge about oral agents amongst 261 patients with Type 2 diabetes mellitus (mean age 64 years) and 102 health professionals (including doctors, nurses and pharmacists). RESULTS: Only 15% of patients knew the correct mechanism of action of their medication and 62% took tablets correctly in relation to food. Only 10% of those taking a sulphonylurea knew it may cause hypoglycaemia and 20% of those taking metformin were aware of its gastrointestinal side-effects. Twenty per cent forgot to take their tablets at least once a week and 5% omitted tablets because of hyperglycaemia. Only 35% of patients recalled receiving advice about their medication with only 1% receiving written advice. The healthcare professionals showed important gaps in their knowledge on dosage timing and mechanism of action, particularly with respect to metformin and acarbose. CONCLUSION: It is concluded that patients' and professionals' knowledge of oral hypoglycaemic agents is poor. More appropriate advice and information to patients from prescribers may improve patient understanding and hence compliance. Community pharmacists are ideally placed to reinforce this information.

A detailed examination of the clinical terms and concepts required for communication by electronic messages in diabetes care.

The wider electronic exchange of clinical information between heterogeneous information systems in the delivery of diabetes care demands a common structure in the form of a message standard. A European Standard electronic diabetes message is being developed in conjunction with CEN TC251. This paper describes the methodologies that the 1998 DO IT Workshop has used to identify potential areas of difficulty in the design and implementation of the preliminary message model. To facilitate implementation and to avoid ambiguity in electronic messaging it is particularly important that there is standardisation of the definitions of the clinical terms specifically used in diabetes care across systems. Comprehensive lists of such terms to describe all areas of diabetes care do not exist and there is a lack of harmonisation of definitions in many areas. Thus, to better understand the user requirements of diabetes messaging several approaches were adopted. A review of the clinical terms and concepts contained in pre-existing datasets was undertaken with detailed study of a number of specific areas of diabetes care, analysing the conceptual structure of all the clinical terms that they comprised. Consideration of several worst case clinical scenarios for messages to communicate was also made to identify deficiencies in the message structure. This activity confirmed the importance of creating a Standard for a superset or thesaurus of diabetes specific terms, with appropriate definitions, to harmonise data communication in different IT systems to facilitate messaging. A substantial number of new terms were identified in the workshop and these will form an important first step to accomplishing a first draft superset once fully analysed. It was also apparent that certain specific areas within diabetes care, but most particularly in nursing, dietetics and podiatry, need urgent work to further develop the concepts and terms. This needs to be facilitated for an appropriate group of such professionals. To achieve such a Standard, continued co-operation with CEN/ISSS was recognised to be very important.

Screening for diabetic retinopathy using computer based image analysis and statistical classification.

Diabetic retinopathy is one of the most common causes of blindness in Europe. However, efficient therapies do exist. An accurate and early diagnosis and correct application of treatment can prevent blindness in more than 50% of all cases. Digital imaging is becoming available as a means of screening for diabetic retinopathy. As well as providing a high quality permanent record of the retinal appearance, which can be used for monitoring of progression or response to treatment, and which can be reviewed by an ophthalmologist, digital images have the potential to be processed by automatic analysis systems. We have described the preliminary development of a tool to provide automatic analysis of digital images taken as part of routine monitoring of diabetic retinopathy in our clinic. Various statistical classifiers, a Bayesian, a Mahalanobis, and a KNN classifier were tested. The system was tested on 134 retinal images. The Mahalanobis classifier had the best results: microaneurysms, haemorrhages, exudates, and cotton wool spots were detected with a sensitivity of 69, 83, 99, and 80%, respectively.

DiasNet--an Internet tool for communication and education in diabetes.

Although studies have shown that intensive diabetes treatment with the goal of maintaining blood glucose concentrations close to the normal range lead to a substantial reduction of the rate of the complications (e.g. blindness, kidney failure, amputations and circulatory diseases), this can be difficult to achieve using conventional means. It is recognised that a number of patients may have poor control despite specialist care, and this along with devolution of care to non-specialists suggests that alternative interventions should be developed. DiasNet, which is used by patients as a tool for education and communication, is based on a well documented decision support system used by clinicians to give advise on insulin dose. In DiasNet the patients can experiment with their own data, adjusting insulin doses or meals sizes, and thereby learning how to cope with various situations. The system can run both as an ordinary application on a standard PC, and as an Internet application using a standard web browser. The latter enables a new way of communication between patient and clinician. DiasNet is currently being tested on a small group of diabetes patients.

Dynamic updating in DIAS-NIDDM and DIAS causal probabilistic networks.

Diabetes advisory system (DIAS) is a decision support system, which has been developed to provide advice on the amount of insulin injected by subjects with insulin-dependent diabetes mellitus (IDDM). DIAS employs a temporal causal probabilistic network (CPN) to implement a stochastic model of carbohydrate metabolism. The CPN network has recently been extended to provide also advice to subjects with noninsulin-dependent diabetes mellitus (NIDDM). However, due to increased complexity and size of the extended CPN the calculations became unfeasible. The CPN network was, therefore, simplified and a novel approach employed to generate conditional probability tables. The principles of dynamic CPN's were adopted and, in combination with the method of conditioning, learning, and forecasting, were implemented in a time- and memory-efficient way. An evaluation using experimental data was carried out to compare the original and revised DIAS implementations employing data collected by patients with IDDM, and to assess the a posteriori identifiability of model parameters in patients with NIDDM.

Beyond retinal screening: digital imaging in the assessment and follow-up of patients with diabetic retinopathy.

Many screening methods are available for detecting diabetic retinopathy. However, once patients develop retinopathy, it is unclear as to what method should be used for their review. We describe a novel and integrated system for the screening and treatment of diabetic retinopathy using high street optometrists for primary screening and digital imaging as a secondary screening tool, with referral to a joint retinal clinic only where ophthalmological intervention may be required. Of 3586 patients screened by optometrists, 328 were classified as having moderate/severe pre-proliferative retinopathy or diabetic maculopathy. Patients with proliferative retinopathy (1% of the total) were recalled directly to the joint retinal clinic. A consecutive sample (281) of these patients, together with a further 100 classified by the optometrists as having no or background retinopathy were compared using digital images and standard 35 mm colour transparencies. These, together with the original optometrist reports, were reviewed independently and individually by an ophthalmologist. A further sample of 124 patients who had undergone both digital imaging and ophthalmologist slit-lamp examination were also compared. Comparison of 35 mm colour transparencies with optometrist reports showed the latter had a sensitivity for detecting sight-threatening retinopathy (STR) of 62%, a specificity of 84%, and a kappa score of 0.62. The results for digital images were 90%, 97%, and 0.90, respectively, although the extent of retinopathy was under-reported in 10 patients. With ophthalmologist slit-lamp examination as the gold standard, the sensitivity of digital imaging was 90% with a substantial level of agreement between them (kappa 0.61). We conclude that digital images provide an efficient method for the follow-up of patients with established or previously treated retinopathy.

Preliminary experience of the DIAS computer model in providing insulin dose advice to patients with insulin dependent diabetes.

The Diabetes Advisory System (DIAS) is a model of human glucose metabolism which predicts hourly blood glucose concentrations and provides advice on insulin dose. Its ability to provide appropriate advice was assessed in 20 well-controlled IDDM patients (mean (SD) age 38 (11), duration 17 (9) years; HbA1 8.8 (0.9)%, reference range 5.4-7.6%). Patients recorded blood glucose measurements, insulin dose and food intake for 4 days. These data were used to generate insulin dose advice by both DIAS and a diabetes specialist nurse. Patients were then allocated to follow either DIAS or nurse advice for a further 4 days. There was no significant difference in mean recorded blood glucose values or frequency of reported hypoglycaemia between the DIAS and nurse groups either before or after insulin dose adjustment. The DIAS model, however, generated significantly lower insulin dose advice than the nurse (median (range)% change in insulin dose: DIAS group -13.3% (-25.0 to +11.6) versus nurse group 0% (-8.7 to +2.5), P < 0.05). We conclude that, in the patients studied, DIAS provided insulin dose advice which maintained good short term control of diabetes, despite significant reductions in dose in some cases.

Using a double blind controlled clinical trial to evaluate the function of a Diabetes Advisory System: a feasible approach?

This paper assesses the feasibility of using a double blind controlled clinical trial to evaluate the function of a decision support system by applying such a design to the evaluation of a Diabetes Advisory System (DIAS). DIAS is based on a model of the human carbohydrate metabolism and is designed an interactive clinical tool, which can be used to predict the effects of changes in insulin dose or food intake on the blood glucose concentration in patients with insulin dependent diabetes. It can also be used to identify risk periods for hypoglycaemia. and to provide advice on insulin dose. The latter feature was evaluated in the present study. We believe double blind controlled clinical trials are prerequisites for clinical application of many decision support systems, and conclude that the present double blind controlled clinical trial is a suitable evaluation method for the function of DIAS.