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The teaching of effective insulin adjustment is a formal process that benefits from being carried out in a standardized way. The unique methods outlined in this report have been taught to people with diabetes for over 8 years. Iterative in nature, the methods are safe and work to achieve specified blood glucose or HbA1c targets. They are designed to accommodate each individual's habits, recognizing that acceptance depends on adapting the medication to the life-style rather than vice versa. New technology was used to mediate insulin adjustments at home. Insulin adjustment of itself, however, is but one of five interdependent factors involved in successful self-management. These include (1) choosing sites of insulin injection; (2) choosing species of origin of insulins to be used; (3) reviewing life-style habits, including diet and exercise; (4) implementing dosage titration; and (5) follow-up. Lack of formalized insulin adjustment methods may be a major reason why many diabetes control programs fail to demonstrate control in their patients. [ABSTRACT FROM AUTHOR]

Background: Glycemic control is fundamental to the management of diabetes and maintenance of health. Popular measures of performance in glycemic control include A1c and self-monitoring of blood glucose (SMBG). As measures of performance, A1c has perspective but fails to recognize hypoglycemia while SMBG lacks overall perspective but finds use mainly by patients to self evaluate their glycemic status and current response to therapy. Predictions of future glycemia and the risks of hypoglycemia are now available to assist providers with interventions that avert iatrogenic hypoglycemia. Methods and results: A diabetes data centre has been created. It incorporates the customary hardware and, besides the usual database services, provides an engine for glycemic prediction that can utilize SMBG data captured remotely. Clinical use of the engine's glucose predictions support interventions that avert iatrogenic hypoglycemia while allowing providers to optimize glycemic control. Other centre resources include distribution of supporting software and user instruction. Conclusions: Use of the resources of a shared diabetes data centre can empower providers to identify problems in glycemic control, take proactive action, adopt beneficial strategies, evaluate outcomes and, most importantly, avoid interventions that engender hypoglycemia. In this light, glycemic predictions appear crucial to better diabetes care. [ABSTRACT FROM AUTHOR]

Objective: To propose that automation of the consensus guidelines and mandated targets (CG&MT) in glycemia, hemoglobin A1c, and body weight will facilitate optimal clinical management of patients with diabetes., Methods: (1) A simplified method for capturing diabetes outcomes at home was devised, (2) relevant portions of the CG&MT were translated into computer code and automated, and (3) algorithms were applied to transform data from self-monitoring of blood glucose into circadian profiles and hemoglobin A1c levels. (4) The resulting procedures were integrated into a USB memory drive for use by health-care providers at the point of care., Results: For input from patients, a simple form is used to capture data on diabetes outcomes, including blood glucose measurements before and after meals and at bedtime, medication, and lifestyle events in a structured fashion. At each encounter with a health-care provider, the patient's data are transferred into the device and become available to assist in identifying deviations from mandated targets, potential risks of hypoglycemia, and necessary prescription changes. Preliminary observations during a 2 1/2-year period from a community support group dedicated to glycemic control on 20 unselected patients (10 with and 10 without use of the device) are summarized., Conclusion: With use of the automated information, the health professional is supported at the point of care to achieve better, safer outcomes and practice evidence-based medicine entirely in lockstep with the CG&MT. This automation helps to overcome clinical inertia.

Is the medical prescription the root cause of the long-term complications of diabetes mellitus? This article presents the argument for introducing prescription checking into diabetes disease management. It discusses an evidence-based need for frequent revisions of the medical prescription as the key to preventing treatment-related complications in diabetes while achieving the now mandated standards in patient care. To do this it will be prudent for diabetes healthcare providers to enrich their clinical services with new information technology-based tools. These are easily acquired by participating in professional workshops focused on advanced diabetes management. In this light, the case presented here challenges leading practitioners to become early participants in the evolution of information technology that will ultimately enhance the management of all patients with diabetes.

Background: Satisfactory glycemic control, meeting American Diabetes Association recommendations, is difficult to achieve. Technologically, this is most likely because the circle of care is incomplete. Many have suggested that the introduction of information technology may remedy the situation. However, previous attempts have not succeeded. Recognizing this, we evolved firmware that supports and links both the patient at home and their care providers in the clinic., Firmware Design and Methods: The device includes software and a database, all contained in a standard USB flash drive. At home, patients use the database portion of the device (MyDiaBase). It fully complements their diabetes education while capturing pertinent self-management information by tracking self-monitored blood glucose data, body weight, medication dosing, physical activity, diet, lifestyle, and stress. In the clinic, providers use the RxChecker program to perform prescription checks that are based on their patients' outcomes data, thereby effectively closing the circle of care., (2009 Diabetes Technology Society.)

Background: Satisfactory glycemic control, meeting American Diabetes Association recommendations, is often accompanied by unsatisfactory hypoglycemia. The converse is also true. We hypothesize that this diabetes treatment dilemma may be resolved by repeated, objective, prescription checks. To do this, a new, two-part device has been developed. It includes a personal diabetes database for the patient and a built-in diabetes prescription checker for the provider. Its goals are to enhance diabetes education and improve patient care., Research Design and Methods: The device includes a database and supporting software, all contained in a standard USB flash drive. Using the medical prescription, body weight, and recent self-monitored blood glucose (SMBG) data, prescription checks can be done at any time. To demonstrate the device's capabilities, an observational study was performed using data from 11 patients with type 1 diabetes mellitus, on intensified therapy, with a mean glycated hemoglobin A1c <7%, and who all suffered intractable hypoglycemia. Patients had performed SMBG contours on successive days at monthly intervals. Each contour included pre- and postmeal as well as bedtime measurements. The replicated contours were used to predict the patient's glycemic profile each month. Applying a built-in simulator to each profile, changes in the prescription were explored that were consistent with reducing the recalcitrant hypoglycemia., Results: A total of 110 glycemic profiles containing 822 profile points were explored. Of these profile points, 351 (43%) showed risks of hypoglycemia, whereas 385 (47%) fell outside desired ranges. With the simulated changes in the prescription, the predicted risks of hypoglycemia were reduced 2.5-fold with insignificant increases predicted in hemoglobin A1c levels of +0.6 +/- 0.9%., Conclusions: A novel support tool for diabetes promises to resolve the diabetes treatment dilemma. Supporting the patient, it improves self-management. Supporting the provider, it reviews the medical prescription in light of objective outcomes and formalizes interventions for maximum safety and efficacy., (2009 Diabetes Technology Society.)

Background: Hypoglycemia is a risk factor common to all insulin therapy. The hypothesis is that efforts to reduce or prevent this adverse side effect may fail because providers generally lack the resources to predict not only future blood glucose levels but also future risks of hypoglycemia. This lack has been remedied. A controlled study was undertaken to test the hypothesis., Methods: Twenty-two insulin dependent subjects suffering more than one (1) episode/week of hypoglycemia with similar insulin regimens, similar diabetes education and similar self-management training participated in this study. For all subjects, a remote monitoring resource (registry and database) was used to capture daily SMBG and afford a return path for provider interventions and decision support. Identical telemedical methods were used which differed only for the provider either by the presence (prediction group) or by the absence (control group) of an on-screen, visual display of predicted glycemia and predicted risks of hypoglycemia. The study lasted 2 months., Results: Over an average of 41 days from baseline to follow up and while using the glycemic prediction resource, providers intervened more effectively in the prediction group reducing rates of hypoglycemia nine-fold (P<0.0001) and insulin therapy by just -9 U/day (P<0.01). Mean pre-meal glycemia was not compromised. Over 61 days from baseline to final follow up but without glycemic predictions in the control group, providers' interventions were less effective and resulted in no net changes in rates of hypoglycemia, daily insulin therapy, or mean pre-meal glycemia., Conclusions: Given knowledge of future glycemia and future risks of hypoglycemia, providers in clinical practice can now avert iatrogenic hypoglycemia in less than 2 months. A shared diabetes data center furnishing remote data capture and decision support is fundamental to the implementation of this as a new clinical procedure in diabetes.

Background: Insulin treated diabetic patients often do not adjust their insulin doses. We developed a method to provide a quantitative and qualitative assessment of this behavior., Methods: Fourteen patients provided logbook pages of their self-monitoring of blood glucose (SMBG) data and insulin doses. We compared the actual decisions of patients in real-life to what they would decide on the same SMBG, as an a posteriori exercise. We also compared these decisions and those proposed by 6 diabetologists on the same sets of data to the recommendations made by HumaLink, an automated insulin dosage system., Results: 1) Patients in real-life modified their insulin doses least often. However, given a chance to make these decisions a posteriori, they modified their insulin doses more often. HumaLink proposed changes even more often, and diabetologists were the most aggressive in changing insulin doses. 2) The decisions proposed by the patients in real-life or a posteriori and by the diabetologists were compared to the recommendations made by HumaLink, using a decisions analysis grid (DAG). For these three groups, full disagreement with HumaLink (patient or physician increases while HumaLink decreases and the opposite) was observed for less than 5% of the cases. 3) By comparison to HumaLink, patient decisions seemed guided by the desire to avoid hypoglycemia. By contrast, decisions by diabetologists seemed often to be guided by the desire to avoid hyperglycemia., Conclusion: These methods provide an objective evaluation of insulin dose adjustments by patients with diabetes and may be useful to assess the effectiveness of educational programs.

Aims/hypothesis: Diabetic subjects do home monitoring to substantiate their success (or failure) in meeting blood glucose targets set by their providers. To succeed, patients require decision support, which, until now, has not included knowledge of future blood glucose levels or of hypoglycaemia. To remedy this, we devised a glucose prediction engine. This study validates its predictions., Methods: The prediction engine is a computer program that accesses a central database in which daily records of self-monitored blood glucose data and life-style parameters are stored. New data are captured by an interactive voice response server on-line 24 h a day, 7 days a week. Study subjects included 24 patients with debilitating hypoglycaemia (unawareness), which qualified them for islet cell transplantation. Comparison of each prediction with the actually observed data was done using a Clarke Error Grid (CEG). Patients and providers were blinded as to the predictions., Results: Prior to transplantation, a total of 31,878 blood glucose levels were reported by the study subjects. Some 31,353 blood glucose predictions were made by the engine on a total of 8,733 days-used. Of these, 79.4% were in the clinically acceptable Zones of the CEG. Of 728 observed episodes of hypoglycaemia, 384 were predicted. After transplantation, a total of 45,529 glucose measurements were reported on a total of 12,906 days-used. Some 42,316 glucose predictions were made, of which 97.5% were in the acceptable CEG Zones A and B. Successful transplantation eliminated hypoglycaemia, improved glycaemic control, lowered HbA(1)c and freed 10 of 24 patients from daily insulin therapy., Conclusions/interpretation: It is clinically feasible to generate valid predictions of future blood glucose levels. Prediction accuracy is related to glycaemic stability. Risk of hypoglycaemia can be predicted. Such knowledge may be useful in self-management.

Objective: Self-blood glucose control is crucial to improving long term outcomes in diabetes. To facilitate this task, we offered patients access to a remote computer continuously online for data collection, dosing decision support, and medical monitoring. Imbedded algorithms for home glucose clamping were custom programmed for each patient. The objectives of the present work were to determine what proportion of patients chose to use such support and whether users benefited from the effort compared to non-users., Research Design and Methods: A single central computer system was used. Algorithms for home glucose clamping were custom programmed for each patient by their physician who set glucose targets, clamping factors and safety constraints. The systems were voice-interactive and required the remote patient to handle only a touch-tone telephone. Patients were free to access the system each day to report self-measured blood glucose levels or hypoglycemia symptoms together with carbohydrate counting, planned exercise, stress, illness or other life-style events. Clinical experience was in patients followed for 12 months in samples derived from three health-care environments., Results: Some 388 patients were offered access to the system. Sixty percent of patients (N=231) actively used the system. Among the 3 study centers, over 104,000 blood glucose measurements were received during the start-up year. Each call was processed instantly and automatically. Patients benefited from the 24 hours access. Those receiving algorithmic assistance for home glucose clamping adjusted daily therapy more effectively: prevalence of hyper-glycemia and hypo-glycemia fell ~ 2-fold (p<0.05) and glycated hemoglobin levels declined 1.3% (p<0.001)., Conclusions: Physicians and patients benefited. Patients with diabetes may be receptive to computer assistance. Many can accomplish glucose clamping at home and meet targets set by their physicians for self-blood glucose control while reducing the incidence of diabetic crises. The centralized system adds no costs for the patients and empowers physicians to provide safer and superior diabetes care.

Two mathematical models for the description of diabetic patient glucose behaviour are proposed. Unlike high order differential-equation based compartmental models, these models employ only the data typically available to a diabetic patient: the history of measured blood glucose concentrations and of insulin injections. The model structures are compared with a native benchmark (zero-order hold) model in a computer simulation. It is demonstrated that, given four daily blood glucose measurements and two daily insulin injections, a parametrized model of patient blood glucose response to insulin can provide relevant data in the estimation of a patient's future blood glucose response in terms of past blood glucose measurements and insulin injections. Parametrized model root means squared errors of glycaemic predictions for 18 simulated patients ranged from 7-22 mg dl-1, as compared with 19-42 mg dl-1 for the benchmark model.

Sustained improvement in blood glucose control is the only treatment outcome which will reduce or eliminate the long term complications of diabetes mellitus. We have designed and evaluated an electronic information system which facilitates this task. The system is voice-interactive, physician directed and affords, to remote patients, 24 h access via touch-tone telephone. Accordingly, patients access the system each day to report self-measured blood glucose levels or hypoglycaemic symptoms together with dietary changes, planned exercise, stress, illness or other lifestyle events. In turn they receive immediate advice with respect to medication dosing changes, and other pertinent feedback. Preliminary system beta-testing for safety and efficacy was performed for one year in an open study of 204 patients derived from two independent, health-care environments. Among the two testing centres, over 60,000 telephone cells were received by the computer systems during the start-up year. Safety and efficacy expectations were met. In addition, prevalence of diabetes related crises (hyperglycaemia or hypoglycaemia) fell approximately 3-fold. Glycated haemoglobin fell significantly (1.0-1.3%) in patients actively using the system. In control groups of patients not actively using the system, there were no improvements in metabolic control while body weights were stable in all groups. The new system was safe and effective in our hands and empowered our health professionals to provide improved diabetes care.

Because the dog can respond to a mixed-meal challenge with little or no change in plasma glucose concentration, we used kinetic techniques to quantify the magnitude and duration of changes in glucoregulation. Glucose turnover was measured using [3-3H]glucose and [U-14C]glucose over two 19-h periods in healthy dogs, first during a fast (n = 6) and then throughout the postprandial state (n = 6) after a single mixed meal. Mean arterial glycemia remained constant in the fasted state (7.5 +/- 0.2 mM) and in the fed state (7.6 +/- 0.3 mM). Glucose appearance (Ra), however, increased slowly after the meal from 38 +/- 2 mg/min to a maximum of 79 +/- 8 mg/min after 6 h and stayed elevated until 12 h (P < 0.001). In parallel, glucose disappearance (Rd) rose from 35 +/- 3 to 83 +/- 7 mg/min, closely matching the corresponding Ra. Glucose recycling rose from 25 +/- 8% at baseline to a maximum of 53 +/- 15% (P < 0.05) at 14 h in fed dogs, whereas levels for fasted dogs stayed between 19 +/- 7% at 0 h and 27 +/- 12% at 6 h. Insulin levels rose significantly 30 min after the meal from 67 +/- 7 pM to a peak of 208 +/- 54 pM at 6 h but remained elevated for 12 h. We conclude that 1) the dog was able to maintain postprandial glucoregulation by very precise matching of Ra and Rd such as to maintain glycemia constant.(ABSTRACT TRUNCATED AT 250 WORDS)

In order to elucidate the effect of a relative time delay on glucose regulation, we performed experiments with differently timed infusions of insulin and glucose in a canine model. When portal insulin infusion (0.03 U/kg over 5 minutes) preceded portal glucose infusion (0.05 g/kg over 5 minutes) by 1 minute, glycemia increased to a maximum value of 104 +/- 4 mg/dL at 6 minutes, whereas insulinemia peaked at 3 minutes at a level of 130 +/- 4 microU/mL (baseline, 21 +/- 7 microU/mL). C-peptide levels increased from 200 +/- 50 to 270 +/- 30 pmol/L. Glycemia then decreased to a minimum level of 61 +/- 4 mg/dL, significantly lower (P less than .02) than the corresponding values in control experiments when insulin was infused alone. With a reversed timing sequence of infusions with glucose infusion preceding insulin infusion by 1 minute, glycemia increased similarly, but decreased to a minimum level of only 84 +/- 4 mg/dL, which was significantly higher (P less than .01) than in the above experiment. Insulinemia peaked similarly at 126 +/- 7 microU/mL, and C-peptide increased from 210 +/- 50 to 280 +/- 50 pmol/L. These experiments demonstrated an unexpected effect: adding glucose to an insulin infusion almost doubled the biological activity of the exogenous insulin as measured by its hypoglycemic action. They also indicated that small perturbations of glycemia and insulinemia in the portal circulation have a profound effect on metabolism, and that even short relative time delays in elevating either insulinemia or glycemia can cause significantly different metabolic outcomes.(ABSTRACT TRUNCATED AT 250 WORDS)

A controlled trial of a new microprocessor device for insulin-dosage adjustment was undertaken in two matched groups of a priori well-controlled diabetic children. A prospective study design with three equal 8-wk periods was used. In the first period, both groups used manual methods for insulin-dosage adjustment after manual criteria. In the second period, one group of children adjusted insulin dosage by computer algorithms, whereas the other continued to use manual methods. In the third period, both groups again adjusted insulin by traditional methods. Mean premeal glycemia and glycosylated hemoglobin levels did not change in either group throughout the study. During the second period, episodes of hypoglycemia were more frequent in children without the computer than in those who used the device. In keeping with the latter outcome, the group that used the microprocessor device was given less insulin in the second period than the first (0.88 +/- 0.02 vs. 0.94 +/- 0.02 U.kg-1.day-1, P less than 0.0001) and in comparison to the control group of patients who concurrently were given an increased insulin dose in the second period compared with the first. This study showed that insulin treatment through specific computer-mediated dosage-adjusting algorithms was safe and minimized hypoglycemia by effectively accommodating seasonally changing insulin requirements. We recommend the device to help diabetic children and their families in the care of insulin-dependent diabetes.

Adjustment algorithms for conventional insulin therapy must be tested for safety and efficacy before clinical implementation. We did this by computer simulation. Accordingly, a computer simulator of human intermediary metabolism created 10 randomly chosen diabetic subjects for study. All were well defined with respect to compliance (i.e., medication and diet) and life-style (i.e., physical and emotional stress). Insulin-adjustment algorithms that were tested calculated daily insulin dosages for these computer-simulated patients based on either blood or urine glucose concentrations self-measured 4 times/day before breakfast, lunch, dinner, and bedtime snack. The twofold purpose of the simulation study was to determine the ability of the adjustment algorithms to improve initially poor metabolic control and to compare the outcomes when either blood or urine glucose measurements were the basis on which glycemic control was implemented. A significant improvement in metabolic control could be achieved with either blood or urine glucose measurements as input to the algorithms. Detailed comparisons between blood and urine glucose-based treatments showed no significant advantage of blood glucose-based algorithms at breakfast (122 +/- 21 vs. 131 +/- 16 mg/dl) and dinner (117 +/- 27 vs. 130 +/- 23 mg/dl), whereas mean glycemia at lunch (122 +/- 24 vs. 164 +/- 21 mg/dl) and bedtime (117 +/- 25 vs. 150 +/- 21 mg/dl) after 120 days of simulation did differ significantly (P less than 0.01). Hypoglycemia was not provoked by either treatment. Total daily insulin doses evolved by blood glucose-based algorithms were significantly (P less than 0.05) higher than the doses used by urine glucose-based algorithms (53 vs. 47 U).(ABSTRACT TRUNCATED AT 250 WORDS)

Modern technology and dedicated micro-processors in particular, are revolutionizing the treatment of diabetes. Through specialized centres and a select group of new medical experts, conventional diabetes management is gradually being replaced by a system of technology assisted self-care. The present paper outlines the characteristics of six consecutive generations of a new device called an insulin dosage computer. It facilitates self-care by calculating insulin dosages each day at each meal based on glucose measurements made by the patients themselves. The device was initially developed in 1982 and is now extended to over 1200 patients each of whom has acquired expert skills for self-management and thereby achieved improved metabolic control with freedom both from hypoglycemia and from the psychological dependencies usually accompanying this disorder.

Exogenous insulin exists primarily as the monomer in human plasma. However, in U100 regular insulin formulations, the concentrations of zinc and peptide are such that the insulin hexamer predominates. The biologic result is further disassociation to the monomer after subcutaneous or i.v. administration. Because of this, human plasma from seven normal controls dissolved 20-30 microm hexagonal insulin crystals in 3-8 min. This ability was inhibited by acid titration to a stable pH of 6.30, at which point bicarbonate depletion could be suggested. Repletion of bicarbonate remarkably restored the solvent effect, while back-titration to the initial pH without repleting bicarbonate had only a moderate result. To establish whether the in vivo reduction of bicarbonate in pathologic states had similar results, plasma from five Type I diabetics in severe acidosis (pH 7.06 +/- 0.04, HCO3 -7.3 +/- 0.6 mmol/l) was similarly studied after stabilization under 5% CO2 (pH, 6.97-7.17). In all cases, the dissolution of insulin crystals was inhibited (dissolution times greater than 25 min). When bicarbonate was replenished (HCO3- 24.1-26.7 mmol/l) and pH accordingly renormalized (pH 7.39-7.43), the dissolution of insulin crystals was completely restored. Because of these observations, we conclude that both plasma bicarbonate and pH markedly affect the dissolution of insulin and that reduced bicarbonate/pH in diabetic ketoacidosis may limit the availability of the biologically active monomer. These influences may play a role in the initial insensitivity to insulin frequently seen in severe insulin deficiency and ketoacidosis.

A physiologic additive for dissolving insulin crystals for parenteral application has been found. Insulin crystals are relatively insoluble in simple aqueous solutions. They will dissolve, however, in highly acidic solutions, but these are not suitable for parenteral use. Both neutral and acid pH insulin solutions have a tendency for the dissolved hormone to reaggregate. Notwithstanding possible changes in biologic activity, such formed aggregates must be prevented because they interfere with the flow in portable insulin delivery devices and result in the loss of glycemic control. The addition of 1.5% autologous serum to the aqueous diluent for insulin has eliminated these difficulties and increased by 37% the apparent biologic activity of insulin solutions prepared in this way. With this additive, continuous uninterrupted intravenous insulin infusion has provided near ideal blood glucose control in four pancreatectomized dogs for 5 mo and four patients with juvenile-onset diabetes for 18--23 days. Serum apparently contains factor(s) that promote the dissolution of insulin and prevent the formation of peptide aggregates in dilute solutions.

An extracorporeal "closed-loop" system has been employed to maintain glycemia in the normal range during consumption of meals in nine insulin-treated diabetics. This artificial pancreas system incorporated continuous blood glucose monitoring (0.05 ml. per minute, delay time 90 seconds), a computer programed to respond to glycemia, and a hormone delivery system. Intravenous insulin delivery rates were determined by control parameters responsive to both glucose concentration and its rate of change. Because insulin-dependent diabetics often defend themselves poorly against hypoglycemia (in some cases due to inadequate glucagon responses), the instrument was also programed for exogenous glucagon delivery. A priori selection of ideal parameters for insulin and glucagon delivery for each individual is not yet possible. Consequently, when the parameters were used for the first time on each subject, they were varied over a reasonable range. This approach resulted in a corresponding variety of glycemic responses, the average of which characterized a set of initial parameters that is generally applicable. Appropriate control parameters are presented that successfully prevented hypoglycemia. Glucagon delivery directly related to glycemia appeared sufficient for this purpose, thus obviating the need for dextrose administration. This system provides a technique for complete normalization of blood glucose concentration in the types of diabetics tested, during both fed and interprandial periods. It has yielded insights essential to the development of more sophisticated future devices.

This paper describes a miniature precision peristaltic pump and a silicone rubber reservoir developed for the infusion of insulin in diabetic subjects. The ability of the 100-ml reservoir to maintain sterility of its contents over 26 refilling cycles (48 days) is demonstrated. Accelerated bench tests on 10 pumps over 30 days indicate an accuracy of +/- 1% on flow rate whether measured over 10 min or 24 h and with or without 1 atm of outlet back pressure. Comparison of calibrations made before and after 58 animal and clinical tests of 6--71 days' duration showed a percentage difference in calibration that varied with a mean +/- SD of 0.05 +/- 3.09%. Microscopic examination of pump tube samples after 21 days of clinical use indicated redistribution of surface material without evidence of particle spallation. Samples subjected to accelerated wear equivalent to 620 days of clinical use showed extensive luminal surface modification and particulate deposits on downstream filters. These were identified by X-ray spectroscopy as silicon compounds.

The artificial endocrine pancreas (AEP) can normalize glycemia at rest and with meals. To determine whether insulin, glucagon, and amino acid profiles are also normalized, nine diabetics on subcutaneous insulin (S/C) and AEP control were compared to ten normal controls (NC). Glycemia was monitored continuously over 10 hr during which meals were consumed. Insulin infusion rate, and the levels of immunoreactive insulin (IRI) (in NC), free insulin (in S/C and AEP), C-peptide, glucagon, and amino acids are reported. Glycemia in AEP started at somewhat higher levels than in NC, but with breakfast and thereafter, it was identical. In S/C, hyperglycemia prevailed throughout, with no systematic change in free IRI. In AEP, both basal and peak free insulin levels, measured in four patients, were significantly higher than in NC. C-peptide values were significantly lower in diabetics and did not change with meals. Basal glucagon values were not different in the three groups and changes with meals were of small magnitude. Branched chain amino acids were higher in S/C and did not increase as in NC. In AEP, levels were lower than NC after the first two meals. Similarly, lysine and threonine were lower in AEP than in NC at the same times. Alanine, though similar at the onset, was lower 2 hr postbreakfast and higher 2 hrs postsupper in AEP and S/C compared to NC. These studies demonstrate that glycemic control with AEP is accompanied by hyperinsulinemia, which could account for the amino acid responses and the small alterations in immunoreactive glucagon (IRG) patterns. Further refinement is needed to obtain full normalization of metabolic profiles.

Hyperinsulinism frequently accompanies glucose normalization in type I diabetes but the long-term consequences of this exaggerated hormonal state are not known. To study this condition, normal dogs received constant exogenous sulfated insulin infusions for prolonged periods up to 43 weeks. During the interval and inspite of prevailing postabsorptive and fasting hypoglycemia, overt resistance to the infused insulin or loss of sensitivity did not occur. In counterring the imposed fasting hyperinsulinemia and the resulting hypoglycemia, fasting pancreatic glucagon levels rose while the fasting levels of several glucogenic precursors (lactate, pyruvate, and alanine) decreased. Fasting free fatty acid (FFA) levels were suppressed, but beta-hydroxybutyrate (beta-OHB) levels were unchanged. Body weight did not change. Most remarkably, all changes measured in the fasting levels of the hormones and metabolites reverted to normal following the cessation of exogenous sulfated insulin infusion. In addition to the hormonal and metabolite adaptations invoked by chronic exogenous hyperinsulinism in the fasting state of these normal dogs, there were interesting responses to their usual mixed meals. Of particular interest in this regard were the plasma glucose, insulin, and FFA diurnal profiles. First of all, a definite and unusual postprandial glycemic excursion occurred. Second, insulin levels were elevated some sixfold, and rather unresponsive to the meal in general. Inspite of the depressed fasting FFA levels and the absence of a postprandial rise in insulinemia, FFA showed a distinct fall after the meal. Whether the sulfated insulins infused were of the bovine or porcine species of origin made no discernible difference.(ABSTRACT TRUNCATED AT 250 WORDS)

Various routes of insulin infusion have been utilized to improve metabolic control in type I (insulin-dependent) diabetes. To determine the relative effectiveness of subcutaneous (SC) and intravenous (IV) systems of insulin-pump therapy, we studied five type I diabetic subjects aged 20-39 yr who were randomly assigned to a 3-mo period of either SC or IV insulin infusion and then crossed over to the alternate route for a similar period. After an initial 7- to 14-day period of in-hospital insulin-dose adjustment, all subjects were similarly followed as outpatients during both infusion periods, with a minimum of four daily preprandial self-measurements of blood glucose. Although the overall mean levels of blood glucose and HbA1c (116 +/- 6 vs. 114 +/- 5 mg/dl and 6.1 +/- 0.2 vs. 5.9 +/- 0.1% for the SC and IV systems, respectively) were similar, there was a greater incidence of low (less than 50 mg/dl) and high (greater than 180 mg/dl) preprandial blood glucose readings during SC- than during IV-pump therapy (P less than .05). Furthermore, the frequency of nocturnal and preprandial hypoglycemia was greater during SC-pump therapy (P less than .05 and P less than .02, respectively). Eight documented technical problems related to the pump and catheter occurred with the SC system, whereas 17 episodes occurred with the IV system. The number of episodes of ketosis (4 vs. 5 for SC and IV, respectively) was similar with both systems.(ABSTRACT TRUNCATED AT 250 WORDS)