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Changes In Diabetes Care A History Of Insulin & Pumps Past, Present, and Future John Walsh, P.A, C.D.E. Online slide presentation
© 2004, John Walsh, P.A., C.D.E. What We Will Cover Early history of diabetes Discovery of insulin When insulin was found to not be the full answer High glucose as the culprit Lack of change in the A1c since the DCCT Why the dumb insulin pump has not helped What smart pumps offer The promise of intelligent devices The Super Bolus How simple and intelligent timers can help Screen shots from an intelligent device
© 2004, John Walsh, P.A., C.D.E. In 1500 BC Diabetes First Described In Writing Hindu healers wrote that flies and ants were attracted to urine of people with a mysterious disease that caused intense thirst, enormous urine output, and wasting away of the body
© 2004, John Walsh, P.A., C.D.E. 250 BC The Word Diabetes First Used Apollonius of Memphis coined the name "diabetes meaning "to go through" or siphon. He understood that the disease drained more fluid than a person could consume. Gradually the Latin word for honey, "mellitus," was added to diabetes because it made the urine sweet.
© 2004, John Walsh, P.A., C.D.E. Diabetes is a wonderful affection, not very frequent among men, being a melting down of the flesh and limbs into urine…The flow is incessant, as if from the opening of aqueducts…it takes a long period to form, but the patient is short-lived…for the melting is rapid, the death speedy. Moreover, life is disgusting and painful; thirst unquenchable; excessive drinking…and one cannot stop them either from drinking or making water... they are affected with nausea, restlessness, and a burning thirst; and at no distant term they expire. 150 BC Aretaeus the Cappadocian
© 2004, John Walsh, P.A., C.D.E. Early Diabetes Treatments In 1000, Greek physicians recommended horseback riding to reduce excess urination In the 1800s, bleeding, blistering, and doping were common In 1915, Sir William Osler recommended opium Overfeeding was commonly used to compensate for loss of fluids and weight In the early 1900s a leading American diabetologist, Dr. Frederick Allen, recommended a starvation diet
© 2004, John Walsh, P.A., C.D.E. Early Research In 1798, John Rollo documented excess sugar in the blood and urine In 1813, Claude Bernard linked diabetes to glycogen metabolism In 1869, Paul Langerhans, a German medical student, discovered islet cells in the pancreas In 1889, Joseph von Mehring and Oskar Minkowski created diabetes in dogs by removing the pancreas In 1910, Sharpey-Shafer of Edinburgh suggested a single chemical was missing from the pancreas. He proposed calling this chemical "insulin."
© 2004, John Walsh, P.A., C.D.E. Near Miss In 1908, a young internist in Berlin, Georg Ludwig Zuelzer created a pancreas extract named acomatrol. After injecting acomatrol into a dying diabetic patient, the patient improved at first, but died when the acomatrol was gone Zuelzer filed an American patent in 1911 for a "Pancreas Preparation Suitable for the Treatment of Diabetes Disappointing results, however, caused his lab to be taken over by the German military during WWI
© 2004, John Walsh, P.A., C.D.E. Other Pancreas Extractors American scientist E. L. Scott was partially successful in extracting insulin with alcohol A Romanian, R. C. Paulesco, made an extract from the pancreas that lowered the blood glucose of dogs. Some claim Paulesco may have been the first to discover insulin about 10 years before Banting and Best.
© 2004, John Walsh, P.A., C.D.E. Before Insulin Before insulin was discovered in 1921, everyone with type 1 diabetes died within weeks to years of its onset JL on 12/15/22 and 2 mos later
© 2004, John Walsh, P.A., C.D.E Leonard Thompson In Jan, 1922, Banting and Best injected a 14-year-old "charity patient who weighed 64 lb with 7.5 ml of a "thick brown muck" in each buttock Abscesses developed and he became more acutely ill However, his blood glucose had dropped enough to continue refining what was called "iletin insulin 6 weeks later, a refined extract caused his blood glucose to fall from 520 to 120 mg/dL in 24 hours Leonard lived a relatively healthy life for 13 years before dying of pneumonia (no Rx then) at 27
© 2004, John Walsh, P.A., C.D.E. Insulin Production Begins First produced as Connaught by the Univ of Toronto On May 30, 1922, Eli Lilly signed an agreement to pay royalties to the University to increase production First bottles contained U-10 insulin 3 to 5 cc were injected at a time Pain and abscesses were common until purer U-40 insulin became available
© 2004, John Walsh, P.A., C.D.E. Impact Of Insulin On Life Expectancy By The 1940s Age at start of diabetes Avg. age of death in Avg. age of death in Years Gained82634
© 2004, John Walsh, P.A., C.D.E. Not A Cure Some early users died of hypoglycemia, but insulin seemed a remarkable cure. By the 1940s, however, diabetic complications began to appear It became clear that injecting insulin was not the full answer
© 2004, John Walsh, P.A., C.D.E. What Caused Complications? High Glucose Versus Genes During the middle of the 20th century, it was unclear whether better glucose control could prevent diabetes complications
© 2004, John Walsh, P.A., C.D.E. DCCT And Other Studies Results Better health Fewer complications Improved sense of well-being More flexible lifestyle Studies DCCT EDIC 1996 UKPDS Kumamoto Research studies between 1970 and 2000 showed that complications could be prevented by lowering high glucose levels
© 2004, John Walsh, P.A., C.D.E. Little Change In A1c Since DCCT 8.6% in 396 Canadian Type 1s in % in 1,120 German children in % in in U.S. in NHANES III, 1988 to % in 2,873 European children and adolescents in % in 62 Canadian Type 1s in HB Mortensen et al: Diabetes Care May;20(5): Diabetes Care May;20(5): Horm Res 1998;50:107–140 GOAL: A1c < 6.5%
© 2004, John Walsh, P.A., C.D.E. We Know What Controls The A1c Frequency of testing 378 pump (pre-smart) users Paul Davidson et al: Diabetes
© 2004, John Walsh, P.A., C.D.E. Controls The A1c Frequency of daily boluses yo pump users, r = TJ Battelino et al: Diabetes 2004 For injections: MP Garancini et al: Diabetes Care, 1997, 20, #11:
© 2004, John Walsh, P.A., C.D.E. Controls The A1c Recording of BGs 0.5% drop in A1c in several studies Diet Approach 1 CHO Counting Regulated WAG 1. Bode et al: Diabetes, 1999, 48 Suppl 1: % 7.5% 8.0%
© 2004, John Walsh, P.A., C.D.E. Pre/Post DCCT A1c Results On 4 inj. 27.8% (0.4%)72.6% (6.4%) or a pump Median A1c 8.3%8.3% 18,403 German children W Hecker et al: 2004 ADA, poster 22B
© 2004, John Walsh, P.A., C.D.E. What Causes High A1cs? Inaccurate carb counting * Insulin doses that are incorrect, misunderstood, or missed entirely * Too hard to log all the data * Not adapting to spontaneous events * Complexity of the challenge * Unclear accountability * * handled by well-designed intelligent device
© 2004, John Walsh, P.A., C.D.E. Noncompliance is not a patient problem. It is a system failure. Dr. Paul Farmer First to successfully use complex drug regimens to treat AIDs and TB in Haiti Our Current Diabetes Approach Does Not Work
© 2004, John Walsh, P.A., C.D.E. Current Treatment Interval (CTI) Unlike many other chronic diseases where CTI is not critical, the current treatment interval in diabetes with a doctors visit every 3 to 4 months does not work
© 2004, John Walsh, P.A., C.D.E. Required Treatment Interval (RTI) The required treatment interval in diabetes is every 2 to 5 hours rather than 3 to 4 months This is the typical time interval between decisions that significantly affect glucose levels, such as BG monitoring, food intake, and activity Only something that is both available and intelligent can assist the person with a chronic disease like diabetes
© 2004, John Walsh, P.A., C.D.E. When a system is not working for patients, trying harder will not work. Only changing the care system or our approach to care will work.
© 2004, John Walsh, P.A., C.D.E. Convergence Toward Automation InsulinInsulin MonitoringMonitoring HCPSelf ManagementAutomation Insulin & syringes Pumps Pens Connectivity Clinic Monitoring Home Monitors Data Management Advice/Feedback Open Loop DeliveryDelivery Closed Loop You are here
© 2004, John Walsh, P.A., C.D.E. Dumb Smart Intelligent Automatic Results over Features! Do not judge a device by how cool it is, but by whether it lowers the A1c.
© 2004, John Walsh, P.A., C.D.E. Todays Smart Pumps Carb boluses Personalized carb factors for different times of day Easy carb bolus calculations Personalized carb database (soon) Correction boluses Personalized correction factors for different times Easier and safer correction of high BGs Reveal when correction bolus is high, ie > 8% of TDD Combined carb/correction boluses Automatic bolus reduction for Bolus On Board (BOB)
© 2004, John Walsh, P.A., C.D.E. Todays Smart Pumps Track Bolus On Board Improved bolus accuracy Avoids stacking of bolus insulin Helps prevent hypoglycemia Requires BG reading for accuracy Guide whether carbs or insulin are needed Does not yet warn when carbs are needed
© 2004, John Walsh, P.A., C.D.E. Todays Smart Pumps Reminders to Test blood glucose after a bolus Warn when bolus delivery was not completed Test blood glucose following a low or high BG Give boluses at certain times of day Change infusion site Direct BG entry from meter Eliminates errors in data transfer Ensures that all blood glucose data will be entered into a database or logbook format
© 2004, John Walsh, P.A., C.D.E. Smart Pumps Do Not: Todays pumps collect the information needed (insulin doses, BGs, carb intake, and timing), but they do not: Identify problem patterns Automatically test basals and boluses or warn when they are out of balance Suggest dose adjustments Warn of pending lows or suggest carb intake needed for excess BOB Warn when excess correction boluses are used Account for GI differences between foods Guarantee an improved outcome
© 2004, John Walsh, P.A., C.D.E. Intelligent Devices Todays smart pumps are migrating to better pumps, pens, and PDAs Calculus rather than formulas to set bolus amounts Auto analysis of BG patterns Fuzzy and artificial intelligence Provide automatic (retrospective) carb/insulin balance Use of A1c to focus therapy
© 2004, John Walsh, P.A., C.D.E. The Intelligent Device Hypothesis Intelligent devices: * provide meaningful advice, * * improve lifestyles, * * improve medical outcomes with diabetes.* Made by Unidentified company here * Yet to be proven
© 2004, John Walsh, P.A., C.D.E. Smart Vs Intelligent Devices FeatureSmartIntelligent Carb listAlphabeticBy recent use Basal testingBy userAutomatic Bolus testingBy userAutomatic ExerciseNAAutomatic TimerManualAutomatic Corr. bolusIgnoredRedistributed Super BolusNoneAutomatic # of hyposBy userAutomatic CommunicationVerbalBidirectional
© 2004, John Walsh, P.A., C.D.E. Intelligent Devices Pumps Pens PDAs Smart Phones Meters A central reporting station where data is filtered for minor versus major problems and who is to be alerted (user, guardian, MD/RN)
© 2004, John Walsh, P.A., C.D.E. Demands On Intelligent Devices Intuitive interface and language Must be impartial and fair Outcome driven – user feels better and is more confident about control Compatible with clinic workflow Well funded Able to rapidly evolve as errors appear Must close the data loop between user and MD
© 2004, John Walsh, P.A., C.D.E. Intelligent Device Ingredients Automatic BG timer Automatic basal decrease Super Bolus Automatic basal/bolus balancing Automatic adjustment when correction boluses are overused Carb list and carb counter Exercise intensity and duration Database intelligence
© 2004, John Walsh, P.A., C.D.E. Intelligent Device Benefits Provide immediate advice on situations Identify common or infrequent patterns Constant surveillance of data for changes Provide real meaning to BG values Integrate well with continuous monitoring and artificial intelligence
© 2004, John Walsh, P.A., C.D.E. Smart Phones And PDAs Fast internet & communication Convenient remote insulin delivery Larger food and carb database Better graphics for BG analysis, display of patterns, etc Larger event database for long-term analysis
© 2004, John Walsh, P.A., C.D.E. Intelligent Devices 300 personal carb selections with accurate carb counts Carb factor (1:1 TO 1:100) Correction factor (1:4 to 1: 400) 5 sec microdraw BG meter 0.1 unit precision motor Non-volatile memory 3,000 events Bluetooth data transfer
© 2004, John Walsh, P.A., C.D.E. Thoughts And Developments For The Future
© 2004, John Walsh, P.A., C.D.E. Old Basal/Bolus Concepts Basal insulin ~ 50% of daily insulin need Limits hyperglycemia after meals Suppresses glucose production between meals and overnight Bolus insulin (mealtime) Limits hyperglycemia after meals Immediate rise and sharp peak at 1 hour 10% to 20% of total daily insulin requirement at each meal
© 2004, John Walsh, P.A., C.D.E. New: Rapid Basal Reduction A rapid basal reduction offsets excess BOB and eliminates the need to eat at bedtime.
© 2004, John Walsh, P.A., C.D.E. New: The Super Bolus A Super Bolus helps cover high GI foods and prevent postmeal hyperglycemia. A 3 or 4 hour block of basal insulin is turned into a bolus to speed its effect. A Super Bolus can be activated at a user-selected quantity, such as 40 or 50 grams
© 2004, John Walsh, P.A., C.D.E. New: The Super Bolus To ensure safety and success, the Super Bolus will require some clinical testing: How long can basal delivery be stopped or reduced without increasing the risk for clogging of the infusion line How long (3, 4, 5 hours?) can the basal be lowered before a rebound high will occur once the Super Bolus is gone? Is a reduction of the basal delivery rather than complete stoppage a better policy? If a person sets their basal delivery too low or too high, will this affect a Super Bolus?
© 2004, John Walsh, P.A., C.D.E. New: High BG Super Bolus If a pumper misjudges the carb content of a meal, a super bolus enables a faster, safe correction.
© 2004, John Walsh, P.A., C.D.E. New: A Reminder Timer A simple timer alerts the user 25 minutes after a bolus that it is safe to begin eating a high GI meal.
© 2004, John Walsh, P.A., C.D.E. New: An Intelligent Reminder An intelligent pump alerts the user when their BG is likely to cross a selected threshold value, such as 120 mg/dl. They can then eat without exposure to extremely high readings.
© 2004, John Walsh, P.A., C.D.E. New: Less Glucose Exposure The lower the blood glucose is at the start of a meal, the less exposure to glucose there will be.
© 2004, John Walsh, P.A., C.D.E. New: An Intelligent Reminder An intelligent pump alerts the user when their blood glucose is low enough to begin eating
© 2004, John Walsh, P.A., C.D.E. Future Intelligent Devices Useful reminders
© 2004, John Walsh, P.A., C.D.E. Future Pattern Management Finding problem patterns enables solutions Set BG targets Gather and record data Analyze patterns in data Assess factors that influence patterns Recommend action
© 2004, John Walsh, P.A., C.D.E. Only A Few Patterns The relatively low number of BG patterns in diabetes makes them easy to identify: High most of the time Frequent lows High mornings (lunches, dinners, bedtime) Low mornings (lunches, dinners, bedtime) Postmeal spiking High to low Low to high Poor control with little or no pattern
© 2004, John Walsh, P.A., C.D.E. Pattern Analysis: Low-High pm 320. Overtreated low
© 2004, John Walsh, P.A., C.D.E. Low High Pattern Alert Insulin dose suggestions and an alert about past overtreatment of lows.
© 2004, John Walsh, P.A., C.D.E. Low High Pattern Alert An intelligent device can provide a persons precise carb requirement when the blood glucose is tested.
© 2004, John Walsh, P.A., C.D.E. Easy Analysis Breakfast Breakfast highs
© 2004, John Walsh, P.A., C.D.E. Overnight Basal Patterns bedtime2 ambreakfast basal too low Dawn Phenomenon just right too high Goal for overnight BG change = +/- 30 mg/dl just right
© 2004, John Walsh, P.A., C.D.E. User Interface – Critical Component Despite 30 years of pump and meter development, device communication to the user is still in its infancy.
© 2004, John Walsh, P.A., C.D.E. Future Intelligent Devices Carb database for accurate carb counts.
© 2004, John Walsh, P.A., C.D.E. Future Intelligent Devices Suggestion for carb intake or to limit intake based on weight/calorie/carb goals
© 2004, John Walsh, P.A., C.D.E. Future Intelligent Devices A high glucose can be analyzed to determine the magnitude of the error
© 2004, John Walsh, P.A., C.D.E. Future Intelligent Devices Recommended carb intake (or insulin reduction) to balance activity.
© 2004, John Walsh, P.A., C.D.E. Future Intelligent Devices New dose recommendations based on A1c, % of TDD given as correction boluses, and frequency of hypoglycemia
© 2004, John Walsh, P.A., C.D.E. Future Intelligent Devices Pattern alerts and advice
© 2004, John Walsh, P.A., C.D.E. Future Intelligent Devices Fast lab results without calling. Messaging allows physician to make recommendations.
© 2004, John Walsh, P.A., C.D.E. Pump Plus Continuous Monitor Automatic basal and bolus testing Trends allow exact short-term BG predictions for rapid recognition of pending highs or lows Both user and device can relate problems to their source Unfortunately, insulin delivery from an external pump is too slow to create an effective artificial pancreas with this combination
© 2004, John Walsh, P.A., C.D.E. The Closed Loop Will Close Slowly Patents impede device development FDA is slow to allow medical care from a device or via telemedicine Slow acceptance by medical personnel and people with diabetes Liability issues Large financial incentives in current meter and pump technology Even so, truly intelligent and helpful devices could be created soon.
© 2004, John Walsh, P.A., C.D.E. Questions ???
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