Materializing Datafied Body Doubles: Insulin Pumps, Blood Glucose Testing, and the Production of Usable Bodies

2019 ◽  
Vol 5 (1) ◽  
pp. 1-26
Author(s):  
Stephen Horrocks
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Insulin Pump ◽  
The Body ◽  
Glucose Testing ◽  
Physiological Processes ◽  
Blood Glucose Testing ◽  
Continued Use ◽  
Data Collections

The network of devices involved in insulin pump treatment reads and quantifies the physiological processes of Type 1 Diabetes as it performs life-sustaining functions inside and upon users’ bodies. Together, these devices gather that information to produce what I call Datafied Body Doubles: numerical stand-ins for the body that recreate them as both usable and controllable for pump users and their physicians. By establishing and normalizing a system of quantification through blood glucose testing and temporally mapping body-readings into data collections, these Datafied Body Doubles fundamentally alter the conceptual and material experience of living with Diabetes. As medically-compelled users, people with Type 1 Diabetes participate in their own datafication through their continued use of those devices—a choice which is not much of a choice at all—but their bodies are re-created and used to drive their participation in those very techno-medicalized treatments nevertheless.

212-LB: Reporting History of Diabetes Symptoms and Random Blood Glucose Testing to Detect Presymptomatic Type 1 Diabetes (T1D) in the General Pediatric Population

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 212-LB
Author(s):  
KATHLEEN WAUGH ◽  
BRIGITTE I. FROHNERT ◽  
MARIAN REWERS ◽  
JUDITH BAXTER ◽  
CRISTY R. GENO RASMUSSEN
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Pediatric Population ◽  
Random Blood Glucose ◽  
Glucose Testing ◽  
Blood Glucose Testing ◽  
History Of

scholarly journals Adherence to Insulin Pump Behaviors in Young Children With Type 1 Diabetes Mellitus

2016 ◽  
Vol 11 (1) ◽  
pp. 87-91 ◽  
Author(s):  
Susana R. Patton ◽  
Kimberly A. Driscoll ◽  
Mark A. Clements
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Glycemic Control ◽  
Young Children ◽  
Type 1 Diabetes Mellitus ◽  
Insulin Pump ◽  
Insulin Use

Background: Parents of young children are responsible for daily type 1 diabetes (T1DM) cares including insulin bolusing. For optimal insulin pump management, parents should enter a blood glucose result (SMBG) and a carbohydrate estimate (if food will be consumed) into the bolus advisor in their child’s pump to assist in delivering the recommended insulin bolus. Previously, pump adherence behaviors were described in adolescents; we describe these behaviors in a sample of young children. Methods: Pump data covering between 14-30 consecutive days were obtained for 116 children. Assessed adherence to essential pump adherence behaviors (eg, SMBG, carbohydrate entry, and insulin use) and adherence to 3 Wizard/Bolus Advisor steps: SMBG–carbohydrate entry–insulin bolus delivered. Results: Parents completed SMBG ≥4 times on 99% of days, bolused insulin ≥3 times on 95% of days, and entered carbohydrates ≥3 times on 93% of days, but they corrected for hyperglycemia (≥250 mg/dl or 13.9 mmol/l) only 63% of the time. Parents completed Wizard/Bolus Advisor steps (SMBG, carbohydrate entry, insulin bolus) within 30 minutes for 43% of boluses. Inverse correlations were found between children’s mean daily glucose and the percentage of days with ≥4 SMBG and ≥3 carbohydrate entries as well as the percentage of boluses where all Wizard/Bolus Advisor steps were completed. Conclusions: Parents of young children adhered to individual pump behaviors, but showed some variability in their adherence to Wizard/Bolus Advisor steps. Parents showed low adherence to recommendations to correct for hyperglycemia. Like adolescents, targeting pump behaviors in young children may have the potential to optimize glycemic control.

scholarly journals Sensor-Augmented Insulin Pumps and Hypoglycemia Prevention in Type 1 Diabetes

2016 ◽  
Vol 11 (1) ◽  
pp. 50-58 ◽  
Author(s):  
Isabelle Steineck ◽  
Ajenthen Ranjan ◽  
Kirsten Nørgaard ◽  
Signe Schmidt
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Insulin Pump ◽  
Glucose Monitoring ◽  
Severe Hypoglycemia ◽  
Insulin Pumps ◽  
Continuous Glucose Monitor ◽  
Insulin Suspension ◽  
Multiple Daily Injections

Hypoglycemia can lead to seizures, unconsciousness, or death. Insulin pump treatment reduces the frequency of severe hypoglycemia compared with multiple daily injections treatment. The addition of a continuous glucose monitor, so-called sensor-augmented pump (SAP) treatment, has the potential to further limit the duration and severity of hypoglycemia as the system can detect and in some systems act on impending and prevailing low blood glucose levels. In this narrative review we summarize the available knowledge on SAPs with and without automated insulin suspension, in relation to hypoglycemia prevention. We present evidence from randomized trials, observational studies, and meta-analyses including nonpregnant individuals with type 1 diabetes mellitus. We also outline concerns regarding SAPs with and without automated insulin suspension. There is evidence that SAP treatment reduces episodes of moderate and severe hypoglycemia compared with multiple daily injections plus self-monitoring of blood glucose. There is some evidence that SAPs both with and without automated suspension reduces the frequency of severe hypoglycemic events compared with insulin pumps without continuous glucose monitoring.

scholarly journals Control of Blood Glucose Level for Type 1 Diabetes Mellitus using Improved Hovorka Equations: Comparison between Clinical and In-Silico Works

2020 ◽  
Author(s):  
Nur’Amanina Mohd Sohadi ◽  
Ayub Md Som ◽  
Noor Shafina Mohd Nor ◽  
Nur Farhana Mohd Yusof ◽  
Sherif Abdulbari Ali ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Blood Glucose Level ◽  
Type 1 Diabetes Mellitus ◽  
Glucose Level ◽  
In Silico ◽  
Artificial Pancreas ◽  
The Body

AbstractBackgroundType 1 diabetes mellitus (T1DM) occurs due to inability of the body to produce sufficient amount of insulin to regulate blood glucose level (BGL) at normoglycemic range between 4.0 to 7.0 mmol/L. Thus, T1DM patients require to do self-monitoring blood glucose (SMBG) via finger pricks and depend on exogenous insulin injection to maintain their BGL which is very painful and exasperating. Ongoing works on artificial pancreas device nowadays focus primarily on a computer algorithm which is programmed into the controller device. This study aims to simulate so-called improved equations from the Hovorka model using actual patients’ data through in-silico works and compare its findings with the clinical works.MethodsThe study mainly focuses on computer simulation in MATLAB using improved Hovorka equations in order to control the BGL in T1DM. The improved equations can be found in three subsystems namely; glucose, insulin and insulin action subsystems. CHO intakes were varied during breakfast, lunch and dinner times for three consecutive days. Simulated data are compared with the actual patients’ data from the clinical works.ResultsResult revealed that when the patient took 36.0g CHO during breakfast and lunch, the insulin administered was 0.1U/min in order to maintain the blood glucose level (BGL) in the safe range after meal; while during dinner time, 0.083U/min to 0.1 U/min of insulins were administered in order to regulate 45.0g CHO taken during meal. The basal insulin was also injected at 0.066U/min upon waking up time in the early morning. The BGL was able to remain at normal range after each meal during in-silico works compared to clinical works.ConclusionsThis study proved that the improved Hovorka equations via in-silico works can be employed to model the effect of meal disruptions on T1DM patients, as it demonstrated better control as compared to the clinical works.

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