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Glucose sensing in the peritoneal space offers faster kinetics than sensing in the subcutaneous space.

Burnett DR, Huyett LM, Zisser HC, Doyle FJ, Mensh BD - Diabetes (2014)

Bottom Line: We compared the temporal response characteristics of simultaneously placed subcutaneous and intraperitoneal sensors during intravenous glucose tolerance tests in eight swine.Using compartmental modeling based on simultaneous intravenous sensing, blood draws, and intraarterial sensing, we found that intraperitoneal kinetics were more than twice as fast as subcutaneous kinetics (mean time constant of 5.6 min for intraperitoneal vs. 12.4 min for subcutaneous).Combined with the known faster kinetics of intraperitoneal insulin delivery over subcutaneous delivery, our findings suggest that artificial pancreas technologies may be optimized by sensing glucose and delivering insulin in the intraperitoneal space.

View Article: PubMed Central - PubMed

Affiliation: Theranova, LLC, San Francisco, CA.

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Sample of compartmental modeling fit to data. This plot shows an example of the model-fitting process for a single challenge, using glucometer measurements as the input. Shown on the plot are the experimental measurements made by the intraperitoneal (IP) and subcutaneous (SQ) sensors, as well as the model predicted output for each sensor model. The goodness-of-fit values for the intraperitoneal and subcutaneous models shown were 89% and 90%, with time constants of 1.7 and 13.1 min, respectively.
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Figure 3: Sample of compartmental modeling fit to data. This plot shows an example of the model-fitting process for a single challenge, using glucometer measurements as the input. Shown on the plot are the experimental measurements made by the intraperitoneal (IP) and subcutaneous (SQ) sensors, as well as the model predicted output for each sensor model. The goodness-of-fit values for the intraperitoneal and subcutaneous models shown were 89% and 90%, with time constants of 1.7 and 13.1 min, respectively.

Mentions: Figure 2B compares the postglucose-bolus recovery between the two sensor spaces in a plot similar to Fig. 2A. The average recovery for the subcutaneous space was 33%, compared with 59% for the intraperitoneal space. For all challenges, the intraperitoneal space showed a more complete return to prechallenge baseline glucose levels than the subcutaneous space (all points above diagonal identity line, P < 0.001 for challenges, P < 0.01 for animals). Finally, we quantified the glucose kinetics of the subcutaneous and intraperitoneal spaces using compartmental modeling in which the glucometer measurements served as an input function and the transport of glucose into the body spaces was modeled with a first-order transfer function. The glucometer measurements were used in place of the YSI measurements because the YSI data were too sparse to use as a model input. This approach yielded excellent fits to the data, as illustrated in Fig. 3; the mean goodness of fit across all challenges was 75.6% (SD 8.5%) for the intraperitoneal sensor data and 83.2% (SD 8.9%) for the subcutaneous sensor data. The a posteriori identifiability of all model parameters was confirmed (data not shown). The uncertainty of the parameters as determined from the covariance matrix was so small as to be negligible (SDs on the order of 1% of fitted values)


Glucose sensing in the peritoneal space offers faster kinetics than sensing in the subcutaneous space.

Burnett DR, Huyett LM, Zisser HC, Doyle FJ, Mensh BD - Diabetes (2014)

Sample of compartmental modeling fit to data. This plot shows an example of the model-fitting process for a single challenge, using glucometer measurements as the input. Shown on the plot are the experimental measurements made by the intraperitoneal (IP) and subcutaneous (SQ) sensors, as well as the model predicted output for each sensor model. The goodness-of-fit values for the intraperitoneal and subcutaneous models shown were 89% and 90%, with time constants of 1.7 and 13.1 min, respectively.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4066336&req=5

Figure 3: Sample of compartmental modeling fit to data. This plot shows an example of the model-fitting process for a single challenge, using glucometer measurements as the input. Shown on the plot are the experimental measurements made by the intraperitoneal (IP) and subcutaneous (SQ) sensors, as well as the model predicted output for each sensor model. The goodness-of-fit values for the intraperitoneal and subcutaneous models shown were 89% and 90%, with time constants of 1.7 and 13.1 min, respectively.
Mentions: Figure 2B compares the postglucose-bolus recovery between the two sensor spaces in a plot similar to Fig. 2A. The average recovery for the subcutaneous space was 33%, compared with 59% for the intraperitoneal space. For all challenges, the intraperitoneal space showed a more complete return to prechallenge baseline glucose levels than the subcutaneous space (all points above diagonal identity line, P < 0.001 for challenges, P < 0.01 for animals). Finally, we quantified the glucose kinetics of the subcutaneous and intraperitoneal spaces using compartmental modeling in which the glucometer measurements served as an input function and the transport of glucose into the body spaces was modeled with a first-order transfer function. The glucometer measurements were used in place of the YSI measurements because the YSI data were too sparse to use as a model input. This approach yielded excellent fits to the data, as illustrated in Fig. 3; the mean goodness of fit across all challenges was 75.6% (SD 8.5%) for the intraperitoneal sensor data and 83.2% (SD 8.9%) for the subcutaneous sensor data. The a posteriori identifiability of all model parameters was confirmed (data not shown). The uncertainty of the parameters as determined from the covariance matrix was so small as to be negligible (SDs on the order of 1% of fitted values)

Bottom Line: We compared the temporal response characteristics of simultaneously placed subcutaneous and intraperitoneal sensors during intravenous glucose tolerance tests in eight swine.Using compartmental modeling based on simultaneous intravenous sensing, blood draws, and intraarterial sensing, we found that intraperitoneal kinetics were more than twice as fast as subcutaneous kinetics (mean time constant of 5.6 min for intraperitoneal vs. 12.4 min for subcutaneous).Combined with the known faster kinetics of intraperitoneal insulin delivery over subcutaneous delivery, our findings suggest that artificial pancreas technologies may be optimized by sensing glucose and delivering insulin in the intraperitoneal space.

View Article: PubMed Central - PubMed

Affiliation: Theranova, LLC, San Francisco, CA.

Show MeSH
Related in: MedlinePlus