In-Silico Trials for Glucose Control in Hospitalized Patients with Type 2 Diabetes.

Although various basal-bolus insulin therapy (BBIT) protocols have been used in the clinical environment, safer and more effective BBIT protocols are required for glucose control in hospitalized patients with type 2 diabetes (T2D). Modeling approaches could provide an evaluation environment for developing the optimal BBIT protocol prior to clinical trials at low cost and without risk of danger. In this study, an in-silico model was proposed to evaluate subcutaneous BBIT protocols in hospitalized patients with T2D. The proposed model was validated by comparing the BBIT protocol and sliding-scale insulin therapy (SSIT) protocol. The model was utilized for in-silico trials to compare the protocols of adjusting basal-insulin dose (BBIT1) versus adjusting total-daily-insulin dose (BBIT2). The model was also used to evaluate two different initial total-daily-insulin doses for various levels of renal function. The BBIT outcomes were superior to those of SSIT, which is consistent with earlier studies. BBIT2 also outperformed BBIT1, producing a decreased daily mean glucose level and longer time-in-target-range. Moreover, with a standard dose, the overall daily mean glucose levels reached the target range faster than with a reduced-dose for all degrees of renal function. The in-silico studies demonstrated several significant findings, including that the adjustment of total-daily-insulin dose is more effective than changes to basal-insulin dose alone. This research represents a first step toward the eventual development of an advanced model for evaluating various BBIT protocols.

Smartphone-Based Urine Reagent Strip Test in the Emergency Department.

BACKGROUND: Although a smartphone could be used for a urine reagent strip test, few studies have reported on the reliability of the test in a clinical setting. The objective of our study was to access the smartphone-based urine reagent strip test in the clinical emergency department (ED). MATERIALS AND METHODS: We developed a smartphone-based urine reagent strip reader for a rapid and accurate screening of leukocyte esterase (LE) and nitrite (NIT) in urine. The developed reader was evaluated with the clinical urine samples (n = 81). The detection performance of the reader for LE and NIT was evaluated to assess reliability of the reader; turnaround times (TATs) for analysis and the time for the entire study procedure were also calculated to assess the efficiency of the reader. A photometric analyzer (model US-3100R Plus(®); Eiken Chemical, Ltd., Tokyo, Japan) was used as a reference. RESULTS: The proposed reader showed high accuracy (85.2% for LE and 97.5% for NIT), exhibiting close agreement with the true values (κ = 0.903 for LE; κ = 1.000 for NIT). The reader also exhibited a lower median TAT for analysis than the photometric analyzer (3.0 min versus 33.0 min; p < 0.001). This reduction of TAT in the reader was even more evident considering the required time for delivery of urine samples for the photometric analyzer (3.0 min versus 62.0 min; p < 0.001). CONCLUSIONS: Our results demonstrated the clinical capability of a smartphone-based urine reagent strip test, and this reader is expected to enable a more rapid and reliable colorimetric test for screening of LE and NIT at the clinical setting and the point of care.

Simulation of oral glucose tolerance tests and the corresponding isoglycemic intravenous glucose infusion studies for calculation of the incretin effect.

The incretin effect, which is a unique stimulus of insulin secretion in response to oral ingestion of nutrients, is calculated by the difference in insulin secretory responses from an oral glucose tolerance test (OGTT) and a corresponding isoglycemic intravenous glucose infusion (IIGI) study. The OGTT model of this study, which is individualized by fitting the glucose profiles during an OGTT, was developed to predict the glucose profile during an IIGI study in the same subject. Also, the model predicts the insulin and incretin profiles during both studies. The incretin effect, estimated by simulation, was compared with that measured by physiologic studies from eight human subjects with normal glucose tolerance, and the result exhibited a good correlation (r > 0.8); the incretin effect from the simulation was 56.5% ± 10.6% while the one from the measured data was 52.5% ± 19.6%. In conclusion, the parameters of the OGTT model have been successfully estimated to predict the profiles of both OGTTs and IIGI studies. Therefore, with glucose data from the OGTT alone, this model could control and predict the physiologic responses, including insulin secretion during OGTTs and IIGI studies, which could eventually eliminate the need for complex and cumbersome IIGI studies in incretin research.

In vivo photoacoustic monitoring of vasoconstriction induced by acute hyperglycemia.

Postprandial hyperglycemia, blood glucose spikes, induces endothelial dysfunction, increasing cardiovascular risks. Endothelial dysfunction leads to vasoconstriction, and observation of this phenomenon is important for understanding acute hyperglycemia. However, high-resolution imaging of microvessels during acute hyperglycemia has not been fully developed. Here, we demonstrate that photoacoustic microscopy can noninvasively monitor morphological changes in blood vessels of live animals' extremities when blood glucose rises rapidly. As blood glucose level rose from 100 to 400 mg/dL following intraperitoneal glucose injection, heart/breath rate, and body temperature remained constant, but arterioles constricted by approximately -5.7 ± 1.1% within 20 min, and gradually recovered for another 40 min. In contrast, venular diameters remained within about 0.6 ± 1.5% during arteriolar constriction. Our results experimentally and statistically demonstrate that acute hyperglycemia produces transitory vasoconstriction in arterioles, with an opposite trend of change in blood glucose. These findings could help understanding vascular glucose homeostasis and the relationship between diabetes and cardiovascular diseases.

Fully integrated photoacoustic microscopy and photoplethysmography of human in vivo.

Photoacoustic microscopy (PAM) is used to visualize blood vessels and to monitor their time-dependent changes. Photoplethysmography (PPG) measures hemodynamic time-series changes such as heart rate. However, PPG's limited visual access to the dynamic changes of blood vessels has prohibited further understanding of hemodynamics. Here, we propose a novel, fully integrated PAM and photoplethysmography (PAM-PPG) system to understand hemodynamic features in detail. Using the PAM-PPG system, we simultaneously acquire vascular images (by PAM) and changes in the blood volume (by PPG) from human fingers. Next, we determine the heart rate from changes in the PA signals, which match well with the PPG signals. These changes can be measured if the blood flow is not blocked. From the results, we believe that PAM-PPG could be a useful clinical tool in various clinical fields such as cardiology and endocrinology.

Motion Artifact Removal of Photoplethysmogram (PPG) Signal.

Photoplethysmogram (PPG) has been used with great effect for predicting human vitals such as heart rate variability or blood oxygen saturation (SpO2), etc. The quality of PPG signal is affected mainly by noise, drift and motion artifacts. Although noise and drift are relatively easy to remove, motion artifacts pose a challenge. Classical techniques for motion artifact removal are time-frequency based. However, this affects the signal as the PPG signal and motion artifacts distortion lie in the same frequency band, making it difficult to remove the motion artifacts without affecting the signal. In this work, we propose a motion artifact removal technique in time domain, which is based on correcting individual pulses in the PPG signal, considering a global pulse average and a windowed local pulse average. We show the effectiveness of our approach both qualitatively as well as quantitatively.

Application of the Oral Minimal Model to Korean Subjects with Normal Glucose Tolerance and Type 2 Diabetes Mellitus.

BACKGROUND: The oral minimal model is a simple, useful tool for the assessment of ß-cell function and insulin sensitivity across the spectrum of glucose tolerance, including normal glucose tolerance (NGT), prediabetes, and type 2 diabetes mellitus (T2DM) in humans. METHODS: Plasma glucose, insulin, and C-peptide levels were measured during a 180-minute, 75-g oral glucose tolerance test in 24 Korean subjects with NGT (n=10) and T2DM (n=14). The parameters in the computational model were estimated, and the indexes for insulin sensitivity and ß-cell function were compared between the NGT and T2DM groups. RESULTS: The insulin sensitivity index was lower in the T2DM group than the NGT group. The basal index of ß-cell responsivity, basal hepatic insulin extraction ratio, and post-glucose challenge hepatic insulin extraction ratio were not different between the NGT and T2DM groups. The dynamic, static, and total ß-cell responsivity indexes were significantly lower in the T2DM group than the NGT group. The dynamic, static, and total disposition indexes were also significantly lower in the T2DM group than the NGT group. CONCLUSION: The oral minimal model can be reproducibly applied to evaluate ß-cell function and insulin sensitivity in Koreans.

A Computational Method to Determine Glucose Infusion Rates for Isoglycemic Intravenous Glucose Infusion Study.

The results of the isoglycemic intravenous glucose infusion (IIGI) study need to mimic the dynamic glucose profiles during the oral glucose tolerance test (OGTT) to accurately calculate the incretin effect. The glucose infusion rates during IIGI studies have historically been determined by experienced research personnel using the manual ad-hoc method. In this study, a computational method was developed to automatically determine the infusion rates for IIGI study based on a glucose-dynamics model. To evaluate the computational method, 18 subjects with normal glucose tolerance underwent a 75 g OGTT. One-week later, Group 1 (n = 9) and Group 2 (n = 9) underwent IIGI studies using the ad-hoc method and the computational method, respectively. Both methods were evaluated using correlation coefficient, mean absolute relative difference (MARD), and root mean square error (RMSE) between the glucose profiles from the OGTT and the IIGI study. The computational method exhibited significantly higher correlation (0.95 ± 0.03 versus 0.86 ± 0.10, P = 0.019), lower MARD (8.72 ± 1.83% versus 13.11 ± 3.66%, P = 0.002), and lower RMSE (10.33 ± 1.99 mg/dL versus 16.84 ± 4.43 mg/dL, P = 0.002) than the ad-hoc method. The computational method can facilitate IIGI study, and enhance its accuracy and stability. Using this computational method, a high-quality IIGI study can be accomplished without the need for experienced personnel.