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Almagthali A, Alsohimi S, Alkhalaf A, Al Sulaiman K, Aljuhani O. Assessing glycemic variability in critically ill patients: A prospective cohort study comparing insulin infusion therapy with insulin sliding scale. Sci Rep 2024; 14:10128. [PMID: 38698018 PMCID: PMC11066101 DOI: 10.1038/s41598-024-57403-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 03/18/2024] [Indexed: 05/05/2024] Open
Abstract
Glycemic variability (GV) has been associated with an increased mortality rate among critically ill patients. The clinical outcomes of having less GV even with slight hyperglycemia are better than those having tight glycemic control but higher GV. Insulin infusion remains the preferred method to control stress hyperglycemia in critically ill patients. However, its impacts on GV and clinical outcomes in critically ill patients still need further investigation. This study intended to evaluate the impact of insulin infusion therapy (IIT) compared to the insulin sliding scale (ISS) on the extent of GV and explore its impact on the clinical outcomes for critically ill patients. A prospective, single-center observational cohort study was conducted at a tertiary academic hospital in Saudi Arabia between March 2021 and November 2021. The study included adult patients admitted to ICUs who received insulin for stress hyperglycemia management. Patients were categorized into two groups based on the regimen of insulin therapy during ICU stay (IIT versus ISS). The primary outcome was the GV between the two groups. Secondary outcomes were ICU mortality, the incidence of hypoglycemia, and ICU length of stay (LOS). A total of 381 patients were screened; out of them, eighty patients met the eligibility criteria. The distribution of patients having diabetes and a history of insulin use was similar between the two groups. The GV was lower in the IIT group compared to the ISS group using CONGA (- 0.65, 95% CI [- 1.16, - 0.14], p-value = 0.01). Compared with ISS, patients who received IIT had a lower incidence of hypoglycemia that required correction (6.8% vs 2.77%; p-value = 0.38). In contrast, there were no significant differences in ICU LOS and ICU mortality between the two groups. Our study demonstrated that the IIT is associated with decreased GV significantly in critically ill patients without increasing the incidence of severe hypoglycemia. There is no survival benefit with the use of the IIT. Further studies with larger sample size are required to confirm our findings and elaborate on IIT's potential effect in reducing ICU complications in critically ill patients.
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Affiliation(s)
- Alaa Almagthali
- Pharmaceutical Care Department, King Abdulaziz University Hospital, Jeddah, Saudi Arabia.
| | - Samiah Alsohimi
- Pharmaceutical Care Department, King Abdulaziz University Hospital, Jeddah, Saudi Arabia
- Pharmaceutical Care Department, King Fahad Armed Forces hospital, Jeddah, Saudi Arabia
| | - Arwa Alkhalaf
- Measurement and Psychometrics, Psychology Department, Faculty of Graduate Educational Studies, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Khalid Al Sulaiman
- Pharmaceutical Care Department, King Abdulaziz Medical City, Riyadh, Saudi Arabia
- College of Pharmacy, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
- King Abdullah International Medical Research Center-King Saud Bin Abdulaziz University for Health Sciences, Ministry of National Guard-Health Affairs, Riyadh, Saudi Arabia
- Saudi Critical Care Pharmacy Research (SCAPE) Platform, Riyadh, Saudi Arabia
- Saudi Society for Multidisciplinary Research Development and Education (SCAPE Society), Riyadh, Saudi Arabia
| | - Ohoud Aljuhani
- Department of Pharmacy Practice, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia
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Flexible battery-less wireless glucose monitoring system. Sci Rep 2022; 12:12356. [PMID: 35854130 PMCID: PMC9296503 DOI: 10.1038/s41598-022-16714-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 07/14/2022] [Indexed: 11/18/2022] Open
Abstract
In this work, a low power microcontroller-based near field communication (NFC) interfaced with a flexible abiotic glucose hybrid fuel cell is designed to function as a battery-less glucose sensor. The abiotic glucose fuel cell is fabricated by depositing colloidal platinum (co–Pt) on the anodic region and silver oxide nanoparticles-multiwalled carbon nanotubes (Ag2O-MWCNTs) composite on the cathodic region. The electrochemical behavior is characterized using cyclic voltammetry and chronoamperometry. This glucose hybrid fuel cell generated an open circuit voltage of 0.46 V, short circuit current density of 0.444 mA/cm2, and maximum power density of 0.062 mW/cm2 at 0.26 V in the presence of 7 mM physiologic glucose. Upon device integration of the abiotic glucose hybrid fuel cell with the NFC module, the data from the glucose monitoring system is successfully transmitted to an android application for visualization at the user interface. The cell voltage correlated (r2 = 0.989) with glucose concentration (up to 19 mM) with a sensitivity of 13.9 mV/mM•cm2.
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Mavragani A, Ling G, Wray D, DeJonckheere M, Mizokami Stout K, Saslow LR, Fenske J, Serlin D, Stonebraker S, Nisha T, Barry C, Pop-Busui R, Sen A, Richardson CR. Continuous Glucose Monitoring With Low-Carbohydrate Nutritional Coaching to Improve Type 2 Diabetes Control: Randomized Quality Improvement Program. J Med Internet Res 2022; 24:e31184. [PMID: 35107429 PMCID: PMC8851329 DOI: 10.2196/31184] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 09/16/2021] [Accepted: 11/30/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Type 2 diabetes mellitus (T2DM) is a leading cause of morbidity and mortality globally, with adverse health consequences largely related to hyperglycemia. Despite clinical practice guideline recommendations, effective pharmacotherapy, and interventions to support patients and providers, up to 60% of patients diagnosed with T2DM are estimated to have hemoglobin A1c (HbA1c) levels above the recommended targets owing to multilevel barriers hindering optimal glycemic control. OBJECTIVE The aim of this study is to compare changes in HbA1c levels among patients with suboptimally controlled T2DM who were offered the opportunity to use an intermittently viewed continuous glucose monitor and receive personalized low-carbohydrate nutrition counseling (<100 g/day) versus those who received usual care (UC). METHODS This was a 12-month, pragmatic, randomized quality improvement program. All adult patients with T2DM who received primary care at a university-affiliated primary care clinic (N=1584) were randomized to either the UC or the enhanced care (EC) group. Within each program arm, we identified individuals with HbA1c >7.5% (58 mmol/mol) who were medically eligible for tighter glycemic control, and we defined these subgroups as UC-high risk (UC-HR) or EC-HR. UC-HR participants (n=197) received routine primary care. EC-HR participants (n=185) were invited to use an intermittently viewed continuous glucose monitor and receive low-carbohydrate nutrition counseling. The primary outcome was mean change in HbA1c levels from baseline to 12 months using an intention-to-treat difference-in-differences analysis comparing EC-HR with UC-HR groups. We conducted follow-up semistructured interviews to understand EC-HR participant experiences with the intervention. RESULTS HbA1c decreased by 0.41% (4.5 mmol/mol; P=.04) more from baseline to 12 months among participants in the EC-HR group than among those in UC-HR; however, only 61 (32.9%) of 185 EC-HR participants engaged in the program. Among the EC-HR participants who wore continuous glucose monitors (61/185, 32.9%), HbA1c was 1.1% lower at 12 months compared with baseline (P<.001). Interviews revealed themes related to EC-HR participants' program engagement and continuous glucose monitor use. CONCLUSIONS Among patients with suboptimally controlled T2DM, a combined approach that includes continuous glucose monitoring and low-carbohydrate nutrition counseling can improve glycemic control compared with the standard of care.
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Affiliation(s)
| | - Grace Ling
- Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Daniel Wray
- Twine Clinical Consulting LLC, Park City, UT, United States
| | - Melissa DeJonckheere
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, United States.,Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Kara Mizokami Stout
- VA Ann Arbor Healthcare System, Ann Arbor, MI, United States.,Department of Internal Medicine Division of General Medicine, University of Michigan, Ann Arbor, MI, United States.,Department of Internal Medicine Division of Metabolism, Endocrinology and Diabetes, University of Michigan, Ann Arbor, MI, United States
| | - Laura R Saslow
- Department of Health Behavior and Biological Sciences, School of Nursing, University of Michigan, Ann Arbor, MI, United States
| | - Jill Fenske
- Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States
| | - David Serlin
- Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Spring Stonebraker
- Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Tabassum Nisha
- Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Colton Barry
- Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Rodica Pop-Busui
- Department of Internal Medicine Division of General Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Ananda Sen
- Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States.,Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Caroline R Richardson
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, United States.,Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States
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Perspectives of glycemic variability in diabetic neuropathy: a comprehensive review. Commun Biol 2021; 4:1366. [PMID: 34876671 PMCID: PMC8651799 DOI: 10.1038/s42003-021-02896-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 11/16/2021] [Indexed: 12/14/2022] Open
Abstract
Diabetic neuropathy is one of the most prevalent chronic complications of diabetes, and up to half of diabetic patients will develop diabetic neuropathy during their disease course. Notably, emerging evidence suggests that glycemic variability is associated with the pathogenesis of diabetic complications and has emerged as a possible independent risk factor for diabetic neuropathy. In this review, we describe the commonly used metrics for evaluating glycemic variability in clinical practice and summarize the role and related mechanisms of glycemic variability in diabetic neuropathy, including cardiovascular autonomic neuropathy, diabetic peripheral neuropathy and cognitive impairment. In addition, we also address the potential pharmacological and non-pharmacological treatment methods for diabetic neuropathy, aiming to provide ideas for the treatment of diabetic neuropathy. Zhang et al. describe metrics for evaluating glycaemic variability (GV) in clinical practice and summarize the role and related mechanisms of GV in diabetic neuropathy, including cardiovascular autonomic neuropathy, diabetic peripheral neuropathy and cognitive impairment. They aim to stimulate ideas for the treatment of diabetic neuropathy.
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Bent B, Cho PJ, Henriquez M, Wittmann A, Thacker C, Feinglos M, Crowley MJ, Dunn JP. Engineering digital biomarkers of interstitial glucose from noninvasive smartwatches. NPJ Digit Med 2021; 4:89. [PMID: 34079049 PMCID: PMC8172541 DOI: 10.1038/s41746-021-00465-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 05/11/2021] [Indexed: 12/14/2022] Open
Abstract
Prediabetes affects one in three people and has a 10% annual conversion rate to type 2 diabetes without lifestyle or medical interventions. Management of glycemic health is essential to prevent progression to type 2 diabetes. However, there is currently no commercially-available and noninvasive method for monitoring glycemic health to aid in self-management of prediabetes. There is a critical need for innovative, practical strategies to improve monitoring and management of glycemic health. In this study, using a dataset of 25,000 simultaneous interstitial glucose and noninvasive wearable smartwatch measurements, we demonstrated the feasibility of using noninvasive and widely accessible methods, including smartwatches and food logs recorded over 10 days, to continuously detect personalized glucose deviations and to predict the exact interstitial glucose value in real time with up to 84% and 87% accuracy, respectively. We also establish methods for designing variables using data-driven and domain-driven methods from noninvasive wearables toward interstitial glucose prediction.
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Affiliation(s)
- Brinnae Bent
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Peter J Cho
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Maria Henriquez
- Department of Statistical Science, Duke University, Durham, NC, USA
| | - April Wittmann
- Division of Endocrinology, Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | - Connie Thacker
- Division of Endocrinology, Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | - Mark Feinglos
- Division of Endocrinology, Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | - Matthew J Crowley
- Division of Endocrinology, Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | - Jessilyn P Dunn
- Department of Biomedical Engineering, Duke University, Durham, NC, USA. .,Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA.
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Zhang ZY, Miao LF, Qian LL, Wang N, Qi MM, Zhang YM, Dang SP, Wu Y, Wang RX. Molecular Mechanisms of Glucose Fluctuations on Diabetic Complications. Front Endocrinol (Lausanne) 2019; 10:640. [PMID: 31620092 PMCID: PMC6759481 DOI: 10.3389/fendo.2019.00640] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2018] [Accepted: 09/03/2019] [Indexed: 12/11/2022] Open
Abstract
Accumulating evidence indicates the occurrence and development of diabetic complications relates to not only constant high plasma glucose, but also glucose fluctuations which affect various kinds of molecular mechanisms in various target cells and tissues. In this review, we detail reactive oxygen species and their potentially damaging effects upon glucose fluctuations and resultant downstream regulation of protein signaling pathways, including protein kinase C, protein kinase B, nuclear factor-κB, and the mitogen-activated protein kinase signaling pathway. A deeper understanding of glucose-fluctuation-related molecular mechanisms in the development of diabetic complications may enable more potential target therapies in future.
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