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Zhang R, Wu Y, Xv R, Wang W, Zhang L, Wang A, Li M, Jiang W, Jin G, Hu X. Clinical application of real-time continuous glucose monitoring system during postoperative enteral nutrition therapy in esophageal cancer patients. Nutr Clin Pract 2024; 39:837-849. [PMID: 38522023 DOI: 10.1002/ncp.11143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 02/11/2024] [Accepted: 02/16/2024] [Indexed: 03/25/2024] Open
Abstract
BACKGROUND Enteral nutrition (EN) support therapy increases the risk of abnormal blood glucose (BG). The aim of this study is to evaluate the clinical value of a real-time continuous glucose monitoring (rt-CGM) system in BG monitoring during postoperative EN support therapy in patients with esophageal cancer. METHODS Patients without diabetes mellitus (DM) with esophageal cancer who planned to receive postoperative EN were enrolled. With the self-monitoring of BG value as the reference BG, the accuracy of rt-CGM was evaluated by the mean absolute relative difference (MARD) value, correlation efficient, agreement analysis, and Parkes and Clarke error grid plot. Finally, paired t tests were used to compare the differences in glucose fluctuations between EN and non-EN days and slow and fast days. RESULTS The total MARD value of the rt-CGM system was 13.53%. There was a high correlation between interstitial glucose and fingertip capillary BG (consistency correlation efficient = 0.884 [95% confidence interval, 0.874-0.894]). Results of 15/15%, 20/20%, 30/30% agreement analysis were 58.51%, 84.71%, and 99.65%, respectively. The Parkes and Clarke error grid showed that the proportion of the A and B regions were 100% and 99.94%, respectively. The glucose fluctuations on EN days vs non-EN days and on fast days vs slow days were large, and the difference was statistically significant (P < 0.001). CONCLUSION The rt-CGM system achieved clinical accuracy and can be used as a new option for glucose monitoring during postoperative EN therapy. The magnitude of glucose fluctuation during EN therapy remains large, even in the postoperative population without DM.
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Affiliation(s)
- Ranran Zhang
- Department of Endocrinology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
| | - Ying Wu
- Department of Endocrinology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
| | - Rui Xv
- Department of Endocrinology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
| | - Wei Wang
- Department of Thoracic Surgery, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
| | - Lei Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
| | - Ansheng Wang
- Department of Thoracic Surgery, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
| | - Min Li
- Department of Endocrinology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
| | - Wei Jiang
- Department of Endocrinology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
- National Standardized Metabolic Disease Management Center, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
| | - Guoxi Jin
- Department of Endocrinology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
- National Standardized Metabolic Disease Management Center, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
| | - Xiaolei Hu
- Department of Endocrinology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
- National Standardized Metabolic Disease Management Center, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
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Zhang T, Dong X, Wang D, Huang C, Zhang XD. RespirAnalyzer: an R package for analyzing data from continuous monitoring of respiratory signals. BIOINFORMATICS ADVANCES 2024; 4:vbae003. [PMID: 38269257 PMCID: PMC10807906 DOI: 10.1093/bioadv/vbae003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 11/30/2023] [Accepted: 01/11/2024] [Indexed: 01/26/2024]
Abstract
Motivation The analysis of data obtained from continuous monitoring of respiratory signals (CMRS) holds significant importance in improving patient care, optimizing sports performance, and advancing scientific understanding in the field of respiratory health. Results The R package RespirAnalyzer provides an analytic tool specifically for feature extraction, fractal and complexity analysis for CMRS data. The package covers a wide and comprehensive range of data analysis methods including obtaining inter-breath intervals (IBI) series, plotting time series, obtaining summary statistics of IBI series, conducting power spectral density, multifractal detrended fluctuation analysis (MFDFA) and multiscale sample entropy analysis, fitting the MFDFA results with the extended binomial multifractal model, displaying results using various plots, etc. This package has been developed from our work in directly analyzing CMRS data and is anticipated to assist fellow researchers in computing the related features of their CMRS data, enabling them to delve into the clinical significance inherent in these features. Availability and implementation The package for Windows is available from both Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/RespirAnalyzer/index.html and GitHub: https://github.com/dongxinzheng/RespirAnalyzer.
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Affiliation(s)
- Teng Zhang
- Department of Public Health and Medicinal Administration, Faculty of Health Sciences, University of Macau, Taipa, Macau 999078, China
| | - Xinzheng Dong
- Zhuhai Laboratory of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Zhuhai College of Science and Technology, Zhuhai 519041, China
| | - Dandan Wang
- Department of Public Health and Medicinal Administration, Faculty of Health Sciences, University of Macau, Taipa, Macau 999078, China
| | - Chen Huang
- Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, Macau University of Science and Technology, Taipa, Macau 999078, China
| | - Xiaohua Douglas Zhang
- Department of Biostatistics, University of Kentucky, Lexington, KY 40536, United States
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Kubota T, Shoda K, Ushigome E, Kosuga T, Konishi H, Shiozaki A, Kudo M, Arita T, Murayama Y, Morimura R, Ikoma H, Kuriu Y, Nakanishi M, Fujiwara H, Okamoto K, Fukui M, Otsuji E. Utility of continuous glucose monitoring following gastrectomy. Gastric Cancer 2020; 23:699-706. [PMID: 31916026 DOI: 10.1007/s10120-019-01036-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Accepted: 12/27/2019] [Indexed: 02/07/2023]
Abstract
BACKGROUND Glucose fluctuation after gastrectomy represented by dumping syndrome is a well-known post-gastrectomy syndrome that negatively impacts patient quality of life. However, the current methods of post-gastrectomy glucose monitoring do not comprehensively capture the postoperative blood glucose fluctuations that characterize this. METHODS We used a continuous glucose monitoring (CGM) system to document the glycemic profiles of patients undergoing gastrectomy and compared these between patients undergoing distal gastrectomy (DG) and total gastrectomy (TG). To evaluate post-gastrectomy syndromes, including dumping syndrome, we used the Post-gastrectomy Syndrome Assessment Scale 37-item questionnaire. The glycemic profiles were also compared using this tool. RESULTS We studied 57 patients who had undergone DG and 13 who had undergone TG between September 2017 and September 2019. Our results revealed larger diurnal glycemic variability and longer periods of nocturnal hypoglycemia after gastrectomy. The dumping score was worse in the TG than in the DG group (TG 2.4 ± 1.4 vs. DG 1.3 ± 1.2, P = 0.0061). Importantly, 30 of 57 DG patients (52.6%) and 5 of 13 TG patients (38.5%) experienced postprandial hypoglycemia following hyperglycemia without hypoglycemic symptoms. There was no correlation between the dumping symptom score and glycemic variability (ρ = 0.0545, P = 0.6662). CONCLUSIONS CGM demonstrated diurnal glycemic variability and nocturnal hypoglycemia in patients undergoing gastrectomy. Because some hypoglycemic patients did not develop symptoms and glycemic variability was not necessarily associated with dumping symptom, dumping syndrome must only partially explain the postoperative glucose fluctuations.
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Affiliation(s)
- Takeshi Kubota
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan.
| | - Katsutoshi Shoda
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Emi Ushigome
- Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Toshiyuki Kosuga
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Hirotaka Konishi
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Atsushi Shiozaki
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Michihiro Kudo
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Tomohiro Arita
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Yasutoshi Murayama
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Ryo Morimura
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Hisashi Ikoma
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Yoshiaki Kuriu
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Masayoshi Nakanishi
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Hitoshi Fujiwara
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Kazuma Okamoto
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Michiaki Fukui
- Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
| | - Eigo Otsuji
- Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 602-8566, Japan
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Design of a Sandwich Hierarchically Porous Membrane with Oxygen Supplement Function for Implantable Glucose Sensor. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10082848] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
This study aims to develop an oxygen regeneration layer sandwiched between multiple porous polyurethanes (PU) to improve the performance of implantable glucose sensors. Sensors were prepared by coating electrodes with platinum nanoparticles, Nafion, glucose oxidase and sandwich hierarchically porous membrane with an oxygen supplement function (SHPM-OS). The SHPM-OS consisted of a hierarchically porous structure synthesized by polyethylene glycol and PU and a catalase (Cat) layer that was coated between hierarchical membranes and used to balance the sensitivity and linearity of glucose sensors, as well as reduce the influence of oxygen deficiency during monitoring. Compared with the sensitivity and linearity of traditional non-porous (NO-P) sensors (35.95 nA/mM, 0.9987, respectively) and single porous (SGL-P) sensors (45.3 nA /mM, 0.9610, respectively), the sensitivity and linearity of the SHPM-OS sensor was 98.45 nA/mM and 0.9989, respectively, which was more sensitive with higher linearity. The sensor showed a response speed of five seconds and a relative sensitivity of 90% in the first 10 days and remained 78% on day 20. This sensor coated with SHPM-OS achieved rapid responses to changes of glucose concentration while maintaining high linearity for long monitoring times. Thus, it may reduce the difficulty of back-end hardware module development and assist with effective glucose self-management for people with diabetes.
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Design of a Real-time Self-adjusting Calibration Algorithm to Improve the Accuracy of Continuous Blood Glucose Monitoring. Appl Biochem Biotechnol 2019; 190:1163-1176. [PMID: 31713834 DOI: 10.1007/s12010-019-03142-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Accepted: 09/12/2019] [Indexed: 10/25/2022]
Abstract
The aim of this study is to establish a real-time self-adjusting calibration algorithm to compensate for signal drift and sensitivity attenuation of subcutaneous implantable glucose sensors. A real-time self-adjusting in vivo calibration method was designed based on the one-point calibration model. The current signal was compensated in real-time and the sensitivity was calibrated regularly. The least squares method was used to fit the initial parameters of the model, and then, the in vivo monitored current data was calibrated. Comparing with the mean absolute relative difference (MARD) of the blood glucose concentration by the traditional one-point calibration model (22.85 ± 5.76%), the MARD of the blood glucose concentration calibrated by the real-time self-adjusting in vivo calibration method was 6.28 ± 2.31%. The accuracy of the dynamic blood glucose monitoring was effectively improved. This calibration algorithm could compensate the signal drift in real time and correct sensitivity regularly to improve the accuracy of dynamic glucose monitoring, thus significantly enhancing diabetic self-management.
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Chen X, Wang D, Lin J, Zhang T, Deng S, Huang L, Jin Y, Chen C, Zhang Z, Zheng J, Sun B, Bogdan P, Zhang XD. Analyzing Complexity and Fractality of Glucose Dynamics in a Pregnant Woman with Type 2 Diabetes under Treatment. Int J Biol Sci 2019; 15:2373-2380. [PMID: 31595155 PMCID: PMC6775315 DOI: 10.7150/ijbs.33825] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2019] [Accepted: 05/27/2019] [Indexed: 11/05/2022] Open
Abstract
Currently, the rapid development of continuous glucose monitoring (CGM) device brings new insights into the treatment of diabetic patients including those during pregnancy. Complexity and fractality have recently under fast development for extracting information embodied in glucose dynamics measured using CGM. Although scientists have investigated the difference of complexity in glucose dynamics between diabetes and non-diabetes in order to discover better approaches for diabetes care, no one has analyzed the complexity and fractality of glucose dynamics during the process of adopting CGM to successfully treat pregnant women with type 2 diabetes. Thus, we analyzed the complexity and fractality using power spectral density (PSD), multi-scale sample entropy (MSE) and multifractal detrended fluctuation analysis (MF-DFA) in a clinical case. Our results show that (i) there exists multifractal behavior in blood glucose dynamics; (ii) the alpha stable distribution fits to the glucose increment data better than the Gaussian distribution; and (iii) the "global" complexity indicated by multiscale entropy, spectrum exponent and Hurst exponent increase and the "local" complexity indicated by multifractal spectrum decrease after the successful therapy. Our results offer findings that may bring value to health care providers for managing glucose levels of pregnant women with type 2 diabetes as well as provide scientists a reference on applying complexity and fractality in the clinical practice of treating diabetes.
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Affiliation(s)
- Xiaoyan Chen
- Department of Endocrinology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China
| | - Dandan Wang
- Faculty of Health Sciences, University of Macau, Taipa 999078, Macau
| | - Jinxiang Lin
- Department of Endocrinology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China
| | - Teng Zhang
- Faculty of Health Sciences, University of Macau, Taipa 999078, Macau
| | - Shunyou Deng
- Department of Endocrinology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China
| | - Lianyi Huang
- Department of Endocrinology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China
| | - Yu Jin
- Faculty of Health Sciences, University of Macau, Taipa 999078, Macau
| | - Chang Chen
- Faculty of Health Sciences, University of Macau, Taipa 999078, Macau
| | - Zhaozhi Zhang
- Department of Statistical Science, Duke University, Durham, NC 27708, USA
| | - Jun Zheng
- Faculty of Health Sciences, University of Macau, Taipa 999078, Macau
| | - Baoqing Sun
- Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Diseases, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China
| | - Paul Bogdan
- Department of Electrical Engineering - Systems, University of Southern California, CA 90089, USA
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Kohnert KD, Heinke P, Vogt L, Augstein P, Salzsieder E. Applications of Variability Analysis Techniques for Continuous Glucose Monitoring Derived Time Series in Diabetic Patients. Front Physiol 2018; 9:1257. [PMID: 30237767 PMCID: PMC6136234 DOI: 10.3389/fphys.2018.01257] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Accepted: 08/20/2018] [Indexed: 02/05/2023] Open
Abstract
Methods from non-linear dynamics have enhanced understanding of functional dysregulation in various diseases but received less attention in diabetes. This retrospective cross-sectional study evaluates and compares relationships between indices of non-linear dynamics and traditional glycemic variability, and their potential application in diabetes control. Continuous glucose monitoring provided data for 177 subjects with type 1 (n = 22), type 2 diabetes (n = 143), and 12 non-diabetic subjects. Each time series comprised 576 glucose values. We calculated Poincaré plot measures (SD1, SD2), shape (SFE) and area of the fitting ellipse (AFE), multiscale entropy (MSE) index, and detrended fluctuation exponents (α1, α2). The glycemic variability metrics were the coefficient of variation (%CV) and standard deviation. Time of glucose readings in the target range (TIR) defined the quality of glycemic control. The Poincaré plot indices and α exponents were higher (p < 0.05) in type 1 than in the type 2 diabetes; SD1 (mmol/l): 1.64 ± 0.39 vs. 0.94 ± 0.35, SD2 (mmol/l): 4.06 ± 0.99 vs. 2.12 ± 1.04, AFE (mmol2/l2): 21.71 ± 9.82 vs. 7.25 ± 5.92, and α1: 1.94 ± 0.12 vs. 1.75 ± 0.12, α2: 1.38 ± 0.11 vs. 1.30 ± 0.15. The MSE index decreased consistently from the non-diabetic to the type 1 diabetic group (5.31 ± 1.10 vs. 3.29 ± 0.83, p < 0.001); higher indices correlated with lower %CV values (r = -0.313, p < 0.001). In a subgroup of type 1 diabetes patients, insulin pump therapy significantly decreased SD1 (-0.85 mmol/l), SD2 (-1.90 mmol/l), and AFE (-16.59 mmol2/l2), concomitantly with %CV (-15.60). The MSE index declined from 3.09 ± 0.94 to 1.93 ± 0.40 (p = 0.001), whereas the exponents α1 and α2 did not. On multivariate regression analyses, SD1, SD2, SFE, and AFE emerged as dominant predictors of TIR (β = -0.78, -1.00, -0.29, and -0.58) but %CV as a minor one, though α1 and MSE failed. In the regression models, including SFE, AFE, and α2 (β = -0.32), %CV was not a significant predictor. Poincaré plot descriptors provide additional information to conventional variability metrics and may complement assessment of glycemia, but complexity measures produce mixed results.
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Affiliation(s)
| | - Peter Heinke
- Institute of Diabetes "Gerhardt Katsch", Karlsburg, Germany
| | - Lutz Vogt
- Diabetes Service Center, Karlsburg, Germany
| | - Petra Augstein
- Institute of Diabetes "Gerhardt Katsch", Karlsburg, Germany.,Heart and Diabetes Medical Center, Karlsburg, Germany
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Kohnert KD, Heinke P, Vogt L, Augstein P, Thomas A, Salzsieder E. Associations of blood glucose dynamics with antihyperglycemic treatment and glycemic variability in type 1 and type 2 diabetes. J Endocrinol Invest 2017; 40:1201-1207. [PMID: 28484994 DOI: 10.1007/s40618-017-0682-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Accepted: 04/26/2017] [Indexed: 12/20/2022]
Abstract
AIMS The dynamical structure of glucose fluctuation has largely been disregarded in the contemporary management of diabetes. METHODS In a retrospective study of patients with diabetes, we evaluated the relationship between glucose dynamics, antihyperglycemic therapy, glucose variability, and glucose exposure, while taking into account potential determinants of the complexity index. We used multiscale entropy (MSE) analysis of continuous glucose monitoring data from 131 subjects with type 1 (n = 18), type 2 diabetes (n = 102), and 11 nondiabetic control subjects. We compared the MSE complexity index derived from the glucose time series among the treatment groups, after adjusting for sex, age, diabetes duration, body mass index, and carbohydrate intake. RESULTS In type 2 diabetic patients who were on a diet or insulin regimen with/without oral agents, the MSE index was significantly lower than in nondiabetic subjects but was lowest in the type 1 diabetes group (p < 0.001). The decline in the MSE complexity across the treatment groups correlated with increasing glucose variability and glucose exposure. Statistically, significant correlations existed between higher MSE complexity indices and better glycemic control. In multivariate regression analysis, the antidiabetic therapy was the most powerful predictor of the MSE (β = -0.940 ± 0.242, R 2 = 0.306, p < 0.001), whereas the potential confounders failed to contribute. CONCLUSIONS The loss of dynamical complexity in glucose homeostasis correlates more closely with therapy modalities and glucose variability than with clinical measures of glycemia. Thus, targeting the glucoregulatory system by adequate therapeutic interventions may protect against progressive worsening of diabetes control.
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Affiliation(s)
- K-D Kohnert
- Institute of Diabetes "Gerhardt Katsch" Karlsburg, Karlsburg, Germany.
| | - P Heinke
- Institute of Diabetes "Gerhardt Katsch" Karlsburg, Karlsburg, Germany
| | - L Vogt
- Diabetes Service Center, Karlsburg, Germany
| | - P Augstein
- Institute of Diabetes "Gerhardt Katsch" Karlsburg, Karlsburg, Germany
- Department of Medicine A, University Medicine Greifswald, Greifswald, Germany
| | - A Thomas
- Medtronic GmbH, Meerbusch, Germany
| | - E Salzsieder
- Institute of Diabetes "Gerhardt Katsch" Karlsburg, Karlsburg, Germany
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McKinlay CJ, Chase JG, Dickson J, Harris DL, Alsweiler JM, Harding JE. Continuous glucose monitoring in neonates: a review. Matern Health Neonatol Perinatol 2017; 3:18. [PMID: 29051825 PMCID: PMC5644070 DOI: 10.1186/s40748-017-0055-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Accepted: 08/24/2017] [Indexed: 12/17/2022] Open
Abstract
Continuous glucose monitoring (CGM) is well established in the management of diabetes mellitus, but its role in neonatal glycaemic control is less clear. CGM has provided important insights about neonatal glucose metabolism, and there is increasing interest in its clinical use, particularly in preterm neonates and in those in whom glucose control is difficult. Neonatal glucose instability, including hypoglycaemia and hyperglycaemia, has been associated with poorer neurodevelopment, and CGM offers the possibility of adjusting treatment in real time to account for individual metabolic requirements while reducing the number of blood tests required, potentially improving long-term outcomes. However, current devices are optimised for use at relatively high glucose concentrations, and several technical issues need to be resolved before real-time CGM can be recommended for routine neonatal care. These include: 1) limited point accuracy, especially at low or rapidly changing glucose concentrations; 2) calibration methods that are designed for higher glucose concentrations of children and adults, and not for neonates; 3) sensor drift, which is under-recognised; and 4) the need for dynamic and integrated metrics that can be related to long-term neurodevelopmental outcomes. CGM remains an important tool for retrospective investigation of neonatal glycaemia and the effect of different treatments on glucose metabolism. However, at present CGM should be limited to research studies, and should only be introduced into routine clinical care once benefit is demonstrated in randomised trials.
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Affiliation(s)
- Christopher J.D. McKinlay
- Liggins Institute, University of Auckland, Private Bag 92019, Victoria St West, Auckland, 1142 New Zealand
- Department of Paediatrics: Child and Youth Health, University of Auckland, Auckland, New Zealand
| | - J. Geoffrey Chase
- Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
| | - Jennifer Dickson
- Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
| | - Deborah L. Harris
- Liggins Institute, University of Auckland, Private Bag 92019, Victoria St West, Auckland, 1142 New Zealand
- Neonatal Intensive Care Unit, Waikato District Health Board, Hamilton, New Zealand
| | - Jane M. Alsweiler
- Liggins Institute, University of Auckland, Private Bag 92019, Victoria St West, Auckland, 1142 New Zealand
- Department of Paediatrics: Child and Youth Health, University of Auckland, Auckland, New Zealand
| | - Jane E. Harding
- Liggins Institute, University of Auckland, Private Bag 92019, Victoria St West, Auckland, 1142 New Zealand
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Uyttendaele V, Dickson JL, Shaw GM, Desaive T, Chase JG. Untangling glycaemia and mortality in critical care. CRITICAL CARE : THE OFFICIAL JOURNAL OF THE CRITICAL CARE FORUM 2017. [PMID: 28645302 PMCID: PMC5482947 DOI: 10.1186/s13054-017-1725-y] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Background Hyperglycaemia is associated with adverse outcomes in the intensive care unit, and initial studies suggested outcome benefits of glycaemic control (GC). However, subsequent studies often failed to replicate these results, and they were often unable to achieve consistent, safe control, raising questions about the benefit or harm of GC as well as the nature of the association of glycaemia with mortality and clinical outcomes. In this study, we evaluated if non-survivors are harder to control than survivors and determined if glycaemic outcome is a function of patient condition and eventual outcome or of the glycaemic control provided. Methods Clinically validated, model-based, hour-to-hour insulin sensitivity (SI) and its hour-to-hour variability (%ΔSI) were identified over the first 72 h of therapy in 145 patients (119 survivors, 26 non-survivors). In hypothesis testing, we compared distributions of SI and %ΔSI in 6-hourly blocks for survivors and non-survivors. In equivalence testing, we assessed if differences in these distributions, based on blood glucose measurement error, were clinically significant. Results SI level was never equivalent between survivors and non-survivors (95% CI of percentage difference in medians outside ±12%). Non-survivors had higher SI, ranging from 9% to 47% higher overall in 6-h blocks, and this difference became statistically significant as glycaemic control progressed. %ΔSI was equivalent between survivors and non-survivors for all 6-hourly blocks (95% CI of difference in medians within ±12%) and decreased in general over time as glycaemic control progressed. Conclusions Whereas non-survivors had higher SI levels, variability was equivalent to that of survivors over the first 72 h. These results indicate survivors and non-survivors are equally controllable, given an effective glycaemic control protocol, suggesting that glycaemia level and variability, and thus the association between glycaemia and outcome, are essentially determined by the control provided rather than by underlying patient or metabolic condition. Electronic supplementary material The online version of this article (doi:10.1186/s13054-017-1725-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Vincent Uyttendaele
- Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand. .,GIGA - In Silico Medicine, University of Liège, Allée du 6 Août 19, bâtiment B5a, 4000, Liège, Belgium.
| | - Jennifer L Dickson
- Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand
| | - Geoffrey M Shaw
- Department of Intensive Care, Christchurch Hospital, Private Bag 4710, Christchurch, New Zealand
| | - Thomas Desaive
- GIGA - In Silico Medicine, University of Liège, Allée du 6 Août 19, bâtiment B5a, 4000, Liège, Belgium
| | - J Geoffrey Chase
- Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand
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