1
|
Voglová Hagerf B, Protus M, Nemetova L, Mraz M, Kieslichova E, Uchytilova E, Indrova V, Lelito J, Girman P, Haluzík M, Franekova J, Svirlochova V, Klonoff DC, Kohn MA, Jabor A. Accuracy and Feasibility of Real-time Continuous Glucose Monitoring in Critically Ill Patients After Abdominal Surgery and Solid Organ Transplantation. Diabetes Care 2024; 47:956-963. [PMID: 38412005 PMCID: PMC11116916 DOI: 10.2337/dc23-1663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 01/25/2024] [Indexed: 02/28/2024]
Abstract
OBJECTIVE Glycemia management in critical care is posing a challenge in frequent measuring and adequate insulin dose adjustment. In recent years, continuous glucose measurement has gained accuracy and reliability in outpatient and inpatient settings. The aim of this study was to assess the feasibility and accuracy of real-time continuous glucose monitoring (CGM) in ICU patients after major abdominal surgery. RESEARCH DESIGN AND METHODS We included patients undergoing pancreatic surgery and solid organ transplantation (liver, pancreas, islets of Langerhans, kidney) requiring an ICU stay after surgery. We used a Dexcom G6 sensor, placed in the infraclavicular region, for real-time CGM. Arterial blood glucose measured by the amperometric principle (ABL 800; Radiometer, Copenhagen, Denmark) served as a reference value and for calibration. Blood glucose was also routinely monitored by a StatStrip bedside glucose meter. Sensor accuracy was assessed by mean absolute relative difference (MARD), bias, modified Bland-Altman plot, and surveillance error grid for paired samples of glucose values from CGM and acid-base analyzer (ABL). RESULTS We analyzed data from 61 patients and obtained 1,546 paired glucose values from CGM and ABL. Active sensor use was 95.1%. MARD was 9.4%, relative bias was 1.4%, and 92.8% of values fell in zone A, 6.1% fell in zone B, and 1.2% fell in zone C of the surveillance error grid. Median time in range was 78%, with minimum (<1%) time spent in hypoglycemia. StatStrip glucose meter MARD compared with ABL was 5.8%. CONCLUSIONS Our study shows clinically applicable accuracy and reliability of Dexcom G6 CGM in postoperative ICU patients and a feasible alternative sensor placement site.
Collapse
Affiliation(s)
- Barbora Voglová Hagerf
- Department of Diabetes, Diabetes Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
- First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Marek Protus
- First Faculty of Medicine, Charles University, Prague, Czech Republic
- Department of Anesthesiology, Resuscitation and Intensive Care, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Lenka Nemetova
- Department of Diabetes, Diabetes Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Milos Mraz
- Department of Diabetes, Diabetes Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
- First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Eva Kieslichova
- First Faculty of Medicine, Charles University, Prague, Czech Republic
- Department of Anesthesiology, Resuscitation and Intensive Care, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Eva Uchytilova
- First Faculty of Medicine, Charles University, Prague, Czech Republic
- Department of Anesthesiology, Resuscitation and Intensive Care, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Veronika Indrova
- Department of Anesthesiology, Resuscitation and Intensive Care, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Jan Lelito
- Department of Anesthesiology, Resuscitation and Intensive Care, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Peter Girman
- Department of Diabetes, Diabetes Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Martin Haluzík
- Department of Diabetes, Diabetes Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
- First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Janka Franekova
- Department of Laboratory Methods, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Veronika Svirlochova
- Department of Laboratory Methods, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - David C. Klonoff
- Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, CA
| | | | - Antonin Jabor
- Department of Laboratory Methods, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| |
Collapse
|
2
|
Ramos-Hernández WM, Soto LF, Del Rosario-Trinidad M, Farfan-Morales CN, De Jesús-González LA, Martínez-Mier G, Osuna-Ramos JF, Bastida-González F, Bernal-Dolores V, Del Ángel RM, Reyes-Ruiz JM. Leukocyte glucose index as a novel biomarker for COVID-19 severity. Sci Rep 2022; 12:14956. [PMID: 36056114 PMCID: PMC9438363 DOI: 10.1038/s41598-022-18786-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 08/19/2022] [Indexed: 12/03/2022] Open
Abstract
The severity of coronavirus disease 2019 (COVID-19) quickly progresses with unfavorable outcomes due to the host immune response and metabolism alteration. Hence, we hypothesized that leukocyte glucose index (LGI) is a biomarker for severe COVID-19. This study involved 109 patients and the usefulness of LGI was evaluated and compared with other risk factors to predict COVID 19 severity. LGI was identified as an independent risk factor (odds ratio [OR] = 1.727, 95% confidence interval [CI]: 1.026-3.048, P = 0.041), with an area under the curve (AUC) of 0.749 (95% CI: 0.642-0.857, P < 0.0001). Interestingly, LGI was a potential risk factor (OR = 2.694, 95% CI: 1.575-5.283, Pcorrected < 0.05) for severe COVID-19 in female but not in male patients. In addition, LGI proved to be a strong predictor of the severity in patients with diabetes (AUC = 0.915 (95% CI: 0.830-1), sensitivity = 0.833, and specificity = 0.931). The AUC of LGI, together with the respiratory rate (LGI + RR), showed a considerable improvement (AUC = 0.894, 95% CI: 0.835-0.954) compared to the other biochemical and respiratory parameters analyzed. Together, these findings indicate that LGI could potentially be used as a biomarker of severity in COVID-19 patients.
Collapse
Affiliation(s)
- Wendy Marilú Ramos-Hernández
- Unidad Médica de Alta Especialidad, Hospital de Especialidades No. 14, Centro Médico Nacional "Adolfo Ruiz Cortines", Instituto Mexicano del Seguro Social (IMSS), 91897, Veracruz, México
| | - Luis F Soto
- Escuela Profesional de Genética y Biotecnología, Facultad de Ciencias Biológicas, Universidad Nacional Mayor de San Marcos, Lima, 15081, Perú
| | - Marcos Del Rosario-Trinidad
- Unidad Médica de Alta Especialidad, Hospital de Especialidades No. 14, Centro Médico Nacional "Adolfo Ruiz Cortines", Instituto Mexicano del Seguro Social (IMSS), 91897, Veracruz, México
| | - Carlos Noe Farfan-Morales
- Department of Infectomics and Molecular Pathogenesis, Center for Research and Advanced Studies (CINVESTAV-IPN), 07360, Mexico City, Mexico
| | - Luis Adrián De Jesús-González
- Department of Infectomics and Molecular Pathogenesis, Center for Research and Advanced Studies (CINVESTAV-IPN), 07360, Mexico City, Mexico
| | - Gustavo Martínez-Mier
- Unidad Médica de Alta Especialidad, Hospital de Especialidades No. 14, Centro Médico Nacional "Adolfo Ruiz Cortines", Instituto Mexicano del Seguro Social (IMSS), 91897, Veracruz, México
| | - Juan Fidel Osuna-Ramos
- Escuela de Medicina, Universidad Autónoma de Durango Campus Culiacán, 80050, Culiacán Rosales, México
| | - Fernando Bastida-González
- Laboratorio de Biología Molecular, Laboratorio Estatal de Salud Pública del Estado de México, 50130, Mexico City, State of Mexico, Mexico
| | - Víctor Bernal-Dolores
- Unidad Médica de Alta Especialidad, Hospital de Especialidades No. 14, Centro Médico Nacional "Adolfo Ruiz Cortines", Instituto Mexicano del Seguro Social (IMSS), 91897, Veracruz, México
| | - Rosa María Del Ángel
- Department of Infectomics and Molecular Pathogenesis, Center for Research and Advanced Studies (CINVESTAV-IPN), 07360, Mexico City, Mexico.
| | - José Manuel Reyes-Ruiz
- Unidad Médica de Alta Especialidad, Hospital de Especialidades No. 14, Centro Médico Nacional "Adolfo Ruiz Cortines", Instituto Mexicano del Seguro Social (IMSS), 91897, Veracruz, México.
- Facultad de Medicina, Región Veracruz, Universidad Veracruzana, 91700, Veracruz, Mexico.
| |
Collapse
|
3
|
Abstract
BACKGROUND Conflicting information is available regarding the stability of glucose concentrations in frozen plasma samples. Clinical trials could benefit from such long-term storage because it would allow usage of a central laboratory with higher-quality laboratory analyzers in contrast to mobile analyzers in a decentralized setting. METHODS In this study, venous blood samples were collected in lithium-heparin gel tubes. Plasma was separated immediately after blood was drawn, and from each of the 21 plasma samples, 6 aliquots were prepared for measurement at 6 time points: immediately and after 2, 4, 6, 8, and 12 weeks. Between sampling and measurement, aliquots were stored at less than -20°C. Transport on dry ice was simulated by placing aliquots in a -80°C freezer for 5 days between weeks 8 and 12. Measurements were performed on a hexokinase-based laboratory analyzer.Average relative differences and corresponding 99% confidence intervals (CIs) were calculated between the stored aliquots' and the immediately measured aliquots' glucose concentrations. Glucose concentrations were deemed stable as long as average relative differences were ≤±2.5%. RESULTS Over the whole 12-weeks duration, the largest average relative difference was -1.82% (99% CI: -2.25% to -1.39%). Shorter storage durations tended to lead to less bias. CONCLUSION In this study, the stability of glucose concentrations in frozen plasma samples obtained with lithium-heparin gel tubes could be shown for up to 12 weeks. Future studies should be performed to assess whether this is independent of the glucose analyzer and the type of sampling tube used.
Collapse
Affiliation(s)
- Stefan Pleus
- Institut für Diabetes-Technologie, Forschungs-und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Guido Freckmann
- Institut für Diabetes-Technologie, Forschungs-und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Annette Baumstark
- Institut für Diabetes-Technologie, Forschungs-und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Cornelia Haug
- Institut für Diabetes-Technologie, Forschungs-und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| |
Collapse
|
4
|
Huang J, Yeung AM, Nguyen KT, Xu NY, Preiser JC, Rushakoff RJ, Seley JJ, Umpierrez GE, Wallia A, Drincic AT, Gianchandani R, Lansang MC, Masharani U, Mathioudakis N, Pasquel FJ, Schmidt S, Shah VN, Spanakis EK, Stuhr A, Treiber GM, Klonoff DC. Hospital Diabetes Meeting 2022. J Diabetes Sci Technol 2022; 16:1309-1337. [PMID: 35904143 PMCID: PMC9445340 DOI: 10.1177/19322968221110878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The annual Virtual Hospital Diabetes Meeting was hosted by Diabetes Technology Society on April 1 and April 2, 2022. This meeting brought together experts in diabetes technology to discuss various new developments in the field of managing diabetes in hospitalized patients. Meeting topics included (1) digital health and the hospital, (2) blood glucose targets, (3) software for inpatient diabetes, (4) surgery, (5) transitions, (6) coronavirus disease and diabetes in the hospital, (7) drugs for diabetes, (8) continuous glucose monitoring, (9) quality improvement, (10) diabetes care and educatinon, and (11) uniting people, process, and technology to achieve optimal glycemic management. This meeting covered new technology that will enable better care of people with diabetes if they are hospitalized.
Collapse
Affiliation(s)
| | | | | | - Nicole Y. Xu
- Diabetes Technology Society, Burlingame, CA, USA
| | | | | | | | | | - Amisha Wallia
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | | | | | - Umesh Masharani
- University of California San Francisco, San Francisco, CA, USA
| | | | | | | | - Viral N. Shah
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO, USA
| | | | | | | | - David C. Klonoff
- Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, CA, USA
- David C. Klonoff, MD, FACP, FRCP (Edin), Fellow AIMBE, Diabetes Research Institute, Mills-Peninsula Medical Center, 100 South San Mateo Drive, Room 5147, San Mateo, CA 94401, USA.
| |
Collapse
|
5
|
Janjindamai W, Tiwawatpakorn N, Thatrimontrichai A, Dissaneevate S, Maneenil G, Phatigomet M. Accuracy of neonatal venous blood glucose measurements using blood gas analyzer compared with central laboratory chemistry analyzer. J Clin Neonatol 2022. [DOI: 10.4103/jcn.jcn_110_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
|
6
|
See KC. Glycemic targets in critically ill adults: A mini-review. World J Diabetes 2021; 12:1719-1730. [PMID: 34754373 PMCID: PMC8554370 DOI: 10.4239/wjd.v12.i10.1719] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 06/06/2021] [Accepted: 09/03/2021] [Indexed: 02/06/2023] Open
Abstract
Illness-induced hyperglycemia impairs neutrophil function, increases pro-inflammatory cytokines, inhibits fibrinolysis, and promotes cellular damage. In turn, these mechanisms lead to pneumonia and surgical site infections, prolonged mechanical ventilation, prolonged hospitalization, and increased mortality. For optimal glucose control, blood glucose measurements need to be done accurately, frequently, and promptly. When choosing glycemic targets, one should keep the glycemic variability < 4 mmol/L and avoid targeting a lower limit of blood glucose < 4.4 mmol/L. The upper limit of blood glucose should be set according to casemix and the quality of glucose control. A lower glycemic target range (i.e., blood glucose 4.5-7.8 mmol/L) would be favored for patients without diabetes mellitus, with traumatic brain injury, or who are at risk of surgical site infection. To avoid harm from hypoglycemia, strict adherence to glycemic control protocols and timely glucose measurements are required. In contrast, a higher glycemic target range (i.e., blood glucose 7.8-10 mmol/L) would be favored as a default choice for medical-surgical patients and patients with diabetes mellitus. These targets may be modified if technical advances for blood glucose measurement and control can be achieved.
Collapse
Affiliation(s)
- Kay Choong See
- Division of Respiratory and Critical Care Medicine, Department of Medicine, National University Hospital, Singapore 119228, Singapore
| |
Collapse
|
7
|
Toffaletti JG, Buckner KA, Liu B, Green CL. Retrospective Analysis of Quality Control Data Using Pooled Blood to Compare Agreement within Two Models of Blood Gas Analyzers. J Appl Lab Med 2021; 6:1228-1236. [PMID: 34080626 DOI: 10.1093/jalm/jfab029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 03/15/2021] [Indexed: 11/13/2022]
Abstract
BACKGROUND Two previous reports from the same group concluded that the analytical reliability of Instrumentation Laboratory GEM4000 analyzers (GEM4K) deteriorated during a 24-hour period, based on results between samples from the same patient but collected at different times. Our routine blood gas Between-Laboratory Survey is done every 2 weeks using a freshly pooled heparinized blood sample taken to each analyzer location to verify comparability among our GEM4K and Radiometer ABL90 (Rad90) blood gas analyzers. Because another report found a few very large differences in glucose results between the GEM4K and central laboratory analyzers, we reviewed the glucose results on plasma from our Chemistry Between-Laboratory Surveys that includes comparisons between our central laboratory analyzers (Beckman DxC800; DxC800) and our GEM4K and Rad90 blood gas analyzers. METHOD Using data from our Blood Gas and Chemistry Surveys over a 55-week period, we calculated the mean, standard deviation (SD), and concentration intervals of the 27 sets of results by the GEM4K or Rad90 analyzers. Agreement in plasma glucose between DxC800 and blood gas analyzers was evaluated by the limits of agreement and intraclass correlation coefficient analysis. RESULTS For each analyte, the Rad90 had lower average SD than the GEM4K for the 55-week period, although both brands of analyzers showed acceptable performance. For plasma glucose results on our Chemistry Survey, the GEM4K results agreed more closely with the DxC800 results than the Rad90 results. CONCLUSIONS Based on both our Blood Gas and Chemistry Surveys, we conclude that both brands of analyzers performed within analytically and clinically acceptable limits throughout the year, with no evidence for the type of errors reported previously.
Collapse
Affiliation(s)
- John G Toffaletti
- Department of Pathology/Clinical Laboratories, Duke University Medical Center, Durham, NC
| | - Kelly A Buckner
- Department of Pathology/Clinical Laboratories, Duke University Medical Center, Durham, NC
| | - Beiyu Liu
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC
| | - Cynthia L Green
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC
| |
Collapse
|
8
|
Cembrowski G, Jung J, Mei J, Xu E, Curic T, Gibney RTN, Jacka M, Sadrzadeh H. Five-Year Two-Center Retrospective Comparison of Central Laboratory Glucose to GEM 4000 and ABL 800 Blood Glucose: Demonstrating the (In)adequacy of Blood Gas Glucose. J Diabetes Sci Technol 2020; 14:535-545. [PMID: 31686527 PMCID: PMC7576946 DOI: 10.1177/1932296819883260] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
PURPOSE To evaluate the glucose assays of two blood gas analyzers (BGAs) in intensive care unit (ICU) patients by comparing ICU BGA glucoses to central laboratory (CL) glucoses of almost simultaneously drawn specimens. METHODS Data repositories provided five years of ICU BGA glucoses and contemporaneously drawn CL glucoses from a Calgary, Alberta ICU equipped with IL GEM 4000 and CL Roche Cobas 8000-C702, and an Edmonton, Alberta ICU equipped with Radiometer ABL 800 and CL Beckman-Coulter DxC. Blood glucose analyzer and CL glucose differences were evaluated if they were both drawn either within ±15 or ±5 minutes. Glucose differences were assessed graphically and quantitatively with simple run charts and the surveillance error grid (SEG) and quantitatively with the 2016 Food and Drug Administration guidance document, with ISO 15197 and SEG statistical summaries. As the GEM glucose exhibits diurnal variation, CL-arterial blood gas (ABG) differences were evaluated according to time of day. RESULTS Compared to the GEM glucoses measured between 0200 and 0800, the run charts of (GEM-CL) glucose demonstrate significant outliers between 0800 and 0200 which are identified as moderate to severe clinical outliers by SEG analysis (P < .002 and P < .0005 for 5- and 15-minute intervals). Over the entire 24-hour period, the rates of moderate to severe glucose clinical outliers are 3.5/1000 (GEM) and 0.6/1000 glucoses (ABL), respectively, using the 15-minute interval (P < .0001). DISCUSSION The GEM ABG glucose is associated with a higher frequency of moderate to severe glucose clinical outliers, especially between 0800 and 0200, increased CL testing and higher average patient glucoses.
Collapse
Affiliation(s)
- George Cembrowski
- Laboratory Medicine and Pathology,
University of Alberta, Edmonton, AB, Canada
- CC Quality Control Consulting,
Laboratory Concision, Edmonton, AB, Canada
- George Cembrowski, MD, PhD, Laboratory
Medicine and Pathology, University of Alberta, Edmonton, AB, Canada T5N 3M7.
| | - Joanna Jung
- Laboratory Medicine and Pathology,
University of Alberta, Edmonton, AB, Canada
| | - Junyi Mei
- College of Medicine, University of
Manitoba, Winnipeg, MB, Canada
| | - Eric Xu
- College of Medicine, University of
Manitoba, Winnipeg, MB, Canada
| | | | - RT Noel Gibney
- Critical Care, School of Medicine,
University of Alberta, Edmonton, AB, Canada
| | - Michael Jacka
- Critical Care, School of Medicine,
University of Alberta, Edmonton, AB, Canada
| | - Hossein Sadrzadeh
- Calgary Laboratory Services, AB,
Canada
- Cumming School Medicine, University of
Calgary, Calgary, AB, Canada
| |
Collapse
|
9
|
Abstract
Type 1 diabetes mellitus is a lifelong condition. It requires intensive patient involvement including frequent glucose measurements and subcutaneous insulin dosing to provide optimal glycemic control to decrease short- and long-term complications of diabetes mellitus without causing hypoglycemia. Variations in insulin pharmacokinetics and responsiveness over time in addition to illness, stress, and a myriad of other factors make ideal glucose control a challenge. Control-to-range and control-to-target artificial pancreas devices (closed-loop artificial pancreas devices [C-APDs]) consist of a continuous glucose monitor, response algorithm, and insulin delivery device that work together to automate much of the glycemic management for an individual while continually adjusting insulin dosing toward a glycemic target. In this way, a C-APD can improve glycemic control and decrease the rate of hypoglycemia. The MiniMed 670G (Medtronic, Fridley, MN) system is currently the only Food and Drug Administration-cleared C-APD in the United States. In this system, insulin delivery is continually adjusted to a glucose concentration, and the patient inputs meal-time information to modify insulin delivery as needed. Data thus far suggest improved glycemic control and decreased hypoglycemic events using the system, with decreased need for patient self-management. Thus, the anticipated use of these devices is likely to increase dramatically over time. There are limited case reports of safe intraoperative use of C-APDs, but the Food and Drug Administration has not cleared any device for such use. Nonetheless, C-APDs may offer an opportunity to improve patient safety and outcomes through enhanced intraoperative glycemic control. Anesthesiologists should become familiar with C-APD technology to help develop safe and effective protocols for their intraoperative use. We provide an overview of C-APDs and propose an introductory strategy for intraoperative study of these devices.
Collapse
|
10
|
Survey on hypoglycaemia diagnosis and glucometer use—which is the most widely used glucometer in Spanish neonatology units? NUTR HOSP 2020; 37:909-917. [DOI: 10.20960/nh.03203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
|
11
|
Abstract
OBJECTIVES Tight glycemic control using intermittent blood glucose measurements is associated with a risk of hypoglycemia. Glucose concentrations can now be measured near continuously (every 5-15 min). We assessed the quality and safety of glycemic control guided by a near-continuous glucose monitoring system in ICU patients. DESIGN Prospective, cluster-randomized, crossover study. SETTING Thirty-five-bed medico-surgical department of intensive care with four separate ICUs. PATIENTS Adult patients admitted to the department and expected to stay for at least 3 days were considered for inclusion if they had persistent hyperglycemia (blood glucose > 150 mg/dL) up to 6 hours after admission and/or were receiving insulin therapy. INTERVENTIONS A peripheral venous catheter was inserted in all patients and connected to a continuous glucose monitoring sensor (GlucoClear; Edwards Lifesciences, Irvine, CA). The four ICUs were randomized in pairs in a crossover design to glycemic control using unblinded or blinded continuous glucose monitoring monitors. The insulin infusion rate was adjusted to keep blood glucose between 90 and 150 mg/dL using the blood glucose values displayed on the continuous glucose monitor (continuous glucose monitoring group-unblinded units) or according to intermittent blood glucose readings (intermittent glucose monitoring group-blinded units). MEASUREMENTS AND MAIN RESULTS The quality and safety of glycemic control were assessed using the proportion of time in range, the frequency of blood glucose less than 70 mg/dL, and the time spent with blood glucose less than 70 mg/dL (TB70), using blood glucose values measured by the continuous glucose monitoring device. Seventy-seven patients were enrolled: 39 in the continuous glucose monitoring group and 38 in the intermittent glucose monitoring group. A total of 43,107 blood glucose values were recorded. The time in range was similar in the two groups. The incidence of hypoglycemia (8/39 [20.5%] vs 15/38 [39.5%]) and the TB70 (0.4% ± 0.9% vs 1.6% ± 3.4%; p < 0.05) was lower in the continuous glucose monitoring than in the intermittent glucose monitoring group. CONCLUSIONS Use of a continuous glucose monitoring-based strategy decreased the incidence and severity of hypoglycemia, thus improving the safety of glycemic control.
Collapse
|
12
|
|
13
|
Flawed analytical method used for reference glucose. Can J Anaesth 2019; 67:158-159. [DOI: 10.1007/s12630-019-01444-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 05/17/2019] [Accepted: 05/17/2019] [Indexed: 12/17/2022] Open
|
14
|
Abstract
Hyperglycemia is common in the intensive care unit (ICU) both in patients with and without a previous diagnosis of diabetes. The optimal glucose range in the ICU population is still a matter of debate. Given the risk of hypoglycemia associated with intensive insulin therapy, current recommendations include treating hyperglycemia after two consecutive glucose >180 mg/dL with target levels of 140-180 mg/dL for most patients. The optimal method of sampling glucose and delivery of insulin in critically ill patients remains elusive. While point of care glucose meters are not consistently accurate and have to be used with caution, continuous glucose monitoring (CGM) is not standard of care, nor is it generally recommended for inpatient use. Intravenous insulin therapy using paper or electronic protocols remains the preferred approach for critically ill patients. The advent of new technologies, such as electronic glucose management, CGM, and closed-loop systems, promises to improve inpatient glycemic control in the critically ill with lower rates of hypoglycemia.
Collapse
Affiliation(s)
- Pedro D. Salinas
- Aurora Critical Care Services,
University of Wisconsin School of Medicine and Public Health, Milwaukee, WI,
USA
| | - Carlos E. Mendez
- Froedtert and Medical College of
Wisconsin, Division of Diabetes and Endocrinology, Zablocki Veteran Affairs Medical
Center, Milwaukee, WI, USA
| |
Collapse
|
15
|
Villena Gonzales W, Mobashsher AT, Abbosh A. The Progress of Glucose Monitoring-A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors. SENSORS (BASEL, SWITZERLAND) 2019; 19:E800. [PMID: 30781431 PMCID: PMC6412701 DOI: 10.3390/s19040800] [Citation(s) in RCA: 218] [Impact Index Per Article: 43.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 01/20/2019] [Accepted: 01/22/2019] [Indexed: 02/07/2023]
Abstract
Current glucose monitoring methods for the ever-increasing number of diabetic people around the world are invasive, painful, time-consuming, and a constant burden for the household budget. The non-invasive glucose monitoring technology overcomes these limitations, for which this topic is significantly being researched and represents an exciting and highly sought after market for many companies. This review aims to offer an up-to-date report on the leading technologies for non-invasive (NI) and minimally-invasive (MI) glucose monitoring sensors, devices currently available in the market, regulatory framework for accuracy assessment, new approaches currently under study by representative groups and developers, and algorithm types for signal enhancement and value prediction. The review also discusses the future trend of glucose detection by analyzing the usage of the different bands in the electromagnetic spectrum. The review concludes that the adoption and use of new technologies for glucose detection is unavoidable and closer to become a reality.
Collapse
Affiliation(s)
- Wilbert Villena Gonzales
- School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Brisbane 4072, Australia.
| | - Ahmed Toaha Mobashsher
- School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Brisbane 4072, Australia.
| | - Amin Abbosh
- School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Brisbane 4072, Australia.
| |
Collapse
|
16
|
Klonoff DC, Umpierrez GE, Rice MJ. A Milestone in Point of Care Capillary Blood Glucose Monitoring of Critically Ill Hospitalized Patients. J Diabetes Sci Technol 2018; 12:1095-1100. [PMID: 30246543 PMCID: PMC6232725 DOI: 10.1177/1932296818801607] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- David C. Klonoff
- Diabetes Research Institute,
Mills-Peninsula Medical Center, San Mateo, CA, USA
| | - Guillermo E. Umpierrez
- Division of Endocrinology, Metabolism,
and Lipids, Emory University School of Medicine, Atlanta, GA, USA
| | - Mark J. Rice
- Department of Anesthesiology, Vanderbilt
University Medical Center, Nashville, TN, USA
| |
Collapse
|
17
|
Abstract
PURPOSE OF REVIEW There is ongoing controversy surrounding the use of glucose monitoring in the perioperative setting. It is an important aspect of patient care, but the best way to go about monitoring this parameter is still up for debate. This article will review previously established data and new developments in this field. RECENT FINDINGS Several different methods exist to measure blood glucose levels in the perioperative setting, including central laboratory devices, blood gas analyzers, and point-of-care devices. However, it has been recommended that point-of-care devices not be used on 'critically ill' patients, which throws into question the common use of these devices perioperatively. Recently, the Centers for Medicare and Medicaid placed a moratorium on this recommendation, and these devices continue to be a staple in the perioperative setting, but there are other methods of glucose monitoring that can be employed. SUMMARY The monitoring of blood glucose levels in the perioperative patient remains an important part of patient care; however, debate still exist on how best to reliably measure blood glucose levels in the most effective manner.
Collapse
|
18
|
|
19
|
Ba Y, Xu J, Yuan L, Zhu H, Yang Y, Lam MM, Zhang S, Xiao M, Xu J, Zhang R, Chen C. Assessment of the performance of blood glucose monitoring systems for monitoring dysglycaemia in neonatal patients. BMJ Paediatr Open 2018; 2:e000339. [PMID: 30397671 PMCID: PMC6203032 DOI: 10.1136/bmjpo-2018-000339] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2018] [Revised: 08/24/2018] [Accepted: 09/01/2018] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVE To validate a three-step protocol that assesses the clinical risk associated with using blood glucose monitoring systems (BGMS) in neonates for the management of dysglycaemia. METHOD The three-step validation approach included confirmation of the accuracy of the reference method using National Institute of Standards and Technology (NIST) glucose standards, assessment of analytical risk performed on whole blood collected from paediatric patients routinely tested for glucose and a clinical risk assessment performed using heel stick capillary samples collected from 147 new-born babies and neonates admitted to intensive care. BGMS glucose measurements were compared with the NIST aligned laboratory reference method. RESULTS The accuracy of the laboratory reference method was confirmed with the NIST standards. Specificity studies demonstrated that the accuracy of one of the BGMS was affected, particularly, in the hypoglycaemic range, by known interference factors including haematocrit, ascorbic acid, lactose, galactose, N-acetylcysteine and glutathione. The accuracy of the other BGMS was unaffected. The clinical performance of this BGMS in neonates met the system accuracy criteria of Clinical and Laboratory Standards Institute (CLSI) POCT 12-A3 standard for evaluating hospital BGMS with 95.1% of glucose measurements within±0.67 mmol/L for samples ≤5.55 mmol/L and 95.6% within±12.5% for samples>5.55 mmol/L. CONCLUSIONS This three-step validation protocol provides a challenging approach for determining the accuracy and reliability of BGMS for managing dysglycaemia in neonates. StatStrip BGMS achieved analytical and clinical performance criteria confirming its suitability for use in neonates. We advocate that this validation approach should be considered for performance evaluations of both BGMS and continuous glucose monitoring systems going forward.
Collapse
Affiliation(s)
- Yin Ba
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Jin Xu
- Department of Clinical Laboratory, Children's Hospital of Fudan University, Shanghai, China
| | - Lin Yuan
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Haiyan Zhu
- Department of Clinical Laboratory, Children's Hospital of Fudan University, Shanghai, China
| | - Yipei Yang
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Mei Mei Lam
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Shulian Zhang
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Mili Xiao
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Jiayin Xu
- Department of Clinical Laboratory, Children's Hospital of Fudan University, Shanghai, China
| | - Rong Zhang
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Chao Chen
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| |
Collapse
|
20
|
The authors reply. Crit Care Med 2017; 45:e1188-e1189. [DOI: 10.1097/ccm.0000000000002628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
|
21
|
Long MT, Sheehy AM, Coursin DB. The Search Continues for Optimal Intensive Care Unit Glucose Management and Measurement. Mayo Clin Proc 2017. [PMID: 28645516 DOI: 10.1016/j.mayocp.2017.05.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
| | - Ann M Sheehy
- Department of Medicine and Division of Hospital Medicine
| | - Douglas B Coursin
- Department of Anesthesiology and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI.
| |
Collapse
|