Remote Continuous Glucose Monitoring With a Computerized Insulin Infusion Protocol for Critically Ill Patients in a COVID-19 Medical ICU: Proof of Concept

Dexcom G7 Accuracy and Reproducibility in the Intensive Care Unit

Objective: To evaluate the accuracy of Dexcom G7 continuous glucose monitor (CGM) in the intensive care unit (ICU) setting. Methods: We performed a prospective, single-center study in patients with known diagnosis of diabetes or stress hyperglycemia and treated with insulin. Two Dexcom G7 sensors were placed on the abdomen and/or upper arm. Blood glucose (BG) measurements obtained according to usual ICU care were paired with sensor glucose values, and accuracy metrics were analyzed. For further comparison, non-ICU patients were also studied. Results: The analyses included 30 participants with mean ± standard deviation age of 55 ± 12 years, with preexisting diabetes in 40% and stress hyperglycemia in 60%. A total of 1515 sensor-BG pairs were analyzed. The mean difference (bias) was -12 mg/dL (median: -6), and the mean relative absolute difference (RAD) was 16% (median: 12%). Mean RAD was 13% (median: 9%) using plasma glucose as the reference and 17% (median: 13%) using capillary glucose. For comparison, in 35 adults with type 2 diabetes in a non-ICU setting, the mean RAD was 15% (median: 13%). No meaningful differences were observed across the duration of time since sensor insertion. No correlation was found between mean RAD and severity of illness. Conclusions: Mean RAD of the Dexcom G7 sensor in the ICU setting was slightly higher than the outpatient use labeling, but was similar to a non-ICU hospital setting. Further studies are needed to determine whether CGM can be used nonadjunctively in an ICU setting for insulin management, including use of glucose trends and alarms for hypoglycemia or hyperglycemia.

Toward Automation: The Road Traveled and Road Ahead for Integrating Automated Insulin Delivery into Inpatient Care

The introduction of automated insulin delivery (AID) systems represents a significant advancement in diabetes care, offering substantial benefits in outpatient settings. Although clinical studies suggest that these systems can also help improve glycemic control in acutely ill patients, several barriers remain for the actual implementation and use of these technologies in clinical practice. Three main contexts for inpatient use are addressed, including: (a) continuation of personal AID systems, (b) initiation of AID during hospitalization, and (c) initiation of AID systems at discharge. A research road map with immediate to long-term actions is presented. Initially, it calls for clinical studies assessing in-hospital efficacy, safety, and utility, addressing specific patient needs and health care operational impacts. Midterm, it focuses on practical integration, simplifying AID use, ensuring electronic health record compatibility, clarifying regulatory uncertainties, and supporting health care professionals and patients. Long-term goals include system optimizations and policy advocacy for in-hospital AID use.

Continuous Glucose Monitoring for Hyperglycemia in Critically Ill Patients: A Randomized Controlled Trial

BACKGROUND

Continuous glucose monitors (CGMs) could potentially improve management of hyperglycemia compared with standard point-of-care glucose monitoring for critically ill patients. However, there is limited evidence to support routine use of CGMs in the ICU.

RESEARCH QUESTION

In critically ill patients with hyperglycemia, do CGMs improve time within target glucose range compared with standard of care?

STUDY DESIGN AND METHODS

This was an investigator-initiated, single-center, parallel-group, open-label, randomized controlled trial. Adult patients admitted to a medical or surgical ICU who had diabetes mellitus or hyperglycemia and were treated with insulin were eligible for enrollment. Participants were randomly assigned to have glucose monitoring performed with a CGM (intervention group) or standard of care (control group). Groups were compared for glycemic control and other relevant outcomes. The primary outcome for the study was percentage of time within the normoglycemic range, defined as 70 to 180 mg/dL (3.9-10 mmol/L).

RESULTS

Eighty-five participants were enrolled and randomized to study groups, with 43 participants in the intervention (CGM) group and 42 patients in the control (standard of care) group. For the primary outcome, there was no statistically significant difference between the intervention group (mean ± SD, 60.5% ± 30.5%) and the control group (mean ± SD, 61.4% ± 28.3%) in time within the goal glucose range (mean difference, -0.9%; 95% CI, -13.6 to 11.8; P = .9). Except for patient satisfaction, there were no statistically significant differences between groups for secondary and exploratory outcomes.

INTERPRETATION

The results of this study do not support CGMs as a superior method for routine glucose monitoring in the ICU compared with standard of care.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov; No.: NCT05442853; URL: www.

CLINICALTRIALS

gov.

Continuous Glucose Monitoring in Hospitalized Adults With Diabetic Ketoacidosis: A Prospective Open-Label Pilot Study

BACKGROUND

Continuous glucose monitoring (CGM) devices are increasingly used in critical and non-critical care hospital units. The efficacy of CGM in assessing glucose control in adults with diabetic ketoacidosis (DKA) is unknown.

METHODS

This single-center pilot study compared glycemic control by real-time CGM (Dexcom G6), capillary point-of-care (POC), and basic metabolic panel (BMP) during intravenous (IV) insulin treatment and after the resolution of DKA. We compared the mean absolute relative difference (MARD), median absolute relative difference (ARD) glucose values, and Diabetes Technology Society (DTS) Error Grid analyses.

RESULTS

We recruited 52 patients (49 ± 19 years, admission glucose: 503 ± 239.4 mg/dL) with type 1 diabetes (n = 24) and type 2 diabetes (n = 28). Compared with POC testing, the MARD was 17.4% ± 13.2%, and the median ARD was 14.2% (interquartile range [IQR]: 6.4, 28) during the initial IV insulin period and 19.8% ± 18.7% and 14.3% (7, 26.2) after DKA resolution. The DTS Error Grid analysis showed that 100% of values during the IV insulin treatment and 95% after the DKA resolution were in zones A+B. Compared with BMP glucose values, the MARD and median ARD were 18.5% ± 19.1% and 12.2% (5.4, 23.8) during the IV insulin treatment and 22.5% ± 24.7% and 15.1% (6.6, 27.6) after DKA resolution.

CONCLUSION

This is the first report on the use of real-time CGM in adults with DKA. Our study indicates that CGM technology is a reliable tool for hospital use during acute insulin treatment and after the resolution of DKA. Future multicentre randomized studies are needed to determine the benefits of real-time CGM in facilitating diabetes care in hospitalized patients with hyperglycemic crises.

Continuous peri-operative glucose monitoring in noncardiac surgery: A systematic review

BACKGROUND

Glucose management is an important component of peri-operative care. The usefulness of continuous glucose monitoring (CGM) in noncardiac surgery is uncertain.

OBJECTIVE

To systematically assess the glycaemic profile and clinical outcome of patients equipped with a CGM device during the peri-operative period in noncardiac surgery.

DESIGN

Systematic review.

DATA SOURCES

Electronic databases were systematically searched up to July 2024.

ELIGIBILITY CRITERIA

Any studies performed in the peri-operative setting using a CGM device were included. Closed-loop systems also administering insulin were excluded. Analyses were stratified according to diabetes mellitus status and covered intra-operative and postoperative data. Outcomes included glycaemic profile (normal range 3.9 to 10.0 mmol l -1 ), complications, adverse events, and device dysfunction.

RESULTS

Twenty-six studies (1016 patients) were included. Twenty-four studies were not randomised, and six used a control arm for comparison. In bariatric surgery, diabetes mellitus patients had a mean ± SD glucose of 5.6 ± 0.5 mmol l -1 , with 15.4 ± 8.6% time below range, 75.3 ± 5.5% in range and 9.6 ± 6.7% above range. During major surgery, diabetes mellitus patients showed a mean glucose of 9.6 ± 1.1 mmol l -1 , with 9.5 ± 9.1% of time below range, 56.3 ± 13.5% in range and 30.6 ± 13.9% above range. In comparison, nondiabetes mellitus patients had a mean glucose of 6.4 ± 0.6 mmol l -1 , with 6.7 ± 8.4% time below range, 84.6 ± 15.5% in range and 11.2 ± 4.9% above range. Peri-operative complications were reported in only one comparative study and were similar in CGM and control groups. Device-related adverse events were rare and underreported. In 9.21% of cases, the devices experienced dysfunctions such as accidental removal and issues with sensors or readers.

CONCLUSION

Due to the limited number of controlled studies, the impact of CGM on postoperative glycaemic control and complications compared with point-of-care testing remains unknown. Variability in postoperative glycaemic profiles and a device dysfunction rate of 1 in 10 suggest CGM should be investigated in a targeted surgical group.

Use of continuous glucose monitoring and point-of-care glucose testing in hospitalized patients with diabetes mellitus in non-intensive care unit settings: A systematic review and meta-analysis of randomized controlled trials

The benefits of using continuous glucose monitoring (CGM) in hospitalized patients with diabetes remain uncertain. Point-of-care (POC) glucose testing is the standard of care in this setting. We compared the effect of adding CGM to POC testing versus POC testing alone on glycemic outcomes in this population. We have searched the Cochrane Library, Embase, and MEDLINE databases and relevant conferences up to May 2024. We have included six randomized controlled trials (n = 979 patients) comparing CGM plus POC testing to POC testing alone in non-pregnant, non-critically ill hospitalized adults with diabetes. The addition of CGM improved time in range (mean difference [MD] + 7.24 %; 95 % confidence interval [CI]: +5.06, +9.42; P < 0.00001; I2 = 35 %), reduced time below range < 70 mg/dL (MD: -1.23 %; 95 %CI: -2.27, -0.18; P = 0.02; I2 = 64 %) and < 54 mg/dL (MD: -0.95 %; 95 %CI: -1.19, -0.70; P < 0.00001; I2 = 0 %), and time above range > 250 mg/dL (MD: -3.70 %; 95 %CI: -6.10, -1.29; P = 0.003; I2 = 39 %) compared to POC testing alone. We observed no statistically significant differences in glycemic variability or insulin doses. In non-critically ill, hospitalized adults with diabetes, the addition of CGM to POC testing for insulin dosing resulted in superior glycemic control and reduction of hypoglycemia compared to POC testing alone.

American Diabetes Association Professional Practice Committee, ElSayed NA, McCoy RG, Aleppo G, Balapattabi K, Beverly EA, Briggs Early K, Bruemmer D, Echouffo-Tcheugui JB, Ekhlaspour L, Garg R, Khunti K, Lal R, Lingvay I, Matfin G, Pandya N, Pekas EJ, Pilla SJ, Polsky S, Segal AR, Seley JJ, Stanton RC, Bannuru RR. 7. Diabetes Technology: Standards of Care in Diabetes-2025

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Consensus Considerations and Good Practice Points for Use of Continuous Glucose Monitoring Systems in Hospital Settings

Continuous glucose monitoring (CGM) systems provide frequent glucose measurements in interstitial fluid and have been used widely in ambulatory settings for diabetes management. During the coronavirus disease 2019 (COVID-19) pandemic, regulators in the U.S. and Canada temporarily allowed for CGM systems to be used in hospitals with the aim of reducing health care professional COVID-19 exposure and limiting use of personal protective equipment. As such, studies on hospital CGM system use have been possible. With improved sensor accuracy, there is increased interest in CGM usage for diabetes management in hospitals. Laboratorians and health care professionals must determine how to integrate CGM usage into practice. The aim of this consensus guidance document is to provide an update on the application of CGM systems in hospital, with insights and opinions from laboratory medicine, endocrinology, and nursing.

Accuracy of continuous glucose monitoring systems in intensive care unit patients: a scoping review

PURPOSE

Glycemic control poses a challenge in intensive care unit (ICU) patients and dysglycemia is associated with poor outcomes. Continuous glucose monitoring (CGM) has been successfully implemented in the type 1 diabetes out-patient setting and renewed interest has been directed into the transition of CGM into the ICU. This scoping review aimed to provide an overview of CGM accuracy in ICU patients to inform future research and CGM implementation.

METHODS

We systematically searched PubMed and EMBASE between 5th of December 2023 and 21st of May 2024 and reported findings in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline for scoping reviews (PRISMA-ScR). We assessed studies reporting the accuracy of CGM in the ICU and report study characteristics and accuracy outcomes.

RESULTS

We identified 2133 studies, of which 96 were included. Most studies were observational (91.7%), conducted in adult patients (74%), in mixed ICUs (47.9%), from 2014 and onward, and assessed subcutaneous CGM systems (80%) using arterial blood samples as reference test (40.6%). Half of the studies (56.3%) mention the use of a prespecified reference test protocol. The mean absolute relative difference (MARD) ranged from 6.6 to 30.5% for all subcutaneous CGM studies. For newer factory calibrated CGM, MARD ranged from 9.7 to 20.6%. MARD for intravenous CGM was 5-14.2% and 6.4-13% for intraarterial CGM.

CONCLUSIONS

In this scoping review of CGM accuracy in the ICU, we found great diversity in accuracy reporting. Accuracy varied depending on CGM and comparator, and may be better for intravascular CGM and potentially lower during hypoglycemia.

Continuous glucose monitoring versus conventional glucose monitoring in the ICU: A randomized controlled trial

PURPOSE

This study evaluated the clinical utility of continuous glucose monitoring system (CGMS) in critically ill patients.

METHODS

In this randomized controlled trial, we randomly assigned critically ill participants with diabetes or stress-induced hyperglycemia to the CGMS group (n = 48) or to the conventional point-of-care monitoring (POCM) group (n = 48). The glucose values and clinical outcome were compared between the two group. The primary endpoint was 28-day mortality after intensive care unit admission.

RESULTS

The 28-day mortality was not significantly different between the CGMS and POCM group (20.8% vs 31.3%, P = 0.25). The mean glucose, time-weighted average glucose, glucose standard deviation and time in range (3.9-10.0) were significantly improved in the CGMS group (all P < 0.05).

CONCLUSION

Compared with conventional POCM, CGMS did not decrease the 28-day mortality in critically ill participants with diabetes or stress-induced hyperglycemia. But CGMS may improve the glycemic control and may be increasingly used in critically ill patients.

Empowering Hospitalized Patients With Diabetes: Implementation of a Hospital-wide CGM Policy With EHR-Integrated Validation for Dosing Insulin

OBJECTIVE

We aimed to assess the feasibility, clinical accuracy, and acceptance of a hospital-wide continuous glucose monitoring (CGM) policy with electronic health record (EHR)-integrated validation for insulin dosing.

RESEARCH DESIGN AND METHODS

A hospital policy was developed and implemented at Stanford Health Care for using personal CGMs in lieu of fingerstick blood glucose (FSBG) monitoring. It included requirements specific to each CGM, accuracy monitoring protocols, and EHR integration. User experience surveys were conducted among a subset of patients and nurses.

RESULTS

From November 2022 to August 2023, 135 patients used the CGM protocol in 185 inpatient encounters. This group included 27% with type 1 diabetes and 24% with automated insulin delivery systems. The most-used CGMs were Dexcom G6 (44%) and FreeStyle Libre 2 (43%). Of 1,506 CGM validation attempts, 87.8% met the 20% or 20 mg/dL (%20/20) criterion for CGM-based insulin dosing and 99.3% fell within Clarke zones A or B. User experience surveys were completed by 27 nurses and 46 patients. Most nurses found glucose management under the protocol effective (74%), easy to use (67%), and efficient (63%); 80% of nurses preferred inpatient CGM to FSBG. Most patients liked the CGM protocol (63%), reported positive CGM interactions with nursing staff (63%), and felt no significant interruptions to their diabetes management (63%).

CONCLUSIONS

Implementation of a hospital-wide inpatient CGM policy supporting multiple CGM types with real-time accuracy monitoring and integration into the EHR is feasible. Initial feedback from nurses and patients was favorable, and further investigation toward broader use and sustainability is needed.

Glycemic Outcomes and Nurse Perceptions of Continuous Glucose Monitoring for Hospitalized Patients

BACKGROUND

Continuous glucose monitoring (CGM) can decrease hypoglycemic events and health care costs; however, barriers and facilitators that influence CGM use are unknown.

PURPOSE

The purpose of this study was to evaluate hypoglycemic events and cost outcomes after CGM implementation and describe associated barriers and facilitators.

METHODS

A mixed-methods study design was used to evaluate CGM implementation on 2 pulmonary units within an academic health center. Hypoglycemic events were evaluated before and after CGM implementation, and nurses were interviewed about facilitators and barriers that influence CGM use.

RESULTS

Hypoglycemic events decreased from a rate of 0.0906 per 1000 patient days to 0.0503 postimplementation, P < .0001. A $105 766 cost avoidance was recognized. Barriers and facilitators to CGM use are described.

CONCLUSIONS

Findings support CGM implementation, while uniquely contributing financial impact and device use barriers and facilitators. Hospitals may consider CGM use to improve timely identification and treatment of hypoglycemia.

A Randomized Clinical Trial for Meal Bolus Decision Using Learning-based Control in Adults With Type 2 Diabetes

CONTEXT

We propose an artificial-pancreas-like algorithm (AP-A) that could automatically determine the preprandial insulin dose based on intermittently scanned continuous glucose monitoring (isCGM) data trajectories in multiple dose injection (MDI) therapy.

OBJECTIVE

We aim to determine whether preprandial insulin dose adjustments guided by the AP-A are as effective and safe as physician decisions.

METHODS

We performed a randomized, single-blind, clinical trial at a tertiary, referral hospital in Beijing, China. Type 2 diabetes participants were eligible if they were aged 18 years or older, with a glycated hemoglobin A1c of 8.0% or higher. Eligible participants were randomly assigned (1:1) to the AP-A arm supervised by physician and the conventional physician treatment arm. The primary objective was to compare percentage time spent with sensor glucose level in 3.9 to 10.0 mmol/L (TIR) between the 2 study arms. Safety was assessed by the percentage time spent with sensor glucose level below 3.0 mmol/L (TBR).

RESULTS

A total of 140 participants were screened, of whom 119 were randomly assigned to the AP-A arm (n = 59) or physician arm (n = 60). The TIR achieved by the AP-A arm was statistically noninferior compared with the control arm (72.4% [63.3%-82.1%] vs 71.2% [54.9%-81.4%]), with a median difference of 1.33% (95% CI, -6.00 to 10.94, noninferiority margin -7.5%). TBR was also statistically noninferior between the AP-A and control arms (0.0% [0.0%-0.0%] vs 0.0% [0.0%-0.0%]), respectively; median difference (95% CI, 0.00% [0.00%-0.00%], noninferiority margin 2.0%).

CONCLUSION

The AP-A-supported physician titration of preprandial insulin dosage offers noninferior glycemic control compared with optimal physician care in type 2 diabetes.

Accuracy and Feasibility of Real-time Continuous Glucose Monitoring in Critically Ill Patients After Abdominal Surgery and Solid Organ Transplantation

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.

Feasibility and Performance of Continuous Glucose Monitoring to Guide Computerized Insulin Infusion Therapy in Cardiovascular Intensive Care Unit

BACKGROUND

We evaluated the feasibility of real-time continuous glucose monitoring (CGM) for titrating continuous intravenous insulin infusion (CII) to manage hyperglycemia in postoperative individuals in the cardiovascular intensive care unit and assessed their accuracy, nursing acceptance, and postoperative individual satisfaction.

METHODS

Dexcom G6 CGM devices were applied to 59 postsurgical patients with hyperglycemia receiving CII. A hybrid approach combining CGM with periodic point-of-care blood glucose (POC-BG) tests with two phases (initial-ongoing) of validation was used to determine CGM accuracy. Mean and median absolute relative differences and Clarke Error Grid were plotted to evaluate the CGM accuracy. Surveys of nurses and patients on the use of CGMs experience were conducted and results were analyzed.

RESULTS

In this cohort (mean age 64, 32% female, 32% with diabetes) with 864 paired POC-BG and CGM values analyzed, mean and median absolute relative difference between POC-BG and CGM values were 13.2% and 9.8%, respectively. 99.7% of paired CGM and POC-BG were in Zones A and B of the Clarke Error Grid. Responses from nurses reported CGMs being very or quite convenient (n = 28; 93%) and it was favored over POC-BG testing (n = 28; 93%). Majority of patients (n = 42; 93%) reported their care process using CGM as being good or very good.

CONCLUSION

This pilot study demonstrates the feasibility, accuracy, and nursing convenience of adopting CGM via a hybrid approach for insulin titration in postoperative settings. These findings provide robust rationale for larger confirmatory studies to evaluate the benefit of CGM in postoperative care to improve workflow, enhance health outcomes, and cost-effectiveness.

Evaluation of a hybrid protocol using continuous glucose monitoring and point-of-care testing in non-critically ill patients in a community hospital

PURPOSE

Inpatient glycemic management typically involves use of point-of-care (POC) glucose measurements to inform insulin dosing decisions. This study evaluated a hybrid monitoring protocol using real-time continuous glucose monitoring (rtCGM) supplemented with POC testing at a community hospital.

METHODS

Adult inpatients receiving POC glucose testing were monitored using rtCGM in a telemetry unit. The hybrid monitoring protocol required a once-daily POC test but otherwise primarily relied on rtCGM values for insulin dosing decisions. Outcomes assessment included surveillance error grid (SEG) and Clarke Error Grid (CEG) analysis results, the mean absolute relative difference (MARD) for available rtCGM-POC value pairs before and after study protocol application, the number of POC tests avoided, and the number of hypoglycemic events involving a blood glucose value of <70 mg/dL identified by rtCGM and POC values.

RESULTS

Data were collected from 30 inpatients (the mean age was 69.4 years, 77% were female, 80% had type 2 diabetes, and 37% were at-home insulin users). With the protocol applied, a total of 202 rtCGM-POC pairs produced a MARD of 12.5%. SEG analysis showed 2 pairs in the "moderate" risk category, with all other pairs in the "none" or "slight" risk categories. CEG analysis showed 99% of paired values to be in the clinically acceptable range. Six hypoglycemic events in 5 patients were resolved without incident. Three hundred three POC tests were avoided, a 60% reduction for the study duration.

CONCLUSION

Use of a hybrid monitoring protocol of rtCGM and POC testing in a community hospital demonstrated sustained rtCGM accuracy and was found to reduce the frequency of POC testing to manage inpatient glycemia.

Society of Critical Care Medicine Guidelines on Glycemic Control for Critically Ill Children and Adults 2024

RATIONALE

Maintaining glycemic control of critically ill patients may impact outcomes such as survival, infection, and neuromuscular recovery, but there is equipoise on the target blood levels, monitoring frequency, and methods.

OBJECTIVES

The purpose was to update the 2012 Society of Critical Care Medicine and American College of Critical Care Medicine (ACCM) guidelines with a new systematic review of the literature and provide actionable guidance for clinicians.

PANEL DESIGN

The total multiprofessional task force of 22, consisting of clinicians and patient/family advocates, and a methodologist applied the processes described in the ACCM guidelines standard operating procedure manual to develop evidence-based recommendations in alignment with the Grading of Recommendations Assessment, Development, and Evaluation Approach (GRADE) methodology. Conflict of interest policies were strictly followed in all phases of the guidelines, including panel selection and voting.

METHODS

We conducted a systematic review for each Population, Intervention, Comparator, and Outcomes question related to glycemic management in critically ill children (≥ 42 wk old adjusted gestational age to 18 yr old) and adults, including triggers for initiation of insulin therapy, route of administration, monitoring frequency, role of an explicit decision support tool for protocol maintenance, and methodology for glucose testing. We identified the best available evidence, statistically summarized the evidence, and then assessed the quality of evidence using the GRADE approach. We used the evidence-to-decision framework to formulate recommendations as strong or weak or as a good practice statement. In addition, "In our practice" statements were included when the available evidence was insufficient to support a recommendation, but the panel felt that describing their practice patterns may be appropriate. Additional topics were identified for future research.

RESULTS

This guideline is an update of the guidelines for the use of an insulin infusion for the management of hyperglycemia in critically ill patients. It is intended for adult and pediatric practitioners to reassess current practices and direct research into areas with inadequate literature. The panel issued seven statements related to glycemic control in unselected adults (two good practice statements, four conditional recommendations, one research statement) and seven statements for pediatric patients (two good practice statements, one strong recommendation, one conditional recommendation, two "In our practice" statements, and one research statement), with additional detail on specific subset populations where available.

CONCLUSIONS

The guidelines panel achieved consensus for adults and children regarding a preference for an insulin infusion for the acute management of hyperglycemia with titration guided by an explicit clinical decision support tool and frequent (≤ 1 hr) monitoring intervals during glycemic instability to minimize hypoglycemia and against targeting intensive glucose levels. These recommendations are intended for consideration within the framework of the patient's existing clinical status. Further research is required to evaluate the role of individualized glycemic targets, continuous glucose monitoring systems, explicit decision support tools, and standardized glycemic control metrics.

[Current Status of Research on COVID-19 Patients With Concomitant Hyperglycemia and the Management Strategies of Hyperglycemia]

The global pandemic of coronavirus disease 2019 (COVID-19) poses a serious threat to human health, leading to a relatively high mortality in patients with severe or critical conditions in particular. Hyperglycemia is one of the high-risk factors for poor prognosis in these patients. Patients with COVID-19 are more likely to develop hyperglycemia, regardless of whether there is a previous history of diabetes mellitus. Glucocorticoid therapy is an important part of the anti-inflammatory regimen for COVID-19. However, the use of glucocorticoid significantly increases the occurrence of hyperglycemic events in COVID-19 patients, ultimately leading to poor prognosis. Timely monitoring of blood glucose and early intervention for hyperglycemia contribute to the improvement in the outcome of COVID-19 patients. In this paper, we comprehensively reviewed the potential mechanisms of COVID-19 and concomitant hyperglycemia. We reviewed the latest findings on the blood glucose management strategies for COVID-19 patients with concomitant hyperglycemia, aiming to optimize the management of hyperglycemia in COVID-19 patients and improve the outcome of the disease.

American Diabetes Association Professional Practice Committee, ElSayed NA, Aleppo G, Bannuru RR, Bruemmer D, Collins BS, Ekhlaspour L, Hilliard ME, Johnson EL, Khunti K, Lingvay I, Matfin G, McCoy RG, Perry ML, Pilla SJ, Polsky S, Prahalad P, Pratley RE, Segal AR, Seley JJ, Stanton RC, Gabbay RA. 7. Diabetes Technology: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

A Consensus Statement for Continuous Glucose Monitoring Metrics for Inpatient Clinical Trials

Diabetes Technology Society organized an expert consensus panel to develop metrics for research in the use of continuous glucose monitors (CGMs) in a hospital setting. The experts met virtually in small groups both before and after an April 13, 2023 virtual meeting of the entire panel. The goal of the panel was to develop consensus definitions in anticipation of greater use of CGMs in hospital settings in the future. Establishment of consensus definitions of inpatient analytical metrics will be easier to compare outcomes between studies. Panelists defined terms related to 10 dimensions of measurements related to the use of CGMs including (1) hospital hypoglycemia, (2) hospital hyperglycemia, (3) hospital time in range, (4) hospital glycemic variability, (5) hospital glycemia risk index, (6) accuracy of CGM devices and reference methods for CGMs in the hospital, (7) meaningful time blocks for hospital glycemic goals, (8) hospital CGM data sufficiency, (9) using CGM data for insulin dosing, and (10) miscellaneous factors. The panelists voted on 51 proposed recommendations. Based on the panel vote, 51 recommendations were classified as either strong (43) or mild (8). Additional research is needed on CGM performance in the hospital. This consensus report is intended to support that type of research intended to improve outcomes for hospitalized people with diabetes.

Continuous glucose monitoring for inpatient diabetes management: an update on current evidence and practice

Over the last few years, several exciting changes in continuous glucose monitoring (CGM) technology have expanded its use and made CGM the standard of care for patients with type 1 and type 2 diabetes using insulin therapy. Consequently, hospitals started to notice increased use of these devices in their hospitalized patients. Furthermore during the coronavirus disease 2019 (COVID) pandemic, there was a critical need for innovative approaches to glycemic monitoring, and several hospitals started to implement CGM protocols in their daily practice. Subsequently, a plethora of studies have demonstrated the efficacy and safety of CGM use in the hospital, leading to clinical practice guideline recommendations. Several studies have also suggested that CGM has the potential to become the standard of care for some hospitalized patients, overcoming the limitations of current capillary glucose testing. Albeit, there is a need for more studies and particularly regulatory approval. In this review, we provide a historical overview of the evolution of glycemic monitoring in the hospital and review the current evidence, implementation protocols, and guidance for the use of CGM in hospitalized patients.

Automated Insulin Delivery with Remote Real-Time Continuous Glucose Monitoring for Hospitalized Patients with Diabetes: A Multicenter, Single-Arm, Feasibility Trial

Introduction: Multiple daily injection insulin therapy frequently fails to meet hospital glycemic goals and is prone to hypoglycemia. Automated insulin delivery (AID) with remote glucose monitoring offers a solution to these shortcomings. Research Design and Methods: In a single-arm multicenter pilot trial, we tested the feasibility, safety, and effectiveness of the Omnipod 5 AID System with real-time continuous glucose monitoring (CGM) for up to 10 days in hospitalized patients with insulin-requiring diabetes on nonintensive care unit medical-surgical units. Primary endpoints included the proportion of time in automated mode and percent time-in-range (TIR 70-180 mg/dL) among participants with >48 h of CGM data. Safety endpoints included incidence of severe hypoglycemia and diabetes-related ketoacidosis (DKA). Additional glycemic endpoints, CGM accuracy, and patient satisfaction were also explored. Results: Twenty-two participants were enrolled; 18 used the system for a total of 96 days (mean 5.3 ± 3.1 days per patient), and 16 had sufficient CGM data required for analysis. Median percent time in automated mode was 95% (interquartile range 92%-98%) for the 18 system users, and the 16 participants with >48 h of CGM data achieved an overall TIR of 68% ± 16%, with 0.17% ± 0.3% time <70 mg/dL and 0.06% ± 0.2% time <54 mg/dL. Sensor mean glucose was 167 ± 21 mg/dL. There were no DKA or severe hypoglycemic events. All participants reported satisfaction with the system at study end. Conclusions: The use of AID with a disposable tubeless patch-pump along with remote real-time CGM is feasible in the hospital setting. These results warrant further investigation in randomized trials.

Time requirements for perioperative glucose management using fully closed-loop versus standard insulin therapy: A proof-of-concept time-motion study

AIMS

To compare the time required for perioperative glucose management using fully automated closed-loop versus standard insulin therapy.

METHODS

We performed a time-motion study to quantify the time requirements for perioperative glucose management with fully closed-loop (FCL) and standard insulin therapy applied to theoretical scenarios. Following an analysis of workflows in different periods of perioperative care in elective surgery patients receiving FCL or standard insulin therapy upon hospital admission (pre- and intra-operatively, at the intermediate care unit and general wards), the time of process-specific tasks was measured by shadowing hospital staff. Each task was measured 20 times and its average duration in combination with its frequency according to guidelines was used to calculate the cumulative staff time required for blood glucose management. Cumulative time was calculated for theoretical scenarios consisting of elective minor and major abdominal surgeries (pancreatic surgery and sleeve gastrectomy, respectively) to account for the different care settings and lengths of stay.

RESULTS

The FCL insulin therapy reduced the time required for perioperative glucose management compared to standard insulin therapy, across all assessed care periods and for both perioperative pathways (range 2.1-4.5). For a major abdominal surgery, total time required was 248.5 min using FCL versus 753.9 min using standard insulin therapy. For a minor abdominal surgery, total time required was 68.6 min and 133.2 min for FCL and standard insulin therapy, respectively.

CONCLUSIONS

The use of fully automated closed-loop insulin delivery for inpatient glucose management has the potential to alleviate the workload of diabetes management in an environment with adequately trained staff.

Use of Continuous Glucose Monitors in the Hospital: The Diabetes Technology Society Hospital Meeting Report 2023

The annual Virtual Hospital Diabetes Meeting was hosted by the Diabetes Technology Society on April 14 and 15, 2023, with the goal of reviewing the progress made in the hospital use of continuous glucose monitors (CGMs). Meeting topics included (1) Nursing Issues, Protocols, Order Sets, and Staff Education for Using CGMs, (2) Implementing CGM Programs for Use in the Wards, (3) Quality Metrics and Financial Implications of CGMs in the Hospital, (4) CGMs in the Critical Care Setting, (5) Special Situations: Labor/Delivery and Hemodialysis, (6) Research Session on CGMs in the Hospital, (7) Starting a CGM on Hospitalized Patients, (8) Automated Insulin Delivery Systems in the Hospital, (9) CGMs in Children, (10) Data Integration of CGMs for Inpatient Use and Telemetry, (11) Accuracy of CGMs/Comparison with Point-of-care Blood Glucose Testing, and (12) Discharge Planning with CGMs. Outcome data as well as shared collective real-life experiences were reviewed, and expert recommendations for CGM implementation were formulated.

Diabetes Research and Resource Sharing During the COVID-19 Pandemic: A Systematic Review and Experience from an Academic/Non-Profit Resource Website

BACKGROUND

The magnitude of the response of the diabetes professional community to the COVID-19 pandemic is not known. We aimed to examine diabetes technology research trends and resources offered by professional organizations during this period.

METHODS

We explored patterns of the response from the professional diabetes community to the pandemic by (1) systematically searching for articles related to diabetes, COVID-19, and diabetes technologies; (2) examining publication trends of research protocols (clinicaltrials.gov) and preprints (medRxiv); and (3) reviewing online resources from professional organizations including our website (COVIDinDiabetes.org; an Emory University-Diabetes Technology Society collaboration).

RESULTS

We identified 492 articles published between December 2019 and December 2022 meeting our inclusion criteria. Telemedicine and continuous glucose monitoring were the most common reported technologies from most parts of the world. The largest number of preprint articles was published in 2020, with a decline in 2021 and 2022. The number of research protocols related to COVID-19 was the highest in 2020 and declined in 2021 and 2022. Resources from organizations included protocols adapted to treat patients with diabetes and COVID-19, training programs, emergency preparedness, and literature on diabetes and COVID-19. On our website (COVIDinDiabetes.org), there were 12 236 visits and 18 149 pageviews, with 1.6 actions per visits, with most visits coming from North America (N = 7233, 54.2%), South America (N = 2663, 21.8%), and Europe (N = 1219).

CONCLUSIONS

We conclude that the COVID-19 pandemic promoted unprecedented global research productivity related to diabetes and COVID-19 and that the transition to the use of technology resources has been evident during this period.

Interpretable physiological forecasting in the ICU using constrained data assimilation and electronic health record data

OBJECTIVE

Prediction of physiological mechanics are important in medical practice because interventions are guided by predicted impacts of interventions. But prediction is difficult in medicine because medicine is complex and difficult to understand from data alone, and the data are sparse relative to the complexity of the generating processes. Computational methods can increase prediction accuracy, but prediction with clinical data is difficult because the data are sparse, noisy and nonstationary. This paper focuses on predicting physiological processes given sparse, non-stationary, electronic health record data in the intensive care unit using data assimilation (DA), a broad collection of methods that pair mechanistic models with inference methods.

METHODS

A methodological pipeline embedding a glucose-insulin model into a new DA framework, the constrained ensemble Kalman filter (CEnKF) to forecast blood glucose was developed. The data include tube-fed patients whose nutrition, blood glucose, administered insulins and medications were extracted by hand due to their complexity and to ensure accuracy. The model was estimated using an individual's data as if they arrived in real-time, and the estimated model was run forward producing a forecast. Both constrained and unconstrained ensemble Kalman filters were estimated to compare the impact of constraints. Constraint boundaries, model parameter sets estimated, and data used to estimate the models were varied to investigate their influence on forecasting accuracy. Forecasting accuracy was evaluated according to mean squared error between the model-forecasted glucose and the measurements and by comparing distributions of measured glucose and forecast ensemble means.

RESULTS

The novel CEnKF produced substantial gains in robustness and accuracy while minimizing the data requirements compared to the unconstrained ensemble Kalman filters. Administered insulin and tube-nutrition were important for accurate forecasting, but including glucose in IV medication delivery did not increase forecast accuracy. Model flexibility, controlled by constraint boundaries and estimated parameters, did influence forecasting accuracy.

CONCLUSION

Accurate and robust physiological forecasting with sparse clinical data is possible with DA. Introducing constrained inference, particularly on unmeasured states and parameters, reduced forecast error and data requirements. The results are not particularly sensitive to model flexibility such as constraint boundaries, but over or under constraining increased forecasting errors.

Implementation of Continuous Glucose Monitoring in Critical Care: A Scoping Review

PURPOSE OF REVIEW

The aim of this review is to identify the implementation approaches, strategies, and outcomes for continuous glucose monitoring (CGM) in the intensive care unit (ICU). Medline and Web of Science databases were searched to report relevant literature published between September 12, 2016 and September 12, 2021. Implementation outcomes and strategies, defined by the Expert Recommendations for Implementing Change (ERIC) project, were extracted.

RECENT FINDINGS

Of the 324 titles reviewed, 16 articles were included in the review. While no studies were identified as implementation research, 14 of 16 identified implementation strategies that aligned with ERIC definitions. Included studies described a multi-disciplinary approach. Clinical outcomes included Mean Absolute Relative Difference (MARD), ranging from 7.5 to 15.3%, and 33-71% reduction in frequency of point-of-care (POC) blood glucose monitoring (BGM) using hybrid protocols. This scoping review provides valuable insight into the process of CGM implementation in the ICU. Continued research should include implementation outcomes to inform widespread utilization.

What, why and how to monitor blood glucose in critically ill patients

Critically ill patients are prone to high glycemic variations irrespective of their diabetes status. This mandates frequent blood glucose (BG) monitoring and regulation of insulin therapy. Even though the most commonly employed capillary BG monitoring is convenient and rapid, it is inaccurate and prone to high bias, overestimating BG levels in critically ill patients. The targets for BG levels have also varied in the past few years ranging from tight glucose control to a more liberal approach. Each of these has its own fallacies, while tight control increases risk of hypoglycemia, liberal BG targets make the patients prone to hyperglycemia. Moreover, the recent evidence suggests that BG indices, such as glycemic variability and time in target range, may also affect patient outcomes. In this review, we highlight the nuances associated with BG monitoring, including the various indices required to be monitored, BG targets and recent advances in BG monitoring in critically ill patients.

Continuous Glucose Monitoring in the Intensive Care Unit

Traditionally, the care of critically ill patients with diabetes or stress hyperglycemia in the intensive care unit (ICU) demands the use of continuous intravenous insulin (CII) therapy to achieve narrow glycemic targets. To reduce the risk of iatrogenic hypoglycemia and to achieve glycemic targets during CII, healthcare providers (HCP) rely on hourly point-of-care (POC) arterial or capillary glucose tests obtained with glucose monitors. The burden of this approach, however, was evident during the beginning of the pandemic when the immediate reduction in close contact interactions between HCP and patients with COVID-19 was necessary to avoid potentially life-threatening exposures. Taking advantage of the advancements in current diabetes technologies, including continuous glucose monitoring (CGM) devices integrated with digital health tools for remote monitoring, HCP implemented novel protocols in the ICU to care for patients with COVID-19 and hyperglycemia. We provide an overview of research conducted in the ICU setting with the use of initial CGM technology to current devices and summarize our recent experience in the ICU.

Nursing Perspectives on the Use of Continuous Glucose Monitoring in the Intensive Care Unit

BACKGROUND

The COVID-19 pandemic necessitated rapid implementation of continuous glucose monitoring (CGM) in the intensive care unit (ICU). Although rarely reported, perceptions from nursing staff who used the systems are critical for successful implementation and future expanded use of CGM in the inpatient setting.

METHODS

A 22-item survey focused on CGM use was distributed to ICU nurses at two large academic medical centers in the United States in 2022. Both institutions initiated inpatient CGM in the spring of 2020 using the same CGM+point of care (POC) hybrid protocol. The survey employed a 1- to 5-point Likert scale regarding CGM sensor insertion, accuracy, acceptability, usability, training, and perceptions on workload.

RESULTS

Of the 71 surveys completed, 68 (96%) nurses reported they cared for an ICU patient on CGM and 53% reported they had independently performed CGM sensor insertion. The ICU nurses overwhelmingly reported that CGM was accurate, reduced their workload, provided safer patient care, and was preferred over POC glucose testing alone. Interestingly, nearly half of nurses (49%) reported that they considered trend arrows in dosing decisions although trends were not included in the CGM+POC hybrid protocol. Nurses received training through multiple modalities, with the majority (80%) of nurses reporting that CGM training was sufficient and prepared them for its use.

CONCLUSION

These results confirm nursing acceptance and preference for CGM use within a hybrid glucose monitoring protocol in the ICU setting. These data lay a blueprint for successful implementation and training strategies for future widespread use.

Current management of diabetes patients with COVID-19

INTRODUCTION

Diabetes mellitus (DM) and the 2019 coronavirus (COVID-19) appear to interact in both directions. There is mounting proof that patients with DM have a worse COVID-19 prognosis than those without it. Pharmacotherapy is also known to affect in view of the possible interplay between drugs and the pathophysiology of the above conditions in a given patient.

AREAS COVERED

In this review, we discuss the pathogenesis of COVID-19 and its connections with diabetes mellitus. We also analyze the treatment modalities for COVID-19 and diabetes patients. The possible mechanisms of the different medications and their management limitations are also systematically reviewed.

EXPERT OPINION

COVID-19 management as well as its knowledge base is changing constantly. The Pharmacotherapy and the choice of drugs also need to be specifically considered in view of the concomitant presence of these conditions in a patient. Anti-diabetic agents must be carefully evaluated in diabetic patients in view of the disease's severity, blood glucose level, appropriate treatment, and other components that could aggravate adverse events. A methodical technique is anticipated to enable the safe and rational use of drug therapy in COVID-19-positive diabetic patients to take.

Current management of diabetes patients with COVID-19

INTRODUCTION

Diabetes mellitus (DM) and the 2019 coronavirus (COVID-19) appear to interact in both directions. There is mounting proof that patients with DM have a worse COVID-19 prognosis than those without it. Pharmacotherapy is also known to affect in view of the possible interplay between drugs and the pathophysiology of the above conditions in a given patient.

AREAS COVERED

In this review, we discuss the pathogenesis of COVID-19 and its connections with diabetes mellitus. We also analyze the treatment modalities for COVID-19 and diabetes patients. The possible mechanisms of the different medications and their management limitations are also systematically reviewed.

EXPERT OPINION

COVID-19 management as well as its knowledge base is changing constantly. The Pharmacotherapy and the choice of drugs also need to be specifically considered in view of the concomitant presence of these conditions in a patient. Anti-diabetic agents must be carefully evaluated in diabetic patients in view of the disease's severity, blood glucose level, appropriate treatment, and other components that could aggravate adverse events. A methodical technique is anticipated to enable the safe and rational use of drug therapy in COVID-19-positive diabetic patients to take.

7. Diabetes Technology: Standards of Care in Diabetes-2023

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Supporting the Use of a Person's Own Diabetes Technology in the Inpatient Setting

The use of diabetes technology, including insulin pumps, continuous glucose monitoring devices, and automated insulin delivery systems, has increased significantly in recent years. As more people with diabetes adopt technology in the outpatient setting, we are seeing these devices more frequently in the inpatient setting. This review offers best-practice guidelines for the continuation of personal diabetes technology use in the inpatient setting. It describes policy and guideline stipulations, roles and responsibilities, and device- and brand-specific considerations. Although these devices are not approved for inpatient use by the U.S. Food and Drug Administration, there is general expert consensus that the continuation of personal diabetes devices during hospitalization is appropriate for patients who have sufficient knowledge, are not critically ill, and retain sufficient mental capacity during an acute illness. Health care systems and inpatient providers need to understand the benefits and limitations of personal diabetes technology use during hospitalization.

The Devil Is in the Details: Use, Limitations, and Implementation of Continuous Glucose Monitoring in the Inpatient Setting

Until recently, continuous glucose monitoring (CGM) systems were reserved for use in the outpatient setting or for investigational purposes in hospitalized patients. However, during the coronavirus disease 2019 pandemic, use of CGM in the inpatient setting has grown rapidly. This review outlines important details related to the accuracy, limitations, and implementation of, as well as necessary staff education for, inpatient CGM use and offers a glimpse into the future of CGM in the inpatient setting.

Glucocorticoid-Induced Hyperglycemia Including Dexamethasone-Associated Hyperglycemia in COVID-19 Infection: A Systematic Review

OBJECTIVE

Optimal glucocorticoid-induced hyperglycemia (GCIH) management is unclear. The COVID-19 pandemic has made this issue more prominent because dexamethasone became the standard of care in patients needing respiratory support. This systematic review aimed to describe the management of GCIH and summarize available management strategies for dexamethasone-associated hyperglycemia in patients with COVID-19.

METHODS

A systematic review was conducted using the PubMed/MEDLINE, Cochrane Library, Embase, and Web of Science databases with results from 2011 through January 2022. Keywords included synonyms for "steroid-induced diabetes" or "steroid-induced hyperglycemia." Randomized controlled trials (RCTs) were included for review of GCIH management. All studies focusing on dexamethasone-associated hyperglycemia in COVID-19 were included regardless of study quality.

RESULTS

Initial search for non-COVID GCIH identified 1230 references. After screening and review, 33 articles were included in the non-COVID section of this systematic review. Initial search for COVID-19-related management of dexamethasone-associated hyperglycemia in COVID-19 identified 63 references, whereas 7 of these were included in the COVID-19 section. RCTs of management strategies were scarce, did not use standard definitions for hyperglycemia, evaluated a variety of treatment strategies with varying primary end points, and were generally not found to be effective except for Neutral Protamine Hagedorn insulin added to basal-bolus regimens.

CONCLUSION

Few RCTs are available evaluating GCIH management. Further studies are needed to support the formulation of clinical guidelines for GCIH especially given the widespread use of dexamethasone during the COVID-19 pandemic.

American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update

OBJECTIVE

The objective of this clinical practice guideline is to provide updated and new evidence-based recommendations for the comprehensive care of persons with diabetes mellitus to clinicians, diabetes-care teams, other health care professionals and stakeholders, and individuals with diabetes and their caregivers.

METHODS

The American Association of Clinical Endocrinology selected a task force of medical experts and staff who updated and assessed clinical questions and recommendations from the prior 2015 version of this guideline and conducted literature searches for relevant scientific papers published from January 1, 2015, through May 15, 2022. Selected studies from results of literature searches composed the evidence base to update 2015 recommendations as well as to develop new recommendations based on review of clinical evidence, current practice, expertise, and consensus, according to established American Association of Clinical Endocrinology protocol for guideline development.

RESULTS

This guideline includes 170 updated and new evidence-based clinical practice recommendations for the comprehensive care of persons with diabetes. Recommendations are divided into four sections: (1) screening, diagnosis, glycemic targets, and glycemic monitoring; (2) comorbidities and complications, including obesity and management with lifestyle, nutrition, and bariatric surgery, hypertension, dyslipidemia, retinopathy, neuropathy, diabetic kidney disease, and cardiovascular disease; (3) management of prediabetes, type 2 diabetes with antihyperglycemic pharmacotherapy and glycemic targets, type 1 diabetes with insulin therapy, hypoglycemia, hospitalized persons, and women with diabetes in pregnancy; (4) education and new topics regarding diabetes and infertility, nutritional supplements, secondary diabetes, social determinants of health, and virtual care, as well as updated recommendations on cancer risk, nonpharmacologic components of pediatric care plans, depression, education and team approach, occupational risk, role of sleep medicine, and vaccinations in persons with diabetes.

CONCLUSIONS

This updated clinical practice guideline provides evidence-based recommendations to assist with person-centered, team-based clinical decision-making to improve the care of persons with diabetes mellitus.

Endocrine and metabolic complications of COVID-19: lessons learned and future prospects

Coronavirus disease 2019 (COVID-19) is well known for its respiratory complications; however, it can also cause extrapulmonary manifestations, including cardiovascular, thrombotic, renal, gastrointestinal, neurologic, and endocrinological symptoms. Endocrinological complications of COVID-19 are rare but can considerably impact the outcome of the patients. Moreover, preexisting endocrinologic disorders can affect the severity of COVID-19. Thyroid, pancreas, adrenal, neuroendocrine, gonadal, and parathyroid glands are the main endocrinologic organs that can be targeted by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Endocrinological complications of COVID-19 are rare but can significantly deteriorate the patients' prognosis. Understanding the interaction between COVID-19 and the endocrine system can provide a potential treatment option to improve the outcome of COVID-19. In this article, we aim to review the short-term and long-term organ-based endocrinological complications of COVID-19, the pathophysiology, the influence of each complication on COVID-19 prognosis, and potential therapeutic interventions based on current published data. Moreover, current clinical trials of potential endocrinological interventions to develop therapeutic strategies for COVID-19 have been discussed.

CGM in the Hospital: Is It Ready for Prime Time?

PURPOSE OF REVIEW

The use of continuous glucose monitoring (CGM) in the hospital setting is growing with more patients using these devices at home and when admitted to the hospital, especially during the COVID-19 pandemic.

RECENT FINDINGS

Historically, most evidence for CGM use in the inpatient setting was limited to small studies utilizing outdated CGM technology and analyzing accuracy of sensor measurements. Previous studies have shown reduced sensor accuracy during extreme hypo- or hyperglycemia, rapid fluctuations of glucose, compression of the sensor itself, and in those who are critically ill. Studies that are more recent have shown CGM to have adequate accuracy and may be effective in reducing hypoglycemia in hospitalized patients; some studies have also showed improvement in time in target glycemic range. Furthermore, CGM may reduce nursing workload, cost of inpatient care, and use of personal protective equipment and face-to-face patient care especially for patients during the COVID-19 pandemic. This review will describe the evidence for use of CGM in hospitalized critically ill or non-critically ill patients, address accuracy and safety considerations, and outline paths for future implementation.

Hospital Diabetes Meeting 2022

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.

Type 2 Diabetes Mellitus and COVID-19: A Narrative Review

Type-2 diabetes mellitus (T2DM) is a chronic metabolic disorder. The incidence and prevalence of patients with T2DM are increasing worldwide, even reaching epidemic values in most high- and middle-income countries. T2DM could be a risk factor of developing complications in other diseases. Indeed, some studies suggest a bidirectional interaction between T2DM and COVID-19. A growing body of evidence shows that COVID-19 prognosis in individuals with T2DM is worse compared with those without. Moreover, various studies have reported the emergence of newly diagnosed patients with T2DM after SARS-CoV-2 infection. The most common treatments for T2DM may influence SARS-CoV-2 and their implication in infection is briefly discussed in this review. A better understanding of the link between TD2M and COVID-19 could proactively identify risk factors and, as a result, develop strategies to improve the prognosis for these patients.

Monitoring of paediatric type 1 diabetes

PURPOSE OF REVIEW

This article reviews recent developments in methods used to monitor paediatric type 1 diabetes (T1D), including an examination of the role of glycated haemoglobin (haemoglobin A1c) and its limitations for long-term assessment of glycaemia in individual patients, self-monitoring of blood glucose, continuous glucose monitoring (CGM) systems and ketone monitoring.

RECENT FINDINGS

Monitoring of glycemia and ketones, when indicated, is a cornerstone of paediatric T1D management and is essential to optimize glycaemic control. Ongoing technological advancements have led to rapid changes and considerable improvement in the methods used to monitor glucose concentrations in people with T1D. As a result of recent innovations that have enhanced accuracy and usability, CGM is now considered the optimal method for monitoring glucose concentrations and should be introduced soon after diagnosis of T1D.

SUMMARY

Patients/families and healthcare providers must receive comprehensive education and proper training in the use of CGM and interpretation of the vast amounts of data. Future challenges include ensuring equal access to and optimizing clinical use of CGM to further improve T1D care and outcomes.

Subcutaneous continuous glucose monitoring in critically ill patients during insulin therapy: a meta-analysis

BACKGROUND

Using continuous glucose monitoring (CGM) in critically ill adult patients requiring insulin therapy has increased with inconsistent results. Thus, we conducted a meta-analysis to assess the effect of CGM and frequent point-of-care (POC) measurements in such a patient population.

METHODS

We searched PubMed, Embase, Cochrane Library, China national knowledge infrastructure, and Wanfang for relevant articles from inception to Jan 15, 2022. Randomized controlled trials (RCTs) were considered if they focused on critically ill patients who required insulin and were treated with CGM or any POC measurements. We used the Cochrane risk evaluating tool to assess study quality. Subgroup analysis and publication bias were also conducted.

RESULTS

We finally included 19 RCTs with 1,852 participants. The quality of the included studies were at a low to moderate levels. Overall, CGM devices significantly reduced hypoglycemia incidence (Risk ratio (RR) 0.35; 95% CI, 0.25-0.49; P<0.00001) than the POC measurement. Further subgroup and sensitivity analyses confirmed this result. The CGM group also had lower overall mortality (RR 0.54; 95% CI, 0.34-0.86; P=0.01), lower glucose variability, and nosocomial infection. The time in, below, or above target blood glucose range, insulin use, and length of stay in the ICU were comparable between the two groups. In addition, few studies provided data in favor of decreased nursing workload and medical costs in the CGM group.

CONCLUSIONS

The CGM technique could significantly reduce hypoglycemia incidence, overall mortality, and glucose variability compared to POC measurement in critically ill patients. However, further large, well-designed RCTs are required to confirm our results.

The Launch of the iCoDE Standard Project

INTRODUCTION

The first meeting of the Integration of Continuous Glucose Monitor Data into the Electronic Health Record (iCoDE) project, organized by Diabetes Technology Society, took place virtually on January 27, 2022.

METHODS

Clinicians, government officials, data aggregators, attorneys, and standards experts spoke in panels and breakout groups. Three themes were covered: 1) why digital health data integration into the electronic health record (EHR) is needed, 2) what integrated continuously monitored glucose data will look like, and 3) how this process can be achieved in a way that will satisfy clinicians, healthcare organizations, and regulatory experts.

RESULTS

The meeting themes were addressed within eight sessions: 1) What Do Inpatient Clinicians Want to See With Integration of CGM Data into the EHR?, 2) What Do Outpatient Clinicians Want to See With Integration of CGM Data into the EHR?, 3) Why Are Data Standards and Guidances Useful?, 4) What Value Can Data Integration Services Add?, 5) What Are Examples of Successful Integration?, 6) Which Privacy, Security, and Regulatory Issues Must Be Addressed to Integrate CGM Data into the EHR?, 7) Breakout Group Discussions, and 8) Presentation of Breakout Group Ideas.

CONCLUSIONS

Creation of data standards and workflow guidance are necessary components of the Integration of Continuous Glucose Monitor Data into the Electronic Health Record (iCoDE) standard project. This meeting, which launched iCoDE, will be followed by a set of working group meetings intended to create the needed standard.

Impact of newly diagnosed diabetes on coronavirus disease 2019 severity and hyperglycemia

AIMS/INTRODUCTION

Diabetes is associated with poor clinical outcomes of coronavirus disease 2019 (COVID-19). However, the impact of newly diagnosed diabetes on prognosis has not been clarified. The objective of this study was to show the features and outcome of COVID-19 patients with newly diagnosed diabetes in Japan.

MATERIALS AND METHODS

We retrospectively analyzed 62 patients with diabetes hospitalized for COVID-19 between 1 April and 18 August 2021 at the National Center for Global Health and Medicine in Tokyo, Japan. We evaluated the worst severity of COVID-19 and plasma blood glucose levels in patients with newly diagnosed diabetes or pre-existing diabetes.

RESULTS

This study included 62 confirmed COVID-19 patients with diabetes, including 19 (30.6%) patients with newly diagnosed diabetes and 43 (69.4%) patients with pre-existing diabetes. Patients with newly diagnosed diabetes significantly progressed to a critical condition more frequently during hospitalization than patients with pre-existing diabetes (52.6% vs 20.9%, P = 0.018). In addition, patients with newly diagnosed diabetes had significantly higher average plasma blood glucose levels for the first 3 days after admission than those with pre-existing diabetes.

CONCLUSIONS

Our study suggests that the proportion of COVID-19 patients who are newly diagnosed with diabetes is high, and they have an increased risk of developing severe disease than those with pre-existing diabetes. It might be advisable that at the point of COVID-19 diagnosis, blood glucose and glycated hemoglobin levels be assessed in all patients.

A continuous intravenous insulin infusion protocol to manage high-dose methylprednisolone-induced hyperglycemia in patients with severe COVID-19

Background

Many patients with severe COVID-19 have impaired glucose tolerance, and steroid therapy is a standard treatment. Thus, good glycemic control is important and correlates with better patient outcomes. We began using a continuous intravenous insulin infusion protocol for glycemic control whose infusion rate changes based on the currently measured value and previous value. This study aimed to evaluate this protocol for COVID-19 patients requiring mechanical ventilation.

Methods

This single-center, retrospective, case control study was conducted on all adult patients who required mechanical ventilation for severe COVID-19 pneumonia admitted to our critical care center from April 1, 2020 through June 20, 2021. Blood glucose levels were measured in all patients every 4 h after admission. We started using the insulin infusion protocol from August 1, 2020. Patients before starting the protocol comprised the non-protocol group and those after starting the protocol comprised the protocol group. Blood glucose levels and hypo- or hyperglycemia events were compared between groups. We also surveyed ICU nurses about their experience using the protocol.

Results

During the study period, 173 patients with COVID-19 were admitted. After 15 patients were excluded for several reasons, the study included 158 patients: non-protocol group (n = 14) and protocol group (n = 144). In the initial phase (days 1–2), blood glucose levels of the protocol group were higher compared with the non-protocol group, and as the number of measurements increased, blood glucose levels were gradually brought under control within the target range in the protocol group. Almost no hypoglycemic events (blood glucose < 80 mg/dL) were detected in either group. The rate of hyperglycemia (blood glucose > 300 mg/dL) was about 5–10% in the initial phase in the protocol group and about 10–15% in the early phase (days 3–4) in the non-protocol group. The questionnaire survey revealed that 80% of ICU nurses responded favorably.

Conclusions

This insulin protocol gradually brought the blood glucose level within target levels in severe COVID-19 patients treated with high-dose steroid. Some hyperglycemia events were detected despite patients being under the protocol in the initial phase, and thus, minor modifications of the protocol might be required in the initial phase.

Effect of Hyperglycemia on COVID-19 Outcomes: Vaccination Efficacy, Disease Severity, and Molecular Mechanisms

Background/Aims: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive-stranded single-stranded RNA virus, a member of the subgenus Sarbecovirus (beta-CoV lineage B) and responsible for the coronavirus disease 2019 (COVID-19). COVID-19 encompasses a large range of disease severity, from mild symptoms to severe forms with Intensive Care Unit admission and eventually death. The severe forms of COVID-19 are usually observed in high-risk patients, such as those with type two diabetes mellitus. Here, we review the available evidence linking acute and chronic hyperglycemia to COVID-19 outcomes, describing also the putative mediators of such interactions. Findings/Conclusions: Acute hyperglycemia at hospital admission represents a risk factor for poor COVID-19 prognosis in patients with and without diabetes. Acute and chronic glycemic control are both emerging as major determinants of vaccination efficacy, disease severity and mortality rate in COVID-19 patients. Mechanistically, it has been proposed that hyperglycemia might be a disease-modifier for COVID-19 through multiple mechanisms: (a) induction of glycation and oligomerization of ACE2, the main receptor of SARS-CoV-2; (b) increased expression of the serine protease TMPRSS2, responsible for S protein priming; (c) impairment of the function of innate and adaptive immunity despite the induction of higher pro-inflammatory responses, both local and systemic. Consistently, managing acute hyperglycemia through insulin infusion has been suggested to improve clinical outcomes, while implementing chronic glycemic control positively affects immune response following vaccination. Although more research is warranted to better disentangle the relationship between hyperglycemia and COVID-19, it might be worth considering glycemic control as a potential route to optimize disease prevention and management.