Early Intervention for Diabetes in Medical and Surgical Inpatients Decreases Hyperglycemia and Hospital-Acquired Infections: A Cluster Randomized Trial

Hyperglycemia in Hospital: An Independent Marker of Infection, Acute Kidney Injury, and Stroke for Hospital Inpatients

CONTEXT

Hyperglycemia in hospital inpatients without pre-existing diabetes is associated with increased mortality. However, the independent contribution of hyperglycemia to health care-associated infection (HAI), acute kidney injury (AKI), and stroke is unclear.

OBJECTIVE

To investigate the relationship between hyperglycemia and adverse clinical outcomes in hospital for patients with and without diabetes.

METHODS

Diabetes IN-hospital: Glucose and Outcomes (DINGO) was a 26-week (October 2019-March 2020) prospective cohort study. Clinical and glucose data were collected up to the 14th day of admission. Primary stratification was by hyperglycemia, defined as ≥2 random capillary blood glucose (BG) measurements ≥11.1 mmol/L (≥200 mg/dL). Propensity weighting for 9 clinical characteristics was performed to allow interrogation of causality. To maintain the positivity assumption, patients with HbA1c >12.0% were excluded and prehospital treatment not adjusted for. The setting was the Royal Melbourne Hospital, a quaternary referral hospital in Melbourne, Australia. Admissions with at least 2 capillary glucose values and length of stay >24 hours were eligible, with half randomly sampled. Outcome measures were HAI, AKI, stroke, and mortality.

RESULTS

Of 2558 included admissions, 1147 (45%) experienced hyperglycemia in hospital. Following propensity-weighting and adjustment, hyperglycemia in hospital was found to, independently of 9 covariables, contribute an increased risk of in-hospital HAI (130 [11.3%] vs 100 [7.1%], adjusted odds ratio [aOR] 1.03, 95% CI 1.01-1.05, P = .003), AKI (120 [10.5%] vs 59 [4.2%], aOR 1.07, 95% CI 1.05-1.09, P < .001), and stroke (10 [0.9%] vs 1 [0.1%], aOR 1.05, 95% CI 1.04-1.06, P < .001).

CONCLUSION

In hospital inpatients (HbA1c ≤12.0%), irrespective of diabetes status and prehospital glycemia, hyperglycemia increases the risk of in-hospital HAI, AKI, and stroke compared with those not experiencing hyperglycemia.

Are we Ready for Real-Time Continuous Glucose Monitoring in the Hospital Setting? Benefits, Challenges, and Practical Approaches for Implementation : Case Vignette: Remote Real-Time Continuous Glucose Monitoring for Hospitalized Care in Quincy Koala

PURPOSE OF REVIEW

While preliminary evidence for use of real-time continuous glucose monitoring (rtCGM) in the hospital setting is encouraging, challenges with currently available devices and technology will need to be overcome as part of real-world integration. This paper reviews the current evidence and guidelines regarding use of rtCGM in the hospital and suggests a practical approach to implementation.

RECENT FINDINGS

There is now a considerable body of real-world evidence on the benefits of reducing dysglycemia in the hospital using both traditional point-of-care (POC) glucose testing and rtCGM. Benefits of rtCGM include decreased frequency of hypo- and hyperglycemia with reduced need of frequent POC checks and it is both feasible and well-accepted by nursing staff and providers. If expansion to additional sites is to be considered, practical solutions will need to be offered. Recommendations for an operational workflow and tools are described to guide implementation in the non-ICU setting. Further testing in randomized controlled trials and real-world dissemination and implementation designs is needed, together with industry and technology collaborations, to further streamline the integration into health systems.

SMART DIABETES HOSPITAL: CLINICAL IMPACT IN COMPLEX SURGICAL UNITS OF A TERTIARY HOSPITAL

AIM

To evaluate the impact of a proactive action of a specialized diabetes team (SDT) on different health outcomes in patients hospitalized in high complexity surgery units, including solid organ transplant surgical units, of a tertiary hospital.

METHODS

Nested case control study matched (1:1) by age and gender. The control group consisted of patients (n = 120) who were under the standard of care diabetes management admitted three months' prior the cases. The cases were admitted in the same surgical units (n = 120) and were treated in the setting of the so called "Smart Diabetes Hospital" (SDH) consisting in a SDT that prioritized their actions through a digital map showing blood glucose levels obtained during the previous 24 h.

RESULTS

SDH implementation resulted in a significant reduction in both blood glucose levels (mean 162.1 ± SD 44.4 vs. mean 145.5 ± SD 48.0; p = 0.008) and hypoglycaemic episodes (19.7% vs. 8.4%: p = 0.002). Furthermore, a reduction of 3 days in the length of stay (LOS) was observed (15.6 ± 10.3 vs. 12.4 ± 6.0), which represents a significant cost-saving. Moreover, more new cases of diabetes were detected during the SDT period (2.5% vs. 6.7%, p = 0.04).

CONCLUSION

SDH is effective in diabetes management and reduce LOS in complex surgical units.

Glucose levels at hospital admission are associated with 5 year mortality

AIM

We aimed to determine if hospital admission hyperglycaemia and hypoglycaemia are associated with increased long-term mortality.

METHODS

A post-hoc analysis of data from a trial of glucose screening in the emergency department was conducted. Data were linked with a death registry up to 5 years after admission. The relationship between admission glucose and mortality was examined by cox regression. Further analyses of people who survived the admission and subsequent 28 days was performed.

RESULTS

There were 131,322 patients, of whom 38,712 (29.5 %) died. Mean follow-up was 3·3 ± 1·5 years. Compared to the reference glucose band of 6·1-8·0 mmol/L, there was increased mortality in higher bands, reaching a hazard ratio (HR) of 1·44 (95 %CI 1·34-1·55, p < 0·001) for people with glucose > 20·0 mmol/L. The HR was 1·56 (95 %CI 1·46-1·68, p < 0·001) for people with glucose ≤ 4·0 mmol/L. Similar relationships were observed among 28-day survivors. The relationships were attenuated among people with known diabetes. Among 4867 subjects with glucose ≥ 14·0 mmol/L, those diagnosed with diabetes during the admission had lower mortality compared to subjects where the diagnosis was not made (HR 0·53, 95 %CI 0·40-0·72, p < 0·001). This was attenuated among 28-day survivors.

CONCLUSION

Hyperglycaemia and hypoglycaemia on hospital admission are associated with increased long-term mortality.

Economic burden attributable to hospital-acquired infections among tumor patients from a large regional cancer center in Southern China

BACKGROUND

To evaluate the economic loss of hospital-acquired infections (HAIs) among tumor patients so as to help policymakers to allocate health care resources and address the issue.

METHODS

We conducted a retrospective, 1:1 matched case-control study in a large region cancer hospital between January 1 and December 31, 2022. The economic burden was estimated as the median of the 1:1 pair differences of various hospitalization fees and hospital length of stay (LOS).

RESULTS

In this study of 329 matched pairs, the patients with HAIs incurred higher hospitalization cost (ie, $16,927) and experienced longer hospital LOS (ie, 22 days), compared to the non-HAI groups. The extra hospitalization cost and the prolonged hospital LOS caused by HAIs were $4,919 and 9 days, respectively. Accordingly, the direct nonmedical economic loss attributable to HAI was approximately $478 to 835 per case. Furthermore, the increment of hospitalization costs varied by sites of infection, types of tumors, and stratum of age.

CONCLUSIONS

HAIs lead to the increment of direct economic burden and hospital LOS in tumor patients. Our findings highlight the importance of implementing effective infection control measures in hospitals to reduce the financial burden on tumor patients.

Glycaemic outcomes in hospital with IDegAsp versus BIAsp30 premixed insulins

BACKGROUND AND AIMS

IDegAsp (Ryzodeg 70/30), a unique premixed formulation of long-acting insulin degludec and rapid-acting insulin aspart, is increasing in use. Management of IDegAsp during hospitalisation is challenging because of degludec's ultra-long duration of action. We investigated inpatient glycaemia in patients treated with IDegAsp compared to biphasic insulin aspart (BIAsp30; Novomix30).

METHODS

We performed a retrospective observational study at two hospitals assessing inpatients with type 2 diabetes treated with IDegAsp or BIAsp30 prior to and during hospital admission. Standard inpatient glycaemic outcomes were analysed based on capillary blood glucose (BG) measurements.

RESULTS

We assessed 88 individuals treated with IDegAsp and 88 HbA1c-matched individuals treated with BIAsp30. Patient characteristics, including insulin dose at admission, were well matched, but the IDegAsp group had less frequent twice-daily insulin dosing than the BIAsp30 group (49% vs 87%, P < 0.001). Patient-days with BG <4 mmol/L were not different (10.6% vs 9.9%, P = 0.7); however, the IDegAsp group had a higher patient-day mean BG (10.4 (SD 3.4) vs 10.0 (3.4) mmol/L, P < 0.001), and more patient-days with mean BG >10 mmol/L (48% vs 38%, P < 0.001) compared to the BIAsp30 group. Glucose was higher in the IDegAsp group in the evening (4 PM to midnight) (11.6 (SD 4.0) vs 10.9 (4.6) mmol/L, P = 0.004), but not different at other times during the day.

CONCLUSIONS

Inpatients treated with IDegAsp compared to BIAsp30 had similar hypoglycaemia incidence, but higher hyperglycaemia incidence, potentially related to less frequent twice-daily dosing. With the increasing use of IDegAsp in the community, development of hospital management guidelines for this insulin formulation is needed.

Continuous Glucose Monitoring of Steroid-Induced Hyperglycemia in Patients With Dermatologic Diseases

BACKGROUND AND OBJECTIVES

Systemic administration of glucocorticoids is a mainstay therapy for various inflammatory diseases and may lead to hyperglycemia, which carries the risk of worsening preexisting diabetes and triggering steroid-induced diabetes. Therefore, we aimed to identify patients at risk and to quantify severity of steroid-induced hyperglycemia (SIH) by continuous glucose monitoring (CGM) in hospitalized patients needing systemic glucocorticoid treatment.

PATIENTS AND METHODS

This prospective study included 51 steroid-naive, dermatological patients requiring systemic high-dose glucocorticoid treatment at the Department of Dermatology of the University Hospital Essen. After careful diabetes-specific assessment at admission, glucose monitoring was performed using a CGM system and glucose profile was analyzed in patients with and without SIH.

RESULTS

SIH occurred in 47.1% of all treated patients, and a relevant part of patients with initial normoglycemia developed SIH (2/10 patients). Doubling of SIH incidence was observed with each severity grade of dysglycemia (4/10 in prediabetes; 9/10 in diabetes). Patients with SIH spend nearly 6 hours daily above targeted glucose range, and severe hyperglycemia was observed for 1.2 hours/day.

CONCLUSIONS

Our study underlines the need for dedicated glucose monitoring in dermatologic patients on systemic glucocorticoid therapy by demonstrating its impact on glucose metabolism.

Proactive review for people with diabetes in hospital: a cluster randomised feasibility trial with process evaluation, protocol V3.1

BACKGROUND

Diabetes inpatient specialist services vary across the country, with limited evidence to guide service delivery. Currently, referrals to diabetes inpatient specialists are usually 'reactive' after diabetes-related events have taken place, which are associated with an increased risk of morbidity/mortality and increased length of hospital stay. We propose that a proactive diabetes review model of care, delivered by diabetes inpatient specialist nurses, may contribute to the prevention of such diabetes-related events and result in a reduction in the risk of harm.

METHOD

We will conduct a cluster randomised feasibility study with process evaluation. The proactive diabetes review model (PDRM) is a complex intervention that focuses on the prevention of potentially modifiable diabetes-related harms. All eligible patients will receive a comprehensive, structured diabetes review that aims to identify and prevent potentially modifiable diabetes-related harms through utilising a standardised review structure. Reviews are undertaken by a diabetes inpatient specialist nurse within one working day of admission. This differs from usual care where patients are often only seen after diabetes-related harms have taken place. The trial duration will be approximately 32 weeks, with intervention delivery throughout. There will be an initial 8-week run-in phase, followed by a 24-week data collection phase. Eight wards will be equally randomised to either PDRM or usual care. Adult patients with a known diagnosis of diabetes admitted to an included ward will be eligible. Data collection will be limited to that typically collected as part of usual care. Data collected will include descriptive data at both the ward and patient level and glucose measures, such as frequency and results of capillary glucose testing, ketonaemia and hypoglycaemic events. The analysis aims to determine the fidelity and acceptability of the intervention and the feasibility of a future definitive trial. Whilst this study is primarily about trial feasibility, the findings of the process evaluation may lead to changes to both trial processes and modifications to the intervention. A qualitative process evaluation will be conducted in parallel to the trial. A minimum of 22 patients, nurses, doctors, and managers will be recruited with methods including direct non-participant observation and semi-structured interviews. The feasibility of a future definitive trial will be assessed by evaluating recruitment and randomisation processes, staffing resources and quality of available data.

DISCUSSION

The aim of this cluster randomised feasibility trial with a process evaluation is to explore the feasibility of a definitive trial and identify appropriate outcome measures. If a trial is feasible and the effectiveness of PDRM can be evaluated, this could inform the future development of inpatient diabetes services nationally.

TRIAL REGISTRATION

UK Clinical Research Network, 51,167. ISRCTN, ISRCTN70402110. Registered on 21 February 2022.

The Specialist Treatment of Inpatients: Caring for Diabetes in Surgery (STOIC-D Surgery) Trial: A Randomized Controlled Trial of Early Intervention With an Electronic Specialist-Led Model of Diabetes Care

OBJECTIVE

To investigate the effect of early intervention with an electronic specialist-led "proactive" model of care on glycemic and clinical outcomes.

RESEARCH DESIGN AND METHODS

The Specialist Treatment of Inpatients: Caring for Diabetes in Surgery (STOIC-D Surgery) randomized controlled trial was performed at the Royal Melbourne Hospital. Eligible participants were adults admitted to a surgical ward during the study with either known diabetes or newly detected hyperglycemia (at least one random blood glucose result ≥11.1 mmol/L). Participants were randomized 1:1 to standard diabetes care or the intervention consisting of an early consult by a specialist inpatient diabetes team using electronic tools for patient identification, communication of recommendations, and therapy intensification. The primary outcome was median patient-day mean glucose (PDMG). The key secondary outcome was incidence of health care-associated infection (HAI).

RESULTS

Between 12 February 2021 and 17 December 2021, 1,371 admissions met inclusion criteria, with 680 assigned to early intervention and 691 to standard diabetes care. Baseline characteristics were similar between groups. The early intervention group achieved a lower median PDMG of 8.2 mmol/L (interquartile range [IQR] 6.9-10.0 mmol/L) compared with 8.6 mmol/L (IQR 7.2-10.3 mmol/L) in the control group for an estimated difference of -0.3 mmol/L (95% CI -0.4 to -0.2 mmol/L, P < 0.0001). The incidence of HAI was lower in the intervention group (77 [11%] vs. 110 [16%]), for an absolute risk difference of -4.6% (95% CI -8.2 to -1.0, P = 0.016).

CONCLUSIONS

In surgical inpatients, early diabetes management intervention with an electronic specialist-led diabetes model of care reduces glucose and HAI.

Longitudinal Digital Glucometric Benchmarking to Evaluate the Impact of Institutional Diabetes Care Initiatives in Adults With Diabetes Mellitus Over the 2016-2020 Period

BACKGROUND

While glucometric benchmarking has been used to compare glucose management between institutions, the value of longitudinal intra-institution benchmarking to assess quality improvement changes is not established.

METHODS

A prospective six-month observational study (October 2019-March 2020 inclusive) of inpatients with diabetes or newly detected hyperglycemia admitted to eight medical and surgical wards at the Royal Melbourne Hospital. Networked blood glucose (BG) meters were used to collect capillary BG levels. Outcomes were measures of glycemic control assessed by mean and threshold glucometric measures and comparison with published glucometric benchmarks. Intra-institution comparison was over the 2016-2020 period.

RESULTS

In all, 620 admissions (588 unique individuals) met the inclusion criteria, contributing 15 164 BG results over 4023 admission-days. Compared with the 2016 cohort from the same institution, there was increased BG testing (3.8 [SD = 2.2) vs 3.3 [SD = 1.7] BG measurements per patient-day, P < .001), lower mean patient-day mean glucose (PDMG; 8.9 mmol/L [SD = 3.2] vs 9.5 mmol/L [SD = 3.3], P < .001), and reduced mean and threshold measures of hyperglycemia (P < .001 for all). Comparison with institutions across the United States revealed lower incidence of mean PDMG >13.9 or >16.7 mmol/L, and reduced hypoglycemia (<3.9, <2.8, and <2.2 mmol/L), when compared with published benchmarks from an earlier period (2009-2014).

CONCLUSIONS

Comprehensive digital-based glucometric benchmarking confirmed institutional quality improvement changes were followed by reduced hyperglycemia and hypoglycemia in a five-year comparison. Longitudinal glucometric benchmarking enables evaluation and validation of changes to institutional diabetes care management practices.

The Canadian Hypoglycemia During Hospitalization Score Is Externally Valid in the Australian Diabetes IN-hospital: Glucose & Outcomes (DINGO) Cohort

OBJECTIVES

The Hypoglycemia During Hospitalization (HyDHo) score predicts hypoglycemia in a population of Canadian inpatients by assigning various weightings to 5 key clinical criteria known at the time of admission, in particular age, recent presentation to an emergency department, insulin use, use of oral hypoglycemic agents, and chronic kidney disease. Our aim in this study was to externally validate the HyDHo score by applying this risk calculator to an Australian population of inpatients with diabetes.

METHODS

This study was a retrospective data analysis of a subset of the Diabetes IN-hospital: Glucose & Outcomes (DINGO) cohort. The HyDHo score was applied based on clinical information known at the time of admission to stratify risk of inpatient hypoglycemia.

RESULTS

The HyDHo score was applied to 1,015 patients, generating a receiver-operating characteristic c-statistic of 0.607. A threshold of ≥9, as per the original study, generated a sensitivity of 83% and specificity of 20%. A threshold of ≥10, to better suit this Australian population, generated a sensitivity of 90% and specificity of 34%. The HyDHo score has been externally valid in a geographically different population; in fact, it outperformed the original study after accounting for local hypoglycemia rates.

CONCLUSIONS

Our findings support the external validity of the HyDHo score in a geographically different population. Application of this simple and accessible tool can serve as an adjunct to predict an inpatient's risk of hypoglycemia and guide more appropriate glucose monitoring and diabetes management.

Improving the outcomes for people with diabetes undergoing surgery: An observational study of the Improving the Peri-operative Pathway of People with Diabetes (IP3D) intervention

AIMS

We evaluated the effectiveness of an intervention to improve the care of people with diabetes undergoing surgery when implemented across multiple organisations.

METHODS

This was an observational study using routinely collected data. Eight hospitals in England implemented the Improving the Peri-operative Pathway of People with Diabetes (IP3D) intervention, with pre-implementation data collected from 1st February to 31st July 2019 and post-implementation data collection within the period 1st February to 31st October 2021. Key elements were the use of a patient empowering peri-operative passport and the employment of a peri-operative diabetes specialist nurse. The primary outcome was the change in length of stay.

RESULTS

In total 1837 patients at pre-implementation and 1164 patients at post-implementation undergoing elective surgery were included. Pre- and post-implementation 23.8 % and 33.4 % of patients had day-case surgery respectively. For in-patients median length of stay decreased from 3.2 days (inter-quartile range 1.5-6.1) pre-implementation to 2.5 days (inter-quartile range 1.4-5.4) post-implementation. There were also significant improvements in patient experience, hypo- and hyper-glycaemic events, wound complications and diabetes related complications.

CONCLUSIONS

The IP3D intervention has the potential to increase efficiency and reduce waiting lists for elective surgery on a nationwide basis.

Healthcare-associated infections in critical COVID-19 patients in Tunis: epidemiology, risk factors, and outcomes

BACKGROUND

Coronavirus disease 2019 (COVID-19) pandemic disrupted adherences to healthcare-associated infection (HAI) prevention protocols. Herein, we studied the characteristics of all HAIs occurring in critically ill COVID-19 patients.

METHODS

A retrospective, single-center cohort of critical COVID-19 patients during 2021. Microbiological samples were collected if HAI was suspected. We analyzed all factors that could potentially induce HAI, using septic shock and mortality as endpoints.

RESULTS

Sixty-four among 161 included patients (39.7%) presented a total of 117 HAIs with an incidence density of 69.2 per 1,000 hospitalization days. Compared to the prior COVID-19 period (2013-2019), the identification of HAI increased in 2021. HAIs were classified into ventilator-associated pneumonia (VAP; n=38), bloodstream infection (n=32), urinary tract infection (n=24), catheter-related infection (n=12), and fungal infection (n=11). All HAIs occurred significantly earlier in the post-COVID-19 period (VAP: 6 vs. 10 days, P=0.045, in 2017 and 2021). Acinetobacter baumannii (39.5%) and Klebsiella pneumoniae (27%) were the most commonly isolated pathogens that exhibited a multidrug-resistant (MDR) profile, observed in 89% and 64.5%, respectively. The HAI factors were laboratory abnormalities (odds ratio [OR], 6.4; 95% confidence interval [CI], 2.3-26.0), cumulative steroid dose (OR, 1.9; 95% CI, 1.3-4.0), and invasive procedures (OR, 20.7; 95% CI, 5.3-64.0). HAI was an independent factor of mortality (OR, 8.5; P=0.004).

CONCLUSIONS

During the COVID-19 era, the incidence of HAIs increased and MDR isolates remained frequent. A severe biological inflammatory syndrome, invasive devices, and elevated cumulative steroid dosages were related to HAIs. HAI was a significant death factor.

The occurrence of Hospital-Acquired Pneumonia is independently associated with elevated Stress Hyperglycaemia Ratio at admission but not elevated blood glucose

BACKGROUND

The association between stress-induced hyperglycaemia (SIH) and increased infection rates in hospitalised subjects is well-known. It is less clear if SIH at admission independently drives new-onset infections. We assessed the relationship between early exposure at admission to both the Stress Hyperglycaemia Ratio (SHR) and Blood Glucose (BG) with Hospital-Acquired Pneumonia (HAP).

METHODS

This observational retrospective study included those with length-of-stay > 1 day, BG within 24 h of admission and recent haemoglobin A1c. SIH was defined as BG ≥ 10 mmol/L, or SHR ≥ 1.1, measured at both admission and as a 24-hour maximum. Multivariable analyses were adjusted for length-of-stay, age, mechanical ventilation, and chronic respiratory disease.

RESULTS

Of 5,339 eligible subjects, 110 (2.1%) experienced HAP. Admission SHR ≥ 1.1 was independently associated with HAP (OR 3.04, 95% CI 1.98-4.68, p < 0.0001) but not BG ≥ 10 mmol/L (OR 0.65, 95% CI 0.41-1.03, p = 0.0675). The association with SHR strengthened using maximum 24-hour values (OR 3.37, 95% CI 2.05-5.52, p < 0.0001) while BG ≥ 10 mmol/L remained insignificant (OR 0.96, 95% CI 0.63-1.46, p = 0.86). Of those experiencing HAP 40 (36.4%) occurred in subjects with no recorded BG ≥ 10 mmol/L but SHR ≥ 1.1.

CONCLUSION

SIH at admission defined as SHR ≥ 1.1, but not the conventional marker of BG ≥ 10 mmol/L, was independently associated with the subsequent onset of HAP, commonly at BG < 10 mmol/L.

Decreased rates of hospital-acquired infection after introduction of an active surveillance, virtual glucose management system

Addition of an active surveillance virtual glucose management (VGM) system to usual consultation-based diabetes inpatient care at our hospital was associated with a decrease in hospital-acquired infection from 8.7% (17/196) to 3.5% (6/172) with an adjusted odds ratio of 0.17 (95%CI: 0.05-0.61), and a reduction in hypoglycemic and hyperglycemic patient-stay days.

Real-Time Continuous Glucose Monitoring in the Hospital: A Real-World Experience

BACKGROUND

Glycemic control in the hospital setting is imperative for improving outcomes among patients with diabetes. Bedside point-of-care (POC) glucose monitoring has remained the gold standard for decades, while only providing momentary glimpses into a patient's glycemic control. Continuous glucose monitoring (CGM) has been shown to improve glycemic control in the ambulatory setting. However, a paucity of inpatient experience and data remains a barrier to US Food and Drug Administration (FDA) approval and expanded/non-research use in the hospital setting.

METHOD

Amid the COVID-19 pandemic, the FDA exercised its enforcement discretion to not object to the use of CGM systems for the treatment of patients in hospital settings to support COVID-19 health care-related efforts to reduce viral exposure of health care workers. Following this announcement, Scripps Health, a large not-for-profit health care system in San Diego, California, implemented CGM as the new "standard of care" (CGM as SOC) for glucose monitoring and management in the hospital.

RESULTS

The present report serves to (1) detail the implementation procedures for employing this new SOC; (2) describe the patients receiving CGM as SOC, their glycemic control, and hospital outcomes; and (3) share lessons learned over two years and nearly 900 hospital encounters involving CGM.

CONCLUSIONS

Here, we conclude that CGM is feasible in the hospital setting by using a dedicated diabetes care team and the CGM technology with remote monitoring.

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.

Early intervention model of inpatient diabetes care improves glycemia following hospitalization

Admission to hospital provides an opportunity to optimize long-term diabetes management, but clinical inertia is common. We previously reported the randomized study of a proactive inpatient diabetes service (RAPIDS), investigating an early intervention model of care and demonstrated improved in-hospital glycemia and clinical outcomes. This follow-up study assessed whether proactive care in hospital improved postdischarge HbA1c. In a subgroup of 298 RAPIDS trial participants with type 2 diabetes, age <80 years, and admission HbA1c ≥ 7.0%, diabetes treatment intensification occurred more often in early intervention versus usual care groups (37% vs. 19% [p = .001]), adjusted odds ratio 3.2 (95% confidence interval [CI]: 1.7-6.0). There was a greater change in HbA1c in the early intervention group (mean -0.9% [95% CI -1.3 to -0.4]) versus the usual care group (-0.3% [-0.6 to -0.1]), p = .029. The value of acute care by dedicated inpatient diabetes teams can extend beyond improving inpatient clinical outcomes and can lead to sustained improvement in glycemia.

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.

Quantification of stress-induced hyperglycaemia associated with key diagnostic categories using the stress hyperglycaemia ratio

AIM

Stress-induced hyperglycaemia (SIH) is the acute increase from preadmission glycaemia and is associated with poor outcomes. Early recognition of SIH and subsequent blood glucose (BG) management improves outcomes, but the degree of SIH provoked by distinct diagnostic categories remains unknown. Quantification of SIH is now possible using the stress hyperglycaemia ratio (SHR), which measures the proportional change from preadmission glycaemia, based on haemoglobin A_1c (HbA_1c ).

METHODS

We identified eligible patients for eight medical (n = 892) and eight surgical (n = 347) categories. Maximum BG from the first 24 h of admission for medical, or postoperatively for surgical patients was used to calculate SHR.

RESULTS

Analysis of variance indicated differing SHR and BG within both the medical (p < 0.0001 for both) and surgical cohort (p < 0.0001 for both). Diagnostic categories were associated with signature levels of SHR that varied between groups. Medically, SHR was greatest for ST-elevation myocardial infarction (1.22 ± 0.33) and sepsis (1.37 ± 0.43). Surgically, SHR was greatest for colectomy (1.62 ± 0.48) and cardiac surgeries (coronary artery graft 1.56 ± 0.43, aortic valve replacement 1.71 ± 0.33, and mitral valve replacement 1.75 ± 0.34). SHR values remained independent of HbA_1c , with no difference for those with HbA_1c above or below 6.5% (p > 0.11 for each). BG however was highly dependent on HbA_1c , invariably elevated in those with HbA_1c  ≥ 6.5% (p < 0.001 for each), and unreliably reflected SIH.

CONCLUSION

The acute stress response associated with various medical and surgical categories is associated with signature levels of SIH. Those with higher expected SHR are more likely to benefit from early SIH management, especially major surgery, which induced SIH typically 40% greater than medical cohorts. SHR equally recognised the acute change in BG from baseline across the full HbA_1c spectrum while BG did not and poorly reflected SIH.

In-hospital hyperglycemia but not diabetes mellitus alone is associated with increased in-hospital mortality in community-acquired pneumonia (CAP): a systematic review and meta-analysis of observational studies prior to COVID-19

The objective of this review was to quantify the association between diabetes, hyperglycemia, and outcomes in patients hospitalized for community-acquired pneumonia (CAP) prior to the COVID-19 pandemic by conducting a systematic review and meta-analysis. Two investigators independently screened records identified in the PubMed (MEDLINE), EMBASE, CINAHL, and Web of Science databases. Cohort and case-control studies quantitatively evaluating associations between diabetes and in-hospital hyperglycemia with outcomes in adults admitted to hospital with CAP were included. Quality was assessed using the Newcastle-Ottawa Quality Assessment Scale, effect size using random-effects models, and heterogeneity using I2 statistics. Thirty-eight studies met the inclusion criteria. Hyperglycemia was associated with in-hospital mortality (adjusted OR 1.28, 95% CI 1.09 to 1.50) and intensive care unit (ICU) admission (crude OR 1.82, 95% CI 1.17 to 2.84). There was no association between diabetes status and in-hospital mortality (adjusted OR 1.04, 95% CI 0.72 to 1.51), 30-day mortality (adjusted OR 1.13, 95% CI 0.77 to 1.67), or ICU admission (crude OR 1.91, 95% CI 0.74 to 4.95). Diabetes was associated with increased mortality in all studies reporting >90-day postdischarge mortality and with longer length of stay only for studies reporting crude (OR 1.50, 95% CI 1.11 to 2.01) results. In adults hospitalized with CAP, in-hospital hyperglycemia but not diabetes alone is associated with increased in-hospital mortality and ICU admission. Diabetes status is associated with increased >90-day postdischarge mortality. Implications for management are that in-hospital hyperglycemia carries a greater risk for in-hospital morbidity and mortality than diabetes alone in patients admitted with non-COVID-19 CAP. Evaluation of strategies enabling timely and effective management of in-hospital hyperglycemia in CAP is warranted.

Comparison of Glycemic Variability and Hypoglycemic Events in Hospitalized Older Adults Treated with Basal Insulin plus Vildagliptin and Basal-Bolus Insulin Regimen: A Prospective Randomized Study

Background: The basal−bolus insulin regimen is recommended in hospitalized patients with diabetes mellitus (DM), but has an increased risk of hypoglycemia. We aimed to compare dipeptidyl peptidase 4 inhibitors (DPP4-i) and basal−bolus insulin glycemic outcomes in hospitalized type 2 DM patients. Methods and patients: Our prospective randomized study included 102 elderly T2DM patients (82 ± 9 years, HbA1c 6.6% ± 1.9). Glycemic control: A variability coefficient assessed by continuous glucose monitoring (Free Style® sensor), mean insulin dose and hypoglycemia rates obtained with the two treatments were analyzed. Results: No differences were found between groups in glycemic control (mean daily glycemia during the first 10 days: 152.6 ± 38.5 vs. 154.2 ± 26.3 mg/dL; p = 0.8). The total doses Kg/day were 0.40 vs. 0.20, respectively (p < 0.001). A lower number of hypoglycemic events (9% vs. 15%; p < 0.04) and lower glycemic coefficient of variation (22% vs. 28%; p < 0.0002) were observed in the basal−DPP4-i compared to the basal−bolus regimen group. Conclusions: Treatment of inpatient hyperglycemia with basal insulin plus DPP4-i is an effective and safe regimen in old subjects with T2DM, with a similar mean daily glucose concentration, but lower glycemic variability and fewer hypoglycemic episodes compared to the basal bolus insulin regimen.

The impact of nursing staff education on diabetes inpatient glucose management: a pilot cluster randomised controlled trial

BACKGROUND

An increasing number of patients in hospital have diabetes, with most of them cared for by non-specialist staff. The effect of diabetes education for staff on patient outcomes, as well as the most effective method of staff education is unclear. Therefore, the aim of this study was to compare diabetes outcomes in medical wards where nursing staff were offered one face-to-face (F2F) session followed by access to online education (online), F2F education only, or standard care (control).

METHODS

We conducted a pilot cluster randomised controlled trial involving 16-weeks baseline/rollout followed by a 28-week post-intervention period across three medical wards (clusters) in a Sydney Teaching Hospital. The online ward provided an online competency-based diabetes education program and 1-h F2F teaching from a diabetes nurse educator (DNE), the F2F ward provided four separate 1-h teaching sessions by a DNE, with no additional sessions in the control ward. The primary outcome was length of stay (LOS); secondary outcomes included good diabetes days (GDD), hypoglycaemia and medication errors. Poisson and binary logistic regression were used to compare clusters.

RESULTS

Staff attendance/completion of ≥ 2 topics was greater with online than F2F education [39/48 (81%) vs 10/33 (30%); p < 0.001]. Among the 827/881 patients, there was no difference in LOS change between online [Median(IQR) 5(2-8) to 4(2-7) days], F2F [7(4-14) to 5(3-13) days] or control wards [5(3-9) to 5(3-7) days]. GDD improved only in the online ward 4.7(2.7-7.0) to 6.0(2.3-7.0) days; p = 0.038. Total patients with hypoglycaemia and appropriately treated hypoglycaemia increased in the online ward.

CONCLUSIONS

The inclusion of online education increased diabetes training uptake among nursing staff. GDD and appropriate hypoglycaemia management increased in the online education wards.

TRIAL REGISTRATION

Prospectively registered on the Australia New Zealand Clinical Trials Registry (ANZCTR) on 24/05/2017: ACTRN12617000762358 .

Electronic dashboard-based remote glycemic management program reduces length of stay and readmission rate among hospitalized adults

AIMS/INTRODUCTION

Currently, the impact of hospital-wide glycemic control interventions on length of hospital stay (LOS) and readmission rates are largely unknown. We investigated the impact of a 4-year hospital-wide remote glycemic management program on LOS and 30-day readmission rates among hospitalized adults who received glucose monitoring.

MATERIALS AND METHODS

In this retrospective study, hospitalized patients who received glucose monitoring were classified into groups 1 (high glucose variability), 2 (hypoglycemia), 3 (hyperglycemia) and 4 (relatively stable). The monthly percentage changes, and average monthly percentage changes of hyperglycemia, hypoglycemia and treat to target were determined using joinpoint regression analysis.

RESULTS

A total of 106,528 hospitalized patients (mean age 60.9 ± 18.5 years, 57% men) were enrolled. We observed a significant reduction in the percentage of inpatients in poor glycemic control groups (groups 1, 2 and 3, all P < 0.001), and a reciprocal increase in the relatively stable group (group 4) from 2016 to 2019. We found a significant reduction in LOS by 11.4% (10.5-9.3 days, P = 0.002, after adjustment for age, sex, and admission department). The 30-day readmission rate decreased from 29.9% to 29.3%, mainly among those in group 4 in 2019 (P < 0.001 after adjustment of sex, age, admission department and LOS).

CONCLUSIONS

Improved glycemic control through a hospital-wide electronic remote glycemic management system reduced LOS and 30-day readmission rates. Findings observed in this study might be associated with the reduction in cost of avoidable hospitalizations.

Triangulating evidence from longitudinal and Mendelian randomization studies of metabolomic biomarkers for type 2 diabetes

The number of people affected by Type 2 diabetes mellitus (T2DM) is close to half a billion and is on a sharp rise, representing a major and growing public health burden. Given its mild initial symptoms, T2DM is often diagnosed several years after its onset, leaving half of diabetic individuals undiagnosed. While several classical clinical and genetic biomarkers have been identified, improving early diagnosis by exploring other kinds of omics data remains crucial. In this study, we have combined longitudinal data from two population-based cohorts CoLaus and DESIR (comprising in total 493 incident cases vs. 1360 controls) to identify new or confirm previously implicated metabolomic biomarkers predicting T2DM incidence more than 5 years ahead of clinical diagnosis. Our longitudinal data have shown robust evidence for valine, leucine, carnitine and glutamic acid being predictive of future conversion to T2DM. We confirmed the causality of such association for leucine by 2-sample Mendelian randomisation (MR) based on independent data. Our MR approach further identified new metabolites potentially playing a causal role on T2D, including betaine, lysine and mannose. Interestingly, for valine and leucine a strong reverse causal effect was detected, indicating that the genetic predisposition to T2DM may trigger early changes of these metabolites, which appear well-before any clinical symptoms. In addition, our study revealed a reverse causal effect of metabolites such as glutamic acid and alanine. Collectively, these findings indicate that molecular traits linked to the genetic basis of T2DM may be particularly promising early biomarkers.

Glucose as the Fifth Vital Sign: A Randomized Controlled Trial of Continuous Glucose Monitoring in a Non-ICU Hospital Setting

OBJECTIVE

The current standard for hospital glucose management is point-of-care (POC) testing. We conducted a randomized controlled trial of real-time continuous glucose monitoring (RT-CGM) compared with POC in a non-intensive care unit (ICU) hospital setting.

RESEARCH DESIGN AND METHODS

A total of 110 adults with type 2 diabetes on a non-ICU floor received RT-CGM with Dexcom G6 versus usual care (UC). RT-CGM data were wirelessly transmitted from the bedside. Hospital telemetry monitored RT-CGM data and notified bedside nursing of glucose alerts and trends. Standardized protocols were used for interventions.

RESULTS

The RT-CGM group demonstrated significantly lower mean glucose (M∆ = -18.5 mg/dL) and percentage of time in hyperglycemia >250 mg/dL (-11.41%) and higher time in range 70-250 mg/dL (+11.26%) compared with UC (P values <0.05). Percentage of time in hypoglycemia was very low.

CONCLUSIONS

RT-CGM can be used successfully in community-based hospital non-ICU settings to improve glucose management. Continuously streaming glucose readings may truly be the fifth vital sign.

Clinical Prediction Tool To Identify Adults With Type 2 Diabetes at Risk for Persistent Adverse Glycemia in Hospital

OBJECTIVES

Given the high incidence of hyperglycemia and hypoglycemia in hospital and the lack of prediction tools for this problem, we developed a clinical tool to assist early identification of individuals at risk for persistent adverse glycemia (AG) in hospital.

METHODS

We analyzed a cohort of 594 consecutive adult inpatients with type 2 diabetes. We identified clinical factors available early in the admission course that were associated with persistent AG (defined as ≥2 days with capillary glucose <4 or >15 mmol/L during admission). A prediction model for persistent AG was constructed using logistic regression and internal validation was performed using a split-sample approach.

RESULTS

Persistent AG occurred in 153 (26%) of inpatients, and was associated with admission dysglycemia (odds ratio [OR], 3.65), glycated hemoglobin ≥8.1% (OR, 5.08), glucose-lowering treatment regimen containing sulfonylurea (OR, 3.50) or insulin (OR, 4.22), glucocorticoid medication treatment (OR, 2.27), Charlson Comorbidity Index score and the number of observed days. An early-identification prediction tool, based on clinical factors reliably available at admission (admission dysglycemia, glycated hemoglobin, glucose-lowering regimen and glucocorticoid treatment), could accurately predict persistent AG (receiver-operating characteristic area under curve = 0.806), and, at the optimal cutoff, the sensitivity, specificity and positive predictive value were 84%, 66% and 53%, respectively.

CONCLUSIONS

A clinical prediction tool based on clinical risk factors available at admission to hospital identified patients at increased risk for persistent AG and could assist early targeted management by inpatient diabetes teams.

Inpatient Transition to Virtual Care During COVID-19 Pandemic

Introduction: During the coronavirus disease 2019 (COVID-19) outbreak, novel approaches to diabetes care have been employed. Care in both the inpatient and outpatient setting has transformed considerably. Driven by the need to reduce the use of personal protective equipment and exposure for patients and providers alike, we transitioned inpatient diabetes management services to largely "virtual" or remotely provided care at our hospital. Methods: Implementation of a diabetes co-management service under the direction of the University of North Carolina division of endocrinology was initiated in July 2019. In response to the COVID-19 pandemic, the diabetes service was largely transitioned to a virtual care model in March 2020. Automatic consults for COVID-19 patients were implemented. Glycemic outcomes from before and after transition to virtual care were evaluated. Results: Data over a 15-week period suggest that using virtual care for diabetes management in the hospital is feasible and can provide similar outcomes to traditional face-to-face care. Conclusion: Automatic consults for COVID-19 patients ensure that patients with serious illness receive specialized diabetes care. Transitioning to virtual care models does not limit the glycemic outcomes of inpatient diabetes care and should be employed to reduce patient and provider exposure in the setting of COVID-19. These findings may have implications for reducing nosocomial infection in less challenging times and might address shortage of health care providers, especially in the remote areas.

Debate on Insulin vs Non-insulin Use in the Hospital Setting-Is It Time to Revise the Guidelines for the Management of Inpatient Diabetes?

PURPOSE OF REVIEW

Hyperglycemia contributes to a significant increase in morbidity, mortality, and healthcare costs in the hospital. Professional associations recommend insulin as the mainstay of diabetes therapy in the inpatient setting. The standard of care basal-bolus insulin regimen is a labor-intensive approach associated with a significant risk of iatrogenic hypoglycemia. This review summarizes recent evidence from observational studies and clinical trials suggesting that not all patients require treatment with complex insulin regimens.

RECENT FINDINGS

Evidence from clinical trials shows that incretin-based agents are effective in appropriately selected hospitalized patients and may be a safe alternative to complicated insulin regimens. Observational studies also show that older agents (i.e., metformin and sulfonylureas) are commonly used in the hospital, but there are few carefully designed studies addressing their efficacy. Therapy with dipeptidyl peptidase-4 (DPP-4) inhibitors, alone or in combination with basal insulin, may effectively control glucose levels in patients with mild to moderate hyperglycemia. Further studies with glucagon-like peptide-1 (GLP-1) receptor analogs and older oral agents are needed to confirm their safety in the hospital.

Glucometric benchmarking in an Australian hospital enabled by networked glucose meter technology

OBJECTIVE

To assess glucometric outcomes and to estimate the incidence of hypo- and hyperglycaemia among non-critical care inpatients in a major Australian hospital.

DESIGN, SETTING AND PARTICIPANTS

A prospective 10-week observational study (7 March - 22 May 2016) of consecutive inpatients with diabetes or newly detected hyperglycaemia admitted to eight medical and surgical wards at the Royal Melbourne Hospital. Point-of-care blood glucose (BG) data were collected with networked glucose meters.

MAIN OUTCOME MEASURES

Glycaemic control, as assessed with three glucometric models (by population, by patient, by patient-day); incidence of adverse glycaemic days (AGDs; patient-days with BG levels below 4 mmol/L or above 15 mmol/L).

RESULTS

During the study period, there were 465 consecutive admissions of 441 patients with diabetes or newly detected hyperglycaemia, and 9817 BG measurements over 2953 patient-days. The mean patient-day BG level was 9.5 mmol/L (SD, 3.3 mmol/L). The incidence of hyperglycaemia was higher than for a United States hospital benchmark (patient-days with mean BG level above 10 mmol/L, 37% v 32), and that of hypoglycaemia lower (proportion of patient-days with mean BG level below 3.9 mmol/L, 4.1% v 6.1%). There were 260 (95% CI, 245-277) AGDs per 1000 patient-days; the incidence was higher in medical than surgical ward patients (290 [CI, 270-310] v 206 [CI, 181-230] per 1000 patient-days). 604 AGDs (79%) were linked with 116 patients (25%). Episodes of hyperglycaemia (BG above 15 mmol/L) were more frequent before lunch, dinner, and bedtime; 94 of 187 episodes of hypoglycaemia (BG below 4 mmol/L) occurred between 11 pm and 8 am.

DISCUSSION

Glucometric analysis supported by networked glucose meter technology provides detailed inpatient data that could enable local benchmarking for promoting safe diabetes care in Australian hospitals.