Diurnal temporal patterns of hypoglycaemia in hospitalized people with diabetes may reveal potentially correctable factors

Daily variation in blood glucose levels during continuous enteral nutrition in patients on the intensive care unit: a retrospective observational study

BACKGROUND

The circadian timing system coordinates daily cycles in physiological functions, including glucose metabolism and insulin sensitivity. Here, the aim was to characterise the 24-h variation in glucose levels in critically ill patients during continuous enteral nutrition after controlling for potential sources of bias.

METHODS

Time-stamped clinical data from adult patients who stayed in the Intensive Care Unit (ICU) for at least 4 days and received enteral nutrition were extracted from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Linear mixed-effects and XGBoost modelling were used to determine the effect of time of day on blood glucose values.

FINDINGS

In total, 207,647 glucose measurements collected during enteral nutrition were available from 6,929 ICU patients (3,948 males and 2,981 females). Using linear mixed-effects modelling, time of day had a significant effect on blood glucose levels (p < 0.001), with a peak of 9.6 [9.5-9.6; estimated marginal means, 95% CI] mmol/L at 10:00 in the morning and a trough of 8.6 [8.5-8.6] mmol/L at 02:00 at night. A similar impact of time of day on glucose levels was found with the XGBoost regression model.

INTERPRETATION

These results revealed marked 24-h variation in glucose levels in ICU patients even during continuous enteral nutrition. This 24-h pattern persists after adjustment for potential sources of bias, suggesting it may be the result of endogenous biological rhythmicity.

FUNDING

This work was supported by a VENI grant from the Netherlands Organisation for Health Research and Development (ZonMw), an institutional project grant, and by the Dutch Research Council (NWO).

The Daily Patterns of Emergency Medical Events

This study examines population-level daily patterns of time-stamped emergency medical service (EMS) dispatches to establish their situational predictability. Using visualization, sinusoidal regression, and statistical tests to compare empirical cumulative distributions, we analyzed 311,848,450 emergency medical call records from the US National Emergency Medical Services Information System (NEMSIS) for years 2010 through 2022. The analysis revealed a robust daily pattern in the hourly distribution of distress calls across 33 major categories of medical emergency dispatch types. Sinusoidal regression coefficients for all types were statistically significant, mostly at the p < 0.0001 level. The coefficient of determination ( R 2 ) ranged from 0.84 and 0.99 for all models, with most falling in the 0.94 to 0.99 range. The common sinusoidal pattern, peaking in mid-afternoon, demonstrates that all major categories of medical emergency dispatch types appear to be influenced by an underlying daily rhythm that is aligned with daylight hours and common sleep/wake cycles. A comparison of results with previous landmark studies revealed new and contrasting EMS patterns for several long-established peak occurrence hours-specifically for chest pain, heart problems, stroke, convulsions and seizures, and sudden cardiac arrest/death. Upon closer examination, we also found that heart attacks, diagnosed by paramedics in the field via 12-lead cardiac monitoring, followed the identified common daily pattern of a mid-afternoon peak, departing from prior generally accepted morning tendencies. Extended analysis revealed that the normative pattern prevailed across the NEMSIS data when reorganized to consider monthly, seasonal, daylight-savings versus civil time, and pre-/post-COVID-19 periods. The predictable daily EMS patterns provide impetus for more research that links daily variation with causal risk and protective factors. Our methods are straightforward and presented with detail to provide accessible and replicable implementation for researchers and practitioners.

Bridging technology and clinical practice: innovating inpatient hyperglycaemia management in non-critical care settings

Emerging evidence shows that suboptimal glycaemic control is associated with increased morbidity and length of stay in hospital. Various guidelines for safe and effective inpatient glycaemic control in the non-critical care setting have been published. In spite of this, implementation in practice remains limited because of the increasing number of people with diabetes admitted to hospital and staff work burden. The use of technology in the outpatient setting has led to improved glycaemic outcomes and quality of life for people with diabetes. There remains an unmet need for technology utilisation in inpatient hyperglycaemia management in the non-critical care setting. Novel technologies have the potential to provide benefits in diabetes care in hospital by improving efficacy, safety and efficiency. Rapid analysis of glucose measurements by point-of-care devices help facilitate clinical decision-making and therapy adjustment in the hospital setting. Glucose treatment data integration with computerized glucose management systems underpins the effective use of decision support systems and may streamline clinical staff workflow. Continuous glucose monitoring and automation of insulin delivery through closed-loop systems may provide a safe and efficacious tool for hospital staff to manage inpatient hyperglycaemia whilst reducing staff workload. This review summarizes the evidence with regard to technological methods to manage inpatient glycaemic control, their limitations and the future outlook, as well as potential strategies by healthcare organizations such as the National Health Service to mediate the adoption, procurement and use of diabetes technologies in the hospital setting.

Is all hypoglycaemia treated as equal? An observational study of how the type of diabetes and treatment prescribed prior to admission influences quality of treatment of inpatient hypoglycaemia

AIMS

Inpatient hypoglycaemia is common and associated with adverse outcomes. There is often increased vigilance of hypoglycaemia in inpatients with type 1 diabetes (T1DM) compared to type 2 diabetes (T2DM). We aimed to investigate this apparent discrepancy, utilising the time to repeat (TTR) capillary blood glucose (CBG) measurement as a surrogate for engagement with guidelines stating that CBG should be rechecked following intervention within 15 min of an initial CBG of <4 mmol/L.

METHODS

This is an observational study of inpatient CBG data from 8 hospitals over a 7-year period. A national diabetes registry allowed identification of individual's diagnosis and diabetes therapy. For each initial (index) CBG, the TTR for individuals with T2DM-on insulin or sulphonylurea-was compared with the TTR for individuals with T1DM, using a t test for significance performed on log(TTR). The median TTR was plotted for each group per index CBG.

RESULTS

In total, 1480,335 CBG measurements were obtained. A total of 26,664 were <4 mmol/L. The TTR in T2DM individuals on sulphonylurea was significantly greater than in T1DM individuals where index CBG was ≥2.3 mmol/L (except index CBG 2.6 mmol/L). For T2DM patients receiving insulin significance exists for index CBGs of ≥3.2 mmol/L.

CONCLUSIONS

This analysis suggests that quality of care of hypoglycaemia varies according to diagnosis and medication. The group with the highest TTR (T2DM sulphonylurea treated) are possibly the clinical group in whom hypoglycaemia is most concerning. These data therefore suggest a need for education and raising awareness within the inpatient nursing staff.

Diabetic emergencies - ketoacidosis, hyperglycaemic hyperosmolar state and hypoglycaemia

Diabetic ketoacidosis (DKA), hyperglycaemic hyperosmolar state (HHS) and hypoglycaemia are serious complications of diabetes mellitus that require prompt recognition, diagnosis and treatment. DKA and HHS are characterized by insulinopaenia and severe hyperglycaemia; clinically, these two conditions differ only by the degree of dehydration and the severity of metabolic acidosis. The overall mortality recorded among children and adults with DKA is <1%. Mortality among patients with HHS is ~10-fold higher than that associated with DKA. The prognosis and outcome of patients with DKA or HHS are determined by the severity of dehydration, the presence of comorbidities and age >60 years. The estimated annual cost of hospital treatment for patients experiencing hyperglycaemic crises in the USA exceeds US$2 billion. Hypoglycaemia is a frequent and serious adverse effect of antidiabetic therapy that is associated with both immediate and delayed adverse clinical outcomes, as well as increased economic costs. Inpatients who develop hypoglycaemia are likely to experience a long duration of hospital stay and increased mortality. This Review describes the clinical presentation, precipitating causes, diagnosis and acute management of these diabetic emergencies, including a discussion of practical strategies for their prevention.

Predictors of recurrent hypoglycemia following a severe hypoglycemic event among hospitalized patients

OBJECTIVES

Severe hypoglycemia is associated with poor hospital outcomes, but variables contributing to the adequacy of treatment have not been described. The objective of this study was to determine predictors of recurrent hypoglycemia among hospitalized patients with a severe hypoglycemic event.

METHODS

Patients with severe hypoglycemia (glucose <40 mg/dl) with a concomitant insulin order were identified using the study institution's Information Warehouse. The primary outcome was the prevalence of recurrent hypoglycemia (defined as <70 mg/dl within 24 hours) and to identify independent predictors of recurrent hypoglycemia. Secondary outcomes included time to blood glucose recheck, time to blood glucose ≥ 70 mg/dl, and rebound hyperglycemia (defined as glucose >300 mg/dl within 24 hours). Multivariable linear and logistic regression models were performed.

RESULTS

A total of 129 patients with severe hypoglycemia were identified. The median time to repeat glucose measurement was 29 (IQR 15-61) minutes, while the time to resolution of hypoglycemia was 49 (IQR 26-103) minutes. Recurrent hypoglycemia occurred in 49% of patients, while 19% of patients experienced rebound hyperglycemia. Independent predictors of recurrent hypoglycemia included lower repeat glucose (p = 0.025), low glomerular filtration rate (p = 0.033), and lack of insulin adjustment (p = 0.012). Independent predictors of maximum glucose post-event were type 1 diabetes (p = 0.0003), history of any diabetes (p = 0.013), and total bolus dose of insulin (p < 0.0001). Overnight timing of events was the only predictor of shorter time to hypoglycemia resolution (p < 0.0001).

CONCLUSIONS

Recurrent hypoglycemia following severe hypoglycemia is common in the hospital, suggesting the need for enhanced monitoring in such patients. Further research is needed to identify methods to reduce the incidence of recurrent hypoglycemia.

Randomized controlled trial of insulin supplementation for correction of bedtime hyperglycemia in hospitalized patients with type 2 diabetes

OBJECTIVE

Clinical guidelines recommend point-of-care glucose testing and the use of supplemental doses of rapid-acting insulin before meals and at bedtime for correction of hyperglycemia. The efficacy and safety of this recommendation, however, have not been tested in the hospital setting.

RESEARCH DESIGN AND METHODS

In this open-label, randomized controlled trial, 206 general medicine and surgery patients with type 2 diabetes treated with a basal-bolus regimen were randomized to receive either supplemental insulin (n = 106) at bedtime for blood glucose (BG) >7.8 mmol/L or no supplemental insulin (n = 100) except for BG >19.4 mmol/L. Point-of-care testing was performed before meals, at bedtime, and at 3:00 a.m. The primary outcome was the difference in fasting BG. In addition to the intention-to-treat analysis, an as-treated analysis was performed where the primary outcome was analyzed for only the bedtime BG levels between 7.8 and 19.4 mmol/L.

RESULTS

There were no differences in mean fasting BG for the intention-to-treat (8.8 ± 2.4 vs. 8.6 ± 2.2 mmol/L, P = 0.76) and as-treated (8.9 ± 2.4 vs. 8.8 ± 2.4 mmol/L, P = 0.92) analyses. Only 66% of patients in the supplement and 8% in the no supplement groups received bedtime supplemental insulin. Hypoglycemia (BG <3.9 mmol/L) did not differ between groups for either the intention-to-treat (30% vs. 26%, P = 0.50) or the as-treated (4% vs. 8%, P = 0.37) analysis.

CONCLUSIONS

The use of insulin supplements for correction of bedtime hyperglycemia was not associated with an improvement in glycemic control. We conclude that routine use of bedtime insulin supplementation is not indicated for management of inpatients with type 2 diabetes.

Point-of-care blood glucose testing for diabetes care in hospitalized patients: an evidence-based review

Glycemic control in hospitalized patients with diabetes requires accurate near-patient glucose monitoring systems. In the past decade, point-of-care blood glucose monitoring devices have become the mainstay of near-patient glucose monitoring in hospitals across the world. In this article, we focus on its history, accuracy, clinical use, and cost-effectiveness. Point-of-care devices have evolved from 1.2 kg instruments with no informatics to handheld lightweight portable devices with advanced connectivity features. Their accuracy however remains a subject of debate, and new standards for their approval have now been issued by both the International Organization for Standardization and the Clinical and Laboratory Standards Institute. While their cost-effectiveness remains to be proved, their clinical value for managing inpatients with diabetes remains unchallenged. This evidence-based review provides an overall view of its use in the hospital setting.

Temporal patterns of hypoglycaemia and burden of sulfonylurea-related hypoglycaemia in UK hospitals: a retrospective multicentre audit of hospitalised patients with diabetes

OBJECTIVES

To determine whether temporal patterns of hypoglycaemia exist in inpatients with diabetes 'at risk' of hypoglycaemia (those on insulin and/or sulfonylureas), and if so whether patterns differ between hospitals and between these treatments.

SETTING

Retrospective multicentre audit of inpatients with diabetes involving 11 acute UK National Health Service (NHS) trusts.

PARTICIPANTS

Capillary blood glucose readings of 3.9 mmol/L or less (hypoglycaemia) for all adult (≥18 years) inpatients with diabetes 'at risk' of hypoglycaemia were extracted from the Abbott PrecisionWeb Point-of-Care Data Management System over a 4-week period. Overall, 2521 readings of 3.9 mmol/L or less (hypoglycaemia) occurring in 866 participants between 1 June 2013 and 29 June 2013 were analysed.

RESULTS

The majority (65%) occurred between 21:00 and 08:59, a pattern common to all Trusts. This was more frequent in sulfonylurea-treated than insulin-treated participants (75.3% vs 59.3%, p=0.0001). Furthermore, hypoglycaemic readings were more frequent between 5:00 and 7:59 in sulfonylurea-treated than insulin-treated participants (46.7% vs 22.7% of readings for respective treatments, p=0.0001). Sulfonylureas accounted for 31.8% of all hypoglycaemic readings. As a group, sulfonylurea-treated participants were older (median age 78 vs 73 years, p=0.0001) and had lower glycated haemoglobin (median 56 (7.3%) vs 69 mmol/mol (8.5%), p=0.0001). Hypoglycaemic readings per participant were as frequent for sulfonylurea-treated participants as for insulin-treated participants (median=2 for both) as were the proportions in each group with ≥5 hypoglycaemic readings (17.3% vs 17.7%).

CONCLUSIONS

In all Trusts, hypoglycaemic readings were more frequent between 21:00 and 08:59 in 'at risk' inpatients with diabetes, with a greater frequency in the early morning period (5:00-7:59) in sulfonylurea-treated inpatients. This may have implications for the continuing use of sulfonylureas in the inpatient setting.

Enhancing diabetes management while teaching quality improvement methods

Six medical units realized that they were having issues with accurate timing of bedtime blood glucose measurement for their patients with diabetes. They decided to investigate the issues by using their current staff nurse committee structure. The clinical nurse specialists and nurse education specialists decided to address the issue by educating and engaging the staff in the define, measure, analyze, improve, control (DMAIC) framework process. They found that two issues needed to be improved, including timing of bedtime blood glucose measurement and snack administration and documentation. Several educational interventions were completed and resulted in improved timing of bedtime glucose measurement and bedtime snack documentation. The nurses understood the DMAIC process, and collaboration and cohesion among the medical units was enhanced.