Outcome measures for outpatient hypoglycemia prevention studies

Systems are being developed that utilize algorithms to predict impending hypoglycemia using commercially available continuous glucose monitoring (CGM) devices and to discontinue insulin delivery if hypoglycemia is predicted. In outpatient studies designed to test such systems, CGM-measured glycemic indices will not only be important outcome measures of efficacy but, in certain cases, will be the only good outcome. This is especially true in short-term studies designed to reduce hypoglycemia since the event rate for severe hypoglycemic events is too low for it to be a good outcome, and milder hypoglycemia often will be variably detected. Continuous glucose monitoring inaccuracy can be accounted for in the study design by increasing sample size and/or study duration.     

Durability of the effect of online diabetes training for medical residents on knowledge, confidence, and inpatient glycemia

Background: Inpatient dysglycemia is associated with increased morbidity, mortality and cost. Medical education must not only address knowledge gaps, but also improve clinical care. Methods: All 129 medicine residents at a large academic medical center were offered a case‐based online curriculum on the management of inpatient dysglycemia in the fall of 2009. First‐year residents took a 3‐h course with 10 modules. Second and third‐year residents, who had been educated the prior year, underwent abbreviated training. All residents were offered a 20‐min refresher course in the spring of 2009. We assessed resident knowledge, resident confidence, and patient glycemia on two teaching wards before and after the initial intervention, as well as after the refresher course. Results: A total of 117 residents (91%) completed the initial training; 299 analyzed admissions generated 11 089 blood glucose values and 4799 event blood glucose values. Admissions with target glycemia increased from 19.4% to 33.0% (P = 0.035) by the end of the curriculum. There was a strong downward trend in hyperglycemia from 22.4% to 11.3% (P = 0.055) without increased hypoglycemia. Confidence and knowledge increased significantly among first‐time and repeat participants. Residents rated the intervention as highly relevant to their practice and technologically well implemented. Conclusion: Optimization of an online curriculum covering the management of inpatient glycemia over the course of 2 years led to significantly more admissions in the target glycemia range. Given its scalability, modularity and applicability, this web‐based educational intervention may become the standard curriculum for the management of inpatient glycemia.     

Prediction and prevention of Type 1 diabetes mellitus

Type 1A diabetes mellitus (T1DM) is caused by autoimmune islet β-cell destruction with consequent severe insulin deficiency. We can now predict the development of T1DM by determining four biochemically characterized islet autoantibodies, namely those antibodies against insulin, glutamic acid decarboxylase 65, insulinoma antigen (IA)-2 (ICA512) and the zinc transporter ZnT8. We can also prevent T1DM in animal models, but the final goal is the prevention of T1DM in humans. Multiple clinical trials are underway investigating methods to prevent β-cell destruction.     

低血糖后葡萄糖再灌注脑损伤相关机制及预防

糖尿病发病率越来越高,已成为全球性问题,随着强化控糖观念的提出及胰岛素的广泛应用,糖尿病相关的低血糖发生率也逐渐增加.持续低血糖会导致各种急性心脑血管疾病,然而新近研究发现胰岛素诱导低血糖后,给予葡萄糖升高血糖后出现了比低血糖状态时更严重的心脑血管损害,尤其是对脑的损伤尤为显著,类似于缺血再灌注,因此人们提出"葡萄糖再...     

Living with hypoglycemia

OBJECTIVE: To increase understanding of the everyday experiences of hypoglycemia for patients with type 1 diabetes through the use of a narrative research approach. SETTING: Center for diabetes treatment and research. DESIGN: Cross-sectional assessment using a narrative research approach. PATIENTS/PARTICIPANTS: Twenty outpatients (aged 21–30 years) diagnosed with type 1 diabetes for at least 10 years. MEASUREMENTS AND MAIN RESULTS: Experiences of hypoglycemia were investigated during in-depth, semistructured interviews that were tape-recorded, transcribed, and analyzed to identify common themes, Self-report measures of depression (Revised Hamilton Rating Scale for Depression) and anxiety (State-Trait Anxiety Inventory) also were administered. Subjects reported the following common themes: interpersonal conflict including fears of dependency and loss of control and problems addressing concerns about hypoglycemia with significant others; difficulty making sense of their hypoglycemic behaviors in relation to their usual ways of functioning; and perceived lack of understanding by others, including physicians, about the emotional experiences of hypoglycemia. Subjects were neither clinically depressed nor anxious. CONCLUSIONS: These findings suggest that type 1 diabetes patients’ experiences of hypoglycemia negatively affect their interpersonal relationships and views of themselves. Hypoglycemia also was described as an extremely private experience that was rarely discussed with others. Patient education and professional support in the treatment of hypoglycemia are recommended to enhance treatment decision making for patients with type 1 diabetes. Funded by Behavioral and Mental Health Research Department Funding, Joslin Diabetes Center.     

Hypoglycemia Prediction Using Machine Learning Models for Patients With Type 2 Diabetes

Background:Minimizing the occurrence of hypoglycemia in patients with type 2 diabetes is a challenging task since these patients typically check only 1 to 2 self-monitored blood glucose (SMBG) readings per day.Method:We trained a probabilistic model using machine learning algorithms and SMBG values from real patients. Hypoglycemia was defined as a SMBG value < 70 mg/dL. We validated our model using multiple data sets. In addition, we trained a second model, which used patient SMBG values and information about patient medication administration.Results:The optimal number of SMBG values needed by the model was approximately 10 per week. The sensitivity of the model for predicting a hypoglycemia event in the next 24 hours was 92% and the specificity was 70%. In the model that incorporated medication information, the prediction window was for the hour of hypoglycemia, and the specificity improved to 90%.Conclusions:Our machine learning models can predict hypoglycemia events with a high degree of sensitivity and specificity. These models—which have been validated retrospectively and if implemented in real time—could be useful tools for reducing hypoglycemia in vulnerable patients.     

Frequently Repeated Glucose Measurements Overestimate the Incidence of Inpatient Hypoglycemia and Severe Hyperglycemia

Objective

The aim was to determine if frequently repeated glucose measurements mandated by an inpatient protocol led to falsely elevated reported rates of both hypo- and hyperglycemia.

Methods

In our academic medical center, a mandatory standardized subcutaneous insulin order form and protocol was implemented in May 2006. We analyzed point-of-care blood glucose (BG) measurements collected on all medical/surgical wards during the month of August in both 2005 and 2006 by all BGs measured, by patient admission, and by monitored patient-day. We then repeated all analyses using an algorithm that excluded BG values if another BG was measured less than 5 minutes later or 5-60 minutes earlier.

Results

In 2005 versus 2006, there were 7034 versus 8016 glucoses measured in 397 versus 389 patients over 1704 versus 1710 patient days, respectively. Analyses based on patient-day balanced differences in BG measurement frequency and patient length of stay. In both years, failure to exclude repeat values overestimated both the proportion of patient days with hypoglycemia (3.5% versus 1.8% in 2005, p = .003; 2.6% versus 1.3% in 2006, p = .007) and severe hyperglycemia (9.3% versus 7.4% in 2005, p = .09; 7.7% versus 5.9% in 2006, p = .08). Mean, median, and proportion of patient-day means within our target range (80-150 mg/dl) were not significantly different.

Conclusions

Glucometric reports should exclude repeated BG measurements from a single clinical episode of hypo- or hyperglycemia in order to accurately reflect inpatient glycemic control.     

老年2型糖尿病低血糖反应的特点与预防

目的加强对老年2型糖尿病的低血糖反应特点的认识及预防措施的探讨。方法回顾性分析58例老年2型糖尿病低血糖反应患者的临床资料。结果老年2型糖尿病低血糖反应具有临床症状不典型、低血糖持续时间长、恢复慢等特点，其诱因主要与饮食不规律有关，医源性因素也是另一重要原因。结论老年2型糖尿病患者应加强健康宣教和血糖监测，对其血糖的控制要相对放宽标准。     

Computerized Algorithms: Improving Hyperglycemia in the Hospital: Outcomes of a Nursing In-Service to Evaluate Acceptance of a Web-Based Insulin Infusion Calculator

Background

Many insulin infusion protocols are available for clinical use. We developed a Web-based, online intravenous insulin infusion calculator (IVIIC) for use in our intensive care and medical–surgical units.

Methods

In September 2006, we implemented a quality improvement project: an online survey to evaluate the acceptance of this protocol by the nursing staff. Of the 103 registered nurses (RNs) who participated, there was no difference among experience levels of the RNs (≥ or <5 years) or among durations that RNs had been working within their unit (≥ or <2 years).

Results

The nurses were surveyed regarding the use and interpretation of the protocol, their comfort with, confidence in, and experience in using the protocol. More than 80% of the RNs found the protocol easy to implement, easy to interpret, and successful in controlling the blood glucose levels. Approximately 71% (±9%) of the RNs were comfortable with the tight blood glucose levels of the protocol. The nurses'' confidence with the protocol was 82% (±8%), likely because 70% (±9%) of the nurses believed the training to be adequate. Significantly less than 25% of the RNs (18 ± 7%) believed it was necessary to deviate from the protocol. More than 85% of the RNs appreciated the ability to make changes at their level of practice (92 ± 5%).

Conclusions

In summary, the IVIIC is well accepted by RNs for care of hyperglycemia in a hospital setting.     

Factors associated with hypoglycemia unawareness and severe hypoglycemia in type 1 diabetes mellitus patients

Aims/IntroductionSeveral factors are associated with hypoglycemia unawareness and severe hypoglycemia, but few large studies have analyzed Japanese patients with type 1 diabetes. The aim of this study was to analyze the risk factors for hypoglycemia unawareness and severe hypoglycemia in Japanese type 1 diabetes patients.Materials and MethodsA self‐administered questionnaire investigated events, complications and treatments associated with hypoglycemia in patients with type 1 diabetes. Multiple logistic regression analysis of factors associated with hypoglycemia unawareness and severe hypoglycemia requiring medical treatment was carried out. The coefficient of variation (CV) of blood glucose levels was determined using blood samples collected at six outpatient visits.ResultsOf the 1,619 participants, 44.2% and 10.4% experienced hypoglycemia unawareness and severe hypoglycemia, respectively. Mean HbA1c levels in patients with hypoglycemia unawareness were lower than those in patients without hypoglycemia unawareness. The type 1 diabetes subtype, glycated hemoglobin (HbA1c) level, CV of blood glucose levels and history of severe hypoglycemia requiring medical treatment were significant independent variables predicting the presence of hypoglycemia unawareness. The glucose CV and a history of hypoglycemia unawareness were significant independent variables predicting severe hypoglycemia requiring medical treatment. In stratified analyses of patients divided into four groups according to glucose CV and HbA1c levels, the high‐glucose‐CV/low‐HbA1c group had the highest odds ratios for hypoglycemia unawareness (2.60) and severe hypoglycemia requiring medical treatment (2.55).ConclusionsThe ambulant glucose CV correlated with both hypoglycemia unawareness and severe hypoglycemia. Patients with high glucose CV and low HbA1c are at high risk of such adverse events, and their treatment strategies should be reviewed.     

The relation between HbA1c and hypoglycemia revisited; a secondary analysis from an intervention trial in patients with type 1 diabetes and impaired awareness of hypoglycemia

Aims

We aimed to re-assess the previously shown but recently disputed association between HbA1c and severe hypoglycemia.

肝硬化合并糖尿病患者发生低血糖症的临床分析

目的 探讨肝硬化合并糖尿病患者发生低血糖的原因及临床指标的特点。方法 选取首都医科大学附属北京佑安医院2017年1月-2019年6月收治的肝硬化合并糖尿病患者共50例为研究对象,其中发生1次低血糖的25例为试验组,未发生低血糖的25例为对照组。对两组患者肝肾功能、空腹血糖、糖化血红蛋白及Child-Pugh分级进行评估,并分析低血糖发生的时间段及可能原因。计量资料两组比较采用独立样本t检验或Mann-Whitney U检验,计数资料两组间比较采用χ2检验。结果 试验组空腹血糖明显低于对照组[6.10(3.45~8.96)mmol/L vs 8.12(6.18±12.59)mmol/L, Z=-2.687, P=0.007],ChE明显低于对照组[3009.00(1788.50~4493.50)U/L vs 4936.00(4051.00~6740.50)U/L, Z=-3.095, P=0.002],Alb明显低于对照组[(32.02±7.07)g/L vs (35.89±5.49)g/L, t=2.161,P=0.036],糖化血红蛋白明显低于对照组[(6.97±1.64)mmol/L vs (8.04±1.78)mmol/L,t=2.047,P=0.047]。试验组Child-Pugh分级以B级(36%)及C级(36%)为主,对照组以A级(56%)及B级(40%)为主,两组Child-Pugh分级差异有统计学意义(χ^2=8.786,P=0.012)。肝硬化合并糖尿病患者大部分低血糖发生在晨起空腹及白天,原因以胰岛素过多(44%)及进食或热量补充不足(40%)为主,部分患者有空腹无症状性低血糖(16%)。结论 临床上应重视肝硬化合并糖尿病患者的血糖监测及管理,减少低血糖事件的发生。     

Patient Self-Management of Diabetes Care in the Inpatient Setting: Con

Self-management of diabetes by inpatients can be problematic. People with type 1 diabetes often prefer to self-manage their diabetes in the inpatient setting. We report the case of a patient admitted to the surgical service who was self-administering his home insulin, often without telling his nurse or physician. He was aiming for tight glycemic control, which resulted in life-threatening hypoglycemia. While patients can often self-manage their diabetes in the outpatient setting, inpatient management of diabetes is very different. Patients may not be familiar with common scenarios requiring adjustments of insulin therapy. Therefore, we recommend against self-management of diabetes in the hospital. However, the patients should be involved in discussions about management of their diabetes in the hospital to allay their concerns about changes made to their insulin regimens. An example of successful cooperative management is with use of protocols that allow continued use of insulin pumps in the hospital.     

Population-based study of severe hypoglycemia requiring emergency medical service assistance reveals unique findings

Objective

The objective is to report a contemporary population-based estimate of hypoglycemia requiring emergency medical services (EMS), its burden on medical resources, and its associated mortality in patients with or without diabetes mellitus (DM, non-DM), which will enable development of prospective strategies that will capture hypoglycemia promptly and provide an integrated approach for prevention of such episodes.

Methods

We retrieved all ambulance calls activated for hypoglycemia in Olmsted County, Minnesota, between January 1, 2003 and December 31, 2009.

Results

A total of 1473 calls were made by 914 people (DM 8%, non-DM 16%, unknown DM status 3%). Mean age was 60 ± 16 years with 49% being female. A higher percentage of calls were made by DM patients (87%) with proportionally fewer calls coming from non-DM patients (11%) (chi-square test, p < .001), and the remaining 2% calls by people with unknown DM status. Emergency room transportation and hospitalization were significantly higher in non-DM patients compared to DM patients (p < .001) and type 2 diabetes mellitus compared to type 1 diabetes mellitus (p < .001). Sulphonylureas alone or in combination with insulin varied during the study period (p = .01). The change in incidence of EMS for hypoglycemia was tracked during this period. However, causality has not been established.Death occurred in 240 people, 1.2 (interquartile range 0.2–2.7) years after their first event. After adjusting for age, mortality was higher in non-DM patients compared with DM patients (p < .001) but was not different between the two types of DM.

Conclusions

The population burden of EMS requiring hypoglycemia is high in both DM and non-DM patients, and imposes significant burden on medical resources. It is associated with long-term mortality.     

Fear of hypoglycemia and its predictive factors among diabetic pregnant women

ObjectiveThe purpose of the present study was to investigate the fear of hypoglycemia (FoH) and its predictors among diabetic pregnant women.Study designCross-sectional conducted between January to August 2022.MethodsIn the present study, 250 diabetic pregnant women from Qazvin province participated. Demographic and fertility characteristics, FoH, adherence to treatment, self-efficacy, anxiety and depression were assessed. Data were analyzed using univariable and multivariable linear regression models.ResultsThe participants’ mean age was 31.02 years (SD=4.72). The FoH mean score was 32.88 (out of 72). Based on the multivariable linear regression model, having a history of hypoglycemia (β = 0.44, p < 0.001), lower education (β = 0.17, p = 0.001), being treated with insulin (β = 0.22, p < 0.001), being treated with both insulin and diet (β = 0.16 p = 0.003), being of younger age (β = ?0.13, p = 0.008), and depression (β = 0.16, p = 0.002) were independent predictors of FoH among pregnant women.ConclusionDiabetic pregnant women experience FoH, particularly those with a history of hypoglycemia. Therefore, providing education and counseling concerning hypoglycemia, complications, and necessary measures for this group of diabetic pregnant women are needed along with those who are younger, less educated, and have comorbid mental health conditions.     

Effects of alcohol on plasma glucose and prevention of alcohol‐induced hypoglycemia in type 1 diabetes—A systematic review with GRADE

Because ethanol is thought to be a risk factor for severe hypoglycemia, patients with type 1 diabetes (T1D) are recommended to limit ethanol intake. However, little is known on how ethanol affects plasma glucose and how ethanol‐induced hypoglycemia can be prevented. In this study, we systematically reviewed the literature for ethanol effects on plasma glucose and for prevention strategies on ethanol‐induced hypoglycemia. Electronic searches on PubMed and Google were conducted in February 2017. Randomized clinical trials and observational studies were included. Studies involved patients with T1D with no history of ethanol abuse. The primary aims were changes in plasma glucose after ethanol intake and prevention strategies for ethanol‐induced hypoglycemia. Quality of the studies was assessed by GRADE. Additionally, we searched for guidelines from diabetes associations on their suggested prevention strategies. We included 13 studies. Eight studies reported that ethanol, regardless of administration intravenously or orally, were associated with an increased risk of hypoglycemia due to decrease in plasma glucose, impaired counter‐regulatory response, awareness of hypoglycemia, and cognitive function. Five studies did not report an increased risk of hypoglycemia. None of the studies investigated prevention strategies for ethanol‐induced hypoglycemia. Recommendations from 13 diabetes associations were included. All associations recommend that ethanol should only be consumed with food intake. The majority of included studies showed that ethanol intake increased the risk of hypoglycemia in patients with T1D. However, the evidence for how to prevent ethanol‐induced hypoglycemia is sparse, and further investigations are needed to establish evidence‐based recommendations.     

Randomized cross‐over trial comparing inpatient and outpatient administration of high‐dose cisplatin

Background/Aims: Treatment with high‐dose cisplatin (HDC) previously required inpatient (IP) admission with overnight hospitalization, but recently practice has shifted to outpatient (OP) therapy. We aimed to determine whether it is preferable to give HDC as an IP or OP using a two‐period cross‐over trial. Methods: Eligible patients were starting chemotherapy with ≥2 cycles of HDC (≥100 mg/dose) and were suitable for OP treatment. All patients received an IP cycle and OP cycle: the order was randomly allocated. Pre‐hydration, anti‐emetics and chemotherapy were identical for IP and OP. Post‐hydration varied by group (3 L normal saline (NS) for IP, 2 L NS for OP). The primary outcome was patient preference for IP versus OP treatment. Secondary outcomes included aspects of health‐related quality of life, adverse events (dose delays and reductions, elevated creatinine and unplanned readmissions) and resource use. Results: Fifty‐nine patients were randomized, 53 completed two cycles of HDC. Most patients preferred OP treatment (36 vs 13, P= 0.002). There were no significant differences in patients' ratings of nausea, vomiting, fatigue, anxiety, depression or overall quality of life. Adverse events were few and unrelated to IP versus OP treatment. Nursing time was longer for IP than OP (163 vs 104 min, P < 0.001). Conclusion: OP treatment was preferred by most patients, appeared safe and used less resources.     

Factors influencing the effectiveness of glucagon for preventing hypoglycemia

Background

Administration of small, intermittent doses of glucagon during closed-loop insulin delivery markedly reduces the frequency of hypoglycemia. However, in some cases, hypoglycemia occurs despite administration of glucagon in this setting.

Methods

Fourteen adult subjects with type 1 diabetes participated in 22 closed-loop studies, duration 21.5 ± 2.0 h. The majority of subjects completed two studies, one with insulin + glucagon, given subcutaneously by algorithm during impending hypoglycemia, and one with insulin + placebo. The more accurate of two subcutaneous glucose sensors was used as the controller input. To better understand reasons for success or failure of glucagon to prevent hypoglycemia, each response to a glucagon dose over 0.5 µg/kg was analyzed (n = 19 episodes).

Results

Hypoglycemia occurred in the hour after glucagon delivery in 37% of these episodes. In the failures, estimated insulin on board was significantly higher versus successes (5.8 ± 0.5 versus 2.9 ± 0.5 U, p < .001). Glucose at the time of glucagon delivery was significantly lower in failures versus successes (86 ± 3 versus 95 ± 3 mg/dl, p = .04). Sensor bias (glucose overestimation) was highly correlated with starting glucose (r = 0.65, p = .002). Prior cumulative glucagon dose was not associated with success or failure.

Conclusion

Glucagon may fail to prevent hypoglycemia when insulin on board is high or when glucagon delivery is delayed due to overestimation of glucose by the sensor. Improvements in sensor accuracy and delivery of larger or earlier glucagon doses when insulin on board is high may further reduce the frequency of hypoglycemia.