Average Glucose Research Articles

Presumptive Identification of Clinically Significant Hemoglobin Variants Hb E, Hb S, Hb D in Hb A1c Capillary Electrophoresis.

The quantitation of glycated hemoglobin (Hb A1c) represents an average blood glucose level for a period of 2 to 3 months for diagnosing, monitoring, and managing diabetes mellitus. Unreliable results are reported when hemoglobin (Hb) variants are present in the sample. Patients are advised to use an alternate method due to the presence of the variant Hb and a reflex test to Hb electrophoresis to obtain precise information about the Hb variant. The present study utilizes x axis values from Hb A1c capillary electrophoresis (CE) to identify clinically significant Hb variants Hb E, S, and D. Patient samples (n = 60) that showed a variant peak in the Hb A1c test with an x axis value of 190 to 240 were selected for the study. The migration position of the Hb variant (x axis value) and variant percent of the Hb A1c test were compared with the x axis value and variant percent in the Hb electrophoresis test to presumptively identify the variants. The identity of the variants was confirmed using mass spectrometry (MS). Out of 60 samples, 20 samples were identified as Hb E (x axis 225-227), 20 samples were identified as Hb S (x axis 210-214), and 18 samples were identified as Hb D-Punjab (x axis 200-201). Two variants with an x axis value of 194 were identified as an α variant Hb Q India using MS. There is an overall negative shift of the x axis (-1 to -13 units) and a lower variant percent (-0.2% to -8.7%) in Hb A1c CE when compared with Hb electrophoresis. The present study highlights the significance of the x axis value and variant percent to identify clinically significant Hb variants in the Hb A1c CE test.

A reduced carbohydrate diet improves glycemic regulation in hyperglycemic older people in a retirement home: the SAGE study.

Poor glucose regulation associated with gradual insulin resistance is a significant risk factor in several age-related chronic diseases. An eating plan that promotes a lower carbohydrate intake may have a beneficial effect on glucose metabolism. This study aimed to evaluate how a diet reduced in carbohydrate by 32% (RCHO) over a 2 month period would influence the metabolic profile of older individuals (N=24) living in a retirement home (RH). A continuous glucose monitor was used to measure blood glucose during four periods: the standard diet before (baseline) and after (washout) the intervention, during the 4 initial days of the RCHO diet (RCHO-early), and the final days of the 2 month intervention (RCHO-end). The blood metabolic profile was also measured (glucose, ketones, insulin, triglycerides, and cholesterol). RCHO intake decreased average blood glucose compared to the standard diet in hyperglycemic participants: RCHO-early 7.8±1.0vs 7.5±1.1mM (p=0.012) and RCHO-end 7.8±1.0vs 7.0±0.9mM (p=0.050). In the hyperglycemic participants, the percentage of time spent in hyperglycemia (>10.0mM) decreased by 50% during the RCHO-early (p=0.012) and by 66% at RCHO-end (p =0.021) compared to baseline. Glycated hemoglobin was significantly lower at RCHO-end in both hyperglycemic and normoglycemic participants compared to baseline (p<0.008). Plasma ketones increased threefold in hyperglycemic participants at RCHO-end compared to baseline (p<0.028). This study shows that an RCHO diet has metabolic health benefits in an older population and confirms its safety, tolerability, and acceptability in an RH (NCT06022094).

The Effect of COVID-19 Lockdown Among Adolescents with Type 1 Diabetes: A Systematic Review and Meta-Analysis.

The aim of this study was to assess how the lockdown of the COVID-19 pandemic had affected the glycaemic control of adolescents aged 10-19 with type 1 diabetes. A comprehensive search of literature was performed in PubMed, Scopus, Web of Science, and ProQuest. Published articles up to September 2022 were included. The Glucose Monitoring Index (GMI) and HbA1c level were defined as outcome variables. Average glucose level was found to be a common variable in both HbA1c levels and GMI; therefore, HbA1c and GMI were converted to average glucose (mg/dL) using appropriate formulas. Studies reported the outcomes in two or three periods (pre-lockdown, lockdown, and post-lockdown) were included in the analysis. A paired wise meta-analysis was performed among the studies that reported all three periods. Homogeneity across studies was assessed using I2 statistic. Fourteen studies were included in the study. The pooled average glucose during the lockdown decreased to 166.9 mg/dL (95% CI, 153.78, 180.02) from 205.793 mg/dL (95% CI, 188.412, 223.173) during the pre-lockdown period, then it increased to 204.23 mg/dL (95% CI, 186.17, 222.29) during the post-lockdown period. A paired wise meta-analysis indicated a reduction in average glucose levels. However, it was not statistically significant, possibly due to the small number of studies that reported data from all three periods. Although the descriptive analysis of our study showed that the lockdown had affected (decreased) the average glucose level among adolescents with type 1 diabetes, this was not statistically significant in the pooled analysis.

A-063 Correlation of 1,5-anhydroglucitol (AG) with A1c: understanding this relationship in terms of an established physiological model for AG mass balance as a function of [glucose

Abstract Background Diet-derived 1,5-anhydroglucitol (AG) is an unmetabolizable glucose analogue present in plasma (reference interval: 7.4-32.5 µg/mL). In diabetes, hyperglycemia can accelerate AG excretion, producing an inverse relationship between A1c and AG. There are no established guidelines regarding use or interpretation of AG in diabetes, but it is often described as being useful for detection of short-term variation in [glucose]. We examined AG usage at our institution, and, additionally, analyzed the information content of AG as derived from an established model for the relationship between AG and [glucose]. Methods Medical records were scanned for all combined orders for AG and A1c between September 2020 and August 2023. Estimated average glucose (eAG) was calculated from A1c [PMID: 18540046]. AG vs. A1c data were compared to calculations for AG vs. eAG using an established physiological model for AG mass balance [PMID: 9357814]. Results Among 104 AG measurements, there were 93 AG/A1c measurement pairs (see Figure). 70% had elevated A1c (n=65). 43% had decreased AG (n=40), all with elevated A1c. Among all AG/A1c pairs, 66% (closed points; n=61) were within the boundaries of model calculations for AG when assuming a simple steady-state [glucose] equal to eAG, a normal glomerular filtration rate, and a normal AG ingestion rate. AG outside of these boundaries (34%; open points, n=32) were almost entirely above the upper boundary (32%; n=30), where results are consistent either with increased AG ingestion rate, decreased glomerular filtration rate, or a discrepancy between eAG and A1c. Only two points (2.2%) were compatible with interpretation of variation in prevailing glucose from eAG. Conclusions For our data, paired AG/A1c measurements were in majority well characterized by a physiological model based simply on steady-state (invariant) [glucose] equal to eAG as derived from A1c alone. Only a small fraction of AG results suggested possible variation in [glucose].

A-037 A1c by separation and enzymatic methods: what's the difference?

Abstract Background Accurate values for hemoglobin A1c (HbA1c) are crucial for diagnosing and monitoring diabetes mellitus. Two common methods to measure HbA1c are capillary electrophoresis (CE) and immunoassay (IA). Many methods used to measure HbA1c are prone to interferences from hemoglobin variants and abnormalities affecting the red blood cell’s (RBC) turnover. Consequently, the average estimated glucose levels using the HbA1c value can be unreliable in diabetics with hemoglobinopathies and other RBC lifetime disorders. Separation methods such as CE can capture hemoglobinopathy information, while IA methods may not. We performed this study in a population with relatively high levels of hemoglobin disorders to evaluate the performance of HbA1c testing on the Alinity platform (IA) against the Sebia Capillarys 3 Tera instrument (CE). Methods Samples were identified retrospectively based on a search of the Electronic Medical Record for all patients with an ordered and resulted HbA1c and complete blood count in the Montefiore Medical Center the day prior to sampling. Routine HbA1c testing was performed by an Abbott Immunoassay method on the Abbott Alinity Instrument and CBC results were obtained from a Sysmex XN2100 instrument. Records were compared by patient name, medical record number, and sample collection time to identify all patients with CBC and HbA1c drawn within one hour of each other. Those samples were retrieved from storage (a 4° automated refrigerator) within 48 hours of draw and tested via the Sebia Capillarys 3 Tera instrument using HBA1c kits. Results In this large representative population study (N=2075), there was overall excellent agreement between IA and CE. The correlation coefficient (R2) of the whole dataset was 0.989, with an average bias of 2.7% between the two methods. Additional analysis was performed on those with possible RBC turnover disorder (patients with RBC counts below 4x106/uL or above 6x106/uL, MCVs above 96 fL or below 80 fL, RDW above 17%, or abnormal A2 value: total of 638 samples), those with a hemoglobin variant as detected by the Capillarys 3 instrument (162 samples), or with a measurable hemoglobin F value detected by the Capillarys 3 instrument (37 samples). Samples were sorted into these groups independently and thus there was significant overlap between groups, notably with 23 of 37 samples with elevated HbF also having a hemoglobin variant. In both the RBC disorder and hemoglobinopathies group, similar low bias and high correlations were seen. The elevated F samples showed a clear negative bias (5.6%) for all patients on the IA method as compared with CE. The IA method states that samples with HbF above 5% should not be tested. However, as this is not a separation method, there is no way to test samples for HbF before analysis, and bias was seen for samples below 5%. Conclusions The IA and CE methods showed similar performance across patients regardless of RBC lifetime or hemoglobin disorder status, though presence of HbF is a potential interference and should be considered. Further questions remain for these instruments in terms of correlation with average glucose levels as calculated through CGM instruments.

Utilization of Smart Healthcare for Gestational Diabetes Mellitus Management

Gestational diabetes mellitus (GDM) poses significant health risks to both mothers and newborns, requiring rigorous self-management and frequent medical consultations. Advances in information and communications technology (ICT) have shown promising results in reducing the number of in-person visits for GDM management. ICT enhances patient self-care engagement, with some studies reporting reductions in average blood glucose and HbA1c levels. ICT for GDM management has demonstrated benefits such as fewer in-person visits, improved adherence to self-monitoring of blood glucose, increased global user satisfaction, and maintenance of blood glucose control and perinatal outcomes. Common barriers to ICT for GDM include technological literacy, inadequate education, limited technical support, the additional burden of non-customized applications, and restricted interoperability. Further research is needed on the impact of technology on GDM management to optimize digital health solutions.

Evaluating HbA1c-to-average glucose conversion with patient-specific kinetic models for diverse populations.

The discrepancy between estimated glycemia from HbA1c values and actual average glucose (AG) levels has significant implications for treatment decisions and patient understanding. Factors contributing to the gap include red blood cell (RBC) lifespan and glucose uptake into the RBC. Personalized models have been proposed to enhance AG prediction accuracy by considering interpersonal variation. This study contributes to our understanding of personalized models for estimating AG from HbA1c. Utilizing data from seven studies (340 participants), including Hispanic/Latino populations with or at risk of non-insulin-treated type 2 diabetes (T2D), we examined kinetic features across cohorts. Additionally, the study simulated scenarios to understand data requirements for improving accuracy. Personalized approaches improved agreement between AG estimations and CGM-AG, particularly with four or more weeks of training CGM data. A multiple linear regression model using kinetic parameters and added clinical features was shown to improve the accuracy of personalized models further. As CGM usage extends beyond type 1 diabetes, there is growing interest in leveraging CGM data for clinical decision-making. Patient-specific models offer a valuable tool for managing glycemic status in patients with discordant HbA1c and AG values.

Relationship Between Average Glucose Levels and HbA1c Differs Across Racial Groups: A Substudy of the GRADE Randomized Trial.

To determine whether the relationship between average glucose (AG) levels and hemoglobin A1c (HbA1c) differs across racial/ethnic groups. We performed a prospective substudy of GRADE, a comparative effectiveness randomized trial conducted in 36 centers in the U.S. A total of 1,454 of the 5,047 participants in the GRADE cohort, including 534 non-Hispanic White (NHW), 389 non-Hispanic Black (NHB), and 327 Hispanic White patients and 204 patients of other racial/ethnic backgrounds, were included in the substudy. Continuous glucose monitoring (CGM) performed for 10 days was used to calculate AG10. Immediately after CGM, HbA1c and glycated albumin were measured. Fasting plasma glucose (FPG) and glucose area under the curve (AUC) were derived from a 75-g oral glucose tolerance test. The relationship between AG10 and HbA1c was significantly different for NHB compared with NHW patients and those of other racial/ethnic groups. HbA1c levels were 0.2-0.6 percentage points higher in NHB than in NHW patients for AG10 levels from 100 to 250 mg/dL. For an HbA1c of 7%, AG10 was 11 mg/dL higher for NHW than for NHB patients. Similar findings were observed across races for relationships of FPG and AUC with HbA1c and for glucose measurements with glycated albumin levels. Differences in the relationship between AG10 and HbA1c across racial groups remained after adjustments for any demographic or other differences between racial/ethnic subgroups. The relationship between several measures of glucose with HbA1c and glycated albumin consistently differed across races. These findings should be considered in setting treatment goals and diagnostic levels.

Data Management Analysis for Predicting Stroke using RapidMiner

Stroke are known as the second most leading cause of death. Because of this, data mining techniques are already being used to predict patients that may have stroke. Therefore, we are doing a study to try using data mining techniques using RapidMiner to find information or patterns regarding stroke from a dataset obtained from Kaggle. Three data mining techniques are used in this study, that is classification using decision trees, association rule using FP-Growth algorithm, and clustering technique using k-Means algorithm. Using RapidMiner, we are able to process the dataset using the operators provided in the application. As the result, we found out that due to an unbalanced data, the decision tree model made were only able to predict 68,75% patients as having stroke. With the association rule technique, we found out that most attributes in the dataset does not really associated with each other. With the clustering technique, we were able to group up patients and found out that most patients that have stroke are averaged in the age of 58, with 31 bmi, and 201 average glucose level.

The glycemic gap as a prognostic indicator in cardiogenic shock: a retrospective cohort study

BackgroundStress-induced hyperglycemia (SIH) is associated with poor outcomes in cardiogenic shock (CS), and there have been inconsistent results among patients with or without diabetes mellitus (DM). The glycemic gap (GG) is derived by subtracting A1c-derived average glucose from blood glucose levels; it is a superior indicator of SIH. We aimed to explore the role of GG in the outcomes of patients with CS.MethodsData on patients diagnosed with CS were extracted from the MIMIC-IV v2.0 database to investigate the relationship between GG and 30-day mortality (Number of absolute GG subjects = 359; Number of relative GG subjects = 357). CS patients from the Second Affiliated Hospital of Wenzhou Medical University were enrolled to explore the correlation between GG and lactic acid (Number of absolute GG subjects = 252; Number of relative GG subjects = 251). Multivariate analysis, propensity score-matched (PSM) analysis, inverse probability treatment weighting (IPTW), and Pearson correlation analysis were applied.ResultsAbsolute GG was associated with 30-day all-cause mortality in CS patients (HRadjusted: 1.779 95% CI: 1.137–2.783; HRPSM: 1.954 95% CI: 1.186–3.220; HRIPTW: 1.634 95% CI: 1.213–2.202). The higher the absolute GG level, the higher the lactic acid level (βadjusted: 1.448 95% CI: 0.474–2.423). A similar trend existed in relative GG (HRadjusted: 1.562 95% CI: 1.003–2.432; HRPSM: 1.790 95% CI: 1.127–2.845; HRIPTW: 1.740 95% CI: 1.287–2.352; βadjusted:1.294 95% CI: 0.369–2.219). Subgroup analysis showed that the relationship existed irrespective of DM. The area under the curve of GG combined with the Glasgow Coma Scale (GCS) for 30-day all-cause mortality was higher than that of GCS (absolute GG: 0.689 vs. 0.637; relative GG: 0.688 vs. 0.633). GG was positively related to the triglyceride-glucose index. Kaplan–Meier curves revealed that groups of higher GG with DM had the worst outcomes. The outcomes differed among races and GG levels (all P < 0.05).ConclusionsAmong patients with CS, absolute and relative GGs were associated with increased 30-day all-cause mortality, regardless of DM. The relationship was stable after multivariate Cox regression analysis, PSM, and IPTW analysis. Furthermore, they reflect the severity of CS to some extent. Hyperlactatemia and insulin resistance may underlie the relationship between stress-induced hyperglycemia and poor outcomes in CS patients. They both improve the predictive efficacy of the GCS.

Effect of Infection on the Incidence of Hyperglycemic Hemichorea: A Case-Series.

To explore the effect of infection on hyperglycemic hemichorea. The clinical data of 11 patients with hyperglycemic hemichorea admitted to the Affiliated People' s Hospital of Xinxiang Medical College and the Second People's Hospital of Xinxiang were retrospectively analyzed, including gender, age, clinical symptoms, imaging features, blood glucose, glycated hemoglobin, infection indicators, and treatment conditions. Eleven patients had acute or sub-acute onset, including 9 females and 2 males, with an average age of 74.55 years. Nine patients presented with unilateral limb involuntary movement and 2 patients presented with bilateral limb involuntary movement. Imaging findings of 9 patients showed abnormalities in the basal ganglia region. Random blood glucose levels were all elevated at admission, with an average blood glucose value of 26.20 mmol/l. Urine ketone bodies were positive in 2 patients, inflammatory indexes were elevated in 7 patients, symptoms of hypoglycemic treatment and anti-infection treatment in 10 patients disappeared, and symptoms of 1 patient disappeared after improved microcirculation treatment. The disease tends to occur in middle-aged and elderly women, and the blood glucose may fluctuate significantly during the onset. Infection may lead to the occurrence and development of the disease. Active control of blood sugar, inflammation and improvement of brain metabolism can effectively control symptoms and prevent recurrence.

The Effect of Aerobic Exercise Frequency on Reducing Blood Glucose in Type 2 Diabetes Mellitus Sufferers in the Lingsar Health Center Working Area in 2024

One of the keys to a person suffering from diabetes mellitus being able to live a healthy life like other people without diabetes is to maintain balanced blood glucose levels within normal limits. One important way to reduce blood glucose levels, especially in type 2 DM sufferers, is exercise. This study aims to identify the effect of aerobic exercise, on changes in blood glucose levels. This research is a pre-experimental research with a one group pre-posttest approach. The research sample was 33 people suffering from type 2 DM at the Lingsar Community Health Center, selected using a simple random sampling technique. Each respondent was given aerobic exercise 3 times a week with a minimum duration of 20 minutes. Data on blood glucose levels before and after the intervention were collected using an observation sheet. The results of the study showed that the average blood glucose before the intervention was 162.2 mg/dL and after the intervention it fell to 156.14 mg/dL. The t-test with a=0.05 showed r=0.000. It can be concluded that there is an effect of aerobic exercise on the respondents' blood glucose levels. Aerobic exercise has been proven to reduce the average blood glucose level after this is done regularly. This study results can be an evidenced base for community nursing to promote regular aerobic exercise among people with DM, to help reduce or control their blood glucose.

Investigating the Prevalence of Autonomic Neuropathy in Diabetic Patients with Urinary Irritation Symptoms Without a Known Cause.

Evaluating pseudomotor performance can be a valuable tool for investigating the peripheral autonomic nervous system in diabetic patients. Sudoscan, a simple and non-invasive method for assessing pseudomotor performance, has been developed in recent years. This study aimed to investigate autonomic neuropathy using Sudoscan in diabetic patients with lower urinary tract symptoms (LUTS) of unknown cause. In this cross-sectional study conducted from April 2022 to April 2023, we included 195 patients with type 2 diabetes who were referred to the urology clinic. We extracted demographic, clinical, and laboratory data from the patient files and evaluated urinary symptoms using the International Prostate Symptom Score (IPSS) questionnaire. Patients underwent Sudoscan testing to evaluate autonomic neuropathy in the physical medicine and rehabilitation clinic. To further assess urinary irritative symptoms, patients underwent urodynamic studies (UDS) and ultrasonography. The Sudoscan test results showed that autonomic neuropathy was present in 77 patients (40%), with 43 (22.1%) having moderate and 44 (22.6%) having severe neuropathy. Patients with autonomic neuropathy were found to be older, had longer diabetes durations, higher average blood glucose levels, and higher creatinine levels. Additionally, we found a significant correlation between autonomic neuropathy and signs of high post-void residue on ultrasound and detrusor contraction disorders on UDS (p-value < 0.05). Our study found a higher prevalence of autonomic neuropathy in diabetic patients with LUTS using Sudoscan (40%). Longer diabetes duration and poor glycemic control were associated with an increased risk of autonomic neuropathy linked with LUTS, such as urge incontinence.

Value of Glycemic Indices for Delayed Cerebral Ischemia after Aneurysmal Subarachnoid Hemorrhage: A Retrospective Single-Center Study.

Delayed cerebral ischemia (DCI) is a severe complication following aneurysmal subarachnoid hemorrhage (aSAH), linked to poor functional outcomes and prolonged intensive care unit (ICU) stays. Timely DCI diagnosis is crucial but remains challenging. Dysregulated blood glucose, commonly observed after aSAH, may impair the constant glucose supply that is vital for brain function, potentially contributing to DCI. This study aimed to assess whether glucose indices could help identify at-risk patients and improve DCI detection. This retrospective, single-center observational study examined 151 aSAH patients between 2016 and 2019. Additionally, 70 of these (46.4%) developed DCI and 81 did not (no-DCI). To determine the value of glycemic indices for DCI, they were analyzed separately in patients in the period before (pre-DCI) and after DCI (post-DCI). The time-weighted average glucose (TWAG, p = 0.024), mean blood glucose (p = 0.033), and novel time-unified dysglycemic rate (TUDR140, calculated as the ratio of dysglycemic to total periods within a glucose target range of 70-140 mg/dL, p = 0.042), showed significantly higher values in the pre-DCI period of the DCI group than in the no-DCI group. In the time-series analysis, significant increases in TWAG and TUDR140 were observed at the DCI onset. In conclusion, DCI patients showed elevated blood glucose levels before and a further increase at the DCI onset. Prospective studies are needed to confirm these findings, as this retrospective, single-center study cannot completely exclude confounders and limitations. In the future blood glucose indices might become valuable parameters in multiparametric models to identify patients at risk and detect DCI onset earlier.

Stress hyperglycemia ratio and its influence on mortality in elderly patients with severe community-acquired pneumonia: a retrospective study

BackgroundCommunity-acquired pneumonia (CAP) is a significant health issue among the elderly, with severe cases (SCAP) having high mortality rates. This study assesses the predictive significance of the stress hyperglycemia ratio (SHR) in elderly SCAP patients and its impact on outcomes in both diabetic and non-diabetic patients.Methods and materialsThis retrospective study included 406 SCAP patients aged 65 or older from the Second People’s Hospital of Lianyungang (January 2020 to December 2023). Data collected included demographics, medical history, vital signs, and lab results. SHR was calculated from initial blood glucose and estimated average glucose (HbA1c). Statistical analyses, including Cox regression and Kaplan-Meier analysis, evaluated SHR’s impact on mortality. Mediation models explored the effects of neutrophil-lymphocyte ratio (NLR) and SHR.ResultsThe 28-day mortality rate was 21.67%. Deceased patients had higher age, Charlson Comorbidity Index, procalcitonin, NLR, glucose, and SHR levels compared to survivors (P < 0.05). Both SHR and NLR significantly increased mortality risk, particularly in non-diabetic patients. Combining NLR and SHR improved ROC AUC to 0.898, with 89.80% sensitivity and 81.10% specificity. Kaplan-Meier analysis showed higher cumulative survival for SHR < 1.14, regardless of diabetes status (P < 0.05). NLR mediated 13.02% of the SHR-survival relationship, while SHR mediated 14.06% of the NLR-survival relationship.ConclusionElevated SHR is a significant mortality risk factor in elderly SCAP patients, independent of diabetes status. Stringent glucose control and careful monitoring of SHR may improve outcomes in elderly patients with acute respiratory conditions.

Adverse Effects of Gliptins in Type 2 Diabetics in Morocco.

Gliptins are a relatively recent class of oral antidiabetic agents used in the treatment of type 2 diabetes. The aim of this study is to identify the adverse effects of gliptins in patients with type 2 diabetes, compare the tolerability of these drugs with data from the literature, and determine patients' behavior in the face of these adverse effects with a view to optimizing their management. Our study is cross-sectional, descriptive, and analytical, involving 100 patients aged over 20 years, followed at the Endocrinology Department of the Military Hospital Mohammed V. The average age of the patients was 63 years, with a sex ratio F/H of 1.13. The median age of diabetes in the patients was 13 years, with an average blood glucose level of 1.64 and an average hemoglobin A1c of 8.26. The comorbidities were 30% cardiovascular disease, 25% hypertension, and 14% dyslipidemia, and 30% of patients had no comorbidities. Forth-six percent of patients reported adverse events and 54% did not report any adverse event. Twenty-eight percent of the adverse events were gastrointestinal, 18% skin disorders, 14% urinary tract infections, 12% hypoglycemia, 12% nervous system disorders, 8% airway infections, and 8% general disorders. This study shows that gliptins remain a safe option as the side effects seem fairly well tolerated by patients. Adverse events may impact patient compliance and pose a problem of adherence to treatment. Thus, it would be advantageous to develop therapeutic education for diabetic patients to detect and manage adverse effects.

An explainable Artificial Intelligence software system for predicting diabetes

Implementing diabetes surveillance systems is paramount to mitigate the risk of incurring substantial medical expenses. Currently, blood glucose is measured by minimally invasive methods, which involve extracting a small blood sample and transmitting it to a blood glucose meter. This method is deemed discomforting for individuals who are undergoing it. The present study introduces an Explainable Artificial Intelligence (XAI) system, which aims to create an intelligible machine capable of explaining expected outcomes and decision models. To this end, we analyze abnormal glucose levels by utilizing Bi-directional Long Short-Term Memory (Bi-LSTM) and Convolutional Neural Network (CNN). In this regard, the glucose levels are acquired through the glucose oxidase (GOD) strips placed over the human body. Later, the signal data is converted to the spectrogram images, classified as low glucose, average glucose, and abnormal glucose levels. The labeled spectrogram images are then used to train the individualized monitoring model. The proposed XAI model to track real-time glucose levels uses the XAI-driven architecture in its feature processing. The model's effectiveness is evaluated by analyzing the performance of the proposed model and several evolutionary metrics used in the confusion matrix. The data revealed in the study demonstrate that the proposed model effectively identifies individuals with elevated glucose levels.

Evaluation of High-dose versus Standard-dose of Dexamethasone on Mortality among the Mechanically Ventilated COVID-19 Patients.

Anti-inflammatory agents like dexamethasone (DEX) are a mainstay of treatment for COVID-19. Despite randomized trials demonstrating that a 6 mg daily dose of DEX improved patient outcomes in hospitalized COVID-19 patients receiving oxygen, clinicians often prescribe higher doses of corticosteroids without evidence to support this practice. The purpose of this study was to compare outcomes of ventilated COVID-19 patients who received standard dose (SD) versus high dose (HD) DEX. This was a multi-site, retrospective, observational study on ventilated COVID-19- positive patients who received DEX for at least three days between June 1, 2020, and January 31, 2022. The primary outcome of this study was the association between mortality and SD (<6 mg daily) versus HD (>10 mg daily) DEX in ventilated COVID-19 patients. Secondary outcomes included average blood glucose (BG), number of BG readings above 200, incidence of bacterial nosocomial infection, ventilator-free days, length of stay (LOS), and ICU LOS. Of the 212 included patients, 53 (25%) received SD DEX, and 159 (75%) received HD DEX. There was no significant effect of DEX dose on mortality, number of BG readings >200, incidence of nosocomial infections, LOS, or ventilator-free days (p >0.05). After controlling for confounding factors, no difference in mortality persisted (OR 1.34 95% CI 0.62- 2.90). Average daily BG and ICU LOS were significantly greater in the HD group compared to the SD group (p = 0.003, p = 0.019, respectively). There was no association between HD DEX and mortality among ventilated COVID- 19 patients compared to SD DEX. Moreover, HD DEX is associated with detrimental effects such as prolonged ICU LOS and higher average daily BG. This study supports the use of SD DEX in ventilated COVID-19 patients.

Effectiveness of Blood Glucose Time in Range to Reduce Risk of Blood Glucose Extrusion and Improve Blood Glucose Metrics in Type 1 Diabetic Patients.

With evolving diabetes technology, continuous glucose monitoring (CGM) and time in range have been advanced as critical measurements to assess complications. They have shown improvement in A1C levels and decreased episodes of blood glucose extrusion. This study aimed to assess the awareness and utilization of blood glucose time in range and its effectiveness in reducing the risk of blood glucose extrusion and improving blood glucose metrics among patients with type 1 diabetes mellitus. A retrospective study included 342 patients who met the inclusion criteria and were using the CGM, aiming for a TIR of 70% daily. Glycemic control was followed using TIR data, blood glucose extrusion frequency (including hyperglycemia and hypoglycemia events), active sensor time, average blood glucose, and glucose management indicator (GMI) levels. A total of 342 individuals participated in this study, the majority of whom were below 18 years of age (62.3%). The hypoglycemic frequency was significantly increased compared to the baseline, and most participants experienced hypoglycemia events (p = 0.0001). The incidences increased over time, with 90.9% and 93% having hypoglycemia at 60 and 90 days (p = 0.0001), respectively. The active scan and sensor time were not followed, which led to the blood glucose target not being achieved, with no improvement throughout the study. Consequently, no improvement occurred in glycemic control. CGM technology has been promising and proven effective in improving glycemic. However, our study did not show these benefits as expected, which could be explained by the underutilization and improper use of the CGM.

The Effect of Healthy Boba Pearl Drink on Post-Prandial Glucose

This study was a randomized controlled trial using a repeated experimental design with a pre-test and a post-test control group. The study subjects were women of childbearing age, aged 20‒30 years, with no diagnosed chronic diseases and with baseline fasting blood glucose levels less than 125 mg/dL. Participants were randomly assigned to treatment and control groups. The treatment group received 350 mL of healthy boba drink, while the control group received 350 mL of commercial boba drink. The healthy boba drink was made by mixing 67 mL of fresh milk, 133 mL of soy milk, 1 g of stevia sweetener, 100 g of red dragon fruit, and 40 g of healthy boba pearls. It contained 215 kcal of energy, 8.82 g of protein, 8.90 g of fat, 30.78 g of carbohydrate, and 1,808 g of fiber. Each group had an initial fasting blood glucose levels measurement before the intervention, and postprandial glucose levels were measured at the end of the intervention (one time of intervention). The collected data were analyzed univariately to analyze the effect of treatment on postprandial glucose using the independent t-test. The result indicated that the subjects in the treatment group and 96.2% of the subjects in the control group had fasting glucose levels less than 126 mg/dL. Both participants in the control and treatment groups had postprandial glucose levels less than 200 mg/dL. The mean glucose level was 89.49 mg/dL in the treatment group and 92.57 mg/dL in the control group. The study results showed that the treatment group that consumed the healthy boba drink had a lower average postprandial glucose level than the control group. The statistical test results showed that there was a significant effect of healthy boba drink consumption on postprandial glucose levels in the treatment group (p&lt;0.000). It is concluded that the healthy boba drink intervention had a significant effect (p&lt;0.000) on lowering blood glucose by 5.82 mg/dL after the initial treatment. The results of this study are a major first step for future work to develop a healthier boba drink.