Diabetes mellitus is a prevalent chronic disease necessitating timely identification for effective management. This paper introduces a reliable, straightforward, and efficient method for the minimally invasive identification of diabetes mellitus through nanosecond pulsed laser-induced breakdown spectroscopy (LIBS) by integrating a state-of-the-art machine learning approach. LIBS spectra were collected from urine samples of diabetic and healthy individuals. Principal component analysis and an ensemble learning classification model were used to identify significant changes in LIBS peak intensity between the diseased and normal urine samples. The model, integrating six distinct classifiers and cross-validation techniques, exhibited high accuracy (96.5%) in predicting diabetes mellitus. Our findings emphasize the potential of LIBS for diabetes mellitus identification in urine samples. This technique may hold potential for future applications in diagnosing other health conditions.

Diabetes-associated focal myonecrosis is a rare complication seen in individuals with long-standing uncontrolled diabetes, characterized by inflammation and necrosis of a single or group of muscles. The exact cause of this condition is not well understood, but it is believed to be due to focal muscle infarction secondary to arteriosclerosis and diabetic microangiopathy. Diagnosis is challenging and often requires clinical examination, lab investigations, imaging, and EMG. Treatment is mainly supportive with pain control and tight glycemic control, and surgical intervention is rarely needed. The clinical presentation includes a sudden onset of localized pain and swelling in the affected muscle, which may be accompanied by fever, malaise, and weight loss. Diabetic myonecrosis exhibits a slightly higher prevalence in females and commonly manifests at an early stage. While the short-term prognosis is good, the recurrence rate is high, often affecting the opposite limb within six months. Our case describes a 35-year-old young male with uncontrolled diabetes mellitus, diagnosed one year ago, who presented with medial thigh pain and tenderness for the last two days. Due to his early disease, focal myonecrosis was not our first differential diagnosis. A CT scan with contrast revealed findings consistent with either focal myositis or infarction. We ruled out other causes, including infections, autoimmune disease, trauma, and medications, and in combination with the patient\'s uncontrolled diabetes mellites, a diagnosis of diabetes-associated focal myonecrosis was made. The patient improved with blood sugar control and supportive care, including nonsteroidal anti-inflammatory drugs and muscle relaxants.

Peyronie\'s disease (PD) is a connective tissue disorder that affects the penis and is characterized by abnormal collagen structure in the penile tunica albuginea, resulting in plaque formation and penile deformity. PD\'s overall prevalence is estimated at 3.2% to 8.9%, with rates as high as 20.3% among men with type 2 diabetes mellitus (DM). However, the characteristics of DM associated with PD complications remain unclear.
To explore clinical associations between DM characteristics and PD complications.
We conducted a retrospective analysis of patients with DM and PD who presented at our institution between 2007 and 2022. We examined patients\' clinical histories, DM- and PD-related clinical parameters, and complications. Penile deformities were assessed through physical examination, photographs, and penile Doppler ultrasound. Patients were categorized into subgroups based on age of DM onset: early (<45 years), average (45-65 years), and late (>65 years).
Outcomes included effects of DM characteristics on PD development, progression, and severity.
In total, 197 patients were included in the evaluation. Early-onset diabetes and elevated hemoglobin A1c (HbA1c) levels exhibited significant correlations with the early development of PD (ρ = 0.66, P < .001, and ρ = -0.24, P < .001, respectively). Furthermore, having DM at an early age was associated with the occurrence of penile plaque (ρ = -0.18, P = .03), and there were no significant differences in plaque dimensions (ρ = -0.29, P = .053). A rise in HbA1c levels after the initial PD diagnosis displayed positive correlations with the formation of penile plaque (ρ = 0.22, P < .006).
These findings emphasize the need for comprehensive assessments and personalized treatment strategies for individuals with DM and PD. Enhanced management approaches can improve outcomes for those facing both challenges.
Limitations include the single-site retrospective design with potential selection bias, inaccuracies in medical record data, and challenges in controlling confounding variables.
This study highlights that early-onset diabetes and poor diabetes control, as indicated by a subsequent rise in HbA1c levels following PD diagnosis, are significantly correlated with the onset and severity of PD. Revealing the mechanisms behind these findings will help us develop better management strategies for individuals with DM and PD.

This study investigates the relationship between vitamin D deficiency and uncontrolled type 2 diabetes mellitus (T2DM) indicated by elevated glycosylated hemoglobin (HbA1c) levels, alongside assessing the association between fasting C peptide levels and uncontrolled T2DM, considering their roles in β-cell function and insulin secretion. The study employs a cohort design, selecting individuals diagnosed with T2DM aged 18 years or older with baseline data on vitamin D, fasting C peptide, and HbA1c. Data were collected through electronic medical records and follow-up assessments at regular intervals. Binary logistic regression analyses were conducted to explore associations between exposure variables and uncontrolled T2DM. Significant associations were observed between vitamin D and C peptide levels with uncontrolled diabetes, with coefficients of -0.097 and -0.222, respectively. Higher vitamin D and C peptide levels are linked to a decreased likelihood of uncontrolled diabetes. In conclusion, there is a potential connection between vitamin D levels, C peptide levels, and uncontrolled diabetes mellitus (HbA1C > 7%), while higher levels of both vitamin D and C peptide appeared to correlate with a decreased likelihood of uncontrolled diabetes.

UNASSIGNED: Patients with uncontrolled type 2 diabetes mellitus (T2DM) require close follow-up, support, and education to achieve glycemic control, especially during the initiation or intensification of insulin therapy and self-care management. This study aimed to describe and evaluate the impact of implementing a hybrid model of in-person and telemedicine care and education on glycemic control for patients with uncontrolled T2DM (hemoglobin A1c [HbA1c] ≥9%) during the coronavirus disease pandemic.
UNASSIGNED: This prospective multicenter-cohort pre-/post-intervention study was conducted on patients with uncontrolled T2DM. This study included three chronic illness centers affiliated with the Family and Community Medicine Department at Prince Sultan Military Medical City in Riyadh, Saudi Arabia. A hybrid model of in-person (onsite) and telemedicine care and education was developed. This involved implementing initial in-person care at the physicians\' clinic and initial in-person education at the diabetes education clinic, followed by telemedicine services of tele-follow-ups, support, and education for an average 4-month follow-up period.
UNASSIGNED: Of the enrolled 181 patients, more than half of the participants were women (n = 103, 56.9%). The mean age of participants (standard deviation) was 58.64 ± 11.23 years and the mean duration of diabetes mellitus was 13.80 ± 8.55 years. The majority of the patients (n = 144; 79.6%) were on insulin therapy. Overall, in all three centers, the hybrid model had significantly reduced HbA1c from 10.47 ± 1.23% to 7.87 ± 1.59% (mean difference of reduction 2.59% [95% confidence interval (CI) = 2.34-2.85%], p < 0.001). At the level of each center, HbA1c was reduced significantly with mean differences of 3.17% (95% CI = 2.81-3.53%), 2.49% (95% CI = 1.92-3.06%), and 2.16% (95% CI = 1.76-2.57%) at centers A, B, and C, respectively (all p < 0.001).
UNASSIGNED: The findings showed that the hybrid model of in-person and telemedicine care and education effectively managed uncontrolled T2DM. Consequently, the role of telemedicine in diabetes management could be further expanded as part of routine diabetes care in primary settings to achieve better glycemic control and minimize nonessential in-person visits when appropriate.

Aim of our study was to report unusual presentation of mucormycosis in patients, who were recovered from COVID-19 infection. This was a prospective observational study, undertaken at Ravindra Nath Tagore Medical College, Udaipur, India, over a period of last 3 months (April-June 2021). All patients with maxillofacial and dental mucormycosis were included in the study. All patients either have COVID-19 infection or recovered from it. Eight (40%) patients had history of use of corticosteroids for COVID1-19 infection, fifteen patients had either known case of diabetes or newly diagnosed diabetes with uncontrolled blood sugar at the time of presentation, three (15%) patients were in pre-diabetic state with HbA1c between 6.0 and 6.5% and two patients had no diabetes. None of patients had diabetic ketoacidosis and only one patient reported complete loss of vision with dental symptoms. There was unusual presentation of mucormycosis in form of loosening of teeth in uncontrolled diabetes. Injudicious use of steroids and uncontrolled diabetes are two main risk factors, so eyes should be kept on both of these.

UNASSIGNED: Noncommunicable diseases are one of the main challenges that affect health worldwide and have been found to be increasing in both low- and middle-income countries compared with high-income countries. The aim of this study was to assess the impact of financial incentives and a comprehensive care program focusing on patients\' behavior and self-management of uncontrolled type 2 diabetes (glycosylated hemoglobin [HbA1c] ≥ 7), as well as modifiable risk factors for disease complications in a Saudi Arabian population.
UNASSIGNED: This quasiexperimental study, using a pre- and postevaluation approach, was used to compare the level of HbA1c among patients with uncontrolled diabetes before and after the financial incentives and comprehensive care program were implemented. Financial awards were given to patients who achieved a significantly greater decrease in HbA1c levels with his/her responsible physician. The study population included 702 Saudi Arabian patients with type 2 diabetes from 14 regions and 34 primary healthcare centers in the Kingdom of Saudi Arabia. All of these patients (≥ 15 years old) with uncontrolled type 2 diabetes who attended local primary healthcare centers in Saudi Arabia for a follow-up visit from February to October 2018.
UNASSIGNED: The mean age, in years, of the sample was 56.14 (± SD = 9.909); slightly more than half of the patients 401 (57.1%) were females. Most of the participants 645 (91.9%) were married, and 381(54.3%) patients were housewives. Linear mixed modeling revealed that all groups showed improvements over time in the primary outcome of HbA1c levels (p = 0.009), Including the secondary outcomes of body mass index and systolic and diastolic blood pressure (p = 0.04, < 0.001, 0.019 respectively).
UNASSIGNED: Patient behavior was improved, which was reflected by decreases in HbA1c, body mass index, and blood pressure levels. A comprehensive care program is recommended by healthcare providers to increase awareness among patients with diabetes to reduce other risk factors. These kinds of interventions positively motivate patients with diabetes to control their health measurements and to adopt a healthy lifestyle.

There is a paucity of predictive models for uncontrolled diabetes mellitus. The present study applied different machine learning algorithms on multiple patient characteristics to predict uncontrolled diabetes. Patients with diabetes above the age of 18 from the All of Us Research Program were included. Random forest, extreme gradient boost, logistic regression, and weighted ensemble model algorithms were employed. Patients who had a record of uncontrolled diabetes based on the international classification of diseases code were identified as cases. A set of features including basic demographic, biomarkers and hematological indices were included in the model. The random forest model demonstrated high performance in predicting uncontrolled diabetes, yielding an accuracy of 0.80 (95% CI: 0.79-0.81) as compared to the extreme gradient boost 0.74 (95% CI: 0.73-0.75), the logistic regression 0.64 (95% CI: 0.63-0.65) and the weighted ensemble model 0.77 (95% CI: 0.76-0.79). The maximum area under the receiver characteristics curve value was 0.77 (random forest model), while the minimum value was 0.7 (logistic regression model). Potassium levels, body weight, aspartate aminotransferase, height, and heart rate were important predictors of uncontrolled diabetes. The random forest model demonstrated a high performance in predicting uncontrolled diabetes. Serum electrolytes and physical measurements were important features in predicting uncontrolled diabetes. Machine learning techniques may be used to predict uncontrolled diabetes by incorporating these clinical characteristics.

UNASSIGNED: Blood glucose stability has recently been considered important in the treatment of diabetes. Both hypoglycemia and hyperglycemia can frequently occur in patients with diabetes undergoing hemodialysis. This study aimed to determine the usefulness of continuous glucose monitoring (CGM) for glycemic control and glycemic variability stabilization in patients with diabetes undergoing hemodialysis.
UNASSIGNED: Eighteen patients aged ≥18 years with type 1 or 2 diabetes and ≥3 months on hemodialysis at the Eulji Medical Center, Daejeon, Republic of Korea between November 2021 and May 2022 were included. Patients underwent 7 days CGM twice: the baseline study period (T0) and the follow-up study period (T1), at a 12 weeks interval. Physicians modified the treatment strategy according to the T0 results, and then patients conducted T1. As indicators of glycemic control, the mean glucose levels, glycated hemoglobin A1c (HbA1c), and time in range were measured. As indicators of glycemic variability, standard deviation (SD) and % coefficient variation (%CV) were measured.
UNASSIGNED: Data from 18 patients were analyzed. The mean glucose levels, HbA1c, SD, and %CV improved in T1 compared to T0 (P < 0.05). During T0, the mean glucose level was significantly lower on a day with hemodialysis than on a day without (P < 0.05), and SD and %CV were significantly higher on a day with hemodialysis than on a day without (P < 0.05). After the physicians modified the treatment according to the T0 results, there were no differences in the mean glucose levels, SD, and %CV between days with and without hemodialysis during T1.
UNASSIGNED: Continuous glucose monitoring could be a promising tool for individualizing treatment strategies in patients with diabetes undergoing hemodialysis.

UNASSIGNED: This study aimed to estimate the risk of cardiovascular disease (CVD) among patients with and without diabetes mellitus (DM) using the Framingham risk score (FRS) and to investigate the effect of DM control on CVD risk.
UNASSIGNED: A total of 2432 participants who had their glycosylated hemoglobin (HbA1c) measured within the last three months were included in this study. The study cohort was divided into three categories: non-diabetic, participants with controlled DM (HbA1c<7%), and uncontrolled DM (HbA1c≥7%). The World Health Organization\'s stepwise approach to chronic disease risk factor Surveillance-Instrument v2.1 was used in this study to collect the anthropometric and biochemical measurements. The Framingham Coronary Heart Risk Score (FRS) was used to calculate the 10-year cardiovascular risk (CVR). The groups were compared concerning the prevalence of metabolic, socioeconomic, and cardiac risks.
UNASSIGNED: Out of 2432 participants, 149 had controlled DM (6.1%), 286 had uncontrolled DM (11.8%), and 1997 participants were normoglycemic (82.1%). Compared to healthy participants, diabetic participants showed more high-risk characteristics across all CVR parameters. Uncontrolled diabetic patients had a graver laboratory and clinical profiles compared to the controlled DM group. As measured by FRS, nearly half of patients with controlled DM (49.9%) and two-thirds of patients with uncontrolled DM (63.3%) were classified as intermediate and high-risk compared to 4.6% of the healthy participants. Compared to healthy participants, patients with controlled DM showed a threefold increased CVR (OR = 3.02, 95% C.I. = 1.41-7.24) while this risk catapulted to 13 times among those with uncontrolled DM (OR = 13.57, 95% C.I. = 6.99-26.36).
UNASSIGNED: Participants with DM are at moderate to high CVR. Individuals with uncontrolled DM showed higher CVR profiles as measured by FRS and have a higher prevalence of obesity, unhealthy diet, and physical inactivity.