Abundant evidence suggests that sleep is closely associated with metabolic diseases. However, studies focusing on sleep patterns in relation to metabolic comorbidities defined as the coexistence of obesity, type 2 diabetes mellitus (T2DM), hypertension, dyslipidemia, hyperuricemia, and non-alcoholic fatty liver disease (NAFLD) remain limited. This study aimed to explore the association between sleep patterns and both metabolic comorbidities and individual metabolic diseases using novel analytical methods.

A total of 4,970 participants was included. Four sleep-related factors and six metabolic diseases were examined. Multiple correspondence analysis (MCA), K-means clustering, logistic regression, and subgroup analysis were applied to assess associations between sleep patterns and metabolic conditions.

MCA and clustering of sleep factors identified three categories of sleep patterns: good sleep pattern (GSP), intermediate sleep pattern (ISP), and poor sleep pattern (PSP). Within the PSP group, 77.9% had a late bedtime, 83.7% reported poor or very poor sleep quality, 90.4% slept fewer than 7 h per night, and 29.1% snored. After adjusting for sex, age, and other confounders, PSP was associated with a 34.5% higher odds of metabolic comorbidities compared with GSP, with an even stronger association observed in men (51.9%). ISP was not associated with metabolic comorbidities overall, but was associated with increased odds of T2DM (19.4%) and NAFLD (23.4%). Specific sleep factors, including consistently having a late bedtime and snoring, were associated with higher odds of metabolic comorbidities by 67.7% [OR (95%CI): 1.677 (1.059-2.658)] and 46.4% [OR (95%CI): 1.464 (1.179-1.819)], respectively. Mediation analysis indicated that body mass index (BMI) explained only 31.58% of the total effect of sleep patterns on comorbidity risk in men.

Sleep factors aggregated into three prevalent sleep patterns, with strong internal correlations observed within each pattern. PSP was associated with increased odds of metabolic comorbidities, with this association being pronounced in all participants and men. Notably, BMI served as a partial mediator of this relationship in the male subgroup. ISP showed significant associations with T2DM and NAFLD, highlighting their clinical relevance. These findings emphasize the role of sleep in metabolic health and support the need for longitudinal sleep interventions and strategies to improve sleep conditions.

Scheuermann's disease always occurs in adolescent, and it is uncommon for elderly individuals. The aim of this research is to investigate the different potential pathogenic mechanisms and clinical characteristics of thoracolumbar disc herniation (TLDH) in Scheuermann's disease between elderly and adolescent patients.

We retrospectively analyzed data from patients with Scheuermann's disease who underwent surgical treatment for TLDH from a single center between June 2013 and June 2023. Patients were divided into two groups: elderly (≥ 65 years) and adolescent (≤ 20 years), with 24 patients in each group. Data, including medical records and imaging parameters, were independently collected and analyzed by two doctors.

The elderly group exhibited significantly lower preoperative modified Japanese Orthopaedic Association (mJOA) scores (5.58 ± 2.38 vs. 7.25 ± 2.19, P = 0.009) and longer symptom duration (48.29 ± 62.32 vs. 8.37 ± 13.19 months, P < 0.001) compared to the adolescent group. The elderly group also had a higher prevalence of diabetes mellitus (6/24 vs. 0/24, P = 0.029), fewer Schmorl's nodes, more severe intervertebral disc degeneration, and a higher frequency of intervertebral disc vacuum phenomena. Additionally, elderly patients exhibited more frequent localized ossification or hypertrophy of the ligamentum flavum in the thoracolumbar region.

The later onset of TLDH in Scheuermann's disease among elderly patients is likely due to a combination of genetically determined higher endplate strength and age-related degenerative factors. Elderly patients also commonly show localized ossification or hypertrophy of the ligamentum flavum, which may contribute to more severe symptoms.

Cardiovascular disease (CVD) is the leading cause of death among individuals with diabetes, accounting for nearly 50% of diabetes-related mortality. In Ethiopia, the burden of diabetes is increasing, yet there is a lack of predictive tools for identifying those at highest risk of developing CVD. In Ethiopia recent studies report a CVD prevalence of 37.26% among diabetic patients. This study employed machine earning to predict CVD among Ethiopia diabetic patients using Ethiopian public Health Institute (EPHI) datasets, with a focus on identifying the most influential risk factors for public health decision-making.

The main objective of this study is to predict CVD among diabetic patients in Ethiopia using machine learning techniques.

The dataset comprised of 9030 instances with 22 features sourced from Ethiopian Public Health Institute. This prediction of cardiovascular disease (CVD) incorporated socio-demographic, behavioral, and clinical measurement data. Logistic regression, decision tree, Support Vector Machine, Random forest, Gradient boosting machine and artificial neural network were employed. Those models were trained on 80% of the data and tested on the remaining 20%. The analysis was conducted with python using 3.10.

According to the results analyzed, Gradient Boosting Model (GBM) demonstrated the highest overall performance, achieving an accuracy of 93%, followed closely by Logistic Regression (LR) with 90% accuracy. In terms of precision, GBM and LR performed comparably, while the LR achieved the highest recall at 88%. Regarding the F1 score, GBM attained 82%, indicating a strong balance between precision and recall. Additionally, the receiver operating characteristics (ROC) analysis showed that GBM had the largest area under the curve (AUC) of 0.96, reflecting superior descriptive ability 0.96.

The gradient boosting machine (GBM) model demonstrated the highest performance compared to the other models, achieving an accuracy of 93%. The most significant factors influencing the GBM model were total cholesterol, hypertension, and fasting blood glucose levels. The gradient boosting model shows potential for future integration into clinical decision-support systems, pending external validation and early prediction of cardiovascular disease in individuals with diabetes.

Cognitive impairment and dementia present significant global health challenges, particularly in low-income and rural populations. As the prevalence of cognitive impairment continues to rise, early identification of risk factors is essential to prevent further cognitive impairment and mitigate the associated socioeconomic burden. This study aims to explore the associations between novel obesity indices-conicity index (C-index), relative fat mass (RFM), and Chinese visceral adiposity index (CVAI)-and cognitive impairment in a low-income rural population in Tianjin, China.

This cross-sectional study included 1,132 participants aged 60 years and older from rural Tianjin, China. Data were gathered through face-to-face interviews, covering socio-demographic and clinical information. Physical measurements were taken, including height, weight, and waist circumference. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). The C-index, RFM, and CVAI were calculated using standard formulas and categorized into quartiles. Multivariate logistic regression was conducted to examine the associations between obesity indices and cognitive impairment, adjusting for potential confounders. Restricted cubic spline (RCS) curves were utilized to explore the nonlinear relationship between RFM and cognitive impairment. Subgroup analyses were performed based on gender and age groups.

The study found that 47.7% of the participants exhibited cognitive impairment. Univariate analysis revealed significant associations between cognitive impairment and several factors, including gender, age, waist circumference, smoking history, alcohol consumption, diabetes mellitus, and fasting blood glucose (FBG). Multivariate analysis indicated a significant association between RFM and cognitive impairment, with individuals in the third quartile of RFM having 59% higher odds of prevalent cognitive impairment compared to those in the lowest quartile (OR = 1.59, 95% CI: 1.05-2.41, p = 0.028), and demonstrated a U-shaped association (p = 0.005). Higher RFM was protective in men (OR = 0.94, p = 0.003) but not in women and no age-specific effects emerged.

This study underscores the significant role of relative fat mass in cognitive health, revealing a nonlinear relationship in which both high and low levels of RFM are linked to an increased risk of cognitive impairment. Given the cross-sectional design, temporal ordering cannot be established and causality cannot be inferred; our findings indicate associations between RFM and prevalent cognitive impairment and highlight the need for longitudinal confirmation in low-income rural populations.

Diabetic Kidney Disease (DKD) is a leading cause of chronic kidney disease and end-stage renal disease, significantly impacting global public health. Despite the availability of conventional treatments like renin-angiotensin system (RAAS) inhibitors, disease progression remains a challenge. Pentoxifylline, an anti-inflammatory and immunomodulatory agent, has emerged as a promising adjunctive therapy for DKD. This review explores pentoxifylline's mechanisms of action, including its effects on inflammation, oxidative stress, fibrosis, and renal function, supported by clinical and preclinical evidence. Studies indicate that pentoxifylline can reduce proteinuria, improve glomerular filtration rate, and protect against kidney fibrosis in DKD, offering a multifaceted approach to disease management. By addressing several key pathways in DKD progression, pentoxifylline may provide an essential addition to existing therapeutic strategies, especially in patients with advanced disease.

Catheter-associated urinary tract infections (CAUTI) lead to increased morbidity, mortality, prolonged hospital stays, and frequent antimicrobial use, potentially leading to development of multidrug-resistant pathogens. This study aimed to determine the prevalence of CAUTI and identify risk factors among patients in intensive care units (ICU) at King Abdullah Hospital (KAH), Bisha, Saudi Arabia.

A retrospective cross-sectional, hospital-based study was conducted between November 2023 and June 2024 among 327 patients admitted to the ICU at KAH and catheterized with a Foley catheter. Clinical data and general characteristics of the patients were gathered. Identification and antibiotic sensitivity testing of bacterial pathogens were performed as per standard laboratory methods. Univariate and multivariate logistic regressions identified factors associated with CAUTI. Results were presented as odds ratios with 95% confidence intervals (95% CI), and p-values < 0.05 indicated statistical significance.

A total of 327 adult patients were enrolled, with a CAUTI prevalence of 27.8% (n = 91). Klebsiella species were the most prevalent isolate (46.2%), followed by Escherichia coli (24.2%) and Pseudomonas aeruginosa (11.0%). Cotrimoxazole exhibited the highest resistance at 74.7%, followed by cefoxitin at 52.7% and piperacillin/tazobactam at 50.5%. Independent factors associated with CAUTI included advance age (adjusted odds ratio [aOR] = 4.34, p < .001), flank pain (aOR = 17.3, p < .001), catheter duration of more than 10 days (aOR = 18.0, p = .022), urinary incontinence (aOR = 18.0, p = .006), urine retention (aOR = 50.81, p < .001), patient with comorbidity (aOR = 37.07, p = .004), number of comorbidities (aOR = 32.07, p < .001), diabetes mellitus (aOR = 35.52, p < .001), hypertension (aOR = 25.02, p = .002), chronic renal diseases (aOR = 9.03, p = .008), cardiovascular diseases (aOR = 30.22, p < .001) and chronic pulmonary diseases (aOR = 15.31, p = .005).

The prevalence of CAUTI was 27.8%. We identified several factors that affect the development of CAUTI in hospitalized patients. Understanding these risk factors helps identify effective interventions. Enhanced education on catheter management for healthcare providers and patients is crucial to reducing CAUTI.

Not applicable.

Aging and diabetes mellitus (DM) are associated with declines in physical fitness, such as reduced muscle strength, balance, and flexibility, increasing the risk of falls and functional limitations. This pilot study used a quasi-experimental design with pre- and post-intervention assessments to evaluate the effects of a 6-month sensorimotor training (SMT) program on physical fitness in older women with type 2 diabetes. Ten women aged 65 and older were divided into an intervention group (IG, n = 5) and a control group (CG, n = 5). The IG participated in a twice-weekly SMT program, while the CG maintained their usual routines. Physical fitness was assessed at baseline and after 24 weeks using the Timed Up and Go (TUG) test for agility and dynamic balance; the 30-second sit-to-stand test for lower limb strength; the arm curl test for upper limb strength; and the sit-and-reach and back scratch tests for lower and upper limb flexibility, respectively. The IG showed significant improvements in agility (TUG, p = 0.020), lower limb flexibility (sit-and-reach, p = 0.049), and upper limb flexibility on the left side (back scratch, p = 0.023) compared to the CG. Both groups improved in lower limb strength (p = 0.330), while upper limb strength showed no significant changes (p = 0.166). Although the CG also improved in some measures, the IG achieved greater functional gains. These results suggest that SMT enhances neuromuscular control, proprioception, and flexibility-key factors in reducing fall risk and improving independence in older adults with diabetes. SMT appears to be a promising intervention to support physical function, balance, and quality of life in this population.Trial registrationClinical trial registry 01/09/2021. Clinical trial number: NCT05398354. Trial Name: Active Retirement: Effects of the Application of a Training Program.

Early vascular aging (EVA) is a key contributor to the elevated risk of cardiovascular disease, which remains a leading cause of mortality and disability in patients with type 2 diabetes mellitus (T2DM). This study aims to investigate the association between the triglyceride-glucose (TyG) index and EVA in T2DM patients.

T2DM patients were enrolled, and their clinical data were collected. Bilateral brachial-ankle pulse wave velocity (baPWV) was measured and used to determine the presence of EVA. Binary logistic regression analysis was conducted to evaluate the effect of the TyG index and identify factors associated with EVA. A predictive model was constructed using a nomogram, and its performance was assessed using receiver operating characteristic (ROC) curve analysis.

A total of 380 patients were included in the study, among whom 144 (37.89%) were identified as having EVA. After adjusting for all relevant covariates, the TyG index remained independently and positively associated with EVA (odds ratio [OR] = 2.76, 95% confidence interval [CI]: 1.57-4.85), patients in the highest TyG tertile had a 4.30-fold increased risk of developing EVA compared to those in the lowest tertile (95% CI: 1.97-9.42). Elevated TyG index (OR = 2.53, 95% CI: 1.79-3.57) and systolic blood pressure (OR = 1.04, 95% CI: 1.02-1.06) were positively associated with EVA in T2DM patients, while male sex (OR = 0.50, 95% CI: 0.30-0.83) and absence of T2DM complications (OR = 0.56, 95% CI: 0.34-0.92) were negatively associated with EVA. Based on these findings, a predictive model was developed, which demonstrated good discrimination with an area under the ROC curve (AUC) of 0.776 (95% CI: 0.728-0.824).

A higher TyG index and elevated systolic blood pressure were independently associated with the presence of EVA, whereas male sex and the absence of T2DM complications were associated with a lower likelihood of its occurrence. These findings provide valuable insights for the early identification of high-risk individuals.

Background Gastrointestinal autonomic dysfunction (GAD) is a common complication of Type 2 Diabetes Mellitus (T2DM) leading to gastroparesis, constipation, and gastroesophageal reflux disease, consequently affecting the overall quality of life. However, its prevalence and risk factors remain underexplored, particularly in low-resource settings like Zanzibar. This study assessed the prevalence of GAD and its associations with pharmacological, clinical, and lifestyle factors among T2DM patients in Zanzibar using the Composite Autonomic Symptom Score (COMPASS 31) questionnaire. Methods A cross-sectional study was conducted among 364 T2DM patients attending clinics in Zanzibar. Participants were recruited from local healthcare facilities, and data were collected through structured interviews. The gastrointestinal subdomain of the COMPASS 31 questionnaire quantified symptoms of gastrointestinal dysfunction. Descriptive and inferential analyses were performed to explore prevalence and associated factors. Results Among 364 participants, 140 (38.4%) had GAD. Longer diabetes duration was significantly associated with GAD, with those having diabetes for 7-9 years (adjusted OR: 2.19, p = 0.050) and > 10 years (adjusted OR: 2.04, p = 0.036) at higher risk. Use of oral hypoglycemic agents, more common in those with shorter disease duration, was linked to significantly lower odds of GAD (adjusted OR: 0.43, p = 0.007) compared to insulin alone. Additionally, consuming > 2 portions of fruit per day was associated with reduced risk (adjusted OR: 0.41, p = 0.019). Other factors, including gender and BMI, showed trends but were not statistically significant. Conclusion GAD is common among T2DM patients in Zanzibar, with longer diabetes duration increasing risk, while oral hypoglycemic use and higher fruit intake are linked to lower risk. The protective association of oral hypoglycemics may reflect earlier disease stages, reinforcing the importance of early diagnosis and intervention. Findings highlight the need for integrated lifestyle and pharmacological approaches to mitigate autonomic complications. Future research, including longitudinal studies and clinical trials, should explore causal relationships, underlying mechanisms, and the impact of dietary modifications and pharmacological interventions on GAD.

Insulin resistance is an underrecognized cardiovascular risk factor in type 1 diabetes. The effect of metformin on insulin resistance in adults with type 1 diabetes is unknown. Forty adults with type 1 diabetes, and twenty adults without diabetes were studied in a baseline only cross-sectional study assessing insulin resistance using the two-step hyperinsulinemic-euglycemic clamp. Participants with type 1 diabetes exhibited hepatic (EGP 64% higher), muscle (glucose infusion rate [GIR] 29% lower) and adipose (higher non-esterified fatty acids [NEFA]) insulin resistance. We then conducted a parallel group randomized, placebo-controlled trial to assess the efficacy of metformin 1500 mg (n = 20) versus placebo (n = 20) in reducing insulin resistance in adults with type 1 diabetes over 26 weeks. The primary outcome was change in endogenous glucose production (EGP) during the low-dose phase of the clamp. Thirty seven of 40 adults with type 1 diabetes completed the study. At 26 weeks, there was no difference in change in EGP between metformin and placebo groups (mean difference 0.2 µmol/kg fat-free mass [FFM]/min [95%CI, -0.4 to 0.8 µmol/kgFFM/min]; p = 0.53). There was no increase in hypoglycemia or episodes of ketoacidosis in either group. These results do not support prescribing metformin to reduce hepatic insulin resistance in adults with type 1 diabetes. Australian New Zealand Clinical Trials Registry identifier, ACTRN12619001440112.