Effectiveness of Spironolactone in Terms of Galectin-3 Levels in Patients with Heart Failure with a Reduced Ejection Fraction in the Vietnamese Population.

Background: Galectin-3 is a biomarker that has been demonstrated to play a significant role in myocardial fibrosis and remodeling in the pathogenesis of heart failure. Furthermore, spironolactone has the ability to control galectin-3 levels in heart failure patients. Objectives: The aim of our study was to determine the factors associated with the increase in galectin-3 and the alteration of galectin-3 concentration in patients with heart failure with a reduced ejection fraction after 12 weeks of treatment with spironolactone. Materials and methods: A cross-sectional descriptive study was conducted on 122 patients with heart failure with a reduced ejection fraction. Those patients were nonusers of spironolactone and presented for examination or had been hospitalized at the Can Tho Cardiovascular Hospital in Vietnam. The demographic and cardiovascular risk factor details were obtained at baseline, and galectin-3 levels were measured at baseline and also 12 weeks after taking spironolactone 25 mg once daily vs. 50 mg once daily. Results: The median baseline galectin-3 was 54.82 ± 26.06. Galectin-3 levels were positively correlated with age, NT-proBNP, and negatively correlated between EF and galectin-3 levels (p < 0.05). After 12 weeks of treatment with spironolactone, the galectin-3 concentration decreased from 54.82 ± 26.06 to 44.20 ± 24.36 (p < 0.05). According to the subgroup analysis, the average concentration of galectin-3 decreased the most in the group of patients with grade 3 hypertension and NYHA class III heart failure. The 50 mg once-daily dose of spironolactone significantly improved galectin-3 concentrations compared with the 25 mg once-daily group, at 17.11 ± 20.81 (p < 0.05) (reduced 29.05%) and 3.46 ± 6.81 ng/mL (p < 0.05) (reduced 6.87%), respectively. Conclusion: Treatment with spironolactone played an essential role in reducing galectin-3 concentrations, especially spironolactone 50 mg once daily, which showed a significant effect on reducing galectin-3 compared with a 25 mg once-daily dose.

A Review on Visual-SLAM: Advancements from Geometric Modelling to Learning-Based Semantic Scene Understanding Using Multi-Modal Sensor Fusion.

Simultaneous Localisation and Mapping (SLAM) is one of the fundamental problems in autonomous mobile robots where a robot needs to reconstruct a previously unseen environment while simultaneously localising itself with respect to the map. In particular, Visual-SLAM uses various sensors from the mobile robot for collecting and sensing a representation of the map. Traditionally, geometric model-based techniques were used to tackle the SLAM problem, which tends to be error-prone under challenging environments. Recent advancements in computer vision, such as deep learning techniques, have provided a data-driven approach to tackle the Visual-SLAM problem. This review summarises recent advancements in the Visual-SLAM domain using various learning-based methods. We begin by providing a concise overview of the geometric model-based approaches, followed by technical reviews on the current paradigms in SLAM. Then, we present the various learning-based approaches to collecting sensory inputs from mobile robots and performing scene understanding. The current paradigms in deep-learning-based semantic understanding are discussed and placed under the context of Visual-SLAM. Finally, we discuss challenges and further opportunities in the direction of learning-based approaches in Visual-SLAM.

Feasibility Study of Constructing a Screening Tool for Adolescent Diabetes Detection Applying Machine Learning Methods.

Prediabetes and diabetes are becoming alarmingly prevalent among adolescents over the past decade. However, an effective screening tool that can assess diabetes risks smoothly is still in its infancy. In order to contribute to such significant gaps, this research proposes a machine learning-based predictive model to detect adolescent diabetes. The model applies supervised machine learning and a novel feature selection method to the National Health and Nutritional Examination Survey datasets after an exhaustive search to select reliable and accurate data. The best model achieved an area under the curve (AUC) score of 71%. This research proves that a screening tool based on supervised machine learning models can assist in the automated detection of youth diabetes. It also identifies some critical predictors to such detection using Lasso Regression, Random Forest Importance and Gradient Boosted Tree Importance feature selection methods. The most contributing features to Youth diabetes detection are physical characteristics (e.g., waist, leg length, gender), dietary information (e.g., water, protein, sodium) and demographics. These predictors can be further utilised in other areas of medical research, such as electronic medical history.

Depression in psoriatic arthritis: Related to socio-demographics, comorbid loads or disease activity?

AIM: Psychological distress commonly occurs in patients with psoriatic arthritis (PsA). The primary objective of this study was to determine the prevalence of depression in PsA. The secondary objective was to explore its associated factors, including socio-demographics, disease activity data and comorbidities. METHODS: Patients with PsA fulfilling the Classification Criteria for Psoriatic Arthritis were consecutively recruited from local rheumatology clinics. Depression was assessed by a self-administered Chinese-Cantonese version of the Hospital Anxiety and Depression Scale (HADS). RESULTS: Two hundred and eight eligible patients with PsA were recruited, with 82 females and 126 males. Depression was found in 62 (29.8%) of them. The univariate model identified these associated factors: (1) Psoriasis Area and Severity Index score; (2) disease activity measurement, that is tender and swollen joint count, erythrocyte sedimentation rate, C-reactive protein, Disease Activity in Psoriatic Arthritis (DAPSA) score, Leeds Enthesitis Index and tender dactylitis count; (3) quality of life measurement, that is Health Assessment Questionnaire - Disability Index (HAQ-DI), pain and general health perception; (4) PsA duration; and (5) body mass index. The final regression model identified DAPSA and HAQ-DI were closely associated with depression, P = .007 and P = .02 respectively. Moderate and strong correlations with HADS score were found with DAPSA (Kendall's tau-b coefficient [τb] = 0.25) and HAQ-DI (τb = 0.4) respectively. No associations with depression were found between age, living and employment status, gender, demographics, inflammatory markers, disease duration, skin involvement and comorbidities, in term of Charlson's Comorbidity Index. CONCLUSION: Depression was prevalent among PsA patients and it was closely correlated with disease activity and physical function impairment. Achieving low disease activity and maintaining physical function in patients with PsA may mitigate the psychological burden. The present study also highlighted the unmet needs of strategies to identify this common phenomenon.

Fatigue in psoriatic arthritis: Is it related to disease activity?

AIM: Fatigue is commonly associated with psoriatic arthritis (PsA). However, information about its prevalence and associated factors is sparse. The primary objective here was to find the prevalence and magnitude of PsA fatigue. The secondary objective was to explore its associated risk factors, particularly emphasis on the effect of disease activity control. METHODS: PsA patients who fulfilled Classification Criteria For Psoriatic Arthritis were consecutively recruited from local rheumatology clinics. Fatigue was assessed by a 13-item self-administered questionnaire (Functional Assessment of Chronic Illness Therapy - Fatigue [FACIT-F]) (0-52). Data collected and analyzed included: demographic data, disease activity data, comorbidities and medications use. RESULTS: There were 231 eligible PsA patients recruited. The mean FACIT-F score was 37.5 ± 9.1. Severe fatigue, defined as FACIT-F score < 30, was found in 49 (22.1%) of them. The univariate model identified these associated factors of fatigue: tender and swollen joint count, dactylitis count, Psoriasis Area and Severity Index (PASI) score, pain and general health perception, Disease Activity in Psoriatic Arthritis (DAPSA) score, Health Assessment Questionnaire, the use of cyclosporine, sulphasalazine and biologic agents. The final regression model identified DAPSA and PASI were closely associated with severe fatigue (P = .003 and P = .04 respectively). No associations with fatigue were found between age, gender, disease duration, comorbidities and medication use. However, there were weak correlations between the magnitude of FACIT-F score, DAPSA and PASI with r = -.3 and r = -.26 respectively. CONCLUSION: Severe fatigue was common in PsA patients, and its magnitude was closely correlated with DAPSA and PASI score, indicating its multifactorial nature. Achieving DAPSA and PASI remission could significantly alleviate the fatigue intensity to a certain extent. However, treatment for PsA-related fatigue should adopt a multidisciplinary approach in addition to disease activity control.

Risk of community-acquired pneumonia requiring hospitalization in patients with spondyloarthritis.

AIMS: To compare the risk of community-acquired pneumonia (CAP) requiring hospitalization in spondyloarthritis (SpA) and non-specific back pain (NSBP), and to identify the risk factors for CAP in SpA. METHODS: A total of 2984 patients with SpA from 11 rheumatology centers and 2526 patients with NSBP from orthopedic units were reviewed from the centralized electronic database in Hong Kong. Incidence of CAP requiring hospitalization and demographic data including age, gender, smoking and drinking status, use of sulfasalazine, individual biological-disease modifying anti-rheumatic drugs (DMARDs) used, micro-organisms, other immunosuppressants or immunosuppressive states, use of steroid for more than ½ year, and co-morbidities were identified. Risks of CAP in SpA were compared with those in NSBP using propensity score regression method. Multivariate Cox regression model was used to identify the risk factors in SpA. RESULTS: CAP requiring hospitalization was found in 183 patients with SpA and 138 patients with NSBP. Increased risk for CAP was found in the following groups with SpA: all subgroups (hazard ratio (HR) 2.14, p < 0.001), without use of DMARDs (HR 2.64, p < 0.001), without psoriasis and not taking DMARDs (HR 2.38, p < 0.001). Infliximab (HR2.55, p = 0.04), smoking (HR 1.68, p = 0.003), comorbid psoriasis (HR 1.67, p = 0.003), and use of steroid for more than ½ year (HR 1.94, p = 0.003) were found to associate with CAP after adjustments for traditional risk factors. CONCLUSION: Risk of CAP is increased in patients with SpA. Our data favor universal influenza and pneumococcal vaccination programs in the population. Rheumatologists should also advise smoking cessation and avoid long term steroid therapy.

Hyperuricemia in Asian psoriatic arthritis patients.

AIM: It is generally accepted that hyperuricemia is commonly associated with psoriatic arthritis (PsA). However, variations in ethnicity, diet and habitat may contribute to differences in prevalence and risk factors for hyperuricemia in PsA patients. Moreover, Asian specific data is deficient. The primary objective of the present study was to determine the prevalence of hyperuricemia among PsA patients. The secondary objective was to explore its associated risk factors. METHODS: This was a multi-center, cross-sectional observational study of 160 PsA patients from local Rheumatology clinics. Serum uric acid (SUA) level and other clinical parameters were measured and hyperuricemia was defined as SUA level greater or equal to 360 umol/L in females and 420 umol/L in males. RESULTS: Forty-nine of 160 patients (30.6%) had hyperuricemia, of which 32 were men, 17 were women. Among those with hyperuricemia, mean SUA level was 500.7 ± 95.9 umol/L and 427.8 ± 83.1 umol/L in males and females, respectively. Univariate analysis found: (i) overweight status; (ii) obesity; (iii) Psoriasis Area and Severity Index; (iv) body surface area; (v) severe skin involvement, as being potentially associated with hyperuricemia. Regression model identified overweight status increased the likelihood of hyperuricemia in PsA, with an odds ratio of 4.4 (95% CI: 2.0-9.5). Furthermore, there was moderately positive correlation (r = 0.37) between body mass index (BMI) and SUA level. No associations were found between arthritis conditions and duration, lipid profile, creatinine clearance; and hyperuricemia. CONCLUSION: A significant proportion of PsA patients had asymptomatic hyperuricemia. It was closely related with BMI, which represented metabolic dysregulation; but not with severity of skin disease, joint involvement or renal function.

Frequent Exacerbator: The Phenotype at Risk of Depressive Symptoms in Geriatric COPD Patients.

INTRODUCTION: Depression is associated with a poorer quality of life and higher rate of COPD exacerbations and mortality. However, with multiple confounding factors, 'independent' risk factor for depression among COPD patients remains ambiguous. Our study aims to identify independent risk factors for depression by specifically evaluating for any independent relationship between frequent exacerbations and various domains of the BODE index on depression. METHODS: This study is a cross-sectional study, conducted in Hong Kong SAR. Age and comorbidity-matched COPD and control subjects were recruited. Depressive symptoms were measured by a validated Chinese version of the Geriatric Depression Scale (GDS-15 items). Prevalence rates of depressive symptoms were compared between COPD and control groups. Predictors for depression (GDS ≥ 8) were determined using univariate and multivariate analyses. RESULTS: A total of 161 patients (89 and 72 patients, mean ages 75.2 and 75.6 in COPD and control group, respectively) were recruited. Higher prevalence rate of significant depressive symptoms was seen in COPD patients (20.2 vs. 4.2 %, p = 0.006*). Univariate analysis suggested that predictors for depression in COPD patients included (i) exacerbation frequencies in prior year, (ii) dyspnea level, (iii) BMI, (iv) functional status (Barthel index, 6MWD, activity domain of SGRQ), and (v) BODE index. In multivariate analysis, only the 'exacerbation frequencies in prior year' (OR 1.46, p = 0.042*) and 'dyspnea level' (MMRC) (OR 2.75, p = 0.001*) remained significant independent predictors for depression in COPD patients. CONCLUSIONS: A high prevalence of depressive symptoms was observed in COPD patients. 'Frequent exacerbation phenotype' remained a significant independent predictor for depressive symptoms in COPD. Among the BODE index domains, dyspnea level is the most important predictor for depression in COPD patients.