Incorporating AI into cardiovascular diseases prevention-insights from Singapore.

Improved upstream primary prevention of cardiovascular disease (CVD) would enable more individuals to lead lives free of CVD. However, there remain limitations in the current provision of CVD primary prevention, where artificial intelligence (AI) may help to fill the gaps. Using the data informatics capabilities at the National University Health System (NUHS), Singapore, empowered by the Endeavour AI system, and combined large language model (LLM) tools, our team has created a real-time dashboard able to capture and showcase information on cardiovascular risk factors at both individual and geographical level- CardioSight. Further insights such as medication records and data on area-level socioeconomic determinants allow a whole-of-systems approach to promote healthcare delivery, while also allowing for outcomes to be tracked effectively. These are paired with interventions, such as the CHronic diseAse Management Program (CHAMP), to coordinate preventive cardiology care at a pilot stage within our university health system. AI tools in synergy allow the identification of at-risk patients and actionable steps to mitigate their health risks, thereby closing the gap between risk identification and effective patient care management in a novel CVD prevention workflow.

Distinguishing risk of curve progression in adolescent idiopathic scoliosis with bone microarchitecture phenotyping: a 6-year longitudinal study.

Low bone mineral density and impaired bone quality have been shown to be important prognostic factors for curve progression in adolescent idiopathic scoliosis (AIS). There is no evidence-based integrative interpretation method to analyze high-resolution peripheral quantitative computed tomography (HR-pQCT) data in AIS. This study aimed to (1) utilize unsupervised machine learning to cluster bone microarchitecture phenotypes on HR-pQCT parameters in girls with AIS, (2) assess the phenotypes' risk of curve progression and progression to surgical threshold at skeletal maturity (primary cohort), and (3) investigate risk of curve progression in a separate cohort of girls with mild AIS whose curve severity did not reach bracing threshold at recruitment (secondary cohort). Patients were followed up prospectively for 6.22 ± 0.33 years in the primary cohort (n = 101). Three bone microarchitecture phenotypes were clustered by fuzzy C-means at time of peripubertal peak height velocity (PHV). Phenotype 1 had normal bone characteristics. Phenotype 2 was characterized by low bone volume and high cortical bone density, and phenotype 3 had low cortical and trabecular bone density and impaired trabecular microarchitecture. The difference in bone quality among the phenotypes was significant at peripubertal PHV and continued to skeletal maturity. Phenotype 3 had significantly increased risk of curve progression to surgical threshold at skeletal maturity (odd ratio [OR] = 4.88; 95% CI, 1.03-28.63). In the secondary cohort (n = 106), both phenotype 2 (adjusted OR = 5.39; 95% CI, 1.47-22.76) and phenotype 3 (adjusted OR = 3.67; 95% CI, 1.05-14.29) had increased risk of curve progression ≥6° with mean follow-up of 3.03 ± 0.16 years. In conclusion, 3 distinct bone microarchitecture phenotypes could be clustered by unsupervised machine learning on HR-pQCT-generated bone parameters at peripubertal PHV in AIS. The bone quality reflected by these phenotypes was found to have significant differentiating risk of curve progression and progression to surgical threshold at skeletal maturity in AIS.

Adolescent idiopathic scoliosis (AIS) is an abnormal spinal curvature that commonly presents during puberty growth. Evidence has shown that low bone mineral density and impaired bone quality are important risk factors for curve progression in AIS. High-resolution peripheral quantitative computed tomography (HR-pQCT) has improved our understanding of bone quality in AIS. It generates a large amount of quantitative and qualitative bone parameters from a single measurement, but the data are not easy for clinicians to interpret and analyze. This study enrolled girls with AIS and used an unsupervised machine-learning model to analyze their HR-pQCT data at the first clinic visit. The model clustered the patients into 3 bone microarchitecture phenotypes (ie, phenotype 1: normal; phenotype 2: low bone volume and high cortical bone density; and phenotype 3: low cortical and trabecular bone density and impaired trabecular microarchitecture). They were longitudinally followed up for 6 years until skeletal maturity. We observed the 3 phenotypes were persistent and phenotype 3 had a significantly increased risk of curve progression to severity that requires invasive spinal surgery (odds ratio = 4.88, p = .029). The difference in bone quality reflected by these 3 distinct phenotypes could aid clinicians to differentiate risk of curve progression and surgery at early stages of AIS.

Predictors of SARS-CoV-2 transmission in congregate living settings: a multicenter prospective study.

BACKGROUND: Older adults residing in congregate living settings (CLS) such as nursing homes and independent living facilities remain at increased risk of morbidity and mortality from coronavirus disease 2019. We performed a prospective multicenter study of consecutive severe acute respiratory coronavirus virus 2 (SARS-CoV-2) exposures to identify predictors of transmission in this setting. METHODS: Consecutive resident SARS-CoV-2 exposures across 17 CLS were prospectively characterized from 1 September 2022 to 1 March 2023, including factors related to environment, source, and exposed resident. Room size, humidity, and ventilation were measured in locations where exposures occurred. Predictors were incorporated in a generalized estimating equation model adjusting for the correlation within CLS. RESULTS: Among 670 consecutive exposures to SARS-CoV-2 across 17 CLS, transmission occurred among 328 (49.0%). Increased risk was associated with nursing homes (odds ratio (OR) = 90.8; 95% CI, 7.8-1047.4), Jack and Jill rooms (OR = 2.2; 95% CI, 1.3-3.6), from source who was pre-symptomatic (OR = 11.2; 95% CI, 4.1-30.9), symptomatic (OR = 6.5; 95% CI, 1.4-29.9), or rapid antigen test positive (OR = 35.6; 95% CI, 5.6-225.6), and in the presence of secondary exposure (OR = 6.3; 95% CI, 1.6-24.0). Exposure in dining room was associated with reduced risk (OR = 0.02; 95% CI, 0.005-0.08) as was medium room size (OR = 0.3; 95% CI, 0.2-0.6). Recent vaccination of exposed resident (OR = 0.5; 95% CI, 0.3-1.0) and increased ventilation of room (OR = 0.9; 95% CI, 0.8-1.0) were marginally associated with reduced risk. CONCLUSION: Prospective assessment of SARS-CoV-2 exposures in CLS suggests that source characteristics and location of exposure are most predictive of resident transmission. These findings can inform risk assessment and further opportunities to prevent transmission in CLS.

Oleanolic acid exerts bone anabolic effects via activation of osteoblastic 25-hydroxyvitamin D 1-alpha hydroxylase.

Oleanolic acid (OA) is previously shown to exert bone protective effects in aged animals. However, its role in regulating osteoblastic vitamin D bioactivation, which is one of major causes of age-related bone loss, remains unclear. Our results revealed that treatment of OA significantly increased skeletal CYP27B1 expression and circulating 1,25(OH)2D3 in ovariectomized mice (p <0.01). Moreover, OA upregulated CYP27B1 protein expression and activity, as well as the vitamin D-responsive bone markers alkaline phosphatase (ALP) activity and osteopontin (OPN) protein expression, in human osteoblast-like MG-63 cells (p<0.05). CYP27B1 expression increased along with the osteoblastic differentiation of human bone marrow derived mesenchymal stem cells (hMSCs). CYP27B1 expression and cellular 1,25(OH)2D3 production were further potentiated by OA in cells at mature osteogenic stages. Notably, our study suggested that the osteogenic actions of OA were CYP27B1 dependent. In summary, the bone protective effects of OA were associated with the induction of CYP27B1 activity and expression in bone tissues and osteoblastic lineages. Hence, OA might be a potential approach for management of age-related bone loss.

Kinematic difference and asymmetries during level walking in adolescent patients with different types of mild scoliosis.

BACKGROUND: Adolescent idiopathic scoliosis (AIS), three-dimensional spine deformation, affects body motion. Previous research had indicated pathological gait patterns of AIS. However, the impact of the curve number on the walking mechanism has not been established. Therefore, this study aimed to compare the gait symmetry and kinematics in AIS patients with different curve numbers to healthy control. RESULTS: In the spinal region, double curves AIS patients demonstrated a smaller sagittal symmetry angle (SA) and larger sagittal convex ROM of the trunk and lower spine than the control group. In the lower extremities, the single curve patients showed a significantly reduced SA of the knee joint in the frontal plane, while the double curves patients showed a significantly reduced SA of the hip in the transverse plane. CONCLUSION: The curve number indeed affects gait symmetry and kinematics in AIS patients. The double curves patients seemed to adopt a more "careful walking" strategy to compensate for the effect of spinal deformation on sensory integration deficits. This compensation mainly occurred in the sagittal plane. Compared to double curves patients, single curve patients unitized a similar walking strategy with healthy subjects.