Individual Risk Factors Research Articles

No Difference between the Efficacy of High-Nitrate and Low-Nitrate Vegetable Supplementation on Blood Pressure after 16 Weeks in Individuals with Early-Stage Hypertension: An Exploratory, Double-Blinded, Randomized, Controlled Trial.

Dietary inorganic nitrate lowers blood pressure (BP) in healthy individuals through improved nitric oxide (NO) bioavailability. However, there is limited evidence examining the long-term effects of dietary nitrate for managing hypertension. We aimed to determine whether the sustained intake of dietary nitrate improved BP and cardiovascular disease (CVD) risk factors in individuals with early-stage hypertension. The Dietary Nitrate (NO3) on BP and CVD Risk Factors (DINO3) Trial was a multi-center, double-blinded, parallel, randomized, controlled trial in participants with elevated BP. Participants were supplemented with high-nitrate (HN) (~400 mg nitrate) or low-nitrate (LN) vegetable powder (~50 mg nitrate) on top of their usual diets for 16 weeks. The primary outcome was office systolic BP at 16 weeks. The secondary outcomes were 24 h ambulatory BP, central BP, heart-rate-corrected augmentation index (AIx75), carotid-femoral pulse wave velocity (cf-PWV), lipids, and high-sensitivity C-reactive protein (hs-CRP). Sixty-six participants were randomized at baseline (39M:27F, age: 51.5 ± 10.8 years, BMI:27.9 ± 3.2 kg/m2). In an intention-to-treat analysis, no differences were observed between HN and LN groups in terms of office systolic BP at 16 weeks (3.91 ± 3.52 mmHg, p = 0.27) or secondary outcomes. In this exploratory study, sustained HN vegetable supplementation did not exhibit more favorable vascular effects than LN vegetable supplementation in individuals with elevated BP.

Digital Twins in 3D Printing Processes Using Artificial Intelligence

Digital twins (DTs) provide accurate, data-driven, real-time modeling to create a digital representation of the physical world. The integration of new technologies, such as virtual/mixed reality, artificial intelligence, and DTs, enables modeling and research into ways to achieve better sustainability, greater efficiency, and improved safety in Industry 4.0/5.0 technologies. This paper discusses concepts, limitations, future trends, and potential research directions to provide the infrastructure and underlying intelligence for large-scale semi-automated DT building environments. Grouping these technologies along these lines allows for a better consideration of their individual risk factors and use of available data, resulting in an approach to generate holistic virtual representations (DTs) to facilitate predictive analyses in industrial practices. Artificial intelligence-based DTs are becoming a new tool for monitoring, simulating, and optimizing systems, and the widespread implementation and mastery of this technology will lead to significant improvements in performance, reliability, and profitability. Despite advances, the aforementioned technology still requires research, improvement, and investment. This article’s contribution is a concept that, if adopted instead of the traditional approach, can become standard practice rather than an advanced operation and can accelerate this development.

Heart Failure Among Asian American Subpopulations

Heart failure (HF) is a leading cause of death in the US. The current evidence on the burdens of HF in Asian American populations, especially Asian American subgroups, is limited and inconsistent. To assess and compare the incidence and prevalence of HF in Asian American subgroups. This retrospective cohort study used electronic health record data from patients 40 years or older with health care encounters from January 1, 2015, to December 31, 2019, recorded in the Oracle Electronic Health Record Real-World Data database, which has more than 100 health care systems across the US contributing to the database as of February 2024. For prevalence analysis, the study samples were those who had at least 1 encounter in the study calendar year. For incidence analysis, participants were additionally limited to those without HF before the study year who also had encounter(s) the year before the study year. Data analysis was performed from August 1, 2023, to July 31, 2024. Race and ethnicity were determined using patient self-reported data, which were categorized as Black, East Asian, South Asian, Southeast Asian, other Asian (without specified ethnicity), and White. Outcomes were incidence and prevalence of HF, identified using recorded International Classification of Diseases, Ninth Revision, Clinical Modification and International Statistical Classification of Diseases, Tenth Revision, Clinical Modification codes. Age- and sex-standardized incidence and prevalence were used to calculate the risk ratio of each racial and ethnic group compared with White patients. Incidence and prevalence analyses were performed for 6 845 791 patients (mean [SD] age, 62.1 [12.5] years; 59.9% female; 2.8% Asian, 6.7% Black, and 90.5% White) and for 13 440 234 patients (mean [SD] age, 61.7 [12.7] years; 57.0% female; 2.9% Asian, 7.1% Black, and 90.0% White), respectively. Using the 2015 population as the standard, age- and sex-standardized HF incidence was 2.26% (95% CI, 2.07%-2.45%) for Southeast Asian patients, 1.56% (95% CI, 1.31%-1.82%) for South Asian patients, and 1.22% (95% CI, 1.06%-1.38%) for East Asian patients compared with 1.58% (95% CI, 1.57%-1.59%) for White patients and 2.39% (95% CI, 2.36%-2.42%) for Black patients. Similarly, heterogeneous rates in Asian American subgroups were also observed in the prevalence analysis. In this study of HF outcomes, the disparities between Southeast and East Asian patients were larger than those between Black and White patients, with the estimates in Southeast Asian patients being similar to those of Black patients. These findings reinforce that individual Asian ethnicities and cardiovascular risk factors should be considered in the assessment of HF risks.

Effectiveness of receiving genetic risk information for cardiovascular disease on health behaviors, psychological responses, and associated risk factor modification in individuals: a systematic review protocol.

This review aims to assess the effectiveness of receiving genetic risk information for cardiovascular disease (CVD) on individual health behaviors, psychological responses, and risk factor modification. Advancements in genomics have identified strong genetic predispositions for CVD, leading to the development of CVD genetic risk information. Integrating genetic risk information into clinical practice shows promise in predicting CVD risk and facilitating multifactorial management. This review will focus on randomized controlled trials assessing individual responses to CVD genetic risk information. Participants will be adults aged 18 and older, both with and without CVD. The review will compare the effectiveness of receiving genetic risk information with receiving traditional risk information or no risk information, assessing outcomes such as health behaviors, psychological responses, and risk factor modification. Cochrane CENTRAL, MEDLINE, Embase and Emcare will be searched for relevant studies. Current or unpublished trials will be searched for in Clinical-Trials.gov and World Health Organization International Clinical Trials Registry Platform. Articles will be screened and assessed for inclusion by 2 independent reviewers. Methodological quality will be assessed using the standardized instrument from JBI. Data will be extracted and synthesized for the objectives of the study. If data are sufficient, a meta-analysis will be conducted; otherwise, the findings will be presented in narrative format, including tables and figures to aid in presentation. The certainty of evidence will be assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach. PROSPERO CRD42023390876.

A Comprehensive Analysis of Metastatic Disease following Surgery for Clinically Localized Cutaneous Melanoma.

The NCCN considers "baseline staging" (whole body CT or PET scan +/- brain MRI) for all asymptomatic melanoma patients with a positive sentinel lymph node biopsy. The true yield of these workups is unknown. We created cohorts of adult malignant melanoma patients, using the National Cancer Database (2012-2020) to mimic three common scenarios: (1) clinically node negative, with positive sentinel lymph node(s) (SLNB[+]); (2) clinically node negative, with negative sentinel lymph node(s) (SLNB[-]); (3) clinically node positive with confirmed lymph node metastases (cN[+] and pN[+]). Multivariable regression, supervised decision trees, and nomograms were constructed to assess the risk of metastases based on key features. 10,371 patients were SLNB[+], 55,172 were SLNB[-], and 4,012 were cN[+] and pN[+]. The proportion of patients with any metastatic disease (brain metastases) were as follows: SLNB[+]: 1.4% (0.3%); SLNB[-] 0.3% (<0.1%); cN[+] and pN[+] 11.6% (1.6%). On multivariable regression, Breslow depth > 4, ulceration, and lymphovascular invasion were associated with greater risk of metastatic disease. A supervised decision tree for SLNB[+] and SLNB[-] patients found the only groups with >2% risk of metastases were T4 tumors or T2/T3 tumors with ulceration and LVI. Most groups had a negligible risk (<0.1%) of brain metastases. This is the first large analysis to guide the use of imaging for cutaneous melanoma. Among clinically node negative patients, metastatic disease is uncommon and brain metastases are exceedingly rare. Further investigation could promote a tailored approach to metastatic workups guided by individual risk factors.

General practitioner support needs to implement cardiovascular disease risk assessment and management guidelines: Qualitative interviews.

Previous research identified numerous barriers to general practitioner (GP) use of cardiovascular disease (CVD) risk guidelines, and it is unclear whether these issues have been resolved. This study explored recent GP experiences. Interviews with 18 GPs in an Australian state with relatively few COVID-19 cases in 2021 were transcribed and coded using a framework analysis approach, with data mapped to five previously identified CVD risk assessment strategies: absolute risk focused, absolute risk adjusted, clinical judgement, passive disregard and active disregard. GPs used various CVD risk calculators to inform clinical decision making, but there were concerns about accuracy, the role of extra risk factors and less 'personalised' assessment. GPs addressed these concerns by requesting additional tests, subjectively adjusting the CVD risk assessment to account for extra risk factors and focusing on individual risk factors. Many barriers to CVD risk assessment guidelines remain. GP support is needed to implement revised guidelines.

Coronary Artery Calcium for Risk Stratification Among Persons With Very High HDL Cholesterol

BackgroundCompared to normal high-density lipoprotein (HDL) cholesterol values, very high HDL cholesterol is associated with a higher incidence of mortality and atherosclerotic cardiovascular disease (ASCVD). As such, clinical risk stratification among persons with very high HDL cholesterol is challenging. ObjectivesAmong persons with very high HDL cholesterol, the purpose was to determine the prevalence of coronary artery calcium (CAC) and compare the association between traditional risk factors vs CAC for all-cause mortality and ASCVD. MethodsThe primary analysis was completed among 446 participants from the Cedars-Sinai Medical Center of the CAC Consortium with very high HDL cholesterol (≥77 mg/dL in men, ≥97 mg/dL in women). Cox proportional hazards regression assessed the association of CAC and traditional risk factors with all-cause mortality during a median follow-up of 10.7 years. Replication and validation analyses were performed for all-cause mortality among 119 participants from the Multi-Ethnic Study of Atherosclerosis (MESA) with very high HDL cholesterol, who also had information on incident ASCVD. ResultsThe mean age was 57.9 years old, 49% were women, and the median HDL cholesterol was 98 mg/dL. One-half of participants (50%) had prevalent CAC, in whom the median CAC score was 118. Prevalent CAC conferred a 3.6-fold higher risk of all-cause mortality (HR: 3.64; 95% CI: 1.21-11.01), which appeared to be a more robust predictor than individual traditional risk factors beyond age. In the validation sample, prevalent CAC but not individual traditional risk factors were associated with all-cause mortality (HR: 2.39; 95% CI: 1.07-5.34) and a 4.0-fold higher risk of ASCVD (HR: 4.06; 95% CI: 1.11-14.84). ConclusionsMeasurement of CAC may facilitate clinical risk assessment among individuals with very high HDL cholesterol.

Burden of risk factors in women and men with unrecognised myocardial infarction: a systematic review and meta-analysis.

Unrecognised myocardial infarction (MI) is a MI that remains undetected in the acute phase and is associated with an unfavourable prognosis. With this systematic review and meta-analysis, we evaluated the burden of cardiovascular risk factors in individuals with unrecognised MI. We searched general population-based cohort studies diagnosing unrecognised MI by electrocardiogram or myocardial imaging up to 24 November 2023. Pooled mean differences (MD) or risk ratios (RR) with 95% confidence intervals (CI) were determined, and random-effects meta-analyses were performed. Fourteen cohort studies were included involving 200,450 individuals (mean age 62.8±9.9 years, 56.0% women), among which 4,322 (2.2%) experienced unrecognised MI (mean age 66.3±8.2 years, 47.8% women) and 4,653 (2.1%) recognised MI (mean age 68.5±7.3 years, 33.8% women). Compared to individuals without MI, those with unrecognised MI had higher body mass index (MD 0.27, 95% CI 0.16-0.39) and systolic blood pressure (MD 4.48, 95% CI 2.81-6.15), and higher prevalence of hypertension (RR 1.27, 95% CI 1.06-1.51) and diabetes mellitus (RR 1.67, 95% CI 1.36-2.06). Furthermore, individuals with unrecognised MI had lower prevalence of hypertension (RR 0.92, 95% CI 0.88-0.97) and diabetes mellitus (RR 0.80, 95% CI 0.70-0.92). Individuals with unrecognised MI are characterised by a substantial burden of metabolic risk factors. Our findings suggest insufficient recognition and management of cardiovascular risk factors among individuals with unrecognised MI.

Partnerships with primary care providers: Opportunities to prevent eating disorders and mitigate their progression in young people

ABSTRACT Epidemiologic research has identified numerous interpersonal and individual risk factors for and warning signs of emerging eating disorders in adolescents. These findings have informed public health prevention and treatment strategies, including translation of findings to clinical recommendations for primary care providers (PCPs). A next step in this translational work could include a comprehensive approach where PCPs are seen as partners in efforts to improve population health outcomes. PCPs have great potential to implement high-yield interventions that prevent or attenuate the course of adolescent eating disorders. To illustrate this potential, we present a case that highlights missed opportunities for a PCP to prevent, detect, and intervene during a patient’s developing eating disorder. We then relate the case to two emerging research programs that utilize PCP partnerships: one trains PCPs in Strengths-Based Adolescent Healthcare to improve eating disorder prevention; the other adapts Family-Based Treatment for primary care to improve early access to evidence-based treatment. In addition to these promising areas of research, efforts are needed to widen requirements for eating disorder curricula in medical training programs and to address weight stigma in primary care. Together these efforts will help PCPs become effective partners in the prevention and treatment of eating disorders.

Awareness and knowledge of cardiovascular disease and their associations with the lifestyles of 8-16-year-old girls: a perspective from Saudi Arabia

BackgroundThere has been an increased focus on children as a target for primordial prevention of cardiovascular disease (CVD). In particular, girls should receive attention to combat the burden of CVD in women, because women have higher CVD mortality and morbidity rates than men do. As health literacy is paramount, the evaluation of awareness, and knowledge of CVD and its risk factors and their associations with the lifestyles of girls forms the basis for planning cardiovascular health promotion programs aiming to improve girls’ immediate health and reduce the future burden of CVD among women.MethodsA prospective cross-sectional study was conducted on a random sample of girls attending elementary and intermediate schools in Riyadh, Saudi Arabia. The girls completed a newly validated 24-item questionnaire that assessed their demographic data, lifestyles, and awareness and knowledge of CVD and its risk factors. Anthropometric and blood pressure measurements were obtained. Knowledge scores were calculated on the basis of correct responses and compared between subgroups via analysis of variance to determine associated factors.ResultsIn total, 469 girls (mean age of 12.5 years) were included. Approximately 41.4% of them did not exercise or only exercised once a week. The dietary intake of important food groups was below or just at the minimal recommended servings for most. Overall, 44.1% were overweight/obese, and almost half were identified as hypertensive on the basis of a single resting measurement. Awareness of CVD as a dangerous disease in adults was 50.3%, whereas, cancer was identified by 61% of participants. Individual risk factors were identified by ≈ 25%, and 16.6% were not aware of any risk factors. The overall knowledge score of the participants was 2.6 (± 1.6) out of a total possible score of 8 representing 32.5% (± 20%). Knowledge levels were positively influenced by increasing school grade (P = 0.001) and family history of CVD (P < 0.001). There was no significant favorable association between improved knowledge level and lifestyle factors.ConclusionThe awareness and knowledge of CVD among girls aged 8–16 years are poor and are largely dissociated from their lifestyle. Improved knowledge scores with increasing school grade and family history of CVD confirm a role for schools and families in improving girls’ knowledge. Our findings mirror those obtained in older women, showing that misinformation among women starts in childhood and should be targeted early in life.

Serious gaming as potential training tool for recognition of adverse drug reactions: side-effect exposure—medical education (SeeMe)

PurposeThe recognition of adverse drug reactions (ADRs) is an important part of daily clinical work. However, medical education in this field is mostly drug-based and does not address adequately the complexity of this field regarding individual risk factors and polypharmacy. This study investigates the potential of the web-based serious game SeeMe (side-effect exposure—medical education) in pharmacological education of medical students to improve the recognition of relevant ADRs.MethodsOne hundred fifty-seven medical students were recruited to evaluate the serious game SeeMe. SeeMe was developed to improve knowledge and recognition of ADRs in clinical practice. Players take on the role of a physician trying to understand fictional patients with ADRs. Before and after an 8-week playing period, an evaluation was carried out through a pre- and post-questionnaire and a pre- and post- knowledge test.ResultsThe students achieved significantly better results in the knowledge test, as almost twice as many exam-relevant questions were answered correctly (p < 0.001). The serious game had a positive effect on the students’ perception of the importance of ADRs.ConclusionThis study demonstrates the potential of web- and case-based fictional serious games in medical education. The improved recognition of side effects represents a crucial step for education and training in clinical pharmacology. Future versions of the serious game may take this further and focus on training in the treatment of ADRs and their relevance in various healthcare professions.

Substituting Refined Sugars With Maple Syrup Decreases Key Cardiometabolic Risk Factors in Individuals With Mild Metabolic Alterations: A Randomized, Double-Blind, Controlled Crossover Trial

BackgroundMaple syrup, a minimally transformed sweetener rich in polyphenols, can exert a action and improve metabolic parameters in animal models. However, no randomized clinical trial has investigated this. ObjectivesThis study aims to determine whether replacing refined sugars with an equivalent quantity of maple syrup could decrease key cardiometabolic risk factors in individuals with mild metabolic alterations. MethodsIn a randomized, double-blind, controlled crossover trial with 42 overweight adults with mild cardiometabolic alterations, participants were instructed to substitute 5% of their total caloric intake from added sugars with either maple syrup or an artificially flavored sucrose syrup for 8 wk. The primary outcome included changes in glucose homeostasis, whereas secondary outcomes were changes in other cardiometabolic risk factors such as blood pressure, anthropometric indices, and blood lipid profiles. Exploratory outcomes involved analyzing changes in gut microbiota composition. ResultsReplacing refined sugars with maple syrup over 8 wk decreased the glucose area under the curve when compared with substituting refined sugars with sucrose syrup, as determined during the oral glucose tolerance test, leading to a significant difference between the intervention arms (−50.59 ± 201.92 compared with 29.93 ± 154.90; P < 0.047). Substituting refined sugar with maple syrup also significantly decreased android fat mass (−7.83 ± 175.05 g compared with 67.61 ± 206.71 g; P = 0.02) and systolic blood pressure (−2.72 ± 8.73 mm Hg compared with 0.87 ± 8.99 mm Hg; P = 0.03). No changes in the blood lipid profile were observed. As an exploratory outcome, we further observed that substituting refined sugars with maple syrup promoted selective taxonomic changes in the gut microbiota such as a significant reduction in the abundance of Klebsiella species and decreased microbial functions associated with bacterial-induced cytokine response, when compared with substitution with sucrose syrup. ConclusionsSubstituting refined sugars with maple syrup in individuals with mild metabolic alterations result in a significantly greater reduction of key cardiometabolic risk factors compared with substitution with sucrose syrup, in association with specific changes in gut microbiota. The role of the gut microbiota in these effects remains to be further explored.This trial was registered at clinicaltrials.gov as NCT04117802.

Multi-factor early monitoring method based on D-dimer for iliac crest flap loss

BackgroundIn recent years, the utilization of autogenous vascularized iliac crest flap for repairing jaw defects has seen a significant rise. However, the visual monitoring of iliac bone flaps present challenges, frequently leading to delayed detection of flap loss. Consequently, there’s a urgent need to develop effective indicators for monitoring postoperative complications in iliac crest flaps.MethodsA retrospective analysis was conducted on 160 patients who underwent vascularized iliac crest flap transplantation for jawbone reconstruction from January 2020 to December 2022. We investigated the changes in D-dimer levels among patients with or without postoperative complications. Additionally, multivariable logistic regression analysis was performed to explore potential individual risk factors, including surgical duration, age, pathology type, absolute and relative D-dimer levels, and gender, culminating in the development of a nomogram.ResultsOn the first day following surgery, patients who experienced thrombosis exhibited a substantial increase in plasma D-dimer levels, reaching 3.75 mg/L, 13.84 times higher than the baseline. This difference was statistically significant (P < 0.05) compared to patients without postoperative complications. Furthermore, the nomogram we have developed and validated effectively predicts venous thrombosis, assigning individual risk scores to patients. This predictive tool was assessed in both training and validation cohorts, achieving areas under the curve (AUC) of 0.630 and 0.600, with the 95% confidence intervals of 0.452–0.807 and 0.243–0.957, respectively.ConclusionsOur study illustrates that postoperative plasma D-dimer levels can serve as a sensitive biomarker for monitoring thrombosis-induced flap loss. Moreover, we have developed a novel prediction model that integrates multiple factors, thereby enhancing the accuracy of early identification of patients at risk of thrombosis-associated flap loss. This advancement contributes to improving the overall management and outcomes of such procedures.

Early-Stage Colon Cancer Surveillance: Pattern and Timing of Recurrence and the Role of 5-Year Surveillance

Introduction: Colorectal cancer is the third most prevalent cancer among both men and women with 80% of patients having localized disease enabling curative treatments. Given the low recurrence rate in early-stage disease, there is a growing interest in reviewing follow-up protocols. The aim of this study was to assess the frequency and timing of recurrence in early-stage colon cancer, as well as recurrence patterns. Methods: The data from all patients with colon adenocarcinoma consecutively treated with surgery at the Instituto Português de Oncologia do Porto, EPE, between January 2013 and December 2016, were retrospectively reviewed. Results: A total of 1,372 patients with colon cancer were submitted to surgery during the study period. From this group, 51.4% (n = 705) were early-stage colon cancers. Regarding the pathological stage, 3.5% were stage 0, 37.4% were stage I and 59.1% were stage II. The overall recurrence rate was 6.7%. When considering the group of patients without risk factors, the recurrence rate was 5.6%. The majority of recurrences occurred in the first 3 years of follow-up. The recurrence was diagnosed in the majority of patients through carcinoembryonic antigen elevation, followed by imaging exams. The presence of one or more risk factors (high nuclear grade, vascular invasion, extramural venous invasion, and perineural invasion) showed a statistically significant association with recurrence rate. Conclusion: The recurrence rate was low in early-stage colon cancer, with the majority of recurrences occurring in the first 3 years. Our study results show that surveillance should be tailored according to individual risk factors.

Evaluation of the relationship between dietary acid load and cardiovascular risk factors in patients with type 2 diabetes: a case-control study.

Diets high in dietary acid load are thought to be associated with metabolic diseases. However, the number of studies examining the relationship between dietary acid load and metabolic diseases in Turkey is insufficient. The aim of this study was to investigate the relationship between cardiovascular disease risk factors and dietary acid load in individuals with type 2 diabetes. In this case-control study, 51 participants aged 30-65 years with type 2 diabetes and 59 participants in the control group were included. Blood pressure and biochemical findings were measured. Anthropometric measurements and body composition measurements were made. Dietary intake was assessed using a 3-day (1 day on weekends, 2 days on weekdays) food consumption record. Dietary acid load scores, including potential renal acid load (PRAL) and net endogenous acid production (NEAP), were calculated based on dietary intake. NEAP and PRAL scores were categorized as low and high according to the median value. Smoking status, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), trigylceride (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL), waist-hip ratio (WHR), waist-to- height ratio (WtHR), hemoglobin and fat mass (%) were evaluated as cardiovascular risk factors. The cut-off values of PRAL and NEAP were 3.61 and 44.78 mEq/d, respectively. After adjustment for various covariates, a significant positive association between PRAL and TG levels was observed in the diabetic group [odds ratio (OR), 5.98; 95% CI, 1.45-24.67; p = 0.013]. In contrast, a negative association was found between PRAL and SBP in the control group [odds ratio (OR), 0.21; 95% CI, 0.05-0.83; p = 0.026]. However, these associations were not observed for NEAP values in either group. A higher PRAL value was consistently associated with higher TG level, but other cardiovascular risk factors were not. More longitudinal and interventional studies are needed to better establish a causal effect between dietary acid load and cardiovascular risk factors in individuals with diabetes.

Effects of transcranial direct current stimulation on cognition in MCI with Alzheimer's disease risk factors using Bayesian analysis

Despite the growing interest in precision medicine-based therapies for Alzheimer's disease (AD), little research has been conducted on how individual AD risk factors influence changes in cognitive function following transcranial direct current stimulation (tDCS). This study evaluates the cognitive effects of sequential tDCS on 63 mild cognitive impairment (MCI) patients, considering AD risk factors such as amyloid-beta deposition, APOE ε4, BDNF polymorphism, and sex. Using both frequentist and Bayesian methods, we assessed the interaction of tDCS with these risk factors on cognitive performance. Notably, we found that amyloid-beta deposition significantly interacted with tDCS in improving executive function, specifically Stroop Word-Color scores, with strong Bayesian support for this finding. Memory enhancements were differentially influenced by BDNF Met carrier status. However, sex and APOE ε4 status did not show significant effects. Our results highlight the importance of individual AD risk factors in modulating cognitive outcomes from tDCS, suggesting that precision medicine may offer more effective tDCS treatments tailored to individual risk profiles in early AD stages.

Individual suicide risk factors with resting-state brain functional connectivity patterns in bipolar disorder patients based on latent Dirichlet allocation model

BackgroundThe widespread problem of suicide and its severe burden in bipolar disorder (BD) necessitate the development of objective risk markers, aiming to enhance individual suicide risk prediction in BD. MethodsThis study recruited 123 BD patients (61 patients with prior suicide attempted history (PSAs), 62 without (NSAs)) and 68 healthy controls (HEs). The Latent Dirichlet Allocation (LDA) model was used to decompose the resting state functional connectivity (RSFC) into multiple hyper/hypo-RSFC patterns. Thereafter, according to the quantitative results of individual heterogeneity over latent factor dimensions, the correlations were analyzed to test prediction ability. ResultsModel constructed without introducing suicide-related labels yielded three latent factors with dissociable hyper/hypo-RSFC patterns. In the subsequent analysis, significant differences in the factor distributions of PSAs and NSAs showed biases on the default-mode network (DMN) hyper-RSFC factor (factor 3) and the salience network (SN) and central executive network (CEN) hyper-RSFC factor (factor 1), indicating predictive value. Correlation analysis of the individuals' expressions with their Nurses' Global Assessment of Suicide Risk (NGASR) revealed factor 3 positively correlated (r = 0.4180, p < 0.0001) and factor 1 negatively correlated (r = − 0.2492, p = 0.0055) with suicide risk. Therefore, it could be speculated that patterns more associated with suicide reflected hyper-connectivity in DMN and hypo-connectivity in SN, CEN. ConclusionsThis study provided individual suicide-associated risk factors that could reflect the abnormal RSFC patterns, and explored the suicide related brain mechanisms, which is expected to provide supports for clinical decision-making and timely screening and intervention for individuals at high risks of suicide.

Mendelian randomization study on causal association of TEF and circadian rhythm with pulmonary arterial hypertension

BackgroundPrevious research has revealed the potential impact of circadian rhythms on pulmonary diseases; however, the connection between circadian rhythm-associated Thyrotroph Embryonic Factor (TEF) and Pulmonary Arterial Hypertension (PAH) remains unclear. We aim to assess the genetic causal relationship between TEF and PAH by utilizing two sets of genetic instrumental variables (IV) and publicly available Pulmonary Arterial Hypertension Genome-Wide Association Studies (GWAS).MethodsTotal of 23 independent TEF genetic IVs from recent MR reports and PAH GWAS including 162,962 European individuals were used to perform this two-sample MR study. Gain- and loss-of-function experiments were used to demonstrate the role of TEF in PAH.ResultsOur analysis revealed that as TEF levels increased genetically, there was a corresponding increase in the risk of PAH, as evidenced by IVW (OR = 1.233, 95% CI: 1.054–1.441; P = 0.00871) and weighted median (OR = 1.292, 95% CI for OR: 1.064–1.568; P = 0.00964) methods. Additionally, the up-regulation of TEF expression was associated with a significantly higher likelihood of abnormal circadian rhythm (IVW: P = 0.0024733, β = 0.05239). However, we did not observe a significant positive correlation between circadian rhythm and PAH (IVW: P = 0.3454942, β = 1.4980398). In addition, our in vitro experiments demonstrated that TEF is significantly overexpressed in pulmonary artery smooth muscle cells (PASMCs). And overexpression of TEF promotes PASMC viability and migratory capacity, as well as upregulates the levels of inflammatory cytokines.ConclusionOur analysis suggests a causal relationship between genetically increased TEF levels and an elevated risk of both PAH and abnormal circadian rhythm. Consequently, higher TEF levels may represent a risk factor for individuals with PAH.

A Machine Learning Model for Risk Stratification of Postdiagnosis Diabetic Ketoacidosis Hospitalization in Pediatric Type 1 Diabetes: Retrospective Study.

Diabetic ketoacidosis (DKA) is the leading cause of morbidity and mortality in pediatric type 1 diabetes (T1D), occurring in approximately 20% of patients, with an economic cost of $5.1 billion/year in the United States. Despite multiple risk factors for postdiagnosis DKA, there is still a need for explainable, clinic-ready models that accurately predict DKA hospitalization in established patients with pediatric T1D. We aimed to develop an interpretable machine learning model to predict the risk of postdiagnosis DKA hospitalization in children with T1D using routinely collected time-series of electronic health record (EHR) data. We conducted a retrospective case-control study using EHR data from 1787 patients from among 3794 patients with T1D treated at a large tertiary care US pediatric health system from January 2010 to June 2018. We trained a state-of-the-art; explainable, gradient-boosted ensemble (XGBoost) of decision trees with 44 regularly collected EHR features to predict postdiagnosis DKA. We measured the model's predictive performance using the area under the receiver operating characteristic curve-weighted F1-score, weighted precision, and recall, in a 5-fold cross-validation setting. We analyzed Shapley values to interpret the learned model and gain insight into its predictions. Our model distinguished the cohort that develops DKA postdiagnosis from the one that does not (P<.001). It predicted postdiagnosis DKA risk with an area under the receiver operating characteristic curve of 0.80 (SD 0.04), a weighted F1-score of 0.78 (SD 0.04), and a weighted precision and recall of 0.83 (SD 0.03) and 0.76 (SD 0.05) respectively, using a relatively short history of data from routine clinic follow-ups post diagnosis. On analyzing Shapley values of the model output, we identified key risk factors predicting postdiagnosis DKA both at the cohort and individual levels. We observed sharp changes in postdiagnosis DKA risk with respect to 2 key features (diabetes age and glycated hemoglobin at 12 months), yielding time intervals and glycated hemoglobin cutoffs for potential intervention. By clustering model-generated Shapley values, we automatically stratified the cohort into 3 groups with 5%, 20%, and 48% risk of postdiagnosis DKA. We have built an explainable, predictive, machine learning model with potential for integration into clinical workflow. The model risk-stratifies patients with pediatric T1D and identifies patients with the highest postdiagnosis DKA risk using limited follow-up data starting from the time of diagnosis. The model identifies key time points and risk factors to direct clinical interventions at both the individual and cohort levels. Further research with data from multiple hospital systems can help us assess how well our model generalizes to other populations. The clinical importance of our work is that the model can predict patients most at risk for postdiagnosis DKA and identify preventive interventions based on mitigation of individualized risk factors.

The Expansion of Artificial Intelligence in Modifying and Enhancing the Current Management of Abdominal Aortic Aneurysms: A Literature Review.

An abdominal aortic aneurysm(AAA) is a pathological dilation that is 3cm or greater resulting in a bulging or balloon appearance. To meet a personalized therapeutic approach for patients, artificial intelligence (AI) can exhibit an array of applications ranging from decoding patterns from large data sets to predicting new data. The review aims to discuss how AI can assist and improve the standard of care and management plans for these patients. A comprehensive non-systematic literature review was carried out for published material on the use of AI relating to AAAs. The PubMed and Google Scholar databases were used to scout for articles relating to the title of this review. The review included 54 literature papers in this study. AI is involved on a genomic level, which assists in screening, diagnosing, and identifying individual risk factors of a patient. Personalized management plans can be created with AI predictions using patient data to reduce the risk of in-hospital mortality following a repair or due to complications. AI represents a promising group of programs aimed at improving patient management and assisting surgeons in making beneficial decisions to improve the patient's prognosis.