Multiple Risk Factors Research Articles

The Impact of Misaligned Perceived and Objective Fall Risk in Cognitively Impaired Older People.

Cognitive impairment (CI) may impair the ability to accurately perceive physical capacity and fall risk. We investigated perceived (measured as concern about falls) and physiological fall risk in community-dwelling older people with CI, the characteristics of the aligned and misaligned groups and the impact of misaligned perceptions on falls. Participants (n= 293) with mild-moderate CI were classified into four groups based on validated physiological and perceived fall risk assessments: 1) vigorous: low perceived and physiological fall risk; 2) anxious: high perceived and low physiological fall risk; 3) unaware: low perceived and high physiological fall risk; and 4) aware: high perceived and physiological fall risk. Groups were compared with respect to neuropsychological and physical function, activity and quality of life measures, and prospective falls (12-months). The anxious (IRR = 1.70, 95% CI = 1.02-2.84), unaware (IRR = 2.00, 95% CI = 1.22-3.26), and aware (IRR = 2.53, 95% CI = 1.67-3.84) groups had significantly higher fall rates than the vigorous group but fall rates did not significantly differ among these groups. Compared with the vigorous group: the anxious group had higher depression scores and reduced mobility and quality of life; the unaware group had poorer global cognition, executive function and mobility and lower physical activity levels; and the aware group had an increased prevalence of multiple physical and cognitive fall risk factors. Fall rates were increased in participants who had increased perceived and/or physiological fall risk. Contrasting fall risk patterns were evident in those who under- and over-estimated their fall risk. Understanding these characteristics will help guide fall risk assessment and prevention strategies in community-dwelling older people with CI.

A Latent Class Analysis of Family Eating Behaviors and Home Environment Habits on Preschool-Aged Children's Body Mass Index.

Background: The etiology of obesity is multifaceted, with multiple risk factors occurring during early childhood (e.g., fast food frequency, eating dinner as a family, TV in the bedroom). Many past studies have largely considered obesity risk factors in isolation, when in reality, the risk factors likely cluster together. A latent class analysis can be used to identify patterns in child eating behaviors, parent feeding behaviors, and household habits among preschool-aged children and their families to identify distinct, heterogenous classes and to determine if classes are associated with overweight and obesity. Methods: We used data from a community-based study of 624 three- to five-year-old children and a parent in New Hampshire, from March 2014 to October 2015. Parent-reported data were used to determine frequency of eating behaviors and household habits. Height and weight were objectively measured. Results: Four classes were identified; Class 1: "Healthy/Mildly accommodating," Class 2: "Healthy/Accommodating," Class 3: "Moderately healthy/Moderately accommodating," and Class 4: "Least healthy/Least accommodating." Compared with Class 1, children in Class 4 had increased odds of being overweight or obese [adjusted odds ratio (aOR): 1.64, 95% confidence interval (CI): 1.13-2.15], whereas Classes 2 and 3 were not associated with BMI (Class 2: aOR: 1.24, 95% CI: 0.62-1.86; Class 3: aOR: 1.31, 95% CI: 0.81-1.81). Conclusion: Study findings highlight that child-parent interactions around meals differentially relate to children's weight status given the context of children's eating habits. Most important, our study findings confirm the importance of adapting multiple healthy habits within the home social and physical environment to offset obesity risk in young children.

Fuzzy risk analysis in crop selection using information measures on quadripartitioned single-valued neutrosophic sets

Crop selection is a critical task that involves assessing multiple risk factors to achieve maximum yield. Therefore, risk assessment plays a pivotal role in choosing suitable crops for cultivation. Probabilistic and possibilistic methods are the two primary approaches used for the crop selection process. Probabilistic methods are cost-intensive due to data handling, while possibilistic methods, utilizing linguistic variables, are considered more reliable. In this article, we represent such linguistic variables using Quadripartitioned Single-Valued Neutrosophic Sets (QSVNSs), extensions of Single-Valued Neutrosophic Sets (SVNSs) characterized by four independent membership functions that enhance uncertainty accommodation. We propose two QSVNS-based information measures, entropy and similarity, to transform the final risks evaluated in the form of QSVNSs into linguistic variables for easier comprehension by the general audience. We apply this framework to mustard and paddy cultivation in Assam, a state located in northeastern India, conducting thorough analyses and validation tests. Additionally, statistical tests are presented to demonstrate the significance of the obtained results. The final risk of mustard cultivation is found to be ‘absolutely high’, as the largest similarity value of 0.9910 is obtained for the linguistic term ‘absolutely high’ among all computed similarity value results. Similarly, for paddy cultivation, the largest similarity value of 0.9159 is obtained for the linguistic term ‘very low’, indicating its final risk in our assumed scenario. Thus, the veracity and proficiency of our newly constructed measures are reflected in their practical applications.

Influence of multiple risk factor control level on cardiovascular outcomes in hypertensive patients.

The relationship between the level of baseline risk factor control and cardiovascular outcomes in hypertensive patients with blood pressure intervention is not well understood. It is also unclear whether the level of baseline risk factor control is persuasively associated with cardiovascular outcomes in hypertensive patients with blood pressure lowering strategy. We performed an analysis of the Strategy of Blood Pressure Intervention in the Elderly Hypertensive Patients (STEP) trial. Participants without complete baseline risk factor data were excluded. The primary outcome was a composite of cardiovascular events and all-cause mortality. Cox proportional hazard models were used to calculate the hazard ratio (HR) and estimate association between risk factor control levels (≥6, 5, 4, and≤3) and cardiovascular outcomes. A total of 8337 participants were involved in the analysis and the median follow-up period was 3.19 years. Each additional risk factor uncontrolled was associated with a 24% higher cardiovascular risk (HR 1.24, 95% CI 1.11-1.37). Compared with participants with optimal risk factor control, those with≤3 factors control exhibited 95% higher cardiovascular risk (HR 1.95, 95% CI 1.37-2.77). The corresponding protective effects of multiple risk factor modification were not influenced by intensive or standard antihypertensive treatment (P for interaction=0.71). A stepwise association was observed between cardiovascular risk and the number of risk factor control in hypertensive patients. The more risk factor was modified, the less cardiovascular risk was observed, irrespective of different blood pressure lowering strategies. Comprehensive risk factor control strategies are warranted to reduce cardiovascular disease risk in hypertensive patients. Trial registration STEP ClinicalTrials.gov number, NCT03015311. Registered 2 January 2017.

Prevalence of Cutaneous Adverse Drug Reactions According to Iraqi Pharmacovigilance Center; A retrospective study for 11 years (2010-2021)

Background: Cutaneous Adverse Drug Reactions (CADRs) are among the leading causes of morbidity and mortality. Insufficient data exists on cutaneous adverse reactions, as many of these reactions are not reported due to their constantly changing patterns and the interaction of multiple risk factors. Aim: This study aims to evaluate the prevalence of cutaneous reactions in Iraq and find the most commonly involved active ingredients with the commonest skin manifestations. Method: A retrospective study based on the safety reports of patients having cutaneous reactions that were collected and submitted to VigiBase by the Iraqi Pharmacovigilance Center between 2010 and 2021. The study involved the analysis of gender, age, medicines, type of CADR, and seriousness of more than 4,300 reports. Results: Skin rash was the most commonly reported CADR, and antibiotics were the leading drug class; ceftriaxone and vancomycin were responsible for 40.3% and 16.2% of the cases caused by antibiotics only, respectively. The mean age of the patients was 28 years, and the male-to-female ratio was 0.78:1. Out of the total number of cases, more than 1300 were deemed serious, and 15 patients have passed away. Conclusion: Iraq comes in the 51st place among other countries in the number of skin and skin-related ADR cases. Older adults are at higher risk of developing serious CADRs. Ceftriaxone and rash were the leading drug and cutaneous manifestations, respectively.

Random survival forest for predicting the combined effects of multiple physiological risk factors on all-cause mortality

Understanding the combined effects of risk factors on all-cause mortality is crucial for implementing effective risk stratification and designing targeted interventions, but such combined effects are understudied. We aim to use survival-tree based machine learning models as more flexible nonparametric techniques to examine the combined effects of multiple physiological risk factors on mortality. More specifically, we (1) study the combined effects between multiple physiological factors and all-cause mortality, (2) identify the five most influential factors and visualize their combined influence on all-cause mortality, and (3) compare the mortality cut-offs with the current clinical thresholds. Data from the 1999–2014 NHANES Survey were linked to National Death Index data with follow-up through 2015 for 17,790 adults. We observed that the five most influential factors affecting mortality are the tobacco smoking biomarker cotinine, glomerular filtration rate (GFR), plasma glucose, sex, and white blood cell count. Specifically, high mortality risk is associated with being male, active smoking, low GFR, elevated plasma glucose levels, and high white blood cell count. The identified mortality-based cutoffs for these factors are mostly consistent with relevant studies and current clinical thresholds. This approach enabled us to identify important cutoffs and provide enhanced risk prediction as an important basis to inform clinical practice and develop new strategies for precision medicine.

Correlation between platelet metrics and cardiovascular risk in prediabetes with coronary artery disease: A two-year cross-sectional study

ObjectivesPrediabetes is associated with coronary artery disease (CAD), as even a 1% increase in glycated hemoglobin (HbA1c) may increase CAD severity and associated mortality over ten years. A definite association exists between platelet indices, CAD, and diabetes mellitus. Although research has demonstrated an association between CAD and prediabetes as well as platelet indices, there have been no attempts to assess the association of platelet indices in prediabetic patients who are at risk of CAD. MethodsA cross-sectional study took place between 2019 and 2020 in the medical department of a rural medical college located in Central Maharashtra, India. A total of 180 patients with prediabetes and documented CAD on coronary angiography were enrolled in this study. For all participants, platelet indices, blood sugar levels, glycosylated hemoglobin (HbA1c) levels, lipid profiles, and anthropometric measurements were recorded, and then statistical analysis was conducted. ResultsMean platelet volume had a substantial positive correlation with HbA1c, fasting blood sugar, postprandial blood sugar, systolic blood pressure, diastolic blood pressure, body mass index, waist circumference, and waist/hip ratio, with correlation coefficients of 0.2, 0.173, 0.219, 0.218, 0.234, 0.165, 0.182, and 0.164, respectively. A significant negative correlation was found between platelet distribution width and high-density lipoprotein (HDL) level, with a correlation coefficient of −0.373. ConclusionPlatelet indices, which are routinely available through standard clinical investigations, can effectively predict the risk of CAD in prediabetic patients. Their strong association with multiple risk factors allows for enhanced prognosis and facilitates early intervention planning for CAD in this high-risk group.

Risk assessment and prediction of nosocomial infections based on surveillance data using machine learning methods

BackgroundNosocomial infections with heavy disease burden are becoming a major threat to the health care system around the world. Through long-term, systematic, continuous data collection and analysis, Nosocomial infection surveillance (NIS) systems are constructed in each hospital; while these data are only used as real-time surveillance but fail to realize the prediction and early warning function. Study is to screen effective predictors from the routine NIS data, through integrating the multiple risk factors and Machine learning (ML) methods, and eventually realize the trend prediction and risk threshold of Incidence of Nosocomial infection (INI).MethodsWe selected two representative hospitals in southern and northern China, and collected NIS data from 2014 to 2021. Thirty-nine factors including hospital operation volume, nosocomial infection, antibacterial drug use and outdoor temperature data, etc. Five ML methods were used to fit the INI prediction model respectively, and to evaluate and compare their performance.ResultsCompared with other models, Random Forest showed the best performance (5-fold AUC = 0.983) in both hospitals, followed by Support Vector Machine. Among all the factors, 12 indicators were significantly different between high-risk and low-risk groups for INI (P < 0.05). After screening the effective predictors through importance analysis, prediction model of the time trend was successfully constructed (R2 = 0.473 and 0.780, BIC = -1.537 and -0.731).ConclusionsThe number of surgeries, antibiotics use density, critical disease rate and unreasonable prescription rate and other key indicators could be fitted to be the threshold predictions of INI and quantitative early warning.

Charting Wellness in India: Piloting the iTHRIVE's Functional Nutrition Approach to Improve Glycaemic and Inflammatory Parameters in Prediabetes and Type 2 Diabetes Mellitus.

Introduction Type 2 diabetes mellitus (T2DM) is characterized by elevation of blood glucose levels due to underlying insulin resistance and inflammation. Multiple modifiable risk factors such as unhealthy dietary habits, physical inactivity, obesity, smoking and psychological stress contribute toT2DM. Weinvestigated the efficacy of a comprehensive functional nutrition approach aimed at mitigating T2DMusing the iTHRIVE approach which encompassed anti-inflammatory and elimination diets, micronutrient supplements, physical activity, stress managementand environmental modifications through a pre-post study design. The research assessed changes in blood glucose and inflammatory markers following the implementation of thefunctional nutrition program. Methods A prospective pre-post intervention pilot study was conducted at ThriveTribe Wellness Solutions Pvt Ltd. (iTHRIVE), where 50 study participants from urban areas of Pune city, India(n=25 each group) were recruited voluntarily in the age group of 20-60 years. The participants were subjected to 90 days of the iTHRIVE functional nutrition approach which consisted of eliminating certain inflammatory foods and adding a combination of nutritious organic foods, adding dietary supplements like magnesium, vitamin D, alpha lipoic acid, chromium picolinate, berberine and biogymnema, physical activities like resistance training, stress reduction techniques like meditation and deep breathing exercises along with environmental changes. The blood parameters like fasting blood glucose, postprandial blood glucose, glycated haemoglobin (HbA1C), fasting serum insulin, post-prandial serum insulin, high sensitivity C-reactive protein (hs-CRP), erythrocyte sedimentation rate (ESR), vitamin D, body weight and waist circumference were measured before and after the intervention. The changes were statistically analyzed using a paired t-test. Results The mean age of the participants was found to be 43.76±10.58 years. Around 68%of the participants were prediabetic (HbA1c: 5.7-6.4%) and 32% had T2DM (HbA1c ≥6.5%). A significant reduction was observed in the average HbA1c (13.75% reduction, p<0.0001), average post-prandial blood glucose levels (14.51% reduction, p<0.048), average post-prandial serum insulin (34.31% reduction, p<0.017) and average ESR levels (34.51% reduction, p<0.006). The hs-CRP levels were reduced by 6.6%, but not statistically significant. The average body weight of the participants dropped from 78.59±15.18 kg to 75.20±14.20 kg with a mean loss of 2.91 kg (p<0.05) whereas the waist circumference decreased from 37.54±5.09 to 35.97±4.74 inches with an average loss of 1.19 inches (p<0.0004). Conclusions Following the intervention, several health indicators indicated significant improvements. Particularly, there was a significant drop in HbA1c levels, suggesting better long-term blood glucose control. Blood glucose and serum insulin levels after a meal dropped significantly, indicating enhanced insulin sensitivity. There was a decrease in systemic inflammation as evidenced by the decreasein ESR levels. These results imply that the iTHRIVE functional nutrition approach used in this investigation might be beneficial for enhancing glycemic controland insulin sensitivity, along with reducing inflammatory markers in people with prediabetes and T2DM. Larger sample sizes and longer periods of monitoring would be useful in subsequent research to validate and build on these encouraging findings.

A new competing risks model with applications to blood cancer data

Competing risks models are invaluable probabilistic models in survival analysis, a particular part of medical research. Such models deal with research problems that involve multiple potential risk factors that compete with each other to cause death (i.e., failure from a statistical perspective). Competing risks models' flexibility must be thoroughly explored to guarantee suitability for multifaceted risk scenarios (e.g., modeling data of malicious diseases where factors such as treatment response and progression are intertwined). This article considers a new competing risks model called the additive generalized linear-exponential (AGLE) competing risks model. The proposed model is expected to be more robust and superior to other well-known models when modeling real-life data. A mathematical treatment for the properties of the new model is first considered. Afterward, model parameters estimation via various estimation methods is discussed. The critical role of estimating shape parameters in understanding blood cancer's survival and failure mechanisms is highlighted. Furthermore, the bias and root mean square error of different estimation methods are examined numerically through Monte Carlo simulations. The simulation study indicated that the maximum product of spacings estimation method for the model parameters has the optimal balance of bias and variance as the sample sizes increase. Two real-life blood cancer data sets are analyzed to illustrate the application of the proposed model. The analysis outcomes support the AGLE model's robustness, with low Kolmogorov-Smirnov statistics and high p-value, affirming its superior fit for blood cancer data compared to other well-known models.

The severity of dry eye symptoms and risk factors among university students in Saudi Arabia: a cross-sectional study

Dry eye syndrome (DES) is a tear film disorder caused by increased tear evaporation or decreased production. The heavy workload on the eye and the increased usage of digital screens may decrease blink frequency, leading to an increased evaporation rate and an upsurge in the incidence and severity of DES. This study aims to assess the severity of DES symptoms and the risk factors among university students. A cross-sectional study was conducted at Umm AlQura University to evaluate the severity of DES among students and explore its potential association with digital screen use. Validated questionnaires were used to assess the severity of DES and digital screen usage. The study included 457 participants, of which 13% had symptoms suggestive of severe DES. Furthermore, multiple risk factors had a significant association with the severity of DES, including gender, use of monitor filters, monitor and room brightness, and smoking habits. DES symptoms were prevalent among university students, particularly female students. Although there was no significant association with the duration of screen usage and collage distribution. Other factors however, such as the usage of screen monitors and the brightness of both the monitor and the room, were significantly associated with the severity of DES symptoms.

Analyzing ship collision accidents in China: A framework based on the N-K model and Bayesian networks

Maritime accidents are frequent in China, with collisions constituting a significant portion, leading to substantial casualties, financial losses, and environmental harm. Analyzing collision risk is crucial for safe shipping operations, as such accidents arise when multiple risk factors interact beyond certain thresholds. Thus, understanding the coupled relationships among these factors is essential for accident prevention. This study presents a quantitative coupling risk assessment approach for collisions using the N–K model and Bayesian networks (BNs). Through an analysis of 304 accident reports from the China Maritime Safety Administration (CMSA), four primary risk factors (human, ship, environment, and management) are identified. The N–K model quantifies the coupling degree between these factors, while a BN model further elucidates and quantifies the collision risk based on the calculations of N–K model. Validation of the BN model is followed by sensitivity analysis to assess the impact of risk factors on accident occurrence. Subsequently, the method is applied to a case study on collision risk assessment in Chinese waters. Findings indicate that multifactor coupling has a higher occurrence probability than two-factor coupling, with human-ship-environment-management coupling presenting the highest likelihood. Human and management factors emerge as pivotal in collision incidents, while the impact of ship and environmental factors on coupling becomes more pronounced as their probabilities vary. Leveraging the capability of BNs to handle uncertainties and logical relationships, combined with the data-driven N–K model, mitigates subjectivity. The results propose the formulation of risk management strategies and measures for practitioners to enhance maritime safety.

Risk factors and development of machine learning diagnostic models for lateral lymph node metastasis in rectal cancer: multicentre study.

The diagnostic criteria for lateral lymph node metastasis in rectal cancer have not been established. This research aimed to investigate the risk factors for lateral lymph node metastasis and develop machine learning models combining these risk factors to improve the diagnostic performance of standard imaging. This multicentre prospective study included patients who underwent lateral lymph node dissection without preoperative treatment for rectal cancer between 2017 and 2019 in 15 Japanese institutions. First, preoperative clinicopathological factors and magnetic resonance imaging findings were evaluated using multivariable analyses for their correlation with lateral lymph node metastasis. Next, machine learning diagnostic models for lateral lymph node metastasis were developed combining these risk factors. The models were tested in a training set and in an internal validation cohort and their diagnostic performance was tested using receiver operating characteristic curve analyses. Of 212 rectal cancers, 122 patients were selected, including 232 lateral pelvic sides, 30 sides of which had pathological lateral lymph node metastasis. Multivariable analysis revealed that poorly differentiated/mucinous adenocarcinoma, extramural vascular invasion, tumour deposit and a short-axis diameter of lateral lymph node ≥ 6.0 mm were independent risk factors for lateral lymph node metastasis. Patients were randomly divided into a training cohort (139 sides) and a test cohort (93 sides) and machine learning models were computed on the basis of a combination of significant features (including: histological type, extramural vascular invasion, tumour deposit, short- and long-axis diameter of lateral lymph node, body mass index, serum carcinoembryonic antigen level, cT, cN, cM, irregular border and mixed signal intensity). The top three models with the highest sensitivity in the training cohort were as follows: support vector machine (sensitivity, 1.000; specificity, 0.773), light gradient boosting machine (sensitivity, 0.950; specificity, 0.918) and ensemble learning (sensitivity, 0.950; specificity, 0.917). The diagnostic performances of these models in the test cohort were as follows: support vector machine (sensitivity, 0.750; specificity, 0.667), light gradient boosting machine (sensitivity, 0.500; specificity, 0.852) and ensemble learning (sensitivity, 0.667; specificity, 0.864). Machine learning models combining multiple risk factors can contribute to improving diagnostic performance of lateral lymph node metastasis.

Long-term retention and survival of cemented implant-supported zirconia and metal-ceramic single crowns: A retrospective study.

To evaluate the effect of different cement types on the incidence of failure and loss of retention of zirconia and metal-ceramic single crowns (SCs) cemented on implant abutments. We placed 567 implant-supported SCs in 358 patients and retrospectively evaluated long-term retention for up to 12.8 years. The frameworks were made from metal alloy (n = 307) or zirconia (n = 260). SCs were cemented with permanent (glass-ionomer cement; n = 376) or semipermanent cement (zinc oxide non-eugenol cement; n = 191) on standardized (n = 446) or customized (n = 121) abutments. Kaplan-Meier curves were used to calculate the incidence of decementation. Differences between survival curves were assessed with log-rank tests. Cox-regression analysis was performed to evaluate multiple risk factors. Of the 567 SCs, 22 failed because of technical complications and four because of implant loss. Loss of retention was observed in 50 SCs. Analysis revealed a 7% probability of loss of retention for zirconia and 16% for metal-ceramic SCs after 10 years (p = .011). After 5 years, loss of retention was higher for standardized abutments than for customized abutments (p = .014). The probability of loss of retention was higher with semipermanent than with permanent cement (p = .001). Cox-regression analysis revealed semipermanent cement as the only significant risk factor for SC failure (p = .026). In contrast to semipermanent cement, permanent cement provides acceptable long-term retention of cemented implant-supported SCs. These possible positive effects of customized abutments have to be controlled with larger sample sizes.

Coexistence of Standard Modifiable, Other Classical, and Novel and Classical Atherosclerotic Cardiovascular Disease Risk Factors in Middle Eastern Young Women.

The coexistence of multiple standard modifiable risk factors (SMuRFs),classical and novel risk factors (RFs) for atherosclerotic cardiovascular disease (ASCVD) is common in the Middle East (ME). There is a paucity of data on the coexistence of these RFs in ME young women. Comparing the prevalence and the statistical patterns of the SMuRFs, classical and novel RFs in target population. In this case-control (1:2) study, consecutive young women aged 18-50 years were enrolled in 12 centers (July 2021 to October 2023). Prevalence and coexistence of 19 RFs were compared between cases with ASCVD and their controls. The RFs included SMuRFs (hypertension, type 2 diabetes, dyslipidemia, and cigarette smoking), other classical RF (obesity, family history of premature ASCVD, and physical inactivity), novel RFs and social determinants of health (health insurance, place of residence, depression, and level of education). The study included 627 subjects; 209 had ASCVD (median age 46 years, IQR 49-42 years) and 418 controls (median age 45 years, IQR 48-41 years). The presence of 1-2 RFs; (ASCVD: 63.2%, Control: 54.1%, p=0.037) and 3-4 RFs; (ASCVD: 27.8%, Control: 3.3%, p < 0.001) SMuRFs was more prevalent in women with ASCVD. Similarly, the presence of 4-5 RFs; (ASCVD: 40.7%, Control: 14.6%, p<0.001), and 6-7 (ASCVD: 10.5%, Control: 1%, p < 0.001). The classical RF were also significantly common in these women. The distribution of multiple novel RF was not statistically significant across both groups. Finally, regarding the socioeconomic RFs in women with ASCVDs, the presence of 1-2 RFs (ASCVD: 59.8%, Control: 76.1%, p < 0.001) was significantly less common while the presence of 3-4 RFs (ASCVD: 39.2%, Control: 21.8%, p < 0.001) was vastly more common. An elevated rate of coexistence of classical RF in the case group, mainly socioeconomic and SMuRFs. By managing them primary and secondary ASCVDs prevention attained.

A Study of Abnormal Echocardiogram Findings in Patients With Chronic Kidney Disease With Reference to Cardiac Biomarkers.

Background Chronic kidney disease (CKD) isprevalent, especially in populations with multiple risk factors, such as undiagnosed and untreated hypertension and diabetes mellitus. Cardiovascular diseases (CVDs) leading to poor quality of life or even death have been noted as an increasing trend among CKD patients. This study aims to use cardiac biomarkers to evaluate their association with abnormal echocardiogram findings in CKD patients, which may allow for the improvement of quality of life with early treatment. Methods and materials This observational, cross-sectional study was conducted on 103 diagnosed CKD patients at the Department of Medicine, Dr. D.Y. Patil Medical College, Hospital, and Research Centre in Pimpri, Pune, from January 2023 to January 2024. Ethical approval was acquired, and written consent was obtained from participants. The study utilised cardiac biomarkers such as N-terminal pro-B type natriuretic peptide (NT-proBNP), troponin I (Trop I), and a radiological tool, transthoracic echocardiography (TTE). All patients with diagnosed stages 3, 4, and 5 CKD between the ages of 18-80 years were included, and the exclusion criteria consisted of patients who had already undergone cardiac interventional procedures or known cases of CVDs. Results In our study, out of 103 participants, the majority were aged between 51 and 60 years (35, 34%). The study had a majority of male participants (76, 73.8%). Major risk factors were considered, noting hypertension in 63 (61.2%) and diabetes mellitus in 81(78.6%). Participants were divided into stages of CKD. Cardiac biomarkers such as NT-proBNP and Trop I levels were assessed in all participants in the different stages of CKD showing elevated levels of NT-proBNP across all stages. Transthoracic echocardiogram (TTE) screening tests were also evaluated for all patients, showing diastolic dysfunction (DD) as the most common finding in stage 3 (5, 41.67%), stage 4 (25, 62.5%), and stage 5 (35, 68.83%), followed by left ventricular hypertrophy (LVH) as a common finding in stage 3 (4, 33.3%), stage 4 (20, 50%), and stage 5 (30, 58.2%) CKD. Furthermore, the association between raised cardiac biomarkers and abnormal echocardiogram findings across the stages of CKD was evaluated, resulting in a statistically significant association with p-values < 0.05. Conclusion This research sheds light on the association between cardiac biomarkers and abnormal echocardiogram findings in CKD patients and helps us determine if there is any added benefit orpredictive value in screening these individuals at different stages of the disease to allow early interventionand improvement in treatment and quality of life.

Evaluation of the prevalence of giardiasis and associated factors in Wardak province, center of Afghanistan

Introduction: Giardia intestinalis is a causative agent of gastrointestinal infections worldwide. Contaminated food, feces, drinking water (orofecal route), and factors like economic conditions, culture, and behavioral factors contribute to its transmission. Wardak province is located in the central region of Afghanistan, divided into eight districts, with a population of 656,720. Methods: A total of 274 patients with diarrhea referred to Wardak Hospital were studied, and among them, 17 individuals (10 males (58.8%) and 7 females (41.2%) tested positive for Giardia spp. by microscopy during 2023. In this cross-sectional study, socioeconomic, cultural, and symptomatology information were collected. The association between risk factors and intestinal parasitic infections was analyzed using Chi-Square and Fisher's exact tests with SPSS 26 and GraphPad Prism 8 software at a significance level of P ≤ 0.05. Results: More than half of the patients were under 30 years old. Most cases of the disease were observed in hot seasons (spring and summer). A significant correlation was found between the prevalence of giardiasis and factors such as close contact with animals, the use of unfiltered water, soil contact, and warmer seasons. No significant correlation was observed between economic status and travel history. 85% of patients had watery diarrhea, and 15% had bloody diarrhea. Conclusion: This is the first epidemiological study conducted in Wardak province, central Afghanistan. The findings reveal the prevalence of giardiasis and its interaction with multiple risk factors. This study suggests that giardiasis is an important causative factor for gastrointestinal diseases in the study region.

SIC Position paper: Treat to prevent the first event - intensive LDL cholesterol lowering in patients at very high cardiovascular risk without a previous cardiovascular event. From ESC guidelines to clinical practice

Cardiovascular (CV) diseases account for over 4 million deaths every year in Europe and over 220 000 deaths in Italy, representing the leading cause of morbidity and mortality worldwide. The European Society of Cardiology (ESC) guidelines have visionary included in the at very high CV risk group patients without previous acute ischemic events, such as those with subclinical atherosclerosis, chronic coronary syndrome or peripheral arterial disease, familial hypercholesterolemia, diabetes mellitus with target organ damage or multiple associated risk factors, and those with high calculated CV risk score, recommending to consider them and to achieve the same LDL-cholesterol targets as for secondary prevention patients. The aim of this position paper is to provide an updated overview of ESC guidelines that focuses on these patient categories to raise awareness within the clinical community regarding CV risk reduction in this specific epidemiological context.

Patterns of acetaminophen toxicity among patients with low-risk serum concentrations.

In 2012, the Commission on Human Medicines mandated lowering the acetaminophen toxicity nomogram treatment threshold in the UK to 100 µg/ml at 4 h post-ingestion. The present study aim was to evaluate biochemical and liver toxicity patterns in patients who presented with acetaminophen overdose and had low serum acetaminophen concentrations (<150 µg/ml). Patients admitted to the emergency department with a clear history of acute acetaminophen overdose with or without other medication or ethanol were consecutively enrolled into this retrospective cohort study. Patients with serum acetaminophen concentration >150 µg/ml or an unknown ingestion time were excluded. Data were extracted from electronic medical records and are presented as mean ± SD or median (interquartile range). A total of 103 patients were included (median age, 17 [4-21] years) and 80 (78%) were female. The median ingested acetaminophen dose was 5000 (2850-7650) mg. At baseline, the median serum acetaminophen concentration was 42 (4.5-64.8) µg/ml, and median alanine aminotransferase and aspartate aminotransferase levels were 22 (17-28) and 27 (16-45) IU/L, respectively. Twenty patients were treated with acetylcysteine, with none developing adverse reactions. No patient developed hepatotoxicity, including patients with initial multiple product ingestion or other risk factors. Patients presenting with an acute acetaminophen overdose with acetaminophen level <150 µg/ml, including patients with other risk factors, are at low risk of hepatotoxicity.

Insights on the Correlation between Mitochondrial Dysfunction and the Progression of Parkinson's Disease.

The aetiology of a progressive neuronal Parkinson's disease has been discussed in several studies. However, due to the multiple risk factors involved in its development, such as environmental toxicity, parental inheritance, misfolding of protein, ageing, generation of reactive oxygen species, degradation of dopaminergic neurons, formation of neurotoxins, mitochondria dysfunction, and genetic mutations, its mechanism of involvement is still discernible. Therefore, this study aimed to review the processes or systems that are crucially implicated in the conversion of MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) into its lethal form, which directly blockades the performance of mitochondria, leading to the formation of oxidative stress in the dopaminergic neurons of substantia nigra pars compacta (SNpc) and resulting in the progression of an incurable Parkinson's disease. This review also comprises an overview of the mutated genes that are frequently associated with mitochondrial dysfunction and the progression of Parkinson's disease. Altogether, this review would help future researchers to develop an efficient therapeutic approach for the management of Parkinson's disease via identifying potent prognostic and diagnostic biomarkers.