Pediatric acute kidney injury and adverse health outcomes: using a foundational framework to evaluate a causal link.

Acute kidney injury (AKI) is a major global health problem, expensive to manage, and its associations with negative pediatric health outcomes have been clearly demonstrated. One of the most fundamental questions to consider as we use previous epidemiological information to advance research and care paradigms is the strength of the causal link between pediatric AKI and health outcomes. In this review, we apply the foundational framework of the Bradford Hill criteria to evaluate the extent to which a causal link exists between AKI and the associated adverse outcomes in children. Available data in children support a causal link between AKI and short-term outcomes including mortality, length of stay, and ventilation time. Clarifying the causal nature of longer term associations requires further high-quality observational studies in children, careful consideration of what defines the most meaningful and measurable longer term outcomes after pediatric AKI, and integration of evolving biological data related to mechanisms of disease. Preventing or mitigating AKI should lead to improved outcomes. Demonstrating such reversibility will solidify confidence in the causal relationship, improve child health, and highlight an aspect which is highly relevant to clinicians, scientists, and policy makers.

Causal relationship between Helicobacter pylori infection and IgA nephropathy: a bidirectional two-sample mendelian randomization study.

IgA nephropathy (IgAN) is one of the most common primary glomerulonephritis, and serum Helicobacter pylori (H. pylori) antibody levels are increased in patients with IgA N, but the role of H. pylori infection in the pathogenesis of IgAN is unclear. In this study, we investigated whether there is a causal relationship and reverse causality between IgAN and H. pylori infection by using a bidirectional two-sample Mendelian randomization (MR) analysis. This study was estimated using inverse variance weighted (IVW), MR-Egger and weighted median methods, with the IVW method having the strongest statistical efficacy. Seven common serum H. pylori antibodies were selected as exposure factors for positive MR analysis. The results showed that there was no evidence of a causal relationship between H. pylori infection and IgAN. Reverse MR analysis showed that there was also no evidence that the occurrence of IgAN leads to an increased risk of H. pylori infection.

Regional Brain Activity and Neural Network Changes in Cognitive-motor Dual-task Interference: A Functional Near-infrared Spectroscopy Study.

Previous neuroimaging studies have reported dual-task interference (DTi) and deterioration of task performance in a cognitive-motor dual task (DT) compared to that in a single task (ST). Greater frontoparietal activity is a neural signature of DTi; nonetheless, the underlying mechanism of cortical network in DTi still remains unclear. This study aimed to investigate the regional brain activity and neural network changes during DTi induced by highly demanding cognitive-motor DT. Thirty-four right-handed healthy young adults performed the spiral-drawing task. They underwent a paced auditory serial addition test (PASAT) simultaneously or independently while their cortical activity was measured using functional near-infrared spectroscopy. Motor performance was determined using the balanced integration score (BIS), a balanced index of drawing speed and precision. The cognitive task of the PASAT was administered with two difficulty levels defined by 1 s (PASAT-1s) and 2 s (PASAT-2s) intervals, allowing for the serial addition of numbers. Cognitive performance was determined using the percentage of correct responses. These motor and cognitive performances were significantly reduced during DT, which combined a drawing and a cognitive task at either difficulty level, compared to those in the corresponding ST conditions. The DT conditions were also characterized by significantly increased activity in the right dorsolateral prefrontal cortex (DLPFC) compared to that in the ST conditions. Multivariate Granger causality (GC) analysis of cortical activity in the selected frontoparietal regions of interest further revealed selective top-down causal connectivity from the right DLPFC to the right inferior parietal cortex during DTs. Furthermore, changes in the frontoparietal GC connectivity strength between the PASAT-2s DT and ST conditions significantly correlated negatively with changes in the percentage of correct responses. Therefore, DTi can occur even in cognitively proficient young adults, and the right DLPFC and frontoparietal network being crucial neural mechanisms underlying DTi. These findings provide new insights into DTi and its underlying neural mechanisms and have implications for the clinical utility of cognitive-motor DTs applied to clinical populations with cognitive decline, such as those with psychiatric and brain disorders.

A causal relationship between particulate matter 2.5 and obesity and its related indicators: a Mendelian randomization study of European ancestry.

Background: In recent years, the prevalence of obesity has continued to increase as a global health concern. Numerous epidemiological studies have confirmed the long-term effects of exposure to ambient air pollutant particulate matter 2.5 (PM2.5) on obesity, but their relationship remains ambiguous. Methods: Utilizing large-scale publicly available genome-wide association studies (GWAS), we conducted univariate and multivariate Mendelian randomization (MR) analyses to assess the causal effect of PM2.5 exposure on obesity and its related indicators. The primary outcome given for both univariate MR (UVMR) and multivariate MR (MVMR) is the estimation utilizing the inverse variance weighted (IVW) method. The weighted median, MR-Egger, and maximum likelihood techniques were employed for UVMR, while the MVMR-Lasso method was applied for MVMR in the supplementary analyses. In addition, we conducted a series of thorough sensitivity studies to determine the accuracy of our MR findings. Results: The UVMR analysis demonstrated a significant association between PM2.5 exposure and an increased risk of obesity, as indicated by the IVW model (odds ratio [OR]: 6.427; 95% confidence interval [CI]: 1.881-21.968; P FDR = 0.005). Additionally, PM2.5 concentrations were positively associated with fat distribution metrics, including visceral adipose tissue (VAT) (OR: 1.861; 95% CI: 1.244-2.776; P FDR = 0.004), particularly pancreatic fat (OR: 3.499; 95% CI: 2.092-5.855; PFDR =1.28E-05), and abdominal subcutaneous adipose tissue (ASAT) volume (OR: 1.773; 95% CI: 1.106-2.841; P FDR = 0.019). Furthermore, PM2.5 exposure correlated positively with markers of glucose and lipid metabolism, specifically triglycerides (TG) (OR: 19.959; 95% CI: 1.269-3.022; P FDR = 0.004) and glycated hemoglobin (HbA1c) (OR: 2.462; 95% CI: 1.34-4.649; P FDR = 0.007). Finally, a significant negative association was observed between PM2.5 concentrations and levels of the novel obesity-related biomarker fibroblast growth factor 21 (FGF-21) (OR: 0.148; 95% CI: 0.025-0.89; P FDR = 0.037). After adjusting for confounding factors, including external smoke exposure, physical activity, educational attainment (EA), participation in sports clubs or gym leisure activities, and Townsend deprivation index at recruitment (TDI), the MVMR analysis revealed that PM2.5 levels maintained significant associations with pancreatic fat, HbA1c, and FGF-21. Conclusion: Our MR study demonstrates conclusively that higher PM2.5 concentrations are associated with an increased risk of obesity-related indicators such as pancreatic fat content, HbA1c, and FGF-21. The potential mechanisms require additional investigation.

A framework for identifying factors controlling cyanobacterium Microcystis flos-aquae blooms by coupled CCM-ECCM Bayesian networks.

Cyanobacterial blooms in freshwater sources are a global concern, and gaining insight into their causes is crucial for effective resource management and control. In this study, we present a novel computational framework for the causal analysis of cyanobacterial harmful algal blooms (cyanoHABs) in Lake Kinneret. Our framework integrates Convergent Cross Mapping (CCM) and Extended CCM (ECCM) causal networks with Bayesian Network (BN) models. The constructed CCM-ECCM causal networks and BN models unveil significant interactions among factors influencing cyanoHAB formation. These interactions have been validated by domain experts and supported by evidence from peer-reviewed publications. Our findings suggest that Microcystis flos-aquae levels are influenced not only by community structure but also by ammonium, phosphate, oxygen, and temperature levels in the weeks preceding bloom occurrences. We demonstrated a non-parametric computational framework for causal analysis of a multivariate ecosystem. Our framework offers a more comprehensive understanding of the underlying mechanisms driving M. flos-aquae blooms in Lake Kinneret. It captures complex interactions and provides an explainable prediction model. By considering causal relationships, temporal dynamics, and joint probabilities of environmental factors, the proposed framework enhances our understanding of cyanoHABs in Lake Kinneret.

Causal relationship between gut microbiota and Behçet's disease: a Mendelian randomization study.

Background: While observational epidemiological studies have suggested an association between gut microbiota and Behçet's disease (BD), the causal relationship between the two remains uncertain. Methods: Statistical data were obtained from gut microbiome Genome-Wide Association Studies (GWAS) published by the MiBioGen consortium, and genetic variation points were screened as instrumental variables (IV). Mendelian randomization (MR) study was performed using inverse variance weighted (IVW), weighted median, MR-Egger regression, simple mode, and weighted mode methods to evaluate the causal relationship between gut microbiota (18,340 individuals) and BD (317,252 individuals). IVW was the main method of analysis. The stability and reliability of the results were verified using the leave-one-out method, heterogeneity test, and horizontal genetic pleiotropy test. Finally, a reverse MR analysis was performed to explore reverse causality. Results: Inverse variance weighted (IVW) results showed that the genus Parasutterella (OR = 0.203, 95%CI 0.055-0.747, p = 0.016), Lachnospiraceae NC2004 group (OR = 0.101, 95%CI 0.015-0.666, p = 0.017), Turicibacter (OR = 0.043, 95%CI 0.007-0.273, p = 0.001), and Erysipelatoclostridium (OR = 0.194, 95%CI 0.040-0.926, p = 0.040) were protective factors against BD, while Intestinibacter (OR = 7.589, 95%CI 1.340-42.978, p = 0.022) might be a risk factor for BD. Conclusion: Our study revealed the causal relationship between gut microbiota and BD. The microbiota that related to BD may become new biomarkers; provide new potential indicators and targets for the prevention and treatment of BD.

Common Relationship Between Causality Orientation and the Prefrontal Region in Psychiatric Disorders as Revealed by Diffusional Kurtosis Imaging.

Background Motivation dysregulation is common in several psychiatric disorders. However, little is known about the relationships between motivation and the regional brain areas involved. We evaluated the relationships between brain microstructural features and causality orientation in patients with schizophrenia, major depressive disorder (MDD), and bipolar disorder (BD) using diffusional kurtosis imaging (DKI) techniques. Methods Forty patients with MDD, 36 with BD, and 30 with schizophrenia underwent DKI and assessment using the General Causality Orientation Scale (GCOS). We analyzed the DKI index and the GCOS subscales. Results The psychiatric patients showed significant positive correlations between the GCOS-autonomy orientation score and the mean kurtosis (MK) values in the prefrontal regions, orbitofrontal regions, and posterior cingulate cortex. When the analyses were performed separately by disease and gender, a positive correlation was found between the GCOS-autonomy orientation score and the MK values in the left prefrontal regions transdiagnostically, especially among female patients with MDD, BD, and schizophrenia. Conclusions A similar association between intrinsic motivation and MK value in the left prefrontal cortex was suggested in patients with schizophrenia, MDD, and BD. The commonality of this association among these disorders might lead to the discovery of a new biomarker for psychiatric clinical research.

Review of machine learning solutions for eating disorders.

BACKGROUND: Eating Disorders (EDs) are one of the most complex psychiatric disorders, with significant impairment of psychological and physical health, and psychosocial functioning, and are associated with low rates of early detection, low recovery and high relapse rates. This underscores the need for better diagnostic and treatment methods. OBJECTIVE: This narrative review explores current Machine Learning (ML) and Artificial Intelligence (AI) applications in the domain of EDs, with a specific emphasis on clinical management in treatment settings. The primary objective are to (i) decrease the knowledge gap between ED researchers and AI-practitioners, by presenting the current state-of-the-art AI applications (including models for causality) in different ED use-cases; (ii) identify limitations of these existing AI interventions and how to address them. RESULTS: AI/ML methods have been applied in different ED use-cases, including ED risk factor identification and incidence prediction (including the analysis of social media content in the general population), diagnosis, monitoring patients and treatment response and prognosis in clinical populations. A comparative analysis of AI-techniques deployed in these use-cases have been performed, considering factors such as complexity, flexibility, functionality, explainability and adaptability to healthcare constraints. CONCLUSION: Multiple restrictions have been identified in the existing methods in ML and Causality in terms of achieving actionable healthcare for ED, like lack of good quality and quantity of data for models to train on, while requiring models to be flexible, high-performing, yet being explainable and producing counterfactual explanations, for ensuring the fairness and trustworthiness of its decisions. We conclude that to overcome these limitations and for future AI research and application in clinical management of ED, (i) careful considerations are required with regards to AI-model selection, and (ii) joint efforts from ED researcher and patient community are essential in building better quality and quantity of dedicated ED datasets and secure AI-solution framework.

The impact of telomere length on the risk of idiopathic normal pressure hydrocephalus: a bidirectional Mendelian randomization study.

Idiopathic normal pressure hydrocephalus (iNPH) affects mainly aged populations. The gradual shortening of telomere length (TL) is one of the hallmarks of aging. Whereas the genetic contribution of TL to the iNPH is incompletely understood. We aimed to investigate the causal relationship between TL and iNPH through the Mendelian randomization (MR) analysis. We respectively obtained 186 qualified single nucleotide polymorphisms (SNPs) of TL and 20 eligible SNPs of iNPH for MR analysis. The result of MR analysis showed that genetically predicted longer TL was significantly associated with a reduced odd of iNPH (odds ratio [OR] = 0.634 95% Confidence interval [CI] 0.447-0.899, p = 0.011). The causal association remained consistent in multivariable MR (OR = 0.530 95% CI 0.327-0.860, p = 0.010). However, there was no evidence that the iNPH was causally associated with the TL (OR = 1.000 95% CI 0.996-1.004, p = 0.955). Our study reveals a potential genetic contribution of TL to the etiology of iNPH, that is a genetically predicted increased TL might be associated with a reduced risk of iNPH.

The causal role of immune cells on lung cancer: a bi-directional Mendelian randomization (MR) study.

Immune cells play a vital role in the development and progression of lung cancer (LC). We aimed to explore the causal role of immune cells in LC with Mendelian randomization (MR) study. Summary statistic data used in the study were obtained from genome-wide association studies (GWAS). A comprehensive two-sample MR was carried out to explore the causal role of 731 immune cell traits (ICTs) in LC, Non-small cell lung cancer (NSCLC), and Small cell lung cancer (SCLC). An inverse-variance weighted (IVW) approach was applied to present the MR estimates. The heterogeneity test was performed using Cochran's Q statistic. MR-Egger intercept test and MR-PRESSO were utilized for the pleiotropy test. MR showed that 15, 31, and 11 ICTs had protective effects on LC, NSCLC, and SCLC, respectively, and 12, 31, and 11 ICTs had adverse effects on LC, NSCLC, and SCLC, respectively. Of note, CD3 on CD28+ CD4+ in the Treg panel could significantly increase the risk of LC, as well as NSCLC and SCLC. Moreover, the MR results revealed that LC was vital in IgD on IgD+ in the B cell panel and NSCLC on CCR2 on CD14- CD16- in the Monocyte panel. Our study revealed multiple close connections between immune cells and LC.

Causal Structure Learning with Conditional and Unique Information Groups-Decomposition Inequalities.

The causal structure of a system imposes constraints on the joint probability distribution of variables that can be generated by the system. Archetypal constraints consist of conditional independencies between variables. However, particularly in the presence of hidden variables, many causal structures are compatible with the same set of independencies inferred from the marginal distributions of observed variables. Additional constraints allow further testing for the compatibility of data with specific causal structures. An existing family of causally informative inequalities compares the information about a set of target variables contained in a collection of variables, with a sum of the information contained in different groups defined as subsets of that collection. While procedures to identify the form of these groups-decomposition inequalities have been previously derived, we substantially enlarge the applicability of the framework. We derive groups-decomposition inequalities subject to weaker independence conditions, with weaker requirements in the configuration of the groups, and additionally allowing for conditioning sets. Furthermore, we show how constraints with higher inferential power may be derived with collections that include hidden variables, and then converted into testable constraints using data processing inequalities. For this purpose, we apply the standard data processing inequality of conditional mutual information and derive an analogous property for a measure of conditional unique information recently introduced to separate redundant, synergistic, and unique contributions to the information that a set of variables has about a target.

Link Prediction in Dynamic Social Networks Combining Entropy, Causality, and a Graph Convolutional Network Model.

Link prediction is recognized as a crucial means to analyze dynamic social networks, revealing the principles of social relationship evolution. However, the complex topology and temporal evolution characteristics of dynamic social networks pose significant research challenges. This study introduces an innovative fusion framework that incorporates entropy, causality, and a GCN model, focusing specifically on link prediction in dynamic social networks. Firstly, the framework preprocesses the raw data, extracting and recording timestamp information between interactions. It then introduces the concept of "Temporal Information Entropy (TIE)", integrating it into the Node2Vec algorithm's random walk to generate initial feature vectors for nodes in the graph. A causality analysis model is subsequently applied for secondary processing of the generated feature vectors. Following this, an equal dataset is constructed by adjusting the ratio of positive and negative samples. Lastly, a dedicated GCN model is used for model training. Through extensive experimentation in multiple real social networks, the framework proposed in this study demonstrated a better performance than other methods in key evaluation indicators such as precision, recall, F1 score, and accuracy. This study provides a fresh perspective for understanding and predicting link dynamics in social networks and has significant practical value.

Pulmonary edema after naloxone administration for opioid reversal: a systematic review of case reports and causality assessment using the Naranjo scale.

INTRODUCTION: Pulmonary edema is a rare complication occurring after naloxone administration, but the causal relationship remains insufficiently investigated. We aimed to determine the likelihood of naloxone as the causative agent in published cases of pulmonary edema. METHODS: A literature search was conducted across multiple databases, utilizing database-specific search terms such as "pulmonary edema/chemically induced" and "naloxone/adverse effects." Each case report was evaluated using the Naranjo scale, a standardized causality assessment algorithm. RESULTS: We identified 49 published case reports of pulmonary edema following naloxone administration. The median total dose of naloxone was 0.2 mg for patients presenting following a surgical procedure and 4 mg for out-of-hospital opioid overdoses. Based on the Naranjo scale, the majority of cases were classified as "possible" (n = 38) or "probable" (n = 11) adverse reactions, while no "definite" cases of naloxone-induced pulmonary edema were identified. Many patients were classified as "possible" due to limited patient information or other potential risks, such as fluid administration or airway obstruction. Forty-six of 49 patients survived (94 percent). DISCUSSION: Pulmonary edema may occur after both low and high doses of naloxone; however, low doses were primarily reported in the surgical population. Despite this complication, the majority of patients survived. Furthermore, no case report in our analysis was classified as a "definite" case of naloxone-induced pulmonary edema which limits the establishment of causality. Future studies should explore patient risk factors, including surgical versus outpatient setting and opioid-naïve versus opioid-tolerant for developing pulmonary edema and employ a causality assessment algorithm. CONCLUSIONS: These case reports suggest pulmonary edema can occur following naloxone administration, irrespective of dose. According to the Naranjo scale, there were no definite cases of naloxone-induced pulmonary edema. Overall, we suggest the benefits of naloxone administration outweigh the risks. Naloxone should be administered to treat opioid overdoses while monitoring for the development of pulmonary edema.

Therapeutic potential of single-nucleotide polymorphism-mediated IL6R inhibitors in ankylosing spondylitis treatment.

Objective: Interleukin-6 (IL-6) is a multiple-effect cell factor implicated in the etiopathogenesis of several rheumatologic disorders. The blockade of the IL-6 pathway via IL6R inhibitors effectively treats these disorders. However, the clinical significance of the IL6R blockade for ankylosing spondylitis (AS) therapy remains controversial. With advances in genomics, increasing evidence has revealed the role of heritability in the etiology of disease, and Mendelian randomization (MR) analyses are being used more broadly to infer causation. Therefore, this MR study aims to evaluate the potential therapeutic utility of IL6R-targeted approaches in AS. Methods: The C-reactive protein (CRP) level was used as an exposure factor, and rheumatoid arthritis (RA) was used as a positive control. As-related genome-wide association study (GWAS) data were used as the primary outcome of drug-targeted MR analyses to test the relation between IL6R blockers and AS. Inverse variance weighting (IVW) is the primary analytical approach. Various sensitivity tests were performed to check the robustness and trustworthiness of the causality estimation, including consistency, heterogeneity, and pleiotropy analyses. In addition, repeated analysis was conducted using different GWAS data related to exposures and outcomes to examine the results for stability. Results: According to the IVW results, IL6R inhibitors significantly reduced the risk of AS in ukb-b-18194 (OR: 0.995, 95% CI 0.993-0.996, P = 5.12 × 10-08) and ukb-a-88 (OR: 0.994, 95% CI 0.993-0.996, P = 6.25 × 10-15). Moreover, repeated analyses were performed using different exposure-related GWAS data, yielding similar results, ukb-b-18194 (OR: 0.995, 95% CI 0.993-0.997, P = 1.25 × 10-06) and ukb-a-88 (OR: 0.995, 95% CI 0.994-0.997, P = 7.81 × 10-09). Heterogeneity analyses and pleiotropy analyses indicated no significant heterogeneity or pleiotropy. Conclusion: This MR analysis result further validates that the IL-6 pathway may contribute to the pathogenesis of AS and that the inhibition of IL6R reduces the risk of AS. These findings may guide future studies and provide more favorable drug treatment options for people at high risk of AS.

Circulating metabolites and coronary heart disease: a bidirectional Mendelian randomization.

Background: Numerous studies have established a link between coronary heart disease and metabolic disorders. Yet, causal evidence connecting metabolites and Coronary Heart Disease (CHD) remains scarce. To address this, we performed a bidirectional Mendelian Randomization (MR) analysis investigating the causal relationship between blood metabolites and CHD. Methods: Data were extracted from published genome-wide association studies (GWASs) on metabolite levels, focusing on 1,400 metabolite summary data as exposure measures. Primary analyses utilized the GWAS catalog database GCST90199698 (60,801 cases and 123,504 controls) and the FinnGen cohort (43,518 cases and 333,759 controls). The primary method used for causality analysis was random inverse variance weighting (IVW). Supplementary analyses included MR-Egger, weighted mode, and weighted median methods. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. Reverse MR analysis was employed to evaluate the direct impact of metabolites on coronary heart disease. Additionally, replication and meta-analysis were performed. We further conducted the Steiger test and colocalization analysis to reflect the causality deeply. Results: This study identified eight metabolites associated with lipids, amino acids and metabolite ratios that may influence CHD risk. Findings include: 1-oleoyl-2-arachidonoyl-GPE (18:1/20:4) levels: OR = 1.08; 95% CI 1.04-1.12; P = 8.21E-06; 1-palmitoyl-2-arachidonoyl-GPE (16:0/20:4) levels: OR = 1.07; 95% CI 1.04-1.11; P = 9.01E-05; Linoleoyl-arachidonoyl-glycerol (18:2/20:4): OR = 1.08; 95% CI 1.04-1.22; P = 0.0001; Glycocholenate sulfate: OR = 0.93; 95% CI 0.90-0.97; P = 0.0002; 1-stearoyl-2-arachidonoyl-GPE (OR = 1.07; 95% CI 1.03-1.11; P = 0.0002); N-acetylasparagine (OR = 1.04; 95% CI 1.02-1.07; P = 0.0030); Octadecenedioate (C18:1-DC) (OR = 0.93; 95% CI 0.90-0.97; P = 0.0004); Phosphate to linoleoyl-arachidonoyl-glycerol (18:2-20:4) (1) ratio (OR = 0.92; 95% CI 0.88-0.97; P = 0.0005). Conclusion: The integration of genomics and metabolomics offers novel insights into the pathogenesis of CHD and holds significant importance for the screening and prevention of CHD.

Clinical Profile of Patients with Lichenoid Drug Eruption: A Observational Study.

Background: Lichenoid drug eruption (LDE) is an uncommon cutaneous adverse drug reaction, where a variety of drugs used in day-to-day clinical practice have been implicated. Objective: To describe the clinico-demographic characteristics of patients with LDE and to identify the most likely drugs involved. Methods: In this prospective, observational study, consecutive patients with LDE presenting to the dermatology department of a tertiary teaching hospital were included. The clinico-demographic profile of patients with LDE and implicated drugs was noted. Treatment of drug reaction along with outcome was also documented. Naranjo adverse drug reaction probability scale was used for causality assessment of the drug reactions. A thorough literature review on LDE was also undertaken due to the paucity of existing literature. Results: A total of 15 patients (11 males and 4 females) with LDE were evaluated. Their age ranged from 37 to 61 years, with a mean of 51.53 ± 7.59 years. Anti-hypertensive medications (40%) were the most common culprit agent, followed by antitubercular drugs (33.4%), anti-diabetic agents (13.3%), and others (13.3%). The latent period (time from drug initiation to the appearance of a cutaneous eruption) varied from 15 days to 6 months (mean 2.2 months). Cutaneous involvement was generalized in 73.4% and photo-distributed lesions in 26.6%. Drug provocation test was done to identify the culprit drug. According to the Naranjo adverse drug reaction probability scale, one-third of LDEs were "definite," whereas two-thirds were designated as "probable." Conclusion: LDE is more common in the elderly population. The latent period is comparatively longer in LDE than in other common drug reactions. Prompt recognition and withdrawal of suspected drug are essential to minimize disease morbidity.

Osteoporosis and coronary heart disease: a bi-directional Mendelian randomization study.

Background: Osteoporosis (OP) and cardiovascular disease (CVD) are major global public health issues, especially exacerbated by the challenges of an aging population. As these problems intensify, the associated burden on global health is expected to increase significantly. Despite extensive epidemiological investigations into the potential association between OP and CVD, establishing a clear causal relationship remains elusive. Methods: Instrumental variables were selected from summary statistics of the IEU GWAS database. Five different components of BMD (heel BMD, LS BMD, FA BMD, FN BMD, and TB BMD) were used as OP phenotypes. CHD, MI, and stroke were selected to represent CVD. Multiple analysis methods were used to evaluate the causal relationship between CVD and OP comprehensively. In addition, sensitivity analyses(Cochran's Q test, MR-Egger intercept test, and "leave one out" analysis) were performed to verify the reliability of the results. Results: The MR showed a significant causal relationship between CHD on heel BMD and TB BMD; in the reverse analysis, there was no evidence that OP has a significant causal effect on CVD. The reliability of the results was confirmed through sensitivity analysis. Conclusion: The study results revealed that CHD was causally associated with Heel BMD and TB BMD, while in the reverse MR analysis, the causal relationship between OP and CVD was not supported. This result posits CHD as a potential etiological factor for OP and prompts that routine bone density assessment at traditional sites (forearm, femoral neck, lumbar spine) using DAX may inadequately discern underlying osteoporosis issues in CHD patients. The recommendation is to synergistically incorporate heel ultrasound or DAX for total body bone density examinations, ensuring clinical diagnostics are both precise and reliable. Moreover, these findings provide valuable insights for public health, contributing to the development of pertinent prevention and treatment strategies.

Diastolic and systolic blood pressure and gout: a Mendelian randomization study.

Background: Although there is solid epidemiological evidence supporting the connection between hypertension and gout, little has been said about the relationship between diastolic and systolic blood pressure and gout, the causal relationship and direction associated are uncertain, so we aim to research the causal relationship between diastolic and systolic blood pressure and gout. Methods: We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal effect between 2 blood pressure phenotypes (including diastolic blood pressure and systolic blood pressure) and 5 gout phenotypes (including gout, drug-induced gout, idiopathic gout, unspecified gout, and strictly defined gout) using genome-wide association study statistics. The inverse variance weighting method was used to generate the main results, while sensitivity analyses using MR-Egger, weighted median, Cochran's Q test, Egger intercept test, and leave-one-out analysis, were performed to assess the stability and reliability of the results. Results: After the screening, we found a causal relationship between diastolic blood pressure and gout, idiopathic gout, unspecified gout, and strictly defined gout, and a causal relationship between systolic blood pressure and gout, idiopathic gout, unspecified gout, and strictly defined gout. Conclusion: From a genetic predisposition, controlling blood pressure may reduce the risk of gout.

A Mendelian randomization study on the causal effects of cigarette smoking on liver fibrosis and cirrhosis.

Background: Liver fibrosis significantly impacts public health globally. Untreated liver fibrosis eventually results in cirrhosis. Cigarette smoking is the main etiologic factor for various diseases. However, the causal effects of cigarette smoking on liver fibrosis and cirrhosis have yet to be fully elucidated. Methods: In this study, Mendelian randomization (MR) analysis was performed to assess the association between cigarette smoking, liver fibrosis, and cirrhosis. Single-nucleotide polymorphisms (SNPs) were selected as instrumental variables from a genome-wide association study (GWAS) of European ancestry. Patients were divided into six exposure categories as follows: "ever smoked," "pack years of smoking," "age of smoking initiation," "smoking status: never," "smoking status: current," and "smoking status: previous." The outcomes of this study included liver fibrosis and cirrhosis. MR-Egger, weighted median, inverse variance weighted, simple mode, and weighted mode were selected as the analysis methods. Cochran's Q and the MR-PRESSO tests were conducted to measure heterogeneity. The MR-Egger method was performed to evaluate horizontal pleiotropy, while the "leave-one-out" analysis was performed for sensitivity testing. Results: The results of this study showed that having a smoking history increases the risk of liver fibrosis and cirrhosis ["ever smoked": odds ratio (OR) = 5.704, 95% CI: 1.166-27.910, p = 0.032; "smoking status: previous": OR = 99.783, 95% CI: 2.969-3.353e+03, p = 0.010]. A negative correlation was observed between patients who never smoked and liver fibrosis and cirrhosis ("smoking status: never": OR = 0.171, 95% CI: 0.041-0.719, p = 0.016). However, there were no significant associations between "smoking status: current," "pack years of smoking," and "age of smoking initiation" and liver fibrosis and cirrhosis. Cigarette smoking did not have a significant horizontal pleiotropic effect on liver fibrosis and cirrhosis. The "Leave-one-out" sensitivity analysis indicated that the results were stable. Conclusion: The study confirmed the causal effects of cigarette smoking on liver fibrosis and cirrhosis.

An exploration of meteorological effects on PM2.5 air quality in several provinces and cities in Vietnam.

Linking meteorology and air pollutants is a key challenge. The study investigated meteorological effects on PM2.5 concentration using the advanced convergent cross mapping method, utilizing hourly PM2.5 concentration and six meteorological factors across eight provinces and cities in Vietnam. Results demonstrated that temperature (ρ = 0.30) and radiation (ρ = 0.30) produced the highest effects, followed by humidity (ρ = 0.28) and wind speed (ρ = 0.24), while pressure (ρ = 0.22) and wind direction (ρ = 0.17) produced the weakest effects on PM2.5 concentration. Comparing the ρ values showed that temperature, wind speed, and wind direction had greater impacts on PM2.5 concentration during the dry season whereas radiation had a more influence during the wet season; Southern stations experienced larger meteorological effects. Temperature, humidity, pressure, and wind direction had both positive and negative influences on PM2.5 concentration, while radiation and wind speed mostly had negative influences. During PM2.5 pollution episodes, there was more contribution of meteorological effects on PM2.5 concentration indicated by ρ values. At contaminated levels, humidity (ρ = 0.45) was the most dominant factor affecting PM2.5 concentration, followed by temperature (ρ = 0.41) and radiation (ρ = 0.40). Pollution episodes were pointed out to be more prevalent under higher humidity, higher pressure, lower temperature, lower radiation, and lower wind speed. The ρ calculation also revealed that lower temperature, lower radiation, and higher humidity greatly accelerated each other under pollution episodes, further enhancing PM2.5 concentration. The findings contributed to the literature on meteorology and air pollution interaction.