Risk Curves Research Articles

Construction of an immune-related gene signature for overall survival prediction and immune infiltration in gastric cancer.

Treatment options for patients with gastric cancer (GC) continue to improve, but the overall prognosis is poor. The use of PD-1 inhibitors has also brought benefits to patients with advanced GC and has gradually become the new standard treatment option at present, and there is an urgent need to identify valuable biomarkers to classify patients with different characteristics into subgroups. To determined the effects of differentially expressed immune-related genes (DEIRGs) on the development, prognosis, tumor microenvironment (TME), and treatment response among GC patients with the expectation of providing new biomarkers for personalized treatment of GC populations. Gene expression data and clinical pathologic information were downloaded from The Cancer Genome Atlas (TCGA), and immune-related genes (IRGs) were searched from ImmPort. DEIRGs were extracted from the intersection of the differentially-expressed genes (DEGs) and IRGs lists. The enrichment pathways of key genes were obtained by analyzing the Kyoto Encyclopedia of Genes and Genomes (KEGGs) and Gene Ontology (GO) databases. To identify genes associated with prognosis, a tumor risk score model based on DEIRGs was constructed using Least Absolute Shrinkage and Selection Operator and multivariate Cox regression. The tumor risk score was divided into high- and low-risk groups. The entire cohort was randomly divided into a 2:1 training cohort and a test cohort for internal validation to assess the feasibility of the risk model. The infiltration of immune cells was obtained using 'CIBERSORT,' and the infiltration of immune subgroups in high- and low-risk groups was analyzed. The GC immune score data were obtained and the difference in immune scores between the two groups was analyzed. We collected 412 GC and 36 adjacent tissue samples, and identified 3627 DEGs and 1311 IRGs. A total of 482 DEIRGs were obtained. GO analysis showed that DEIRGs were mainly distributed in immunoglobulin complexes, receptor ligand activity, and signaling receptor activators. KEGG pathway analysis showed that the top three DEIRGs enrichment types were cytokine-cytokine receptors, neuroactive ligand receptor interactions, and viral protein interactions. We ultimately obtained an immune-related signature based on 10 genes, including 9 risk genes (LCN1, LEAP2, TMSB15A mRNA, DEFB126, PI15, IGHD3-16, IGLV3-22, CGB5, and GLP2R) and 1 protective gene (LGR6). Kaplan-Meier survival analysis, receiver operating characteristic curve analysis, and risk curves confirmed that the risk model had good predictive ability. Multivariate COX analysis showed that age, stage, and risk score were independent prognostic factors for patients with GC. Meanwhile, patients in the low-risk group had higher tumor mutation burden and immunophenotype, which can be used to predict the immune checkpoint inhibitor response. Both cytotoxic T lymphocyte antigen4+ and programmed death 1+ patients with lower risk scores were more sensitive to immunotherapy. In this study a new prognostic model consisting of 10 DEIRGs was constructed based on the TME. By providing risk factor analysis and prognostic information, our risk model can provide new directions for immunotherapy in GC patients.

Rib and sternum fracture risks for restrained occupants in frontal car crashes

Objective Most car occupant fatalities occur in frontal crashes and the thorax is the most frequently injured body region. The objectives of the study were, firstly, to quantify the relation between risk factors (such as speed and occupant age) and rib and sternum fracture injury probability in frontal car crashes, and, secondly, to evaluate whether rib fracture occurrence can predict sternum fractures. Methods Weighted German data from 1999-2021 were used to create the injury risk curves to predict both, at least moderate and at least serious, rib and sternum fracture risks. A contingency table for rib and sternum fractures allowed the calculation of sensitivity, specificity, and precision, as well as testing for the association. Results Elderly occupants (≥65 years old) had increased rib and sternum fracture risk compared to mid aged occupants (18-64 years old). Besides occupant age, delta-V was always and sex sometimes a significant predictor for skeletal thoracic injury. Sternum fractures were more common than rib fractures and more likely to occur at any given delta-V. Sternum fractures occurred often in isolation. Female occupants were at higher risk than males to sustain at least moderate rib and sternum fractures together and sternum fractures in isolation. Rib and sternum fractures were associated, but low sensitivity and precision show that rib fractures do not predict sternum fractures well. Conclusions Elderly and female occupants were at the highest risk and should be targeted by thoracic injury criteria and thresholds for frontal crash occupant protection. Rib and sternum fractures were not associated. Therefore, sternum fractures need to be predicted and evaluated separately from rib fractures.

Risk of fracture in patients with myasthenia gravis: a nationwide cohort study in Korea.

Myasthenia gravis (MG) is an autoimmune disorder that affects the neuromuscular junctions, resulting in muscle weakness and fatigue. Muscle weakness, restricted mobility, and frequent use of corticosteroids in patients with MG may predispose them to a higher risk of fractures. However, studies on the impact of MG on bone health and the associated fracture risk are scarce. Utilizing claim database of the Korean National Health Insurance Service collected between 2002 and 2020, we compared the risk of major osteoporotic fracture between 23 118 patients with MG and 115 590 individuals as an age- and sex-matched control group using multivariable Cox proportional hazard models. Over a median follow-up duration of 5.58years, the MG group (mean age 53.7years; 55% women) had higher risk of major osteoporotic fracture compared with controls (incidence rate 13.59 versus 9.74 per 10 000 person-years), which remained independent of age, sex, comorbidities, drug use including anti-osteoporotic agents, and previous fracture history (adjusted hazard ratio [aHR] 1.19, P < 0.001; subdistributed HR 1.14, P < 0.001 adjusted for mortality as competing risk). Subgroup analyses showed a greater association between MG and major osteoporotic fracture risk in younger (age 50 or younger) than older individuals (aHR 1.34 vs. 1.17) and in men compared with women (aHR 1.32 vs. 1.15; P for interaction < 0.05 for all). An imminent divergence of the fracture risk curve between MG and controls was observed for vertebral fracture, while there was time delay for non-vertebral sites, showing site-specific association. Factors associated with higher fracture risk in patients with MG were older age, female gender, high dose glucocorticoid use (>7.5mg/day), immunosuppressant use, and previous history of fracture. In summary, patients with MG had higher risk of major osteoporotic fracture compared with controls, which calls further preventive actions in this patient group.

The association between alcohol consumption and all-cause mortality: An umbrella review of systematic reviews using lifetime abstainers or low-volume drinkers as a reference group.

Systematic reviews of the relationship between alcohol consumption and all-cause mortality have reported different relative risk (RR) curves, possibly due to the choice of reference group. Results have varied from 'J-shaped' curves, where low-volume consumption is associated with reduced risk, to monotonically increased risk with increasing consumption. We summarised the evidence on alcohol consumption and all-cause mortality exclusively from systematic reviews using lifetime abstainers or low-volume/occasional drinkers as the reference group. We conducted a systematic umbrella review of systematic reviews of the relationship between alcohol consumption and all-cause mortality in prospective cohort studies using a reference group of lifetime abstainers or low-volume/occasional drinkers. Several databases (PubMed/Medline/Embase/PsycINFO/Cochrane Library) were searched to March 2022. Reviews were assessed for risk of bias, and those with reference groups containing former drinkers were excluded. From 2149 articles retrieved, 25 systematic reviews were identified, and five did not include former drinkers in the reference group. Four of the five included reviews had high risk of bias. Three reviews reported a J-shaped relationship between alcohol consumption and all-cause mortality with significant decreased risk for low-volume drinking (RR range 0.84 to 0.95), while two reviews did not. The one review at low risk of bias reported monotonically increased risk with greater consumption (RRs = 1.02, 1.13, 1.33 and 1.52 for low-, medium-, high- and higher-volume drinking, respectively, compared with occasional drinking). All five reviews reported significantly increased risk with higher levels of alcohol consumption (RR range 1.28 to 3.70). Sub-group analyses were reported by sex and age; however, there were evidence gaps for many important factors. Conversely, 17 of 20 excluded systematic reviews reported decreased mortality risk for low-volume drinking. Over 70% of systematic reviews and meta-analyses published to March 2022 of all-cause mortality risk associated with alcohol consumption did not exclude former drinkers from the reference group and may therefore be biased by the 'sick-quitter effect'.

Association of echocardiography-related parameters with the prognosis of decompensated cirrhosis: a retrospective cohort study

Background Cardiac morphology and function, which are conventionally evaluated by echocardiography, are often abnormal in decompensated cirrhosis. We aimed to evaluate the association of echocardiography-related parameters with prognosis in cirrhosis. Methods This retrospective study included 104 decompensated cirrhotic patients, in whom cardiac structure and function were measured by echocardiography, including mitral inflow early diastolic velocity/mitral inflow late diastolic velocity (E/A), left atrium diameter, left ventricular end-diastolic dimension, interventricular septal thickness, left ventricular posterior wall thickness, right atrial transverse diameter, right atrial longitudinal diameter, right ventricular dimension (RVD), stroke volume, cardiac output, left ventricular ejection fraction, and fractional shortening. Cox regression and competing risk analyses and Kaplan-Meier and Nelson-Aalen cumulative risk curves were used to evaluate their associations with further decompensation and death in cirrhotic patients, if appropriate. Results Lower RVD was a predictor of further decompensation in Cox regression (adjusted by Child-Pugh score: p = 0.138; adjusted by MELD score: p = 0.034) and competing risk analyses (p = 0.003), and RVD ≤17 mm was significantly associated with higher cumulative incidence of further decompensation in Kaplan-Meier (p = 0.002) and Nelson-Aalen cumulative risk curves (p = 0.002). E/A ≤ 0.8 was a significant predictor of death in Cox regression (adjusted by Child-Pugh score: p = 0.041; adjusted by MELD score: p = 0.045) and competing risk analyses (p = 0.024), and E/A ≤ 0.8 was significantly associated with higher cumulative incidence of death in Kaplan-Meier (p = 0.023) and Nelson-Aalen cumulative risk curves (p = 0.024). Other echocardiography-related parameters were not significantly associated with further decompensation or death. Conclusion RVD and E/A may be considered for the prognostic assessment of decompensated cirrhosis.

Interaction effects of MTHFR C677T and A1298C polymorphisms with maternal glycated haemoglobin levels on adverse birth outcomes.

The role of maternal genetic factors in the association between high glycated haemoglobin (HbA1c) levels and adverse birth outcomes remains unclear. In this study, the maternal HbA1c levels of 5108 normoglycemic pregnant women in China were measured, and A1298C and C677T polymorphisms in the methylenetetrahydrofolate reductase (MTHFR) gene were genotyped. Elevated HbA1c levels during the second trimester were associated with increased risks of macrosomia, large-for-gestational age (LGA), preterm birth (PTB), and reduced gestational age (p<0.05). Pregnant women with MTHFR A1298C AA or C677T CT+TT genotypes were susceptible to adverse pregnancy outcomes related to HbA1c levels. Among pregnant women with the A1298C AA genotype, each standard deviation (SD) increase in HbA1c levels increased the risk of PTB by 1.32-times and reduced the gestational age by 0.11weeks (p<0.05). For MTHFR C677T CC+TT genotype carriers, higher HbA1c levels were associated with 1.49-, 1.24-, and 1.23-times increased risks of macrosomia, LGA, and PTB, respectively (p<0.05). A U-shaped curve for PTB risk in relation to HbA1c levels was observed among the C677T CC+TT participants, with a cut-off value of 4.58%. Among subjects with the A1298C AA genotype combined with the C677T CT+TT genotype, each SD increase in HbA1c levels was associated with 1.40 and 1.37-times increased risks of LGA and PTB, respectively. Our findings highlight the importance of glycaemic control during pregnancy and the potential impact of genetic factors on birth outcomes. However, further large-scale studies are required to confirm these findings.

Deep learning-based prediction of major arrhythmic events in dilated cardiomyopathy: A proof of concept study.

Prediction of major arrhythmic events (MAEs) in dilated cardiomyopathy represents an unmet clinical goal. Computational models and artificial intelligence (AI) are new technological tools that could offer a significant improvement in our ability to predict MAEs. In this proof-of-concept study, we propose a deep learning (DL)-based model, which we termed Deep ARrhythmic Prevention in dilated cardiomyopathy (DARP-D), built using multidimensional cardiac magnetic resonance data (cine videos and hypervideos and LGE images and hyperimages) and clinical covariates, aimed at predicting and tracking an individual patient's risk curve of MAEs (including sudden cardiac death, cardiac arrest due to ventricular fibrillation, sustained ventricular tachycardia lasting ≥30 s or causing haemodynamic collapse in <30 s, appropriate implantable cardiac defibrillator intervention) over time. The model was trained and validated in 70% of a sample of 154 patients with dilated cardiomyopathy and tested in the remaining 30%. DARP-D achieved a 95% CI in Harrell's C concordance indices of 0.12-0.68 on the test set. We demonstrate that our DL approach is feasible and represents a novelty in the field of arrhythmic risk prediction in dilated cardiomyopathy, able to analyze cardiac motion, tissue characteristics, and baseline covariates to predict an individual patient's risk curve of major arrhythmic events. However, the low number of patients, MAEs and epoch of training make the model a promising prototype but not ready for clinical usage. Further research is needed to improve, stabilize and validate the performance of the DARP-D to convert it from an AI experiment to a daily used tool.

Numerical analysis of injuries of e-scooter riders in frontal impacts against SUVs

The rising popularity of e-scooters in urban areas highlights the importance of understanding potential collision dynamics and consequences to enhance rider safety, especially since 80% of fatalities for these vulnerable road users result from incidents involving motor vehicles. This study aims to identify potential injury mechanisms of e-scooter riders involved in frontal impacts against Sports Utility Vehicles (SUVs) using Finite Element Analysis (FEA) and a Human Body Model (HBM). Six impact scenarios at 25 km/h were simulated: on the passenger's side door (1-SD), on the trunk door (2-TD), on the bonnet (3-FB), on the bonnet from the side (4-SB), on the windshield from the side (5-SW), and finally, on the bonnet with an offset (6-FO). A wide range of Injury Risk Criteria (IRCs) was analyzed, including A3MS, HIC15, BrIC, DAMAGE, Cmax and PC Score, and head contact forces were output. Injury Risk Curves were then used to calculate the probability and severity of the sustained injuries predicted by the mentioned IRCs. Overall, the results corresponding to the most injurious scenarios suggested serious (30% to 40% overall probability) and critical (45% probability for the 4-SB scenario) brain, moderate head (30% probability for scenarios 1-SD and 2-TD), and serious thoracic (26% to 78% overall probability) injuries. Additionally, in two scenarios (1-SD and 2-TD), the e-scooter rider's mandible impacted against the vehicle's roof side rail and rear spoiler, involving potential anterior-posterior serious mandible fractures. The conclusions reached in this study help to understand potential injury sources and provide valuable information for the design of specific safety systems or the creation or improvement of e-scooter legislation.

The systematic identification of survival-related alternative splicing events and splicing factors in glioblastoma.

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor, making it one of the most life-threatening human cancers. Nevertheless, research on the mechanism of action between alternative splicing (AS) and splicing factor (SF) or biomarkers in GBM is limited. AS is a crucial post-transcriptional regulatory mechanism. More than 95% of human genes undergo AS events. AS can diversify the expression patterns of genes, thereby increasing the diversity of proteins and playing a significant role in the occurrence and development of tumors. In this study, we downloaded 599 clinical data and 169 transcriptome analysis data from The Cancer Genome Atlas (TCGA) database. Besides, we collected AS data about GBM from TCGA-SpliceSeq. The overall survival (OS) related AS events in GBM were determined through least absolute shrinkage and selection operator (Lasso) and Cox analysis. Subsequently, the association of these 1825 OS-related AS events with patient survival was validated using the Kaplan-Meier survival analysis, receiver operating characteristic curve, risk curve analysis, and independent prognostic analysis. Finally, we depicted the AS-SF regulatory network, illustrating the interactions between splicing factors and various AS events in GBM. Additionally, we identified three splicing factors (RNU4-1, SEC31B, and CLK1) associated with patient survival. In conclusion, based on AS occurrences, we developed a predictive risk model and constructed an interaction network between GBM-related AS events and SFs, aiming to shed light on the underlying mechanisms of GBM pathogenesis and progression.

Classification of bladder cancer based on immune cell infiltration and construction of a risk prediction model for prognosis.

To classify bladder cancer based on immune cell infiltration score and to construct a prognosis assessment model of patients with bladder cancer. The transcriptome data and clinical data of breast cancer patients were obtained from the The Cancer Genome Atlas (TCGA) database. Single sample gene set enrichment analysis was used to calculate the infiltration scores of 16 immune cells. The classification of breast cancer patients was achieved by unsupervised clustering, and the sensitivity of patients with different types to immunotherapy and chemotherapy was analyzed. The key modules significantly related to the infiltration of key immune cells were identified by weighted correlation network analysis (WGCNA), and the key genes in the modules were identified. A risk scoring model and a nomogram for prognosis assessment of bladder cancer patients were constructed and verified. B cells, mast cells, neutrophils, T helper cells and tumor infiltrating lymphocytes were determined to be the key immune cells of bladder cancer. The patients were clustered into two groups (Cluster 1 ´ and Custer 2) based on immune cell infiltration scores. Compared with patients with Cluster 1 ´, patients with Cluster 2 were more likely to benefit from immunotherapy (P<0.05), and patients with Cluster 2 were more sensitive to Enbeaten, Docetaxel, Cyclopamine, and Akadixin (P<0.05). 35 genes related to key immune cells were screened out by WGCNA and 4 genes (GPR171, HOXB3, HOXB5 and HOXB6) related to the prognosis of bladder cancer were further screened by LASSO Cox regression. The areas under the ROC curve (AUC) of the bladder cancer prognosis risk scoring model based on these 4 genes to predict the 1-, 3- and 5-year survival of patients were 0.735, 0.765 and 0.799, respectively. The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1-, 3-, and 5-year overall survival of bladder cancer patients. According to the immune cell infiltration score, bladder cancer patients can be classified. Furthermore, bladder cancer prognosis risk scoring model and nomogram based on key immune cell-related genes have high accuracy in predicting the prognosis of bladder cancer patients.

Lower Extremity Injury Risk Curve Development for a Human Body Model in the Underbody Blast Environment.

Computational human body models (HBMs) provide the ability to explore numerous candidate injury metrics ranging from local strain based criteria to global combined criteria such as the Tibia Index. Despite these efforts, there have been relatively few studies that focus on determining predicted injury risk from HBMs based on observed postmortem human subjects (PMHS) injury data. Additionally, HBMs provide an opportunity to construct risk curves using measures that are difficult or impossible to obtain experimentally. The Global Human Body Models Consortium (GHBMC) M50-O v 6.0 lower extremity was simulated in 181 different loading conditions based on previous PMHS tests in the underbody blast (UBB) environment and 43 different biomechanical metrics were output. The Brier Metric Score were used to determine the most appropriate metric for injury risk curve development. Using survival analysis, three different injury risk curves (IRC) were developed: "any injury," "calcaneus injury," and "tibia injury." For each injury risk curve, the top three metrics selected using the Brier Metric Score were tested for significant covariates including boot use and posture. The best performing metric for the "any injury," "calcaneus injury" and "tibia injury" cases were calcaneus strain, calcaneus force, and lower tibia force, respectively. For the six different injury risk curves where covariates were considered, the presence of the boot was found to be a significant covariate reducing injury risk in five out of six cases. Posture was significant for only one curve. The injury risk curves developed from this study can serve as a baseline for model injury prediction, personal protective equipment (PPE) evaluation, and can aid in larger scale testing and experimental protocols.

Impact Location Dependence of Behind Armor Blunt Trauma Injury Assessed Using a Human Body Finite Element Model.

Behind armor blunt trauma (BABT), resulting from dynamic deformation of protective ballistic armor into the thorax, is currently assessed assuming a constant threshold of maximum backface deformation (BFDs) (44 mm). Although assessed for multiple impacts on the same armor, testing is focused on armor performance (shot-to-edge and shot-to-shot) without consideration of the underlying location on the thorax. Previous studies identified the importance of impacts on organs of animal surrogates wearing soft armor. However, the effect of impact location was not quantified outside the threshold of 44 mm. In the present study, a validated biofidelic advanced human thorax model (50th percentile male) was utilized to assess the BABT outcome from varying impact location. The thorax model was dynamically loaded using a method developed for recreating BABT impacts, and BABT events within the range of real-world impact severities and locations were simulated. It was found that thorax injury depended on impact location for the same BFDs. Generally, impacts over high compliance locations (anterolateral rib cage) yielded increased thoracic compression and loading on the lungs leading to pulmonary lung contusion (PLC). Impacts at low compliance locations (top of sternum) yielded hard tissue fractures. Injuries to the sternum, ribs, and lungs were predicted at BFDs lower than 44 mm for low compliance locations. Location-based injury risk curves demonstrated greater accuracy in injury prediction. This study quantifies the importance of impact location on BABT injury severity and demonstrates the need for consideration of location in future armor design and assessment.

The hidden curves of risk: a nonlinear model of cumulative risk and school bullying victimization among adolescents with autism spectrum disorder

BackgroundSchool bullying victimization (SBV) occurs more frequently in students with autism spectrum disorder (ASD) in general education than in special classes, and there is a cumulative risk effect on SBV exposure among young people with ASD reported by their parents and teachers. However, SBV is a personal experience, the predictive patterns of cumulative risk on SBV reported by themselves and its psychological mechanism remain unclear. This study aims to explore the relationship between cumulative risk and SBV based on self-report, and to test whether internalizing problems mediates this relationship among adolescents with ASD placed in regular classes.MethodsThis study used data from the Taiwan Special Needs Education Longitudinal Study (SNELS) in 2011. The analysis included 508 adolescents with ASD who were in regular classes across Taiwan. The primary variables under study were the quality of friendship interactions, teacher-student relationship, school connection, perceived stigma, the impact caused by the disabilities, internalizing problem, and whether the participants had experienced SBV over the past semester, while control variables were adaptability and social-emotional skills. Established risk factors were summed to form a cumulative risk score.ResultsThe cumulative risk was positively associated with SBV. The relationship was characterized by the nonlinear pattern of the quadratic function (negative acceleration model) between cumulative risk and SBV. Internalizing problem played a partial mediating role in the effect of cumulative risk on SBV.ConclusionsIntervention measures to reduce SBV should include the strategies to reduce the number of risks to which adolescents with ASD in regular classes are exposed, comprehensive prevention targeting each risk factor is needed specially when the number of risks is one or two, and more attention needs to be given to their internalizing problem in various ways.

Navigating the challenges of minimally invasive mitral valve surgery: a risk analysis and learning curve evaluation

BackgroundThis study aimed to report the risk and learning curve analysis of a minimally invasive mitral valve surgery program performed through a right mini-thoracotomy at a single institution.MethodsFrom January 2013 through December 2019, 266 consecutive patients underwent minimally invasive mitral valve surgery in our department and were included in the current study. Multiple logistic regression analysis was used for the adverse event outcome. Distribution over time of perioperative complications, defined as clinical endpoints in the Valve Academic Research Consortium-2 (VARC-2) consensus document, as well as CUSUM charts for assessment of cardiopulmonary bypass and aortic cross-clamping duration over time, has been performed for learning curve assessment.ResultsOverall incidences of postoperative stroke (1.1%), myocardial infarction (1.1%), and thirty-day mortality (1.5%) were low. The mitral valve reconstruction rate in our series was 95%. Multivariable analysis revealed that concomitant tricuspid valve surgery (OR 4.44; 95%CI 1.61–11.80; p = 0.003) was significantly associated with adverse event outcomes. Despite a trend towards adverse event outcomes in patients with preexisting active mitral valve endocarditis (OR 2.69; 95%CI 0.81–7.87; p = 0.082), mitral valve pathology did not significantly impact postoperative morbidity and mortality. Distribution over time of perioperative complications, defined as clinical endpoints in the VARC-2 consensus document, showed a trend towards an improved complication rate after the initial 65–100 procedures.ConclusionsMitral valve surgery via right-sided mini-thoracotomy can be implemented safely with low perioperative morbidity and mortality rates. Careful patient selection regarding isolated mitral valve surgery in the presence of degenerative mitral valve disease may represent a significant safety issue during the learning curve.Trial Registration: The cantonal ethics commission of Zurich approved the study (registration ID 2020-00752, date of approval 24 April 2020).

Probabilistic seismic collapse risk assessment of non-engineered masonry buildings in Malawi

This study presents the most recent development of a nationwide earthquake risk model for non-engineered masonry buildings in Malawi. Due to its location within the East African Rift, Malawi experienced several moderate earthquakes that caused seismic damage and loss. Recently, a new probabilistic seismic hazard model has been developed by considering fault-based seismic sources, in addition to conventional areal sources. The most recent 2018 national census data provide accurate exposure information for Malawian people and their assets at detailed spatial resolutions. To develop seismic fragility functions that are applicable to Malawian housing stocks, building surveys and experimental tests of local construction materials have been conducted. By integrating these new developments of seismic hazard, exposure, and vulnerability modules, a quantitative seismic building collapse risk model for Malawi is developed on a national scale. For the rapid computation of seismic risk curves at individual locations, an efficient statistical approach for approximating the upper tail distribution of a seismic hazard curve is implemented. Using this technique, a seismic risk curve for a single location can be obtained in a few seconds, thereby, this can be easily expanded to the whole country with reasonable computational times. The results from this new quantitative assessment tool for seismic impact will provide a sound basis for risk-based disaster mitigation policies in Malawi.

Influence of Neonatal Ankyloglossia on exclusive breastfeeding in the six first months of life: a cohort study.

To analyze the influence of ankyloglossia on the prevalence and duration of exclusive breastfeeding of full-term infants up to the sixth month of life. Prospective cohort study, carried out with 225 mother-infant dyads who were followed up in the first six months of life in a center specialized in breastfeeding in a tertiary hospital. Full-term infants with asymptomatic ankyloglossia (no need for surgery) were compared with infants without change at monthly follow-up. Ankyloglossia was diagnosed using the Bristol Tongue Assessment Tool, with a positive diagnosis being considered for those with a score less than or equal to 5 considering functional and anatomical aspects. Statistical analyzes were performed using descriptive statistics, logistic regression (weaning determinants), relative risk, and survival curves (to analyze breastfeeding duration between groups with and without ankyloglossia). Ankyloglossia was associated with weaning (considered even partial) before the sixth month of life. After adjusted analysis, a higher risk of weaning was detected in infants with this alteration, with a risk present from the second month of life. In the survival analysis, the duration of breastfeeding in infants with ankyloglossia was shorter when compared to children without alterations. Compared to infants with normal lingual frenulum, babies with ankyloglossia had shorter exclusive breastfeeding time, but well above the average observed in the general population. The risk of weaning for this group was also higher.

Influência da Anquiloglossia neonatal na amamentação exclusiva nos seis primeiros meses de vida: estudo de coorte

ABSTRACT Purpose To analyze the influence of ankyloglossia on the prevalence and duration of exclusive breastfeeding of full-term infants up to the sixth month of life. Methods Prospective cohort study, carried out with 225 mother-infant dyads who were followed up in the first six months of life in a center specialized in breastfeeding in a tertiary hospital. Full-term infants with asymptomatic ankyloglossia (no need for surgery) were compared with infants without change at monthly follow-up. Ankyloglossia was diagnosed using the Bristol Tongue Assessment Tool, with a positive diagnosis being considered for those with a score less than or equal to 5 considering functional and anatomical aspects. Statistical analyzes were performed using descriptive statistics, logistic regression (weaning determinants), relative risk, and survival curves (to analyze breastfeeding duration between groups with and without ankyloglossia). Results Ankyloglossia was associated with weaning (considered even partial) before the sixth month of life. After adjusted analysis, a higher risk of weaning was detected in infants with this alteration, with a risk present from the second month of life. In the survival analysis, the duration of breastfeeding in infants with ankyloglossia was shorter when compared to children without alterations. Conclusion Compared to infants with normal lingual frenulum, babies with ankyloglossia had shorter exclusive breastfeeding time, but well above the average observed in the general population. The risk of weaning for this group was also higher.

Adverse events of topical ocular prostaglandin medications for glaucoma treatment: a pharmacovigilance study based on the FAERS database.

As prostaglandin medications, crucial in glaucoma treatment, become more widely used, their local adverse events are increasingly observed. To evaluate the common adverse events of four clinically commonly used prostaglandin F (FP) receptor agonists in the treatment of glaucoma in the Food and Drug Administration Adverse Event Reporting System (FAERS) database. We screened and analyzed the generic and brand names of latanoprost, bimatoprost, travoprost, and tafluprost in the FAERS database and summarized and cleaned the baseline information of subjects receiving the above-mentioned drugs. Perform descriptive statistical analysis on the baseline information of subjects using the drugs. Conduct disproportionality analysis of drug-related adverse events. The criteria for positive signals of adverse events are established by simultaneously meeting the thresholds set by four methods: the ratio of reported odds, proportional reporting ratio, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker. Additionally, assess the cumulative risk curves for drug-induced time of the aforementioned drugs and use one-way ANOVA to compare differences in drug-induced time across different groups. The study included 1567 latanoprost, 1517 bimatoprost, 696 travoprost, and 82 tafluprost subjects. Adverse events mainly affected eye disorders, with significant issues in iris hyperpigmentation, ocular pemphigoid, corneal endothelial cell loss, periorbital fat atrophy, corneal irritation, eyelash growth, and ocular hyperemia. The time to onset varied among drugs, with latanoprost showing the longest (mean days = 344.37) and bimatoprost the shortest duration (mean days = 155.65; p < 0.001). Although signal detection analysis based on the FAERS database cannot establish a definitive causal relationship, our study found that FP receptor agonists used in glaucoma can cause various adverse events. Assessing their clinical suitability and potential side effects is crucial for providing personalized treatment and ensuring medication safety.

Competing Risk Model to Determine the Prognostic Factors for Patients with Gliosarcoma

BackgroundGlioma (GSM) is a highly aggressive variant of brain cancer with an extremely unfavorable prognosis. Prognosis is not feasible by traditional methods due to lack of staging criteria, and the present study aims to screen more detailed demographic factors to predict the prognostic factors of the tumors. MethodsFor this study, we extracted data of diagnosed with GSM from the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2019.. To account for the influence of competing risks, we employed a cumulative incidence function (CIF). Subsequently, univariate analysis was conducted to evaluate the individual variables under investigation. Specifically for GSM patients, we generated cumulative risk curves for specific mortality outcomes and events related to competing risks. Additionally, we utilized both univariate and multivariate Cox analysis to account for non-GSM-related deaths that may potentially confound our research. ResultsThe competing risk model revealed that age, marital, tumor size, and adjuvant therapy were prognostic factors in GSM-related death. The analysis results showed that older age (60-70 years, ≥ 71 years) and larger tumor size (≥ 5.3 cm) significantly increased the risk of GSM-related death. Conversely, surgical intervention, chemotherapy and being single were identified as protective factors against GSM-related death. ConclusionOur study using a competing risk model provided valuable insights into the prognostic factors associated with GSM-related death. Further research and clinical interventions targeted at minimizing these risk factors and promoting the utilization of protective measures may potentially contribute to improved outcomes and reduced mortality rates for GSM patients.

Validation of a Proteomic-Based Prognostic Model for Breast Cancer and Immunological Analysis.

Breast cancer (BC) has emerged as an extremely destructive malignancy, causing significant harm to female patients and society at large. Proteomic research holds great promise for early diagnosis and treatment of diseases, and the integration of proteomics with genomics can offer valuable assistance in the early diagnosis, treatment, and improved prognosis of BC patients. In this study, we downloaded breast cancer protein expression data from The Cancer Genome Atlas (TCGA) and combined proteomics with genomics to construct a proteomic-based prognostic model for BC. This model consists of nine proteins (HEREGULIN, IDO, PEA15, MERIT40_pS29, CIITA, AKT2, CD171 DVL3, and CABL9). The accuracy of the model in predicting the survival prognosis of BC patients was further validated through risk curve analysis, survival curve analysis, and independent prognostic analysis. We further confirmed the impact of differential expression of these nine key proteins on overall survival in BC patients, and the differential expression of the key proteins and their encoding genes was validated using immunohistochemical staining. Enrichment analysis revealed functional associations primarily related to PPAR signaling pathway, steroid hormone metabolism, chemokine signaling pathway, DNA conformation changes, immunoglobulin production, and immunoglobulin complex in the high- and low-risk groups. Immune infiltration analysis revealed differential expression of immune cells between the high- and low-risk groups, providing a theoretical basis for subsequent immunotherapy. The model constructed in this study can predict the survival of BC patients, and the identified key proteins may serve as biomarkers to aid in the early diagnosis of BC. Enrichment analysis and immune infiltration analysis provide a necessary theoretical basis for further exploration of the molecular mechanisms and subsequent immunotherapy.