High-risk Class Research Articles

626 CARDIOVASCULAR DISEASE PHENOTYPES IN PREGNANCY: GESTATION, PERIPARTUM, AND LONG-TERM OUTCOMES

Abstract Background Maternal cardiovascular physiology is affected by changes that may be impaired in women with cardiovascular disease. Management of these pregnancies is challenging, as prevalence of late childbearing and of women with congenital heart disease achieving pregnancy is increasing. Objective This single-center prospective study sought to evaluate the effects of maternal cardiovascular disease (CVD) on pregnancy outcome and, after birth, on maternal and fetal morbidity and mortality. Methods 140 patients with cardiovascular disease prior to pregnancy (congenital or acquired) or cardiovascular disease developed during pregnancy were enrolled at our tertiary referral hospital between 2011 and 2021. Baseline data included cardiovascular risk factors, cardiological therapy, mWHO class in pregnancy, 12-lead EKG, and transthoracic echocardiography. Birth-related data included gestational age at delivery; neonatal weight, Apgar score at 1 and 5 minutes from birth; admission to neonatal ICU. A medium-to-long term follow-up of these patients was carried out by telemedicine. The primary endpoint was pregnancy outcome in terms of live births, week of delivery and fetal growth. Secondary endpoints included neonatal complications, maternal adverse cardiovascular events (death from cardiovascular causes, sustained arrhythmia, acute heart failure, postpartum cardiac surgery) and adverse obstetric events (spontaneous abortion, fetal loss, intrauterine death, neonatal death, SGA, prematurity, frequency of caesarean sections). Results Six cohorts were identified: adult congenital heart disease (ACHD); arrhythmias; valvular heart disease (VHD); ischemic CVD; cardiomyopathies and myopericarditis (CM/MYO); aortic disease. Heart disease prior to pregnancy was the most common setting (88%), mainly including ACHD (54%), followed by VHD (15%) and arrhythmias (11%). The pregnancy-onset cardiovascular diseases (12%) were predominantly CM/MYO (53%), mainly peripartum dilated cardiomyopathy, followed by arrhythmias (35%). Intermediate and high-risk classes (mWHO II-III, III and IV) were observed in 94 patients (67%). There were no maternal deaths; acute heart failure occurred in 6% of patients with no significant difference between groups. Sustained arrhythmias were found in 7% of the total cases, with a significantly higher prevalence in the cohort with preexisting arrhythmia (p <0.05). Cardiac surgery was performed in 4% of the patients, all in the ACHD cohort. Live births were 135 (94%); fetal deaths were 5 (one spontaneous abortion, 3 fetal losses and one neonatal death). Caesarean section was performed in 74% of patients. The mean gestational age at birth was low in all groups (36.6 ± 4.6 weeks), as well as the neonatal weight in grams (2676.9 ± 698.3) and the percentile of neonatal weight (37.8 ± 25.2). Reduced LVEF was significantly associated with low neonatal weight in the mWHO risk class IV patients (p = 0.04). At a mean follow-up of 26 months, cardiac surgery was significantly higher in the group of aortic disease (50% in diseases of the aorta, 8% in the ACHD group, 7% in the CM/MYO group, no events in other groups; p = 0.007), despite the small sample under investigation. Conclusions We provide insights of how, by strict and timely follow-up and a multidisciplinary approach implemented before pregnancy and throughout gestation, good outcomes can be achieved in pregnancies with congenital or acquired cardiovascular disease, despite the high prevalence of intermediate and high-risk patients.

1570. Cumulative Antibiotic Exposure and Risk for Candidemia

Abstract Background Broad-spectrum antibiotic use is a known risk factor for candidemia, but the duration and type of antibiotic exposure associated with greatest risk are not well characterized. Measurements of antibiotic days may be useful to assess cumulative burden of selective pressure on the microbiome and risk for candidemia. Methods This retrospective cohort study aimed to quantify the effect of antibiotic exposure on risk for candidemia. The primary outcome was hazard for developing candidemia across an array of antibiotic agents, classes and spectra. We measured antibiotic days of therapy (DOT) for adults admitted to Duke University hospitals 1/1/2016–12/31/2021. We excluded patients with community-onset candidemia, defined as growth of Candida spp. in blood culture collected ≤ 48 hours of admission, because antibiotic exposure prior to arrival was not reliably accessible. Time-to-event analyses were performed using the Nelson-Aalen estimator for modeling cumulative hazard functions to compare the proportion of candidemia observed based on exposure to each antibiotic. Logrank tests were used to evaluate for differences between hazard functions with a pre-specified alpha level of 0.05, and exponential cumulative proportional hazards models were implemented to generalize hazard functions. Results During 164,185 encounters in 105,330 unique patients, we identified candidemia in 237 patients. Prior to developing candidemia, cases received a total of 9,604 antibacterial DOT distributed across 46 unique antibiotic agents (Fig. 1) Carbapenems were associated with increased hazard for candidemia compared to beta-lactams (p< 0.005) (Figs. 2–3). There were 57 encounters for candidemia where meropenem was administered with a median of 10 DOT prior to onset of candidemia. Days of Antibiotic Therapy by Agent and Outcome. Conclusion This work represents a novel approach to quantifying antibiotic exposure as a risk factor for candidemia. In an unadjusted model, we identified carbapenems as a high-risk class; additional analysis with adjusted regression models will help contextualize exposure risk with respect to comorbidity and illness severity. This work may serve as a reference for antibiotic stewards as they promote appropriate antibiotic use, including reducing overuse of broad-spectrum antibiotics. Disclosures Rebekah W. Moehring, MD, MPH, FIDSA, FSHEA, UpToDate, Inc.: Author Royalties Barbara D. Alexander, MD, Astellas: Advisor/Consultant|HealthtrackRx: Advisor/Consultant|HealthtrackRx: Grant/Research Support|Scynexis: Grant/Research Support|UpToDate: Advisor/Consultant Melissa D. Johnson, PharmD, Biomeme: Licensed Transcriptional Signature for Candidemia|Charles River Laboratories: Grant/Research Support|Entasis Therapeutics: Advisor/Consultant|Merck & Co. Inc: Advisor/Consultant|Merck & Co. Inc: Grant/Research Support|Pfizer, Inc.: Advisor/Consultant|Scynexis Inc.: Grant/Research Support|Theratechnologies: Advisor/Consultant.

1129 IMAGING STRESS TEST OR CORONARY COMPUTED TOMOGRAPHY PRIOR TO NON-CARDIAC SURGERY? A SEVEN YEARS SINGLE CENTRE EXPERIENCE

Abstract Introduction Recent published ESC guidelines on non-cardiac surgery suggest the use of imaging stress test in patients with poor functional capacity and high likelihood of coronary artery disease or high clinical risk (class I, level B), while the use of coronary computed tomography has lower evidence (class IIa, level B). Witch test has the best performance in the clinical contest of pre-operative risk assessment is a matter of debate. Aim The aim of our single centre, retrospective study was to compare the prognostic role of the three main cardiac imaging modalities (CCT: Cardiac computed tomography, sCMR: stress cardiac magnetic resonance, SPECT MPI:single photon emission computed tomography myocardial perfusion imaging) in relation to 30 days post-surgery cardiac events (composite endpoint of myocardial infarction, unstable angina, cardiac death, cardiogenic shock, pulmonary oedema, life threatening cardiac arrythmias). Method Clinical data of patients from January 2015 to December 2021 were retrospectively collected from review of electronical medical records. Recorded data included demographic characteristics, clinical risk factors, results from laboratory tests, results from cardiac imaging tests, pharmacological therapy, type of intervention, cardiac complication within 30 days after surgery. Results Eight-hundred eighty-three patients were included (287 sCMR, 382 SPECT-MPI, 214 CCT). Rate of 30-days myocardial infarction was not significantly different between different modalities (CMR 1.1%, SPECT 1.3%; CT 0.5%; CMR vs SPECT p 0.998; sCMR vs CT p 0.639; SPECT vs CT 0.427); while planned invasive coronary angiography (ICA) was more common in CT group (CT 34%, CMR 16%, SPECT 10%, p<0,001). Absence of ischemia on stress test and absence of relevant coronary artery disease on CT are associate to lower cardiac events at follow-up (0.67%). Conclusions The use of imaging stress test and coronary CT are both associated to low incidence of cardiac events and should be recommended in risk assessment before non-cardiac surgery, in the appropriate clinical context.

Human Monkeypox—A Global Public Health Emergency

Monkeypox, a viral zoonosis caused by an Orthopoxvirus, is clinically characterized by fever, headache, lymphadenopathy, myalgia, rash and burdened by some complications that can be severe and life threatening. Monkeypox, endemic in some central and west African countries, in tropical areas near equator, rose to the headlines following its recent outbreak in non-endemic countries of Europe and the USA. Thus, the World Health Organization, worried about the growing dimension of the problem, declared monkeypox a global public health emergency. Now, after months of careful observation, the western scientific research is drawing conclusion that African endemic countries represent a reserve pool able to feed, through travelers and sexual networks, the outbreak in non-endemic countries in which high-risk communities such as gay and bisexual men are the most affected. Prevention through vaccination and early diagnosis are the core to breaking the chain of diffusion of this epidemic. Particular attention should be paid to avoid the spread from endemic countries, also implementing the economic investments in their public health system. Information campaigns and assistance to high-risk classes in non-endemic countries are important priorities, however, assuming that specific treatments for this disease are still tentative.

Alien trees and shrubs of Latvia – evaluation of current status and invasiveness

Abstract This article presents an updated list of annotated invasive trees and shrubs in Latvia. This list includes 178 taxa about which extensive information has been collected and analysed: family, first records in the area, native range, invasiveness status, vector of introduction, and species distribution in Latvia. In this article, the authors, for the first time in Latvia, provided an invasiveness risk assessment and distinguished risk classes for trees and shrubs. The methodology previously developed by E. Weber and D. Gut was used to assess the risk of invasiveness. The most widely represented families in the list of invasive trees and shrubs are Rosaceae (51 taxa or 28.65%) and Salicaceae (20 taxa or 11.24%). Having assessed the invasiveness status, two species (Acer negundo L. and Sorbaria sorbifolia (L.) A. Braun) were identified as transformers, and 42 tree and shrub taxa were identified as invasive. After the assessment of the invasiveness risk, the species were divided into three risk classes. The highest risk class includes 32 taxa that are threatening or are likely to threaten natural habitats in Latvia in the future. The results of this study can be used for further dendrological studies in relation to global change and for practical nature conservation and landscape gardening.

MRI- and Histologic-Molecular-Based Radio-Genomics Nomogram for Preoperative Assessment of Risk Classes in Endometrial Cancer.

High- and low-risk endometrial carcinoma (EC) differ in whether or not a lymphadenectomy is performed. We aimed to develop MRI-based radio-genomic models able to preoperatively assess lymph-vascular space invasion (LVSI) and discriminate between low- and high-risk EC according to the ESMO-ESGO-ESTRO 2020 guidelines, which include molecular risk classification proposed by "ProMisE". This is a retrospective, multicentric study that included 64 women with EC who underwent 3T-MRI before a hysterectomy. Radiomics features were extracted from T2WI images and apparent diffusion coefficient maps (ADC) after manual segmentation of the gross tumor volume. We constructed a multiple logistic regression approach from the most relevant radiomic features to distinguish between low- and high-risk classes under the ESMO-ESGO-ESTRO 2020 guidelines. A similar approach was taken to assess LVSI. Model diagnostic performance was assessed via ROC curves, accuracy, sensitivity and specificity on training and test sets. The LVSI predictive model used a single feature from ADC as a predictor; the risk class model used two features as predictors from both ADC and T2WI. The low-risk predictive model showed an AUC of 0.74 with an accuracy, sensitivity, and specificity of 0.74, 0.76, 0.94; the LVSI model showed an AUC of 0.59 with an accuracy, sensitivity, and specificity of 0.60, 0.50, 0.61. MRI-based radio-genomic models are useful for preoperative EC risk stratification and may facilitate therapeutic management.

A latent class analysis of adverse childhood life events in Ugandan adolescents

This study aimed to characterise adverse childhood events (ACEs) experiences of school-going Ugandan adolescents (female = 50.6%, with diagnosis of post-traumatic stress disorder: PTSD = 38.2%; mean age = 15.9 years, SD = 1.2 years). The children completed the Harvard Trauma Questionnaire. Latent class analysis yielded three groups of “low risk” (individuals with low probabilities of experiencing most of the adverse life events), “intermediate risk” (individuals with higher probability of being exposed to adverse life events compared to the low-risk group), and “high risk” (individuals with extremely high probabilities of having experienced all the adverse life events). Compared with the low-risk class, the high-risk class was found to be significantly more likely to have a diagnosis of PTSD. Being a female may be an antecedent risk factor for high exposure to ACE in the Ugandan setting. These findings indicate the feasibility of grouping Uganda children with ACEs for targeted treatment interventions.

An Unsupervised Machine Learning Method Stratifies Chronic Lymphocytic Leukemia Patients in Novel Categories with Different Risk of Early Treatment

Novel scoring systems have been developed in recent years to improve the accuracy of prognostication from historical clinical staging systems (Rai, Binet) for chronic lymphocytic leukemia (CLL). Most of them, however, rely on discretized and dichotomic values of the various biomarkers to infer prognosis. Here we analyzed the immunophenotypic and (immuno)genetic profiles in a wide CLL cohort by applying unsupervised machine learning methods elaborating prognostic factors as continuous variables, to identify novel relationships and interactions likely missed in conventional models. The study included 989 CLL patients with Rai stages 0-I-II (50, 36, 14% respectively), 420 (42.4%) treated, analyzed between 2003 and 2020. Treatment-free survival (TFS) was calculated from sampling (median TFS, 46 months). Median time of sampling from diagnosis was 7.2 months (~60% cases within 12 months). The studied laboratory-based markers were: CD20, FMC7, CD49d, CD49c, CD38, CD23, CD43, CD22, ZAP-70 expression by flow cytometry (reported as % of positive cells); del13, tris12, del11 and del17 cytogenetic abnormalities detected by FISH, reported as % of nuclei with abnormal signal; mutational status of TP53 by deep NGS, reported as % variant allele fraction (VAF); IGHV gene mutational status, reported as % mutations. By applying Cox proportional hazard model to estimate TFS on this pool of features, we selected the features with a fit p-value<0.05, i.e. del11, tris12, TP53 mutations, % IGHV mutation, expression of CD38 and CD49d. Then we grouped similar profiles with an unsupervised k-means algorithm, optimized by the Elbow method, to partition observations into 6 clusters (C1-C6). Clustering confidence for each patient was estimated through leave-one-out procedure and the average normalized score was 0.83 (0.85, 0.86, 0.79, 0.91, 0.73, 0.84, for C1 through C6, respectively). Centroid analysis was employed to evaluate which features mostly defined each cluster, as detailed below. C1 (n=220): all cases with <4.1% IGHV mutations, mostly (70%) IGHV-unmutated (UM, <2% cut-off), low CD49d expression (<30% of positive cells) in 90% of cases, low representation of other features (tris12, del11, CD38, TP53 mutations); C2 (n=210): high CD49d expression (99% of cases), equally balanced IGHV status (52% UM), low representation of other features; C3 (n=147): tri12 cases (100%; >10% of nuclei), concurrent high expression of CD49d (95%) and CD38 (67%), slightly enriched in UM IGHV cases (60%); C4 (n=303): cases heavily mutated in IGHV genes (mutation range 4.1-22.0%), low representation of all the other features; C5 (n=52): TP53 mutated cases with high mutation burden (VAF 35-97%), skewed towards UM IGHV (70%), irrelevant all the other features; C6 (n=57): highly clonal del11q cases (range 50-98%) mutually exclusive with TP53 mutations (2 mutated cases only), mostly UM IGHV (89%), low representation of all other features. Notably, in C1-C4, cases bearing TP53 mutations were present, although representing a minority (5-10%), mostly with low-VAF (median 6.7%, range 5-39%). Kaplan-Meier analysis revealed heterogeneous behaviors: C2, C3, C5, C6 presented a 50% TFS of 59, 25, 5, 9 months respectively, whereas TFS was not reached for C1 and C4 (Figure, A). Hierarchical agglomerative clustering identified 3 major risk classes (Figure, B). The high risk class (n=109) comprised C5 and C6 (TP53 mutations and del11q); the intermediate risk class (n=577) stratified on C1-2-3; the low risk class (n=303) was made by C4 only (CLL with highly mutated IGHV). The 50% TFS for high-intermediate-low risk was 7, 50 and not reached, respectively. In conclusion, we present here a novel machine-learning-driven, laboratory-based classification for predicting the risk of early treatment in CLL. Our approach identifies clusters at different risk with some novelties: i) a high IGHV mutational burden (i.e >4%) in the absence of other markers (e.g. CD49d) identifies patients with a particularly benign clinical course; ii) TP53 mutations and del11q associate with high risk of early treatment only if present in the vast majority of the CLL clone; iii) a IGHV status with low burden of mutations (i.e. <4%) along with CD49d expression or tris12 identifies patients at intermediate risk. These novel stratifications should be incorporated in risk algorithms for treatment prediction of CLL patients. Validation in additional independent cohorts is needed. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Çıldır Gölü Havzasında Erozyon Risk Analizi

Bu çalışmaya konu olan Çıldır Gölü Havzası, Türkiye’nin kuzeydoğusunda Doğu Anadolu Bölgesi’nin Erzurum - Kars Bölümü içerisinde yer almaktadır. Çıldır Gölü havzasında erozyon riskinin ve dağılışının belirlenmesi ile yıllık toplam toprak kaybının tespit edilmesi bu çalışmanın amacını oluşturmaktadır. İnceleme sahasında, havza ölçeğinde buna benzer bir çalışmanın bulunmaması ve aynı zamanda erozyonun, Çıldır Gölü üzerindeki etkilerinin belirlenmesi bu çalışmanın önemini arttırmaktadır. Sahadaki erozyon riskinin belirlenmesi için, günümüzde erozyon çalışmalarında sıklıkla kullanılan bir yöntem olan Düzenlenmiş Evrensel Toprak Kaybı Denklemi (RUSLE) tercih edilmiştir. Çalışmada altlık veri olarak 1/25.000 ölçekli topoğrafya paftaları kullanılmıştır. Sahaya ait arazi kullanım ve yağış verileri ile havzanın farklı noktalarından alınan toprak örnekleri, kullanılan diğer veri setlerini oluşturmaktadır. Çalışma kapsamında yapılan analizler ve üretilen haritalar sonucunda sahanın erozyon risk sınıfları ve yıllık toplam toprak kaybı miktarı hesaplanmıştır. Analizler sonucunda altı farklı erozyon risk sınıfı belirlenmiştir. Sahanın büyük bir bölümünün (% 82,75) çok hafif ve hafif erozyon risk sınıfları içerisinde kaldığı belirlenmiştir. Sahanın geri kalan kesiminin ise “orta derece” ve “çok yüksek” erozyon risk sınıfları içerisinde kaldığı tespit edilmiştir. Havzadaki yıllık toplam toprak kaybı ise 430.140 ton olarak hesaplanmıştır. Çalışmadan elde edilen sonuçlara göre sahada erozyon riski çok yüksek değildir, fakat gerekli önlemler alınmadığı durumda erozyon riski artabilir. Buna bağlı olarak, erozyon sonucu Çıldır Gölü’ne taşınacak olan sediment, göl alanının daralmasına neden olacak, inceleme alanındaki önemli geçim kaynaklarından olan balıkçılık bu durumdan olumsuz anlamda etkilenecek ve bölge halkı ekonomik kayıplara uğrayacaktır.

Risk prediction of pancreatic cancer using AI analysis of pancreatic subregions in computed tomography images.

Early detection of Pancreatic Ductal Adenocarcinoma (PDAC) is complicated as PDAC remains asymptomatic until cancer advances to late stages when treatment is mostly ineffective. Stratifying the risk of developing PDAC can improve early detection as subsequent screening of high-risk individuals through specialized surveillance systems reduces the chance of misdiagnosis at the initial stage of cancer. Risk stratification is however challenging as PDAC lacks specific predictive biomarkers. Studies reported that the pancreas undergoes local morphological changes in response to underlying biological evolution associated with PDAC development. Accurate identification of these changes can help stratify the risk of PDAC. In this retrospective study, an extensive radiomic analysis of the precancerous pancreatic subregions was performed using abdominal Computed Tomography (CT) scans. The analysis was performed using 324 pancreatic subregions identified in 108 contrast-enhanced abdominal CT scans with equal proportion from healthy control, pre-diagnostic, and diagnostic groups. In a pairwise feature analysis, several textural features were found potentially predictive of PDAC. A machine learning classifier was then trained to perform risk prediction of PDAC by automatically classifying the CT scans into healthy control (low-risk) and pre-diagnostic (high-risk) classes and specifying the subregion(s) likely to develop a tumor. The proposed model was trained on CT scans from multiple phases. Whereas using 42 CT scans from the venous phase, model validation was performed which resulted in ~89.3% classification accuracy on average, with sensitivity and specificity reaching 86% and 93%, respectively, for predicting the development of PDAC (i.e., high-risk). To our knowledge, this is the first model that unveiled microlevel precancerous changes across pancreatic subregions and quantified the risk of developing PDAC. The model demonstrated improved prediction by 3.3% in comparison to the state-of-the-art method that considers the global (whole pancreas) features for PDAC prediction.

Whole-body magnetic resonance imaging for staging Langerhans cell histiocytosis in children and young adults.

Radiographic skeletal survey (R-SS) is the standard imaging technique for the initial staging of Langerhans cell histiocytosis (LCH). Whole-body magnetic resonance imaging (WB-MRI) has been proposed as an effective, radiation-free alternative. We prospectively assessed patients with LCH followed at three tertiary centers in Italy and Austria. Two national study protocols were independently designed, and data were then pooled to increase the power of their findings. R-SS and WB-MRI were performed at diagnosis and repeated at the follow-up to confirm the nature of the identified lesions and to study their evolution. Data from 67 patients were analyzed (52 from Italy and 15 from Austria). Compared to R-SS, WB-MRI identified 29 additional skeletal lesions in 14 patients (including two false-positive lesions). Two skeletal lesions were detected at R-SS and missed at WB-MRI (false negative). Per-lesion sensitivity rates were 78.6% (95% CI: 71.0-85.9) for R-SS and 98.4% (95% CI: 94.4-99.8) for WB-MRI, respectively. Based on WB-MRI findings, six patients would have been upstaged to a higher risk class than staging with R-SS. WB-MRI had a significantly higher detection rate for skeletal lesions compared to R-SS. Clinical and radiology expertise is required to avoid upstaging and overtreatment.

Peran Pemerintah Kabupaten Pandeglang dalam Edukasi Mitigasi Bencana Tsunami di Sekolah Pesisir Pantai Pandeglang - Banten

Indonesia is located between 3 tectonic plates, which are the Pacific plate, the Indo-Australian plate, and the Eurasian plate. These 3 plates can collide with each other and can cause earthquakes and tsunamis, based on BNPB data, and in the Indonesia Disaster Risk Index (known as IRBI), Banten province is included in the high-risk class for disasters, including tsunami disasters. The location of the current research was carried out at SMA Negeri 3 Pandeglang and SMA Negeri 15 Pandeglang which were on the coast that were prone to tsunami disasters. The purpose of this study was to describe the relationship between government and schools in tsunami disaster preparedness. This study used a qualitative approach with a descriptive method. Data collection techniques consisted of observation, interviews and documentation. Based on the research results, it is known that the government could demonstrate its role in disaster management through 4 (four) ways, which were legislation, institutions, planning, and capacity building. The results showed that the Pandeglang Regency Government in this case the Pandeglang Regency BPBD was quite successful in Tsunami Disaster Mitigation Education at the Pandeglang Coastal School Banten. In carrying out disaster risk reduction efforts, the Pandeglang Regency Government had a legal basis and was also able to formulate disaster mitigation strategies in schools, which were the establishment of Disaster Resistant Schools (known as STB) and the formation of the Pandeglang Regency Regional Disaster Management Task Force (known as PBD.

Usefulness of Carotid Ultrasonography in the Diagnosis of Coronary Artery Disease Patients

Objective: The research aimed to examine whether the carotid condition is linked to coronary artery disease in sufferers sent to exercise echocardiography and when it raises the exercise echocardiography capability to forecast coronary artery disease. Place and Duration: During the last five years, continuous subjects over eighteen years with diagnosed coronary artery disease underwent exercise echocardiography and carotid ultrasound at Indus Hospital Karachi. Study Design: Cross-sectional Methodology: We studied 312 participants without past heart disease who experienced exercise echocardiography, coronary angiography, and carotid ultrasonography over five years. Specific variables had been described as proportions, and evaluation among groups was according to Fisher’s exact and chi-square tests. Constant variables had been described as mean or median whenever their distribution deceased from average, and variations had been evaluated through the un-paired t-test. Continuous and binary quantitative variables have been likened to utilizing binary logistic regression. IBM SPSS, Version 20 was utilized. Results: 178 (57.1 percent) participants had substantial coronary artery disease. Components linked to CAD in multi-variate evaluation were FPG (OR 2.04, p=0.062), pre-test possibility of CAD greater than 65 percent (odds ratio 7.42, p less than0.004), positive exercise echocardiography (odds ratio 42.04, p less than 0.004) and carotid plaque presence (odds ratio 5.8, p= 0.052). There wasn't a statistical factor in the area below the curve after the inclusion of carotid plaque to exercise echocardiography results (3.08 vs. 3.24, p=1.05) nor the level of sensitivity, uniqueness, predictive efficiency, or values. Conclusion: Carotid plaque is linked to CAD in sufferers going through exercise echocardiography (EE), although its inclusion to EE doesn't improve coronary artery disease (CAD) prediction, most likely because of inadequate mathematical power. Carotid plaque reclassified 1 / 3 of sufferers to high risk class in spite of negative exercise echocardiography (EE) or absence of coronary artery disease; these subjects take advantage of aggressive primary prevention treatments. Keywords: Carotid Ultrasonography, Coronary Artery Disease, echocardiography

Psychometric properties of the Slovenian version of Internet Disorder Scale-IDS-15.

BackgroundConceptualising internet addiction and assessing its symptoms has presented a significant challenge for researchers over the past 25 years. Recently, the Internet Disorder Scale (IDS-15), which is based on the criteria for Internet Gaming Disorder (IGD) from DSM-5, has emerged as a promising instrument to assess internet addiction. The main objective of the present study was to evaluate the psychometric properties of the Slovenian IDS-15.MethodsThe sample was recruited from the National Survey on the Use of Tobacco, Alcohol and Other Drugs that was conducted in 2018 on a nationally representative sample (N = 16,000; age range: 15–64 years; 62.4% response rate). The final sample comprised 9,161 participants, with 80.9% reporting having used the internet at least once a week (n = 7,413). A structured questionnaire was designed and internet addiction was assessed using the IDS-15.ResultsConfirmatory Factor Analysis showed acceptable fit to the proposed four-factor structure of the IDS-15. The reliability, and criterion, convergent and discriminant validity were also found to be adequate with a notable exception of the first item of the scale, as shown by its lower factor loading and higher variability. Additionally, latent profile analysis was used to distinguish between internet users with low (n = 3,818; 51.5%), medium (n = 3,111; 42.0%) and high (n = 484; 6.4%) addiction risk. Furthermore, the high-risk class was associated with higher IDS-15 factor scores, higher frequency of internet use in leisure time, and lower age of first internet use.ConclusionsThe present study provides new insights about the strengths and shortcomings of the IDS-15. Moreover, the results provide an insight into the prevalence of internet addiction in Slovenia, as well as associations with other potential factors. The results serve as the basis for further analyses on internet addiction epidemiology, policymaking activities, and design for targeted public health interventions in Slovenia.

Assessment of slope failure susceptibility along road networks in a forested region, northern Iran

The risk of slope failure is always associated with the roads constructed in mountain regions. Estimation of the susceptibility of roads to slope failure is a part of the solutions for decreasing road maintenance costs. In this study, we modeled the susceptibility of slope failure along a forest road in northern Iran using the random forest (RF) method. The distribution of past failures was surveyed during field reconnaissance to produce an inventory map. Then the failures were randomly divided into two groups such that 70% (176 locations) were used for model training and the remaining 30% (75 locations) were used for model validation. Eleven geoenvironmental factors (i.e., altitude, slope degree, slope direction, plan curvature, flow accumulation, stream power index, topographic wetness index, topographic position index, topographic roughness index, slope-length, and valley depth) that thought directly or indirectly affected slope failure were selected and linked to the failure locations. The spatial associations between the influencing factors and the failure locations were assessed using the RF method and used for generating spatially explicit maps of slope failure susceptibility. The results showed that stream power index, flow accumulation, and plan curvature with Gini coefficients of 74%, 66%, and 51%, respectively, were the most influential factors in the occurrence and distribution of slope failures. The slope failure susceptibility maps were classified using the natural breaks and geometrical intervals classification methods and showed that nearly 38.11% and 42.42% of the study area are in high to very high risk classes, respectively. Model validation using the sensitivity (92.31%), specificity (85.68%), accuracy (88.54%), root mean square error (RMSE) (0.303), and area under the curve (0.902) proved the excellent performance of the RF model in elucidating the failure mechanisms and predicting future failures. The slope failure susceptibility maps produced in this study allow the development of mitigation strategies for road construction projects.

Outcomes of Complex Abdominal Wall Reconstruction Using Acellular Dermal Matrix in High-Risk CDC Class III and IV Defects

Outcomes of Complex Abdominal Wall Reconstruction Using Acellular Dermal Matrix in High-Risk CDC Class III and IV Defects

Risk-Taking Behaviors Considering Internet Gaming Disorder among Iranian University Students: A Latent Class Analysis.

Dangerous behaviors adversely affect the health of adolescents and young adults. This study aimed to identify the subgroups of college students based on the parameters of risky behavior and analyze the impact of demographic factors and internet gaming disorder (IGD) belonging to each class. A cross-sectional study. The study was conducted on 1355 students through a multi-stage random sampling method in 2020. A survey questionnaire was used to collect data, and all students completed 1294 sets of questionnaires. The data were analyzed using t test and latent class analysis (LCA) through SPSS and PROC LCA in SAS 9.2 software. Three latent classes have been identified as low-risk (75%), tobacco smoker (8%), and high-risk (17%). There was a high possibility of risky behavior in the third class. Marital status (being single) (OR = 2.28, 95% CI: 1.19-4.37), unemployment (having no job) along with education (OR = 1.56, 95% CI: 1.04-2.33), and IGD (OR = 1.06, 95% CI: 1.04-1.09) increased the risk of inclusion in the tobacco smoker class. Moreover, unemployment (having no job) along with education (OR = 1.43, 95% CI: 1.11-1.84) increased the chance of being in the high-risk class. According to the findings of this study, 25% of the students were tobacco smokers or were in the high-risk class. The results of this study may help develop and evaluate preventive strategies that simultaneously take into account different behaviors.

S695 Factors Affecting Likelihood of Peptic Ulcer Disease as the Etiology of Suspected Upper Gastrointestinal Bleeding

Introduction: Patients presenting with suspected upper gastrointestinal bleeding (UGIB) have a broad differential diagnosis. Any process which affects mucosal integrity must be considered when developing a management plan. When treating UGIB a patient’s medical history may provide clues that prioritize consideration of certain diagnoses. This study aims to assess components of the medical history that affect the likelihood of finding a peptic ulcer during endoscopic evaluation. Methods: An IRB-approved retrospective study was performed to evaluate all adult patients who underwent endoscopy for suspected UGIB within five days of presentation, at two affiliated academic hospitals, between 2018 and 2022. Patients were excluded if they had prior endoscopy within 90 days of presentation. Demographic, procedural, and clinical data were obtained via electronic record. Descriptive statistics included t-tests and Chi-square tests. Multivariate analysis was conducted using logistic regression. (Table) Results: A total of 1392 charts were reviewed and 874 patients were included in the analysis. Average age was 64 years, and 525 (60%) were male. The most common symptoms were melena (68%), abdominal pain (32%) and hematemesis (28%). Peptic ulcer disease (PUD) was diagnosed in 397 patients (45%), with 97 patients (11%) classified as high-risk Forrest class 1a/1b/2a/2b lesions where endoscopic intervention is indicated. Another 300 patients (34%) had low risk PUD with Forrest class 2c/3 lesions, and 477 patients (55%) had no PUD. PPI-naïve patients were found to have PUD in 47% of endoscopies, compared to 36% in active PPI users. Multivariate analysis revealed PPI users were 37% less likely to have any ulcer (p< 0.0001). The risk of finding an ulcer increased by 2.0% for every year of age (p< 0.0001). High risk ulcers were more likely to be seen in males (OR 1.73, 95% CI 1.05-2.82), and a history of hepatic disease decreased the likelihood of finding these lesions (OR 0.56, 95% CI 0.37-0.85). Conclusion: Active outpatient PPI use leads to a significant decrease in the likelihood of finding PUD in patients with suspected UGIB. This result underscores the importance of considering other etiologies of bleeding in order to prevent a missed diagnosis and delay in care. The “protective” effect of hepatic disease likely stems from liver-related sources of UGIB present in this population. Even when PUD is suspected in these patients, the data suggest timely empiric treatment with antibiotics and vasoactive agents is warranted. Table 1. - Univariate & Multivariate Analysis of Factors Associated with Upper Gastrointestinal Bleed Presentations Any Ulcer High Risk Ulcer (Forrest 1a/1b/2a/2b) Low Risk Ulcer (Forrest 2c/3) No Ulcer Subjects (N=874) PPI Naïve (N=732) 346 (47%) 84 (11%) 262 (36%) 386 (53%) PPI Use (N=142) 51 (36%) 13 (9%) 38 (27%) 91 (64%) Active PPI Use OR 0.63 0.64 0.65 N/A (95% CI) (0.43-0.93) (0.33-1.23) (0.43-0.99) Age OR 1.02 1.04 1.01 N/A (95% CI) (1.01-1.03) (1.02-1.05) (1.01-1.02) Male Gender OR 1.29 1.73 1.21 N/A (95% CI) (0.97-1.72) (1.05-2.82) (0.88-1.64) Hepatic Disease History OR 0.56 0.86 0.46 N/A (95% CI) (0.37-0.85) (0.46-1.60) (0.28-0.73)

Washed microbiota transplantation improves patients with high blood glucose in South China.

Background and AimsAlthough fecal microbiota transplantation (FMT) from healthy donors has been shown to have hypoglycemic effects in animal models of diabetes, its clinical impact in patients with abnormal blood glucose metabolism is unclear, especially in southern Chinese populations. The aim of this study was to investigate the feasibility and efficacy of washed microbiota transplantation (WMT) in the treatment of abnormal blood glucose metabolism in a population in southern China.MethodsThe clinical data of patients with different indications who received 1-3 treatments of WMT were retrospectively collected. The changes of blood glucose, blood lipids, blood pressure, liver function and blood routine before and after WMT were compared, such as fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), total cholesterol (TC), triglyceride (TG), systolic blood pressure (SBP), white blood cells (WBC), lymphocytes (LY) and platelets (PLT), etc.ResultsA total of 195 patients were included in the First Affiliated Hospital of Guangdong Pharmaceutical University, including 20 patients with high blood glucose and 175 patients with normal blood glucose. WMT has a significant effect in reducing short term blood glucose level (FBG) in patients with high blood glucose (p < 0.05). The fasting blood glucose (FBG) of 72.22% of patients with high blood glucose decreased to normal in a short term (about 1 month) (p < 0.001); In the medium term (about 2 months), there was a significant hypolipidemic (TG) (p = 0.043) effect, long term (about 6 months) significant blood pressure lowering (SBP, p = 0.048) effect. Overall, WMT significantly reduced the risk of high risk classes of Atherosclerotic Cardiovascular Disease (ASCVD) in the short term (p = 0.029) and medium term (p = 0.050).ConclusionWMT can significantly improve blood glucose in patients with high blood glucose, and there is no long-term elevated risk of blood glucose and ASCVD. FBG levels were significantly reduced in both the short and medium term in patients with high blood glucose treated with WMT. Therefore, the regulation of gut microbiota by WMT may provide a new clinical approach for the treatment of abnormal blood glucose metabolism.

Arrests, Mental Health Outcomes, and Discharge Status in U.S. Military Veterans: A Latent Class Analysis

Most U.S. military service members are discharged routinely, but about 15% receive non-routine discharges. Little is known about how patterns of arrests prior-to and in-service relate to neuropsychological symptoms acquired through military service, or how these symptoms and patterns are associated with discharge type. We investigated latent group differences in post-9/11 era veterans’ patterns of arrests; examined mental health-related predictors of subgroup membership; and modeled associations between latent class structure and non-routine discharge. Veterans with traumatic brain injury, alcohol misuse, and post-traumatic stress disorder, had greater odds of belonging to a high-risk vs. low-risk class with the highest probabilities of arrests in-service. The high-risk class had a 45% chance of non-routine discharge compared with 35% for a stable-risk class and 6% for a low-risk class. Veterans with increased probabilities of arrests in-service compared with pre-service showed the highest odds of mental and behavioral health problems and non-routine discharge.