Reliable Risk Assessment Tool Research Articles

Reduced-order models for the greenhouse gas leakage prediction from depleted hydrocarbon reservoirs using machine learning methods

Geologic storage of carbon dioxide (CO2) is one of the potential technological options to mitigate human-induced climate change. Depleted hydrocarbon reservoirs are promising candidates for storing CO2. However, these reservoirs contain residual hydrocarbons that may migrate beyond primary reservoirs during CO2 storage operations. Therefore, it is imperative to quantify the leakage risks of residual hydrocarbons (primarily methane) and CO2 to shallow aquifers. We focus on developing models that quantify leakage risks from wellbores that provide potential leakage pathways. To offset the computational intensity of high-fidelity reservoir simulations, we develop a Reduced-order model (ROM) enabling fast and accurate CO2 and hydrocarbon leakage predictions through wellbores. The ROM is generated using a dataset of 1000 high-fidelity, compositional reservoir simulations of CO2 injection into generic hydrocarbon reservoirs. The input parameters include reservoir depth, permeability, net to the gross ratio (NTG), reservoir pressure multiplier, wellbore permeability, average water saturation, oil compositions, and time. We analyze the performance of various ROM development techniques, including multivariate adaptive regression splines, gradient boosting, and neural networks. While all ROM development techniques yield excellent agreement with R2 higher than 0.95, the neural network model performs best compared to the other two methods. Furthermore, we explore developing a ROM as a collection of multiple sub-ROMs to improve accuracy across a wide range of predictions. We observe that using a set of sub-ROMs outperforms the prediction accuracy of a single ROM. Our work enables fast and reliable risk-assessment tools for CO2 geologic storage in depleted hydrocarbon fields.

Analysis and Prediction of Financial Stock Risk Value Based On Improved FAST-ICA Algorithm and GARCH Model

This study focuses on improving the FAST-ICA algorithm and GARCH model to more accurately analyze and predict the value at risk of financial stocks. Accurately measuring stock risk is crucial for investors and securities managers in today's financial markets, as it directly affects investment decisions and risk control. We have improved the FAST-ICA algorithm and proposed the TS-ICA algorithm, aiming to improve the separation performance and iteration efficiency of the algorithm. And we combine the TNA method for data preprocessing to eliminate noise and improve the robustness and prediction accuracy of the model. In terms of GARCH model, we constructed the TS-ICA-GARCH model using the independent decomposition results of the TS-ICA algorithm to more accurately predict the volatility and value at risk (VaR) of stocks. Through empirical analysis and backtesting, we have verified the superiority of the TS-ICA-GARCH model in measuring risk, especially in extreme market conditions with stronger coping ability. This study provides a more reliable risk assessment tool for financial market participants, which helps to develop more effective investment strategies and risk management measures.

Spatiotemporal Mammography-based Deep Learning Model for Improved Breast Cancer Risk Prediction.

Breast cancer is one of the most prevalent cancers among women. It is the second leading cause of death in cancer-related deaths. Early detection and personalized risk assessment can reduce the mortality rate and improve survival rates. Classical risk prediction models which rely on traditional risk factors produce inconsistent results among the different populations. Thus, they are not routinely used in screening programs. Deep learning was proven to improve the results of breast cancer risk prediction. CNNs can detect risk cues from screening mammograms. However, the deep learning models utilize the spatial information of each screening mammogram independently. This study aims to further improve the risk prediction models by exploiting the spatiotemporal information in multiple screening time points. We implemented a Siamese neural network for spatiotemporal risk prediction and compared the results against CNN trained using two different time points (T1 and T2) independently. We tested our results on 191 cases, 61 of which were diagnosed with cancer. The Siamese model showed a superior AUC of 0.81 against 0.75 and 0.77 at T1 and T2 respectively. The Siamese network also exhibited higher accuracy and F1-score with values of 0.78 and 0.61 while CNNs have the same accuracy of 0.76 with an F1-score of 0.54 at T1, and 0.59 at T2. The results suggest that spatiotemporal risk prediction can be a more reliable risk assessment tool.

Risk prediction in patients with classical low-flow, low-gradient aortic stenosis undergoing surgical intervention.

Classical low-flow, low-gradient aortic stenosis (LFLG-AS) is an advanced stage of aortic stenosis, which has a poor prognosis with medical treatment and a high operative mortality after surgical aortic valve replacement (SAVR). There is currently a paucity of information regarding the current prognosis of classical LFLG-AS patients undergoing SAVR and the lack of a reliable risk assessment tool for this particular subset of AS patients. The present study aims to assess mortality predictors in a population of classical LFLG-AS patients undergoing SAVR. This is a prospective study including 41 consecutive classical LFLG-AS patients (aortic valve area ≤1.0 cm2, mean transaortic gradient <40 mmHg, left ventricular ejection fraction <50%). All patients underwent dobutamine stress echocardiography (DSE), 3D echocardiography, and T1 mapping cardiac magnetic resonance (CMR). Patients with pseudo-severe aortic stenosis were excluded. Patients were divided into groups according to the median value of the mean transaortic gradient (≤25 and >25 mmHg). All-cause, intraprocedural, 30-day, and 1-year mortality rates were evaluated. All of the patients had degenerative aortic stenosis, with a median age of 66 (60-73) years; most of the patients were men (83%). The median EuroSCORE II was 2.19% (1.5%-4.78%), and the median STS was 2.19% (1.6%-3.99%). On DSE, 73.2% had flow reserve (FR), i.e., an increase in stroke volume ≥20% during DSE, with no significant differences between groups. On CMR, late gadolinium enhancement mass was lower in the group with mean transaortic gradient >25 mmHg [2.0 (0.0-8.9) g vs. 8.5 (2.3-15.0) g; p = 0.034), and myocardium extracellular volume (ECV) and indexed ECV were similar between groups. The 30-day and 1-year mortality rates were 14.6% and 43.8%, respectively. The median follow-up was 4.1 (0.3-5.1) years. By multivariate analysis adjusted for FR, only the mean transaortic gradient was an independent predictor of mortality (hazard ratio: 0.923, 95% confidence interval: 0.864-0.986, p = 0.019). A mean transaortic gradient ≤25 mmHg was associated with higher all-cause mortality rates (log-rank p = 0.038), while there was no difference in mortality regarding FR status (log-rank p = 0.114). In patients with classical LFLG-AS undergoing SAVR, the mean transaortic gradient was the only independent mortality predictor in patients with LFLG-AS, especially if ≤25 mmHg. The absence of left ventricular FR had no prognostic impact on long-term outcomes.

Nomogram to predict postpartum hemorrhage in cesarean delivery for twin pregnancies: a retrospective cohort study in China.

Postpartum hemorrhage (PPH) is the most common cause of maternal morbidity and mortality worldwide. A reliable risk assessment tool for PPH could optimize available interventions to reduce adverse maternal outcomes. The objective of this study was to explore a nomogram predicting the risk of postpartum hemorrhage after cesarean delivery for twin pregnancies. This single-center retrospective cohort study conducted twin pregnancies who underwent cesarean delivery between January 2014 and July 2021. Propensity score matching at baseline was used to match PPH (blood loss ≥1000 mL) and non-PPH group (blood loss <1000 mL). A nomogram was developed to predict the risk of PPH in cesarean delivery for twin pregnancies. The receiver operating characteristic curve (ROC), calibration plot, and decision curve analysis (DCA) were, respectively, used to evaluate the discrimination, calibration, and clinical utility of the prediction models. After propensity score matching, 186 twin pregnancies in the PPH group were matched with 186 controls in the non-PPH group. Seven independent prognostic variables, including antepartum albumin, assisted reproductive technology, hypertensive disorders of pregnancy, placenta previa, placenta accrete spectrum, intrapartum cesarean delivered, and estimated weights of twins, were used to build the nomogram. Based on the performance of the model, it appears that a good calibration (Hosmer-Lemeshow χ2 = 4.84, P > 0.05), an excellent predictive ability (area under the curve: 0.778, 95% CI: 0.732-0.825), and a good positive net benefit in the predictive model have been achieved. The nomogram was first generated to predict PPH in cesarean delivery for twin pregnancies, which could help clinicians to provide a reference for the preoperative surgical plan, choose optimal treatments, optimize healthcare resources, and thereby reduce the associated adverse maternal outcomes.

Comparison of Lactate Clearance with Established Risk Assessment Tools in Predicting Outcomes in Acute Upper Gastrointestinal Bleeding

Early risk stratification is mandatory in acute upper gastrointestinal bleeding (AUGIB) to guide optimal treatment. Numerous risk scores were introduced, but lack of practicability led to limited use in daily clinical practice. Lactate clearance is an established risk assessment tool in a variety of diseases, such as trauma and sepsis. Therefore, this study compares the predictive ability of pre-endoscopic lactate clearance and established risk scores in patients with AUGIB at the University Hospital of Cologne. Active bleeding was detected in 27 (25.2%) patients, and hemostatic intervention was performed in 35 (32.7%). In total, 16 patients (15%) experienced rebleeding and 12 (11.2%) died. Initially, lactate levels were elevated in 64 cases (59.8%), and the median lactate clearance was 18.7% (2.7-48.2%). Regarding the need for endoscopic intervention, the predictive ability of Glasgow Blatchford Score, pre-endoscopic Rockall score, initial lactate and lactate clearance did not differ significantly, and their area under the receiver operating characteristic curves were 0.658 (0.560-0.747), 0.572 (0.473-0.667), 0.572 (0.473-0.667) and 0.583 (0.483-0.677), respectively. Similar results were observed in relation to rebleeding and mortality. In conclusion, lactate clearance had comparable predictive ability compared to established risk scores. Further prospective research is necessary to clarify the potential role of lactate clearance as a reliable risk assessment tool in AUGIB.

Association of IgG N-glycomics with prevalent and incident type 2 diabetes mellitus from the paradigm of predictive, preventive, and personalized medicine standpoint.

Type 2 diabetes mellitus (T2DM), a major metabolic disorder, is expanding at a rapidly rising worldwide prevalence and has emerged as one of the most common chronic diseases. Suboptimal health status (SHS) is considered a reversible intermediate state between health and diagnosable disease. We hypothesized that the time frame between the onset of SHS and the clinical manifestation of T2DM is the operational area for the application of reliable risk assessment tools, such as immunoglobulin G (IgG) N-glycans. From the viewpoint of predictive, preventive, and personalized medicine (PPPM/3PM), the early detection of SHS and dynamic monitoring by glycan biomarkers could provide a window of opportunity for targeted prevention and personalized treatment of T2DM. Case-control and nested case-control studies were performed and consisted of 138 and 308 participants, respectively. The IgG N-glycan profiles of all plasma samples were detected by an ultra-performance liquid chromatography instrument. After adjustment for confounders, 22, five, and three IgG N-glycan traits were significantly associated with T2DM in the case-control setting, baseline SHS, and baseline optimal health participants from the nested case-control setting, respectively. Adding the IgG N-glycans to the clinical trait models, the average area under the receiver operating characteristic curves (AUCs) of the combined models based on repeated 400 times fivefold cross-validation differentiating T2DM from healthy individuals were 0.807 in the case-control setting and 0.563, 0.645, and 0.604 in the pooled samples, baseline SHS, and baseline optimal health samples of nested case-control setting, respectively, which presented moderate discriminative ability and were generally better than models with either glycans or clinical features alone. This study comprehensively illustrated that the observed altered IgG N-glycosylation, i.e., decreased galactosylation and fucosylation/sialylation without bisecting GlcNAc, as well as increased galactosylation and fucosylation/sialylation with bisecting GlcNAc, reflects a pro-inflammatory state of T2DM. SHS is an important window period of early intervention for individuals at risk for T2DM; glycomic biosignatures as dynamic biomarkers have the ability to identify populations at risk for T2DM early, and the combination of evidence could provide suggestive ideas and valuable insight for the PPPM of T2DM. The online version contains supplementary material available at 10.1007/s13167-022-00311-3.

Comparison of Two Risk Assessment Scores in Predicting Peri-Implantitis Occurrence during Implant Maintenance in Patients Treated for Periodontal Diseases: A Long-Term Retrospective Study.

Background: There is a need for reliable risk assessment tools to better predict peri-implantitis occurrence. This study compared the long-term prognosis value of two models of risk assessment scoring in predicting peri-implantitis. Methods: Seventy-three patients with treated periodontitis representing 232 implants and attending long-term implant maintenance were evaluated. The Periodontal Risk Assessment (PRA) score, which combines only periodontal risk factors/indicators, and the Implant Risk Assessment (IRA) score, which combines both periodontal and implant risk factors/indicators, were calculated during implant maintenance. Peri-implantitis was defined by the presence of probing depth ≥6 mm with bleeding on probing/suppuration and bone level ≥3 mm. Analyses were performed at the patient level. Results: The mean implant follow-up was 6.5 years. Peri-implantitis incidence was 17.8%, and high-risk PRA and IRA percentages were 36.9% and 27.3%, respectively. High-risk PRA and IRA were significantly associated with peri-implantitis incidence, with hazard ratio (HR) = 4.8 and 3.65, respectively. Risk factors/indicators considered separately showed reduced associations with peri-implantitis. Conclusions: The PRA score combining periodontal parameters and IRA score combining both periodontal and implant parameters have comparable value in predicting peri-implantitis. These scores could allow practicians to intercept the risk of peri-implantitis and to manage follow-up modalities in patients with treated periodontitis.

Getting Ready for Wound Certification: Promoting Skin Health and Preventing Injuries.

Getting Ready for Wound Certification: Promoting Skin Health and Preventing Injuries.

All around suboptimal health \u2014 a joint position paper of the Suboptimal Health Study Consortium and European Association for Predictive, Preventive and Personalised Medicine

First two decades of the twenty-first century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The time-frame between onset of SHS and clinical manifestation of associated disorders is the operational area for an application of reliable risk assessment tools and predictive diagnostics followed by the cost-effective targeted prevention and treatments tailored to the person.This article demonstrates advanced strategies in bio/medical sciences and healthcare focused on suboptimal health conditions in the frame-work of Predictive, Preventive and Personalised Medicine (3PM/PPPM). Potential benefits in healthcare systems and for society at large include but are not restricted to an improved life-quality of major populations and socio-economical groups, advanced professionalism of healthcare-givers and sustainable healthcare economy. Amongst others, following medical areas are proposed to strongly benefit from PPPM strategies applied to the identification and treatment of suboptimal health conditions:Stress overload associated pathologiesMale and female healthPlanned pregnanciesPeriodontal healthEye disordersInflammatory disorders, wound healing and pain management with associated complicationsMetabolic disorders and suboptimal body weightCardiovascular pathologiesCancersStroke, particularly of unknown aetiology and in young individualsSleep medicineSports medicineImproved individual outcomes under pandemic conditions such as COVID-19.

Comparing approaches for modelling indirect contact transmission of infectious diseases.

Mathematical models describing indirect contact transmission are an important component of infectious disease mitigation and risk assessment. A model that tracks microorganisms between compartments by coupled ordinary differential equations or a Markov chain is benchmarked against a mechanistic interpretation of the physical transfer of microorganisms from surfaces to fingers and subsequently to a susceptible person's facial mucosal membranes. The primary objective was to compare these models in their estimates of doses and changes in microorganism concentrations on hands and fomites over time. The abilities of the models to capture the impact of episodic events, such as hand hygiene, and of contact patterns were also explored. For both models, greater doses were estimated for the asymmetrical scenarios in which a more contaminated fomite was touched more often. Differing representations of hand hygiene in the Markov model did not notably impact estimated doses but affected pathogen concentration dynamics on hands. When using the Markov model, losses due to hand hygiene should be handled as separate events as opposed to time-averaging expected losses. The discrete event model demonstrated the effect of hand-to-mouth contact timing on the dose. Understanding how model design influences estimated doses is important for advancing models as reliable risk assessment tools.

The Thermo-Pressure Concept: A New Model in Diabetic Foot Risk Stratification

Elevated foot pressure and high temperatures have been proposed as predictive factors for diabetic foot ulceration; however, on their own, their predictive value is still questionable. This pilot study hypothesized that combining these two measurements in a thermo-pressure model could result in a more reliable risk assessment tool for providing risk categorization aimed to determine whether there is a correlation between foot plantar pressure and temperature in patients living with diabetes mellitus (DM) when compared with healthy individuals following a 15 min walk. Foot pressure and thermographic images were taken from 48 participants who were categorised into four groups following clinical evaluation into healthy individuals (Group A), living with DM with no complications (Group B), DM with peripheral arterial disease (Group C) and DM patients with neuropathy (Group D). This study demonstrated a positive correlation between pressure and temperature; as pressure increases, so does temperature. This was more pronounced in the groups with DM when compared to the healthy group. More research is warranted to further develop this innovative thermo-pressure model, which could hopefully be more sensitive in categorizing and identifying patients living with DM who are at risk of developing foot ulceration to initiate prompt care.

A Comparison of the P-POSSUM and NELA Risk Score for Patients Undergoing Emergency Laparotomy in Singapore.

Emergency laparotomy (EL) is a high-risk surgical procedure associated with considerable morbidity and mortality around the world. A reliable risk-assessment tool that is specific to patients undergoing EL allows the early identification of high-risk patients and enables appropriate healthcare resource allocation. The objective of this study was to compare the commonly used Portsmouth-physiologic and operative severity score for the enumeration of mortality and morbidity (P-POSSUM) with the recently developed National Emergency Laparotomy Audit (NELA) score in terms of their accuracy for identifying patients at increased risk of 30-day mortality in a predominantly Asian population. Physiological and operative data from a prospectively collected audit of adult patients undergoing EL in 2018 and 2019 across two tertiary hospitals in Singapore were used to retrospectively calculate both the P-POSSUM and NELA scores for each patient encounter. This was then compared to actual mortality rates to determine each model's accuracy and precision. 830 patients were included in the study with a 30-day mortality of 5.66%. The area under the receiver operating characteristics curve (AUROC) was similar for both the NELA (0.86, p < 0.001, 95% CI 0.81-0.91) and the P-POSSUM models (0.84, p < 0.001, 95% CI 0.78-0.89). While the models over-predicted mortality, overall O:E ratios showed that the NELA model performance was superior to that of P-POSSUM (0.58 [95% CI 0.43-0.77] compared to 0.34 [95% CI 0.26-0.46]). The NELA risk-prediction model accurately predicts 30-day mortality in this large cohort of patients undergoing EL and outperforms the current P-POSSUM model. We recommend that the NELA score should replace the P-POSSUM score as a model to distinguish between high- and low-risk patients undergoing EL.

Exploring ergonomists’ experiences after participation in a theoretical and practical research project on observational risk assessment tools

Objective. The aim of this qualitative study was to explore how ergonomists experienced an e-learning concept as a tool for knowledge translation; furthermore, to explore what, if any, impact the knowledge translation had regarding the ergonomists’ work with risk assessments. Methods. Twelve Swedish ergonomists employed in the occupational health service (OHS) participated in a research project, which included an e-learning program in risk assessment training. Focus group interviews and individual interviews were used for data collection. Results. The ergonomists appreciated the e-learning concept, e.g., its flexibility enabled them to decide when and where to practice. The concept was considered feasible within the context of the OHS. The ergonomists experienced an increased knowledge of different observation-based risk assessment tools, which expanded their professional toolboxes. Additionally, they began to reflect more regarding the reliability of risk assessment tools and how to enhance quality in risk assessment assignments. Conclusion. This study showed that e-learning may comprise an efficient knowledge translation for improved risk assessments in the OHS. The program contributed to changes in ergonomists’ risk assessment procedures, e.g., in the selection of tools, increasing the number of observers, employing a participatory approach and more often actively involving stakeholders during the risk assessment process.

HARİZMİ Düşme Riski Ölçeği’nin Psikometrik Özelliklerinin İncelenmesi

Giriş: Hasta düşmelerine neden olan risk faktörlerinin belirlenebilmesi için geçerli ve güvenilir risk değerlendirme araçlarına ihtiyaç vardır. Amaç: Bu araştırma ile HARİZMİ Düşme Riski Ölçeği'nin psikometrik özelliklerinin incelenmesi amaçlanmıştır. Yöntem: Araştırma retrospektif desende vaka-kontrol korelasyonel psikometrik bir çalışmadır. Araştırmanın örneklemini bir üniversite ve bir eğitim araştırma hastanesinde yatarak sağlık hizmeti alan 16 yaş ve altı 480 hasta oluşturmaktadır. Ölçeğin güvenirliği Cronbach alpha katsayısı ve madde toplam puan korelasyonu, geçerliği ise ROC eğrisi, duyarlılık, özgüllük, pozitif öngörü değeri ve negatif öngörü değerleri hesaplanarak değerlendirilmiştir. Bulgular: Ölçeğin Cronbach alpha katsayısı .35 olarak hesaplanmış ve ölçekte yer alan maddelerin hepsinin toplam puan ile istatistiksel olarak anlamlı bir korelasyona sahip olduğu saptanmıştır. HARİZMİ Düşme Riski Ölçeği’nin duyarlılık değeri .43, özgüllük değeri .62, pozitif öngörü değeri .37, negatif öngörü değeri ise .68 olarak hesaplanmıştır. ROC analizi sonucunda ROC Eğrisi Altında Kalan .61 bulunmuştur (p = .031; %95 Güven Aralığı = .51 - .69). Sonuç: Araştırma kapsamında HARİZMİ Düşme Riski Ölçeği’nin güvenirliğinin ve hastaları ayırım gücünün düşük olduğu saptanmıştır. Sonraki araştırmalarda ölçeğin revize edilerek daha geniş bir örneklemde uygulanması önerilir.

LUNG NODULES: VALLEY FEVER OR CANCER IN HIV

SESSION TITLE: Medical Student/Resident Pulmonary Manifestations of Systemic Disease 3 SESSION TYPE: Med Student/Res Case Rep Postr PRESENTED ON: 10/09/2018 01:15 PM - 02:15 PM INTRODUCTION: The Human Immunodeficiency Virus (HIV) epidemic has vastly changed the prevalence and epidemiological burden of fungal infections. With worldwide travel, diseases such as coccidioidomycosis, while rare in non endemic parts of the United States of America, <1%, have been increasing in incidence. Coccidioidomycosis may present with a constellation of clinical and radiological findings that often confound diagnosticians, further emphasizing the need for more sensitive risk calculators. CASE PRESENTATION: A 45 year old caucasian male with HIV, last CD4 845, on highly active antiretroviral therapy (HAART) presents with a six week history of cough. He reports a persistent dry cough associated with right-sided chest pain now resolved and constitutional symptoms. He also has shortness of breath, treated with Albuterol inhaler. He is a current smoker with 16 pack years. Prior to onset of his symptoms, he completed a cross-country road trip from California to the east coast. He denied any ill-contacts or limitations in activity. On exam, he is afebrile in no respiratory distress with an unremarkable exam. His white blood cell count was 9.7 (13% eosinophils) along with positive coccidioidomycosis antibody complement fixation 1:4 and elevated IgG and IgM. Notably tuberculosis quantiferon gold, histoplasmosis antibodies and urine antigen were within normal limits. Computerized Tomography chest with contrast revealed 1.9x1.4x1.1 cm spiculated solid upper lobe nodule along with scattered subcentimeter, noncalcified solid round nodules in all lobes bilaterally and mediastinal lymphadenopathy. He was commenced on oral fluconazole for pulmonary coccidioidomycosis and scheduled for follow-up. DISCUSSION: Numerous advances have been made in the management of HIV, however aspects of the pathophysiology still remain unknown. ATS (2010) recommended treatment of coccidioidomycosis in all immunocompromised patients e.g. HIV AIDS as well as treatment in immunocompetent patients with HIV (BII). Nathan et al, later highlighted not only the role of a decreased number of CD4 cells as a component of immunosuppression in HIV patients but also the progressive loss of T cell function due to neutrophil immunosuppression in chronic HIV infection. As HIV places patients at higher risk for disseminated disease, it further confounds differentiating lung nodules due to coccidioidomycosis from lung cancer. Ronaghi et al, found significant radiographic overlap between the aforementioned. A study by Peterson et al, evaluated three existing online risk calculators and found they performed well in patients with lung cancer but poorly in patients with coccidioidomycosis. No serological marker has been validated. CONCLUSIONS: The increasing prevalence of HIV along with worldwide travel will mandate the need for more reliable risk assessment tools to prevent unnecessary invasive procedures and treatment for decades to come. Reference #1: Nathan L. Bowers, E. Scott Helton, Richard P. H. Huijbregts, Paul A. Goepfert, Sonya L. Heath, Zdenek Hel. Immune Suppression by Neutrophils in HIV-1 Infection: Role of PD-L1/PD-1 Pathway. PLOS Pathogens. 2014 March; 10(3). E10003993 Reference #2: Reza Ronaghi, MD; Ali Rashidian, MD; Paul Mills, PhD; Kurt Hildebrandt, MD; Keith Carson, MD; Michael Peterson, MD. Radiographic Features Differentiating Lung Nodules Caused by Coccidioidomycosis From Lung Cancer. CHEST. 2015 October; 148(4_MeetingAbstracts): 509A. https://doi.org/10.1378/chest.2248593 Reference #3: Michael Peterson, Reza Ronagi, Paul Mills. Differentiating incidental lung nodules due to lung cancer from those due to coccidioidomycosis. European Respiratory Journal. 2015; 46. https://doi.org/10.1183/13993003.congress-2015.PA2996 DISCLOSURES: No relevant relationships by Sahai Donaldson, source=Web Response No relevant relationships by Karlene Williams, source=Web Response

Risk assessment for a long-span cable-stayed bridge subjected to multiple support excitations

Current probabilistic seismic risk assessment framework does not fully address the impact of the spatial variability of ground motions on long bridges. However, recent studies have highlighted that long-span bridges are more vulnerable to damage due to spatial varying ground motions. To achieve this increased vulnerability, this research presents a reliable risk assessment tool for long-span bridges subjected to spatial varying ground motions. The proposed method includes the following tasks: (i) the simulation of spatially variable ground motions, (ii) creation of numerical bridge model, (iii) generation of probabilistic seismic demand models, (iv) development of component and system fragility curves, (v) estimation of annual exceedance of damage through site-compatible hazard curves, and (vi) computation of repair time. As an illustration, a cable-stayed bridge is selected to highlight the effect of spatial variability of ground motions on the seismic risk and repair time of individual bridge components and bridge system in comparison to uniform excitations. Additionally, a sensitivity analysis is performed to examine the effect of spatial variability parameters and hazard curve-related parameters on the seismic risk of the bridge.

Waist: Hip ratio is a more reliable risk assessment tool for acute myocardial infarction: A hospital based case – control study among rural Maharashtra, India

Background: Worldwide, incidence of Acute Myocardial Infarction (AMI) has been increasing over the years and now reflected as the leading cause of death universally.Aims and Objectives: To determine the strength and degree of association between obesity indices and serum lipid profile with incidence of AMI in rural Indian population.Materials and Methods: Hospital based case-control study was conducted among newly diagnosed cases of AMI and matched controls. A total of 40 patients admitted in ICCU at rural tertiary care centre and equal number of healthy age/sex controls were enrolled in the study. Over the period of three months, by employing personal interview, anthropometric, clinical and laboratory examination information was obtained. Data were analysed by using SPSS version17 and results were expressed on Mean ± SD, Chi-Square test and Odds ratio.Results: Mean age of cases and controls was 58.5 and 60 yrs respectively with mean difference of 1.5 years. Maximum, 47.5% cases were in age 60-69 yrs and shown 1.5 times risk of getting AMI. The Overweight, Waist- Hip ratio and hyperlipidemia (cholesterol, H:L ratio and triglycerides) were significantly associated with AMI (p &lt; 0.05 at 95% CI) and risk predicted by odd’s was of 9.3, 3.4, 2.4, 4.8, and 9.4 respectively. Every unit rise in overweight, Waist:Hip ratio, serum cholesterol, LDL and triglycerides; the risk of occurrence of AMI increases by 1.7, 2.8, 1.02, 1.01 and 1.03 times respectively.Conclusion: Study demonstrated, W:H ratio is a more valid, single, reliable risk assessment tool for AMI could be practiced at health care institutions as well as community surveillance.Asian Journal of Medical Sciences Vol.8(2) 2017 38-43

Framework of aftershock fragility assessment–case studies: older California reinforced concrete building frames

SummaryCurrent seismic design codes and damage estimation tools neglect the influence of successive events on structures. However, recent earthquakes have demonstrated that structures damaged during an initial event (mainshock) are more vulnerable to severe damage and collapse during a subsequent event (aftershock). This increased vulnerability to damage translates to increased likelihood of loss of use, property, and life. Thus, a reliable risk assessment tool is required that characterizes the risk of the undamaged structure subjected to an initial event and the risk of the damaged structure under subsequent events. In this paper, a framework for development of aftershock fragilities is presented; these aftershock fragilities define the likelihood that a building damaged during a mainshock will exhibit a given damage state following one or more aftershocks. Thus, the framework provides a method for characterizing the risk associated with damage accumulation in the structure. The framework includes the following: (i) creation of a numerical model of the structure; (ii) characterization of building damage states; (iii) generation of a suite of mainshock–aftershocks; (iv) mainshock–aftershock analyses; and (v) development of aftershock fragility curves using probabilistic aftershock demand models, defined as a linear regression of aftershock demand–intensity pairs in a logarithmic space, and damage‐state prediction models. The framework is not limited to a specific structure type but requires numerical models defining structural response and linking structural response with damage. In the current study, non‐ductile RC frames (low‐rise, mid‐rise, and high‐rise) are selected as case studies for the application of the framework. Copyright © 2015 John Wiley &amp; Sons, Ltd.

Risk assessment tools to identify women with increased risk of osteoporotic fracture: Complexity or simplicity? A systematic review

A huge number of risk assessment tools have been developed. Far from all have been validated in external studies, more of them have absence of methodological and transparent evidence, and few are integrated in national guidelines. Therefore, we performed a systematic review to provide an overview of existing valid and reliable risk assessment tools for prediction of osteoporotic fractures. Additionally, we aimed to determine if the performance of each tool was sufficient for practical use, and last, to examine whether the complexity of the tools influenced their discriminative power. We searched PubMed, Embase, and Cochrane databases for papers and evaluated these with respect to methodological quality using the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS) checklist. A total of 48 tools were identified; 20 had been externally validated, however, only six tools had been tested more than once in a population-based setting with acceptable methodological quality. None of the tools performed consistently better than the others and simple tools (i.e., the Osteoporosis Self-assessment Tool [OST], Osteoporosis Risk Assessment Instrument [ORAI], and Garvan Fracture Risk Calculator [Garvan]) often did as well or better than more complex tools (i.e., Simple Calculated Risk Estimation Score [SCORE], WHO Fracture Risk Assessment Tool [FRAX], and Qfracture). No studies determined the effectiveness of tools in selecting patients for therapy and thus improving fracture outcomes. High-quality studies in randomized design with population-based cohorts with different case mixes are needed.