Overestimation Of Risk Research Articles

Novel methodology for developing a safety standard based on clustering of experts’ assessments of safety requirements

The practice of developing product or system safety standards is currently conducted with high level of subjectivity, which affects the reliability of development outcomes. The decision to adopt specific safety requirements into the standard is usually based on the knowledge, intuition and experience of the technical expert involved in developing the body of the safety standard made up of those requirements or specifications. This is usually carried out without analyzing risk attributes or factors addressed by each safety requirement constituting a safety standard. This can lead to inaccuracy and lack of reliability due to either under-estimation or over-estimation of risks involved. This research presents unprecedented, novel, structured and objective methodology, that aims to improve the practice of developing safety standards. In order to accomplish the above end, the proposed methodology acts to prioritize the system’ safety requirements of each system’s design elements based on a set of commonly identified risk factors they address. We have investigated the currently existing risk prioritization and multi-criterion decision making techniques, and found that machine learning data clustering approaches can be adequate especially in case of relatively large number of assessed decision alternatives (i.e., the assessed safety requirements). We have elaborated the merits of the proposed clustering-based methodology over existing prominent ones. The proposed methodology starts with analyzing product or system safety to identify common risk factors. A numerical scale is used to enable objective quantification of risk factors’ values for each safety requirement by multiple experts. The obtained experts’ numerical assessments of each safety requirement are then averaged to represent the raw data set containing risk profiles of each safety requirement assessed. This risk factors data set is then used by fuzzy c-means clustering algorithm, to organize them into groups of different level of priorities, so as to prioritize their corresponding safety requirements. We have applied the proposed methodology on a real case study of developing school bus safety standard. The main benefit of the proposed methodology includes its capability to support the safety standards development practitioners and policy makers, as well as technical experts in objectively and systematically carry out the critical decision of adoption, exclusion and update of the safety requirements into the developed safety standard. Additionally, it can efficiently guide safety engineers and inspectors to undertake more reliable and structured risk assessment process. Over and above, the implementation of the proposed methodology is guaranteed to result in more reliable, accurate and risk-informed safety standard.

Fewer patients receive recommendations for pharmacotherapy in primary prevention using the 2018 atherosclerotic cardiovascular disease risk estimator

Shortly after the introduction of the 2013 original Pooled Cohort Equation (PCE), an overestimation of risk was suggested. As such, the updated 2018 PCE was developed to more accurately assess atherosclerotic cardiovascular disease (ASCVD) risk in the population. Hence, this study aims to compare drug prescribing recommendations in a large, real-world patient population, depending on which PCE is used to estimate 10-year ASCVD risk. This retrospective cohort study identified 20,843 patients aged between 40 and 75 years with no previous ASCVD. The 10-year ASCVD risk score was assessed by using both PCE. Patients were assigned to the four risk categories according to the 2018 ACC/AHA guideline. The percentage of patients qualifying for guideline-recommended primary prevention with statins and/or anti-hypertensives were compared between both PCE. Risk reclassification occurred in 26.7% of patients overall (n = 5571), of which 98.1% (n = 5466) were assigned to lower risk categories with the updated PCE. Non-diabetic (14.0%) patients no longer met the threshold for recommending statins as primary prevention with the updated PCE. Likewise, 13.8% of patients with stage I hypertension no longer met the threshold for recommending antihypertensive drugs with the updated PCE. In conclusion, risk reclassification occurred among 26.7% of patients overall, mostly due to lower risk categories assigned by the updated PCE. Up to 14.0% of patients no longer met the threshold for recommending statin therapy and/or antihypertensive drugs by using the updated PCE. These findings suggest that using the updated PCE could translate into fewer patients receiving pharmacotherapy for ASCVD primary prevention.

Performance of the Pooled Cohort Equations in Hispanic Individuals Across the United States: Insights From the Multi‐Ethnic Study of Atherosclerosis and the Dallas Heart Study

Performance of the Pooled Cohort Equations in Hispanic Individuals Across the United States: Insights From the Multi‐Ethnic Study of Atherosclerosis and the Dallas Heart Study

Involvement of Tunisian General Practitioners in the Management of Patients at Risk of Infective Endocarditis: A Cross-Sectional Study

Objectives This work aimed to estimate the knowledge and practice of general dentists in the governorate of Manouba regarding the management of patients at risk of infective endocarditis. Materials and Methods A survey involving private sector general dentists in the governorate of Manouba was performed. It contained 21 questions, and it was addressed to 111 dentists. Only 82 dentists responded. To carry out the descriptive study, we used the SPSS software version 21.0. Results Our results proved the lack of knowledge among dentists in the governorate of Manouba with regard to the management of patients at risk of infective endocarditis. An overestimation of the risk and an overprescription of antibiotic were found in order to ensure an over-protection for the patients as well as the dentist. In fact, 85.4% of these dentists prescribed antibiotic prophylaxis for the two groups of patients (high risk and moderate risk). Only 9.8% followed the right modality of antibiotic prophylaxis prescription; 4.9% of the dentists prescribed antibiotic only 1 hour before the act and 4.9% of them prescribed antibiotic 1 hour before the act and continued the treatment in case of the presence of an infectious site. Conclusion A discrepancy towards an over-estimation of risk and overprescription of antibiotic was found between the recommendations and real practice. Similar studies in the other governorates of Tunisia are recommended in order to better understand the problem.

How urban layout and pedestrian evacuation behaviours can influence flood risk assessment in riverine historic built environments

Riverine Historic Built Environments (HBEs) in urban centres are relevant scenarios for flood risk, due to the compact layout of their outdoor spaces, that are squares and streets, and their position in flood-prone areas. Differences in HBE layout can provide differences in flood risks, but excluding the response of exposed individuals can lead to risk underestimation or overestimation, as for other hazards. This work is a first attempt to compare how accounting or not pedestrian evacuation behaviours can affect flood risk assessment and emergency strategies evaluation. Parametric configurations of typical HBEs are provided on case-studies, and existing tools for hydrodynamic and pedestrian evacuation simulation are applied to them. Risk indexes for the whole HBE (macroscale) and each outdoor space (microscale) in it are provided. Results show how the risk indexes trends accounting or not pedestrian evacuation behaviours are similar if considering the macroscale, while differences at the microscale exist (about 15 % in absolute terms). Concerning emergency strategies, sheltering seems to decrease the risk for the whole HBE up to 33 % in comparison to leaving the flood-affected area. Results also support where/how to place gathering areas in the HBE.

Good general health and lack of family history influence the underestimation of cardiovascular risk: a cross-sectional study.

Underestimation of cardiovascular risk may interfere with prevention of cardiovascular diseases (CVDs). We investigate whether general health and family history of myocardial infarction (MI) are associated with underestimation of perceived cardiovascular risk, and if the participants' calculated risk modifies that association. The analysis sample consisted of 526 individuals, 50-64 years old, from a population-based cohort study. Information on general health (poor/fairly good, good, and very good/excellent), family history of MI, and self-perceived risk relative to others of similar age and sex were collected though a web-based survey. Participants were categorized into underestimation (n = 162, 31%), accurate estimation (n = 222, 42%), and overestimation (n = 142, 27%) of cardiovascular risk by comparing calculated Systematic Coronary Risk Estimation (SCORE) with self-perceived risk. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for underestimation vs. accurate estimation of cardiovascular risk were computed using logistic regression (n = 384). Very good general health (OR 2.60, 95% CI 1.10-6.16) and lack of family history (OR 2.27, 95% CI 1.24-4.18) were associated with underestimation of cardiovascular risk. The associations were modified by the participants' calculated risk level; the association was stronger for high-risk individuals; without family history OR 22.57 (95% CI 6.17-82.54); with very good/excellent health OR 15.78 (95% CI 3.73-66.87). A good general health and the lack of family CVD history can obscure the presence of other risk factors and lead to underestimation of cardiovascular risk, especially for high-risk individuals. It is, therefore, crucial to address the fact that the development of CV disease may be silent and multifactorial.

A hybrid copula-fragility approach for investigating the impact of hazard dependence on a process facility’s failure

Multiple disasters induced by hurricanes such as floods, strong winds, and heavy rainfall have always been a significant threat to coastal infrastructures. However, few studies have attempted to model the dependence between hazards and study its impact on multi-hazard risks—these cognitive deficiencies inevitably affect the control of risks. This paper addresses these difficulties by first using the copulas to capture the dependence between hurricane-induced floods and strong winds based on synthetic multi-hazard events. Moreover, another two types of dependence, regression-based and mutually independent, are constructed to compare the impact of different dependence behaviors on the facility’s failure. Second, the frequency of concurrent events and a scenario-based fragility function are convolved to quantify the multi-hazard risk of storage tanks. Subsequently, the annualized failure risk (AFR) and the mean return period of failure (MRPF) are used as two metrics for the multi-hazard risk. The case study results demonstrate that the BB1 copula can accurately describe the change in dependence across the full range of the multivariate distribution, avoiding overestimation or underestimation of equipment failure risks. The application of risk zoning provides decision-makers with more intuitive and convenient tools for planning and layout, highlighting the practicability of the proposed multi-hazard risk assessment method.

External Validation of a Risk Prediction Model for Ventricular Arrhythmias in Arrhythmogenic Right Ventricular Cardiomyopathy

The new 5-year ventricular arrhythmia (VA) occurrence risk model is a major breakthrough for arrhythmia risk stratification in the challenging population of patients with arrhythmogenic right ventricular cardiomyopathy (ARVC). In the original study, the model resulted in a 20.6% reduction in implantable cardioverter-defibrillator (ICD) placement compared with the 2015 consensus, for the same protection level. However, only internal validation was performed, limiting generalisation. We externally validated the model in a European tertiary care cohort of 128 patients with ARVC with restrictive indications for primary prevention ICD placement. Overall, 74% were men, none had VA history, and a single patient had an ICD at baseline. Median age at diagnosis was 38 years (interquartile range [IQR] 28-50). During a median follow-up of 7.8 years (IQR 6.1-9.7), 15 patients (12%) experienced VA. The model provided good discrimination, with a C-index for 5-year VA risk prediction of 0.84 (95% confidence interval 0.74-0.93). However, the model led to an overestimation of the 5-year VA risk when applying thresholds < 50%. With a < 10% predicted risk, no patient showed VA. With a 7.5% predicted risk, the ICD:VA ratio was 6.3 vs 3.4 in the original study. The model still outperformed the 2015 International Task Force Consensus. Overall, in a relatively large European ARVC cohort with restrictive indications for ICD placement, the ARVC model for VA prediction successfully identified ARVC patients with VA during follow-up. Yet, our study underscores the need for careful threshold selection, considering the model’s associated risk overestimation in low- to intermediate-risk patients.

A lognormal model for evaluating maximum residue levels of pesticides in crops.

To evaluate pesticide regulatory standards in agricultural crops, we introduced a regulatory modeling framework that can flexibly evaluate a population's aggregate exposure risk via maximum residue levels (MRLs) under good agricultural practice (GAP). Based on the structure of the aggregate exposure model and the nature of variable distributions, we optimized the framework to achieve a simplified mathematical expression based on lognormal variables including the lognormal sum approximation and lognormal product theorem. The proposed model was validated using Monte Carlo simulation, which demonstrates a good match for both head and tail ends of the distribution (e.g., the maximum error=2.01% at the 99th percentile). In comparison with the point estimate approach (i.e., theoretical maximum daily intake, TMDI), the proposed model produced higher simulated daily intake (SDI) values based on empirical and precautionary assumptions. For example, the values at the 75th percentile of the SDI distributions simulated from the European Union (EU) MRLs of 13 common pesticides in 12 common crops were equal to the estimated TMDI values, and the SDI values at the 99th percentile were over 1.6-times the corresponding TMDI values. Furthermore, the model was refined by incorporating the lognormal distributions of biometric variables (i.e., food intake rate, processing factor, and body weight) and varying the unit-to-unit variability factor (VF) of the pesticide residues in crops. This ensures that our proposed model is flexible across a broad spectrum of pesticide residues. Overall, our results show that the SDI is significantly reduced, which may better reflect reality. In addition, using a point estimate or lognormal PF distribution is effective as risk assessments typically focus on the upper end of the distribution.

Maternal perception of the risk of vertically transmitted infections: the impact of expert counseling

Insufficient and imprecise information during pregnancy can lead to an overestimation of maternal and fetal risk associated to various exposures during gestation. This study aimed to assess whether expert obstetrical counseling in cases of maternal infections at risk of vertical transmission could impact maternal perception of risk and the tendency to terminate pregnancy. This is a monocentric prospective observational study of 185 consecutive pregnant women with confirmed diagnosis of infectious diseases at risk of vertical transmission during the first or second trimester of pregnancy. Patients were divided into 2 different groups, according to the type infectious disease: infections at high risk of fetal damages and infections at low risk. Every woman included in the study underwent medical counseling with a physician with experience of vertically transmitted infections. Moreover, each woman involved in the study was offered a detailed second trimester ultrasound scan. Maternal concern for their pregnancy and the disposition to interrupt the pregnancy were investigated by 2 questionnaires submitted to patients before and after medical expert counseling; a third questionnaire was completed only by those women who decided to undergo second trimester ultrasound scan at our hospital. Of the 185 consecutive patients meeting the inclusion criteria, 171 (92.4%) filled out the visual analog scale for concern about the baby's health both before and after medical consultation. After medical consultation, there was a significant decrease in mean visual analog scale for concern: from 67.1±26.0 to 41.3±28.8 (change score, -25.8; 95% confidence interval, -29.9 to -21.7). Higher baseline levels of concern had more room for reduction, and infections at high fetal risk of damage were associated with lower decrease in concern. However, risk perception decreased in both low-risk and high-risk pregnancies. Notably, 82 patients (53.2%) underwent ultrasonography and filled out the visual analog scale after examination. The mean score after examination was 28.3±24.4 and significantly lower than the mean score registered after consultation (change score, -16.6; 95% confidence interval, -22.9 to -10.3). A total of 162 women (87.6%) declared their tendency to interrupt pregnancy both before and after the consultation. There was a significant decrease in mean tendency from 42.1±32.6 to 22.7±27.1 (change score, -19.4; 95% confidence interval, -23.6 to -15.2). Regression analysis revealed that both low- and high-risk patients significantly reduced their tendency. A total of 73 patients (45.1%) underwent ultrasonography and filled out the visual analog scale after examination. The mean score after examination was 9.9±20.6 and significantly lower than the mean score registered after consultation (change score, -13.4; 95% confidence interval, -19.1 to -7.7). Our results confirm the importance of a comprehensive and sufficient expert medical counseling that, on one hand, can reduce maternal risk perception, improving quality of life for mothers, and, on the other hand, can lead to feasible results, reducing a woman's disposition to termination of pregnancy.

Casualty Risk Analysis for Remotely Piloted Aircraft Systems Operations

This paper offers an alternative Casualty Area assessment. This parameter appears in all flying vehicles risk evaluation. This work arises from the intention of contributing to the subject of risk assessment in aviation. All the formulations of the Casualty Area — which will be analyzed in this paper — are tailored for debris with high kinetic energies. These models lead to an overestimation of the risk associated with small drones flight, preventing both their use and the implied operational benefits. The proposed version tailors the small Remotely Piloted Aircraft Systems (commonly known as drones) falling under the A2 European Aviation Safety Agency (EASA) category, C2 class [European Aviation Safety Agency, Civil drones (Unmanned aircraft, 2018), https://www.easa.europa.eu/easa-and-you/civil-drones-rpas , accessed November (2019)], i.e. drones with a mass up to 4 kg. To obtain the new formulation, the authors started with the most used formula, proposed by Montgomery [R. M. Montgomery and J. A. Ward, Casualty Areas from Impacting Inert Debris for People in the Open (Research Triangle Institute, 1995)], used by FAA (Federal Aviation Administration, [Range Safety Group, Common Risk Criteria for National Test Ranges Inert Debris (Range Commanders Council, 2000)] and [Range Safety Group, Common Risk Criteria Standards for National Test Ranges (Range Commanders Council, 2010)]), adopting new hypotheses but following the same process. The results allow a risk formulation more suitable for drones of the above-mentioned size [Range Safety Group, Range Safety Criteria For Unmanned Air Vehicles Supplement (Range Commanders Council, 1999)]. The proposed formulation can be of use for specific regulatory issues. As a matter of fact, many services use small drones: aerial photography during public assemblies, concerts, sporting events, home deliveries, buildings thermal evaluation, to name just a few. The implementation of the present results allows a wider series of operations previously restricted due to the estimation of an incompatible level of risk. In fact, with the new formulation of the Casualty Area, the level of risk is safely lowered, mainly addressing the small dimension drones [European Aviation Safety Agency, Civil drones (Unmanned aircraft), https://www.easa.europa.eu/easa-and-you/civil-drones-rpas , Online accessed November (2019)]. The steps leading to the final formulation derive from a comprehensive analysis, coherent with the guidelines set by FAA and EASA.

Competing Risk Analysis in Renal Allograft Survival: A New Perspective to an Old Problem.

Graft survival after kidney transplant (KTX) is often estimated by the Kaplan-Meier (KM) method censoring for competing endpoints, primarily death. This method overestimates the incidence of graft loss. In 3157 adult KTX recipients followed for a mean of 79.2 months, we compared kidney and patient survival probabilities by KM versus competing risk analysis (CRA). These methods are extended to comparing different regression methods. Compared with CRA, the probabilities of death and graft loss (censored for the other outcome) were substantially higher by KM. These differences increased with increasing follow-up time. Importantly, differences in graft losses were magnified in subgroups with greater probabilities of death. Among recipients with diabetes, the probabilities of graft loss at 20 years were 57% by KM and 32% by CRA, while for non-diabetes mellitus corresponding values were 44% and 35%. Similar results are noted when comparing older versus younger recipients. Finally, we find that the Fine-Gray method assumptions are violated when using age and gender as covariates and that the alternative method of Aalen-Johansen may be more appropriate. CRA provides more accurate estimates of long-term graft survival and death, particularly in subgroups of recipients with higher rates of the competing event. Overestimation of risk by KM leads to both quantitative and qualitative misinterpretations of long-term KTX outcomes. When using regression analyses, care should be taken to check assumptions to guide the choice of appropriate method.

Dilution-based evaluation of airborne infection risk - Thorough expansion of Wells-Riley model

Evaluation of airborne infection risk with spatial and temporal resolutions is indispensable for the design of proper interventions fighting infectious respiratory diseases (e.g., COVID-19), because the distribution of aerosol contagions is both spatially and temporally non-uniform. However, the well-recognized Wells-Riley model and modified Wells-Riley model (i.e., the rebreathed-fraction model) are limited to the well-mixed condition and unable to evaluate airborne infection risk spatially and temporally, which could result in overestimation or underestimation of airborne infection risk. This study proposes a dilution-based evaluation method for airborne infection risk. The method proposed is benchmarked by the Wells-Riley model and modified Wells-Riley model, which indicates that the method proposed is a thorough expansion of the Wells-Riley model for evaluation of airborne infection risk with both spatial and temporal resolutions. Experiments in a mock hospital ward also demonstrate that the method proposed effectively evaluates the airborne infection risk both spatially and temporally. The proposed method is convenient to implement for the development of healthy built environments.

ESC 2019 guidelines on chronic coronary syndromes: can calcium scoring improve the risk underestimation associated with the updated pre-test probability risk score?

Abstract Funding Acknowledgements Type of funding sources: None. Introduction The European Society of Cardiology (ESC) published an updated stable chest pain guideline in 2019. It recommends the use of an updated pre-test probability (PTP) risk score (RS) to assess the likelihood of coronary artery disease (CAD), to try and reduce the risk overestimation associated with previous risk scores. We sought to assess the performance of the 2019 PTPRS in a contemporary cohort of patients undergoing CT coronary angiography (CTCA). Furthermore, we focussed on patients with PTPRS &amp;lt;15%, and assessed the utility of CT calcium scores as a discriminator of risk. Methods 652 patients who were investigated with CTCA for stable chest pain between January 2017 and May 2018 were included in a retrospective analysis. CTCA reported CAD degree of stenosis as normal/minimal stenosis, mild (30-50%), moderate (50-70%), or severe (&amp;gt;70%). ESC 2019 pre-test probability risk scores were retrospectively calculated and compared. Results A total of 652 patients underwent CTCA between 01 January 2017 and 31 May 2018, of which 330 were male and 322 were female, with an average age of 55 years ±11 years. Using the ESC 2019 PTPRS there were no patients with PTPRS &amp;gt;85%. 2 patients had PTPRS 50-85%; one patient had moderate stenosis and one mild stenosis on CTCA. There were 267 patients with PTPRS 15-50%; 23 (9%) patients had severe CTCA stenosis, 37 (14%) a moderate stenosis, and 34 (13%) a mild stenosis. A further 379 patients had PTPRS &amp;lt;15%; 11 (3%) had severe stenosis and 20 (5%) moderate stenosis. A further 27 (7%) patients had mild CTCA stenosis. A total of 357 of 379 patients with PTPRS &amp;lt;15% based on ESC 2019 had a CT calcium score. 236 patients were found to have a calcium score of zero, and 121 patients had a score greater than zero, with a range between 1 and 930. Of patients with zero calcium score, only 1 (0.4%) patient had severe stenosis, 2 (0.8%) moderate stenoses and 6 (2.5%) mild stenosis. In contrast, in patients with positive calcium scores, 10 (8%) had severe stenosis, 18 (15%) moderate stenosis, and 22 (18%) mild stenosis. Conclusions The ESC 2019 PTPRS classified this as an overall low risk cohort. The downward risk modification of PTPRS has led to a large number of patients being classified as low risk with PTPRS &amp;lt;15%. No or deferred investigation is recommended by the ESC in this cohort. However, the use of CT calcium scores in patients with PTPRS &amp;lt;15%, detected the majority of patients with any degree of CAD. CT calcium scores are a simple and low cost risk modifier, and may help identify patients who may benefit from primary prevention as per SCOT-Heart. Patients with calcium score greater than zero could be investigated with CTCA.

Laxative Use and Risk of Dyskalemia in Patients with Advanced CKD Transitioning to Dialysis.

Patients with advanced CKD experience increased intestinal potassium excretion. This compensatory mechanism may be enhanced by laxative use; however, little is known about the association of laxative use with risk of dyskalemia in advanced CKD. Our study population encompassed 36,116 United States veterans transitioning to ESKD from 2007 to 2015 with greater than or equal to one plasma potassium measurement during the last 1-year period before ESKD transition. Using generalized estimating equations with adjustment for potential confounders, we examined the association of time-varying laxative use with risk of dyskalemia (i.e., hypokalemia [potassium <3.5 mEq/L] or hyperkalemia [>5.5 mEq/L]) versus normokalemia (3.5-5.5 mEq/L) over the 1-year pre-ESKD period. To avoid potential overestimation of dyskalemia risk, potassium measurements within 7 days following a dyskalemia event were disregarded in the analyses. Over the last 1-year pre-ESKD period, there were 319,219 repeated potassium measurements in the cohort. Of these, 12,787 (4.0%) represented hypokalemia, and 15,842 (5.0%) represented hyperkalemia; the time-averaged potassium measurement was 4.5 mEq/L. After multivariable adjustment, time-varying laxative use (compared with nonuse) was significantly associated with lower risk of hyperkalemia (adjusted odds ratio [aOR], 0.79; 95% confidence interval [95% CI], 0.76 to 0.84) but was not associated with risk of hypokalemia (aOR, 1.01; 95% CI, 0.95 to 1.07). The results were robust to several sensitivity analyses. Laxative use was independently associated with lower risk of hyperkalemia during the last 1-year pre-ESKD period. Our findings support a putative role of constipation in potassium disarrays and also support (with a careful consideration for the risk-benefit profiles) the therapeutic potential of laxatives in hyperkalemia management in advanced CKD.

Characteristics of patients affecting the duration of positivity at SARS-CoV-2: a cohort analysis of the first wave of epidemic in Italy.

to investigate the characteristics of patients affecting the duration of positivity test by RT-PCR in the population of Piedmont, a Region of North-West of Italy.DESIGN: observational cohort study. from the administrative database of the regional SARS-CoV-2 surveillance system, a cohort of all patients who tested positive by a RT-PCR assay to SARS-CoV-2 occurring from 22.02.2020 to 30.09.2020 in the Piedmont Region (N. 29,292) was obtained. The cohort has been linked to the hospital discharge database and to the vital statistics database. outcome of the study was the risk of non negativization, estimated by fitting Generalizing Estimating Equation model (GEE), a longitudinal model which consider for each subject several records collected on fixed time intervals 15, 30, 45 or 60+ days from the first positive test. Negativization was defined as the condition in which two consecutive samples taken from the patient at least 24 hours apart were negative for the presence of SARS-CoV-2. the median duration of positive RT-PCR was 27 days. A higher median of days until positive persistence was observed in people over 80 (34 days, IQR 25-49), female (28 days, IQR 18-40), symptomatic patients (28 days, IQR 19-40), hospitalized people (32 days, IQR 21-44), patients with Charlson's index >0 (34 days, IQR 23-49), patients host of elderly nursing homes (37 days, IQR 25-51). In the GEE multivariable model, the variables associated to the non negativization at all times intervals were: older age (at 15th day: class 65+, OR 2.56, 95%CI 2.39-2.74), female gender (at 15th day: OR 1.12, 95%CI 1.06-1.18), and to be hospitalized for COVID-19 (at 15th day: OR 1.38, 95%CI 1.29-1.48). The presence of comorbidities and of symptoms were associate with the non negativization at 15th day (respectively, class 4+: OR 1.29, 95%CI 1.08-1.56 and symptoms: OR 1.20, 95%CI 1.13-1.27), but not at 45th day. older age, female gender, presence of comorbidities and severity of disease (proxy hospitalization for COVID-19) were risk factors for non negativization at all times intervals. The presence of symptoms was a risk factors for the non negativization after 2 weeks from the first diagnosis and not at 45th day. Using a longitudinal model for the analysis of the dataset, it is possible to compare the weight of the variables included in the model at different times and correct an overestimation of the attributable risk after the first considered time interval.

Integrating Clinical and Polygenic Factors to Predict Breast Cancer Risk in Women Undergoing Genetic Testing.

PURPOSEScreening and prevention decisions for women at increased risk of developing breast cancer depend on genetic and clinical factors to estimate risk and select appropriate interventions. Integration of polygenic risk into clinical breast cancer risk estimators can improve discrimination. However, correlated genetic effects must be incorporated carefully to avoid overestimation of risk.MATERIALS AND METHODSA novel Fixed-Stratified method was developed that accounts for confounding when adding a new factor to an established risk model. A combined risk score (CRS) of an 86–single-nucleotide polymorphism polygenic risk score and the Tyrer-Cuzick v7.02 clinical risk estimator was generated with attenuation for confounding by family history. Calibration and discriminatory accuracy of the CRS were evaluated in two independent validation cohorts of women of European ancestry (N = 1,615 and N = 518). Discrimination for remaining lifetime risk was examined by age-adjusted logistic regression. Risk stratification with a 20% risk threshold was compared between CRS and Tyrer-Cuzick in an independent clinical cohort (N = 32,576).RESULTSSimulation studies confirmed that the Fixed-Stratified method produced accurate risk estimation across patients with different family history. In both validation studies, CRS and Tyrer-Cuzick were significantly associated with breast cancer. In an analysis with both CRS and Tyrer-Cuzick as predictors of breast cancer, CRS added significant discrimination independent of that captured by Tyrer-Cuzick (P < 10−11 in validation 1; P < 10−7 in validation 2). In an independent cohort, 18% of women shifted breast cancer risk categories from their Tyrer-Cuzick–based risk compared with risk estimates by CRS.CONCLUSIONIntegrating clinical and polygenic factors into a risk model offers more effective risk stratification and supports a personalized genomic approach to breast cancer screening and prevention.

Bridging gaps in demographic analysis with phylogenetic imputation.

Phylogenetically informed imputation methods have rarely been applied to estimate missing values in demographic data but may be a powerful tool for reconstructing vital rates of survival, maturation, and fecundity for species of conservation concern. Imputed vital rates could be used to parameterize demographic models to explore how populations respond when vital rates are perturbed. We used standardized vital rate estimates for 50 bird species to assess the use of phylogenetic imputation to fill gaps in demographic data. We calculated imputation accuracy for vital rates of focal species excluded from the data set either singly or in combination and with and without phylogeny, body mass, and life-history trait data. We used imputed vital rates to calculate demographic metrics, including generation time, to validate the use of imputation in demographic analyses. Covariance among vital rates and other trait data provided a strong basis to guide imputation of missing vital rates in birds, even in the absence of phylogenetic information. Mean NRMSE for null and phylogenetic models differed by <0.01 except when no vital rates were available or for vital rates with high phylogenetic signal (Pagel's λ > 0.8). In these cases, including body mass and life-history trait data compensated for lack of phylogenetic information: mean normalized root mean square error (NRMSE) for null and phylogenetic models differed by <0.01 for adult survival and <0.04 for maturation rate. Estimates of demographic metrics were sensitive to the accuracy of imputed vital rates. For example, mean error in generation time doubled in response to inaccurate estimates of maturation time. Accurate demographic data and metrics, such as generation time, are needed to inform conservation planning processes, for example through International Union for Conservation of Nature Red List assessments and population viability analysis. Imputed vital rates could be useful in this context but, as for any estimated model parameters, awareness of the sensitivities of demographic model outputs to the imputed vital rates is essential.

Prediction of perioperative mortality in cardiac surgery – Risk scoring systems: In quest of the holy grail

Prediction of perioperative mortality in cardiac surgery – Risk scoring systems: In quest of the holy grail

CHARGE-AF in a national routine primary care electronic health records database in the Netherlands: validation for 5-year risk of atrial fibrillation and implications for patient selection in atrial fibrillation screening

AimsTo validate a multivariable risk prediction model (Cohorts for Heart and Aging Research in Genomic Epidemiology model for atrial fibrillation (CHARGE-AF)) for 5-year risk of atrial fibrillation (AF) in routinely...