Development Of Risk Scores Research Articles

Machine Learning Model of Clinical Risk Factors and Peripheral Calcium Scoring on Computed Tomography for the Prediction of Amputation in Patients with Peripheral Arterial Disease

To date, there is no quantifiable evidence of the preferred measure of peripheral arterial disease (PAD) to best predict outcomes. Lower extremity calcium scoring is a novel tool that helps risk stratify patients with PAD. This study uses a machine learning (ML)-based approach to develop risk scores based on clinical variables and peripheral calcium scoring in an attempt to predict risk of major amputation in patients with PAD.

Landscape of Metabolic Fingerprinting for Diagnosis and Risk Stratification of Sepsis.

BackgroundSepsis and septic shock, a subset of sepsis with higher risk stratification, are hallmarked by high mortality rates and necessitated early and accurate biomarkers.MethodsUntargeted metabolomic analysis was performed to compare the metabolic features between the sepsis and control systemic inflammatory response syndrome (SIRS) groups in discovery cohort, and potential metabolic biomarkers were selected and quantified using multiple reaction monitoring based target metabolite detection method.ResultsDifferentially expressed metabolites including 46 metabolites in positive electrospray ionization (ESI) ion mode, 22 metabolites in negative ESI ion mode, and 4 metabolites with dual mode between sepsis and SIRS were identified and revealed. Metabolites 5-Oxoproline, L-Kynurenine and Leukotriene D4 were selected based on least absolute shrinkage and selection operator regularization logistic regression and differential expressed between sepsis and septic shock group in the training and test cohorts. Respective risk scores for sepsis and septic shock based on a 3-metabolite fingerprint classifier were established to distinguish sepsis from SIRS, septic shock from sepsis. Significant relationship between developed sepsis risk scores, septic shock risk scores and Sequential (sepsis-related) Organ Failure Assessment (SOFA), procalcitonin (PCT) and lactic acid were observed.ConclusionsCollectively, our findings demonstrated that the characteristics of plasma metabolites not only manifest phenotypic variation in sepsis onset and risk stratification of sepsis but also enable individualized treatment and improve current therapeutic strategies.

Venous Thromboembolism Risk Score and Pregnancy.

Venous thromboembolism (VTE) is a major contributor to maternal morbidity and mortality worldwide. Pregnancy is associated with the development of a baseline hypercoagulable state. The two strongest risk factors for pregnancy-associated VTE are previous VTE and/or high risk thrombophilia. The others risk factors for VTE during pregnancy are well known such as maternal, pregnancy and delivery characteristics. Considering the variation in recommendation in guidelines and low-quality evidence on the prevention, diagnosis and treatment, practice differs between countries and clinical institutions. Some authors developed risk scores, enabling individualized estimation of thrombotic risk during pregnancy, and permitting implementation of a risk-adapted strategy for thromboprophylaxis during pregnancy and postpartum. This review describes the existing VTE risk scores during the antenatal and postnatal period. The important message beyond the score used is that all women should undergo VTE risk factor assessment. The use of a Computerized Clinical Decision Support System for VTE risk assessment should be explored in obstetrics.

Development and validation of a risk-score model for opioid overdose using a national claims database

Opioid overdose can be serious adverse effects of opioid analgesics. Thus, several strategies to mitigate risk and reduce the harm of opioid overdose have been developed. However, despite a marked increase in opioid analgesic consumption in Korea, there have been no tools predicting the risk of opioid overdose in the Korean population. Using the national claims database of the Korean population, we identified patients who were incidentally prescribed non-injectable opioid analgesic (NIOA) at least once from 2017 to 2018 (N = 1,752,380). Among them, 866 cases of opioid overdose occurred, and per case, four controls were selected. Patients were randomly allocated to the development (80%) and validation (20%) cohort. Thirteen predictive variables were selected via logistic regression modelling, and a risk-score was assigned for each predictor. Our model showed good performance with c-statistics of 0.84 in the validation cohort. The developed risk score model is the first tool to identify high-risk patients for opioid overdose in Korea. It is expected to be applicable in the clinical setting and useful as a national level surveillance tool due to the easily calculable and identifiable predictors available from the claims database.

A Risk Stratification Scheme for In-Hospital Cardiogenic Shock in Patients With Acute Myocardial Infarction.

ObjectiveCardiogenic shock (CS) is the leading cause of death in patients with acute myocardial infarction (AMI) despite advances in care. This study aims to derive and validate a risk score for in-hospital development of CS in patients with AMI.MethodsIn this study, we used the Improving Care for Cardiovascular Disease in China–Acute Coronary Syndrome (CCC–ACS) registry of 76,807 patients for model development and internal validation. These patients came from 158 tertiary hospitals and 82 secondary hospitals between 2014 and 2019, presenting AMI without CS upon admission. The eligible patients with AMI were randomly assigned to derivation (n = 53,790) and internal validation (n = 23,017) cohorts. Another cohort of 2,205 patients with AMI between 2014 and 2016 was used for external validation. Based on the identified predictors for in-hospital CS, a new point-based CS risk scheme, referred to as the CCC–ACS CS score, was developed and validated.ResultsA total of 866 (1.1%) and 39 (1.8%) patients subsequently developed in-hospital CS in the CCC–ACS project and external validation cohort, respectively. The CCC–ACS CS score consists of seven variables, including age, acute heart failure upon admission, systolic blood pressure upon admission, heart rate, initial serum creatine kinase-MB level, estimated glomerular filtration rate, and mechanical complications. The area under the curve for in-hospital development of CS was 0.73, 0.71, and 0.85 in the derivation, internal validation and external validation cohorts, respectively.ConclusionThis newly developed CCC–ACS CS score can quantify the risk of in-hospital CS for patients with AMI, which may help in clinical decision making.Clinical Trial Registrationwww.ClinicalTrials.gov, identifier: NCT02306616.

Toward Accurate Spatiotemporal COVID-19 Risk Scores Using High-Resolution Real-World Mobility Data

As countries look toward re-opening of economic activities amidst the ongoing COVID-19 pandemic, ensuring public health has been challenging. While contact tracing only aims to track past activities of infected users, one path to safe reopening is to develop reliable spatiotemporal risk scores to indicate the propensity of the disease. Existing works which aim at developing risk scores either rely on compartmental model-based reproduction numbers (which assume uniform population mixing) or develop coarse-grain spatial scores based on reproduction number (R0) and macro-level density-based mobility statistics. Instead, in this article, we develop a Hawkes process-based technique to assign relatively fine-grain spatial and temporal risk scores by leveraging high-resolution mobility data based on cell-phone originated location signals. While COVID-19 risk scores also depend on a number of factors specific to an individual, including demography and existing medical conditions, the primary mode of disease transmission is via physical proximity and contact. Therefore, we focus on developing risk scores based on location density and mobility behaviour. We demonstrate the efficacy of the developed risk scores via simulation based on real-world mobility data. Our results show that fine-grain spatiotemporal risk scores based on high-resolution mobility data can provide useful insights and facilitate safe re-opening.

Racism Is a Modifiable Risk Factor: Relationships Among Race, Ethnicity, and Colorectal Cancer Outcomes

Racism Is a Modifiable Risk Factor: Relationships Among Race, Ethnicity, and Colorectal Cancer Outcomes

Abstract 11963: A Digital Heart Failure Coach Intervention for Improving Education, Self-Management and Outcomes in Patients Admitted for Acute Decompensated Heart Failure: Barriers to Effective Implementation

Introduction: Heart Failure (HF) education is fundamental for improving outcomes. The use of mobile health (m-health) devices and Artificial Intelligence (AI) are becoming more broadly available. We designed an avatar style digital HF coach (HF-app) to improve HF knowledge and self-care management. Hypothesis: We hypothesized that an avatar style HF-app could improve outcomes by enhancing HF knowledge and improving quality of life and self-care behaviors in patients admitted for Acute Decompensated HF (ADHF). Methods: The Risk-HF trial recruited patients admitted for ADHF who were at high risk for hospital readmission and/or death (defined by a previously developed risk score, ETHELRED trial). Patients were randomized to usual care or intervention, in which the HF-app was a component of a multifactorial intervention aimed at reducing HF readmissions. Our HF-app was designed to engage daily with the patient by monitoring HF symptoms and delivering education over 52-days. Results: Over a period of 16 months (August 2019 up until December 2020), 36 of 74 high risk patients were randomized to the intervention arm and were offered education with our HF-app. Of these, 26/36 (72%) had restricted access to the HF-app ( unable to use a tablet device and/or unwilling to be taught how to use it, n=20; no internet access, n=4; died in hospital n= 2 ) and 10/36 (28%) were enrolled to use the HF-app [ gender male n=7; median age 71.5 years, p<0.01 (IQR: 57.50 - 78.50); mean years of education 11.6(±2.5), p<0.01 ]. Younger patients [ Odds Ratio (OR) 0.89 [95% Confidence Interval (CI): 0.82-0.97], p<0.01 ] and those with a higher education level [ OR 1.58 (1.09-2.28), p=0.03 ] were more likely to enroll. Of those enrolled, only two patients engaged and completed ≥70% of the program. Six of the remaining 8 patients who did not engage were readmitted. Conclusions: Our study provides a note of caution in studies using m-health devices and apps in critically ill and elderly patients with unstable HF. Future research should consider how to use such technology-based interventions with elderly patients as well as to target younger ADHF patients, which may provide stronger evidence of benefits in patient self-care and outcomes.

Non-Invasive Risk Prediction Based on Right Ventricular Function in Patients with Pulmonary Arterial Hypertension.

Background: Right ventricular dysfunction is a major determinant of outcome in pulmonary arterial hypertension (PAH). We aimed to identify echocardiographic right heart parameters associated with adverse outcome and to develop a non-invasive, echocardiography-based risk score for PAH patients. Methods and Results: In 254 PAH patients we analyzed functional status, laboratory results, and echocardiographic parameters. We included these parameters to estimate all-cause death or lung transplantation using Cox regression models. The analyses included a conventional model using guideline-recommended variables and an extended echocardiographic model. Based on the final model a 12-point risk score was derived, indicating the association with the primary outcome within five years. During a median follow-up time of 4.2 years 74 patients died or underwent lung transplantation. The conventional model resulted in a C-Index of 0.539, whereas the extended echocardiographic model improved the discrimination (C-index 0.639, p-value 0.017). Ultimately, the newly developed risk score included WHO functional class, 6-min walking distance, N-terminal brain natriuretic peptide concentrations, pericardial effusion, right atrial area, tricuspid annular plane systolic excursion, and fractional area change. Conclusion: Integrating right heart function assessed by echocardiography improves prediction of death or lung transplantation in PAH patients. Independent validation of this finding is warranted.

Risk scores for risk stratification in chronic coronary syndrome and their improvement by Gensini and SYNTAX scores

Abstract Introduction There is a substantial residual risk in patients with chronic coronary syndrome (CCS). Risk scores could be useful tools to allocate intensified secondary preventive medications to address this residual risk. Whether their predictive value can be improved by addition of angiographic scores of the extent of coronary artery disease (CAD) is unknown. Purpose To test and compare the predictive value of three externally developed risk scores for CAD and to investigate the effect of addition of SYNTAX and Gensini scores. Methods We tested the TIMI risk score for secondary prevention (TRS 2°P), a risk score derived from the INVEST study, and the ABC-CHD model (see references 1–3) in 1280 patients with CCS from a contemporary observational CAD cohort ongoing since 2015 with a median follow-up of 3.6 years. In a second step we added SYNTAX and Gensini scores to the models. The endpoints tested were cardiovascular death and major adverse cardiovascular events (MACE), consisting of cardiovascular death, myocardial infarction and ischemic stroke. Results All investigated scores yielded continuously increasing event rates for MACE and cardiovascular death with increasing score points obtained. As an example Figure 1 displays 3-year rates for cardiovascular death and MACE against the points obtained in the TRS 2°P, whilst also displaying the distribution of patients amongst the risk categories. The three scores showed modest predictive value for occurrence of cardiovascular death (c-indices 0.60, 0.64, 0.70 for TRS 2°P, INVEST score, ABC-CHD score, respectively). Addition of both SYNTAX and Gensini scores to the models yielded c-indices of 0.66, 0.69 and 0.70 respectively (Figure 2a). Similar predictive values were observed for the occurrence of MACE (c-indices 0.59, 0.60, 0.64 for TRS 2°P, INVEST score, ABC-CHD score, respectively) as well after addition of both SYNTAX and Gensini scores (c-indices 0.62, 0.63, 0.64, see Figure 2b). Conclusion (I) Currently available risk scores are modestly predictive for the occurence of cardiovascular events in patients with CCS. (II) Addition of Gensini and SYNTAX scores improves their predictive value particularly in weaker risk scores. Funding Acknowledgement Type of funding sources: None. Figure 1Figure 2a (left) and 2b (right)

Develop and Apply Electrocardiography-Based Risk Score to Identify Community-Based Elderly Individuals at High-Risk of Mortality.

With an aging world population, risk stratification of community-based, elderly population is required for primary prevention. This study proposes a combined score developed using electrocardiographic (ECG) parameters and determines its long-term prognostic value for predicting risk of cardiovascular mortality. A cohort-study, conducted from December 2008 to April 2019, enrolled 5,380 subjects in Taiwan, who were examined, using three-serial-12-lead ECGs, and their health/demographic information were recorded. To understand the predictive effects of ECG parameters on overall-survival, Cox hazard regression analysis were performed. The mean age at enrollment was 69.04 ± 8.14 years, and 47.4% were males. ECG abnormalities, LVH [hazard ratio (HR) = 1.39, 95% confidence intervals (CI) = (1.16–1.67), P = 0.0003], QTc [HR = 1.31, CI = (1.07–1.61), P = 0.007] and PR interval [HR = 1.40, CI = (1.01–1.95), P = 0.04], were significantly associated with primary outcome all-cause death. Furthermore, LVH [HR = 2.37, CI = (1.48–3.79), P = 0.0003] was significantly associated with cardiovascular death, while PR interval [HR = 2.63, CI = (1.24– 5.57), P = 0.01] with unexplained death. ECG abnormality (EA) score was defined based on the number of abnormal ECG parameters for each patient, which was used to divide all patients into sub-groups. Competing risk survival analysis using EA score were performed by using the Gray's test, which reported that high-risk EA groups showed significantly higher cumulative incidence for all three outcomes. Prognostic models using the EA score as predictor were developed and a 10-fold cross validation design was adopted to conduct calibration and discrimination analysis, to establish the efficacy of the proposed models. Overall, ECG model could successfully predict people, susceptible to all three death outcomes (P < 0.05), with high efficacy. Statistically significant (P < 0.001) improvement of the c-indices further demonstrated the robustness of the prediction model with ECG parameters, as opposed to a traditional model with no EA predictor. The EA score is highly associated with increased risk of mortality in elderly population and may be successfully used in clinical practice.

The determinants of very severe immune-related adverse events associated with immune checkpoint inhibitors: A prospective study of the French REISAMIC registry

BackgroundImmune-related adverse events (irAEs) remain generally unpredictable, and severe irAEs remain challenging to detect early and manage. Very severe (grade IV–V) irAEs have not been extensively characterised in prospective studies, and their predictive factors remain unknown. ObjectiveThe objective of the study was to describe and identify predictive factors of very severe (grade IV–V) irAEs. DesignThe French Registre des Effets Indésirables Sévères des Anticorps Monoclonaux Immunomodulateurs en Cancérologie (REISAMIC) registry has prospectively collected all clinically significant irAEs occurring in patients treated with immune checkpoint inhibitors at Gustave Roussy Institute since 2014. SettingThis was a single-centre prospective cohort study at the Gustave Roussy Institute cancer centre (Villejuif, France). ParticipantsThe participants were all adult patients with a solid or haematological cancer treated with an anti–programmed cell death 1 (PD-1) or an anti–programmed cell death-ligand 1 (PD-L1) and who presented a clinically significant irAE. Main outcomes and measuresThe main outcomes included the clinical and laboratory characteristics of patients with very severe irAEs, including tumour type, affected organs, time to irAE occurrence, blood cell count and serum biochemistry parameters. ResultsOf the 1187 patients prospectively followed in REISAMIC between December 2014 and January 2020, 380 (32.0%) had at least one irAE, and 34 (2.86%) presented with very severe irAEs (grades IV–V). Among the 380 patients with an irAE, the distribution of very severe irAEs (grades IV–V) was 8.95% and death (grade V) was 3.95%. Among the 34 patients with very severe irAEs, 33 were treated with monotherapy of PD-1 or PD-L1 inhibitors, and one patient was treated with a combination of PD-1 and cytotoxic T-lymphocyte–associated protein 4 inhibitors. The median time to occurrence was shorter for very severe irAEs (median [interquartile range]: 41 days [0–634] for grades IV–V; versus 91 days [0–1123] for grades I–III; p = 0.01680). On initiation of immunotherapy, the predictive factors for very severe irAEs were performance status ≥2, elevated neutrophil/lymphocyte ratio and treatment for lung cancer. ConclusionsVery severe (grade IV–V) immunological toxicities occurred earlier than mild severe toxicities. On initiation of immunotherapy, patients with poor performance status, elevated neutrophil/lymphocyte ratio and lung cancer are identified at risk of developing these very severe toxicities. These results could help to develop risk scores to identify patients at risk of developing severe toxicities.

Outcomes and Predictors of Mortality in a Belgian Population of Patients Admitted with Ruptured Abdominal Aortic Aneurysm and Treated by Open Repair in the Contemporary Era

Abdominal aortic aneurysm (AAA) rupture is a serious condition that results in extremely high mortality rates. Some improvements in outcome have been reported during the last 2 decades. The objective of the present study was to determine the overall and operative (by open repair) mortality related to ruptured AAA in the contemporary era and to identify preoperative, intraoperative, and early postoperative parameters associated with poor outcomes. We performed a retrospective review of all consecutive patients admitted to our single institution with a diagnosis of ruptured AAA between 2004 and 2013. A total of 103 parameters, including demographic characteristics, medical history, clinical and biological parameters, cardiovascular risk factors, emergency level, diagnostic modalities, time from symptoms to diagnosis and treatment, type of operative procedure and postoperative complications, were analyzed. The primary endpoint considered in this study was the cumulative incidence rate of mortality. The secondary endpoint was the identification, by logistic regression methods, of risk factors for overall mortality as well as for operative, and postoperative mortality. Within our study period, 104 patients were admitted for a ruptured AAA. The majority of patients (84.6%) were male, and the AAA was known in 34.6% of the patients. Rupture occurred for a maximal diameter lower than 55 mm in 25% of the female population, compared to 5.7% of the male population (P = 0.030). The proportions of admitted patients who died before (preoperative mortality), during (intraoperative mortality) or after (postoperative hospital mortality) surgery was 17.3%, 16.3%, and 18.3%, respectively, yielding a cumulative in-hospital mortality of 51.9%. In the multivariate analysis, age ≥ 80 (P = 0.001), myocardial ischemia on the admission ECG (P = 0.046), and management by the physician response unit (P = 0.002) were the only preoperative parameters associated with a higher risk of hospital mortality. Four risk factors were found to be associated with a higher risk of postoperative mortality in the multivariate analysis, and all patients presenting with 3 or more of these risk factors (n = 5) died. The overall mortality of ruptured AAA in a contemporary cohort of patients who underwent open repair remains high and does not seem to have decreased during recent decades. Ruptures occur at smaller diameters in women than in men, supporting a lower threshold for intervention in women with known AAA. We developed risk scores to predict the mortality of patients with rAAA at different times of their hospital course. The validity of these scores should be assessed in prospective clinical studies.

Liver transplantation for hepatocellular carcinoma: Improving eligibility without compromising outcomes

BackgroundIn the context of liver transplantation for hepatocellular carcinoma (HCC), traditional transplant criteria appear restrictive. The objective of the current study was to determine risk factors for recurrence and improve transplant eligibility in patients with HCC. Materials and methodsThis was a retrospective study of patients who underwent living donor liver transplant (LDLT) for HCC (n = 219). Largest tumor diameter, tumor number, AFP and neutrophil to lymphocyte ratio were assessed. Multivariate analysis was performed to develop risk scores. The new model was compared with seven previously published transplant criteria using receiver operator curves. ResultsLargest tumor size >3.7 cm [HR:2.6, P = 0.02], and AFP > 600 ng/ml [HR:4.7, P = 0.001] were independent predictors of recurrence. Patients with risk scores of 0, 1–3, 4–6 and 7–9 had recurrence rate of 5.9%, 12.5%, 25% and 58.4% respectively. When compared with Milan criteria, Metro ticket 2.0, AFP model and Samsung criteria; transplant eligibility increased by 31.5%, 22.9%, 8.7%, and 7% respectively. Recurrence rate with the current model was 16/199 (8%) (P < 0.0001) and was comparable with other transplant criteria (6.9–9.1%). On ROC analysis, only Milan criteria (AUC = 0.7, P = 0.001) and the current model (AUC = 0.66, P = 0.01) showed significance for recurrence. All patients with high risk scores within Milan criteria had recurred at 3 years (P = 0.03). ConclusionsLow AFP can be used to select patients for LDLT outside traditional criteria for HCC, with comparable recurrence rates.

Abstract 2602: Leveraging cell-free methylome markers for early cancer detection

Abstract Cancer survival rates are significantly improved when detected at early stages, particularly when the tumor is still localized to the tissue of origin. However, effective screening tools for early cancer detection is currently limited to a subset of cancer types. The early development of human malignancies are difficult to observe as cancers are often detected once it becomes symptomatic, as such many cancer biomarker and evolution studies to date have primarily examined the genomics from solid tumor or liquid biopsies following a diagnosis. Investigating early tumor evolution in the pre-diagnosis context could allow us to better understand how to prevent or detect cancers in the earliest stage when survival rates are significantly higher, however this requires application of new technologies to biologics collected prior to a cancer diagnosis. Here, we leverage blood samples collected from participants in the Canadian Partnership for Tomorrow Project (CPTP), a longitudinal population cohort, prior to the onset of a cancer. Specifically, we utilize hybrid capture approaches to enrich for and characterize early mutations and methylation changes in circulating tumor DNA (ctDNA) of pre-cancer plasma samples collected from patients several months to years prior to clinical diagnosis. Here, we identify the earliest detectability of aberrant genetic and epigenetic events in ctDNA and describe the molecular evolution of these events at various stages prior to clinical detection of cancers. Further, we develop molecular biomarkers and implement machine learning tools to classify individuals with early cancers, and to develop risk scores from survival analyses predictive of cancer development up to 5 years prior to diagnosis. In our current study, we focus specifically on breast, prostate, lung and pancreatic cancer cases, and are extending this to pan-cancer applications in subsequent studies. Citation Format: Nicholas Cheng, Kimberly Skead, David Soave, Jocelyn Meng, Elias Gbeha, Ilinca Lungu, Bernard Lam, Scott Bratman, Daniel De Carvalho, Philip Awadalla. Leveraging cell-free methylome markers for early cancer detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2602.

HIV testing criteria to reduce testing volume and increase positivity in Botswana.

We used data from a routine HIV testing program to develop risk scores to identify patients with undiagnosed HIV infection while reducing the number of total tests performed. Multivariate logistic regression. We included demographic factors from HIV testing data collected in 134 Botswana Ministry of Health & Wellness facilities during two periods (1 October 2018- 19 August 2019 and 1 December 2019 to 30 March 2020). In period 2, the program collected additional demographic and risk factors. We randomly split each period into prediction/validation datasets and used multivariate logistic regression to identify factors associated with positivity; factors with adjusted odds ratios at least 1.5 were included in the risk score with weights equal to their coefficient. We applied a range of risk score cutoffs to validation datasets to determine tests averted, test positivity, positives missed, and costs averted. In period 1, three factors were significantly associated with HIV positivity (coefficients range 0.44-0.87). In period 2, 12 such factors were identified (coefficients range 0.44-1.37). In period 1, application of risk score cutoff at least 1.0 would result in 50% fewer tests performed and capture 61% of positives. In period 2, a cutoff at least 1.0 would result in 13% fewer tests and capture 96% of positives; a cutoff at least 2.0 would result in 40% fewer tests and capture 83% of positives. Costs averted ranged from 12.1 to 52.3%. Botswana's testing program could decrease testing volume but may delay diagnosis of some positive patients. Whether this trade-off is worthwhile depends on operational considerations, impact of testing volume on program costs, and implications of delayed diagnoses.

Risk and protective factors for anxiety during COVID-19 pandemic

BackgroundCoronavirus Disease 2019 (COVID-19) is a global pandemic and an anxiety-provoking event. There are few studies to identify potential risk and protective factors related to anxiety during COVID-19 pandemic.MethodsWe collected information on demographic data and lifestyles by a web-based survey of 19,802 participants from 34 provinces in China during COVID-19 pandemic. Level of anxiety was evaluated using the Self-Rating Anxiety Scale. We used ordinal multivariable logistic regression to estimate the associations of anxiety level with potential risk and protective factors. We further developed a new score to simplify the assessment of anxiety during COVID-19 crisis.ResultsAmong 19,802 participants, we found that those who were front-line medical personnel, suffered from chronic disease, with present symptoms of SARS-CoV-2 infection or contact history had 112, 93, 40 and 15% increased risk of higher anxiety level; while those with knowledge about personal protective measures or wore masks had 75 and 29% lower risk of higher anxiety level respectively. We developed a risk score by calculating the sum of single score of 17 factors. Each one increase of the risk score was associated with a 297% increase in anxiety index score. In categorical analysis, low risk (the risk score between 1 to 2), the moderate risk group (the risk score of 3) and high risk group (the risk score ≥ 4) had − 0.40 (95% CI: − 1.55, 0.76), 1.44 (95% CI: 0.27, 2.61) and 9.18 (95% CI: 8.04, 10.33) increase in anxiety index score, and 26% (95% CI: − 7, 72%), 172% (95% CI: 100, 270%), and 733% (95% CI: 516, 1026%) higher risk of anxiety respectively, when compared with the very low risk group (the risk score of 0). The AUC was 0.73 (95% CI, 0.72, 0.74) for the model fitted the developed risk score, with the cut-off point of 3.5.ConclusionsThese findings revealed protective and risk factors associated with anxiety, and developed a simple method of identifying people who are at an increased risk of anxiety during COVID-19 pandemic.

Response and outcomes to immune checkpoint inhibitors (ICI) in advanced urothelial cancer (aUC) based on prior intravesical BCG.

4537 Background: Little is known regarding response and outcomes to ICI for patients (pts) with aUC who were previously treated with BCG for non-muscle invasive bladder cancer. We hypothesized that prior intravesical BCG would not be associated with changes in objective response or survival in pts with aUC treated with ICI. Methods: We performed a retrospective cohort study across 25 institutions. Demographic, intravesical BCG history, treatment and outcomes data were collected for pts with aUC who received ICI. Pts with aUC treated with ICIs were included, pts with pure non-UC, those treated with combination or on clinical trials, pts with multiple ICI treatment lines and those with upper tract UC were excluded. Pts were stratified to prior exposure versus no exposure to BCG. We compared overall response rate (ORR) using logistic regression; and progression-free survival (PFS) and overall survival (OS) using Kaplan-Meier and Cox proportional hazards. All analyses were performed in the overall population and further stratified by treatment line (first-line [1L] vs salvage [2+L]) and multivariable models. The stratified analysis was also adjusted for an internally developed risk score for 1L and Bellmunt risk score for 2+L; p&lt;0.05 was significant. Results: 1026 aUC pts treated with ICI were identified; 614 pts, 617 pts, and 641 pts were included in ORR, OS and PFS analyses, respectively. Overall, mean age at CPI initiation was 70, 76% were men, 70% were current or former smokers, 75% White, 29% with mixed histology, and 24% had prior exposure to BCG. ORR to ICI in pts with or without prior exposure to BCG was similar, 27% and 28% respectively (OR=0.93 [95% CI 0.61-1.42], p=0.73). Median OS (mOS) for pts with vs without prior BCG exposure was 9 vs 10 mo (HR=1.13 [95% CI 0.88-1.44], p=0.35). Median PFS (mPFS) was 4 months (mo) in both groups (HR=1.02 [95% CI 0.82-1.27], p=0.83). ORR, PFS and OS analyses stratified by ICI treatment line (1L vs 2+L) are listed in the table. Conclusions: In this multi-institutional retrospective analysis, prior intravesical BCG was not associated with objective response or survival in pts with aUC treated with ICI. Limitations of this study include retrospective nature, lack of randomization and possible confounding, but it does provide important preliminary data that selection for ICI treatment should not be impacted by prior exposure to BCG. Further clinical and molecular biomarker exploration is needed to refine patient selection for ICI in aUC.[Table: see text]

Risk score of contrast-induced nephropathy in patients after percutaneous coronary intervention

Background: Contrast-induced nephropathy (CIN) after percutaneous coronary intervention (PCI) is still an issue in modern revascularization era. Recent risk stratification model used creatinine as biomarker which has some limitations. Increased ≥ 10 % of Cystatin-C after PCI has proven to be one of the earliest and accurate CIN after PCI biomarkers. The study aims to develop risk score based on predictors of contrast-induced nephropathy in patients after PCI with Cystatin-C as biomarkerMethods: A prospective cohort study of 129 patients after PCI at Dr. Kariadi General Hospital Semarang. Predictor analysis was carried out using bivariate chi-square test and multivariate logistic regression. The independent predictors obtained were then used as risk score variables. The Hosmer and Lemeshow calibration test and AUC ROC analysis for discrimination test tested the quality of the risk score.Results: There were 3 independent predictors used as the risk score variables: Hypotension (score 1), anemia (score 1), creatinine baseline &gt;1.5 mg/dl (score 1). Patients with total score ≥1 have higher risk to have CIN after PCI. The risk score had a good quality with the Hosmer and Lemeshow calibration test &gt; 0.05 and relative modest discrimination ROC AUC 0.700 (95% IK 0.585-0.815; p=0.001).Conclusions: A risk score for risk stratification CIN after PCI has been created. The score has good calibration and modest discrimination in predicting the risk of CIN after PCI.

Development and Validation of a Nomogram for Lower Extremity Deep Venous Thrombosis in Patients after Acute Stroke

ObjectivesTo develope and validate a nomogram to predict the probability of deep venous thrombosis (DVT) in patients after acute stroke during the first 14 days with clinical features and easily obtainable biochemical parameters. MethodsThis is a single-center prospective cohort study. The potential predictive variables for DVT at baseline were collected, and the presence of DVT was evaluated using ultrasonography within the first 14 days. Data were randomly assigned to either a modeling data set or a validation data set. Univariable and Multivariate logistic regression analysis was used to develop risk scores to predict DVT in the modeling data set and the area under the receiver operating characteristic curve to validate the score in the test data set, and nomogram and calibration curve were constructed by R project. ResultsA total of 1651 patients with acute stroke were enrolled in the study. The overall incidence of DVT after acute stroke within two weeks was 14.4%. Multivariable analysis detected older age (≥65 years),female gender, hemorrhagic stroke, malignancy, lower limb muscle strength<3 grade, Albumin<40 g·L−1 and D-dimer>0.5 mg·L−1 were highly predictive of 14-day risk of DVT. The AUC of the nomogram with these above-mentioned independent risk factors to predict the 14-day risk of DVT was 0.756 (95% CI, 0.712-0.812) and 0.811 (95%CI, 0.762-0.859) for the modeling cohort and external validation cohort, respectively. Moreover, the calibration of the nomogram showed a nonsignificant Hosmer-Lemeshow test statistic in the modeling (P = 0.250) and validation sets (P = 0.995). With respect to decision curve analyses, the nomogram exhibited preferable net benefit gains than the staging system across a wide range of threshold probabilities. ConclusionThis nomogram had a good performance in predictive accuracy, discrimination capability, and clinical utility, which was helpful for clinicians to identify high-risk groups of DVT and formulate relevant prevention and treatment measures.