Association of estimated cardiorespiratory fitness in middle-aged and elderly people with cardiovascular disease: Evidence from the China health and retirement longitudinal study.

BACKGROUND AND AIM: Cardiovascular diseases (CVD) is a major threat to public health, while cardiorespiratory fitness (CRF) is a key predictor of chronic disease. Given this, the purpose of this study was to investigate the relationship between estimated CRF (eCRF) and CVD in middle-aged and elderly Chinese people. METHODS AND RESULTS: The China Health and Retirement Longitudinal Study (CHARLS) with 4761 individuals were included in analysis. Participants were divided into three groups according to eCRF quantile in sex subgroups. Cox proportional hazards regression models were used to explore the correlation of eCRF with CVD (stroke or cardiac events). In total, 4761 participants were included in this cohort study (2500 [52.51%] women). During a 7-year follow-up from 2011 to 2018, 796 CVDs (268 Strokes and 588 cardiac events) were recorded. In multivariable-adjusted analyses, for per 1 SD increase of eCRF, the age-adjusted risk of CVD was reduced by about 18% (HR = 0.82; 95% CI, 0.72-0.93) in men, and was reduced by about 29% (HR = 0.71; 95% CI, 0.62-0.81) in women. Similar associations were also found between eCRF and stroke and cardiac events. Both subgroup and interaction analyses showed that the interaction of age had a statistically significant effect on CVD risk. CONCLUSION: ECRF was inversely associated with CVD risk (stroke or cardiac events) in both men and women. Remarkable sex and age differences exist in the effectiveness of increasing eCRF to reduce the risk of CVD. As a potential, efficient and cost-effective risk prediction tool, eCRF deserves further attention and wide application.

Therapeutic plasma exchange for life-threatening pediatric disorders.

INTRODUCTION: Therapeutic plasma exchange (TPE) is acknowledged to be an effective treatment in life-threatening pediatric disorders. Apheresis for pediatric diseases has been poorly investigated, and most studies to date featured small numbers of patients and lacked control groups. The objective of the present study was to evaluate the tolerance of TPE in pediatric patients. MATERIALS AND METHODS: A retrospective cohort study via a web-based electronic case report form including pediatric patients referred for TPE between January 2005 and December 2014. RESULTS: A total of 78 patients (median [range] age: 9.8 [0.53-17.93]) and 731 TPE procedures were analyzed. The indications were antibody-mediated rejection (n = 33; 42%) and desensitization therapy (n = 5; 6%) after solid organ or hematopoietic stem cell transplantation, thrombotic microangiopathy (n = 17; 22%), pediatric inflammatory diseases (n = 16; 21%), kidney diseases (n = 6; 8%), and hyperviscosity syndrome (n = 1; 1%). On average, each patient underwent six procedures during the first session [range: 1-19]. In the 2 weeks following the start of a session, 72 patients (92%) presented a total of 311 adverse events (AEs) potentially related to TPE. The risk of AEs was not related to the indication for TPE, the intensity of care, venous access, plasma substitute use, or body weight. None of the deaths was related to the TPE. CONCLUSION: We studied one of the largest retrospective pediatric cohorts described to date. Our experience of TPE children's TPE feasibility concerned specific, life-threatening conditions and otherwise treatment-refractory diseases.

Toolbox for Research, or how to facilitate a central data management in small-scale research projects.

BACKGROUND: In most research projects budget, staff and IT infrastructures are limiting resources. Especially for small-scale registries and cohort studies professional IT support and commercial electronic data capture systems are too expensive. Consequently, these projects use simple local approaches (e.g. Excel) for data capture instead of a central data management including web-based data capture and proper research databases. This leads to manual processes to merge, analyze and, if possible, pseudonymize research data of different study sites. RESULTS: To support multi-site data capture, storage and analyses in small-scall research projects, corresponding requirements were analyzed within the MOSAIC project. Based on the identified requirements, the Toolbox for Research was developed as a flexible software solution for various research scenarios. Additionally, the Toolbox facilitates data integration of research data as well as metadata by performing necessary procedures automatically. Also, Toolbox modules allow the integration of device data. Moreover, separation of personally identifiable information and medical data by using only pseudonyms for storing medical data ensures the compliance to data protection regulations. This pseudonymized data can then be exported in SPSS format in order to enable scientists to prepare reports and analyses. CONCLUSIONS: The Toolbox for Research was successfully piloted in the German Burn Registry in 2016 facilitating the documentation of 4350 burn cases at 54 study sites. The Toolbox for Research can be downloaded free of charge from the project website and automatically installed due to the use of Docker technology.

An information and communication technology-based centralized clinical trial to determine the efficacy and safety of insulin dose adjustment education based on a smartphone personal health record application: a randomized controlled trial.

BACKGROUND: A Personal Health Record (PHR) is an online application that allows patients to access, manage, and share their health data. PHRs not only enhance shared decision making with healthcare providers, but also enable remote monitoring and at-home-collection of detailed data. The benefits of PHRs can be maximized in insulin dose adjustment for patients starting or intensifying insulin regimens, as frequent self-monitoring of glucose, self-adjustment of insulin dose, and precise at-home data collection during the visit-to-visit period are important for glycemic control. The aim of this study is to examine the efficacy and safety of insulin dose adjustment based on a smartphone PHR application in patients with diabetes mellitus (DM) and to confirm the validity and stability of an information and communication technology (ICT)-based centralized clinical trial monitoring system. METHODS: This is a 24-week, open-label, randomized, multi-center trial. There are three follow-up measures: baseline, post-intervention at week 12, and at week 24. Subjects diagnosed with type 1 DM, type 2 DM, and/or post-transplant DM who initiate basal insulin or intensify their insulin regimen to a basal-bolus regimen are included. After education on insulin dose titration and prevention for hypoglycemia and a 1-week acclimation period, subjects are randomized in a 1:1 ratio to either an ICT-based intervention group or a conventional intervention group. Subjects in the conventional intervention group will save and send their health information to the server via a PHR application, whereas those in ICT-based intervention group will receive additional algorithm-based feedback messages. The health information includes level of blood glucose, insulin dose, details on hypoglycemia, food diary, and step count. The primary outcome will be the proportion of patients who reach an optimal insulin dose within 12 weeks of study enrollment, without severe hypoglycemia or unscheduled clinic visits. DISCUSSION: This clinical trial will reveal whether insulin dose adjustment based on a smartphone PHR application can facilitate the optimization of insulin doses in patients with DM. In addition, the process evaluation will provide information about the validity and stability of the ICT-based centralized clinical trial monitoring system in this research field. TRIAL REGISTRATION: Clinicaltrials.gov NCT 03112343 . Registered on 12 April 2017.

Estimated Cardiorespiratory Fitness and Metabolic Risks.

This review focuses on the emerging evidence for the association between non-exercise fitness testing, estimated cardiorespiratory fitness (eCRF), and metabolic risk factors. Given the challenges associated with directly measuring cardiorespiratory fitness (CRF) in large populations, eCRF presents a practical alternative for predicting metabolic health risks. A literature search identified seven relevant cohort studies from 2020 to 2024 that investigated the association of eCRF with hypertension, hyperglycemia, dyslipidemia, and obesity. This review consistently demonstrates an inverse relationship between higher eCRF and a lower incidence of metabolic risks, which is in line with CRF cohort studies. It highlights the importance of low eCRF as a primordial indicator for metabolic risks and underscores the potential for broader application. Future research directions should include exploring eCRF's predictive ability across diverse populations and health outcomes and testing its real-world applicability in healthcare and public health settings.

Protocol of Validation Mechanisms Within the Design of an Electronic Case Report Form for the MULTI-SITA Project.

With the wide diffusion of web technology, dedicated electronic Case Report Forms (eCRFs) became the main tool for collecting patient data. The focus of this work is to thoroughly consider the data quality in every aspect of the design of the eCRF, with the result of having multiple steps of validation that should produce a diligent and multidisciplinary approach towards every step of data acquisition. This goal affects every aspect of the system design.

Migrating a Well-Established Longitudinal Cohort Database From Oracle SQL to Research Electronic Data Entry (REDCap): Data Management Research and Design Study.

BACKGROUND: Providing user-friendly electronic data collection tools for large multicenter studies is key for obtaining high-quality research data. Research Electronic Data Capture (REDCap) is a software solution developed for setting up research databases with integrated graphical user interfaces for electronic data entry. The Swiss Mother and Child HIV Cohort Study (MoCHiV) is a longitudinal cohort study with around 2 million data entries dating back to the early 1980s. Until 2022, data collection in MoCHiV was paper-based. OBJECTIVE: The objective of this study was to provide a user-friendly graphical interface for electronic data entry for physicians and study nurses reporting MoCHiV data. METHODS: MoCHiV collects information on obstetric events among women living with HIV and children born to mothers living with HIV. Until 2022, MoCHiV data were stored in an Oracle SQL relational database. In this project, R and REDCap were used to develop an electronic data entry platform for MoCHiV with migration of already collected data. RESULTS: The key steps for providing an electronic data entry option for MoCHiV were (1) design, (2) data cleaning and formatting, (3) migration and compliance, and (4) add-on features. In the first step, the database structure was defined in REDCap, including the specification of primary and foreign keys, definition of study variables, and the hierarchy of questions (termed "branching logic"). In the second step, data stored in Oracle were cleaned and formatted to adhere to the defined database structure. Systematic data checks ensured compliance to all branching logic and levels of categorical variables. REDCap-specific variables and numbering of repeated events for enabling a relational data structure in REDCap were generated using R. In the third step, data were imported to REDCap and then systematically compared to the original data. In the last step, add-on features, such as data access groups, redirections, and summary reports, were integrated to facilitate data entry in the multicenter MoCHiV study. CONCLUSIONS: By combining different software tools-Oracle SQL, R, and REDCap-and building a systematic pipeline for data cleaning, formatting, and comparing, we were able to migrate a multicenter longitudinal cohort study from Oracle SQL to REDCap. REDCap offers a flexible way for developing customized study designs, even in the case of longitudinal studies with different study arms (ie, obstetric events, women, and mother-child pairs). However, REDCap does not offer built-in tools for preprocessing large data sets before data import. Additional software is needed (eg, R) for data formatting and cleaning to achieve the predefined REDCap data structure.

A Wide Database for a Multicenter Study on Pneumocystis jirovecii Pneumonia in Intensive Care Units.

Pneumocystis jirovecii pneumonia (PJP) is an opportunistic fungal infection that may affect patients with immunosuppression. In order to improve the diagnosis accuracy for PJP, facilitating the collection of data across Europe to reliably assess the performance of diagnostic tests for PJP is essential to improve the care of critically ill patients developing this severe condition. Such large data can be collected thanks to the contribution of several European hospitals in the compilation of a dedicated electronic Case Report Form (eCRF). The main focus of this work is to create an interface with high ergonomics both in the compilation and in the subsequent validation of the records.

Microservices-Based Architecture to Support the Adaptive RECORDS-Trial.

Information systems used by platform trials should handle changes that are not predefined. Unfortunately, the technical architecture of most existing clinical data management systems (CDMS) do not support changes to be incorporated into an ongoing trial. Adaptive clinical trials need advanced architectural solutions setup to enable biomarker stratification and enrichment strategy necessary for the adaptive clinical trial operation. This short paper presents the microservices-based architecture solution that is used to run and support the adaptive RECORDS-Trial.

Data of real-world reference scores for EORTC QLQ-C30 and QLQ-BR23 at baseline in women with early breast cancer and other breast diseases.

Patient-reported outcomes are information about health status and health-related quality of life collected directly from patients. The data in this publication contain the first assessment of patient-reported outcomes (PROs) from real-life measurements in the breast cancer center at Charité - Universitätsmedizin Berlin between November 2016 and March 2021. At baseline (before the start of treatment), 1727 ambulatory patients with early breast cancer, ductal carcinoma in situ (DCIS), fibroadenoma, and other breast diseases were registered in the digital PRO-system as part of clinical routine. Patients' sociodemographic data, medical history, clinical variables, and raw scores of the EORTC QLQ-C30 and EORTC QLQ-BR23 are provided in this publication. This dataset can be used as a reference for PROs in a clinical care setting or in clinical studies with breast diseases and contribute to the discussion about the interpretation of score values. Furthermore, the association between patients' sociodemographic data, clinical variables, and PRO data at baseline can be analysed further.

Association Between Change in Nonexercise Estimated Cardiorespiratory Fitness and Mortality in Men.

Objective: To examine the association between change in nonexercise estimated cardiorespiratory fitness (eCRF) and mortality risk in adult men. Patients and Methods: A total of 10,445 men (mean age, 44.6±9.3 years) from the Aerobics Center Longitudinal Study underwent 2 comprehensive medical examinations and peak work rate tests between January 1, 1979, and December 31, 2002, with an average time between measures of 5.7±4.9 years. Participants were observed for 11.6±6.4 years after their second examination until death or December 31, 2003. The eCRF was calculated with the Jackson et al (2012) and Nes et al (2011) published nonexercise estimation equations. Cox proportional hazards models were performed to examine the association between change in eCRF and all-cause and cardiovascular disease (CVD) mortality. Results: There were 601 deaths (192 CVD deaths) during the follow-up period. For both eCRF equations, a higher eCRF at baseline was associated with significant reductions in mortality risk from all causes and CVD (P<.001). Change in eCRF by the Jackson equation remained significantly associated with all-cause mortality (P<.001) and CVD mortality (P=.02) after multivariable adjustment. Every 1 metabolic equivalent (3.5 mL·kg-1·min-1) increase in eCRF was associated with a 21% and 22% reduction in mortality risk from all causes or CVD, respectively. No significant associations were observed between change in eCRF by the Nes equation and all-cause (P=.69) or CVD (P=.85) mortality risk after multivariable adjustment. Conclusion: The association between change in nonexercise eCRF and mortality risk may be equation dependent.

Using passive extraction of real-world data from eConsent, electronic patient reported outcomes (ePRO) and electronic health record (EHR) data loaded to an electronic data capture (EDC) system for a multi-center, prospective, observational study in diabetic patients.

As clinical trial complexity has increased over the past decade, using electronic methods to simplify recruitment and data management have been investigated. In this study, the Optum Digital Research Network (DRN) has demonstrated the use of electronic source (eSource) data to ease subject identification, recruitment burden, and used data extracted from electronic health records (EHR) to load to an electronic data capture (EDC) system. This study utilized electronic Informed Consent, electronic patient reported outcomes (SF-12) and included three sites using 3 different EHR systems. Patients with type 2 diabetes with an HbA1c ≥ 7.0% treated with metformin monotherapy were recruited. Endpoints consisted of changes in HbA1c, medications, and quality of life measures over 12-weeks of study participation using data from the subjects' eSources listed above. The study began in June of 2020 and the last patient last visit occurred in January of 2021. Forty-eight participants were consented and enrolled. HbA1c was repeated for 33 and ePRO was obtained from all subjects at baseline and 28 at 12-week follow-up. Using eSource data eliminated transcription errors. Medication changes, healthcare encounters and lab results were identified when they occurred in standard clinical practice from the EHR systems. Minimal data transformation and normalization was required. Data for this observational trial where clinical outcomes are available using lab results, diagnoses, and encounters may be achieved via direct access to eSources. This methodology was successful and could be expanded for larger trials and will significantly reduce staff effort and exemplified clinical research as a care option.

The iCRF Generator: Generating interoperable electronic case report forms using online codebooks.

Semantic interoperability of clinical data is essential to preserve its meaning and intent when the data is exchanged, re-used or integrated with other data. Achieving semantic operability requires the use of a communication standard, such as HL7, as well as (functional) information standards. Manually mapping clinical data to a medical thesaurus, such as SNOMED CT, is complicated and requires expert knowledge of both the dataset, including its context, and the thesaurus. As an alternative, the (re-)use of codebooks, data definitions which may already have been mapped to a thesaurus, can be a viable approach. We've developed the iCRF Generator, a Java program that can generate the core of an interoperable electronic case report form (iCRF) for several of the major electronic data capture systems (EDCs). To build their CRFs, users can select one or more items from established codebooks, available from an online system called ART-DECOR. By providing an easy to use method to create CRFs for multiple EDCs based on the same codebooks, interoperability can be more easily attained.

Developing a lung nodule management protocol specifically for cardiac CT: Methodology in the DISCHARGE trial.

PURPOSE: In this methodology paper we describe the development of a lung nodule management algorithm specifically for patients undergoing cardiac CT. METHODS: We modified the Lung-RADS algorithm specifically to manage lung nodules incidentally detected on cardiac CT (Lung-RADS for cardiac CT). We will evaluate the modified algorithm as part of the DISCHARGE trial (www.dischargetrial.eu) in which patients with suspected coronary artery disease are randomly assigned to cardiac CT or invasive coronary angiography across Europe at 16 sites involving 3546 patients. Patients will be followed for up to four years. RESULTS: The major adjustments to Lung-RADS specifically for cardiac CT relate to 1) incomplete coverage of the lungs by cardiac CT compared with chest CT, and when to order a completion chest CT versus a follow up chest CT, 2) cardiac CT findings will not trigger annual lung-cancer screening, and 3) a lower threshold of at least 10 mm for classifying new ground glass nodules as probably benign (category 3). CONCLUSIONS: The DISCHARGE trial will assess a lung nodule management algorithm designed specifically for cardiac CT in patients with stable chest pain across Europe.

LOGIS (LOcalization of Ground-glass-opacity and pulmonary lesions for mInimal Surgery) registry: Design and Rationale.

BACKGROUND AND PURPOSE: An optimal pulmonary localization technique for video-assisted thoracic surgery (VATS) of small lung nodules has not yet been established. The LOcalization of Ground-glass-opacity and pulmonary lesions for mInimal Surgery (LOGIS) registry aims to establish a multicenter database and investigate the usefulness and safety of localization techniques for small pulmonary lesions in individuals undergoing VATS. METHODS/DESIGN: The LOGIS registry is a large-scale, multicenter cohort study, aiming to enroll 825 patients at 10 institutions. Based on the inclusion and exclusion criteria, all study participants with pulmonary lesions indicated for VATS will be screened and enrolled at each site. All study participants will undergo preoperative lesion localization by the hook-wire or lipiodol localization methods according to site-specific methods. Within a few hours of marking, thoracoscopic surgery will be done under general anesthesia by experienced thoracoscopic surgeons. The primary endpoints are the success and complication rates of the two localization techniques. Secondary endpoints include procedure duration, recurrence rate, and all-cause mortality. Study participant enrollment will be completed within 2 years. Procedure success rates and incidence of complications will be analyzed based on computed tomography findings. Procedure duration, recurrence rate, and all-cause mortality will be compared between the two techniques. The study will require 5 years for completion, including 6 months of preparation, 3.5 years for recruitment, and 1 year of follow-up endpoint assessment. DISCUSSION: The LOGIS registry, once complete, will provide objective comparative results regarding the usefulness and safety of the lipiodol and hook-wire localization techniques.

Data Collection of Medication - Impact of Autocompletion in eCRFs on Efficiency and Data Quality.

OBJECTIVE: Openclinica Input Completion (OIC) was developed to increase the efficiency to enter drugs in eCRF in OpenClinica®. The aim of the study was to evaluate the impact on efficiency and data quality as well as usability. METHODS: 20 participants were asked to input 15 drugs with the new tool and by hand. RESULTS: The mean input time got decreased from 16:12m to 3:59m. 31 of 300 (10%) of manual entered medication data sets had one or more errors versus 10 of 300 (3,3%) data sets entered with OIC. CONCLUSION: OIC was able to increase efficiency and data quality. We conclude that new additions to the graphical user interface in electronical Case-Report-Form (eCRF) systems should be validated before usage in research projects.

Series: Pragmatic trials and real world evidence: Paper 8. Data collection and management.

Pragmatic trials can improve our understanding of how treatments will perform in routine practice. In a series of eight papers, the GetReal Consortium has evaluated the challenges in designing and conducting pragmatic trials and their specific methodological, operational, regulatory, and ethical implications. The present final paper of the series discusses the operational and methodological challenges of data collection in pragmatic trials. A more pragmatic data collection needs to balance the delivery of highly accurate and complete data with minimizing the level of interference that data entry and verification induce with clinical practice. Furthermore, it should allow for the involvement of a representative sample of practices, physicians, and patients who prescribe/receive treatment in routine care. This paper discusses challenges that are related to the different methods of data collection and presents potential solutions where possible. No one-size-fits-all recommendation can be given for the collection of data in pragmatic trials, although in general the application of existing routinely used data-collection systems and processes seems to best suit the pragmatic approach. However, data access and privacy, the time points of data collection, the level of detail in the data, and the lack of a clear understanding of the data-collection process were identified as main challenges for the usage of routinely collected data in pragmatic trials. A first step should be to determine to what extent existing health care databases provide the necessary study data and can accommodate data collection and management. When more elaborate or detailed data collection or more structured follow-up is required, data collection in a pragmatic trial will have to be tailor-made, often using a hybrid approach using a dedicated electronic case report form (eCRF). In this case, the eCRF should be kept as simple as possible to reduce the burden for practitioners and minimize influence on routine clinical practice.

Case Study: Converting Paper-based Case Report Forms to an Electronic Format (e-CRF) with ACASI Self-Report Integration.

This paper will discuss the integration of electronic Case Report Forms (e-CRFs) into an already existing Android-based Audio Computer-Assisted Self-Interview (ACASI) software solution that was developed for a public health project in Kampala, Uganda, the technical outcome results, and lessons learned that may be useful to other projects requiring or considering such a technology solution. The developed product can function without a connection to the Internet and allows for synchronizing collected data once connectivity is possible. Previously, only paper-based CRFs were utilized at the Uganda project site. A subset or select group of CRFs were targeted for integration with ACASI in order to test feasibility and success. Survey volume, error rate, and acceptance of the system, as well as the operational and technical design of the solution, will be discussed.

Addition of estimated cardiorespiratory fitness to the clinical assessment of 10-year coronary heart disease risk in asymptomatic men.

The Framingham Risk Score (FRS) was developed to quantify a patient's coronary heart disease (CHD) risk. Non-exercise estimated CRF (e-CRF) may provide a clinically practical method for describing cardiorespiratory fitness. We computed e-CRF and tested its association with the FRS and CHD. Male participants (n = 29,854) in the Aerobics Center Longitudinal Study (ACLS) who completed a baseline examination between 1979-2002 were followed for 12 years to determine incident CHD defined by self-report of myocardial infarction, revascularization, or CHD mortality. e-CRF was defined from a 7-item scale and categorized using age-specific tertiles. Multivariable survival analysis determined associations between FRS, e-CRF, and CHD. Interaction between e-CRF and FRS was tested by stratified analysis by 'low' and 'moderate or high' 10-year CHD risk. Men with high e-CRF were significantly (p-value < 0.0001) younger, and less likely to be smokers, compared to men with low e-CRF. Multivariable survival analysis reported men with high e-CRF were 29% (HR = 0.71; 95% 0.56, 0.88) less likely to experience a CHD event compared to men with low e-CRF. Stratified analyses showed men with 'low' 10-year FRS predicted CHD risk and high e-CRF had a 28% (HR = 0.72; 95% CI 0.57, 0.91) lower CHD-mortality risk compared to men with low e-CRF, no association was found in this group and men with moderate e-CRF. Men who were more fit had a decreased risk for CHD compared to men in the lowest third of fitness. Estimated CRF may add clinical value to the FRS and help clinicians better predict long-term CHD risk.

Nonexercise Estimated Cardiorespiratory Fitness and Mortality Due to All Causes and Cardiovascular Disease: The NHANES III Study.

OBJECTIVE: To investigate associations of estimated cardiorespiratory fitness (eCRF) and all-cause and cardiovascular disease (CVD) mortality in a representative US population. PARTICIPANTS AND METHODS: A total of 12,834 participants, aged 20 to 86 years at baseline, were included in the Third National Health and Nutrition Examination Survey. They were followed up from October 18, 1988, through December 31, 2011, for all-cause and CVD death. Cardiorespiratory fitness was estimated from a nonexercise algorithm and further grouped into tertiles. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% CIs. RESULTS: A total of 3439 deaths (999 due to CVD) occurred during median follow-up of 19.2 years. After adjusting for race/ethnicity, education, age, hypertension, diabetes, hypercholesterolemia, baseline CVD, and cancer status, each metabolic equivalent increase of eCRF was associated with an 18% (range, 15%-21%) lower risk of all-cause mortality and a 19% (range, 15%-24%) lower risk of CVD mortality in men and a 24% (range, 20%-28%) lower risk of all-cause mortality and a 24% (18%-30%) lower risk of CVD mortality in women. Compared with the lower eCRF group, the HRs (95% CIs) of the middle and upper groups were 0.72 (0.61-0.85) and 0.56 (0.47-0.67) for all-cause mortality and 0.76 (0.57-1.01) and 0.48 (0.34-0.66) for CVD mortality in men; and 0.80 (0.66-0.97) and 0.49 (0.40-0.60) for all-cause mortality and 0.84 (0.60-1.17) and 0.46 (0.33-0.66) for CVD mortality in women (trend P<.001 for all). CONCLUSION: High eCRF was associated with lower risk of all-cause and CVD mortality in a national representative population. The eCRF method has great potential for initial clinical risk stratification and mortality prediction.