Research Electronic Data Capture (Redcap) for Building and Managing Databases for Population-Based Biomedical Studies

Atalyan, A. V.; Kolesnikova, L. I.; Колесников, С. И.; Grjibovski, Andrej M.; Suturina, Larisa

doi:10.33396/1728-0869-2019-2-52-59

Cited by 10 publications

(4 citation statements)

References 6 publications

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“…REDCap had a very clear advantage due to its extensive tutorials and online training materials [41,42]. The benefits of EDC include direct data entry at the Point of care leading to greater accuracy, fewer queries, declined paper record storage, and timelier population of the study database.…”

Section: Discussionmentioning

confidence: 99%

Using Electronic Data Capture for Cardiovascular Electrophysiology Invasive Procedures: An Important Step Towards Interoperable Clinical Registries

Shanbehzadeh

Kazemi-Arpanahi²,

Bostan

et al. 2020

Front Health Inform

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Introduction: The capture and integration of structured data from point of care into clinical registries has been a challenge. However, this effort is very important toward a qualitative patient care and research. Collection, organization and interpretation of clinical data can help to improve evidence-based medicine practices. Worksheets data capture are prevalent, but, not flexible, protected, workflow pleasant, and user friendly and do not support the creation of standardized and interoperable data. The aim of this study was to design and implement an Electronic Data Capture (EDC) instruments to be use in context of cardiovascular invasive procedures.Material and Methods: This descriptive and developmental study conducted in three phases as follows. (1) data standardization according national and international data element templates published by specialized societies; (2) developing of an initial data collection and clinical research workflow (3), establishing of electronic case reports using Research Electronic Data Capture (REDCap) in accordance with the Health Insurance Portability and Accountability Act (HIPAA) privacy rule.Results: Three case report forms was developed that included demographics, medical history, physical examination, laboratory tests, radiology examinations, Electrophysiology (EP) procedures, as well as medications and follow-up information. Data-entry validation criteria have been implementing in electronic data collection instrument to assure validity and precision when data enter in electronic form.Conclusion: This paper describes the process used to create an EDC application. Data collection applications were successfully develop as an a priori step in a clinical research for assisting data collection and management in a case of cardiovascular EP invasive procedures.

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Section: Discussionmentioning

confidence: 99%

Using Electronic Data Capture for Cardiovascular Electrophysiology Invasive Procedures: An Important Step Towards Interoperable Clinical Registries

Shanbehzadeh

Kazemi-Arpanahi²,

Bostan

et al. 2020

Front Health Inform

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“…Sample size calculations for the total population were based on the following formula: n= [(Z 1−α ) 2 (P(1 − P)/D 2 )] [13], where n is the individual sample size, Z 1−α = 1.96 (when α = 0.05), P is assumed PCOS prevalence according to previously published data, and D is an absolute error. Data were collected by using Research Electronic Data Capture (REDCap) [14,15]. Outliers were identified during the Exploratory Data Analysis [16,17] by using the box-plot and 3σ methods.…”

Section: Methodsmentioning

confidence: 99%

Establishing Normative Values to Determine the Prevalence of Biochemical Hyperandrogenism in Premenopausal Women of Different Ethnicities from Eastern Siberia

et al. 2022

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Androgen assessment is a key element for diagnosing polycystic ovary syndrome (PCOS), and defining a “normal” level of circulating androgens is critical for epidemiological studies. We determined the upper normal limits (UNLs) for androgens in a population-based group of premenopausal “healthy control” women, overall and by ethnicity (Caucasian and Asian), in the cross-sectional Eastern Siberia PCOS Epidemiology and Phenotype (ESPEP) Study (СlinicalTrials.gov ID: NCT05194384) conducted in 2016–2019. Overall, we identified a “healthy control” group consisting of 143 healthy premenopausal women without menstrual dysfunction, hirsutism, polycystic ovaries, or medical disorders. We analyzed serum total testosterone (TT) by using liquid chromatography with tandem mass spectrometry (LC-MS/MS), and DHEAS, sex-hormone-binding globulin (SHBG), TSH, prolactin, and 17-hydroxyprogesterone (17OHP) were assessed with an enzyme-linked immunosorbent assay (ELISA). The UNLs for the entire population for the TT, free androgen index (FAI), and DHEAS were determined as the 98th percentiles in healthy controls as follows: 67.3 (95% confidence interval (CI): 48.1, 76.5) ng/dl, 5.4 (3.5,14.0), and 355 (289, 371) μg/dl, respectively. The study results demonstrated that the UNLs for TT and FAI varied by ethnicity, whereas the DHEAS UNLs were comparable in the ethnicities studied.

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“…Statistical analysis: Sample size calculations for the total population were based on the following formula: n = [(Z1 − α ) 2 ( p (1 − P)/D2)] [ 42 ], where n = individual sample size, Z1 − α = 1.96 (when α = 0.05), p = assumed PCOS prevalence according to the previously published data [ 1 , 2 ], and D = absolute error. The data were collected using Research Electronic Data Capture (REDCap) [ 43 ]. Outliers were identified during the Exploratory Data Analysis [ 44 , 45 ] using the box-plot and 3σ methods.…”

Section: Methodsmentioning

confidence: 99%

Polycystic Ovary Syndrome and Gut Microbiota: Phenotype Matters

Suturina

Belkova

Igumnov

et al. 2022

Life

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Abnormalities in gut microbiota diversity are considered important mechanisms in metabolic disorders in polycystic ovarian syndrome (PCOS). However, the data on the association of these disorders with the PCOS phenotype remain controversial. The objectives of this study were to estimate the alpha diversity of the gut microbiota of healthy women and PCOS patients depending on phenotype. The study participants (184 premenopausal women: 63 with PCOS, 121 without PCOS) were recruited during the annual employment assessment in the Irkutsk Region and the Buryat Republic (Russia) in 2016–2019. For PCOS diagnosis, we used the Rotterdam (2003) criteria and definitions of PCOS phenotypes. Five indexes of alpha diversity (ASV, Shannon, Simpson, Chao, and ACE) were estimated for the gut microbiota in all participants using amplicon metasequencing. As a result, two out of five alpha diversity indexes showed a statistical difference between the non-PCOS and PCOS groups. We did not find a significant difference in the alpha diversity of gut microbiota in the subgroups of women with hyperandrogenic PCOS phenotypes vs non-androgenic phenotype D and the group of women with the presence of only one of the PCOS criteria. Nevertheless, “classic” PCOS phenotypes demonstrated the most significant decrease in alpha diversity compared with healthy women without any signs of PCOS.

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Research Electronic Data Capture (Redcap) for Building and Managing Databases for Population-Based Biomedical Studies

Cited by 10 publications

References 6 publications

Using Electronic Data Capture for Cardiovascular Electrophysiology Invasive Procedures: An Important Step Towards Interoperable Clinical Registries

Using Electronic Data Capture for Cardiovascular Electrophysiology Invasive Procedures: An Important Step Towards Interoperable Clinical Registries

Establishing Normative Values to Determine the Prevalence of Biochemical Hyperandrogenism in Premenopausal Women of Different Ethnicities from Eastern Siberia

Polycystic Ovary Syndrome and Gut Microbiota: Phenotype Matters

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