3.How to conduct and write a cohort study.
Michael Ian N. Sta. Maria ; Nicolas R. Gordo Jr.
The Filipino Family Physician 2024;62(1):42-50
Cohort studies is an epidemiologic study that follows a group of individuals who share a common characteristic at the start of the study to observe the emergence of outcomes. Cohort studies are classified based on the population characteristics from where they were drawn, the way the data collection occurred or if its open or closed. This allows the computation of the absolute risk or the incidence of an outcome. There are several advantages in conducting a cohort study, such as clarity of temporal relationship of the exposure and outcome, permits the computation of incidence, permits multiple effects of a single exposure, and avoids selection bias on admission. While there are advantages, there are also disadvantages in doing this study, such as it requires long follow-up, need of large sample size, maybe costly, and may make it difficult to argue causation due to the presence of confounding. The statistical test that can be used to analyze the results will depend on the type of variable used. Statistical test such as T-test, Chi square test, and Regression can be used. Writing the final report follows the STROBE guidelines.
Cohort Studies ; Epidemiologic Studies
4.MAP: Mutation Arranger for Defining Phenotype-Related Single-Nucleotide Variant.
In Pyo BAEK ; Yong Bok JEONG ; Seung Hyun JUNG ; Yeun Jun CHUNG
Genomics & Informatics 2014;12(4):289-292
Next-generation sequencing (NGS) is widely used to identify the causative mutations underlying diverse human diseases, including cancers, which can be useful for discovering the diagnostic and therapeutic targets. Currently, a number of single-nucleotide variant (SNV)-calling algorithms are available; however, there is no tool for visualizing the recurrent and phenotype-specific mutations for general researchers. In this study, in order to support defining the recurrent mutations or phenotype-specific mutations from NGS data of a group of cancers with diverse phenotypes, we aimed to develop a user-friendly tool, named mutation arranger for defining phenotype-related SNV (MAP). MAP is a user-friendly program with multiple functions that supports the determination of recurrent or phenotype-specific mutations and provides graphic illustration images to the users. Its operation environment, the Microsoft Windows environment, enables more researchers who cannot operate Linux to define clinically meaningful mutations with NGS data from cancer cohorts.
Cohort Studies
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Humans
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Phenotype
5.Characteristics of Korean Patients with RA: A Single Center Cohort Study.
The Journal of the Korean Rheumatism Association 2009;16(4):261-263
No abstract available.
Cohort Studies
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Humans
6.Acute Ischemic Stroke in Nonconvulsive Status Epilepticus–Underestimated? Results from an Eight-Year Cohort Study.
Christopher TRAENKA ; Gian Marco De MARCHIS ; Lisa HERT ; David J SEIFFGE ; Alexandros POLYMERIS ; Nils PETERS ; Leo H BONATI ; Stefan ENGELTER ; Philippe LYRER ; Stephan RÜEGG ; Raoul SUTTER
Journal of Stroke 2017;19(2):236-238
No abstract available.
Cohort Studies*
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Stroke*
7.Perspectives for cohort studies in China.
Hui WANG ; Erdan DONG ; Zuowen ZHANG
Chinese Journal of Preventive Medicine 2014;48(3):164-166
8.Local Signs and Symptoms in Spontaneous Cervical Artery Dissection: A Single Centre Cohort Study
Lukas MAYER ; Christian BOEHME ; Thomas TOELL ; Benjamin DEJAKUM ; Johann WILLEIT ; Christoph SCHMIDAUER ; Klaus BEREK ; Christian SIEDENTOPF ; Elke Ruth GIZEWSKI ; Gudrun RATZINGER ; Stefan KIECHL ; Michael KNOFLACH
Journal of Stroke 2019;21(1):112-115
No abstract available.
Arteries
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Cohort Studies
9.Development of a validated Diabetes risk chart as a simple tool to predict the onset of Diabetes in Bogor, Indonesia
Eva Sulistiowati ; Julianty Pradono
Journal of the ASEAN Federation of Endocrine Societies 2022;37(1):46-52
Objective:
To develop a simple, non-invasive tool for predicting the onset of type 2 diabetes mellitus (T2DM).
Methodology:
A total of 4418 nondiabetic respondents living in Bogor were included in this cohort study. Their ages ranged from 25 to 60 years old and were followed for 6 years with interviews, physical examinations and laboratory tests. The investigators used logistic regression to create a tool for diabetes risk determination.
Results:
The cumulative incidence of T2DM was 17.9%. Risk factors significantly associated with T2DM included age, obesity, central obesity, hypertension and lack of physical activity. The Bogor Diabetes Risk Prediction (BDRP) chart had a cut-off of 0.128, with sensitivity of 76.6% and specificity of 50.3%. The Positive Predictive Value (PPV) was 21.6% and Negative Predictive Value (NPV) was 92.3%. The Area under the Curve (AUC) was 0.70 with a 95% confidence interval ranging from 0.675-0.721.
Conclusion
The BDRP chart is a simple and non-invasive tool to predict T2DM. In addition, the BDRP chart is reliable and can be easily used in primary health care.
Risk Factors
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Cohort Studies
10.Age-Group Related Cohort Effects on the Association between Age at Menarche and Metabolic Syndrome among Korean Premenopausal Women
Korean Journal of Family Medicine 2019;40(4):280-281
No abstract available.
Cohort Effect
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Cohort Studies
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Female
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Humans
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Menarche