Cargando…

Prediction models for cardiovascular disease risk in the general population: systematic review

Objective To provide an overview of prediction models for risk of cardiovascular disease (CVD) in the general population. Design Systematic review. Data sources Medline and Embase until June 2013. Eligibility criteria for study selection Studies describing the development or external validation of a...

Descripción completa

Detalles Bibliográficos
Autores principales:	Damen, Johanna A A G, Hooft, Lotty, Schuit, Ewoud, Debray, Thomas P A, Collins, Gary S, Tzoulaki, Ioanna, Lassale, Camille M, Siontis, George C M, Chiocchia, Virginia, Roberts, Corran, Schlüssel, Michael Maia, Gerry, Stephen, Black, James A, Heus, Pauline, van der Schouw, Yvonne T, Peelen, Linda M, Moons, Karel G M
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BMJ Publishing Group Ltd. 2016
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4868251/ https://www.ncbi.nlm.nih.gov/pubmed/27184143 http://dx.doi.org/10.1136/bmj.i2416

Ejemplares similares

Performance of the Framingham risk models and pooled cohort equations for predicting 10-year risk of cardiovascular disease: a systematic review and meta-analysis
por: Damen, Johanna A., et al.
Publicado: (2019)

Poor reporting of multivariable prediction model studies: towards a targeted implementation strategy of the TRIPOD statement
por: Heus, Pauline, et al.
Publicado: (2018)

Uniformity in measuring adherence to reporting guidelines: the example of TRIPOD for assessing completeness of reporting of prediction model studies
por: Heus, Pauline, et al.
Publicado: (2019)

How to conduct a systematic review and meta-analysis of prognostic model studies
por: Damen, Johanna A.A., et al.
Publicado: (2023)

Empirical evidence of the impact of study characteristics on the performance of prediction models: a meta-epidemiological study
por: Damen, Johanna A A G, et al.
Publicado: (2019)

Cardiovascular risk prediction models for women in the general population: A systematic review
por: Baart, Sara J., et al.
Publicado: (2019)

A framework for meta-analysis of prediction model studies with binary and time-to-event outcomes
por: Debray, Thomas PA, et al.
Publicado: (2018)

Transparent reporting of multivariable prediction models for individual prognosis or diagnosis: checklist for systematic reviews and meta-analyses (TRIPOD-SRMA)
por: Snell, Kym I E, et al.
Publicado: (2023)

What did we learn in 35 years of research on nutrition and supplements for age‐related macular degeneration: a systematic review
por: Pameijer, Els M., et al.
Publicado: (2022)

Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review
por: de Hond, Anne A. H., et al.
Publicado: (2022)

TRIPOD statement: a preliminary pre-post analysis of reporting and methods of prediction models
por: Zamanipoor Najafabadi, Amir H, et al.
Publicado: (2020)

The increasing need for systematic reviews of prognosis studies: strategies to facilitate review production and improve quality of primary research
por: Damen, Johanna A. A. G., et al.
Publicado: (2019)

Prognostic effect size of cardiovascular biomarkers in datasets from observational studies versus randomised trials: meta-epidemiology study
por: Tzoulaki, Ioanna, et al.
Publicado: (2011)

Treatment use in prognostic model research: a systematic review of cardiovascular prognostic studies
por: Pajouheshnia, Romin, et al.
Publicado: (2017)

The score after 10 years of registration of systematic review protocols
por: van der Braak, Kim, et al.
Publicado: (2022)

The methodological quality of 176,620 randomized controlled trials published between 1966 and 2018 reveals a positive trend but also an urgent need for improvement
por: Vinkers, Christiaan H., et al.
Publicado: (2021)

Impact of provision of cardiovascular disease risk estimates to healthcare professionals and patients: a systematic review
por: Usher-Smith, Juliet A, et al.
Publicado: (2015)

Effectiveness of contact tracing apps for SARS-CoV-2: a rapid systematic review
por: Jenniskens, Kevin, et al.
Publicado: (2021)

Overdiagnosis across medical disciplines: a scoping review
por: Jenniskens, Kevin, et al.
Publicado: (2017)

Reducing low-value care: what can we learn from eight de-implementation studies in the Netherlands?
por: Verkerk, Eva W, et al.
Publicado: (2022)

Prognostic factors for adverse outcomes in patients with COVID-19: a field-wide systematic review and meta-analysis
por: Bellou, Vanesa, et al.
Publicado: (2022)

Detecting small‐study effects and funnel plot asymmetry in meta‐analysis of survival data: A comparison of new and existing tests
por: Debray, Thomas P. A., et al.
Publicado: (2017)

Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review
por: Andaur Navarro, Constanza L, et al.
Publicado: (2021)

Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review
por: Andaur Navarro, Constanza L., et al.
Publicado: (2022)

Association between trial registration and positive study findings: cross sectional study (Epidemiological Study of Randomized Trials—ESORT)
por: Odutayo, Ayodele, et al.
Publicado: (2017)

Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review
por: Dhiman, Paula, et al.
Publicado: (2022)

Risk of bias of prognostic models developed using machine learning: a systematic review in oncology
por: Dhiman, Paula, et al.
Publicado: (2022)

Barriers and facilitators to reduce low-value care: a qualitative evidence synthesis
por: van Dulmen, SA, et al.
Publicado: (2020)

Performance of binary prediction models in high-correlation low-dimensional settings: a comparison of methods
por: Leeuwenberg, Artuur M., et al.
Publicado: (2022)

Meta-analyses triggered by previous (false-)significant findings: problems and solutions
por: Schuit, Ewoud, et al.
Publicado: (2015)

Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques
por: Andaur Navarro, Constanza L, et al.
Publicado: (2020)

Reducing Inappropriate Proton Pump Inhibitors Use for Stress Ulcer Prophylaxis in Hospitalized Patients: Systematic Review of De-Implementation Studies
por: Orelio, Claudia C., et al.
Publicado: (2021)

Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved
por: Dhiman, Paula, et al.
Publicado: (2021)

Assessing variability in results in systematic reviews of diagnostic studies
por: Naaktgeboren, Christiana A., et al.
Publicado: (2016)

Evidence synthesis in prognosis research
por: Debray, Thomas P.A., et al.
Publicado: (2019)

On the aggregation of published prognostic scores for causal inference in observational studies
por: Nguyen, Tri‐Long, et al.
Publicado: (2020)

Individual Participant Data (IPD) Meta-analyses of Diagnostic and Prognostic Modeling Studies: Guidance on Their Use
por: Debray, Thomas P. A., et al.
Publicado: (2015)

Accounting for treatment use when validating a prognostic model: a simulation study
por: Pajouheshnia, Romin, et al.
Publicado: (2017)

Incorporating quality assessments of primary studies in the conclusions of diagnostic accuracy reviews: a cross-sectional study
por: Ochodo, Eleanor A, et al.
Publicado: (2014)

Prediction models for COVID-19 clinical decision making
por: Leeuwenberg, Artuur M, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_crkaj2dfqerkfsum01bi5r20o6