J. Talavera, N. Wacher-Rodarte, and R. Rivas-Ruiz. Revista médica del Instituto Mexicano del Seguro Social, 49 (3):
289-94(2011)6369<m:linebreak></m:linebreak>JID: 101243727; ppublish;<m:linebreak></m:linebreak>Causalitat; Introductori.
Abstract
The need to solve a clinical problem leads us to establish a starting point to address (risk, prognosis or treatment studies), all these cases seek to attribute causality. Clinical reasoning described in the book Clinical Epidemiology. The architecture of clinical research, offers a simple guide to understanding this phenomenon. And proposes three basic components: baseline, maneuver and outcome. In this model, different systematic errors (bias) are described, which may be favored by omitting characteristics of the three basic components. Thus, omissions in the baseline characteristics cause an improper assembly of the population and susceptibility bias, omissions in the application or evaluation of the maneuver provoke performance bias, and omissions in the assessment of out-come cause detection bias and transfer bias. Importantly, if this way of thinking facilitates understanding of the causal phenomenon, the appropriateness of the variables to be selected in the studies to which attribute or not causality, require additional arguments for evaluate clinical relevance.
Revista médica del Instituto Mexicano del Seguro Social
number
3
pages
289-94
volume
49
city
Centro de Adiestramiento en Investigacion Clinica, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Distrito Federal, Mexico. jtalaverap@cis.gob.mx
%0 Journal Article
%1 Talavera2011
%A Talavera, Juan O
%A Wacher-Rodarte, Niels H
%A Rivas-Ruiz, Rodolfo
%D 2011
%J Revista médica del Instituto Mexicano del Seguro Social
%K BiomedicalResearch BiomedicalResearch:methods BiomedicalResearch:standards Causality Humans
%N 3
%P 289-94
%T Clinical research III. The causality studies.
%U http://www.ncbi.nlm.nih.gov/pubmed/21838996
%V 49
%X The need to solve a clinical problem leads us to establish a starting point to address (risk, prognosis or treatment studies), all these cases seek to attribute causality. Clinical reasoning described in the book Clinical Epidemiology. The architecture of clinical research, offers a simple guide to understanding this phenomenon. And proposes three basic components: baseline, maneuver and outcome. In this model, different systematic errors (bias) are described, which may be favored by omitting characteristics of the three basic components. Thus, omissions in the baseline characteristics cause an improper assembly of the population and susceptibility bias, omissions in the application or evaluation of the maneuver provoke performance bias, and omissions in the assessment of out-come cause detection bias and transfer bias. Importantly, if this way of thinking facilitates understanding of the causal phenomenon, the appropriateness of the variables to be selected in the studies to which attribute or not causality, require additional arguments for evaluate clinical relevance.
%@ 0443-5117; 0443-5117
@article{Talavera2011,
abstract = {The need to solve a clinical problem leads us to establish a starting point to address (risk, prognosis or treatment studies), all these cases seek to attribute causality. Clinical reasoning described in the book Clinical Epidemiology. The architecture of clinical research, offers a simple guide to understanding this phenomenon. And proposes three basic components: baseline, maneuver and outcome. In this model, different systematic errors (bias) are described, which may be favored by omitting characteristics of the three basic components. Thus, omissions in the baseline characteristics cause an improper assembly of the population and susceptibility bias, omissions in the application or evaluation of the maneuver provoke performance bias, and omissions in the assessment of out-come cause detection bias and transfer bias. Importantly, if this way of thinking facilitates understanding of the causal phenomenon, the appropriateness of the variables to be selected in the studies to which attribute or not causality, require additional arguments for evaluate clinical relevance.},
added-at = {2023-02-03T11:44:35.000+0100},
author = {Talavera, Juan O and Wacher-Rodarte, Niels H and Rivas-Ruiz, Rodolfo},
biburl = {https://www.bibsonomy.org/bibtex/2745fb212f420afde9891797bc7b0b17c/jepcastel},
city = {Centro de Adiestramiento en Investigacion Clinica, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Distrito Federal, Mexico. jtalaverap@cis.gob.mx},
interhash = {4ba15fd7895a80dc6e26e0e25e9ae14e},
intrahash = {745fb212f420afde9891797bc7b0b17c},
isbn = {0443-5117; 0443-5117},
issn = {0443-5117},
journal = {Revista médica del Instituto Mexicano del Seguro Social},
keywords = {BiomedicalResearch BiomedicalResearch:methods BiomedicalResearch:standards Causality Humans},
note = {6369<m:linebreak></m:linebreak>JID: 101243727; ppublish;<m:linebreak></m:linebreak>Causalitat; Introductori},
number = 3,
pages = {289-94},
pmid = {21838996},
timestamp = {2023-02-03T11:44:35.000+0100},
title = {[Clinical research III. The causality studies].},
url = {http://www.ncbi.nlm.nih.gov/pubmed/21838996},
volume = 49,
year = 2011
}