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Statistical Methods to Support Difficult Diagnoses

Far too often, one meets patients who went for years or even decades from doctor to doctor without obtaining a valid diagnosis. This brings pain to millions of patients and their families, not to speak of the enormous costs. Often patients cannot tell precisely enough which factors (or combinations...

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Autores principales: Pilz, Guenter F., Weber, Frank, Mueller, Werner G., Schaefer, Juergen R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305132/
https://www.ncbi.nlm.nih.gov/pubmed/34359382
http://dx.doi.org/10.3390/diagnostics11071300
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author Pilz, Guenter F.
Weber, Frank
Mueller, Werner G.
Schaefer, Juergen R.
author_facet Pilz, Guenter F.
Weber, Frank
Mueller, Werner G.
Schaefer, Juergen R.
author_sort Pilz, Guenter F.
collection PubMed
description Far too often, one meets patients who went for years or even decades from doctor to doctor without obtaining a valid diagnosis. This brings pain to millions of patients and their families, not to speak of the enormous costs. Often patients cannot tell precisely enough which factors (or combinations thereof) trigger their problems. If conventional methods fail, we propose the use of statistics and algebra to provide doctors much more useful inputs from patients. We use statistical regression for triggering factors of medical problems, and in particular, “balanced incomplete block designs” for factors detection. These methods can supply doctors with much more valuable inputs and can also find combinations of multiple factors through very few tests. In order to show that these methods do work, we briefly describe a case in which these methods helped to solve a 60-year-old problem in a patient and provide some more examples where these methods might be particularly useful. As a conclusion, while regression is used in clinical medicine, it seems to be widely unknown in diagnosing. Statistics and algebra can save the health systems much money, as well as the patients a lot of pain.
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spelling pubmed-83051322021-07-25 Statistical Methods to Support Difficult Diagnoses Pilz, Guenter F. Weber, Frank Mueller, Werner G. Schaefer, Juergen R. Diagnostics (Basel) Article Far too often, one meets patients who went for years or even decades from doctor to doctor without obtaining a valid diagnosis. This brings pain to millions of patients and their families, not to speak of the enormous costs. Often patients cannot tell precisely enough which factors (or combinations thereof) trigger their problems. If conventional methods fail, we propose the use of statistics and algebra to provide doctors much more useful inputs from patients. We use statistical regression for triggering factors of medical problems, and in particular, “balanced incomplete block designs” for factors detection. These methods can supply doctors with much more valuable inputs and can also find combinations of multiple factors through very few tests. In order to show that these methods do work, we briefly describe a case in which these methods helped to solve a 60-year-old problem in a patient and provide some more examples where these methods might be particularly useful. As a conclusion, while regression is used in clinical medicine, it seems to be widely unknown in diagnosing. Statistics and algebra can save the health systems much money, as well as the patients a lot of pain. MDPI 2021-07-20 /pmc/articles/PMC8305132/ /pubmed/34359382 http://dx.doi.org/10.3390/diagnostics11071300 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pilz, Guenter F.
Weber, Frank
Mueller, Werner G.
Schaefer, Juergen R.
Statistical Methods to Support Difficult Diagnoses
title Statistical Methods to Support Difficult Diagnoses
title_full Statistical Methods to Support Difficult Diagnoses
title_fullStr Statistical Methods to Support Difficult Diagnoses
title_full_unstemmed Statistical Methods to Support Difficult Diagnoses
title_short Statistical Methods to Support Difficult Diagnoses
title_sort statistical methods to support difficult diagnoses
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305132/
https://www.ncbi.nlm.nih.gov/pubmed/34359382
http://dx.doi.org/10.3390/diagnostics11071300
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