Quantitative Methods in Biological and Medical Sciences

Lancaster, H. O.

doi:10.1007/978-1-4612-2658-1

Cited by 32 publications

(5 citation statements)

References 157 publications

(227 reference statements)

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“…The germ theory of PS had been proposed some 30 years later. Acceptance of Semmelweis’ discovery therefore meant that the two prevailing theories of the etiology of PS, miasmatic theory (“a bad component in the air”) and atmospheric-cosmic-telluric conditions (Galenic hypothesis), had to be denied without the introduction of a new pathology-based theory; (2) the numerical method in medicine as introduced by Louis was still in its infancy [ 26 ]; (3) Semmelweis delayed the publication of his work until 1861 (13 years delay); (4) Semmelweis’ style of scientific writing was wordy and repetitious [ 7 , 27 , 28 ], and (5) the style of communication that Semmelweis used to defend his discovery of PS transmission was harsh and personally offensive [ 10 , 29 ].…”

Section: Discussionmentioning

confidence: 99%

A twenty-first century perspective on concepts of modern epidemiology in Ignaz Philipp Semmelweis’ work on puerperal sepsis

2022

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We aimed to review Semmelweis’s complete work on puerperal sepsis mortality in maternity wards in relation to exposure to cadavers and chlorine handwashing and other factors from the perspective of modern epidemiological methods. We reviewed Semmelweis' complete work and data as published by von Györy 1905 according to current standards. We paid particular attention to Semmelweis's definition of mortality in and of itself, to concepts of modern epidemiology that were already recognizable in Semmelweis's work, and to bias sources. We did several quantitative bias analyses to address selection bias and information bias from outcome measurement error. Semmelweis addressed biases that have become known to modern epidemiology, such as confounding, selection bias and bias from outcome misclassification. Our bias analysis shows that differential loss to follow-up is an unlikely explanation for his results. Bias due to outcome misclassification would only be relevant if misclassification differed between time periods. Confounding by health status was likely but could not be quantitatively addressed. Semmelweis was aware that cause-specific mortality is a function of incidence and prognosis. He reasoned in potential outcome terms to estimate the reduced number of deaths from an intervention. He advanced a hypothesis of clinic overcrowding as a risk factor for puerperal sepsis mortality that turns out to be wrong. Semmelweis’ data provide a great pool for illustrating the logic of scientific discovery by use of the numerical method. The explanatory power of his work was strong and Semmelweis was able to refute several previous causal explanations.

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Section: Discussionmentioning

confidence: 99%

A twenty-first century perspective on concepts of modern epidemiology in Ignaz Philipp Semmelweis’ work on puerperal sepsis

2022

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“…Es recomendable sugerir a los estudiantes el tratamiento más exhaustivo de tal distribución desde el punto de vista cuantitativo, cualitativo y sus diversos usos para lo cual pueden consultarse (D'Agostino, Sullivan y Beiser, 2006;Bluman, 2009;Lancaster, 2011).…”

Section: Algunas Consideraciones Sobre La Enseñanza De La Distribución Normal En La Carrera De Medicinaunclassified

La distribución normal en ciencias biomédicas: un enfoque a partir de las distribuciones de Pearson

et al. 2020

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La distribución normal es una de las más importantes en el proceso de enseñanza aprendizaje de la Bioestadística para la especialidad de Medicina. Sin embargo, la ausencia de un enfoque deductivo en la introducción al tópico, dificulta la comprensión de su origen. A partir de sistemas de distribuciones continuas de probabilidad, se propone una vía alternativa para presentarla, tanto en la forma general como en la estándar. Teniendo en cuenta los métodos analítico sintético y la revisión documental, se identifican los vacío epistémicos y las dificultades en el tratamiento del tema. Los objetivos esenciales consisten en deducir la expresión matemática de tal distribución y valorar la posibilidad de introducir los elementos cualitativos básicos del procedimiento usado, en el programa de Informática Médica II, enfatizando en las nociones del Cálculo Diferencial, en etapa previa a los elementos del Cálculo Integral. La conclusión fundamental se asocia a la contribución del enfoque sugerido, al rigor y a la armonía al conocimiento estadístico matemático en la disciplina, si bien se precisa de conceptos del Análisis Diferencial, los cuales favorecen la comprensión de las aplicaciones prácticas tanto en el ámbito de la carrera de Medicina como en otras áreas de investigación de las ciencias biomédicas.

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“…Testing for efficacy seems first to have been promoted by Avicenna in his Canon of Medicine [19][20][21][22]. Huff observed that the Canon "contained a set of rules that laid down the conditions for the experimental use and testing of drugs which were a precise guide for practical experimentation in the process of discovering and proving the effectiveness of medical substances" [23].…”

Section: Avicenna As the Pioneer Of Ebmmentioning

confidence: 99%