Cargando…

2148. 100 Years of Sepsis: Using Topic Modeling to Understand Historical Themes Surrounding Sepsis

BACKGROUND: Medical research publications on sepsis have increased at an exponential rate, whereas our capacity to absorb and understand them has remained limited. We used topic modeling, a method that allows machines to distill large amounts of information into its elemental themes, to help us infe...

Descripción completa

Detalles Bibliográficos
Autores principales: Doran Bostwick, A, Peterson, Kelly, Jones, Barbara, Paine, Robert, Samore, Matthew, Jones, Makoto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252740/
http://dx.doi.org/10.1093/ofid/ofy210.1804
_version_ 1783373333518090240
author Doran Bostwick, A
Peterson, Kelly
Jones, Barbara
Paine, Robert
Samore, Matthew
Jones, Makoto
author_facet Doran Bostwick, A
Peterson, Kelly
Jones, Barbara
Paine, Robert
Samore, Matthew
Jones, Makoto
author_sort Doran Bostwick, A
collection PubMed
description BACKGROUND: Medical research publications on sepsis have increased at an exponential rate, whereas our capacity to absorb and understand them has remained limited. We used topic modeling, a method that allows machines to distill large amounts of information into its elemental themes, to help us infer the discourse that led us to the present model/understanding of sepsis. Using this model to augment our understanding of sepsis, an evolving, networked and complex disease, we aimed to recognize connections that could be further explored and aid in knowledge discovery. METHODS: We extracted all abstracts from PubMed containing the terms “sepsis”, “septic shock”, and “septicemia” between 1890 and 2017 and retained the most informative words. Using topic modeling approaches based on Latent Dirichlet Allocation, we trained dynamic models to five topics from the corpus. We conducted a thematic analysis of topics across publication periods by examining the 30 most frequent words in each topic for each decade. We then fit a static topic model to the last 5 years. We compared the respective themes and their relatedness, and compared the frequency of each topic over the first and second halves of the century. RESULTS: Five themes emerged overall: surgery, physiology, microbiology, neonatal/maternal health, and cellular and endothelial responses to infection. When limited to the last 5 years, topics were: acute organ failure and ICU management, early sepsis management and cost, cellular and endothelial response, biomarkers and viruses, and neonatal infection. For the first half of the twentieth century, the bulk of research focused on microbiology while in the latter half of the century there was increased attention on the host response. CONCLUSION: When visualizing the frequency of each topic over the last 100 years we found that the focus has shifted from the pathogen to the host response both from a cellular and physiologic perspective. In the last 5 years, biomarkers, early recognition and system management emerged as new themes. Reasons for this may include: evolution of scientific tools, treatments and statistical abilities, an increasing focus on healthcare cost, and ultimately an incorporation of the individual host response into the disease model. [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures.
format Online
Article
Text
id pubmed-6252740
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-62527402018-11-28 2148. 100 Years of Sepsis: Using Topic Modeling to Understand Historical Themes Surrounding Sepsis Doran Bostwick, A Peterson, Kelly Jones, Barbara Paine, Robert Samore, Matthew Jones, Makoto Open Forum Infect Dis Abstracts BACKGROUND: Medical research publications on sepsis have increased at an exponential rate, whereas our capacity to absorb and understand them has remained limited. We used topic modeling, a method that allows machines to distill large amounts of information into its elemental themes, to help us infer the discourse that led us to the present model/understanding of sepsis. Using this model to augment our understanding of sepsis, an evolving, networked and complex disease, we aimed to recognize connections that could be further explored and aid in knowledge discovery. METHODS: We extracted all abstracts from PubMed containing the terms “sepsis”, “septic shock”, and “septicemia” between 1890 and 2017 and retained the most informative words. Using topic modeling approaches based on Latent Dirichlet Allocation, we trained dynamic models to five topics from the corpus. We conducted a thematic analysis of topics across publication periods by examining the 30 most frequent words in each topic for each decade. We then fit a static topic model to the last 5 years. We compared the respective themes and their relatedness, and compared the frequency of each topic over the first and second halves of the century. RESULTS: Five themes emerged overall: surgery, physiology, microbiology, neonatal/maternal health, and cellular and endothelial responses to infection. When limited to the last 5 years, topics were: acute organ failure and ICU management, early sepsis management and cost, cellular and endothelial response, biomarkers and viruses, and neonatal infection. For the first half of the twentieth century, the bulk of research focused on microbiology while in the latter half of the century there was increased attention on the host response. CONCLUSION: When visualizing the frequency of each topic over the last 100 years we found that the focus has shifted from the pathogen to the host response both from a cellular and physiologic perspective. In the last 5 years, biomarkers, early recognition and system management emerged as new themes. Reasons for this may include: evolution of scientific tools, treatments and statistical abilities, an increasing focus on healthcare cost, and ultimately an incorporation of the individual host response into the disease model. [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2018-11-26 /pmc/articles/PMC6252740/ http://dx.doi.org/10.1093/ofid/ofy210.1804 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Abstracts
Doran Bostwick, A
Peterson, Kelly
Jones, Barbara
Paine, Robert
Samore, Matthew
Jones, Makoto
2148. 100 Years of Sepsis: Using Topic Modeling to Understand Historical Themes Surrounding Sepsis
title 2148. 100 Years of Sepsis: Using Topic Modeling to Understand Historical Themes Surrounding Sepsis
title_full 2148. 100 Years of Sepsis: Using Topic Modeling to Understand Historical Themes Surrounding Sepsis
title_fullStr 2148. 100 Years of Sepsis: Using Topic Modeling to Understand Historical Themes Surrounding Sepsis
title_full_unstemmed 2148. 100 Years of Sepsis: Using Topic Modeling to Understand Historical Themes Surrounding Sepsis
title_short 2148. 100 Years of Sepsis: Using Topic Modeling to Understand Historical Themes Surrounding Sepsis
title_sort 2148. 100 years of sepsis: using topic modeling to understand historical themes surrounding sepsis
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252740/
http://dx.doi.org/10.1093/ofid/ofy210.1804
work_keys_str_mv AT doranbostwicka 2148100yearsofsepsisusingtopicmodelingtounderstandhistoricalthemessurroundingsepsis
AT petersonkelly 2148100yearsofsepsisusingtopicmodelingtounderstandhistoricalthemessurroundingsepsis
AT jonesbarbara 2148100yearsofsepsisusingtopicmodelingtounderstandhistoricalthemessurroundingsepsis
AT painerobert 2148100yearsofsepsisusingtopicmodelingtounderstandhistoricalthemessurroundingsepsis
AT samorematthew 2148100yearsofsepsisusingtopicmodelingtounderstandhistoricalthemessurroundingsepsis
AT jonesmakoto 2148100yearsofsepsisusingtopicmodelingtounderstandhistoricalthemessurroundingsepsis