Determining predictors of sepsis at triage among children under 5 years of age in resource-limited settings: a modified Delphi process
Sepsis is a life-threatening dysfunction of the immune system leading to multiorgan failure that is precipitated by infectious diseases and is a leading cause of death in children under 5 years of age. It is necessary to be able to identify a sick child at risk of developing sepsis at the earliest p...
| Main Authors: | , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Public Library of Science
2019
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| _version_ | 1826296458927669248 |
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| author | Fung, J Akech, S Kissoon, N Wiens, M English, M Ansermino, J |
| author_facet | Fung, J Akech, S Kissoon, N Wiens, M English, M Ansermino, J |
| author_sort | Fung, J |
| collection | OXFORD |
| description | Sepsis is a life-threatening dysfunction of the immune system leading to multiorgan failure that is precipitated by infectious diseases and is a leading cause of death in children under 5 years of age. It is necessary to be able to identify a sick child at risk of developing sepsis at the earliest point of presentation to a healthcare facility so that appropriate care can be provided as soon as possible. Our study objective was to generate a list of consensus-driven predictor variables for the derivation of a prediction model that will be incorporated into a mobile device and operated by low-skilled healthcare workers at triage. By conducting a systematic literature review and examination of global guideline documents, a list of 72 initial candidate predictor variables was generated. A two-round modified Delphi process involving 26 experts from both resource-rich and resource-limited settings, who were also encouraged to suggest new variables, yielded a final list of 45 predictor variables after evaluating each variable based on three domains: predictive potential, measurement reliability, and level of training and resources required. The final list of predictor variables will be used to collect data and contribute to the derivation of a prediction model. |
| first_indexed | 2024-03-07T04:16:39Z |
| format | Journal article |
| id | oxford-uuid:c9a21a19-dd18-41b7-91ff-ad1f9616103b |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:16:39Z |
| publishDate | 2019 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | oxford-uuid:c9a21a19-dd18-41b7-91ff-ad1f9616103b2022-03-27T07:00:50ZDetermining predictors of sepsis at triage among children under 5 years of age in resource-limited settings: a modified Delphi processJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:c9a21a19-dd18-41b7-91ff-ad1f9616103bEnglishSymplectic Elements at OxfordPublic Library of Science2019Fung, JAkech, SKissoon, NWiens, MEnglish, MAnsermino, JSepsis is a life-threatening dysfunction of the immune system leading to multiorgan failure that is precipitated by infectious diseases and is a leading cause of death in children under 5 years of age. It is necessary to be able to identify a sick child at risk of developing sepsis at the earliest point of presentation to a healthcare facility so that appropriate care can be provided as soon as possible. Our study objective was to generate a list of consensus-driven predictor variables for the derivation of a prediction model that will be incorporated into a mobile device and operated by low-skilled healthcare workers at triage. By conducting a systematic literature review and examination of global guideline documents, a list of 72 initial candidate predictor variables was generated. A two-round modified Delphi process involving 26 experts from both resource-rich and resource-limited settings, who were also encouraged to suggest new variables, yielded a final list of 45 predictor variables after evaluating each variable based on three domains: predictive potential, measurement reliability, and level of training and resources required. The final list of predictor variables will be used to collect data and contribute to the derivation of a prediction model. |
| spellingShingle | Fung, J Akech, S Kissoon, N Wiens, M English, M Ansermino, J Determining predictors of sepsis at triage among children under 5 years of age in resource-limited settings: a modified Delphi process |
| title | Determining predictors of sepsis at triage among children under 5 years of age in resource-limited settings: a modified Delphi process |
| title_full | Determining predictors of sepsis at triage among children under 5 years of age in resource-limited settings: a modified Delphi process |
| title_fullStr | Determining predictors of sepsis at triage among children under 5 years of age in resource-limited settings: a modified Delphi process |
| title_full_unstemmed | Determining predictors of sepsis at triage among children under 5 years of age in resource-limited settings: a modified Delphi process |
| title_short | Determining predictors of sepsis at triage among children under 5 years of age in resource-limited settings: a modified Delphi process |
| title_sort | determining predictors of sepsis at triage among children under 5 years of age in resource limited settings a modified delphi process |
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