Development and validation of new poisoning mortality score system for patients with acute poisoning at the emergency department

Abstract Background A prediction model of mortality for patients with acute poisoning has to consider both poisoning-related characteristics and patients’ physiological conditions; moreover, it must be applicable to patients of all ages. This study aimed to develop a scoring system for predicting in...

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Main Authors: Kap Su Han, Su Jin Kim, Eui Jung Lee, Joong Ho Shin, Ji Sung Lee, Sung Woo Lee
Format: Article
Language:English
Published: BMC 2021-01-01
Series:Critical Care
Subjects:
Online Access:https://doi.org/10.1186/s13054-020-03408-1
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spelling doaj-b2ef3e27e9284c4b86de84f8e981d62e2021-01-24T12:18:47ZengBMCCritical Care1364-85352021-01-0125111110.1186/s13054-020-03408-1Development and validation of new poisoning mortality score system for patients with acute poisoning at the emergency departmentKap Su Han0Su Jin Kim1Eui Jung Lee2Joong Ho Shin3Ji Sung Lee4Sung Woo Lee5Department of Emergency Medicine, College of Medicine, Korea UniversityDepartment of Emergency Medicine, College of Medicine, Korea UniversityDepartment of Emergency Medicine, College of Medicine, Korea UniversityDepartment of Emergency Medicine, College of Medicine, Korea UniversityClinical Research Center, Asan Institute for Life Sciences, Asan Medical CenterDepartment of Emergency Medicine, College of Medicine, Korea UniversityAbstract Background A prediction model of mortality for patients with acute poisoning has to consider both poisoning-related characteristics and patients’ physiological conditions; moreover, it must be applicable to patients of all ages. This study aimed to develop a scoring system for predicting in-hospital mortality of patients with acute poisoning at the emergency department (ED). Methods This was a retrospective analysis of the Injury Surveillance Cohort generated by the Korea Center for Disease Control and Prevention (KCDC) during 2011–2018. We developed the new-Poisoning Mortality Scoring system (new-PMS) to generate a prediction model using the derivation group (2011–2017 KCDC cohort). Points were computed for categories of each variable. The sum of these points was the new-PMS. The validation group (2018 KCDC cohort) was subjected to external temporal validation. The performance of new-PMS in predicting mortality was evaluated using area under the receiver operating characteristic curve (AUROC) for both the groups. Results Of 57,326 poisoning cases, 42,568 were selected. Of these, 34,352 (80.7%) and 8216 (19.3%) were enrolled in the derivation and validation groups, respectively. The new-PMS was the sum of the points for each category of 10 predictors. The possible range of the new-PMS was 0–137 points. Hosmer–Lemeshow goodness-of-fit test showed adequate calibration for the new-PMS with p values of 0.093 and 0.768 in the derivation and validation groups, respectively. AUROCs of the new-PMS were 0.941 (95% CI 0.934–0.949, p < 0.001) and 0.946 (95% CI 0.929–0.964, p < 0.001) in the derivation and validation groups, respectively. The sensitivity, specificity, and accuracy of the new-PMS (cutoff value: 49 points) were 86.4%, 87.2%, and 87.2% and 85.9%, 89.5%, and 89.4% in the derivation and validation groups, respectively. Conclusions We developed a new-PMS system based on demographic, poisoning-related variables, and vital signs observed among patients at the ED. The new-PMS showed good performance for predicting in-hospital mortality in both the derivation and validation groups. The probability of death increased according to the increase in the new-PMS. The new-PMS accurately predicted the probability of death for patients with acute poisoning. This could contribute to clinical decision making for patients with acute poisoning at the ED.https://doi.org/10.1186/s13054-020-03408-1MortalityPredictionPoisoningScoring systemValidation
collection DOAJ
language English
format Article
sources DOAJ
author Kap Su Han
Su Jin Kim
Eui Jung Lee
Joong Ho Shin
Ji Sung Lee
Sung Woo Lee
spellingShingle Kap Su Han
Su Jin Kim
Eui Jung Lee
Joong Ho Shin
Ji Sung Lee
Sung Woo Lee
Development and validation of new poisoning mortality score system for patients with acute poisoning at the emergency department
Critical Care
Mortality
Prediction
Poisoning
Scoring system
Validation
author_facet Kap Su Han
Su Jin Kim
Eui Jung Lee
Joong Ho Shin
Ji Sung Lee
Sung Woo Lee
author_sort Kap Su Han
title Development and validation of new poisoning mortality score system for patients with acute poisoning at the emergency department
title_short Development and validation of new poisoning mortality score system for patients with acute poisoning at the emergency department
title_full Development and validation of new poisoning mortality score system for patients with acute poisoning at the emergency department
title_fullStr Development and validation of new poisoning mortality score system for patients with acute poisoning at the emergency department
title_full_unstemmed Development and validation of new poisoning mortality score system for patients with acute poisoning at the emergency department
title_sort development and validation of new poisoning mortality score system for patients with acute poisoning at the emergency department
publisher BMC
series Critical Care
issn 1364-8535
publishDate 2021-01-01
description Abstract Background A prediction model of mortality for patients with acute poisoning has to consider both poisoning-related characteristics and patients’ physiological conditions; moreover, it must be applicable to patients of all ages. This study aimed to develop a scoring system for predicting in-hospital mortality of patients with acute poisoning at the emergency department (ED). Methods This was a retrospective analysis of the Injury Surveillance Cohort generated by the Korea Center for Disease Control and Prevention (KCDC) during 2011–2018. We developed the new-Poisoning Mortality Scoring system (new-PMS) to generate a prediction model using the derivation group (2011–2017 KCDC cohort). Points were computed for categories of each variable. The sum of these points was the new-PMS. The validation group (2018 KCDC cohort) was subjected to external temporal validation. The performance of new-PMS in predicting mortality was evaluated using area under the receiver operating characteristic curve (AUROC) for both the groups. Results Of 57,326 poisoning cases, 42,568 were selected. Of these, 34,352 (80.7%) and 8216 (19.3%) were enrolled in the derivation and validation groups, respectively. The new-PMS was the sum of the points for each category of 10 predictors. The possible range of the new-PMS was 0–137 points. Hosmer–Lemeshow goodness-of-fit test showed adequate calibration for the new-PMS with p values of 0.093 and 0.768 in the derivation and validation groups, respectively. AUROCs of the new-PMS were 0.941 (95% CI 0.934–0.949, p < 0.001) and 0.946 (95% CI 0.929–0.964, p < 0.001) in the derivation and validation groups, respectively. The sensitivity, specificity, and accuracy of the new-PMS (cutoff value: 49 points) were 86.4%, 87.2%, and 87.2% and 85.9%, 89.5%, and 89.4% in the derivation and validation groups, respectively. Conclusions We developed a new-PMS system based on demographic, poisoning-related variables, and vital signs observed among patients at the ED. The new-PMS showed good performance for predicting in-hospital mortality in both the derivation and validation groups. The probability of death increased according to the increase in the new-PMS. The new-PMS accurately predicted the probability of death for patients with acute poisoning. This could contribute to clinical decision making for patients with acute poisoning at the ED.
topic Mortality
Prediction
Poisoning
Scoring system
Validation
url https://doi.org/10.1186/s13054-020-03408-1
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