English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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.

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