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  1. Home
  2. College of Medicine /醫學院
  3. Institute of Medicine/醫學研究所
  4. PEAL Score to Predict the Mortality Risk of Cardiogenic Shock in the Emergency Department: An Observational Study
 
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PEAL Score to Predict the Mortality Risk of Cardiogenic Shock in the Emergency Department: An Observational Study

Journal
Journal of Personalized Medicine
Journal Volume
13
Journal Issue
11
Start Page
1614
ISSN
2075-4426
Date Issued
2023-11-16
Author(s)
Jen-Wen Ma
Sung-Yuan Hu
Ming-Shun Hsieh
Yi-Chen Lee
Shih-Che Huang
Kuan-Ju Chen
Yan-Zin Chang  
Yi-Chun Tsai
DOI
10.3390/jpm13111614
URI
https://scholars.csmu.edu.tw/handle/123456789/4869
Abstract
<jats:p>Background: The in-hospital mortality of cardiogenic shock (CS) remains high (28% to 45%). As a result, several studies developed prediction models to assess the mortality risk and provide guidance on treatment, including CardShock and IABP-SHOCK II scores, which performed modestly in external validation studies, reflecting the heterogeneity of the CS populations. Few articles established predictive scores of CS based on Asian people with a higher burden of comorbidities than Caucasians. We aimed to describe the clinical characteristics of a contemporary Asian population with CS, identify risk factors, and develop a predictive scoring model. Methods: A retrospective observational study was conducted between 2014 and 2019 to collect the patients who presented with all-cause CS in the emergency department of a single medical center in Taiwan. We divided patients into subgroups of CS related to acute myocardial infarction (AMI-CS) or heart failure (HF-CS). The outcome was all-cause 30-day mortality. We built the prediction model based on the hazard ratio of significant variables, and the cutoff point of each predictor was determined using the Youden index. We also assessed the discrimination ability of the risk score using the area under a receiver operating characteristic curve. Results: We enrolled 225 patients with CS. One hundred and seven patients (47.6%) were due to AMI-CS, and ninety-eight patients among them received reperfusion therapy. Forty-nine patients (21.8%) eventually died within 30 days. Fifty-three patients (23.55%) presented with platelet counts < 155 × 103/μL, which were negatively associated with a 30-day mortality of CS in the restrictive cubic spline plot, even within the normal range of platelet counts. We identified four predictors: platelet counts < 200 × 103/μL (HR 2.574, 95% CI 1.379–4.805, p = 0.003), left ventricular ejection fraction (LVEF) < 40% (HR 2.613, 95% CI 1.020–6.692, p = 0.045), age > 71 years (HR 2.452, 95% CI 1.327–4.531, p = 0.004), and lactate > 2.7 mmol/L (HR 1.967, 95% CI 1.069–3.620, p = 0.030). The risk score ended with a maximum of 5 points and showed an AUC (95% CI) of 0.774 (0.705–0.843) for all patients, 0.781 (0.678–0.883), and 0.759 (0.662–0.855) for AMI-CS and HF-CS sub-groups, respectively, all p < 0.001. Conclusions: Based on four parameters, platelet counts, LVEF, age, and lactate (PEAL), this model showed a good predictive performance for all-cause mortality at 30 days in the all patients, AMI-CS, and HF-CS subgroups. The restrictive cubic spline plot showed a significantly negative correlation between initial platelet counts and 30-day mortality risk in the AMI-CS and HF-CS subgroups.</jats:p>
SDGs

[SDGs]SDG3

Publisher
MDPI AG
Type
journal-article
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