ArticlePloS one2019
Development of a risk prediction model (Hangang) and comparison with clinical severity scores in burn patients.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- Longitudinal analysis of ARDS variability and biomarker predictive power in burn patients.Scientific reports · 2024Article
- Advanced biomarker clustering analysis reveals mortality predictors in burn patients with sepsis.Scientific reports · 2024Article
- Deciphering AKI in Burn Patients: Correlations between Clinical Clusters and Biomarkers.International journal of molecular sciences · 2024Article
- A deep dive into burn-mediated ARDS severity assessment: a retrospective study on hematological markers.Scientific reports · 2024Article
- Big data insights into the diagnostic values of CBC parameters for sepsis and septic shock in burn patients: a retrospective study.Scientific reports · 2024Article
- [Research advances on prognosis-related forecasting models for burn patients].Zhonghua shao shang yu chuang mian xiu fu za zhi · 2023Article
- Tracking longitudinal biomarkers in burn patients with sepsis and acute kidney injury: an unsupervised clustering approach.European journal of medical research · 2023Article
- Evaluating clinical heterogeneity and predicting mortality in severely burned patients through unsupervised clustering and latent class analysis.Scientific reports · 2023Article
- External Validation of Three Burn-Specific Mortality Prediction Models in Adult Burn Patients at a Tertiary Care Hospital in India.Indian journal of plastic surgery : official publication of the Association of Plastic Surgeons of India · 2023Article
- Longitudinal profile of routine biomarkers for mortality prediction using unsupervised clustering algorithm in severely burned patients: a retrospective cohort study with prospectively collected data.Annals of surgical treatment and research · 2023Article
- The clinical differentiation of blood culture-positive and -negative sepsis in burn patients: a retrospective cohort study.Burns & trauma · 2023Article
- The analysis and accuracy of mortality prediction scores in burn patients admitted to the intensive care burn unit (ICBU).Annals of medicine and surgery (2012) · 2021Article
- Time-varying discrimination accuracy of longitudinal biomarkers for the prediction of mortality compared to assessment at fixed time point in severe burns patients.BMC emergency medicine · 2021Article
- Trajectories of longitudinal biomarkers for mortality in severely burned patients.Scientific reports · 2020Article
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8 authors.
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Abstract
purposeThe purpose of this study was to develop a new prediction model to reflect the risk of mortality and severity of disease and to evaluate the ability of the developed model to predict mortality among adult burn patients.
methodsThis study included 2009 patients aged more than 18 years who were admitted to the intensive care unit (ICU) within 24 hours after a burn. We divided the patients into two groups; those admitted from January 2007 to December 2013 were included in the derivation group and those admitted from January 2014 to September 2017 were included in the validation group. Shrinkage methods with 10-folds cross-validation were performed to identify variables and limit overfitting of the model. The discrimination was analyzed using the area under the curve (AUC) of the receiver operating characteristic curve. The Brier score, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were also calculated. The calibration was analyzed using the Hosmer-Lemeshow goodness-of-fit test (HL test). The clinical usefulness was evaluated using a decision-curve analysis.
resultsThe Hangang model showed good calibration with the HL test (χ2 = 8.785, p = 0.361); the highest AUC and the lowest Brier score were 0.943 and 0.068, respectively. The NRI and IDI were 0.124 (p-value = 0.003) and 0.079 (p-value <0.001) when compared with FLAMES, respectively.
conclusionsThis model reflects the current risk factors of mortality among adult burn patients. Furthermore, it was a highly discriminatory and well-calibrated model for the prediction of mortality in this cohort.
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