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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Prognostic Factors in Acute Aluminium Phosphide Poisoning: A Risk-Prediction Nomogram Approach
Esmaeil Farzaneh1, Hassan Ghobadi2, Mahdieh Akbarifard2
1Department of Forensic Medicine and Toxicology, Faculty of Medicine, Ardabil University of Medical Sciences, Ardabil, Iran.
Abstract:
Aluminium phosphide (AlP) is a toxic agent associated with a high mortality rate following acute exposure from various routes. The aim of this study was to determine the clinical and laboratory findings useful for predicting the medical outcome of AlP-poisoned patients using established scoring systems. This is a prospective study of AlP-poisoned patients from 2010 to 2015 in Ardabil, Iran. All patients that presented with a confirmed diagnosis of acute AlP poisoning in the study interval were included in the study. Clinical and laboratory data, using Acute Physiology and Chronic Health Evaluation II (APACHE II), Sequential Organ Failure Assessment (SOFA) and Simplified Acute Physiology Score II (SAPS II) scoring systems, were compared for their predictive value in determining differences between survived and non-survived patients. Univariate analysis (Mann-Whitney or t-test), multiple logistic regression analysis, receiver operating characteristic (ROC) curve analysis and the Pearson correlation test were performed using STATA/SE 13.0 and the Nomolog Software. A total of 68 AlP-poisoned patients with confirmed acute AlP poisoning were included for evaluation. Of these, 36 were non-survived. Multiple logistic regression analysis was performed using parameters and values derived from patient clinical and laboratory data, and revealed that four factors were significant for predicting mortality: Glasgow coma score (GCS); systolic blood pressure (SBP); urinary output (UOP); and serum HCO3 . A four-variable, risk-prediction nomogram was developed for identifying high-risk patients and predicting the risk of mortality. Study results showed that SBP of <92.5 mmHg (p = 0.006); HCO3- < 12.9 mEq/L (p = 0.01), UOP < 1725 mL/day (p = 0.04); and GCS < 14.5 (p = 0.003) were significant predictors of AlP mortality. Scoring systems analysis showed SAPS II score >24.5, APACHE II score >8.5 and SOFA score >7.5 were predictive of non-survival patients. The results of our study showed that SBP, GCS, UOP and serum HCO3 levels are the best prognostic factors for predicting mortality in AlP-poisoned patients. According to the area under the ROC curve of the APACHE II score, when compared with SOFA and SAPS II scores, the APACHE II score can more effectively discriminate between non-survivors and survived patients.
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