- The Significance of the Strong Ion Gap in Predicting Acute Kidney Injury and In-hospital Mortality in Critically Ill Patients with Acute Poisoning
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Tae Jin Sim, Jae Wan Cho, Mi Jin Lee, Haewon Jung, Jungbae Park, Kang Suk Seo
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J Korean Soc Clin Toxicol. 2021;19(2):72-82. Published online December 31, 2021
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DOI: https://doi.org/10.22537/jksct.2021.19.2.72
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Abstract
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- Purpose: A high anion gap (AG) is known to be a significant risk factor for serious acid-base imbalances and death in acute poisoning cases. The strong ion difference (SID), or strong ion gap (SIG), has recently been used to predict in-hospital mortality or acute kidney injury (AKI) in patients with systemic inflammatory response syndrome. This study presents a comprehensive acid-base analysis in order to identify the predictive value of the SIG for disease severity in severe poisoning. Methods: A cross-sectional observational study was conducted on acute poisoning patients treated in the emergency intensive care unit (ICU) between December 2015 and November 2020. Initial serum electrolytes, base deficit (BD), AG, SIG, and laboratory parameters were concurrently measured upon hospital arrival and were subsequently used along with Stewart's approach to acid-base analysis to predict AKI development and in-hospital death. The area under the receiver operating characteristic curve (AUC) and logistic regression analysis were used as statistical tests. Results: Overall, 343 patients who were treated in the intensive care unit were enrolled. The initial levels of lactate, AG, and BD were significantly higher in the AKI group (n=62). Both effective SID [SIDe] (20.3 vs. 26.4 mEq/L, p<0.001) and SIG (20.2 vs. 16.5 mEq/L, p<0.001) were significantly higher in the AKI group; however, the AUC of serum SIDe was 0.842 (95% confidence interval [CI]=0.799-0.879). Serum SIDe had a higher predictive capacity for AKI than initial creatinine (AUC=0.796, 95% CI=0.749-0.837), BD (AUC=0.761, 95% CI=0.712-0.805), and AG (AUC=0.660, 95% CI=0.607-0.711). Multivariate logistic regression analyses revealed that diabetes, lactic acidosis, high SIG, and low SIDe were significant risk factors for in-hospital mortality. Conclusion: Initial SIDe and SIG were identified as useful predictors of AKI and in-hospital mortality in intoxicated patients who were critically ill. Further research is necessary to evaluate the physiological nature of the toxicant or unmeasured anions in such patients.
- Discrepancies and Validation of Ethanol Level Determination with Osmolar Gap Formula in Patients with Suspected Acute Poisoning
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Haewon Jung, Mi Jin Lee, Jae Wan Cho, Jae Yun Ahn, Changho Kim
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J Korean Soc Clin Toxicol. 2019;17(2):47-57. Published online December 31, 2019
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DOI: https://doi.org/10.22537/jksct.2019.17.2.47
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Abstract
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- Purpose: Osmolar gap (OG) has been used for decades to screen for toxic alcohol levels. However, its reliability may vary due to several reasons. We validated the estimated ethanol concentration formula for patients with suspected poisoning and who visited the emergency department. We examined discrepancies in the ethanol level and patient characteristics by applying this formula when it was used to screen for intoxication due to toxic levels of alcohol. Methods: We retrospectively reviewed 153 emergency department cases to determine the measured levels of toxic ethanol ingestion and we calculated alcohol ingestion using a formula based on serum osmolality. Those patients who were subjected to simultaneous measurements of osmolality, sodium, urea, glucose, and ethanol were included in this study. Patients with exposure to other toxic alcohols (methanol, ethylene glycol, or isopropanol) or poisons that affect osmolality were excluded. OG (the measured-calculated serum osmolality) was used to determine the calculated ethanol concentration. Results: Among the 153 included cases, 114 had normal OGs (OG≤14 mOsm/kg), and 39 cases had elevated OGs (OG>14). The mean difference between the measured and estimated (calculated ethanol using OG) ethanol concentration was -9.8 mg/dL. The 95% limits of agreement were -121.1 and 101.5 mg/dL, and the correlation coefficient R was 0.7037. For the four subgroups stratified by comorbidities and poisoning, the correlation coefficients R were 0.692, 0.588, 0.835, and 0.412, respectively, and the mean differences in measurement between the measured and calculated ethanol levels were -2.4 mg/dL, -48.8 mg/dL, 9.4 mg/dL, and -4.7 mg/dL, respectively. The equation plots had wide limits of agreement. Conclusion: We found that there were some discrepancies between OGs and the calculated ethanol concentrations. Addition of a correction factor for unmeasured osmoles to the equation of the calculated serum osmolality would help mitigate these discrepancies.
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