Clinical Value of Serum S100A12 in Identifying ARDS Development and Predicting Deterioration in Critically Ill Patients

Author:

Liu Wei1,Ji Dandan2,Zhan Xingping3,Lu Mengshi3,Xu Hao2,Zhu Zigang2,Chen Hongyu3,Ma Jiawei2,Luo Liang2

Affiliation:

1. Jiangnan University

2. Wuxi No.2 People's Hospital

3. Nanjing Medical University

Abstract

Abstract

Objective This study aimed to investigate the clinical value of serum S100A12 in identifying the development of acute respiratory distress syndrome (ARDS), its association with subsequent oxygenation deterioration, and its ability to predict 28-day mortality in patients in the intensive care unit (ICU). Methods Based on the inclusion and exclusion criteria, the demographic data, chronic diseases, and acute physiological indices of ICU patients were collected from two independent general ICUs in the Department of Critical Care Medicine, Jiangnan University Medical Center. Serum S100A12 levels were measured at different time points using an enzyme-linked immunosorbent assay. TS100A12 was derived from serum S100A12 levels and converted to an inverse tangent function in our study. Patients meeting the Berlin definition of ARDS within three days of admission were categorised into ARDS and non-ARDS groups. The ARDS group was further divided into two groups based on the PF (PaO2/FiO2) value at the time of diagnosis: PF < 150 mmHg and PF > 150 mmHg groups. To verify the correlation between serum S100A12 levels and oxygenation deterioration, three grouping sets based on the decrease rate in the oxygenation index within 4 days after ARDS diagnosis were used for substantial analysis: PF decrease rate < 30% group vs. PF decrease rate ≥ 30% group, PF decrease rate < 35% group vs. PF decrease rate ≥ 35% group, and PF decrease rate < 40% group vs. PF decrease rate ≥ 40% group. Additionally, to verify the correlation between serum S100A12 levels and 28-day mortality in patients with ARDS, the ARDS group was divided into survival and non-survival groups. Spearman’s correlation analysis was used to assess the association between indicators, logistic regression analysis was used to determine the odds ratios, and receiver operating characteristic curve analysis was used to evaluate predictive efficacy. Results A total of 144 patients were enrolled in this study from 1 August 2022 to 15 December 2022. At the time of ARDS diagnosis, serum S100A12 levels were significantly higher than those in patients without ARDS, and TS100A12 was identified as a risk factor for the development of ARDS. At the time of ARDS diagnosis, the serum S100A12 levels were significantly higher in the PF < 150 mmHg group than in the PF > 150 mmHg group. Additionally, after ARDS diagnosis, serum S100A12 levels were significantly higher in the group with a higher rate of PF decrease. The PF decrease rate within 4 days was greater with higher serum S100A12 levels at the time of ARDS diagnosis. Additionally, TS100A12 and age were independent risk factors of 28-day mortality, and the combination of serum S100A12 levels and age exhibited a high degree of predictive accuracy for 28-day mortality in patients with ARDS. Conclusion TS100A12 is a risk factor of ARDS and 28-day mortality. Serum S100A12 levels were associated with a decline in oxygenation within four days of ARDS diagnosis. Additionally, the combination of serum S100A12 levels and age exhibited high efficacy in predicting 28-day mortality.

Publisher

Springer Science and Business Media LLC

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