Development of a predictive model for septic shock-associated acute skin failure using readily available clinical variables

利用易于获得的临床变量,建立脓毒性休克相关急性皮肤衰竭的预测模型

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Abstract

BACKGROUND: Acute skin failure (ASF) is an understudied complication in patients with septic shock, and existing predictive models lack disease-specific variables. This study aimed to investigate the characteristics of cutaneous manifestations in patients with septic shock and to identify potential biomarkers and predictive factors for cutaneous deterioration. METHODS: This retrospective cohort study analysed 154 adult patients with septic shock, defined according to the Sepsis 3.0 criteria, who were admitted to a tertiary intensive care unit (ICU) between September 2020 and September 2022. Based on cutaneous manifestations observed during hospitalisation, the patients were stratified into two groups: the ASF group and the non-ASF group. Clinical characteristics, therapeutic interventions and laboratory parameters were evaluated. Significant univariate predictors were included in multivariable logistic regression. A p-value below 0.05 was considered statistically significant. RESULTS: This study enrolled a total of 154 patients with septic shock, among whom 49 developed ASF, yielding an incidence rate of 31.8%. In the multivariate analysis, four independent predictors were identified: maximum norepinephrine (NE) dose (odds ratio [OR] = 2.47, p = 0.051), NE duration (OR = 1.19, p = 0.054), central venous oxygen saturation (ScvO₂) (OR = 0.97, p = 0.042) and absence of oedema (OR = 0.18, p = 0.008). The model achieved an area under the curve of 0.803 (95% CI: 0.730-0.876) with 72.3% sensitivity and 72.4% specificity at the optimal cut-off. CONCLUSIONS: The validated prediction model identifies patients with septic shock who are at high risk for ASF using four readily available clinical parameters: maximum NE dose, NE duration, ScvO₂ and absence of oedema, helping clinicians provide early warning and thereby reduce associated skin complications. CLINICAL TRIAL NUMBER: Not applicable.

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