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DOI 10.1371/journal.pone.0339873

Медицинская библиотека · PloS one · 2026

The relationship between Braden Skin Score (BSS) and the risk of acute respiratory distress syndrome in elderly sepsis patients: An analysis based on the MIMIC-IV database.

Xiao Yingqi, Cao Yi, Guo Jianwen, Shu Liufang, Xu Jingcheng, Li Zhiyong, Li Yongchun

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Аннотация

OBJECTIVE

The Braden Skin Score (BSS) is a validated tool for assessing pressure injury risk. This study aimed to investigate whether BSS can also predict the risk of developing Acute Respiratory Distress Syndrome (ARDS) in elderly sepsis patients in the intensive care unit (ICU).

BACKGROUND

ARDS is a common and serious complication in ICU patients with sepsis, associated with prolonged hospitalization, metabolic disorders, and increased mortality. Elderly sepsis patients are particularly vulnerable to pressure injuries due to prolonged bed rest. Nevertheless, the relationship between BSS and the risk of developing ARDS in this population has not been extensively studied.

METHODS

Elderly sepsis patients from the MIMIC-IV database were chosen and partitioned into quartiles of BSS values. Although the incidence of ARDS was the primary endpoint, hospital mortality in the ARDS subgroup was the secondary endpoint. The correlation between low BSS and risk of ARDS and in-hospital mortality in elderly sepsis patients was assessed using logistic regression models.

RESULTS

Multivariate logistic regression analysis revealed that a lower BSS at ICU admission was significantly associated with an increased risk of ARDS and higher in-hospital mortality among elderly sepsis patients.

CONCLUSION

This study demonstrates that a low BSS at ICU admission is associated with a greater risk of ARDS and higher in-hospital mortality in elderly sepsis patients.

Для цитирования: Xiao Yingqi, Cao Yi, Guo Jianwen, Shu Liufang, Xu Jingcheng, Li Zhiyong, Li Yongchun. The relationship between Braden Skin Score (BSS) and the risk of acute respiratory distress syndrome in elderly sepsis patients: An analysis based on the MIMIC-IV database.. PloS one. 2026. DOI: 10.1371/journal.pone.0339873.

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