MedElevator Войти в исследования
← Поиск публикаций

DOI 10.3389/fpubh.2024.1475292

Медицинская библиотека · Frontiers in public health · 2024

Analysis of risk factors for sepsis-related liver injury and construction of a prediction model.

He Yong, Wang Chi, He Wan, Zhang He, Ding Fei, Liu Ying, He He, Ying Binwu, Nie Xin

СтатьяПеревод в очереди

Аннотация

BACKGROUND

Sepsis is a leading cause of mortality in critically ill patients, and the liver is a key organ affected by sepsis. Sepsis-related liver injury (SRLI) is an independent risk factor for multiple organ dysfunction syndrome (MODS) and mortality. However, there is no clear diagnostic standard for SRLI, making early detection and intervention challenging.

OBJECTIVE

This study aimed to investigate the predictive value of serum indices for the occurrence of SRLI in adults to guide clinical practice.

METHODS

In this study, we investigated the predictive value of serum indices for SRLI in adults. We retrospectively analyzed data from 1,573 sepsis patients admitted to West China Hospital, Sichuan University, from January 2015 to December 2019. Patients were divided into those with and without liver injury. Stepwise logistic regression identified independent risk factors for SRLI, and a predictive model was constructed. The model's diagnostic efficacy was assessed using receiver operating characteristic (ROC) curve analysis.

RESULTS

Our results showed that alanine aminotransferase (ALT), gamma-glutamyl transpeptidase (GGT), carbon dioxide combining power (CO2-CP), antithrombin III (AT III), fibrin/fibrinogen degradation products (FDP), and red blood cell distribution width (RDW-CV) were independent predictors of SRLI. The area under the curve (AUC) of the predictive model was 0.890, with a sensitivity of 80.0% and a specificity of 82.91%, indicating excellent diagnostic value.

CONCLUSION

In conclusion, this study developed a highly accurate predictive model for SRLI using clinically accessible serum indicators, which could aid in early detection and intervention, potentially reducing mortality rates.

Для цитирования: He Yong, Wang Chi, He Wan, Zhang He, Ding Fei, Liu Ying, He He, Ying Binwu, Nie Xin. Analysis of risk factors for sepsis-related liver injury and construction of a prediction model.. Frontiers in public health. 2024. DOI: 10.3389/fpubh.2024.1475292.

Предметные рубрики MeSH

Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.