Infection and drug resistance · 2026
Risk Factors and Predictive Value of Sepsis in Patients with Liver Abscess.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
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.
Ma Xiaoyan, Chen Yanni, An Xing, Zhang Jie, Ma Xigang
Аннотация
OBJECTIVE: To investigate the factors associated with sepsis in patients with liver abscess (LA) and assess their predictive value for the early identification of high-risk patients.
METHODS: Clinical data from 798 patients with LA were retrospectively analyzed. LA was diagnosed according to established diagnostic criteria, and sepsis was defined according to the Sepsis-3 criteria. Patients were divided into a sepsis group (n = 558) and a non-sepsis group (n = 240). Baseline characteristics, laboratory parameters, microbiological features, treatment details, and clinical outcomes were compared between the two groups. Multivariable logistic regression analysis was performed to identify factors associated with sepsis, and receiver operating characteristic (ROC) curve analysis was used to evaluate their predictive value.
RESULTS: Patients in the sepsis group were younger and had a higher prevalence of hepatobiliary surgery history and a higher incidence of jaundice than those in the non-sepsis group (P < 0.05). Multivariable logistic regression analysis showed that a history of hepatobiliary surgery, elevated serum creatinine (Cr), elevated total bilirubin (TBIL), and decreased platelet count (PLT) were independently associated with sepsis (P < 0.05). ROC curve analysis indicated that TBIL, Cr, and PLT each had predictive value, and their combination demonstrated the best predictive performance (AUC = 0.848). In addition, patients in the sepsis group had a longer hospital stay and a higher 28-day mortality rate (P < 0.05).
CONCLUSION: Sepsis in patients with LA is closely associated with a history of hepatobiliary surgery, elevated Cr and TBIL levels, and decreased PLT. A combined predictive model based on TBIL, Cr, and PLT demonstrated good discriminative ability and may facilitate the early identification of patients at high risk of sepsis, thereby supporting risk stratification and clinical decision-making.
METHODS: Clinical data from 798 patients with LA were retrospectively analyzed. LA was diagnosed according to established diagnostic criteria, and sepsis was defined according to the Sepsis-3 criteria. Patients were divided into a sepsis group (n = 558) and a non-sepsis group (n = 240). Baseline characteristics, laboratory parameters, microbiological features, treatment details, and clinical outcomes were compared between the two groups. Multivariable logistic regression analysis was performed to identify factors associated with sepsis, and receiver operating characteristic (ROC) curve analysis was used to evaluate their predictive value.
RESULTS: Patients in the sepsis group were younger and had a higher prevalence of hepatobiliary surgery history and a higher incidence of jaundice than those in the non-sepsis group (P < 0.05). Multivariable logistic regression analysis showed that a history of hepatobiliary surgery, elevated serum creatinine (Cr), elevated total bilirubin (TBIL), and decreased platelet count (PLT) were independently associated with sepsis (P < 0.05). ROC curve analysis indicated that TBIL, Cr, and PLT each had predictive value, and their combination demonstrated the best predictive performance (AUC = 0.848). In addition, patients in the sepsis group had a longer hospital stay and a higher 28-day mortality rate (P < 0.05).
CONCLUSION: Sepsis in patients with LA is closely associated with a history of hepatobiliary surgery, elevated Cr and TBIL levels, and decreased PLT. A combined predictive model based on TBIL, Cr, and PLT demonstrated good discriminative ability and may facilitate the early identification of patients at high risk of sepsis, thereby supporting risk stratification and clinical decision-making.