Abstract：
In this study, we aimed to evaluate the death risk factors of patients included in the sepsis protocol bundle, using clinical data from qSOFA, SIRS, and comorbidities, as well as development of a mortality risk score.
This retrospective cohort study was conducted between 2016 and 2021.
Two university hospitals in Brazil.
Patients with sepsis.
Several clinical and laboratory data were collected focused on SIRS, qSOFA, and comorbidities.
In-hospital mortality was the primary outcome variable. A mortality risk score was developed after logistic regression analysis.
A total of 1,808 patients were included with a death rate of 36%. Ten variables remained independent factors related to death in multivariate analysis: temperature ≥38 °C (odds ratio [OR] = 0.65), previous sepsis (OR = 1.42), qSOFA ≥ 2 (OR = 1.43), leukocytes >12,000 or <4,000 cells/mm3 (OR = 1.61), encephalic vascular accident (OR = 1.88), age >60 years (OR = 1.93), cancer (OR = 2.2), length of hospital stay before sepsis >7 days (OR = 2.22,), dialysis (OR = 2.51), and cirrhosis (OR = 3.97). Considering the equation of the binary regression logistic analysis, the score presented an area under curve of 0.668, is not a potential model for death prediction.
Several risk factors are independently associated with mortality, allowing the development of a prediction score based on qSOFA, SIRS, and comorbidities data, however, the performance of this score is low.
This retrospective cohort study was conducted between 2016 and 2021.
Two university hospitals in Brazil.
Patients with sepsis.
Several clinical and laboratory data were collected focused on SIRS, qSOFA, and comorbidities.
In-hospital mortality was the primary outcome variable. A mortality risk score was developed after logistic regression analysis.
A total of 1,808 patients were included with a death rate of 36%. Ten variables remained independent factors related to death in multivariate analysis: temperature ≥38 °C (odds ratio [OR] = 0.65), previous sepsis (OR = 1.42), qSOFA ≥ 2 (OR = 1.43), leukocytes >12,000 or <4,000 cells/mm3 (OR = 1.61), encephalic vascular accident (OR = 1.88), age >60 years (OR = 1.93), cancer (OR = 2.2), length of hospital stay before sepsis >7 days (OR = 2.22,), dialysis (OR = 2.51), and cirrhosis (OR = 3.97). Considering the equation of the binary regression logistic analysis, the score presented an area under curve of 0.668, is not a potential model for death prediction.
Several risk factors are independently associated with mortality, allowing the development of a prediction score based on qSOFA, SIRS, and comorbidities data, however, the performance of this score is low.
摘要：
目的：在本研究中，我们的目的是评估脓毒症方案中患者的死亡危险因素，使用来自qSOFA的临床数据，SIRS,和合并症，以及死亡风险评分的发展。
方法：这项回顾性队列研究于2016年至2021年进行。
方法：巴西的两家大学医院。
方法：败血症患者。
方法：收集了一些临床和实验室数据，重点是SIRS，qSOFA,和合并症。
■住院死亡率是主要结局变量。Logistic回归分析后得出死亡风险评分。
结果：共纳入1,808例患者，死亡率为36%。在多变量分析中，十个变量仍然是与死亡相关的独立因素：温度≥38°C（比值比[OR]=0.65），既往脓毒症（OR=1.42），qSOFA≥2（OR=1.43），白细胞>12,000或<4,000个细胞/mm3（OR=1.61），脑血管意外（OR=1.88），年龄>60岁（OR=1.93），癌症（OR=2.2），脓毒症前住院时间>7天（OR=2.22，），透析（OR=2.51），和肝硬化（OR=3.97）。考虑二元回归逻辑分析的方程，该评分的曲线下面积为0.668,不是预测死亡的潜在模型.
结论：几个危险因素与死亡率独立相关，允许基于qSOFA开发预测分数，SIRS,和合并症数据，然而,这个分数的表现很低。
方法：这项回顾性队列研究于2016年至2021年进行。
方法：巴西的两家大学医院。
方法：败血症患者。
方法：收集了一些临床和实验室数据，重点是SIRS，qSOFA,和合并症。
■住院死亡率是主要结局变量。Logistic回归分析后得出死亡风险评分。
结果：共纳入1,808例患者，死亡率为36%。在多变量分析中，十个变量仍然是与死亡相关的独立因素：温度≥38°C（比值比[OR]=0.65），既往脓毒症（OR=1.42），qSOFA≥2（OR=1.43），白细胞>12,000或<4,000个细胞/mm3（OR=1.61），脑血管意外（OR=1.88），年龄>60岁（OR=1.93），癌症（OR=2.2），脓毒症前住院时间>7天（OR=2.22，），透析（OR=2.51），和肝硬化（OR=3.97）。考虑二元回归逻辑分析的方程，该评分的曲线下面积为0.668,不是预测死亡的潜在模型.
结论：几个危险因素与死亡率独立相关，允许基于qSOFA开发预测分数，SIRS,和合并症数据，然而,这个分数的表现很低。
