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链球菌血流感染患者预后因素的识别

Identification of Prognostic Factors in Patients With Streptococcus Bloodstream Infection.

作者信息

Duan Xiaoguang, Zhang Ruifang, Zhang Xiaojuan, Ding Xianfei, Sun Tongwen

机构信息

General ICU, Henan Key Laboratory of Critical Care Medicine, Zhengzhou Key Laboratory of Sepsis, Henan Engineering Research Center for Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

出版信息

Front Med (Lausanne). 2022 Apr 26;9:832007. doi: 10.3389/fmed.2022.832007. eCollection 2022.

DOI:10.3389/fmed.2022.832007
PMID:35559342
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9087728/
Abstract

AIM

The purpose of this study was to explore prognostic factors of bloodstream infections (BSIs), a common severe infection and a major cause of mortality worldwide, so as to construct a prognosis model of patients with BSI.

MATERIALS AND METHODS

Clinical and biochemical test data were obtained retrospectively from the medical records of 562 patients with BSI who had been treated at a single center; the end point was 60 days of all-cause death. The chi-square test was used to compare the mortality of patients grouped by the types of antibiotic treatment. The logistic regression analysis was adopted to identify prognostic factors; the Kaplan-Meier survival curve and log-rank test were conducted to compare the survival rate of patients with different prognostic factors; the receiver operating characteristic (ROC) curve was used to estimate the predictive value of different prognostic factors.

RESULTS

Of the 562 patients, 455 survived (80.96%), and 107 died (19.04%). The mortality rate of patients treated with a combination of antibiotics (25.40%) was higher than that treated with a single antibiotic (15.82%). Univariate analysis identified 19 prognostic factors for patients with BSI, including gender, age, diabetes, malignant tumor (non-blood system), total hospitalization time, alanine aminotransferase, aspartate aminotransferase, total protein, albumin, total bilirubin, direct bilirubin, creatinine, ratio of granulocytes, fibrinogen, D-dimer, platelet, C-reactive protein, shock, and respiratory failure ( < 0.05). Multivariate analysis indicated that albumin (odds ratio [OR] = 0.94, 95% confidence interval [CI]: 0.89-0.99), fibrinogen (OR = 0.61, 95%CI: 0.46-0.82), shock (OR = 16.61, 95%CI: 7.00-39.41), and respiratory failure (OR = 47.53, 95%CI: 19.93-133.64) were independent factors. The combination of four indicators demonstrated a favorable predictive value for the 60-day outcome of patients with BSI, with an area under the ROC of 0.96 (95%CI: 0.94-0.99), sensitivity of 90.65%, specificity of 94.95%, and accuracy of 94.13%.

CONCLUSIONS

Shock, respiratory failure, albumin, and fibrinogen are potential independent prognostic factors for 60-day mortality.

摘要

目的

本研究旨在探索血流感染(BSIs)的预后因素,血流感染是一种常见的严重感染,也是全球范围内主要的死亡原因,以便构建血流感染患者的预后模型。

材料与方法

回顾性收集了在单一中心接受治疗的562例血流感染患者的病历中的临床和生化检测数据;终点为全因死亡60天。采用卡方检验比较按抗生素治疗类型分组的患者死亡率。采用逻辑回归分析确定预后因素;采用Kaplan-Meier生存曲线和对数秩检验比较不同预后因素患者的生存率;采用受试者工作特征(ROC)曲线评估不同预后因素的预测价值。

结果

562例患者中,455例存活(80.96%),107例死亡(19.04%)。联合使用抗生素治疗的患者死亡率(25.40%)高于使用单一抗生素治疗的患者(15.82%)。单因素分析确定了19个血流感染患者的预后因素,包括性别、年龄、糖尿病、恶性肿瘤(非血液系统)、总住院时间、丙氨酸氨基转移酶、天冬氨酸氨基转移酶、总蛋白、白蛋白、总胆红素、直接胆红素、肌酐、粒细胞比例、纤维蛋白原、D-二聚体、血小板、C反应蛋白、休克和呼吸衰竭(P<0.05)。多因素分析表明,白蛋白(比值比[OR]=0.94,95%置信区间[CI]:0.89-0.99)、纤维蛋白原(OR=0.61,95%CI:0.46-0.82)、休克(OR=16.61,95%CI:7.00-39.41)和呼吸衰竭(OR=47.53,95%CI:19.93-133.64)是独立因素。这四个指标的组合对血流感染患者60天的预后具有良好的预测价值,ROC曲线下面积为0.96(95%CI:0.94-0.99),敏感性为90.65%,特异性为94.95%,准确性为94.13%。

结论

休克、呼吸衰竭、白蛋白和纤维蛋白原是60天死亡率的潜在独立预后因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3121/9087728/0d42cca81b7d/fmed-09-832007-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3121/9087728/16d4cd805b6f/fmed-09-832007-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3121/9087728/e7ea4f7277b9/fmed-09-832007-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3121/9087728/0d42cca81b7d/fmed-09-832007-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3121/9087728/16d4cd805b6f/fmed-09-832007-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3121/9087728/e7ea4f7277b9/fmed-09-832007-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3121/9087728/0d42cca81b7d/fmed-09-832007-g0003.jpg

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