Risk Factors and Predictors of Sepsis Complicated with ARDS: A Meta-analysis

JIN Yali; JIE Zhiqian; FAN Xianming

doi:10.13718/j.cnki.xdzk.2025.03.015

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A meta-analysis was conducted to evaluate the risk factors and predictors of sepsis complicated with acute respiratory distress syndrome (ARDS) in patients. Relevant studies on sepsis complicated by ARDS were retrieved from following databases: CNKI, Wanfang Data Knowledge Service Platform, VIP, Sinomed, PubMed, EMBASE, Web of Science and the Cochrane Library. The searched period was from January 1, 2016 to August 15, 2024. The search English terms included Sepsis, Acute respiratory distress syndrome, Risk factors, Prevalence, Incidence, Mortality, and Biomarkers. Statistical analysis was performed using Stata SE 15.1 software. A total of 35 studies were included, involving 3 715 patients with sepsis complicated by ARDS. The results indicated that the overall incidence of ARDS in patients with sepsis was 28.8%. In the analyzed risk factors, age, smoking history, pulmonary infection, comorbid chronic obstructive pulmonary disease (COPD), pancreatitis, shock, APACHE Ⅱ score, SOFA score, serum lactate, and serum HMGB1 were all found to be significantly associated with the development of ARDS in sepsis. Regarding to the predictive markers, the APACHE Ⅱ score, SOFA score, C-reactive protein (CRP), and PaO₂/FiO₂ ratio demonstrated significant predictive value. In summary, the incidence of sepsis complicated with ARDS is relatively high, and many risk factors are associated with the increase of the likelihood of its occurrence.

Corresponding author: FAN Xianming

Received Date: 18/11/2024

Available Online: 20/03/2025

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脓毒症(Sepsis)是一种由严重感染引发的全身性炎症反应综合征，可导致多器官功能损伤，并具有较高的病死率^[1]。急性呼吸窘迫综合征(Acute Respiratory Distress Syndrome，ARDS)是一种常见且严重的并发症，其特征是由肺内或肺外因素引发的急性、弥漫性炎症性肺损伤，组织学特征包括肺泡水肿、炎症反应、透明膜形成和肺泡出血^[2]。脓毒症是引起ARDS的主要原因之一，可通过释放炎症介质，损害全身血管并破坏肺部毛细血管内皮细胞，同时激活肺部免疫细胞，加剧肺损伤，最终导致ARDS的发生^[3]。多项研究表明，年龄、吸烟史、感染严重程度以及基础疾病等因素均可能增加脓毒症患者发生ARDS的风险^[4-6]。在预测指标方面，APACHEⅡ和SOFA评分已被广泛应用，APACHEⅡ评分通过综合急性生理指标和基础健康状况，从而反映患者的疾病严重程度；SOFA评分则侧重于多器官功能障碍的评估，尤其在脓毒症相关肺损伤的早期识别中具有重要意义^[7-8]。此外，一些传统的生物标志物(如C反应蛋白和降钙素原)在脓毒症引发ARDS的预测和识别中也同样具有意义^[9]。随着检测技术的进步，研究人员逐渐关注肺上皮损伤标志物的应用潜力，例如表面活性蛋白D(SPD)、晚期糖基化终末产物受体(RAGE)等新兴标志物在预测ARDS风险方面可能具有更高的准确性^[10]。鉴于目前尚无统一的危险因素评估标准和风险预测标准，且不同研究间结果差异较大，本研究运用Meta分析系统评价脓毒症并发ARDS(以下简称SA)的发病率、危险因素及相关指标的预测效能，旨在为临床早期干预和个体化治疗提供理论支持。

1. 材料与方法

1.1. 文献检索策略

计算机检索中国知网(以下简称知网)、万方数据知识服务平台(以下简称万方)、维普网(以下简称维普)、Sinomed、PubMed、EMBASE、Web of Science和Cochrane Library数据库，检索日期为2016年1月1日至2024年8月15日。中文主题检索词：脓毒症、脓毒血症、感染性休克、严重脓毒症、全身炎症反应综合征、急性呼吸窘迫综合征、危险因素、发病率、死亡率、患病率、炎症因子、标志物；英文主题检索词：Sepsis、Acute respiratory distress syndrome、Risk factors、Prevalence、Incidence、Mortality、Biomarkers以及相应的自由词。为确保文献的全面性，还检查了纳入研究及综述的参考文献，以搜寻可能遗漏的相关文献。

1.2. 研究选择

1) 纳入符合Sepsis-3标准的18岁以上非妊娠SA患者(以无ARDS的脓毒症患者作为对照组)，且伴随明确诊断为ARDS(符合柏林定义)。

2) 纳入涉及SA的发病率、危险因素或预测指标的观察性研究。

3) 纳入明确报告先发生脓毒症后并发ARDS的研究，排除未明确疾病先后顺序或因其他原因导致ARDS的研究。

4) 发病率(R_SA)的计算方法：

式中：N_ARDS为脓毒症发作后ARDS患者的发生数；N_脓毒症为符合诊断标准的脓毒症患者数量。

5) 纳入中英文研究，排除信件、综述、评论、摘要和社论。每项研究均由2名评价员独立评估合格性。评价员首先审阅标题和摘要，随后筛查符合纳入标准的全文。在评价过程中，任何分歧或不确定性均通过讨论协商一致解决。

1.3. 数据提取和质量评估

2名评价员单独提取资料并使用预定义的表格评估其质量，任何分歧都通过讨论或咨询第3位评价员来解决。提取的数据包括以下信息：第1作者姓名、地区、研究时间、研究类型、受试者的人口统计学特征、脓毒症例数、SA例数、SA的发病率、危险因素、预测指标。采用纽卡斯尔渥太华质量评估量表(NOS)评估每个队列或病例对照研究的质量。根据NOS评分，研究分为低、中等或高质量，评分为0~3、4~6和7~9。

1.4. 统计学分析

采用Stata SE 15.1软件进行统计分析，使用二分类变量和连续变量的合并比值比(S_OR)、标准均值差(S_MD)及相应的95%CI来权衡SA的危险因素及预测指标。对分析中涉及的中位数数据，将其转换为均值和标准差^[11-12]。采用I²和Q检验评估纳入研究的异质性，显著异质性定义为I²＞50%或Q检验p＜0.01。当存在显著异质性时，采用随机效应模型；反之，使用固定效应模型。应用亚组分析和Meta回归探讨发病率异质性的潜在来源，采用敏感性分析评估结果的稳健性。采用漏斗图和Egger线性回归评价纳入研究的发表偏倚，不对称漏斗图或Egger检验p＜0.05提示存在显著发表偏倚。若检测到显著发表偏倚，进一步使用“剪补法”探讨可能的“缺失研究”对合并效应估计的影响。

3. 讨论与结论

本研究系统性分析了SA的发病率及危险因素，提供了较为全面的流行病学数据和风险因素特征。总体上，SA的发病率为28.8%，然而研究间的异质性显著，Meta回归分析提示异质性主要源自小样本。在样本量较大的研究中，SA的发病率较高(43.7%)，考虑到小样本研究可能因统计效能较低导致发病率的低估，大样本研究覆盖更多患者群体，从而更接近真实水平的发病率。在2017-2019年，SA的发病率为19.2%，这一趋势可能反映出该时期诊疗手段的提升对控制SA的作用^[47]。地理差异影响了SA的发病率，欧美地区的发病率为24.5%，低于亚洲的29.7%。有研究表明，欧洲脓毒症的发生率相对别的地区较低，这种差异很可能与当地的种族构成和社会经济水平有关^[48]。亚组分析显示，65岁以上人群的SA发病率(24.9%)低于65岁以下人群。这一现象与老年人免疫衰老相关，免疫反应的减弱一定程度上减少了过度炎症的反应^[49-50]。

对13个SA危险因素进行分析，最终确定了10个与SA显著相关的危险因素。结果显示，年龄增长被证实为SA的一个显著危险因素，这与早期研究的结论相符^[51]。吸烟史、肺部感染、合并COPD、胰腺炎及休克状态均显著增加了SA的患病风险。这些因素可能通过增强炎症反应(如激活中性粒细胞、促炎性细胞因子的释放)和损害肺功能(如肺泡上皮细胞和内皮细胞的破坏、气体交换受限)等机制来促进ARDS的发生^[52-53]。此外，APACHEⅡ评分和SOFA评分也被认为是影响SA发病率的重要指标，特别是在APACHEⅡ评分超过17分时，SA的发病率显著上升至40.3%，SOFA评分在6.5~7.5的患者，发病率达到了35.7%。脓毒症患者较高的APACHEⅡ评分和SOFA评分，通常意味着患者的全身炎症反应更为剧烈、器官功能受损更为严重，从而提高了ARDS的发生风险^[54]。血清乳酸和血清HMGB1水平升高也与SA有关，这提示了代谢紊乱和炎症在其发病机制中的潜在作用^[55]。此外，CRP、PCT和IL-6与SA发病率相关性不大，可能是因为它们更多地反映了全身的炎症状态，未必直接与肺部特异性损伤相关^[56]，也可能是因为ARDS的发生，除了炎症因子风暴之外，还与氧化应激有关^[57]。

在本研究中，我们观察到APACHEⅡ评分(S_MD=2.39，95%CI为0.38~4.40)和SOFA评分(S_MD=0.74，95%CI为0.47~1.01)在SA预测中具有重要意义。除评分标准外，生物标志物也能对SA进行预测，SA患者的CRP水平显著升高，能够有效区分脓毒症患者和SA患者^[58]。这表明CRP作为一个早期指标，对脓毒症患者发生ARDS具有提示作用。考虑到单一指标可能因个体差异而预测能力有限，未来研究应探索将多种生物标志物组合应用于风险评估中，如联合使用RAGE、CXCL16、Ang-2和PaO₂/FiO₂等指标能很好地预测ARDS的发生风险^[25]。这种多个标志物联合模型有助于全面评估疾病的进展，优化早期干预策略。

本研究存在以下局限性：1)纳入的研究存在较大的异质性，尽管我们进行了详细的亚组分析，但多数组别的异质性仍然较高。2)部分预测指标数据较为有限，可能导致预测估计存在不确定性。3)本研究主要纳入了来自亚洲、欧洲和美洲的研究，缺乏其他地区的数据，可能限制了结果的普适性。

综上所述，SA发病率较高，其发生与年龄、吸烟史及多种临床特征密切相关。疾病严重程度评分和炎性标志物对ARDS的发生具有预测作用。未来需要开展更多大样本、跨区域的研究，以探索SA风险因素和预测生物标志物，为早期预示和临床干预提供更可靠的依据。

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Risk Factors and Predictors of Sepsis Complicated with ARDS: A Meta-analysis

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