Department of Laboratory Medicine and Research Institute of Bacterial Resistance, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea.
Division of Infectious Diseases, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea.
Int J Antimicrob Agents. 2024 Nov;64(5):107330. doi: 10.1016/j.ijantimicag.2024.107330. Epub 2024 Sep 6.
The increasing incidence of antibiotic-associated diarrhoea (AAD) is a serious health care problem. Dysbiosis of the gut microbiota is suspected to play a role in the pathogenesis of AAD, but its impact on the clinical outcomes of patients remains unclear.
Between May and October 2022, 210 patients with AAD admitted to a university hospital and 100 healthy controls were recruited. DNA extraction from stool specimens and shotgun sequencing were performed. Machine learning was conducted to assess profiling at different taxonomic levels and to select variables for multivariable analyses.
Patients were classified into two groups: Clostridioides difficile infection (CDI, n = 39) and non-CDI AAD (n = 171). The in-hospital mortality rate for the patients was 20.0%, but the presence of C. difficile in the gut microbiota was not associated with mortality. Machine learning showed that taxonomic profiling at the genus level best reflected patient prognosis. The in-hospital mortality of patients was associated with the relative abundance of specific gut microbial genera rather than alpha-diversity: each of the five genera correlated either positively (Enterococcus, Klebsiella, Corynebacterium, Pseudomonas, and Anaerofustis) or negatively (Bifidobacterium, Bacteroides, Streptococcus, Faecalibacterium, and Dorea). Genes for vancomycin resistance were significantly associated with in-hospital mortality in patients with AAD (adjusted hazard ratios, 2.45; 95% CI, 1.20-4.99).
This study demonstrates the potential utility of metagenomic studies of the gut microbial community as a biomarker for prognosis prediction in AAD patients.
抗生素相关性腹泻（AAD）的发病率不断上升，是一个严重的医疗保健问题。肠道微生物群落的失调被怀疑在 AAD 的发病机制中起作用，但它对患者临床结局的影响尚不清楚。
2022 年 5 月至 10 月，我们招募了 210 名因 AAD 住院的患者和 100 名健康对照者。从粪便标本中提取 DNA 并进行鸟枪法测序。采用机器学习评估不同分类水平的特征，并选择多变量分析的变量。
患者分为艰难梭菌感染（CDI，n = 39）和非 CDI AAD（n = 171）两组。患者的院内死亡率为 20.0%，但肠道微生物群落中艰难梭菌的存在与死亡率无关。机器学习表明，在属水平上的分类特征最能反映患者的预后。患者的院内死亡率与特定肠道微生物属的相对丰度相关，而与 alpha 多样性无关：五个属中的每一个都与死亡率呈正相关（肠球菌、克雷伯菌、棒状杆菌、假单胞菌和厌氧梭菌）或负相关（双歧杆菌、拟杆菌、链球菌、粪杆菌和多尔菌）。万古霉素耐药基因与 AAD 患者的院内死亡率显著相关（调整后的危险比，2.45；95%CI，1.20-4.99）。
本研究表明，肠道微生物群落的宏基因组研究作为 AAD 患者预后预测的生物标志物具有潜在的应用价值。
