NIHR Biomedical Research Centre, Oxford, UK.
Clin Infect Dis. 2013 Jun;56(11):1589-600. doi: 10.1093/cid/cit127. Epub 2013 Mar 5.
Despite substantial interest in biomarkers, their impact on clinical outcomes and variation with bacterial strain has rarely been explored using integrated databases.
From September 2006 to May 2011, strains isolated from Clostridium difficile toxin enzyme immunoassay (EIA)-positive fecal samples from Oxfordshire, United Kingdom (approximately 600,000 people) underwent multilocus sequence typing. Fourteen-day mortality and levels of 15 baseline biomarkers were compared between consecutive C. difficile infections (CDIs) from different clades/sequence types (STs) and EIA-negative controls using Cox and normal regression adjusted for demographic/clinical factors.
Fourteen-day mortality was 13% in 2222 adults with 2745 EIA-positive samples (median, 78 years) vs 5% in 20,722 adults with 27,550 EIA-negative samples (median, 74 years) (absolute attributable mortality, 7.7%; 95% CI, 6.4%-9.0%). Mortality was highest in clade 5 CDIs (25% [16 of 63]; polymerase chain reaction (PCR) ribotype 078/ST 11), then clade 2 (20% [111 of 560]; 99% PCR ribotype 027/ST 1) versus clade 1 (12% [137 of 1168]; adjusted P < .0001). Within clade 1, 14-day mortality was only 4% (3 of 84) in ST 44 (PCR ribotype 015) (adjusted P = .05 vs other clade 1). Mean baseline neutrophil counts also varied significantly by genotype: 12.4, 11.6, and 9.5 × 10(9) neutrophils/L for clades 5, 2 and 1, respectively, vs 7.0 × 10(9) neutrophils/L in EIA-negative controls (P < .0001) and 7.9 × 10(9) neutrophils/L in ST 44 (P = .08). There were strong associations between C. difficile-type-specific effects on mortality and neutrophil/white cell counts (rho = 0.48), C-reactive-protein (rho = 0.43), eosinophil counts (rho = -0.45), and serum albumin (rho = -0.47). Biomarkers predicted 30%-40% of clade-specific mortality differences.
C. difficile genotype predicts mortality, and excess mortality correlates with genotype-specific changes in biomarkers, strongly implicating inflammatory pathways as a major influence on poor outcome after CDI. PCR ribotype 078/ST 11 (clade 5) leads to severe CDI; thus ongoing surveillance remains essential.
尽管人们对生物标志物非常感兴趣，但很少有研究使用综合数据库来探讨其对临床结局的影响及其与细菌株的变化关系。
从 2006 年 9 月至 2011 年 5 月，从英国牛津郡（约 60 万人）毒素酶免疫测定（EIA）阳性粪便样本中分离出的艰难梭菌菌株进行多位点序列分型。使用 Cox 回归和正常回归比较不同分支/序列型（ST）的连续艰难梭菌感染（CDI）和 EIA 阴性对照之间的 14 天死亡率和 15 种基线生物标志物的水平，调整了人口统计学/临床因素。
在 2222 名成年人（中位数年龄为 78 岁）的 2745 份 EIA 阳性样本中，14 天死亡率为 13%（78 岁），而在 20722 名成年人（中位数年龄为 74 岁）的 27550 份 EIA 阴性样本中，14 天死亡率为 5%（74 岁）（绝对归因死亡率为 7.7%；95%CI，6.4%-9.0%）。5 型分支（25%[63 例中的 16 例]；聚合酶链反应（PCR）核糖体 078/ST11）的死亡率最高，其次是 2 型分支（20%[560 例中的 111 例]；99%PCR 核糖体 027/ST1）和 1 型分支（12%[1168 例中的 137 例]）（调整后 P <.0001）。在 1 型分支内，ST44（PCR 核糖体 015）的 14 天死亡率仅为 4%（84 例中的 3 例）（调整后 P =.05 与其他 1 型分支相比）。中性粒细胞计数的基线均值也因基因型而显著不同：5 型、2 型和 1 型分支分别为 12.4、11.6 和 9.5×10(9)个中性粒细胞/L，EIA 阴性对照为 7.0×10(9)个中性粒细胞/L（P <.0001），ST44 为 7.9×10(9)个中性粒细胞/L（P =.08）。艰难梭菌型特异性对死亡率和中性粒细胞/白细胞计数（rho = 0.48）、C 反应蛋白（rho = 0.43）、嗜酸性粒细胞计数（rho = -0.45）和血清白蛋白（rho = -0.47）之间存在很强的关联。生物标志物预测了 30%-40%的分支特异性死亡率差异。
艰难梭菌基因型可预测死亡率，且过度死亡率与基因型特异性生物标志物变化相关，这强烈提示炎症途径是艰难梭菌感染后不良结局的主要影响因素。PCR 核糖体 078/ST11（5 型分支）导致严重的艰难梭菌感染；因此，持续监测仍然至关重要。
