Does Respiratory Variation in Inferior Vena Cava Diameter Predict Fluid Responsiveness in Mechanically Ventilated Patients? A Systematic Review and Meta-analysis.

ANESTHESIA AND ANALGESIA(2018)

引用 34|浏览27
暂无评分
摘要
BACKGROUND: We performed a systematic review and meta-analysis of studies investigating the diagnostic accuracy of respiratory variation in inferior vena cava diameter (IVC) for predicting fluid responsiveness in patients receiving mechanical ventilation. METHODS: MEDLINE, EMBASE, the Cochrane Library, and Web of Science were screened from inception to February 2017. The meta-analysis assessed the pooled sensitivity, specificity, diagnostic odds ratio, and area under the receiver operating characteristic curve. In addition, heterogeneity and subgroup analyses were performed. RESULTS: A total of 12 studies involving 753 patients were included. Significant heterogeneity existed among the studies, and meta-regression indicated that ventilator settings were the main sources of heterogeneity. Subgroup analysis indicated that IVC exhibited better diagnostic performance in the group of patients ventilated with tidal volume (TV) 8 mL/kg and positive end-expiratory pressure (PEEP) 5 cm H2O than in the group ventilated with TV <8 mL/kg or PEEP >5 cm H2O, as demonstrated by higher sensitivity (0.80 vs 0.66; P = .02), specificity (0.94 vs 0.68; P < .001), diagnostic odds ratio (68 vs 4; P < .001), and area under the receiver operating characteristic curve (0.88 vs 0.70; P < .001). The best IVC threshold for predicting fluid responsiveness was 16% 2% in the group of TV 8 mL/kg and PEEP 5 cm H2O, whereas in the group of TV <8 mL/kg or PEEP >5 cm H2O, this threshold was 14% +/- 5%. CONCLUSIONS: IVC shows limited ability for predicting fluid responsiveness in distinct ventilator settings. In patients with TV 8 mL/kg and PEEP 5 cm H2O, IVC was an accurate predictor of fluid responsiveness, while in patients with TV <8 mL/kg or PEEP >5 cm H2O, IVC was a poor predictor. Thus, intensivists must be cautious when using IVC.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要