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Meta-Analysis
. 2025 May 9;20(5):e0310462.
doi: 10.1371/journal.pone.0310462. eCollection 2025.

Predictive accuracy of changes in the inferior vena cava diameter for predicting fluid responsiveness in patients with sepsis: A systematic review and meta-analysis

Hao Zhang  1   2   3 , Jingyuan Jiang  1   2   3 , Min Dai  1   2   3 , Yan Liang  1   2   3 , Ningxiang Li  1   2   3 , Yongli Gao  1   2   3
Affiliations
Meta-Analysis

Predictive accuracy of changes in the inferior vena cava diameter for predicting fluid responsiveness in patients with sepsis: A systematic review and meta-analysis

Hao Zhang et al. PLoS One. .

Abstract

Background: Existing guidelines emphasize the importance of initial fluid resuscitation therapy in sepsis management. However, in previous meta-analyses, there have been inconsistencies in differentiating between spontaneously breathing and mechanically ventilated septic patients.

Objective: To consolidate the literature on the predictive accuracy of changes in the inferior vena cava diameter (∆IVC) for fluid responsiveness in septic patients.

Methods: The Embase, Web of Science, Cochrane Library, MEDLINE, PubMed, Wanfang, China National Knowledge Infrastructure (CNKI), Chinese Biomedical (CBM) and VIP (Weipu) databases were comprehensively searched. Statistical analyses were performed with Stata 15.0 software and Meta-DiSc 1.4.

Results: Twenty-one research studies were deemed suitable for inclusion. The sensitivity and specificity of ∆ IVC were 0.84 (95% CI 0.76, 0.90) and 0.87 (95% CI 0.80, 0.91), respectively. With respect to the distensibility of the inferior vena cava (dIVC), the sensitivity was 0.79 (95% CI 0.68, 0.86), and the specificity was 0.82 (95% CI 0.73, 0.89). For collapsibility of the inferior vena cava (cIVC), the sensitivity and specificity values were 0.92 (95% CI 0.83, 0.96) and 0.93 (95% CI 0.86, 0.97), respectively.

Conclusion: The results indicated that ∆IVC is as a dependable marker for fluid responsiveness in sepsis patients. dIVC and cIVC also exhibited high levels of accuracy in predicting fluid responsiveness in septic patients.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Search strategy of PubMed database.
Fig 2
Fig 2. Flowchart of study selection.
Fig 3
Fig 3. Quality assessment of diagnostic accuracy studies criteria for the included studies.
Fig 4
Fig 4. Quality assessment of diagnostic accuracy studies criteria for the included studies.
Fig 5
Fig 5. Forest plot of sensitivity and specificity in the diagnosis of
∆ IVC.
Fig 6
Fig 6. Forest plot of PLR and NLR in the diagnosis of
∆ IVC.
Fig 7
Fig 7. Forest plot of DOR in the diagnosis of
∆ IVC.
Fig 8
Fig 8. Summary receiver operator characteristic (SROC) curve in the prediction of
∆ IVC. SENS = sensitivity, SPEC = specificity, AUC = area under the receiver operating characteristic curve.
Fig 9
Fig 9. Forest plot of sensitivity and specificity in the diagnosis of dIVC.
Fig 10
Fig 10. Forest plot of PLR and NLR in the diagnosis of dIVC.
Fig 11
Fig 11. Forest plot of DOR in the diagnosis of dIVC.
Fig 12
Fig 12. Summary receiver operator characteristic (SROC) curve in the prediction of dIVC.
SENS = sensitivity, SPEC = specificity, AUC = area under the receiver operating characteristic curve.
Fig 13
Fig 13. Forest plot of sensitivity and specificity in the diagnosis of cIVC.
Fig 14
Fig 14. Forest plot of PLR and NLR in the diagnosis of cIVC.
Fig 15
Fig 15. Forest plot of DOR in the diagnosis of cIVC.
Fig 16
Fig 16. Summary receiver operator characteristic (SROC) curve in the prediction of cIVC.
SENS = sensitivity, SPEC = specificity, AUC = area under the receiver operating characteristic curve.
Fig 17
Fig 17. Deek’s funnel plots of ∆ IVC.
Fig 18
Fig 18. Deek’s funnel plots of dIVC.
Fig 19
Fig 19. Deek’s funnel plots of cIVC.
Fig 20
Fig 20. Fangan plots of
∆ IVC.
Fig 21
Fig 21. Fangan plots of dIVC.
Fig 22
Fig 22. Fangan plots of cIVC.
Subgroup analysis.
See this image and copyright information in PMC

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