The effect of a quantitative resuscitation strategy on mortality in patients with sepsis: a meta-analysis

Abstract

Objective: Quantitative resuscitation consists of structured cardiovascular intervention targeting predefined hemodynamic end points. We sought to measure the treatment effect of quantitative resuscitation on mortality from sepsis.

Data sources: We conducted a systematic review of the Cochrane Library, MEDLINE, EMBASE, CINAHL, conference proceedings, clinical practice guidelines, and other sources using a comprehensive strategy.

Study selection: We identified randomized control trials comparing quantitative resuscitation with standard resuscitation in adult patients who were diagnosed with sepsis using standard criteria. The primary outcome variable was mortality.

Data abstraction: Three authors independently extracted data and assessed study quality using standardized instruments; consensus was reached by conference. Preplanned subgroup analysis required studies to be categorized based on early (at the time of diagnosis) vs. late resuscitation implementation. We used the chi-square test and I to assess for statistical heterogeneity (p < 0.10, I > 25%). The primary analysis was based on the random effects model to produce pooled odds ratios with 95% confidence intervals.

Results: The search yielded 29 potential publications; nine studies were included in the final analysis, providing a sample of 1001 patients. The combined results demonstrate a decrease in mortality (odds ratio 0.64, 95% confidence interval 0.43-0.96); however, there was statistically significant heterogeneity (p = 0.07, I = 45%). Among the early quantitative resuscitation studies (n = 6) there was minimal heterogeneity (p = 0.40, I = 2.4%) and a significant decrease in mortality (odds ratio 0.50, 95% confidence interval 0.37-0.69). The late quantitative resuscitation studies (n = 3) demonstrated no significant effect on mortality (odds ratio 1.16, 95% confidence interval 0.60-2.22).

Conclusion: This meta-analysis found that applying an early quantitative resuscitation strategy to patients with sepsis imparts a significant reduction in mortality.

Figure 1

Search, inclusion, and exclusion flow diagram.

Figure 2

Forest plot of all included studies and of the subgroup analysis of early vs. late quantitative resuscitation using a random effects model. OR, odds ratio; CI, confidence interval; df, degrees of freedom.

Figure 3

Funnel plot of included studies. Individual included studies are represented by dots and are plotted by the standard error (SE) of the log odds ratio (OR) on the y-axis and the OR on the x-axis. The pooled OR calculated using a random effects model is represented by the vertical dotted line. This plot is provided for visual inspection for detection of publication bias.