Citations for Randomized Controlled Trials in Sepsis Literature: The Halo Effect Caused by Journal Impact Factor - PubMed (original) (raw)

Citations for Randomized Controlled Trials in Sepsis Literature: The Halo Effect Caused by Journal Impact Factor

Zhongheng Zhang et al. PLoS One. 2017.

Abstract

Citations for randomized controlled trials (RCT) are important for the dissemination of study results. However, predictors of citations for RCTs have not been investigated. The study aimed to investigate the predictors of citations for RCTs in sepsis literature. RCTs that investigated the efficacy of treatment strategies on clinical outcomes in sepsis patients were included, and publication dates were restricted to the period from 2000 to 2016. Risk of bias was assessed using the Cochrane handbook for systematic reviews and interventions. A multivariable linear regression model was built to investigate the independent variables associated with total citations. In total, 160 RCTs met our inclusion criteria and were included for analysis. The median of total citations was 28.5 (IQR: 6-76). The journal impact factor (IF) for articles was 6.312 (IQR: 3.143-7.214). The dependent variable was transformed by the square root to improve normality and meet the assumption of homoscedasticity. The journal IF (coefficient: 0.2; 95% CI: 0.16, 0.25) was independently associated with total citations. Large samples were associated with more total citations (coefficient: 0.0026; 95% CI: 0.0013, 0.0039). The study demonstrated that the journal IF was a major determinant of the RCT's total citation number.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1

Fig 1. Flow chart of study selection.

Fig 2

Fig 2. Summary of risk of bias for the included randomized controlled trials.

Fig 3

Fig 3. Scatter plots of the total citations against the journal impact factor, stratified by publication year.

Fig 4

Fig 4. Scatterplot matrix describing the correlations among continuous variables.

Participating centers and sample sizes appeared to be closely correlated with each other, thus we only retained sample size in the model.

Fig 5

Fig 5. Diagnostic plots of multivariable linear regression.

The dependent variable, total citation, was not transformed. The scale-location plot shows a correlation trend between fitted values and square root of the standardized residual, indicating the violation of homoscedasticity. The Q-Q plot also shows the violation of normality.

Fig 6

Fig 6. Diagnostic plots of multivariable linear regression with the dependent variable total citation transformed by square root.

The relationship between the fitted values and square root of standardized residual was weakened. The Q-Q plot showed that the normal assumption of the dependent variable was well satisfied.

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