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Comment
. 2025 Jul 15;29(1):307.
doi: 10.1186/s13054-025-05562-w.

Confused with confounders? Understanding the role of directed acyclic graphs in observational research

Affiliations
Comment

Confused with confounders? Understanding the role of directed acyclic graphs in observational research

Wilson Fandino et al. Crit Care. .
No abstract available

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Directed acyclic graph (DAG) for the variables included in the study of Russotto et al. All variables are mediators for this relationship, except for apneic oxygenation
Fig. 2
Fig. 2
Directed acyclic graph (DAG) for some of the variables included in the study of Russotto et al., to estimate the average causal effect of patient’s positioning for intubation on first-attempt intubation success. In this hypothetical scenario, the covariates included can be potential confounders for the association of interest. The relationships between covariates are omitted for clarity
Fig. 3
Fig. 3
A proposed directed acyclic graph (DAG) for the model illustrated in Fig. 1, after accounting for potential confounders. In this theoretical model, the contribution of residual confounding to the obtained estimates is reduced by including a relevant set of observed confounders for the association between body mass index and first-attempt intubation success. ASA: American Society of Anesthesiology

Comment on

References

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