Application of the E-Value to Assess Bias in Observational Research in Plastic Surgery.

BACKGROUND: The E-value is a statistical measure that is used to quantify the degree of unmeasured confounding that is necessary to undermine the treatment-outcome associations established in observational studies. Despite the substantial amount of observational research that informs evidence-based practice in plastic surgery, sensitivity analyses based on the E-value have not been conducted in the field. METHODS: The authors performed a systematic search of the literature to identify meta-analyses of observational studies in plastic surgery. The authors calculated E-values for various treatment-outcome associations based on the risk, odds, or hazard ratios in each study, to assess unmeasured confounding effects that may influence the validity of the conclusions. The authors then analyzed the distribution of E-values from pooled versus individual studies. RESULTS: The authors identified 45 meta-analyses that met the inclusion criteria, with each containing an average of three pooled assessments of observational data. The E-value of the pooled effect estimates ranged from 1.11 to 19.49, with an average value of 3.82. As for the individual effect estimates from each primary study within the meta-analyses, the E-values ranged from 1.00 to 321.50, with an average value of 8.74. CONCLUSIONS: The authors determined that E-values vary substantially across the literature and that unmeasured confounding may be present in a high number of observational studies. Although extant statistical techniques will continue to be necessary to control for measured confounding, the E-value is a novel concept that can facilitate more robust sensitivity analyses in plastic surgery research.

A Qualitative Study of Patient Protection against Postoperative Opioid Addiction: A Thematic Analysis of Self-Agency.

BACKGROUND: Opioids are commonly used following outpatient surgery. However, we understand little about patients' perspectives and how patients decide on postoperative opioid use. This study seeks to investigate aspects of patients' thought processes that most impact their decisions. METHODS: The authors conducted semistructured interviews with 30 adults undergoing minor elective hand surgery at one tertiary hospital. Narratives were content-coded to arrive at the authors' thematic analysis. The authors incorporated Bandura's concept of self-agency to interpret the data and develop a conceptual framework that best explained the implicit theory within participants' responses. RESULTS: The authors found six themes under two domains of self-agency. Participants actively sought out protective mechanisms supporting their decision on opioid use, but sometimes did so unconsciously. They would avoid opioids postoperatively because they were "tough" and wanted to evade the risk of addiction as "good citizens." They conveyed a nuanced safety against addiction because they were "not the kind" to become addicted and because they trusted the surgeons' prescribing. However, participants felt discouraged by the stigma associated with opioids. Both intentionally and unintentionally, participants integrated a strong sense of self in their decision-making processes. CONCLUSIONS: A robust understanding of how patients choose to take opioids for postoperative pain control is imperative to develop patient-centered strategies to treat the opioid epidemic. Effective opioid-reduction policies should consider patients as active agents who negotiate various internal and external influences in their decision-making processes. Surgeons must incorporate patients' individual goals and perspectives regarding postoperative opioid use to minimize opioid-related harm after surgery.