Re-examining the effect of door-to-balloon delay on STEMI outcomes in the context of unmeasured confounders: a retrospective cohort study

Literature studying the door-to-balloon time-outcome relation in coronary intervention is limited by the potential of residual biases from unobserved confounders. This study re-examines the time-outcome relation with further consideration of the unobserved factors and reports the population average effect. Adults with ST-elevation myocardial infarction admitted to one of the six registry participating hospitals in Australia were included in this study. The exposure variable was patient-level door-to-balloon time. Primary outcomes assessed included in-hospital and 30 days mortality. 4343 patients fulfilled the study criteria. 38.0% (1651) experienced a door-to-balloon delay of >90 minutes. The absolute risk differences for in-hospital and 30-day deaths between the two exposure subgroups with balanced covariates were 2.81 (95% CI 1.04, 4.58) and 3.37 (95% CI 1.49, 5.26) per 100 population. When unmeasured factors were taken into consideration, the risk difference were 20.7 (95% CI −2.6, 44.0) and 22.6 (95% CI −1.7, 47.0) per 100 population. Despite further adjustment of the observed and unobserved factors, this study suggests a directionally consistent linkage between longer door-to-balloon delay and higher risk of adverse outcomes at the population level. Greater uncertainties were observed when unmeasured factors were taken into consideration

Linear low-dose extrapolation for noncancer health effects is the exception, not the rule

The nature of the exposure-response relationship has a profound influence on risk analyses. Several arguments have been proffered as to why all exposure-response relationships for both cancer and noncarcinogenic end-points should be assumed to be linear at low doses. We focused on three arguments that have been put forth for noncarcinogens. First, the general “additivity-to-background” argument proposes that if an agent enhances an already existing disease-causing process, then even small exposures increase disease incidence in a linear manner. This only holds if it is related to a specific mode of action that has nonuniversal properties—properties that would not be expected for most noncancer effects. Second, the “heterogeneity in the population” argument states that variations in sensitivity among members ofthe target population tend to “flatten out and linearize” the exposure-response curve, but this actually only tends to broaden, not linearize, the dose-response relationship. Third, it has been argued that a review of epidemiological evidence shows linear or no-threshold effects at low exposures in humans, despite nonlinear exposure-response in the experimental dose range in animal testing for similar endpoints. It is more likely that this is attributable to exposure measurement error rather than a true non-threshold association. Assuming that every chemical is toxic at high exposures and linear at low exposures does not comport to modern-day scientific knowledge of biology. There is no compelling evidence-based justification for a general low-exposure linearity; rather, case-specific mechanistic arguments are needed