Takagi et al. [1] published an analysis of the effects of possible publication bias in Meyers et al.'s [2] 2009 meta-analysis of 11 studies of the effects of smokefree laws on hospital admissions for acute myocardial infarction. Meyers et al. reported a 17% drop in AMI admissions (RR 0.83 95% CI, 0.75 to 0.92). Using a funnel plot Takagi et al. concluded that there was significant publication bias in Meyers et al.'s estimate and that correcting for this bias using the “trim and fill” method led to a conclusion that these laws were associated with a nonsignificant 3% (95% CI, 0.97 to 1.08) change in hospital admissions.

Since Meyers et al. published their meta-analysis, studies of the effects of smokefree laws on AMI hospital admissions have continued to be published. By 2012 there were 28 studies of strong smokefree laws on AMI hospital admissions. Tan and Glantz [3] conducted a meta-analysis of these papers and found a 15% drop in AMI admissions (RR 0.846, 95% CI, 0.803, 0.890), similar to what Meyers et al. reported.

Tan and Glantz also evaluated these studies for evidence of publication bias using the same methods as Takagi et al. and, like Takagi et al., found evidence of significant publication bias. Like Takagi et al., Tan and Glantz used the trim and fill method to assess the effects of the publication bias. Based on the much larger collection of studies published in recent years, however, Tan and Glantz found that the effect of smokefree laws on AMI hospitalizations was essentially unchanged at a 20% reduction in AMI admissions (RR 0.803, 95% CI, 0.764, 0.840).

Tan and Glantz also found a dose–response between the comprehensiveness of the smoking restriction and effects of the laws on hospital admissions for other cardiovascular endpoints, as well as stroke, asthma and other pulmonary endpoints.

Cardiologists and policy makers can move forward with confidence that smoking restrictions lower hospitalizations for AMIs and other disorders.