Several economic assessments of climate change build on the assumption that reductions of cold-related mortality will overcompensate increases in heat-related mortality at least for moderate levels of global warming. Due to the lack of suitable epidemiological studies with sufficient spatial coverage, many of these assessments rely on one particular dataset: projections of temperature-related mortality in 17 countries published almost 20 years ago. Here, we reanalyse this dataset with a focus on cardiovascular mortality and present evidence for two flaws in the original analysis, which would imply a significant bias towards finding net mortality benefits from climate change: (i) the combination of mortality data for all ages with data specific to the elderly and (ii) the confounding of seasonal effects with direct temperature effects on mortality. This bias appears to be further amplified in the integrated assessment models FUND and ENVISAGE, and related economic assessment tools relying on the same calibration scheme, because heat-related cardiovascular mortality is assumed to affect urban populations only in these models. In an exemplary calculation, we show that while FUND currently projects a net reduction of approximately 380,000 deaths from cardiovascular diseases globally per year at 1 °C of global warming, correcting for the two potential flaws and assuming equal vulnerability of urban and rural populations would result in a net increase of cardiovascular mortality, with approximately 150,000 net additional deaths globally per year. Our findings point to the urgent need of renewing damage functions on temperature-related mortality currently applied in some of the most widely used integrated assessment models.