Publications

BACKGROUND

Identifying the individual hemodynamic significance of tandem coronary artery lesions can be complicated by the crosstalk phenomenon which occurs between serial stenoses under hyperemic conditions. Physiological assessments performed under resting conditions are considered to be, theoretically, less affected by the hemodynamic interaction between serial coronary stenoses. The purpose of this study was to assess whether pressure-wire (PW) pullback measurements at rest and during hyperemia provided different information as to which stenosis appeared to be most functionally significant.

METHODS

In consecutive patients with angiographically discrete serial lesions, physiological lesion predominance (i.e. proximal or distal) was defined according to the pressure gradient along the vessels on PW-pullback trace. We used instantaneous wave-free ratio (iFR) based assessment as the reference standard and compared fractional flow reserve (FFR) based and hyperemic-iFR based lesion predominance.

RESULTS

Eighty-eight vessels (70 patients, mean age 70.3 ± 9.4 years, 80% male) were included in this study. Median iFR, FFR and hyperemic-iFR were 0.85 (interquartile range [IQR]: 0.74 to 0.91), 0.73 (IQR: 0.65 to 0.80) and 0.60 (IQR: 0.49 to 0.71), respectively. When judged against iFR-pullback based physiological assessment, lesion predominance changed in 22.7% (20/88) in FFR and in 20.5% (18/88) in hyperemic-iFR, respectively. There was no statistical difference between FFR and hyperemic-iFR for the impact on these changes (p = 0.77).

CONCLUSIONS

In serial coronary lesions, hyperemic PW-pullback disagreed with resting PW-pullback on the lesion-specific identification of ischemia in approximately 20% of cases, either in whole cardiac cycle or in wave-free period.

Management of the COVID-19 pandemic has proven to be a significant challenge to policy makers. This is in large part due to uneven reporting and the absence of open-access visualization tools to present local trends and infer healthcare needs. Here we report the development of CovidCounties.org, an interactive web application that depicts daily disease trends at the level of US counties using time series plots and maps. This application is accompanied by a manually curated dataset that catalogs all major public policy actions made at the state-level, as well as technical validation of the primary data. Finally, the underlying code for the site is also provided as open source, enabling others to validate and learn from this work.