"Missing" Acute Coronary Syndrome Hospitalizations During Thecovid-19 Era In Greece: Medical Care Avoidance Combined With A True Reduction In Incidence?

CLINICAL CARDIOLOGY(2020)

引用 49|浏览3
暂无评分
摘要
Background Reports from countries severely hit by the COVID-19 pandemic suggest a decline in acute coronary syndrome (ACS)-related hospitalizations. The generalizability of this observation on ACS admissions and possible related causes in countries with low COVID-19 incidence are not known. Hypothesis ACS admissions were reduced in a country spared by COVID-19. Methods We conducted a nationwide study on the incidence rates of ACS-related admissions during a 6-week period of the COVID-19 outbreak and the corresponding control period in 2019 in Greece, a country with strict social measures, low COVID-19 incidence, and no excess in mortality. Results ACS admissions in the COVID-19 (n = 771) compared with the control (n = 1077) period were reduced overall (incidence rate ratio [IRR]: 0.72,P < .001) and for each ACS type (ST-segment elevation myocardial infarction [STEMI]: IRR: 0.76,P= .001; non-STEMI: IRR: 0.74,P < .001; and unstable angina [UA]: IRR: 0.63,P= .002). The decrease in STEMI admissions was stable throughout the COVID-19 period (temporal correlation; R-2= 0.11,P= .53), whereas there was a gradual decline in non-STEMI/UA admissions (R-2= 0.75,P= .026) following the progressively stricter social measures. During the COVID-19 period, patients admitted with ACS presented more frequently with left ventricular systolic impairment (22.2 vs 15.5% control period;P < .001). Conclusions We observed a reduction in ACS hospitalizations during the COVID-19 outbreak in a country with strict social measures, low community transmission, and no excess in mortality. Medical care avoidance behavior is an important factor for these observations, while a true reduction of the ACS incidence due to self-isolation/quarantining may have also played a role.
更多
查看译文
关键词
acute cardiac care, acute coronary syndrome, COVID-19, myocardial infarction, public health
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要