ABSTRACT
Leg malperfusion accompanied with type B acute aortic dissection (AAD) is reported to be an independent predictor for mortality. In such a case, though aortic replacement, extra anatomical arterial bypass or endovascular aortic repair (EVAR) can be selected, an appropriate treatment strategy has not been established yet. A 53-year-old woman was urgently hospitalized with sudden low back pain and right leg weakness, despite the right popliteal and anterior tibial arteries being palpable. Computed tomography (CT) revealed a type B AAD, and antihypertensive therapy was initiated. She complained of intermittent claudication during rehabilitation, and right leg ischemia with decreased ankle brachial pressure index (ABPI) was detected. The follow-up CT revealed the narrow true lumen of the right common iliac artery compressed by the thrombosed false lumen and the large entry of the aortic dissection in the terminal aorta. At the subacute phase of the aortic dissection, EVAR was performed. To expand the true lumen and exclude the entry, Y-shaped stent-grafts were implanted in the infra-renal aorta and the bilateral common iliac arteries. The postoperative course was uneventful. Postoperative ABPI returned to the normal range, and the intermittent claudication disappeared. In conclusion, EVAR should be considered in patients with type B AAD complicated with leg malperfusion.
ABSTRACT
To investigate the association of real-time/observed ozone/PM2.5 levels with COVID-19 prevalence/fatality, meta-regression of data from the Northeast megalopolis was conducted. Daily Air Quality Index (AQI) values based on available ozone/PM2.5 data in these counties/cities (3/15/2020-5/31/2020) were extracted from US Environmental Protection Agency and World Air Quality Project. In each county/city, total confirmed COVID-19 cases/deaths (5/31/2020) were available from Johns Hopkins Coronavirus Resource Center, and total population was extracted from US Census Bureau. Random-effects meta-regression was performed using OpenMetaAnalyst. A meta-regression graph depicted COVID-19 prevalence and fatality (plotted as logarithm-transformed prevalence/fatality on the y-axis) as a function of mean ozone/PM2.5 AQI (plotted on the x-axis). Coefficients were not statistically significant for ozone (P = 0.212/0.814 for prevalence/fatality) and PM2.5 (P = 0.986/0.499). Although multivariable analysis had been planned, it was not performed because of non-significant covariates of interest in the univariable model. In conclusion, ozone/PM2.5 may be unassociated with COVID-19 prevalence/fatality.
ABSTRACT
Although it has been reported that coexistent chronic diseases are strongly associated with COVID-19 severity, investigations of predictors for SARS-CoV-2 infection itself have been seldom performed. To screen potential risk and protective factors for SARS-CoV-2 infection, meta-regression of data from worldwide nations were herein conducted. We extracted total confirmed COVID-19 cases in worldwide 180 nations (May 31, 2020), nation total population, population ages 0-14/[≥]65, GDP/GNI per capita, PPP, life expectancy at birth, medical-doctor and nursing/midwifery-personnel density, hypertension/obesity/diabetes prevalence, annual PM2.5 concentrations, daily ultraviolet radiation, population using safely-managed drinking-water/sanitation services and hand-washing facility with soap/water, inbound tourism, and bachelors or equivalent (ISCED 6). Restricted maximum-likelihood meta-regression in the random-effects model was performed using Comprehensive Meta-Analysis version 3. To adjust for other covariates, we conducted the hierarchical multivariate models. A slope (coefficient) of the meta-regression line for the COVID-19 prevalence was significantly negative for population ages 0-14 (-0.0636; P = .0021) and positive for obesity prevalence (0.0411; P = .0099) and annual PM2.5 concentrations in urban areas (0.0158; P = .0454), which would indicate that the COVID-19 prevalence decreases significantly as children increase and that the COVID-19 prevalence increases significantly as the obese and PM2.5 increase. In conclusion, children (negatively) and obesity/PM2.5 (positively) may be independently associated with SARS-CoV-2 infection.
ABSTRACT
To screen potential risk and protective socioeconomic factors for Coronavirus disease 2019 (COVID-19) prevalence and fatality, meta-regression of data from top 50 U.S. large-population cities was performed. The population estimate (in 2019) of each country to which the city belongs was abstracted from the "County Population Totals: 2010-2019." From the "Johns Hopkins Coronavirus Resource Center," the cumulative number of confirmed cases and deaths of COVID-19 in each country was obtained on May 22, 2020. Socioeconomic characteristics of each country were extracted from the "2014-2018 American Community Survey (ACS) 5-Year Data Profile" and "Small Area Income and Poverty Estimates (SAIPE) Program (for 2018)." Radom-effects meta-regression was performed using OpenMetaAnalyst (http://www.cebm.brown.edu/openmeta/index.html). A coefficient (slope of the meta-regression line) for COVID-19 prevalence was significantly negative for male sex, education attainment, computer and Internet use, and private health insurance. Whereas, the coefficient was significantly positive for black race, never matrimony, unemployment, and poverty. In the multivariable model, the coefficient was significantly negative for male sex (P = 0.036) and computer use (P = 0.024), and significantly positive for never matrimony (P < 0.001). A coefficient for COVID-19 fatality was significantly negative for no health insurance, and significantly positive for elderly, unemployment, and public coverage. In the multivariable model, the coefficient was significantly positive for only elderly (P = 0.002). In conclusion, a number of socioeconomic factors, e.g. male sex (negatively for prevalence), elderly (positively for fatality), never matrimony (positively for prevalence), and computer use (negatively for prevalence) may be associated with COVID-19.
ABSTRACT
Ethnics and economics may affect prevalence and case fatality of Coronavirus disease 2019 (COVID-19). To determine whether COVID-19 prevalence and fatality are modulated by ethnics and economics, meta-regression of data from the countries in the New York metropolitan area were herein conducted. We selected 31 countries in the New York metropolitan area. 1) Prevalence and case-fatality rates of confirmed COVID-19 cases on May 20, 2020 and 2) income and poverty estimates were obtained in each country. We performed random-effects meta-regression using OpenMetaAnalys. The covariates included 1) black (%), 2) Hispanic or Latino (%), 3) poverty rates (%), and 4) median household income ($). Statistically significant (P < .05) covariates in the univariable model were together entered into the multivariable model. A slope (coefficient) of the univariable meta-regression line for COVID-19 prevalence was not significant for household income (P = .639), whereas the coefficient was significantly positive for black (coefficient, 0.021; P = .015), Hispanic/Latino (0.033; P < .001), and poverty (0.039; P = .02), which indicated that COVID-19 prevalence increased significantly as black, Hispanic/Latino, and poverty increased. The multivariable model revealed that the slope was significantly positive for only Hispanic/Latino (P < .001). The coefficient in the univariable model for COVID-19 fatality, however, was not significant for all the covariate. In conclusion, black, Hispanic/Latino, and poverty (not household income), especially Hispanic/Latino independently, may be associated with COVID-19 prevalence. There may be no association of black, Hispanic/Latino, poverty, and household income with COVID-19 fatality.
ABSTRACT
To determine whether prevalence of Coronavirus disease 2019 (Covid-19) is modulated by meteorological conditions, we herein conducted meta-regression of data in large U.S. cities. We selected 33 large U.S. cities with a population of >500,000. The integrated numbers of confirmed Covid-19 cases in the country to which the city belongs on 14 May 2020, the estimated population in 2019 in the country, and monthly meteorological conditions at the city for 4 months (from January to April 2020) were obtained. Meteorological conditions consisted of mean temperature (F), total precipitation (inch), mean wind speed (MPH), mean sky cover, and mean relative humidity (%). Monthly data for 4 months were averaged or integrated. The Covid-19 prevalence was defined as the integrated number of Covid-19 cases divided by the population. Random-effects meta-regression was performed by means of OpenMetaAnalyst. In a meta-regression graph, Covid-19 prevalence (plotted as the logarithm transformed prevalence on the y-axis) was depicted as a function of a given factor (plotted as a meteorological datum on the x-axis). A slope of the meta-regression line was significantly negative (coefficient, -0.069; P < 0.001) for the mean temperature and significantly positive for the mean wind speed (coefficient, 0.174; P = 0.027) and the sky cover (coefficient, 2.220; P = 0.023). In conclusion, lower temperature and higher wind speed/sky cover may be associated with higher Covid-19 prevalence, which should be confirmed by further epidemiological researches adjusting for various risk and protective factors (in addition to meteorological conditions) of Covid-19.
ABSTRACT
A recent study from China suggests that high temperature and ultraviolet (UV) radiation cannot decrease the epidemics of Coronavirus disease 2019 (COVID-19). To determine whether COVID-19 prevalence is modulated by meteorological conditions, meta-regression of Japanese prefectural data was herein conducted. We extracted integrated number of patients testing positive for COVID-19 in each Japanese prefecture on 18 May 2020, population per 1-km2 inhabitable area in the prefecture in 2020, and monthly meteorological conditions at each prefectural capital city for 4 months (from January to April 2020). We averaged or cumulated the monthly data for the 4 months. To adjust for prefectural population density, we defined the COVID-19 prevalence as the integrated number of patients testing positive divided by the population per 100-km2 inhabitable area. Random-effects meta-regression was performed. A slope of the meta-regression line was significantly negative for mean air temperature (coefficient, -0.134; P = 0.019), mean sea level air pressure (-0.351; P = 0.001), and mean daily maximum UV index (-0.908; P = 0.012), which indicated that COVID-19 prevalence decreased significantly as air temperature, air pressure, and UV index increased. In conclusion, higher temperature, pressure, and UV may be associated with less COVID-19 prevalence, which should be confirmed by further epidemiological investigations taking other risk and protective factors of COVID-19 into account.
ABSTRACT
We report a case of endovascular aneurysm repair (EVAR) in a patient with an aortocaval fistula (ACF) who presented with congestive heart failure due to left-to-right shunting. The patient was an 80-year-old man who complained of sudden respiratory discomfort and lower leg edema, and was admitted to the emergency department. The initial diagnosis on admission was acute heart failure. Because the inferior vena cava was visualized by angiography in the arterial phase due to the fistula from the abdominal aorta, after admission, we rediagnosed this case as ACF. As medical treatment did not improve the patient's symptoms, emergency surgery was decided upon. Because preoperative evaluation was able to rule out the existence of an aortic aneurysm, ACF closure was performed by EVAR. The postoperative course was uneventful and the patient was discharged 15 days after surgery. ACF without aortic aneurysm is uncommon and is not easily diagnosed. This case demonstrated that EVAR can be an effective treatment option for ACF.
