Racial Disparity and Trend of Food Scarcity Amid COVID-19 Pandemic in the United States.

An increase in households with food insecurity has been reported during the COVID-19 pandemic, but the trend of food insecurity during the pandemic remains unclear. Using Household Pulse Survey (HPS) data over 34 weeks from June 2020 to September 2021 (nationally representative samples of US adults in the households from the US Census Bureau), we examined racial disparity and trends of food scarcity amid the COVID-19 pandemic. The time series plots illustrated that the food scarcity rate was incremental until December 2020 and began improving thereafter across all racial groups. Such improvements in food scarcity were accompanied by the rise in regular income rates while the use of food assistance programs, unemployment insurance, and stimulus payments remained unchanged or reduced. As the US economy recovered, the gaps in food scarcity rates also narrowed between Black/Hispanic and White households.

Eicosapentaenoic Acid for Cardiovascular Events Reduction- Systematic Review and Network Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Randomized clinical trials (RCTs) investigating the impact of omega-3-fatty acid supplementation on cardiovascular events have largely shown no benefit. However, there is debate about the benign nature of the placebo in these trials. We aimed to conduct a network meta-analysis of RCTs to compare the outcomes of omega-3 fatty acid supplementation to various placebo oils. METHODS: MEDLINE and EMBASE were searched through May, 2021 to identify RCTs investigating cardiovascular outcomes with omega-3-fatty acid formulations [eicosapentaenoic acid (EPA), decosahexanoic acid (DHA), or the combination] versus placebo or standard of care controls. RESULTS: Our analysis included 17 RCTs that enrolled a total of 141,009 patients randomized to EPA (n=13,655), EPA+DHA (n=56,908), mineral oil placebo (n=5,338), corn oil placebo (n =8,876), olive oil placebo (n=41,009), and controls (no placebo oil; n=15,223). Rates of cardiovascular death [hazard ratio (HR) (95% confidence interval, CI) =0.80 (0.65-0.98); p =0.033], myocardial infarction [HR (95% CI) =0.73 (0.55-0.97); p=0.029] and stroke [HR (95% CI) =0.74 (0.58-0.94); p=0.014] were significantly lower in those receiving EPA compared to those receiving mineral oil, but were not different from rates in those receiving other oils or controls. Rates of coronary revascularization were significantly lower in those receiving EPA than in those receiving either EPA+DHA, mineral oil, corn oil, or olive oil placebo, but not controls. All-cause death was similar among all groups, but combined EPA+DHA was associated with reduced risk of cardiovascular death compared to controls [HR (95%CI): 0.83 (0.71-0.98)]. CONCLUSIONS: Our analyses demonstrate that although EPA supplementation lowers risk of coronary revascularization more than other oils, there may not be a benefit relative to standard of care. Further, EPA reduces the risk of cardiovascular events only in comparison to mineral oil and not when compared with other placebo oils or controls. In contrast, combined EPA+DHA was associated with reduced risk of cardiovascular death compared to controls.

Effects of Septal Reduction Therapy on Acute Cardiovascular Events and All-Cause Mortality in Patients with Hypertrophic Cardiomyopathy.

Septal reduction therapy (SRT) -i.e. septal myectomy and alcohol septal ablation-has been performed to treat medically refractory hypertrophic cardiomyopathy (HCM) for decades. However, it is largely unknown whether SRT prevents HCM-related cardiovascular events or death. The objective was to examine the effects of SRT on acute cardiovascular events and all-cause mortality in HCM. We performed a propensity score (PS) -matched study using databases that capture all hospitalizations and outpatient visits in New York state. We identified patients with HCM who underwent SRT between 2007 and 2014 (i.e. the SRT group) and those who had never had SRT but had at least one hospitalization for HCM during the same period (i.e. the control group). We performed PS matching at a 1:1 ratio. The primary outcome was a composite of acute cardiovascular events and all-cause mortality during 0-180 days and 181-360 days. The secondary outcome was 180- and 360-day all-cause mortality. We included 846 patients with HCM (423 PS-matched pairs). Patients who underwent SRT had a lower risk of the primary outcome event (0-180 days: odds ratio [OR], 0.54; 95% confidence intervals (CI), 0.37-0.80; P = 0.002 and 181-360 days: OR, 0.33; 95% CI, 0.22-0.51; P < 0.0001). Furthermore, the risk of all-cause mortality was lower at 180 days (OR, 0.37; 95% CI, 0.22-0.63; P = 0.0003) and 360 days post-SRT (OR, 0.32; 95% CI, 0.20-0.51; P < 0.0001). In conclusion, our PS-matched study using population-based datasets demonstrated that SRT was associated with a reduced risk of a composite of acute cardiovascular events and all-cause mortality in HCM during the first post-SRT year.

Deep Learning Analysis of Echocardiographic Images to Predict Positive Genotype in Patients With Hypertrophic Cardiomyopathy.

Genetic testing provides valuable insights into family screening strategies, diagnosis, and prognosis in patients with hypertrophic cardiomyopathy (HCM). On the other hand, genetic testing carries socio-economical and psychological burdens. It is therefore important to identify patients with HCM who are more likely to have positive genotype. However, conventional prediction models based on clinical and echocardiographic parameters offer only modest accuracy and are subject to intra- and inter-observer variability. We therefore hypothesized that deep convolutional neural network (DCNN, a type of deep learning) analysis of echocardiographic images improves the predictive accuracy of positive genotype in patients with HCM. In each case, we obtained parasternal short- and long-axis as well as apical 2-, 3-, 4-, and 5-chamber views. We employed DCNN algorithm to predict positive genotype based on the input echocardiographic images. We performed 5-fold cross-validations. We used 2 reference models-the Mayo HCM Genotype Predictor score (Mayo score) and the Toronto HCM Genotype score (Toronto score). We compared the area under the receiver-operating-characteristic curve (AUC) between a combined model using the reference model plus DCNN-derived probability and the reference model. We calculated the p-value by performing 1,000 bootstrapping. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). In addition, we examined the net reclassification improvement. We included 99 adults with HCM who underwent genetic testing. Overall, 45 patients (45%) had positive genotype. The new model combining Mayo score and DCNN-derived probability significantly outperformed Mayo score (AUC 0.86 [95% CI 0.79-0.93] vs. 0.72 [0.61-0.82]; p < 0.001). Similarly, the new model combining Toronto score and DCNN-derived probability exhibited a higher AUC compared to Toronto score alone (AUC 0.84 [0.76-0.92] vs. 0.75 [0.65-0.85]; p = 0.03). An improvement in the sensitivity, specificity, PPV, and NPV was also achieved, along with significant net reclassification improvement. In conclusion, compared to the conventional models, our new model combining the conventional and DCNN-derived models demonstrated superior accuracy to predict positive genotype in patients with HCM.