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1.
Am J Med ; 135(7): 897-905, 2022 07.
Article in English | MEDLINE | ID: covidwho-1739511

ABSTRACT

INTRODUCTION: Statins have been commonly used for primary and secondary cardiovascular prevention. We hypothesized that statins may improve in-hospital outcomes for hospitalized patients with Coronavirus disease 2019 (COVID-19) due to its known anti-inflammatory effects. METHODS: We conducted a retrospective study at the largest municipal health care system in the United States, including adult patients who were hospitalized for COVID-19 between March 1 and December 1, 2020. The primary endpoint was in-hospital death. Propensity score matching was conducted to balance possible confounding variables between patients receiving statins during hospitalization (statin group) and those not receiving statins (non-statin group). Multivariate logistic regression was used to evaluate the association of statin use and other variables with in-hospital outcomes. RESULTS: There were 8897 patients eligible for study enrollment, with 3359 patients in the statin group and 5538 patients in the non-statin group. After propensity score matching, both the statin and non-statin groups included 2817 patients. Multivariate logistic regression analysis showed that the statin group had a significantly lower risk of in-hospital mortality (odds ratio 0.71; 95% confidence interval, 0.63-0.80; P < .001) and mechanical ventilation (OR 0.80; 95% confidence interval, 0.71-0.90; P < .001) compared with the non-statin group. CONCLUSION: Statin use was associated with lower likelihood of in-hospital mortality and invasive mechanical ventilation in hospitalized patients with COVID-19.


Subject(s)
COVID-19 , Hydroxymethylglutaryl-CoA Reductase Inhibitors , Adult , Hospital Mortality , Hospitals, Public , Humans , Hydroxymethylglutaryl-CoA Reductase Inhibitors/therapeutic use , New York City/epidemiology , Retrospective Studies , United States
2.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-307725

ABSTRACT

Background: Online healthcare platform (OHP) is a new form of medical treatment, which solves the problems of unbalanced distribution of medical resources and expensive medical treatment in China. Especially under the epidemic of COVID-19, OHP has greatly reduced the medical pressure of the hospital and the risk of cross infection. Methods: : This paper uses evolutionary game theory to analyze behavioral strategies and their dynamic evolution in the promotion of OHP, and then numerical simulations are carried out with the help of program compilation. Results: : The results demonstrate that: (1) both the stricter qualification inspection of doctors and the more investment in information protection promote the participation of doctors and the use of patients;(2) with a higher initial probability of doctors joining, the possibility for patients in using OHP and platforms to provide standardized online healthcare services becomes higher;(3) if the initial probability of patients using is higher, the possibility for doctors to join OHP and platforms to provide standardized online healthcare services raises;(4) the trend of doctors joining the platform is affected by factors, such as registration cost, time cost, reputation loss ;(5) the tendency of patients in using online healthcare is mainly decided by the cost. Conclusions: : Based on theoretical analysis, this article takes the Spring Rain Doctor OHP as an example to verify the game results. Therefore, OHP should attach importance to the inspection of doctors and the protection of privacy information, and strengthen the publicity in remote places. At the same time OHP can promote the active participation of grassroots doctors, and set a reasonable evaluation mechanism, so as to popularize online medical treatment among patients further.

4.
Healthcare (Basel) ; 8(4)2020 Dec 03.
Article in English | MEDLINE | ID: covidwho-963170

ABSTRACT

(1) Background: This study sought to explore how the novel coronavirus (COVID-19) pandemic affected the echocardiography (TTE) laboratory operations at a high volume medical center in New York City. Changes in cardiac imaging study volume, turn-around time, and abnormal findings were analyzed and compared to a pre-pandemic period. (2) Methods: Volume of all cardiac imaging studies and TTE reports between 11 March 2020 to 5 May 2020 and the same calendar period in 2019 were retrospectively identified and compared. (3) Results: During the pandemic, our center experienced a 46.72% reduction in TTEs, 82.47% reduction in transesophageal echocardiograms, 83.16% reduction in stress echo, 70.32% reduction in nuclear tests, 46.25% reduction in calcium score, 73.91% reduction in coronary computed tomography angiography, and 87.23% reduction in cardiac magnetic resonance imaging. TTE findings were overall similar between 2020 and 2019 (all p ≥ 0.05), except for a significantly higher right ventricular systolic pressure in 2020 (39.8 ± 14.2 vs. 34.6 ± 11.2 mmHg, p = 0.012). (4) Conclusions: Despite encountering an influx of critically ill patients, our hospital center experienced a reduction in the number of cardiac imaging studies, which likely represents a change in both patient mindset and physician management approach.

5.
Hormones (Athens) ; 20(2): 305-314, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-893364

ABSTRACT

PURPOSE: Infectious diseases are more frequent and can be associated with worse outcomes in patients with diabetes. The aim of this study was to systematically review and conduct a meta-analysis of the available observational studies reporting the effect of diabetes on mortality among hospitalized patients with COVID-19. METHODS: The Medline, Embase, Google Scholar, and medRxiv databases were reviewed for identification of eligible studies. A random effects model meta-analysis was used, and I2 was utilized to assess the heterogeneity. In-hospital mortality was defined as the endpoint. Sensitivity, subgroup, and meta-regression analyses were performed. RESULTS: A total of 18,506 patients were included in this meta-analysis (3713 diabetics and 14,793 non-diabetics). Patients with diabetes were associated with a higher risk of death compared with patients without diabetes (OR 1.65; 95% CI 1.35-1.96; I2 77.4%). The heterogeneity was high. A study-level meta-regression analysis was performed for all the important covariates, and no significant interactions were found between the covariates and the outcome of mortality. CONCLUSION: This meta-analysis shows that that the likelihood of death seems to be higher in diabetic patients hospitalized with COVID-19 compared with non-diabetic patients. Further studies are needed to assess whether this association is independent or not, as well as to investigate the role of adequate glycemic control prior to infection with COVID-19.


Subject(s)
COVID-19/epidemiology , Diabetes Mellitus/epidemiology , SARS-CoV-2 , Global Health , Hospital Mortality/trends , Humans , Pandemics , Survival Rate/trends
6.
SSRN; 2020.
Preprint | SSRN | ID: ppcovidwho-1037

ABSTRACT

BACKGROUND: New York is the current epicentre of Coronavirus disease 2019 (COVID-19) pandemic. The underrepresented minorities, where the prevalence of obesit

8.
Metabolism ; 108: 154262, 2020 07.
Article in English | MEDLINE | ID: covidwho-276856

ABSTRACT

BACKGROUND & AIMS: New York is the current epicenter of Coronavirus disease 2019 (COVID-19) pandemic. The underrepresented minorities, where the prevalence of obesity is higher, appear to be affected disproportionately. Our objectives were to assess the characteristics and early outcomes of patients hospitalized with COVID-19 in the Bronx and investigate whether obesity is associated with worse outcomes independently from age, gender and other comorbidities. METHODS: This retrospective study included the first 200 patients admitted to a tertiary medical center with COVID-19. The electronic medical records were reviewed at least three weeks after admission. The primary endpoint was in-hospital mortality. RESULTS: 200 patients were included (female sex: 102, African American: 102). The median BMI was 30 kg/m2. The median age was 64 years. Hypertension (76%), hyperlipidemia (46.2%), and diabetes (39.5%) were the three most common comorbidities. Fever (86%), cough (76.5%), and dyspnea (68%) were the three most common symptoms. 24% died during hospitalization (BMI < 25 kg/m2: 31.6%, BMI 25-34 kg/m2: 17.2%, BMI ≥ 35 kg/m2: 34.8%, p = 0.03). Increasing age (analyzed in quartiles), male sex, BMI ≥ 35 kg/m2 (reference: BMI 25-34 kg/m2), heart failure, CAD, and CKD or ESRD were found to have a significant univariate association with mortality. The multivariate analysis demonstrated that BMI ≥ 35 kg/m2 (reference: BMI 25-34 kg/m2, OR: 3.78; 95% CI: 1.45-9.83; p = 0.006), male sex (OR: 2.74; 95% CI: 1.25-5.98; p = 0.011) and increasing age (analyzed in quartiles, OR: 1.73; 95% CI: 1.13-2.63; p = 0.011) were independently associated with higher in-hospital mortality. Similarly, age, male sex, BMI ≥ 35 kg/m2 and current or prior smoking were significant predictors for increasing oxygenation requirements in the multivariate analysis, while male sex, age and BMI ≥ 35 kg/m2 were significant predictors in the multivariate analysis for the outcome of intubation. CONCLUSIONS: In this cohort of hospitalized patients with COVID-19 in a minority-predominant population, severe obesity, increasing age, and male sex were independently associated with higher in-hospital mortality and in general worse in-hospital outcomes.


Subject(s)
Betacoronavirus , Coronavirus Infections/mortality , Hospital Mortality , Obesity/complications , Pneumonia, Viral/mortality , Age Factors , Aged , Aged, 80 and over , Body Mass Index , COVID-19 , Coronavirus Infections/complications , Female , Humans , Logistic Models , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Retrospective Studies , SARS-CoV-2 , Sex Factors
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