Comparison of Framingham Cardiovascular Risk Criteria and ASCVD Score in Iranian Obese Patients

Background: Calculating and predicting the risk of disease plays an important role in preventive medicine. Today, some risk scores have been designed to estimate the risk of cardiovascular diseases (CVDs) by assessing different factors. Obesity is associated with an increased risk of cardiovascular disease, so we decided to calculate the possible risk of heart disease in obese Iranian people to suggest a more accurate calculator. Methods: In this cross-sectional study, we compared the data of 289 people from Framingham Risk Score and ASCVD Risk Score calculations who had been referred to Shariati Hospital Obesity Clinic, Tehran, Iran from 2016 to 2019. In the form of sub-goals, we examined other factors such as blood pressure and hepatic aminotransferases, etc. Results: The mean age of participants was 51.20±7.58 years, 86.2% being women. Of the whole, 19.72%, 31.83%, 21.11%, and 27.34% were categorized as overweight, Obese I, II, and III, respectively. According to the ASCVD score 80.3%, 4.8%, and 14.9%, and according to the Framingham score 95.5%, 3.5%, and 1% were classified as low-risk, intermediate-risk, and high-risk. Moreover, a fair agreement was observed between the two-risk score in the whole (Kappa=0.236; P<0.001), overweight (Kappa=0.304; P=0.028), Obese I (Kappa=0.210; P=0.048), Obese II (Kappa=0.268; P=0.015), and obese III (Kappa=0.202; P=0.023). Conclusion: Despite its age limit, ASCVD has a higher risk of CVDs, causing statin care (which has a protective role for cardiovascular disease) to be given to a larger population.  

Predictive value of initial CT scan for various adverse outcomes in patients with COVID-19 pneumonia

BACKGROUND

Chest computed tomography (CT) scan is frequently used in the diagnosis of COVID-19 pneumonia.

OBJECTIVES

This study investigates the predictive value of CT severity score (CSS) for length-of-stay (LOS) in hospital, initial disease severity, ICU admission, intubation, and mortality.

METHODS

In this retrospective study, initial CT scans of consecutively admitted patients with COVID-19 pneumonia were reviewed in a tertiary hospital. The association of CSS with the severity of disease upon admission and the final adverse outcomes was assessed using Pearson's correlation test and logistic regression, respectively.

RESULTS

Total of 121 patients (60±16 years), including 54 women and 67 men, with positive RT-PCR tests were enrolled. We found a significant but weak correlation between CSS and qSOFA, as a measure of disease severity (r: 0.261, p = 0.003). No significant association was demonstrated between CSS and LOS. Patients with CSS>8 had at least three-fold higher risk of ICU admission, intubation, and mortality.

CONCLUSIONS

CSS in baseline CT scan of patients with COVID-19 pneumonia can predict adverse outcomes and is weakly correlated with initial disease severity.

Clinical characteristics, outcomes, and risk factors for mortality in hospitalized patients with COVID-19 and cancer history: a propensity score-matched study

BACKGROUND

COVID-19 has caused great concern for patients with underlying medical conditions. We aimed to determine the prognosis of patients with current or previous cancer with either a PCR-confirmed COVID-19 infection or a probable diagnosis according to chest CT scan.

METHODS

We conducted a case control study in a referral hospital on confirmed COVID-19 adult patients with and without a history of cancer from February25th to April21st, 2020. Patients were matched according to age, gender, and underlying diseases including ischemic heart disease (IHD), diabetes mellitus (DM), and hypertension (HTN). Demographic features, clinical data, comorbidities, symptoms, vital signs, laboratory findings, and chest computed tomography (CT) images have been extracted from patients' medical records. Multivariable logistic regression was used to estimate odd ratios and 95% confidence intervals of each factor of interest with outcomes.

RESULTS

Fifty-three confirmed COVID-19 patients with history of cancer were recruited and compared with 106 non-cancerous COVID-19 patients as controls. Male to female ratio was 1.33 and 45% were older than 65. Dyspnea and fever were the most common presenting symptoms in our population with 57.86 and 52.83% respectively. Moreover, dyspnea was significantly associated with an increased rate of mortality in the cancer subgroup (p = 0.013). Twenty-six patients (49%) survived among the cancer group while 89 patients (84%) survived in control (p = 0.000). in cancer group, patients with hematologic cancer had 63% mortality while patients with solid tumors had 37%. multivariate analysis model for survival prediction showed that history of cancer, impaired consciousness level, tachypnea, tachycardia, leukocytosis and thrombocytopenia were associated with an increased risk of death.

CONCLUSION

In our study, cancer increased the mortality rate and hospital stay of COVID-19 patients and this effect remains significant after adjustment of confounders. Compared to solid tumors, hematologic malignancies have been associated with worse consequences and higher mortality rate. Clinical and para-clinical indicators were not appropriate to predict death in these patients.

A Methodology to Extract a New Set of Core Indicators of the Information Society

Most contributions that have analyzed the information society complain about the lack of a more standardized and elaborated operationalization. In this article, a methodology is presented to extract the indicators that attempt to appropriately measure the information society and serve as the basis and standard for internationally comparable information society statistics. These indicators, which are called core indicators of the information society, are extracted by studying and analyzing 39 reputable information society and digital divide models and using content analysis, entropy method, Scree test, and Pareto analysis. The proposed methodology is developed as a reaction against the limitation of the non-existence of numerical values for some indicators in the majority of countries. Finally, comparing the global core indicators of the information society and the proposed ones, it reveals that the global core indicators of the information society have ignored two important dimensions: e-learning and networked world enablers.