Highlights CT severity score (CSS) could predict ICU admission, intubation, and mortality. Reticular pattern in lung CT scans, could be protective against adverse outcomes. CSS was weakly correlated with initial qSOFA score. CSS could not predict the length of stay in hospital.

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.

Background Insulin resistance (IR) and fat accumulation in visceral adipose tissue are key players in developing type 2 diabetes (T2D). Several adipose tissue derived-gene polymorphisms are related to higher body mass index (BMI), insulin resistance and T2D. The association of omentin rs2274907 (Val109Asp) and fat-mass and obesity-associated (FTO) rs9939609 gene polymorphisms with overweight/obesity and T2D is controversial. The aim of this study was to determine the association between omentin Val109Asp and FTO rs9939609 polymorphisms and insulin resistance in newly-diagnosed T2D patients. Methods The case-control study included 83 newly-diagnosed T2D patients and 85 healthy matched controls, aged 20–80 years. Fasting blood glucose and insulin levels were measured by the enzymatic method and enzyme-linked-immunosorbent assay, respectively. Insulin resistance was calculated using the homeostasis model assessment (HOMA) index. Genotyping was examined using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Results There are significant differences between both omentin Val109Asp and FTO rs9939609 polymorphisms and studied individuals ( P = 0.011 and P = 0.0001, respectively). Both genetic polymorphisms of omentin Val109Asp and FTO rs9939609 (T/A) are significantly related to higher HOMA index ( P = 0.030 and P = 0.046, respectively). However, omentin Val109Asp polymorphism was only related to individuals who were overweight/obese. Additionally, both omentin Val109Asp and FTO rs9939609 polymorphisms were significantly positively correlated to familial history of diabetes ( P = 0.046 and P = 0.024, respectively). Conclusions Omentin V109D and FTO rs9939609 genetic variations may change insulin metabolism and have key roles in developing T2D through insulin resistance. Thus, the evaluation of these polymorphic regions may be helpful for predicting type 2 diabetes.

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