Development of a clinical risk score to predict death in patients with COVID-19.

OBJECTIVE: To build a clinical risk score to aid risk stratification among hospitalised COVID-19 patients. METHODS: The score was built using data of 417 consecutive COVID-19 in patients from Kuwait. Risk factors for COVID-19 mortality were identified by multivariate logistic regressions and assigned weighted points proportional to their beta coefficient values. A final score was obtained for each patient and tested against death to calculate an Receiver-operating characteristic curve. Youden's index was used to determine the cut-off value for death prediction risk. The score was internally validated using another COVID-19 Kuwaiti-patient cohort of 923 patients. External validation was carried out using 178 patients from the Italian CoViDiab cohort. RESULTS: Deceased COVID-19 patients more likely showed glucose levels of 7.0-11.1 mmol/L (34.4%, p < 0.0001) or >11.1 mmol/L (44.3%, p < 0.0001), and comorbidities such as diabetes and hypertension compared to those who survived (39.3% vs. 20.4% [p = 0.0027] and 45.9% vs. 26.6% [p = 0.0036], respectively). The risk factors for in-hospital mortality in the final model were gender, nationality, asthma, and glucose categories (<5.0, 5.5-6.9, 7.0-11.1, or 11.1 > mmol/L). A score of ≥5.5 points predicted death with 75% sensitivity and 86.3% specificity (area under the curve (AUC) 0.901). Internal validation resulted in an AUC of 0.826, and external validation showed an AUC of 0.687. CONCLUSION: This clinical risk score was built with easy-to-collect data and had good probability of predicting in-hospital death among COVID-19 patients.

Mitochondrial DNA D-loop sequencing reveals obesity variants in an Arab population.

Background: The association of mitochondrial DNA (mtDNA) variations with obesity has been investigated in diverse populations across the world. However, such obesity-associated mtDNA examinations are rarely conducted in Arab populations. Materials and methods: We re-sequenced mtDNA displacement loop (D-loop) region of 395 Arab individuals of Kuwait. We categorized the individuals based on their BMI scores as obese (n=232; BMI ≥30 kg/m2), overweight (n=110; BMI ≥25 kg/m2 and <30 kg/m2), and lean (n=53; BMI <25 kg/m2). We performed all the statistical tests by combining obese and overweight individuals in one group. Association analyses were conducted applying Fisher's exact test and logistic regression model. Results: We identified that the mtDNA variations m.73A>G, and m.523delAC were positively correlated with obesity, while m.310T>C, and m.16318A>T were negatively associated. All these variants, except m.16318A>T, remain statistically significant after adjusting for age and gender. We found that the variant m.73A>G increases the likelihood of being obese by 6-fold, whereas haplogroup H decreases the probability of being obese in Arab individuals of Kuwait. Haplotype analysis revealed that a haplotype, A263G-C309CT-T310C, defining the H2a clade of H haplogroup, reduces the probability of being obese. Conclusion: Our study reports, for the first time, the obesity-related mtDNA variants in Arabs of Kuwait. Based on the mtDNA D-loop region variations, we detected particular variants and haplogroup that are related with increased and decreased probability of being obese in the Kuwait Arab population.

Impact of diabetic status on the hyperglycemia-induced adverse risk of short term outcomes in hospitalized patients with acute coronary syndromes in the Middle East: findings from the Gulf registry of Acute Coronary Events (Gulf RACE).

BACKGROUND: While glucose levels on admission are clearly a much stronger predictor of short term adverse outcomes than diabetes status, there is a paucity of data on how diabetes status impacts the hyperglycemia-induced increased risk. METHODS: 2786 patients admitted to the hospital with acute coronary syndrome (ACS) and diabetic level hyperglycemia (random >11.1 mmol/L or fasting >7 mmol/L) were identified from a Gulf registry of ACS. We divided the cohort into two groups. Those who were previously known to have diabetes mellitus were identified as the known diabetes group, and the non-diabetic group included those without a previous diabetes diagnosis. We used logistic regression models to assess the effect of glycemic status on hospital mortality and other patient outcomes including heart failure, stroke, recurrent ischemia, cardiogenic shock, major bleeding, and ventilation. RESULTS: About two-thirds of the hyperglycemics on admission had been diagnosed previously with diabetes. After adjusting for age, in-hospital mortality was significantly higher in the non-diabetic group (OR: 2.36; 95% CI 1.54-3.61) compared to the diabetic group. As for the other outcomes, known diabetes patients had significantly lower incidences of heart failure, cardiogenic shock, and ventilation compared to non-diabetic patients. CONCLUSION: The effects of hyperglycemia are mitigated by the presence of the chronic diabetic state, and thus, hyperglycemia has a worse effect in those not known to have chronic diabetes. These findings are important and call for further investigation.