The Association Between Bone Remodeling Markers, genes polymorphisms with Incidence of Osteopenia Among Young Saudi Female.

Osteopenia and osteoporosis, are prevalent skeletal systemic conditions, cause weaker bones and an increased risk of fragility fractures. This work is aimed to evaluate the relation between bone-remolding markers and genotypes of four single nucleotide polymorphisms in young Saudi females (rs2297480 of farnesyl diphosphate synthase (FDPS), rs3736228 of Low-density lipoprotein receptor-related protein 5 (LRP5), rs1234612 of sclerostin (SOST), and rs9934438 of Vitamin K epoxide reductase complex subunit 1  (VKORC1) ). For this purpose, 750 premenopausal females aged 18 to 40 years old, either university students, postgraduates, or university employees were recruited and divided into three groups according to bone mineral density BMD (g/cm2) divided by T score into osteoporosis (n = 12), osteopenia (n = 147), and normal (n = 591). Serum SOST, BALP, calcium, phosphate, ALP, albumin, beta-CTXs and human VDR levels were determined. TaqMan SNP Genotyping assays were used to genotype four polymorphisms using real-time PCR (applied biosystem). Results showed that BALP, CTX-1 and SOST were significantly higher in the osteoporosis and osteopenia groups than in the normal group. Bone mineral density readings were considerably lower in females with the GG genotype in FDPS rs2297480 and TT genotype in LRP5 rs3736228, which increase the risk for osteopenia by 3. 6-fold and 3. 06-fold than control respectively. Also, females with the TT genotype in LRP5 rs3736228 have decreased average values for Bone Mineral Density. In conclusion, the GG genotype of FDPS rs2297480 and the TT genotype of LRP5 rs3736228 was shown to be strongly associated with osteopenia in young Saudi females with low bone mineral density and SOST levels.

Performance features and mortality prediction of the 4C Score early in COVID-19 infection: a retrospective study in Saudi Arabia.

The ISARIC4C consortium developed and internally validated the 4C Score for prediction of mortality only in hospitalized patients. We aimed to assess the validity of the 4C Score in mortality prediction of patients with COVID-19 who had been home isolated or hospitalized.This retrospective cross-sectional study was performed after the first wave of COVID-19. Data of all PCR-positive COVID-19 patients who had been discharged, hospitalized, or died were retrospectively analyzed. Patients were classified into four risk groups according to the 4C Mortality Score. A total of (506) patients were classified as follows: low (57.1%), intermediate (27.9%), high (13%), and very high (2%) risk groups. Clinical, radiological, and laboratory data were significantly more severe in the high and very high-risk groups compared with other groups (p<0.001 for all). Mortality rate was correctly estimated by the model with 71% sensitivity, 88.6% specificity, and area under the curve of 0.9. The mortality rate was underestimated among the very high-risk group (66.2% vs 90%). The odds of mortality were significantly greater in the presence of hypoxia (OR 2.6, 95% CI 1.5 to 4.6, p<0.001) and high respiratory rate (OR 5.3, 95% CI 1.6 to 17.9, p<0.007), C reactive protein (CRP) (OR 3.5, 95% CI 1.8 to 6.8, p<0.001), and blood urea nitrogen (BUN) (OR 1.9, 95% CI 1.3 to 3.1, p<0.002). Other components of the model had non-significant predictions. In conclusion, the 4C Mortality Score has good sensitivity and specificity in early risk stratification and mortality prediction of patient with COVID-19. Within the model, only hypoxia, tachypnea, high BUN, and CRP were the independent mortality predictors with the possibility of overlooking other important predictors.