Background/Aim: A wealth of immunological evidence points out that hyperglycemic status (regardless of diabetes) makes individuals more susceptible to infection as well as higher in-hospital complications. In this study, we primarily aimed to identify the clinical and biochemical negative impacts of hyperglycemia risk factor across the two comparative cohorts. Secondly, we also explored the prognosticating utilities of three proposed BG related prognosticators in moderate-severe admitted SARS-CoV-2 infected patients. Methods: This study was retrospectively between Mar 2020 and Sep 2021. All retrievable and calculated variables were thereafter divided into two studied cohorts, Survivors Cohort (Cohort I) and Non-Survivors Cohort (Cohort II). Independent and One-Sample T-Tests and Chi-Square Test were used for comparative analysis and relative risk estimation. The Receiver operating characteristic analysis was used to explore the area under the curve and the sensitivity analysis was also performed to investigate the optimal cutoff values for the BG related prognosticators. Results: The mean age of the whole study cohort was 59.40±10.60 years and the Non-Survivors Cohort were insignificantly younger than the Survivors Cohort. Survivors Cohort had insignificantly higher average blood glucose level than Non-Survivors Cohort. Oppositely, Survivors Cohort had significantly lower average total daily insulin dosing compared to Non-Survivors Cohort. The overall hospital Length of Stay (LOS) which it was significantly lower in Non-Survivors Cohort compared to Survivors Cohort. Conclusion: As there were many cconcerns for the effect of hyperglycemia on immune cells and subsequently the overall clinical impacts, there is an urgent necessity to track the daily blood glucose levels, the changes in blood glucose from baseline, or alternatively the insulin infusion rate to keep their averages around 149.9 mg/dL, -38% and 1.35 IU/hr.

Background/Aim: Having reliable indicators and markers that would help in prognosticating the survival are invaluable and would consequently assist in the course of effective treatment. Our objectives in this study were to compare the ability of SI and mSI to predict the primary outcomes of overall 28-day mortality rate in SARS-CoV-2 infected hemodynamic unstable critically ill patients. Methods: This study was retrospectively conducted and both of confirmed and suspected affected critically ill COVID-19 patients were included in our study. Hemodynamics variables of SI and mSI were mathematically calculated after dividing HR over SBP and MAP. All tested variables and others were comparatively compared across the two studied affected COVID-19 patients; Survivors Cohort (Cohort I) and Non-Survivors Cohort (Cohort II) using One Sample and Independent-T Tests in addition to Chi Square Test for categorical retrievable data. ROC curves were constructed for SI and mSI and the area under the ROC curves (AUROCs) were statistically compared using proposed Delong Method. The optimal operating cutoffs on each ROC curve for the two tested prognosticators were also investigated by picking the highest youden’s index. Results: The mean age of the whole study cohort was 51.88±16.22 years and the Non-Survivors Cohort were significantly older than the Survivors Cohort. Significantly, males were distributed in the study in approximately 2.57: 1 ratio compared to female. There were statistically significant differences regarding serum albumin levels profile during the 1st admission week, among the 3 serial albumin day levels. The overall incidences of NOPST were assessed at 65.9% during an average of 14.08±4.06 days. The Non-Survivors Cohort had also significantly higher SI and mSI compared to Survivors Cohort [1.16±0.14 bpm/mmHg and 1.67±0.23 bpm/mmHg versus 0.92±0.04 bpm/mmHg and 1.30±0.07 bpm/mmHg; +0.24±0.01 bpm/mmHg and -0.37±0.01 bpm/mmHg, respectively, p-value = 0.001]. SI had a higher AUROC than mSI with Area±SEM (95% CI; Range) of 0.983±0.002 (95% CI; 0.978-0.987) versus 0.959±0.004 (95% CI; 0.950-0.967) and the best cut-off values for SI and mSI were 0.99 bpm/mmHg and 1.43 bpm/mmHg, respectively. Conclusion: In summary, our stated hemodynamic based mortality prognosticators may be an early effective, no-cost bedside, realistic, reliable triaging modalities with high sensitivity, specificity, performance. Also, SI may be used as an additional or readily available red flag bedside assessment tool for severe disease.