[1] Y. Adu-Agyeiwaah, M.B. Grant and A.G. Obukhov, The potential role of osteopontin and furin in worsening
disease outcomes in COVID-19 patients with pre-existing diabetes, Cells 9(11) (2020) 2528.
[2] C. Akarsu, M. Karabulut, H. Aydin, N.A. Sahbaz, A.C. Dural, D. Yegul and G.T. Adas, Association between
acute pancreatitis and COVID-19: could pancreatitis be the missing piece of the puzzle about increased mortality
rates?, J. Invest. Surgery 35 (2020) 1–7.
[3] L.N. Bachache, J.A. Hasan and A.Q. Al-Neami, Acousto-optic Design to Measure Glucose Level for Diabetic
Patients Non-invasively, In J. Phys. Conf. Ser. 1818(1) (2021) 012147.[4] Z.T. Bloomgarden, Diabetes and COVID-19, J. Diabetes 12(4) (2020) 347–348.
[5] M.M. Burlew, E.L. Madsen, J.A. Zagzebski, R.A. Banjavic and S.W. Sum, A new ultrasound tissue-equivalent
material, Radiol. Phys. J. 134(2) (1980) 517–520.
[6] E.N. Carlsen, Ultrasound physics for the physician a brief review, J. Clinic. Ultrasound 3 (1975) 69–75.
[7] Y. Cheng, L. Yue, Z. Wang, J. Zhang and G. Xiang, Hyperglycemia associated with lymphopenia and disease
severity of COVID-19 in type 2 diabetes mellitus, J. Diabetes . Compl. 35(2) (2021) 107809.
[8] W.L. Clarke, The original Clarke error grid analysis (EGA), Diabetes Technol. Therap. 7(5) (2005) 776–779.
[9] D.J. Cox, L.A. Gonder-Frederick, B.P. Kovatchev, D.M. Julian and W.L. Clarke, Understanding error grid
analysis, Diabetes Care 20(6) )1997( 911.
[10] G. Jin, X. Zhang, W. Fan, Y. Liu and P. He, Design of non-contact infrared thermometer based on the sensor of
MLX, Open Autom. Control Syst. J. 7(1) (2015) 8–20.
[11] S. Gl¨aser, S. Kr¨uger, M. Merkel, P. Bramlage and F.J. Herth, Chronic obstructive pulmonary disease and diabetes
mellitus: a systematic review of the literature, Respiration 89(3) (2015) 253–264.
[12] I. Kapoor, H. Prabhakar and C. Mahajan, Introduction: History of Coronavirus Disease Pandemic, Clinical
Synopsis of COVID-19, Springer, Singapore, (2020) 1–4.
[13] S.A. Lee, M.C. Jobe, A.A. Mathis, J.A. Gibbons, Incremental validity of coronaphobia: Coronavirus anxiety
explains depression, J. Anxiety Disord 74 (2020) 102268.
[14] J.A. McGrath, R.A.J. Eady and F.M. Pope, Anatomy and organization of human skin, Rook’s Textbook of
Dermatology 1 (2016) 2–3.
[15] Melexis inspired engineering, Datasheet Single and Dual Zone Infra Red Thermometer in TO-39, MLX90614
family datasheet, 2019.
[16] E. Merzon, I. Green, M. Shpigelman, S. Vinker, I. Raz, A. Golan-Cohen and R. Eldor, Haemoglobin A1c is a
predictor of COVID-19 severity in patients with diabetes, Diabetes/metabol. Res. Rev. 37(5) (2021) e3398.
[17] S. Nazar Haddad and R. Istepanian, A feasibility study of mobile phone text messaging to support education and
management of type 2 diabetes in Iraq, Diabetes Technol. Therap. 16(7) (2014) 454–459.
[18] F.J. Pasquel and G.E. Umpierrez, Individualizing inpatient diabetes management during the Coronavirus disease
2019 pandemic, J. Diabetes Sci. Technol. 14(4) (2020) 705–707.
[19] M.C. Petersen G.I. Shulman, Mechanisms of insulin action and insulin resistance, Physiol. Rev. 98(4) (2018)
2133–2223.
[20] A. Pf¨utzner, D.C. Klonoff, S. Pardo and J.L. Parkes, Technical aspects of the Parkes error grid, J. Diabetes Sci.
Technol. 7(5) (2013) 1275–1281.
[21] B. Shirin, Diabetes mellitus and gestational diabetes mellitus, J. Paediatric Surg. Bangl. 5(1) (2015) 30–35.
[22] A.K. Singh, R. Gupta, A. Ghosh and A. Misra, Diabetes in COVID-19: Prevalence, pathophysiology, prognosis
and practical considerations, Diabetes Metab Syndr. 14(4) (2020) 303–310.
[23] A.K. Singh, R. Gupta, A. Ghosh and A. Misra, Diabetes in COVID-19: Prevalence, pathophysiology, prognosis
and practical considerations, Diabetes Metabol. Syndr. Clinical Res. Rev. 14(4) (2020) 303–310.
[24] G. Wilcox, Insulin and insulin resistance, Clinical Bioch. Rev. 26(2) (2005) 19.