Predictors of New-Onset Diabetes in Hospitalized Patients with SARS-CoV-2 Infection
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Patient Selection
2.2. Clinical Data
2.3. Bloodwork Data
2.4. Statistical Method
2.5. Ethics Considerations
3. Results
3.1. Characteristics of Enrolled Patients and NOD Incidence
3.2. Hematological and Bio-Humoral Parameters Analysis
3.3. Predictors of NOD
4. Discussion
Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
- Osuagwu, U.L.; Miner, C.A.; Bhattarai, D.; Mashige, K.P.; Oloruntoba, R.; Abu, E.K.; Ekpenyong, B.; Chikasirimobi, T.G.; Goson, P.C.; Ovenseri-Ogbomo, G.P.; et al. Misinformation about COVID-19 in Sub-Saharan Africa: Evidence from a cross-sectional survey. Health Secur. 2021, 19, 44–56. [Google Scholar] [CrossRef]
- Moline, H.L.; Whitaker, M.; Deng, L.; Rhodes, J.C.; Milucky, J.; Pham, H.; Patel, K.; Anglin, O.; Reingold, A.; Chai, S.J.; et al. Effectiveness of COVID-19 Vaccines in Preventing Hospitalization among Adults Aged > 65 years—COVID-NET, 13 States, February–April 2021. MMWR Recomm. Rep. 2021, 70, 1088–1093. [Google Scholar] [CrossRef] [PubMed]
- Weinreich, D.M.; Sivapalasomgam, S.; Norton, T.; Ali, S.; Gao, H.; Bhore, R.; Xio, J.; Hooper, A.T.; Hamilton, J.D.; Musser, B.J.; et al. REGEN-COV Antibody Combination and Outcomes in Outpatients with COVID-19. N. Engl. J. Med. 2021, 385, e81. [Google Scholar] [CrossRef] [PubMed]
- Zhou, F.; Yu, T.; Du, J.; Fan, G.; Liu, Y.; Liu, Z.; Xiang, J.; Wang, Y.; Song, B.; Gu, X.; et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet 2020, 395, 1054–1062. [Google Scholar] [CrossRef]
- Alves, V.P.; Casemiro, F.G.; Araujo, B.G.; Souza Lima, M.A.; Oliveira, R.S.; Souza Fernandes, F.T.; Gomes, A.V.C.; Gregori, D. Factors associated with mortality among elderly people in the covid-19 pandemic (SARS-cov2): A systematic rewiew and meta-analysis. Int. J. Environ. Res. Public Health 2021, 18, 8008. [Google Scholar] [CrossRef] [PubMed]
- Butkiewicz, S.; Zaczyriski, A.; Hampel, M.; Pańkowski, I.; Galazkowski, R.; Rzońca, P. Analysis of Risk Factors for In-Hospital Death due to COVID-19 in Patients Hospitalised at the Temporary Hospital Located at the National Stadium in Warsaw: A Retrospective Analysis. Int. J. Environ. Res. Public Health 2022, 19, 3932. [Google Scholar] [CrossRef]
- Li, H.; Tian, S.; Chen, T.; Cui, Z.; Shi, N.; Zhong, X.; Qiu, K.; Zhang, J.; Zeng, T.; Chen, L.; et al. Newly diagnosed diabetes is associated with a higher risk of mortality than known diabetes in hospitalized patients with COVID-19. Diabetes Obes. Metab. 2020, 22, 1897–1906. [Google Scholar] [CrossRef]
- Gorjão, R.; Hirabara, S.M.; Masi, L.N.; Serdan, T.D.A.; Gritte, R.B.; Hatanaka, E.; Souza-Siqueira, T.; Pithon-Curi, A.C.; Lima, T.M.; Pithon-Curi, T.C.; et al. Poor prognosis indicators of type-2 diabetic COVID-19 patients. Braz. J. Med. Biol. Res. 2022, 55, 1–11. [Google Scholar] [CrossRef] [PubMed]
- Sękowskii, K.; Grudziąż-Sękowska, J.; Goryński, P.; Pinkas, J.; Jankowski, M. Epidemiological Analysis of Diabetes-Related Hospitalization in Poland before and during the COVID-19 Pandemic, 2014–2020. Int. J. Environ. Res. Public Health 2022, 19, 10030. [Google Scholar] [CrossRef] [PubMed]
- Williams, R.; Karuranga, S.; Malanda, B.; Saeedi, B.; Basit, A.; Besançon, S.; Bommer, C.; Esteghamati, A.; Ogurtsova, K.; Zhang, P.; et al. Global and regional estimates and projections of diabetes-related health expenditure: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res. Clin. Pract. 2020, 162, 108072. [Google Scholar] [CrossRef] [PubMed]
- Sathish, T.; Kapoor, N.; Cao, Y.; Tapp, R.J.; Zimmet, P. Proportion of newly-diagnosed diabetes in COVID-19 patients: A systematic review and meta-analysis. Diabetes Obes. Metab. 2021, 23, 870–874. [Google Scholar] [CrossRef] [PubMed]
- Shrestha, D.B.; Budhathoki, P.; Raut, S.; Adhikari, S.; Ghimire, P.; Thapaliya, S.; Rabaan, A.A.; Karki, B.J. New-onset diabetes in COVID-19 and clinical outcomes: A systematic review and meta-analysis. World J. Virol. 2021, 10, 275–287. [Google Scholar] [CrossRef] [PubMed]
- Beyerstedt, S.; Casaro, E.B.; Rangel, E.B. COVID-19: Angiotensin-converting enzyme 2 (ACE2) expression and tissue susceptibility to SARS-CoV-2 infection. Eur. J. Clin. Microbiol. Infect. Dis. 2021, 40, 905–919. [Google Scholar] [CrossRef] [PubMed]
- Apicella, M.; Campopiano, M.C.; Mantuano, M.; Mazoni, L.; Copelli, A.; Del Prato, S. COVID-19 in people with diabetes: Understanding the reasons for worse outcomes. Lancet Diabetes Endocrinol. 2020, 8, 782–792. [Google Scholar] [CrossRef]
- World Health Organization. COVID-19: Case Definition. Updated in Public Health Surveillance for COVID-19; WHO: Geneva, Switzerland, 2020. [Google Scholar]
- American Diabetes Association. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes. Diabetes Care 2022, 45, 17–38. [Google Scholar] [CrossRef]
- Romanian Ministry of Health. ORDIN nr. 2054/2020 Din 27 Noiembrie 2020 Privind Modificarea Anexei la Ordinul Ministrului Sănătății nr 487/2020 Pentru Aprobarea Protocolului de Tratament al Infecției cu Virusul SARS-CoV-2. Available online: http://www.casan.ro/cascov/post/type/local/comunicat-ordin-nr-2054-2020-din-27-noiembrie-2020.html (accessed on 23 March 2021).
- Youden, W.J. Index for rating diagnostic tests. Cancer 1950, 3, 32–35. [Google Scholar] [CrossRef]
- Fluss, R.; Faraggi, D.; Reiser, B. Estimation of Youden index and its associated cutoff point. Biom. J. 2005, 47, 458–472. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Perkins, N.J.; Schisterman, E.F. The Youden index and the optimal cut-point corrected for measurement error. Biom. J. 2005, 47, 428–441. [Google Scholar] [CrossRef]
- Smith, S.M.; Boppana, A.; Traupman, J.A.; Unson, E.; Maddock, D.A.; Chao, K.; Dobesh, D.P.; Brufsky, A.; Connor, R.I. Impaired glucose metabolism in patients with diabetes, prediabetes, and obesity is associated with severe COVID-19. J. Med. Virol. 2021, 93, 409–415. [Google Scholar] [CrossRef] [PubMed]
- Opal, S.M.; Girard, T.D.; Ely, E.W. The immunopathogenesis of sepsis in elderly patients. Clin. Infect. Dis. 2005, 41, 504–512. [Google Scholar] [CrossRef] [PubMed]
- Kirkman, M.S.; Briscoe, V.J.; Clark, N.; Florez, H.; Haas, L.B.; Halter, J.B.; Huang, E.S.; Korytkowski, M.T.; Munshi, M.N.; Odegard, P.S.; et al. Diabetes in older adults. Diabetes Care 2012, 35, 2650–2664. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lee, P.G.; Halter, J.B. The pathophysiology of hyperglycemia in older adults: Clinical considerations. Diabetes Care 2017, 40, 444–452. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chen, M.; Bergman, R.N.; Pacini, G.; Porte, D. Pathogenesis of Age-Related Glucose Intolerance in Man: Insulin Resistance and Decreased β-Cell Function. J. Clin. Endocrinol. Metab. 1985, 60, 13–20. [Google Scholar] [CrossRef] [PubMed]
- Martha, J.W.; Wibowo, A.; Pranata, R. Prognostic value of elevated lactate dehydrogenase in patients with COVID-19: A systematic review and meta-analysis. Postgrad. Med. J. 2022, 98, 422–427. [Google Scholar] [CrossRef]
- Farag, A.A.; Hassanin, H.M.; Soliman, H.H.; Sallam, A.; Sediq, A.M.; Elbaser, E.S.A.; Elbanna, K. Newly diagnosed diabetes in patients with COVID-19: Different types and short-term outcomes. Trop. Med. Infect. Dis. 2021, 6, 142. [Google Scholar] [CrossRef]
- Hsu, P.P.; Sabatini, D.M. Cancer cell metabolism: Warburg and beyond. Cell 2008, 134, 703–707. [Google Scholar] [CrossRef] [Green Version]
- Henry, B.M.; Aggarwal, G.; Wong, J.; Benoit, S.; Vikse, J.; Plebani, M.; Lippi, G. Lactate dehydrogenase levels predict coronavirus disease 2019 (COVID-19) severity and mortality: A pooled analysis. Am. J. Emerg. Med. 2020, 38, 1722–1726. [Google Scholar] [CrossRef]
- Thorburn, A.W.; Gumbiner, B.; Bulacan, F.; Wallace, P.; Henry, R.R. Intracellular glucose oxidation and glycogen synthase activity are reduced in non-insulin-dependent (type II) diabetes independent of impaired glucose uptake. J. Clin. Investig. 1990, 85, 522–529. [Google Scholar] [CrossRef]
- Richter, E.A.; Garetto, L.P.; Goodman, M.N.; Ruderman, N.B. Muscle glucose metabolism following exercise in the rat. Increase sensitivity to insulin. J. Clin. Investig. 1982, 69, 785–793. [Google Scholar] [CrossRef] [PubMed]
- Berhane, F.; Fite, A.; Daboul, N.; Al-Janabi, W.; Msallaty, Z.; Caruso, M.; Lewis, M.K.; Yi, Z.; Diamond, M.P.; Abou-Samra, A.-B.; et al. Plasma lactate levels increase during hyperinsulinemic euglycemic clamp and oral glucose tolerance test. J. Diabetes Res. 2015, 2015, 102054. [Google Scholar] [CrossRef] [PubMed]
- Akbariqomi, M.; Hosseini, M.S.; Rashidiani, J.; Sedighian, H.; Biganeh, H.; Heidari, R.; Moghaddam, M.M.; Farnoosh, G.; Kooshiki, H. Clinical characteristics and outcome of hospitalized COVID-19 patients with diabetes: A single-center, retrospective study in Iran. Diabetes Res. Clin. Pract. 2020, 169, 108467. [Google Scholar] [CrossRef]
- Birabaharan, M.; Kaelber, D.C.; Pettus, J.H.; Smith, D.M. Risk of new-onset type 2 diabetes in 600,055 people after COVID-19: A cohort study. Diabetes Obes, Metab. 2022, 24, 1176–1179. [Google Scholar] [CrossRef] [PubMed]
- Wu, Y.; Ding, Y.; Tanaka, Y.; Zhang, W. Risk factors contributing to type 2 diabetes and recent advances in the treatment and prevention. Int. J. Med. Sci. 2014, 6, 1185–1200. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sowers, J.R. Diabetes mellitus and vascular disease. Hypertension 2013, 61, 943–947. [Google Scholar] [CrossRef]
- Fadini, G.P.; Morieri, M.L.; Boscari, F.; Fioretto, P.; Maran, A.; Busetto, L.; Bonora, B.M.; Selmin, E.; Arcidiacono, G.; Pinelli, S.; et al. Newly-diagnosed diabetes and admission hyperglycemia predict COVID-19 severity by aggravating respiratory deterioration. Diabetes Res. Clin. Pract. 2020, 168, 108374. [Google Scholar] [CrossRef] [PubMed]
- Tobin, M.J.; Laghi, F.; Jubran, A. Why COVID-19 silent hypoxemia is baffling to physicians. Am. J. Respir. Crit. Care Med. 2020, 202, 356–360. [Google Scholar] [CrossRef]
- Wichmann, D.; Sperhake, J.P.; Lütgehetmann, M.; Steurer, S.; Elder, C.; Heinemann, A.; Heinrich, F.; Mushumba, H.; Kniep, I.; Schröder, A.S.; et al. Autopsy findings and venous thromboembolism in patients with COVID-19: A prospective cohort study. Ann. Intern. Med. 2020, 173, 268–277. [Google Scholar] [CrossRef] [PubMed]
- Kaur, R.; Kaur, M.; Singh, J. Endothelial dysfunction and platelet hyperactivity in type 2 diabetes mellitus: Molecular insight and therapeutic strategies. Cardiovasc. Diabetol. 2018, 17, 121. [Google Scholar] [CrossRef] [PubMed]
- Gęca, T.; Wojtowicz, K.; Guzik, P.; Góra, T. Increased Risk of COVID-19 in Patients with Diabetes Mellitus—Current Challenges in Pathophysiology, Treatment and Prevention. Int. J. Environ. Res. Public Health 2022, 19, 6555. [Google Scholar] [CrossRef]
- Chai, C.; Chen, K.; Li, S.; Cheng, G.; Wang, W.; Wang, H.; Wei, D.; Peng, C.; Sun, Q.; Tang, Z. Effect of elevated fasting blood glucose level on the 1-year mortality and sequelae in hospitalized COVID-19 patients: A bidirectional cohort study. J. Med. Virol. 2022, 94, 3240–3250. [Google Scholar] [CrossRef] [PubMed]
- Wang, S.; Ma, P.; Zhang, S.; Song, S.; Wang, Z.; Ma, Y.; Xu, J.; Wu, F.; Duan, L.; Yin, Z.; et al. Fasting blood glucose at admission is an independent predictor for 28-day mortality in patients with COVID-19 without previous diagnosis of diabetes: A multi-centre retrospective study. Diabetologia 2020, 63, 2102–2111. [Google Scholar] [CrossRef] [PubMed]
- Mehta, P.; McAuley, D.F.; Brown, M.; Sanchez, E.; Tattersall, R.S.; Manson, J.J. COVID-19: Consider cytokine storm syndromes and immunosuppression. Lancet 2020, 395, 1033–1034. [Google Scholar] [CrossRef]
- Zhang, C.; Xiao, C.; Wang, P.; Xu, W.; Zhang, A.; Qing, L.; Xu, X. The alteration of Th1/Th2/Th17/Treg paradigm in patients with type 2 diabetes mellitus: Relationship with diabetic nephropathy. Hum. Immunol. 2014, 75, 289–296. [Google Scholar] [CrossRef]
- Hussain, A.; Bhowmik, B.; Vale Moreira, N.C. COVID-19 and diabetes: Knowledge in progress. Diabetes Res. Clin. Pract. 2020, 162, 108142. [Google Scholar] [CrossRef] [PubMed]
- Lin, Z.; Yang, Y.; Chen, X.; Xu, L.; Yang, M. Serum ferritin as an independent risk factor for severity in COVID-19 patients. J. Infect. 2020, 81, 647–679. [Google Scholar] [CrossRef] [PubMed]
- Ma, R.C.W.; Holt, R.I.G. COVID-19 and diabetes. Diabet. Med. 2020, 37, 723–725. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Adaikalakoteswari, A.; Rema, M.; Mohan, V.; Balasubramanyam, M. Oxidative DNA damage and augmentation of poly (ADP-ribose) polymerase/nuclear factor-kappa B signaling in patients with Type 2 diabetes and microangiopathy. Int. J. Biochem. Cell Biol. 2007, 39, 1673–1684. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Henry, B.M.; de Olivera, M.H.S.; Benoit, S.; Plebani, M.; Lippi, G. Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): A meta-analysis. Clin. Chem. Lab. Med. 2020, 58, 1021–1028. [Google Scholar] [CrossRef] [Green Version]
- Alqahtani, A.; Alamer, E.; Mir, M.; Alasmari, A.; Alshahrani, M.M.; Asiri, M.; Ahmad, I.; Alhazmi, A.; Algaissi, A. Bacterial Coinfections Increase Mortality of Severely Ill COVID-19 Patients in Saudi Arabia. Int. J. Environ. Res. Public Health 2022, 19, 2424. [Google Scholar] [CrossRef]
- Kapugi, M.; Cunningham, K. Corticosteroids. Orthop. Nurs. 2019, 38, 336–339. [Google Scholar] [CrossRef]
- Metwally, A.A.; Mehta, P.; Johnson, B.S.; Nagarjuna, A.; Snyder, M.P. COVID-19-Induced New-Onset Diabetes: Trends and Technologies. Diabetes 2021, 70, 2733–2744. [Google Scholar] [CrossRef] [PubMed]
- Neuhauser, H.K. The metabolic syndrome. Lancet 2005, 366, 1922–1930. [Google Scholar] [CrossRef]
- Laws, A.; Hoenn, H.M.; Selby, J.V.; Saad, M.F.; Haffner, S.M.; Howard, B.V. Differences in Insulin Suppression of Free Fatty Acid Levels by Gender and Glucose Tolerance Stuatus. Arterioscler. Thromb. Vasc. Biol. 1997, 17, 64–71. [Google Scholar] [CrossRef] [PubMed]
- Reiterer, M.; Rajan, M.; Gomez-Banoy, N.; Lau, J.D.; Gomez-Escobar, L.G.; Ma, L.; Gilani, A.; Alvarez-Mulett, S.; Sholle, E.T.; Chandar, V.; et al. Hyperglycemia in acute COVID-19 is characterized by insulin resistance and adipose tissue infectivity by SARS-CoV-2. Cell Metab. 2021, 33, 2174–2188. [Google Scholar] [CrossRef]
- Perez, A.; Jansen-Chaparro, S.; Saigi, I.; Bernal-Lopez, M.R.; Miñambres, I.; Gomez-Huelgas, R. Glucocorticoid-induced hyperglycemia. J. Diabetes 2014, 6, 9–20. [Google Scholar] [CrossRef]
- Yang, J.K.; Jin, J.-M.; Liu, S.; Bai, P.; He, W.; Wu, F.; Liu, X.F.; Chai, Z.L.; Han, D.M. New onset COVID-19 related diabetes: An indicator of mortality. medRxiv 2020. [Google Scholar] [CrossRef]
Characteristics | Total Patients n = 219 | Without NOD n = 161 | NOD n = 58 | p-Value | |||||
---|---|---|---|---|---|---|---|---|---|
Age, years (median; Q1,Q3) | 69.0 | [60.0–77.5] | 69.0 | [60.0–78.0] | 66.5 | [62.0–74.0] | 0.762 | ||
Gender, n (%) | Men | 129 | 58.9 | 90 | 55.9 | 39 | 67.2 | 0.162 | |
Comorbidities, n (%) | Obesity (BMI ≥ 30 kg/m2) | 78 | 35.6 | 53 | 60.2 | 25 | 69.4 | 0.414 | |
Hypertension | 146 | 66.7 | 101 | 62.7 | 45 | 77.6 | 0.051 | ||
Ischemic heart disease | 12 | 5.5 | 9 | 5.6 | 3 | 5.2 | 0.247 | ||
Heart failure | 31 | 14.2 | 24 | 14.9 | 7 | 12.1 | 0.864 | ||
Atrial fibrillation | 27 | 12.3 | 21 | 13.0 | 6 | 10.3 | 0.333 | ||
Stroke | 16 | 7.3 | 14 | 8.7 | 2 | 3.4 | 0.109 | ||
Asthma | 19 | 8.7 | 13 | 8.1 | 6 | 10.3 | 0.869 | ||
COPD | 26 | 11.9 | 18 | 11.2 | 8 | 13.8 | 0.869 | ||
CKD | 22 | 10.0 | 17 | 10.6 | 5 | 8.6 | 0.400 | ||
Cancer | 25 | 11.4 | 20 | 12.4 | 5 | 8.6 | 0.202 | ||
Signs and symptoms, n (%) | Fever | 97 | 44.3 | 69 | 42.9 | 28 | 48.3 | 0.052 | |
Cough | 148 | 67.6 | 105 | 65.2 | 43 | 74.1 | 0.364 | ||
Dyspnea | 127 | 58 | 85 | 52.8 | 42 | 72.4 | 0.013 | ||
Taste loss | 14 | 6.4 | 13 | 8.1 | 1 | 1.7 | 0.047 | ||
Faintness | 6 | 2.7 | 6 | 3.7 | 0 | 0.0 | 0.080 | ||
Pain Chest pain Headache Abdominal pain | 23 25 12 | 10.5 11.4 5.5 | 14 19 7 | 8.7 11.8 4.3 | 9 6 5 | 15.5 10.3 8.6 | 0.269 | ||
Onset of symptom to, days (median; Q1–Q3) | Hospital admission | 3.0 | [1.0–7.0] | 3.0 | [1.0–7.0] | 3.5 | [2.0–6.5] | 0.554 | |
Confirmation of COVID-19 | 1.0 | [0.0–3.0] | 1.0 | [0.0–3.0] | 1.0 | [0.0–3.0] | 0.506 | ||
Hospitalization duration, days (median; Q1-Q3) | 10.0 | [6.0–14.0] | 9.0 | [5.0–13.0] | 12.5 | [9.0–16.0] | <0.0001 | ||
Disease severity, n (%) | Mild | 30 | 13.7 | 29 | 18.0 | 1 | 1.7 | 0.001 | |
Moderate | 50 | 22.8 | 40 | 24.8 | 10 | 17.2 | |||
Severe | 139 | 63.5 | 92 | 57.1 | 47 | 81.0 | |||
Frequency of dexamethasone administration, n (%) | 174 | 79.5 | 123 | 76.4 | 51 | 87.9 | 0.155 | ||
Need of ICU, n (%) | 30 | 13.7 | 17 | 10.6 | 13 | 22.4 | 0.043 |
Parameters | Total Patients n = 219 | Without NOD n = 161 | NOD n = 58 | p-Value | |||
---|---|---|---|---|---|---|---|
Median | [Q1; Q3] | Median | [Q1; Q3] | Median | [Q1; Q3] | ||
White blood cells, ×/L | 7.54 | [5.3–10.6] | 7.2 | [5.2–3.7] | 9.4 | [5.3–11.2] | 0.093 |
Lymphocyte count, ×/L | 0.96 | [0.7–1.4] | 1.0 | [0.7–1.4] | 0.8 | [0.6–1.3] | 0.195 |
Neutrophil count, ×/L | 5.81 | [3.9–9.1] | 5.4 | [3.8–8.0] | 7.6 | [4.1–10.1] | 0.051 |
Hemoglobin, g/dL | 13.4 | [12.1–14.3] | 13.3 | [11.8–14.4] | 13.5 | [12.5–14.3] | 0.264 |
Platelets count, ×/L | 228.5 | [177.0–300.0] | 230.0 | [177.0–302.0] | 225.0 | [172.0–285.0] | 0.603 |
C-reactive protein, mg/L | 54.65 | [17.2–89.8] | 53.9 | [15.7–84.3] | 56.4 | [25.6–95.2] | 0.065 |
D-dimer, µg/mL | 526.0 | [259.0–1789.0] | 499.5 | [175.0–1389.0] | 621.0 | [352.0–2475.0] | 0.224 |
Ferritin (ng/mL) | 579.0 | [270.9–999.0] | 533.1 | [259.4–965.0] | 769.5 | [337.4–1318.5] | 0.015 |
LDH, U/L | 503.0 | [387.5–739.5] | 488.5 | [383.5–664.5] | 662.0 | [443.5–851.5] | 0.015 |
Creatinine (mg/dL) | 1.0 | [0.9–1.3] | 1.0 | [0.9–1.2] | 1.1 | [1.0–1.3] | 0.23 |
Clearance creatinine mL/min/1.73 m2 | 65.0 | [51.0–81.0] | 67.0 | [51.0–82.5] | 61.5 | [43.0–77.0] | 0.416 |
FPG, mg/dL | 118.5 | [99.0–154.0] | 107.5 | [95.0–136.0] | 149.5 | [126.0–166.0] | <0.0001 |
HbA1c, % | 5.5 | [5.1–6.4] | 5.4 | [5.4–5.7] | 5.5 | [5.1–6.5] | 1 |
Triglycerides, mg/dL | 149.0 | [103.0–202.0] | 143.5 | [98.0–201.0] | 168.0 | [117.0–203.0] | 0.099 |
pH | 7.5 | [7.4–7.5] | 7.5 | [7.4–7.5] | 7.5 | [7.4–7.5] | 0.621 |
PaO2, mmHg | 58.0 | [48.0–73.0] | 63.0 | [51.0–74.5] | 53.1 | [47.5–67.5] | 0.064 |
PaCO2 mmHg | 34.0 | [30.0–38.0] | 35.0 | [31.0–38.0] | 32.0 | [28.0–38.0] | 0.056 |
SaO2 % | 92.0 | [84.0–94.8] | 92.5 | [87.3–94.6] | 86.4 | [77.0–95.0] | 0.092 |
HCO3 mmol/L | 24.9 | [22.5–27.9] | 25.2 | [23.3–27.9] | 23.9 | [21.5–26.5] | 0.198 |
PaO2/FiO2 | 122.7 | [62.5–211.5] | 148.3 | [78.9–218.9] | 81.6 | [51.3–166.2] | 0.024 |
A-aDO2 | 206.6 | [117.7–567.3] | 172.8 | [62.6–551.2] | 234.7 | [164.7–588.7] | 0.061 |
Characteristics | Total Patients n = 219 | Without NOD n = 161 | NOD n = 58 | p-Value | |||
---|---|---|---|---|---|---|---|
Median | [Q1; Q3] | Median | [Q1; Q3] | Median | [Q1; Q3] | ||
White blood cells, ×/L | 10.23 | [7.18–13.91] | 9.14 | [6.78–12.32] | 13.85 | [10.62–16.81] | <0.001 |
Neutrophil count, ×/L | 8.56 | [5.3–11.99] | 7.19 | [4.72–10.85] | 10.94 | [9.14–14.13] | <0.001 |
Platelets count, ×/L | 298 | [221–399] | 290.5 | [213–387 | 318.5 | [237–431] | 0.061 |
C-reactive protein, mg/L | 65.7 | [21.8–93.8] | 59.8 | [17.05–92.05] | 75.35 | [35.5–95.7] | 0.020 |
D-dimer, mg/L | 858.5 | [396–3602] | 709 | [338–3049] | 980 | [582–4803] | 0.101 |
Ferritin, ng/mL | 698 | [344.3–1306] | 606.6 | [259.5–1203] | 1012 | [596.5–1582] | <0.001 |
Il-6, pg/mL | 15.9 | [9.49–30.55] | 26.5 | [13.9–56.49] | 15.8 | [6.98–25.9] | 0.07 |
LDH, U/L | 548.5 | [399–804.5] | 510 | [388.5–696] | 723 | [507–1140] | 0.003 |
AST, U/L | 48 | [32–80] | 45.5 | [30.5–71] | 59 | [34–99] | 0.017 |
ALT, U/L | 58 | [33–103] | 55 | [29–90] | 70 | [41–125] | 0.010 |
Pro-calcitonin, ng/mL | 0.22 | [0.18–0.32] | 0.21 | [0.18–0.31] | 0.25 | [0.2–0.32] | 0.102 |
FPG, mg/dL | 138 | [105–198.5] | 118 | [102–158] | 223 | [185–266] | <0.001 |
Triglycerides, mg/dL | 192 | [140–285] | 174 | [132–271.5] | 257 | [191–386] | <0.001 |
OR (95%CI) | p-Value | |
---|---|---|
Disease severity | 2.740 (1.533; 4.897) | 0.001 |
Need for ICU | 2.447 (1.104; 5.424) | 0.028 |
Values at hospital admission | ||
FPG | 1.020 (1.011; 1.029) | <0.001 |
Ferritin | 1.000 (1.000; 1.001) | 0.059 |
LDH | 1.001 (1.000; 1.002) | 0.024 |
PaO2/FiO2 | 0.995 (0.989; 1.000) | 0.047 |
Values during hospitalization (days 5–7) | ||
Leucocytes | 1.077 (1.029; 1.127) | 0.002 |
Neutrophils | 1.077 (1.026; 1.131) | 0.003 |
CRP | 1.009 (1.00; 1.018) | 0.039 |
Ferritin | 1.000 (1.000; 1.000) | 0.487 |
IL-6 | 0.980 (0.961; 0.999) | 0.044 |
LDH | 1.000 (1.000; 1.000) | 0.423 |
AST | 1.000 (1.000; 1.001) | 0.411 |
ALT | 1.001 (1.000; 1.001) | 0.231 |
TG | 1.005 (1.002; 1.007) | <0.001 |
OR (95%CI) | p-Value | |
---|---|---|
Disease severity | 0.325 (0.036; 2.921) | 0.316 |
Need for ICU | 1.906 (0.050; 72.539) | 0.728 |
Values at hospital admission | ||
FPG | 1.016 (0.992; 1.041) | 0.188 |
LDH | 1.009 (1.001; 1.017) | 0.036 |
PaO2/FiO2 | 0.989 (0.968; 1.011) | 0.335 |
Values during hospitalization (days 5–7) | ||
Leucocytes | 1.002 (0.961; 1.044) | 0.940 |
Neutrophils | 0.778 (0.585; 1.035) | 0.778 |
CRP | 0.984 (0.938; 1.032) | 0.501 |
IL-6 | 0.889 (0.764; 1.033) | 0.125 |
TG | 1.010 (0.995; 1.026) | 0.187 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Făgărășan, I.; Rusu, A.; Cristea, M.; Bala, C.-G.; Vulturar, D.-M.; Cristea, C.; Todea, D.-A. Predictors of New-Onset Diabetes in Hospitalized Patients with SARS-CoV-2 Infection. Int. J. Environ. Res. Public Health 2022, 19, 13230. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph192013230
Făgărășan I, Rusu A, Cristea M, Bala C-G, Vulturar D-M, Cristea C, Todea D-A. Predictors of New-Onset Diabetes in Hospitalized Patients with SARS-CoV-2 Infection. International Journal of Environmental Research and Public Health. 2022; 19(20):13230. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph192013230
Chicago/Turabian StyleFăgărășan, Iulia, Adriana Rusu, Maria Cristea, Cornelia-Gabriela Bala, Damiana-Maria Vulturar, Ciprian Cristea, and Doina-Adina Todea. 2022. "Predictors of New-Onset Diabetes in Hospitalized Patients with SARS-CoV-2 Infection" International Journal of Environmental Research and Public Health 19, no. 20: 13230. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph192013230