Iberoamerican Journal of Medicine
Iberoamerican Journal of Medicine
Original article

Predicting of poor outcomes in COVID-19 patients: Experience from an Argentinean hospital

Predicción de malos resultados en pacientes con COVID-19: experiencia de un hospital argentino

Maximiliano Gabriel Castro, María José Sadonio, Aida Agustina Castillo Landaburo, Gisel Cuevas, Florencia Cogliano, Federico Galluccio

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Introduction: The pressure over health systems caused by the COVID-19 pandemic brought about the need to develop tools that would allow for the identification of those patients that require immediate attention. Our objective was to identify clinical and biochemical predictors of poor outcomes (PO) in a cohort of patients hospitalized due to COVID-19 in an Argentinean public hospital.
Methods: Prospective cohort study conducted from March 3rd, 2020 to February 16th, 2021 in a tertiary care center in Santa Fe, Argentina. Clinical and biochemical characteristics of patients with COVID-19 pneumonia admitted consecutively were analyzed in order to identify predictors of a composite of poor outcomes (PO) -all-cause mortality and/or need for invasive mechanical ventilation.
Results: 421 patients were included. The mean age was 56.13 ± 15.05 years. 57.0% were males. 79.7% presented at least one comorbidity. 27.7% (n=116) presented PO. In the multivariate analysis, a higher 4C-score and a higher LDH, as well as a lower SatO2/FiO2, were associated with a higher risk of PO. No variable reached an AUC of 0.800 in the ROC analysis. 4C-score presented a numerically higher AUC (0.766 IC 95% 0.715-0.817).
Conclusions: Each point that the 4C-score increases, the risk of PO rises by 28%. Also, for every 100-units increase in LDH or 50-units decrease in SatO2/FiO2 at admission, there is a 20% increased risk of PO.


COVID-19; Pandemic; Mortality; Mechanical ventilation


Introducción: La presión sobre los sistemas de salud provocada por la pandemia COVID-19 generó la necesidad de desarrollar herramientas que permitan identificar a aquellos pacientes que requieren atención inmediata. Nuestro objetivo fue identificar predictores clínicos y bioquímicos de malos resultados (PO) en una cohorte de pacientes hospitalizados por COVID-19 en un hospital público argentino.
Métodos: Estudio de cohorte prospectivo realizado del 3 de marzo de 2020 al 16 de febrero de 2021 en un centro de tercer nivel de atención de Santa Fe, Argentina. Se analizaron las características clínicas y bioquímicas de los pacientes con neumonía COVID-19 ingresados consecutivamente con el fin de identificar predictores de una combinación de malos resultados (PO): mortalidad por todas las causas y / o necesidad de ventilación mecánica invasiva.
Resultados: Se incluyeron 421 pacientes. La edad media fue de 56,13 ± 15,05 años. El 57,0% eran varones. El 79,7% presentó al menos una comorbilidad. El 27,7% (n = 116) presentó PO. En el análisis multivariado, una puntuación 4C más alta y una LDH más alta, así como una SatO2 / FiO2 más baja, se asociaron con un mayor riesgo de PO. Ninguna variable alcanzó un AUC de 0,800 en el análisis ROC. La puntuación 4C presentó un AUC numéricamente superior (0,766 IC 95% 0,715-0,817).
Conclusiones: Cada punto que aumenta el puntaje 4C, el riesgo de PO aumenta en un 28%. Además, por cada 100 unidades de aumento de LDH o 50 unidades de disminución de SatO2 / FiO2 al ingreso, existe un 20% más de riesgo de PO.

Palabras clave

COVID-19; Pandemia; Mortalidad; Ventilación mecánica


1. WHO Director-General's opening remarks at the media briefing on COVID-19 - 11 March 2020. Available from: https://www.who.int/es/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020 (accessed May 2021).
2. Argentinean Ministry of Health. Epidemiological information. Available from: https://www.argentina.gob.ar/salud/coronavirus-COVID-19/sala-situacion (accessed July 2021).
3. Schönfeld D, Arias S, Bossio JC, Fernández H, Gozal D, Pérez-Chada D. Clinical presentation and outcomes of the first patients with COVID-19 in Argentina: Results of 207079 cases from a national database. PLoS One. 2021;16(2):e0246793. doi: 10.1371/journal.pone.0246793.
4. Rearte A, Baldani AEM, Barcena Barbeira P, Domínguez CS, Laurora MA, Pesce M, et al. Epidemiological characteristics of the first 116 974 cases of COVID-19 in Argentina, 2020. Rev Argent Salud Pública. 2020;12(Supl COVID-19):1-9.
5. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA. 2020;323(11):1061-9. doi: 10.1001/jama.2020.1585.
6. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al, Zhong NS; China Medical Treatment Expert Group for Covid-19. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020;382(18):1708-20. doi: 10.1056/NEJMoa2002032.
7. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al, Cao B. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395(10229):1054-62. doi: 10.1016/S0140-6736(20)30566-3.
8. Wan S, Xiang Y, Fang W, Zheng Y, Li B, Hu Y, et al. Clinical features and treatment of COVID-19 patients in northeast Chongqing. J Med Virol. 2020;92(7):797-806. doi: 10.1002/jmv.25783.
9. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497-506. doi: 10.1016/S0140-6736(20)30183-5.
10. Ruan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med. 2020;46(5):846-8. doi: 10.1007/s00134-020-05991-x.
11. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA Intern Med. 2020;180(7):934-43. doi: 10.1001/jamainternmed.2020.0994.
12. Martínez Chamorro E, Díez Tascón A, Ibáñez Sanz L, Ossaba Vélez S, Borruel Nacenta S. Radiologic diagnosis of patients with COVID-19. Radiologia (Engl Ed). 2021;63(1):56-73. doi: 10.1016/j.rx.2020.11.001.
13. Ojha V, Mani A, Pandey NN, Sharma S, Kumar S. CT in coronavirus disease 2019 (COVID-19): a systematic review of chest CT findings in 4410 adult patients. Eur Radiol. 2020;30(11):6129-38. doi: 10.1007/s00330-020-06975-7.
14. Petrilli CM, Jones SA, Yang J, Rajagopalan H, O'Donnell L, Chernyak Y, et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ. 2020;369:m1966. doi: 10.1136/bmj.m1966.
15. Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020;584(7821):430-6. doi: 10.1038/s41586-020-2521-4.
16. Tian W, Jiang W, Yao J, Nicholson CJ, Li RH, Sigurslid HH, et al. Predictors of mortality in hospitalized COVID-19 patients: A systematic review and meta-analysis. J Med Virol. 2020;92(10):1875-83. doi: 10.1002/jmv.26050.
17. Knight SR, Ho A, Pius R, Buchan I, Carson G, Drake TM, et al. Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score. BMJ. 2020;370:m3339. doi: 10.1136/bmj.m3339.
18. Ageno W, Cogliati C, Perego M, Girelli D, Crisafulli E, Pizzolo F, et al. Clinical risk scores for the early prediction of severe outcomes in patients hospitalized for COVID-19. Intern Emerg Med. 2021;16(4):989-96. doi: 10.1007/s11739-020-02617-4.
19. Xie J, Hungerford D, Chen H, Abrams ST, Li S, Wang G, et al. Development and external validation of a prognostic multivariable model on admission for hospitalized patients with COVID-19. medRxiv. 2020;2020.03.28.20045997. doi: 10.1101/2020.03.28.20045997.
20. Zhou W, Wang W, Wang H, Lu R, Tan W. First infection by all four non-severe acute respiratory syndrome human coronaviruses takes place during childhood. BMC Infect Dis. 2013;13:433. doi: 10.1186/1471-2334-13-433.
21. Glick JH Jr. Serum lactate dehydrogenase isoenzyme and total lactate dehydrogenase values in health and disease, and clinical evaluation of these tests by means of discriminant analysis. Am J Clin Pathol. 1969;52(3):320-8. doi: 10.1093/ajcp/52.3.320.
22. Orlacchio A, Gasparrini F, Roma S, Ravà MS, Salvatori E, Morosetti D, et al. Correlations between chest-CT and laboratory parameters in SARS-CoV-2 pneumonia: A single-center study from Italy. Medicine (Baltimore). 2021;100(14):e25310. doi: 10.1097/MD.0000000000025310.
23. Antonio GE, Ooi CG, Wong KT, Tsui EL, Wong JS, Sy AN, et al. Radiographic-clinical correlation in severe acute respiratory syndrome: study of 1373 patients in Hong Kong. Radiology. 2005;237(3):1081-90. doi: 10.1148/radiol.2373041919.
24. Zhou M, Dong C, Li C, Wang Y, Liao H, Shi H, et al. Longitudinal changes in COVID-19 clinical measures and correlation with the extent of CT lung abnormalities. Int J Med Sci. 2021;18(5):1277-84. doi: 10.7150/ijms.51279.
25. Garibaldi BT, Fiksel J, Muschelli J, Robinson ML, Rouhizadeh M, Perin J, et al. Patient Trajectories Among Persons Hospitalized for COVID-19 : A Cohort Study. Ann Intern Med. 2021;174(1):33-41. doi: 10.7326/M20-3905.
26. Salje H, Tran Kiem C, Lefrancq N, Courtejoie N, Bosetti P, Paireau J, et al. Estimating the burden of SARS-CoV-2 in France. Science. 2020;369(6500):208-11. doi: 10.1126/science.abc3517.
27. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA. 2020;323(20):2052-9. doi: 10.1001/jama.2020.6775.
28. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline Characteristics and Outcomes of 1591 Patients Infected With SARS-CoV-2 Admitted to ICUs of the Lombardy Region, Italy. JAMA. 2020;323(16):1574-81. doi: 10.1001/jama.2020.5394.
29. Grasselli G, Greco M, Zanella A, Albano G, Antonelli M, Bellani G, et al. Risk Factors Associated With Mortality Among Patients With COVID-19 in Intensive Care Units in Lombardy, Italy. JAMA Intern Med. 2020 Oct 1;180(10):1345-55. doi: 10.1001/jamainternmed.2020.3539.
30. Miller EJ, Linge HM. Age-Related Changes in Immunological and Physiological Responses Following Pulmonary Challenge. Int J Mol Sci. 2017;18(6):1294. doi: 10.3390/ijms18061294.
31. Liu Y, Mao B, Liang S, Yang JW, Lu HW, Chai YH, et al. Association between age and clinical characteristics and outcomes of COVID-19. Eur Respir J. 2020;55(5):2001112. doi: 10.1183/13993003.01112-2020.
32. Chen Y, Klein SL, Garibaldi BT, Li H, Wu C, Osevala NM, et al. Aging in COVID-19: Vulnerability, immunity and intervention. Ageing Res Rev. 2021;65:101205. doi: 10.1016/j.arr.2020.101205.
33. Lipsitch M, Grad YH, Sette A, Crotty S. Cross-reactive memory T cells and herd immunity to SARS-CoV-2. Nat Rev Immunol. 2020;20(11):709-13. doi: 10.1038/s41577-020-00460-4.
34. Beretta A, Cranage M, Zipeto D. Is Cross-Reactive Immunity Triggering COVID-19 Immunopathogenesis? Front Immunol. 2020;11:567710. doi: 10.3389/fimmu.2020.567710.
35. Cristiani L, Mancino E, Matera L, Nenna R, Pierangeli A, Scagnolari C, et al. Will children reveal their secret? The coronavirus dilemma. Eur Respir J. 2020;55(4):2000749. doi: 10.1183/13993003.00749-2020.
36. Ebmeier S, Cunnington AJ. What do differences in case fatality ratios between children and adults tell us about COVID-19? Eur Respir J. 2020;56(1):2001601. doi: 10.1183/13993003.01601-2020.
37. Nasiri MJ, Haddadi S, Tahvildari A, Farsi Y, Arbabi M, Hasanzadeh S, et al. COVID-19 Clinical Characteristics, and Sex-Specific Risk of Mortality: Systematic Review and Meta-Analysis. Front Med (Lausanne). 2020;7:459. doi: 10.3389/fmed.2020.00459.
38. Pradhan A, Olsson PE. Sex differences in severity and mortality from COVID-19: are males more vulnerable? Biol Sex Differ. 2020;11(1):53. doi: 10.1186/s13293-020-00330-7.
39. Docherty AB, Harrison EM, Green CA, Hardwick HE, Pius R, Norman L, et al. Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study. BMJ. 2020 May 22;369:m1985. doi: 10.1136/bmj.m1985.
40. Myers LC, Parodi SM, Escobar GJ, Liu VX. Characteristics of Hospitalized Adults With COVID-19 in an Integrated Health Care System in California. JAMA. 2020;323(21):2195-8. doi: 10.1001/jama.2020.7202.
41. Guan WJ, Liang WH, Zhao Y, Liang HR, Chen ZS, Li YM, et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J. 2020;55(5):2000547. doi: 10.1183/13993003.00547-2020.
42. Salazar MR. Is hypertension without any other comorbidities an independent predictor for COVID-19 severity and mortality? J Clin Hypertens (Greenwich). 2021;23(2):232-4. doi: 10.1111/jch.14144.
43. Data World Bank. Life expectancy at birth, total (years) – Argentina. Available from:
https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=AR (accessed May 2021).
44. WHO. World Health Organization. Great Britain and North Ireland. Available from: http://www.who.int/countries/gbr/es/ (accessed May 2021).
45. Weng Z, Chen Q, Li S, Li H, Zhang Q, Lu S, et al. ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019. J Transl Med. 2020;18(1):328. doi: 10.1186/s12967-020-02505-7.
46. Mudatsir M, Fajar JK, Wulandari L, Soegiarto G, Ilmawan M, Purnamasari Y, et al. Predictors of COVID-19 severity: a systematic review and meta-analysis. F1000Res. 2020;9:1107. doi: 10.12688/f1000research.26186.2.
47. Vakili S, Savardashtaki A, Jamalnia S, Tabrizi R, Nematollahi MH, Jafarinia M, et al. Laboratory Findings of COVID-19 Infection are Conflicting in Different Age Groups and Pregnant Women: A Literature Review. Arch Med Res. 2020;51(7):603-7. doi: 10.1016/j.arcmed.2020.06.007.

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