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2022, Number 5

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Med Crit 2022; 36 (5)

Comorbidities and clinical characteristics associated with hospital mortality, due to COVID-19, in the state of Hidalgo, Mexico

Casillas EJD, Cenobio GFJ, Guerrero EJB, Benítez HAE

Language: Spanish
References: 23
Page: 286-290
PDF size: 190.13 Kb.


ABSTRACT

Introduction: The COVID-19 disease has had a great impact on our country; Although various variables that contribute to the prognosis of mortality and/or serious illness in patients have been documented, it is necessary to generate information that accounts for state specificities to contribute to decision-making in the face of imminent hospital saturation. Objective: To identify the comorbidities and clinical characteristics associated with mortality from COVID-19, in hospitalized patients in the state of Hidalgo, Mexico. Material and method: A descriptive and retrospective study was carried out. As a source of information, the COVID-19 open database of the General Directorate of Epidemiology of the Mexican Ministry of Health was used to perform three types of regression: probit, logit and Gaussian. The Gaussian model was the one with the best fit. Results: 3,880 cases (1,696 deaths and 2,184 recovered) were analyzed and 4 comorbidities associated with mortality from COVID-19 were identified: obesity, hypertension, diabetes, and chronic kidney failure (CRF), as well as 2 clinical characteristics: sex and age. Conclusions: Hypertension, obesity, diabetes and CRF increase the probability of death. Among the comorbidities, CRF is the one with the greatest weight. Of the clinical characteristics analyzed, an association was found with sex and age, where age is the variable with the greatest weight in the model.


REFERENCES

  1. Tao C, Di W, Huilong C, Weiming Y, Danlei Y, Guang C, et al. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. BMJ. 2020;368:m1091. Available in: http://dx.doi.org/10.1136/bmj.m1091

  2. Secretaría de Salud. Informe técnico diario COVID-19 México. [Internet] México: Secretaría de Salud; 08/09/2020 [Consultado 17 Agosto 2020]. Disponible en https://www.gob.mx/cms/uploads/attachment/file/576812/Comunicado_Tecnico_Diario_COVID-19_2020.09.08.pdf

  3. Gobierno del Estado de Hidalgo. Resumen técnico sobre coronavirus COVID-19 8/09/2020. Disponible en https://coronavirus.hidalgo.gob.mx/

  4. Qiurong R, Kun Y, Wenxia W, Lingyu J, Jianxin S. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. ICM. 2020;46:846-848. Available in: https://link.springer.com/article/10.1007%2Fs00134-020-05991-x

  5. Secretaría de Salud. Conferencia de prensa, informe diario sobre coronavirus COVID-19 en México. [Internet]. México: Secretaría de Salud; 04/04/2020. [Consultado 18 Agosto 2020] Disponible en https://www.gob.mx/presidencia/articulos/version-estenografica-conferencia-de-prensa-informe-diario-sobre-coronavirus-covid-19-en-mexico-239735?idiom=es

  6. Giannouchos TV, Sussman RA, Mier Jé M, et al. Characteristics and risk factors for COVID-19 diagnosis and adverse outcomes in Mexico: an analysis of 89,756 laboratory–confirmed COVID-19 cases. Eur Respir J. 2020. Available in: https://doi.org/10.1183/13993003.02144-2020

  7. Simonnet A, Chetboun M, Poissy J, Raverdy V, Noulette J, Duhamel A, et al. High prevalence of obesity in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) requiring invasive mechanical ventilation. Obesidad (silver sping). 2020;28(7):1195-1199. doi: 10.1002/oby.22831.

  8. Secretaría de Salud. Informe técnico Covid-19/México 23 de julio 2020 [Video]: Secretaría de Salud; 28 julio 2020. [Consultado 5 Agosto 2020]. Disponible en https://www.youtube.com/watch?v=XlhzslFBrv8.

  9. Izcovich A, Ragusa MA, Tortosa F, Lavena Marzio MA, Agnoletti C, Bengolea A, et al. Prognostic factors for severity and mortality in patients infected with COVID-19: a systematic review. PLoS One. 2020;15(11):e0241955. doi: 10.1371/journal.pone.0241955.

  10. Hernandez-Galdamez DR, Gonzalez-Block MA, Romo-Duenas DK, Lima-Morales R, Hernandez-Vincente IA, Lumbreras-Guzman M, et al. Increased risk of hospitalization and death in patients with COVID-19 and pre-existing noncommunicable diseases and modifiable risk factors in Mexico. Arch Med Res. 2020;(7):683-689. Available in: https://pubmed.ncbi.nlm.nih.gov/32747155/

  11. Taha H. Investigación de operaciones. Novena ed. México: Pearson Educación; 2012.

  12. Peña D. Estadística. Modelos y métodos. Madrid: Alianza; 1987.

  13. Durbán M. Modelos lineales generalizados [Internet]. [Consultado 01 Octubre 2020]. Disponible en http://halweb.uc3m.es/esp/Personal/personas/durban/esp/web/GLM/curso_GLM.pdf

  14. Suárez V, Suárez Quezada M, Oros Ruiz S, Ronquillo De Jesús E. Epidemiología de COVID-19 en México: del 27 de febrero al 30 de abril de 2020. Rev Clin Esp. 2020;220(8):463-471. doi: 10.1016/j.rce.2020.05.007.

  15. Denova-Gutiérrez E, Lopez-Gatell H, Alomia-Zegarra JL, López-Ridaura R, Zaragoza-Jimenez CA, Dyer-Leal DD, et al. The Association of obesity, type 2 diabetes, and hypertension with severe coronavirus disease 2019 on admission among mexican patients. Obesity (Silver Spring). 2020;28(10):1826-1832. doi: 10.1002/oby.22946.

  16. Bello-Chavolla OY, Bahena-López JP, Antonio-Villa NE, Vargas-Vázquez A, González-Díaz A, Márquez-Salinas A, et al. Predicting mortality due to SARS-CoV-2: a mechanistic score relating obesity and diabetes to COVID-19 outcomes in Mexico. J Clin Endocrinol Metab. 2020;105(8):dgaa346. doi: 10.1210/clinem/dgaa346.

  17. Salinas-Aguirre JE, Sánchez-García C, Rodríguez-Sanchez R, Rodríguez-Muñoz L, Díaz-Castaño A, Bernal-Gómez R. Características clínicas y comorbilidades asociadas a mortalidad en pacientes con COVID-19 en Coahuila (México). Rev Clin Esp. 2021. Disponible en: https://doi.org/10.1016/j.rce.2020.12.006

  18. Lusczek ER, Ingraham NE, Karam BS, Proper J, Siegel L, Helgeson ES, et al. Characterizing COVID-19 clinical phenotypes and associated comorbidities and complication profiles. PLOS ONE. 2021;16(3):e0248956. https://doi.org/10.1371/journal.pone.0248956

  19. Instituto Nacional de Salud Pública, Instituto Nacional de Estadística y Geografía. Encuesta Nacional de Salud y Nutrición. México 2018.

  20. Pascual GNF, Monge LI, Granero CI, Figuerola TA, Ramasco RF, von Wernitz TA, et al. Potential biomarkers predictors of mortality in COVID-19 patients in the emergency department. Rev Esp Quimioter. 2020;33(4):267-273. doi: 10.37201/req/060.2020.

  21. Pan F, Yang L, Li Y, Liang B, Li L, Ye T, et al. Factors associated with death outcome in patients with severe coronavirus disease-19 (COVID-19): a case-control study. Int J Med Sci. 2020;17(9):1281-1292. doi: 10.7150/ijms.46614.

  22. Wang F, Hou H, Wang T, Luo Y, Tang G, Wu, et al Establishing a model for predicting the outcome of COVID-19 based on combination of laboratory tests. Travel Med Infect Dis. 2020;36:101782. doi: 10.1016/j.tmaid.2020.101782.

  23. Laguna-Goya R, Utrero-Rico A, Talayero P, Lasa-Lazaro M, Ramirez-Fernandez A, Naranjo L, et al. IL-6-based mortality risk model for hospitalized patients with COVID-19. J Allergy Clin Immunol. 2020;146(4):799-807.e9. doi: 10.1016/j.jaci.2020.07.009.




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