Eficiencia y desempeño de las escalas pronósticos en el paciente con infección por el coronavirus SARS-COV-2 (Covid-19) en la Unidad de Cuidado Intensivo
| datacite.rights | http://purl.org/coar/access_right/c_16ec | spa |
| dc.contributor.advisor | Ariza Algarín, Abul Enrique | |
| dc.contributor.advisor | González-Torres, Henry J. | |
| dc.contributor.author | Mármol Escobar, Darío Ricardo | |
| dc.contributor.author | Burbano Adrada, Anyela Dayana | |
| dc.date.accessioned | 2021-12-13T20:21:50Z | |
| dc.date.available | 2021-12-13T20:21:50Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | (1) Introducción: Las escalas de gravedad para la evaluación de pacientes en estado crítico han sido ampliamente utilizadas en las unidades de cuidados intensivos con el objetivo de predecir mortalidad, caracterizar la gravedad de la enfermedad y establecer el grado de disfunción orgánica. ; (2) Métodos: Para la recolección de datos se utilizará una técnica cuantitativa tomando como fuente principal la información del Sistema (software) de la clínica donde se realizó el estudio, las historias clínicas de los pacientes, se realizará auditoria a las historias clínicas. ; (3) Resultados: Se analizaron 99 pacientes positivos a Covid-19, ingresados en la Unidad de Cuidados Intensivos entre los meses de enero de 2021 y Junio de 2021. Se comparó las proporciones y medias de las variables de acuerdo a la sobrevivencia, ninguno tuvo un p-valor significativo, por lo tanto se puede asumir con un 95% que no hay diferencia estadísticamente significativa entre los vivos y los fallecidos por cada una de sus variables. ; y (4) Conclusiones: La mortalidad durante el año 2020 fue elevada debido a la pandemia que genero un efecto tanto patológico en el paciente (neumonía por Covid-19) y un efecto de disminución del recurso por el número de pacientes remitidos a la Unidad. Las escalas pronosticas fue de utilidad para predecir la probabilidad de muerte. | spa |
| dc.description.abstract | (1) Introduction: Severity scales for evaluating critically ill patients have been widely used in intensive care units with the aim of predicting mortality, characterizing the severity of the disease and establishing the degree of organ dysfunction. ; (2) Methods: For data collection, a quantitative technique will be used, taking as the main source the information from the System (software) of the clinic where the study was carried out, the clinical records of the patients, and the clinical records will be audited. ; (3) Results: 99 Covid-19 positive patients admitted to the Intensive Care Unit between January 2021 and June 2021 were analyzed. The proportions and means of the variables were compared according to survival, none had a significant p-value, therefore it can be assumed with 95% that there is no statistically significant difference between the living and the deceased for each of its variables. ; And (4) Conclusions: Mortality during 2020 was high due to the pandemic that generated both a pathological effect in the patient (Covid-19 pneumonia) and an effect of reducing the resource due to the number of patients referred to the Unit. . The prognostic scales were useful in predicting the probability of death. | eng |
| dc.format.mimetype | spa | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12442/9234 | |
| dc.language.iso | spa | spa |
| dc.publisher | Ediciones Universidad Simón Bolívar | spa |
| dc.publisher | Facultad de Ciencias de la Salud | spa |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
| dc.rights.accessrights | info:eu-repo/semantics/restrictedAccess | spa |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
| dc.subject | Corona virus | spa |
| dc.subject | SOFA | eng |
| dc.subject | NEWS | eng |
| dc.subject | APACHE II | eng |
| dc.title | Eficiencia y desempeño de las escalas pronósticos en el paciente con infección por el coronavirus SARS-COV-2 (Covid-19) en la Unidad de Cuidado Intensivo | spa |
| dc.type.driver | info:eu-repo/semantics/other | spa |
| dc.type.spa | Otros | spa |
| dcterms.references | Yesudhas, D., & Srivastava, A. (2020). COVID‑19 outbreak: history, mechanism, transmission, structural studies and therapeutics. Springer, 1–15. | eng |
| dcterms.references | Bchetnia, M., Girard, C., Duchaine, C., & Laprise, C. (2020). The outbreak of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): A review of the current global status. Journal of Infection and Public Health, 13(11), 1601–1610. https://doi.org/10.1016/j.jiph.2020.07.011 | eng |
| dcterms.references | Chu, D. K., Akl, E. A., Duda, S., Solo, K. yaacoub, S., Schünemann, H. J., El-harakeh, A., Bognanni, A., Lotfi, T., Loeb, M., Hajizadeh, A., Bak, A., Izcovich, A., Cuello-Garcia, C. A., Chen, C., Harris, D. J., Borowiack, E., Chamseddine, F., Schünemann, F., … Reinap, M. (2020). Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis. The Lancet, 395(10242), 1973–1987. https://doi.org/10.1016/S0140-6736(20)31142-9. | eng |
| dcterms.references | Wiersinga, W. J., Rhodes, A., Cheng, A. C., Peacock, S. J., & Prescott, H. C. (2020). Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19): A Review. JAMA - Journal of the American Medical Association, 324(8), 782–793. https://doi.org/10.1001/jama.2020.12839. | eng |
| dcterms.references | Tong, J. Y., Wong, A., Zhu, D., Fastenberg, J. H., & Tham, T. (2020). The Prevalence of Olfactory and Gustatory Dysfunction in COVID-19 Patients: A Systematic Review and Meta-analysis. Otolaryngology - Head and Neck Surgery (United States), 163(1), 3–11. https://doi.org/10.1177/0194599820926473. | eng |
| dcterms.references | Böger, B., Fachi, M. M., Vilhena, R. O., Cobre, A. F., Tonin, F. S., & Pontarolo, R. (2021). Systematic review with meta-analysis of the accuracy of diagnostic tests for COVID-19. American Journal of Infection Control, 49(1), 21–29. https://doi.org/10.1016/j.ajic.2020.07.011. | eng |
| dcterms.references | Arevalo-Rodriguez, I., Buitrago-Garcia, D., Simancas-Racines, D., Zambrano-Achig, P., Campo, R. Del, Ciapponi, A., Sued, O., Martinez-García, L., Rutjes, A. W., Low, N., Bossuyt, P. M., Perez-Molina, J. A., & Zamora, J. (2020). False-negative results of initial RT-PCR assays for COVID-19: A systematic review. PLoS ONE, 15(12 December), 1–19. https://doi.org/10.1371/journal.pone.0242958. | eng |
| dcterms.references | Jones, M. (2012). NEWSDIG: The national early warning score development and implementation group. Clinical Medicine, Journal of the Royal College of Physicians of London, 12(6), 501–503. https://doi.org/10.7861/clinmedicine.12-6-501. | eng |
| dcterms.references | Naved, S. A., Siddiqui, S., & Khan, F. H. (2011). APACHE-II score correlation with mortality and length of stay in an intensive care unit. Journal of the College of Physicians and Surgeons Pakistan, 21(1), 4–8. | eng |
| dcterms.references | Vincent, J. L., Moreno, R., Takala, J., Willatts, S., De Mendonça, A., Bruining, H., Reinhart, C. K., Suter, P. M., & Thijs, L. G. (1996). The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. Intensive Care Medicine, 22(7), 707–710. https://doi.org/10.1007/BF01709751 | eng |
| dcterms.references | West E, Barron DN, Harrison D, Rafferty AM, Rowan K, Sanderson C. Nurse staffing, medical staffing and mortality in Intensive Care: An observational study. Int J Nurs Stud. 2014 May;51(5):781–94. | eng |
| dcterms.references | Blanch L, Abillama FF, Amin P, Christian M, Joynt GM, Myburgh J, et al. Triage decisions for ICU admission: Report from the Task Force of the World Federation of Societies of Intensive and Critical Care Medicine. J Crit Care. 2016 Dec;36(2016):301–5. | eng |
| dcterms.references | Shepherd SJ. Criteria for intensive care unit admission and the assessment of illness severity. Surg. 2018 Apr;36(4):171–9. | eng |
| dcterms.references | Mathews KS, Long EF. A Conceptual Framework for Improving Critical Care Patient Flow and Bed Use. Ann Am Thorac Soc. 2015 Jun;12(6):886–94. | eng |
| dcterms.references | Town JA, Churpek MM yuen TC, Huber MT, Kress JP, Edelson DP. Relationship Between ICU Bed Availability, ICU Readmission, and Cardiac Arrest in the General Wards. Crit Care Med. 2014 Sep;42(9):2037–41. | eng |
| dcterms.references | Orsini. Triage of Patients Consulted for ICU Admission During Times of ICU-Bed Shortage. J Clin Med Res. 2014;6(6):463–8. | eng |
| dcterms.references | Raúl C, Martínez C. La realidad de la Unidad de Cuidados Intensivos. Artículo opinión Med Crit. 2017;31(3):171–3. | eng |
| dcterms.references | Amin P, Fox-Robichaud A, Divatia JV, Pelosi P, Altintas D, Eryüksel E, et al. The Intensive care unit specialist: Report from the Task Force of World Federation of Societies of Intensive and Critical Care Medicine. J Crit Care. 2016 Oct;35(2016):223–8. | eng |
| dcterms.references | Stretch B, Shepherd SJ. Criteria for intensive care unit admission and severity of illness. Surg. 2021 Jan;39(1):22–8. | eng |
| dcterms.references | Christian MD, Sprung CL, King MA, Dichter JR, Kissoon N, Devereaux A V., et al. Triage. Chest. 2014 Oct;146(4):e61S-e74S. | spa |
| dcterms.references | Burdiles P, Pommier AO. El triage en pandemia: fundamentos éticos para la asignación de recursos de soporte vital avanzado en escenarios de escasez. Rev Médica Clínica Las Condes. 2021 Jan;32(1):61–74. | spa |
| dcterms.references | Bulgarelli L, Deliberato RO, Johnson AEW. Prediction on critically ill patients: The role of “big data.” J Crit Care. 2020 Dec;60(2020):64–8. | eng |
| dcterms.references | Sánchez-Casado M, Hostigüela-Martín VA, Raigal-Caño A, Labajo L, Gómez-Tello V, Alonso-Gómez G, et al. Escalas pronósticas en la disfunción multiorgánica: estudio de cohortes. Med Intensiva. 2016 Apr;40(3):145–53. | spa |
| dcterms.references | Balkan B, Essay P, Subbian V. Evaluating ICU Clinical Severity Scoring Systems and Machine Learning Applications: APACHE IV/IVa Case Study. In: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE; 2018. p. 4073–6. | eng |
| dcterms.references | Wu S-C, Chou S-E, Liu H-T, Hsieh T-M, Su W-T, Chien P-C, et al. Performance of Prognostic Scoring Systems in Trauma Patients in the Intensive Care Unit of a Trauma Center. Int J Environ Res Public Health. 2020 Oct;17(19):7226. | eng |
| dcterms.references | Godinjak AG. Predictive value of SAPS II and APACHE II scoring systems for patient outcome in medical intensive care unit. Acta Med Acad. 2016 Dec;45(2):89–95. | eng |
| dcterms.references | Ho KM, Williams TA, Harahsheh Y, Higgins TL. Using patient admission characteristics alone to predict mortality of critically ill patients: A comparison of 3 prognostic scores. J Crit Care. 2016 Feb;31(1):21–5. | eng |
| dcterms.references | Hansted AK, Møller MH, Møller AM, Vester‑Andersen M. APACHE II score validation in emergency abdominal surgery. A post hoc analysis of the InCare trial. Acta Anaesthesiol Scand. 2020 Feb;64(2):180–7. | eng |
| dcterms.references | Hansted AK, Møller MH, Møller AM, Vester‑Andersen M. APACHE II score validation in emergency abdominal surgery. A post hoc analysis of the InCare trial. Acta Anaesthesiol Scand. 2020 Feb;64(2):180–7. | eng |
| dcterms.references | Sharma Z, Bale C, Kakrani A, Dabadghao V. Sequential organ failure assessment score as prognostic marker in critically ill patients in a tertiary care intensive care unit. Int J Med Public Heal. 2013;3(3):155. | eng |
| dcterms.references | Schoe A, Bakhshi-Raiez F, de Keizer N, van Dissel JT, de Jonge E. Mortality prediction by SOFA score in ICU-patients after cardiac surgery; comparison with traditional prognostic–models. BMC Anesthesiol. 2020 Dec;20(1):65. | eng |
| dcterms.references | Elguea-Echavarría P, Prado-Bush O B-AJ. Implementación de una escala de gravedad para la activación del equipo de respuesta rápida: NEWS 2. Med Crit. 2019;33(2):98–103. | spa |
| dcterms.references | Alejandro P, Echavarría E, Alfredo O, Bush P, Ambriz JB. Implementación de una escala de gravedad para la activación del equipo de respuesta rápida: NEWS 2. 2019;33(2):98–103. | spa |
| dcterms.references | Tian H, Liu Y, Li Y, Wu C-H, Chen B, Kraemer MUG, et al. An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China. Science (80- ). 2020 May;368(6491):638–42. | eng |
| dcterms.references | Sun K, Chen J, Viboud C. Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study. Lancet Digit Heal. 2020 Apr;2(4):e201–8. | eng |
| dcterms.references | Ye Z-W yuan S yuen K-S, Fung S-Y, Chan C-P, Jin D-Y. Zoonotic origins of human coronaviruses. Int J Biol Sci. 2020;16(10):1686–97. | eng |
| dcterms.references | Cascella M, Rajnik M, Cuomo A, Dulebohn S, Di Napoli R. Features, evaluation, and treatment of coronavirus (COVID-19). Statpearls …. 2021; | eng |
| dcterms.references | Hassan SA, Sheikh FN, Jamal S, Ezeh JK, Akhtar A. Coronavirus (COVID-19): A Review of Clinical Features, Diagnosis, and Treatment. Cureus. 2020 Mar;12(3). | eng |
| dcterms.references | Guo Z-D, Wang Z-Y, Zhang S-F, Li X, Li L, Li C, et al. Aerosol and Surface Distribution of Severe Acute Respiratory Syndrome Coronavirus 2 in Hospital Wards, Wuhan, China, 2020. Emerg Infect Dis. 2020 Jul;26(7):1583–91. | eng |
| dcterms.references | 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 Feb;395(10223):497–506. | eng |
| dcterms.references | 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 - J Am Med Assoc. 2020 Mar;323(11):1061. | eng |
| dcterms.references | Lima MA, Silva MTT, Oliveira R V., Soares CN, Takano CL, Azevedo AE, et al. Smell dysfunction in COVID-19 patients: More than a yes-no question. J Neurol Sci. 2020;418(June 2020):117107. | eng |
| dcterms.references | Rozado J, Ayesta A, Morís C, Avanzas P, Sars-cov- DET. Fisiopatología de la enfermedad cardiovascular en pacientes con COVID-19 . Isquemia , trombosis y disfunción cardiaca. Rev española Cardiol Supl. 2021;20:2–8. | spa |
| dcterms.references | Fix O, Grover S. COVID-19: Issues related to liver disease in adults - UpToDate. UpToDate. 2021;1–26. | eng |
| dcterms.references | Yu Q, Diab C, Ozen M. Abstract No . 519 The use of arti fi cial ascites in thermal ablation of hepatic lesions : systematic review and meta- analysis Abstract No . 520 Clinical characteristics , imaging manifestations , and outcomes of patients undergoing percutaneous cholecys. J Vasc Interv Radiol. 2021;32(5):S138–9. | eng |
| dcterms.references | Wang K, Kang S, Tian R, Zhang X, Zhang X, Wang Y. Imaging manifestations and diagnostic value of chest CT of coronavirus disease 2019 ( COVID-19 ) in the Xiaogan area. Clin Radiol. 2021;75(5):341–7. | eng |
| dcterms.references | Lampton LM. Covid-19. In: Terapia actual de Conn’s 2021. 2021. p. 554–8. | eng |
| dcterms.references | Shoar S. ICU admission and outcome of patients with COVID-19 : Does ICU stay improve survival ? Hear Lung. 2021;50(3):470. | eng |
| dcterms.references | Kim AAY, Gandhi RT. COVID-19 : Management in hospitalized adults. 2021;1–54. | eng |
| dcterms.references | Gargione R. Brazilian ICUs short of drugs and beds amid COVID-19 surge Doctors are reporting shortages of critical drugs and the need to ration care , pointing to public. Lancet. 2021;397(10283):1431–2. | eng |
| dcterms.references | Anesi AGL. COVID-19 : Manejo del adulto intubado. 2021;1–58. | spa |
| dcterms.references | Mitchell A, Elkind S V, Cucchiara BL, Koralnik IJ. COVID-19 : Neurologic complications and management of neurologic conditions. 2021;12–4. | eng |
| dcterms.references | Alida A, Caforio LP. COVID-19 : Cardiac manifestations in adults. 2021;1–27. | eng |
| dcterms.references | Cohen BA, Wessling EG, Serina PT, Cruz DS, Kim HS, McCarthy DM, et al. Emergency department operations in a large health system during COVID-19. Am J Emerg Med. 2021 Mar;41:241–3. | eng |
| dcterms.references | Asaduzzaman M, Hossain N, Abul M, Shahid A, Alam A. Immune response in COVID-19 : A review. J Infect Public Health. 2021;13(11):1619–29. | eng |
| dcterms.references | Polidori MC, Sies H, Ferrucci L, Benzing T. COVID-19 mortality as a fingerprint of biological age. Ageing Res Rev. 2021 May;67(May 2020):101308. | eng |
| dcterms.references | Saragih ID, Advani S, Ph D, Saragih IS, Suarilah I, Susanto I, et al. Frailty as a mortality predictor in older adults with COVID-19 : A systematic review and meta-analysis of cohort studies. Geriatr Nurs (Minneap). 2021;42(5):983–92. | eng |
| dcterms.references | Page GE. African-American COVID-19 Mortality. 2021;75(21):2020–2. | eng |
| oaire.version | info:eu-repo/semantics/acceptedVersion | spa |
| sb.programa | Especialización en Medicina Crítica y Cuidados Intensivos | spa |
| sb.sede | Sede Barranquilla | spa |