Mostrar el registro sencillo del documento

dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacional
dc.contributor.advisorRuiz Rodriguez, José Guillermo
dc.contributor.advisorEspinosa Almanza, Carmelo José
dc.contributor.authorHernández Almonacid, Pablo Guillermo
dc.date.accessioned2021-01-29T13:00:48Z
dc.date.available2021-01-29T13:00:48Z
dc.date.issued2020
dc.identifier.citationHernández Almonacid, P. G. (2020). Evaluación de escalas pronósticas en sepsis: valoración de SOFA, qSOFA, SIRS y APACHE IV como predictores de mortalidad en pacientes críticamente enfermos de un hospital general de Bogotá, año 2019 [Tesis de especialidad, Universidad Nacional de Colombia]. Repositorio Institucional.
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/78984
dc.description.abstractDesde la actualización de la definición de sepsis, diversos estudios han tratado de validar el rendimiento del SOFA y qSOFA para predecir mortalidad. Los resultados han sido variables en cada población. Es importante seleccionar un sistema de predicción que demuestre buena discriminación y calibración en la población de interés. El propósito del estudio es establecer el sistema pronóstico con mayor rendimiento en predicción de mortalidad entre pacientes que ingresan a UCI con sospecha de infección, comparando (SIRS, qSOFA, SOFA, APACHE II, APACHE IV). Métodos: estudio observacional, analítico, retrospectivo. Se realiza un análisis de subgrupo de pacientes con diagnóstico oncológico activo. Resultados: se seleccionaron 290 pacientes. Se registraron 80 decesos, para una mortalidad global del 27.5%. El AUROC para cada sistema fue SIRS 0.53 (IC 95% 0.4-0.6), qSOFA 0.68 (IC 95% 0.62-0.75), SOFA de 0.8 (IC 95% 0.75-0.86), APACHE II 0.81 (IC 95% 0.76-0.86) y APACHE IV de 0.85 (IC 95% 0.80-0.90). La REM para SOFA fue del 0.95, APACHE II de 1.2 y APCHE IV de 1.47. La CITL fue de -0.09 para el SOFA, 0.13 para APACHE II y 0.71 para APACHE IV. Las curvas de calibración mostraron una buena concordancia para el SOFA, las curvas de los sistemas APACHE muestran tendencia a subestimar eventos. En el grupo de pacientes oncológicos los AUROC fueron comparables y no hay una adecuada calibración. Conclusiones: el SOFA score muestra una buena discriminación y calibración para predicción de mortalidad. Los sistemas APACHE tienen buena discriminación, pero no están calibrados a la población. SIRS y qSOFA tienen una mala AUROC como predictores de mortalidad.
dc.description.abstractIntroduction: Since the last update on sepsis definition, various studies have aimed to validate the performance of SOFA and qSOFA to predict mortality, with variable results in each population. This higlights the importance of selecting a prediction system with efficient discrimination capacity and calibration that suits the target population. Objective: Evaluate and compare the ability of SIRS, qSOFA, SOFA, APACHE II and APACHE IV to predict mortality in patients with suspected infection admitted to ICU Methods: Retrospective observational analytic study. An additional analysis of oncological patients was also made. Discrimination was assessed using the area under the receiver operating characteristic curve (AUROC). Results: Among 290 selected patients, 80 died (global mortality 27,5%). AUROC for each prognosis system was established as follows: SIRS 0.53 (IC 95% 0.4-0.6), qSOFA 0.68 (IC 95% 0.62-0.75), SOFA de 0.8 (IC 95% 0.75-0.86), APACHE II 0.81 (IC 95% 0.76-0.86), APACHE IV de 0.85 (IC 95% 0.80-0.90). Standardized mortality ratio (SMR) for SOFA was 0.95, APACHE II 1.2 and APACHE IV 1.47. Calibration in the large (CITL) was -0.09 for SOFA, 0.13 for APACHE II and 0.71 for APACHE IV. Calibration curves showed suitable concordance of predicted and real mortality for SOFA, while APACHE tended to underestimate events. In oncological patients each AUROC was comparable, without appropriate calibration. Conclusion: SOFA score disclosed adequate discrimination capacity and calibration to predict mortality. Although APACHE systems discriminate well enough, they lack calibration for our population. SIRS and qSOFA do not discriminate mortality.
dc.format.extent61
dc.format.mimetypeapplication/pdf
dc.language.isospa
dc.rightsDerechos reservados - Universidad Nacional de Colombia
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleEvaluación de escalas pronósticas en sepsis: valoración de SOFA, qSOFA, SIRS y APACHE IV como predictores de mortalidad en pacientes críticamente enfermos de un hospital general de Bogotá, año 2019
dc.title.alternativeEvaluation of prognostic severity scores in sepsis: assessment of SOFA, qSOFA, SIRS and APACHE IV as predictors of mortality in critically ill patients of a general hospital in Bogotá,2019
dc.typeOtro
dc.rights.spaAcceso abierto
dc.type.driverinfo:eu-repo/semantics/other
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.publisher.programBogotá - Medicina - Especialidad en Medicina Interna
dc.description.degreelevelEspecialidades Médicas
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotá
dc.relation.referencesSinger M, Deutschman CS, Seymour C, Shankar-Hari M, Annane D, Bauer M, et al. The third international consensus definitions for sepsis and septic shock (sepsis-3). JAMA - J Am Med Assoc. 2016;315(8):801–10
dc.relation.referencesCecconi M, Evans L, Levy M, Rhodes A. Sepsis and septic shock. Lancet [Internet]. 2018;392(10141):75–87. Available from: http://dx.doi.org/10.1016/S0140-6736(18)30696-2
dc.relation.referencesEsposito S, De Simone G, Boccia G, De Caro F, Pagliano P. Sepsis and septic shock: New definitions, new diagnostic and therapeutic approaches. J Glob Antimicrob Resist [Internet]. 2017;10:204–12. Available from: http://dx.doi.org/10.1016/j.jgar.2017.06.013
dc.relation.referencesDriessen RGH, van de Poll MCG, Mol MF, van Mook WNKA, Schnabel RM. The influence of a change in septic shock definitions on intensive care epidemiology and outcome: comparison of sepsis-2 and sepsis-3 definitions. Infect Dis (Auckl) [Internet]. 2018;50(3):207–13. Available from: https://doi.org/10.1080/23744235.2017.1383630
dc.relation.referencesKauss I, Grion CM, Cardoso L, Anami E, Nunes L, Ferreira G, et al. The epidemiology of sepsis in a Brazilian teaching hospital. Brazilian J Infect Dis [Internet]. 2010;14(3):264–70. Available from: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-86702010000300011&lng=en&nrm=iso&tlng=en
dc.relation.referencesOrtíz G, Dueñas C, Rodríguez F, Barrera L, de La Rosa G, Dennis R, et al. Epidemiology of sepsis in Colombian intensive care units. Biomedica [Internet]. 2014;34(1):40–7. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24967858
dc.relation.referencesGotts JE, Matthay MA. Sepsis: pathophysiology and clinical management. BMJ. 2016 May;353:i1585
dc.relation.referencesMartin GS, Mannino DM, Moss M. The effect of age on the development and outcome of adult sepsis. Crit Care Med. 2006 Jan;34(1):15–21
dc.relation.referencesAngus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001 Jul;29(7):1303–10.
dc.relation.referencesVincent J-L, Rello J, Marshall J, Silva E, Anzueto A, Martin CD, et al. International study of the prevalence and outcomes of infection in intensive care units. JAMA. 2009 Dec;302(21):2323–9
dc.relation.referencesBouch DC, Thompson JP. Severity scoring systems in the critically ill. Contin Educ Anaesth Crit Care Pain [Internet]. 2008 Oct 1;8(5):181–5. Available from: http://dx.doi.org/10.1093/bjaceaccp/mkn033
dc.relation.referencesKeegan MT, Gajic O, Afessa B. Severity of illness scoring systems in the intensive care unit. Crit Care Med. 2011 Jan;39(1):163–9
dc.relation.referencesBreslow MJ, Badawi O. Severity scoring in the critically ill: part 2: maximizing value from outcome prediction scoring systems. Chest. 2012 Feb;141(2):518–27
dc.relation.referencesBreslow MJ, Badawi O. Severity scoring in the critically ill: part 1--interpretation and accuracy of outcome prediction scoring systems. Chest. 2012 Jan;141(1):245–52
dc.relation.referencesVan Calster B, McLernon DJ, van Smeden M, Wynants L, Steyerberg EW. Calibration: the Achilles heel of predictive analytics. BMC Med. 2019 Dec;17(1):230
dc.relation.referencesPace NL, Eberhart LHJ, Kranke PR. Quantifying prognosis with risk predictions. Eur J Anaesthesiol. 2012 Jan;29(1):7–16.
dc.relation.referencesAssel M, Sjoberg DD, Vickers AJ. The Brier score does not evaluate the clinical utility of diagnostic tests or prediction models. Diagnostic Progn Res. 2017;1:19
dc.relation.referencesZimmerman JE, Kramer AA. Outcome prediction in critical care: the Acute Physiology and Chronic Health Evaluation models. Curr Opin Crit Care. 2008 Oct;14(5):491–7
dc.relation.referencesRapsang AG, Shyam DC. Scoring systems in the intensive care unit: A compendium. Indian J Crit Care Med. 2014 Apr;18(4):220–8
dc.relation.referencesZimmerman JE, Kramer AA, McNair DS, Malila FM, Shaffer VL. Intensive care unit length of stay: Benchmarking based on Acute Physiology and Chronic Health Evaluation (APACHE) IV. Crit Care Med. 2006 Oct;34(10):2517–29
dc.relation.referencesVincent JL, Moreno R, Takala J, Willatts S, De Mendonca A, Bruining H, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Vol. 22, Intensive care medicine. United States; 1996. p. 707–10.
dc.relation.referencesFerreira FL, Bota DP, Bross A, Mélot C, Vincent J-L. Serial Evaluation of the SOFA Score to Predict Outcome in Critically Ill Patients. JAMA [Internet]. 2001 Oct 10;286(14):1754–8. Available from: https://doi.org/10.1001/jama.286.14.1754
dc.relation.referencesde Grooth H-J, Geenen IL, Girbes AR, Vincent J-L, Parienti J-J, Oudemans-van Straaten HM. SOFA and mortality endpoints in randomized controlled trials: a systematic review and meta-regression analysis. Crit Care. 2017 Feb;21(1):3
dc.relation.referencesSeymour CW, Liu VX, Iwashyna TJ, Brunkhorst FM, Rea TD, Scherag A, et al. Assessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA [Internet]. 2016 Feb 23;315(8):762–74. Available from: https://www.ncbi.nlm.nih.gov/pubmed/26903335
dc.relation.referencesMaitra S, Som A, Bhattacharjee S. Accuracy of quick Sequential Organ Failure Assessment (qSOFA) score and systemic inflammatory response syndrome (SIRS) criteria for predicting mortality in hospitalized patients with suspected infection: a meta-analysis of observational studies. Clin Microbiol Infect. 2018 Nov;24(11):1123–9
dc.relation.referencesBone RC, Balk RA, Cerra FB, Dellinger RP, Fein AM, Knaus WA, et al. Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. Chest. 1992 Jun;101(6):1644–55
dc.relation.referencesSimpson SQ. SIRS in the Time of Sepsis-3. Chest. 2018 Jan;153(1):34–8
dc.relation.referencesRaith EP, Udy AA, Bailey M, McGloughlin S, MacIsaac C, Bellomo R, et al. Prognostic Accuracy of the SOFA Score, SIRS Criteria, and qSOFA Score for In-Hospital Mortality Among Adults With Suspected Infection Admitted to the Intensive Care Unit. JAMA. 2017 Jan;317(3):290–300
dc.relation.referencesSprung CL, Schein RMH, Balk RA. The new sepsis consensus definitions: the good, the bad and the ugly. Vol. 42, Intensive care medicine. United States; 2016. p. 2024–6
dc.relation.referencesRhee C, Klompas M. New Sepsis and Septic Shock Definitions: Clinical Implications and Controversies. Infect Dis Clin North Am. 2017 Sep;31(3):397–413
dc.relation.referencesRosa RG, Moraes RB, Lisboa TC, Schunemann DP, Teixeira C. Does SOFA predict outcomes better than SIRS in Brazilian ICU patients with suspected infection? A retrospective cohort study . Vol. 21, Brazilian Journal of Infectious Diseases . scielo ; 2017. p. 665–9
dc.relation.referencesEstenssoro E, Kanoore Edul VS, Loudet CI, Osatnik J, Rios FG, Vazquez DN, et al. Predictive Validity of Sepsis-3 Definitions and Sepsis Outcomes in Critically Ill Patients: A Cohort Study in 49 ICUs in Argentina. Crit Care Med. 2018 Aug;46(8):1276–83.
dc.relation.referencesOsborn TM, Phillips G, Lemeshow S, Townsend S, Schorr CA, Levy MM, et al. Sepsis severity score: an internationally derived scoring system from the surviving sepsis campaign database*. Crit Care Med. 2014 Sep;42(9):1969–76
dc.relation.referencesGeorgescu A-M, Szederjesi J, Copotoiu S-M, Azamfirei L. Predicting scores correlations in patients with septic shock - a cohort study. Rom J Anaesth intensive care [Internet]. 2014 Oct;21(2):95–8. Available from: https://www.ncbi.nlm.nih.gov/pubmed/28913439
dc.relation.referencesDabhi AS, Khedekar SS, Mehalingam V. A Prospective Study of Comparison of APACHE-IV & SAPS-II Scoring Systems and Calculation of Standardised Mortality Rate in Severe Sepsis and Septic Shock Patients. J Clin Diagn Res. 2014 Oct;8(10):MC09-13.
dc.relation.referencesApril MD, Aguirre J, Tannenbaum LI, Moore T, Pingree A, Thaxton RE, et al. Sepsis Clinical Criteria in Emergency Department Patients Admitted to an Intensive Care Unit: An External Validation Study of Quick Sequential Organ Failure Assessment. J Emerg Med. 2017 May;52(5):622–31.
dc.relation.referencesCheng B, Li Z, Wang J, Xie G, Liu X, Xu Z, et al. Comparison of the Performance Between Sepsis-1 and Sepsis-3 in ICUs in China: A Retrospective Multicenter Study. Shock. 2017 Sep;48(3):301–6.
dc.relation.referencesSadaka F, EthmaneAbouElMaali C, Cytron MA, Fowler K, Javaux VM, O’Brien J. Predicting Mortality of Patients With Sepsis: A Comparison of APACHE II and APACHE III Scoring Systems. J Clin Med Res. 2017 Nov;9(11):907–10
dc.relation.referencesSiddiqui S, Chua M, Kumaresh V, Choo R. A comparison of pre ICU admission SIRS, EWS and q SOFA scores for predicting mortality and length of stay in ICU. J Crit Care. 2017 Oct;41:191–3
dc.relation.referencesFang X, Wang Z, Yang J, Cai H, Yao Z, Li K, et al. Clinical Evaluation of Sepsis-1 and Sepsis-3 in the ICU. Chest. 2018 May;153(5):1169–76
dc.relation.referencesKhwannimit B, Bhurayanontachai R, Vattanavanit V. Validation of the Sepsis Severity Score Compared with Updated Severity Scores in Predicting Hospital Mortality in Sepsis Patients. Shock. 2017 Jun;47(6):720–5
dc.relation.referencesKhwannimit B, Bhurayanontachai R, Vattanavanit V. Comparison of the performance of SOFA, qSOFA and SIRS for predicting mortality and organ failure among sepsis patients admitted to the intensive care unit in a middle-income country. J Crit Care. 2018 Apr;44:156–60
dc.relation.referencesKelsey, Jennifer L; Whittemore, Alice S; Evans ASTW. No Title. 2 edition. Methods in Observational Epidemiology. New York: Oxford University Press; 1996
dc.relation.referencesRothman KJ GT. Modern Epidemiology. 3 edition. Williams LW E, editor. 2012
dc.relation.referencesWhitley E, Ball J. Statistics review 3: hypothesis testing and P values. Crit Care. 2002 Jun;6(3):222–5
dc.relation.referencesSerafim R, Gomes JA, Salluh J, Póvoa P. A Comparison of the Quick-SOFA and Systemic Inflammatory Response Syndrome Criteria for the Diagnosis of Sepsis and Prediction of Mortality: A Systematic Review and Meta-Analysis. Chest. 2018 Mar;153(3):646–55
dc.relation.referencesSterling SA, Puskarich MA, Glass AF, Guirgis F, Jones AE. The Impact of the Sepsis-3 Septic Shock Definition on Previously Defined Septic Shock Patients. Crit Care Med. 2017 Sep;45(9):1436–42
dc.relation.referencesMartos-Benítez FD, Soto-García A, Gutiérrez-Noyola A. Clinical characteristics and outcomes of cancer patients requiring intensive care unit admission: a prospective study. J Cancer Res Clin Oncol. 2018 Apr;144(4):717–23
dc.relation.referencesNathan N, Sculier J-P, Ameye L, Paesmans M, Bogdan-Dragos G, Meert A-P. Sepsis and Septic Shock Definitions in Patients With Cancer Admitted in ICU. J Intensive Care Med. 2019 Dec;885066619894933.
dc.relation.referencesChae B-R, Kim Y-J, Lee Y-S. Prognostic accuracy of the sequential organ failure assessment (SOFA) and quick SOFA for mortality in cancer patients with sepsis defined by systemic inflammatory response syndrome (SIRS). Support care cancer Off J Multinatl Assoc Support Care Cancer. 2020 Feb;28(2):653–9.
dc.relation.referencesKuo W-K, Hua C-C, Yu C-C, Liu Y-C, Huang C-Y. The cancer control status and APACHE II score are prognostic factors for critically ill patients with cancer and sepsis. J Formos Med Assoc. 2020 Jan;119(1 Pt 2):276–81
dc.relation.referencesRojas Ruiz IT, Méndez Toro A, Rincón FJ. Evaluación del desempeño pronóstico de dos puntajes de predicción de mortalidad a siete días en pacientes adultos oncológicos críticamente enfermos admitidos en una unidad de cuidados intensivos . Vol. 43, Acta Medica Colombiana . scieloco ; 2018. p. 81–9
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.subject.proposalSOFA
dc.subject.proposalSOFA
dc.subject.proposalAPACHE
dc.subject.proposalAPACHE
dc.subject.proposalSIRS
dc.subject.proposalSIRS
dc.subject.proposalAUROC
dc.subject.proposalAUROC
dc.subject.proposalSepsis
dc.subject.proposalSepsis
dc.subject.proposalMortalidad
dc.subject.proposalMortality rate
dc.subject.proposalCalibration
dc.subject.proposalCalibración
dc.type.coarhttp://purl.org/coar/resource_type/c_1843
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.contentText
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2


Archivos en el documento

Thumbnail
Thumbnail

Este documento aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del documento

Atribución-NoComercial-SinDerivadas 4.0 InternacionalEsta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial 4.0.Este documento ha sido depositado por parte de el(los) autor(es) bajo la siguiente constancia de depósito