Accuracy of ESI triage, qSOFA Score And Their Combinations As Predictor of Sepsis Prognosis

Nikma Alfi Rosida(1*), Teguh Wahdju Sardjono(2), Laily Yuliatun(3)
(1) Universitas Brawijaya (UB)
(2) Department of Parasitology, Faculty of Medicine, Brawijaya University, Malang, Indonesia
(3) Magister of Nursing Program, Faculty of Medicine, Brawijaya University
(*) Corresponding Author
DOI : 10.30604/jika.v7i3.1041

Abstract

This study is to identify the combination of ESI, qSOFA and their combination as a predictor of sepsis prognosis. The research method was a retrospective study design. Out of a total of 2394 MRs of patients during that period, there were only 112 MRs met the inclusion criteria and then included in this study, consisting of 42 survival and 70 un-survival outcomes respectively. Among the un-survival group, there were 41 (58,6%) have ESI 1-2, and 29 (41.4%) ESI 3-5; also 21 (30%) qSOFA more than 2, and 49 (70%) qSOFA less than 2. The sensitivity of ESI to predict the unsurvive outcome was 71.4% and its specificity was 28.6%. Meanwhile, the sensitivity of qSOFA to predict the unsurvive outcome was 30% and its specificity was 85.7%. The use of a combination of both to predict the prognosis was not significantly increased (p more than 0.05). The sensitivity of the combination of ESI and qSOFA to predict the unsurvive outcome was 61.9% and its specificity was 52.9%. So, a low ESI-score seemed to be more relevant to predicting the risk of unsurvival outcome than a high qSOFA, but a low qSOFA is more relevant to predicting the risk of survival outcome than a high ESI-score. The combination of both does not significantly increase the accuracy of the prognosis-predictor.

 

Abstrak: Penelitian ini bertujuan untuk mengidentifikasi kombinasi ESI, qSOFA dan kombinasinya sebagai prediktor prognosis sepsis. Metode penelitian yang digunakan adalah desain penelitian retrospektif untuk membandingkan akurasi ESI dengan qSOFA. Data yang digunakan adalah seluruh rekam medis pasien di RS Sumberglagah Mojokerto, Jawa Timur, Indonesia. Kriteria inklusi adalah rekam medis pasien berusia lebih dari 18 tahun, data lengkap meliputi tekanan darah, HR, RR, SaO2 dan kadar ESI pasien. Dari total 2394 MR pasien selama periode tersebut, hanya 112 MR yang memenuhi kriteria inklusi dan kemudian dimasukkan dalam penelitian ini, terdiri dari 42 hasil survival dan 70 unsurvival. Diantara kelompok unsurvival, ada 41 (58,6%) memiliki ESI 1-2, dan 29 (41,4%) ESI 3-5; juga 21 (30%) qSOFA 2, dan 49 (70%) qSOFA kurang dari 2. Sensitivitas ESI adalah 71,4% dan spesifisitasnya adalah 28,6% untuk memprediksi unsurvive outcome, sedangkan sensitivitas qSOFA adalah 30% dan spesifisitasnya 85,7%. Kombinasi keduanya untuk memprediksi prognosis tidak meningkat secara signifikan (p lebih dari 0,05). Sensitivitas kombinasi ESI dan qSOFA adalah 61,9% dan spesifisitasnya adalah 52,9%. Skor ESI rendah tampaknya lebih relevan untuk memprediksi risiko hasil yang tidak bertahan hidup daripada skor qSOFA tinggi, tetapi skor qSOFA rendah lebih relevan untuk memprediksi risiko hasil kelangsungan hidup daripada skor ESI tinggi. Kombinasi keduanya tidak secara signifikan meningkatkan akurasi prediktor prognosis.

Keywords


ESI; qSOFA; Prediktor; Prognosis Sepsis

References


Aronsky, D., Jones, I., Raines, B., Hemphill, R., Mayberry, S. R., Luther, M. A., & Slusser, T. (2008). An integrated computerized triage system in the emergency department. AMIA ... Annual Symposium Proceedings. AMIA Symposium, 2008, 16–20. https://pubmed.ncbi.nlm.nih.gov/18999190

Bessière, F., Khenifer, S., Dubourg, J., Durieu, I., & Lega, J.-C. (2013). Prognostic value of troponins in sepsis: a meta-analysis. Intensive Care Medicine, 39(7), 1181–1189. https://doi.org/10.1007/s00134-013-2902-3

Cecconi, M., Evans, L., Levy, M., & Rhodes, A. (2018). Sepsis and septic shock. In The Lancet. https://doi.org/10.1016/S0140-6736(18)30696-2

Dugas, A. F., Kirsch, T. D., Toerper, M., Korley, F., Yenokyan, G., France, D., Hager, D., & Levin, S. (2016). An Electronic Emergency Triage System to Improve Patient Distribution by Critical Outcomes. The Journal of Emergency Medicine, 50(6), 910–918. https://doi.org/https://doi.org/10.1016/j.jemermed.2016.02.026

Garbero, R. de F., Simões, A. A., Martins, G. A., Cruz, L. V. da, & von Zuben, V. G. M. (2019). SOFA and qSOFA at admission to the emergency department: Diagnostic sensitivity and relation with prognosis in patients with suspected infection. Turkish Journal of Emergency Medicine. https://doi.org/10.1016/j.tjem.2019.05.002

Ghafarypour-Jahrom, M., Taghizadeh, M., Heidari, K., Derakhshanfar, H., & Validity, D. H. (2018). Validity and Reliability of the Emergency Severity Index and Australasian Triage System in Pediatric Emergency Care of Mofid Children’s Hospital in Iran. Bull Emerg Trauma, 6(4), 329–333. https://doi.org/10.29252/beat-060410

Gilboy, N., Tanabe, P., Travers, D., & Rosenau, A. . (2012). Emergency Severity Index (ESI): A Triage Tool for Emergency Department Care Version 4 Implementation Handbook. AHRQ Publication.

Girard, T. D., Opal, S. M., & Ely, E. W. (2005). Insights into severe sepsis in older patients: From epidemiology to evidence-based management. Clinical Infectious Diseases. https://doi.org/10.1086/427876

Goetzinger, K. R., Tuuli, M. G., & Odibo, A. O. (2011). Statistical analysis and interpretation of prenatal diagnostic imaging studies, part 3: Approach to study design. Journal of Ultrasound in Medicine, 30(10), 1415–1423. https://doi.org/10.7863/jum.2011.30.10.1415

Gonçalves, L., Subtil, A., Rosário Oliveira, M., & De Zea Bermudez, P. (2014). ROC curve estimation: An overview. Revstat Statistical Journal, 12(1), 1–20.

Hinson, J. S., Martinez, D. A., Schmitz, P. S. K., Toerper, M., Radu, D., Scheulen, J., Stewart de Ramirez, S. A., & Levin, S. (2018). Accuracy of emergency department triage using the Emergency Severity Index and independent predictors of under-triage and over-triage in Brazil: a retrospective cohort analysis. International Journal of Emergency Medicine. https://doi.org/10.1186/s12245-017-0161-8

Janssens, A. C. J. W., & Martens, F. K. (2020). Reflection on modern methods: Revisiting the area under the ROC Curve. International Journal of Epidemiology, 49(4), 1397–1403. https://doi.org/10.1093/ije/dyz274

Kim, M., Ahn, S., Kim, W. Y., Sohn, C. H., Seo, D. W., Lee, Y.-S., & Lim, K. S. (2017). Predictive performance of the quick Sequential Organ Failure Assessment score as a screening tool for sepsis, mortality, and intensive care unit admission in patients with febrile neutropenia. Supportive Care in Cancer, 25(5), 1557–1562. https://doi.org/10.1007/s00520-016-3567-6

Kumar, G., Kumar, N., Taneja, A., Kaleekal, T., Tarima, S., McGinley, E., Jimenez, E., Mohan, A., Khan, R. A., Whittle, J., Jacobs, E., & Nanchal, R. (2011). Nationwide trends of severe sepsis in the 21st century (2000-2007). Chest. https://doi.org/10.1378/chest.11-0352

Kwak, H., Suh, G. J., Kim, T., Kwon, W. Y., Kim, K. S., Jung, Y. S., Ko, J. I., & Shin, S. M. (2018). Prognostic performance of Emergency Severity Index (ESI) combined with qSOFA score. American Journal of Emergency Medicine, 36(10), 1784–1788. https://doi.org/10.1016/j.ajem.2018.01.088

Levin, S., Toerper, M., Hamrock, E., Hinson, J. S., Barnes, S., Gardner, H., Dugas, A., Linton, B., Kirsch, T., & Kelen, G. (2018). Machine-Learning-Based Electronic Triage More Accurately Differentiates Patients With Respect to Clinical Outcomes Compared With the Emergency Severity Index. Annals of Emergency Medicine, 71(5), 565-574.e2. https://doi.org/10.1016/j.annemergmed.2017.08.005

Levy, M. M., Evans, L. E., & Rhodes, A. (2018). The surviving sepsis campaign bundle: 2018 update. Critical Care Medicine. https://doi.org/10.1097/CCM.0000000000003119

Loritz, M., Busch, H. J., Helbing, T., & Fink, K. (2020). Prospective evaluation of the quickSOFA score as a screening for sepsis in the emergency department. Internal and Emergency Medicine, 15(4), 685–693. https://doi.org/10.1007/s11739-019-02258-2

Machado, F. R., De Assunção, M. S. C., Cavalcanti, A. B., Japiassú, A. M., De Azevedo, L. C. P., & Oliveira, M. C. (2016). Getting a consensus: Advantages and disadvantages of Sepsis 3 in the context of middle-income settings. Revista Brasileira de Terapia Intensiva, 28(4), 361–365. https://doi.org/10.5935/0103-507X.20160068

Mistry, B., Stewart De Ramirez, S., Kelen, G., Schmitz, P. S. K., Balhara, K. S., Levin, S., Martinez, D., Psoter, K., Anton, X., & Hinson, J. S. (2018). Accuracy and Reliability of Emergency Department Triage Using the Emergency Severity Index: An International Multicenter Assessment. Annals of Emergency Medicine, 71(5), 581-587.e3. https://doi.org/10.1016/j.annemergmed.2017.09.036

Nieves Ortega, R., Rosin, C., Bingisser, R., & Nickel, C. H. (2019). Clinical Scores and Formal Triage for Screening of Sepsis and Adverse Outcomes on Arrival in an Emergency Department All-Comer Cohort. The Journal of Emergency Medicine, 57(4), 453-460.e2. https://doi.org/https://doi.org/10.1016/j.jemermed.2019.06.036

Ortega, R. N., Rosin, C., Bingisser, R., & Nickel, C. H. (2019). Original Contributions. Journal of Emergency Medicine, 57(4), 453-460.e2. https://doi.org/10.1016/j.jemermed.2019.06.036

Osatnik, J., Tort-Oribea, B., Folco, J., Sosa, A., Ivulich, D., Kleinert, M. M., & Roberti, J. E. (2018). Predictive performance of quick sequential organ failure assessment scoring in an Argentinian Hospital. Journal of Clinical and Diagnostic Research, 12(10), OC22–OC26. https://doi.org/10.7860/JCDR/2018/37018.12150

Phungoen, P., Khemtong, S., Apiratwarakul, K., Ienghong, K., & Kotruchin, P. (2020). Emergency Severity Index as a predictor of in-hospital mortality in suspected sepsis patients in the emergency department. American Journal of Emergency Medicine, 38(9), 1854–1859. https://doi.org/10.1016/j.ajem.2020.06.005

Rudd, K. E., Johnson, S. C., Agesa, K. M., Shackelford, K. A., Tsoi, D., Kievlan, D. R., Colombara, D. V., Ikuta, K. S., Kissoon, N., Finfer, S., Fleischmann-Struzek, C., Machado, F. R., Reinhart, K. K., Rowan, K., Seymour, C. W., Watson, R. S., West, T. E., Marinho, F., Hay, S. I., … Naghavi, M. (2020). Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the Global Burden of Disease Study. The Lancet. https://doi.org/10.1016/S0140-6736(19)32989-7

Sagy, M., Al-Qaqaa, Y., & Kim, P. (2013). Definitions and pathophysiology of sepsis. Current Problems in Pediatric and Adolescent Health Care, 43(10), 260–263. https://doi.org/10.1016/j.cppeds.2013.10.001

Seymour, C. W., Liu, V. X., Iwashyna, T. J., Brunkhorst, F. M., Rea, T. D., Scherag, A., Rubenfeld, G., Kahn, J. M., Shankar-Hari, M., Singer, M., Deutschman, C. S., Escobar, G. J., & Angus, D. C. (2016). Assessment of Clinical Criteria for Sepsis. JAMA. https://doi.org/10.1001/jama.2016.0288

Shahsavarinia, K., Moharramzadeh, P., Arvanagi, R. J., & Mahmoodpoor, A. (2020). Qsofa score for prediction of sepsis outcome in emergency department. Pakistan Journal of Medical Sciences, 36(4), 668–672. https://doi.org/10.12669/pjms.36.4.2031

Singer, M., Deutschman, C. S., Seymour, C., Shankar-Hari, M., Annane, D., Bauer, M., Bellomo, R., Bernard, G. R., Chiche, J. D., Coopersmith, C. M., Hotchkiss, R. S., Levy, M. M., Marshall, J. C., Martin, G. S., Opal, S. M., Rubenfeld, G. D., Poll, T. Der, Vincent, J. L., & Angus, D. C. (2016). The third international consensus definitions for sepsis and septic shock (sepsis-3). In JAMA - Journal of the American Medical Association. https://doi.org/10.1001/jama.2016.0287

Sinha, S., & Ray, B. (2018). Sepsis-3: How useful is the new definition? Journal of Anaesthesiol Ogy Clinic Pharmacology, 34(4), 542–543. https://doi.org/10.4103/joacp.JOACP_335_16

Spoto, S., Cella, E., Cesaris, M. De, Locorriere, L., Mazzaroppi, S., Nobile, E., Lanotte, A. M., Pedicino, L., Fogolari, M., Costantino, S., Dicuonzo, G., Ciccozzi, M., & Angeletti, S. (2018). Procalcitonin and Mr-Proadrenomedullin Combination With SOFA And qSOFA Scores for Sepsis Diagnosis And Prognosis : A Diagnostic Algorithm. SHOCK, 50(1), 44–52. https://doi.org/10.1097/SHK.0000000000001023

Spoto, S., Nobile, E., Carnà, E. P. R., Fogolari, M., Caputo, D., De Florio, L., Valeriani, E., Benvenuto, D., Costantino, S., Ciccozzi, M., & Angeletti, S. (2020). Best diagnostic accuracy of sepsis combining SIRS criteria or qSOFA score with Procalcitonin and Mid-Regional pro-Adrenomedullin outside ICU. Scientific Reports, 10(1), 1–11. https://doi.org/10.1038/s41598-020-73676-y

Wang, S., Li, T., Li, Y., Zhang, J., Jiu, X. D.-Z. wei zhong bing ji, & 2017, U. (2011). Predictive value of four different scoring systems for septic patient’s outcome: a retrospective analysis with 311 patients. Europepmc.Org. https://europepmc.org/article/med/28625260

Wawrose, R., Baraniuk, M., Standiford, L., Wade, C., Holcomb, J., & Moore, L. (2016). Comparison of Sepsis Screening Tools’ Ability to Detect Sepsis Accurately. Surgical Infections, 17(5), 525–529. https://doi.org/10.1089/sur.2015.069

Zweig, M. H., & Campbell, G. (1993). Receiver-operating characteristic (ROC) plots: A fundamental evaluation tool in clinical medicine. Clinical Chemistry, 39(4), 561–577. https://doi.org/10.1093/clinchem/39.4.561


Article Statistic

Abstract view : 22 times
PDF (Bahasa Indonesia) views : 1 times

Dimensions Metrics

How To Cite This :

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Nikma Alfi Rosida

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.