Mehmet Burtaç EREN, Tahir ÖZTÜRK, Erkal BİLGİÇ, Orhan BALTA

Ortopedik Cerrahi Sonrası Seviye 3 Yoğun Bakım Ünitesinde Takip Edilen Hastalarda SOFA, qSOFA, SIRS Kriter Puanlama Sistemleri ile 1 Yıllık Mortalite İlişkisi

Mortalite skolarmaları; taburcu durumu, hasta mortalitesi, Yoğun Bakım Ünitesi (YBÜ) mortalitesini ve hastanede kalış süresini tahmin etmek için tasarlanmıştır. Hastanın genel sağlık durumunun değerlendirilmesi açısından standardize edilmesi ve ortak bir dil oluşturması amaçlanan bu puanlama sistemleri, birçok YBÜ'de hastaların değerlendirilmesinde kullanılmaktadır. Bu çalışmayla, puanlama sistemlerinin spesifik bir hasta grubunda kullanılabilirliği değerlendirilmesi amaçlanmıştır. Ortopedik cerrahi sonrası YBÜ'de nispeten kısa süreli hastaneye yatışlar meydana geldiğinden, mortalitenin bir göstergesi olarak kullanılabilecek tahmin edici puanlama sistemlerinin tahmin gücü arasında hiçbir fark olmayacağı hipotezimizi oluşturduk. Çalışmamız tek merkez retrospektif olarak tasarlandı. Ocak 2017 ile Ağustos 2018 arasında 3. seviye yoğun bakım takibi yapılan tüm hastalar otomasyon sisteminde belirlendi. 146 hasta dosyası ve otomasyon sistemi verilerinin değerlendirilmesinin ardından dahil etme ve dışlama kriterlerine uyan hastalar belirlendi. Çalışmaya toplam 40 hasta dahil edildi. Ortalama yaş 75.69 (SD = 8.66 yıl),% 50 erkek ve% 50 kadındı. On beş hastanın (% 37,5) ilk yıl içerisinde vefat ettikleri görüldü. Hastalar ilk yıl hayatta kalan ve kalamayanlar olarak değerlendirildiğinde, gruplar arasında kantitatif değişkenler açısından postoperatif erken GKS ve erken postoperatif oksijen satürasyonu açısından anlamlı farklılık olduğu görüldü. (P< 0,005) Diğer hiçbir skorlama sistemi açısından anlamlı fark görülmedi(P> 0,005). Yoğun bakım ünitesinde takibi standartlaştırmak için uygun bir mortalite prediktör skoru seçilmelidir. Çalışmamız sonucunda SOFA, qSOFA ve SIRS kriterleri arasında anlamlı bir ilişki bulunmaması, bu skorlama sistemlerinin hasta grubumuzda 1 yıllık mortaliteyi öngörmek için uygun olmadığını düşündürdü. Daha geniş seriler ve daha fazla kriter içeren çalışmalarla ortopedik yoğun bakım hastalarına özgü spesifik kriterlerin oluşturulması gerekmektedir.

Anahtar Kelimeler:

SOFA skoru, qSOFA skoru, SIRS kriterleri, yoğun bakım mortalitesi, ortopedik cerrahi

The Relationship Between SOFA, qSOFA, SIRS Criteria Scoring Systems and 1-Year Mortality in Patients Followed Up in Level 3 Intensive Care Unit after Orthopedic Surgery

Predictive scoring systems are designed to predict patients' discharge status, patient mortality, Intensive Care Unit(ICU) mortality and lenght of hospital stay. These scoring systems, which are aimed to standardize and form a common language in terms of evaluating patient general health situation, are used in the evaluation of patients in many ICU.In this study, we aimed to evaluate the ability of the scoring systems that can be used to predict the mortality of the patients who will be followed up in the ICU after orthopedic surgery and predict the mortality that occurs in the first year outside the hospital. We established our hypothesis that there will be no difference between the predictive power of predictive scoring systems, which can be used as a marker of mortality, since relatively short-term hospitalizations occur in the ICU after orthopedic surgery. Our study was designed as a single center retrospective. Between January 2017 and August 2018, all patients undergoing level 3 intensive care follow-up were identified in the automation system. After the evaluation of 146 patients' files and automation system data, patients who were in compliance with the inclusion and exclusion criteria were identified. A total of 40 patients were included in the study. The mean age was 75.69 (SD = 8.66 years), 50% male and 50% female. Fifteen patients (37.5%) died during their first year follow-up. When the patients were evaluated as survivors and non-survivors in the first year, it was observed that there was a significant difference between the groups in terms of quantitative variables in terms of early postoperative GCS and in terms of early postoperative oxygen saturationThere was no significant difference between the two groups in terms of qualitative variables. (P> 0.005) An appropriate mortality predictor score should be selected to standardize follow-up in intensive care unit. As a result of our study, there was no significant relationship between gropus SOFA, qSOFA scores and SIRS critera met suggested that these scoring systems were not suitable for predicting 1-year mortality in our patient group. We believe that specific criteria should be established with studies with larger series and more criteria.

Keywords:

SOFA score, qSOFA score, SIRS criteria, ICU mortality, orthopedic surgery,

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1. Vincent J-L, De Mendonça A, Cantraine F, Moreno R, Takala J, Suter PM, et al. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Critical care medicine. 1998;26(11):1793-800.
2. Frohlich S, Murphy N, Conlon N. Predictors of outcome in decompensated liver disease: validation of the SOFA-L score. Irish medical journal. 2015;108(4):114-6.
3. Pan HC, Jenq CC, Tsai MH, Fan PC, Chang CH, Chang MY, et al. Scoring systems for 6‐month mortality in critically ill cirrhotic patients: a prospective analysis of chronic liver failure–sequential organ failure assessment score (CLIF‐SOFA). Alimentary pharmacology & therapeutics. 2014;40(9):1056-65.
4. Ñamendys-Silva SA, Texcocano-Becerra J, Herrera-Gómez A. Application of the Sequential Organ Failure Assessment (SOFA) score to patients with cancer admitted to the intensive care unit. American Journal of Hospice and Palliative Medicine®. 2009;26(5):341-6.
5. Gilli K, Remberger M, Hjelmqvist H, Ringden O, Mattsson J. Sequential Organ Failure Assessment predicts the outcome of SCT recipients admitted to intensive care unit. Bone marrow transplantation. 2010;45(4):682.
6. Ferreira FL, Bota DP, Bross A, Mélot C, Vincent J-L. Serial evaluation of the SOFA score to predict outcome in critically ill patients. Jama. 2001;286(14):1754-8.
7. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). Jama. 2016;315(8):801-10.
8. Seymour 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. 2016;315(8):762-74.
9. Shankar-Hari M, Phillips GS, Levy ML, Seymour CW, Liu VX, Deutschman CS, et al. Developing a new definition and assessing new clinical criteria for septic shock: for the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). Jama. 2016;315(8):775-87.
10. Raith 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;317(3):290-300.
11. Freund Y, Lemachatti N, Krastinova E, Van Laer M, Claessens Y-E, Avondo A, et al. Prognostic accuracy of Sepsis-3 criteria for in-hospital mortality among patients with suspected infection presenting to the emergency department. Jama. 2017;317(3):301-8.
12. Costa e Silva VT, de Castro I, Liano F, Muriel A, Rodríguez-Palomares JR, Yu L. Performance of the third-generation models of severity scoring systems (APACHE IV, SAPS 3 and MPM-III) in acute kidney injury critically ill patients. Nephrology Dialysis Transplantation. 2011;26(12):3894-901.
13. Maccariello E, Valente C, Nogueira L, Bonomo H, Ismael M, Machado JE, et al. SAPS 3 scores at the start of renal replacement therapy predict mortality in critically ill patients with acute kidney injury. Kidney international. 2010;77(1):51-6.
14. Zimmerman JE, Kramer AA, McNair DS, Malila FM. Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today’s critically ill patients. Critical care medicine. 2006;34(5):1297-310.
15. Zimmerman 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. Critical care medicine. 2006;34(10):2517-29.
16. Minne L, Abu-Hanna A, de Jonge E. Evaluation of SOFA-based models for predicting mortality in the ICU: A systematic review. Critical care. 2008;12(6):R161.
17. Nassar Jr AP, Mocelin AO, Nunes ALB, Giannini FP, Brauer L, Andrade FM, et al. Caution when using prognostic models: a prospective comparison of 3 recent prognostic models. Journal of critical care. 2012;27(4):423. e1-. e7.
18. Kuzniewicz MW, Vasilevskis EE, Lane R, Dean ML, Trivedi NG, Rennie DJ, et al. Variation in ICU risk-adjusted mortality: impact of methods of assessment and potential confounders. Chest. 2008;133(6):1319-27.
19. Kramer AA, Higgins TL, Zimmerman JE. Comparison of the Mortality Probability Admission Model III, National Quality Forum, and Acute Physiology and Chronic Health Evaluation IV hospital mortality models: implications for national benchmarking. Critical care medicine. 2014;42(3):544-53.
20. Craig D, Reid T, Wright E, Martin K, Davidson J, Hayes P, et al. The sequential organ failure assessment (SOFA) score is prognostically superior to the model for end‐stage liver disease (MELD) and MELD variants following paracetamol (acetaminophen) overdose. Alimentary pharmacology & therapeutics. 2012;35(6):705-13.
21. Soares M, Salluh JI. Validation of the SAPS 3 admission prognostic model in patients with cancer in need of intensive care. Intensive care medicine. 2006;32(11):1839-44.
22. Oliveira VMd, Brauner JS, Rodrigues Filho E, Susin RG, Draghetti V, Bolzan ST, et al. Is SAPS 3 better than APACHE II at predicting mortality in critically ill transplant patients? Clinics. 2013;68(2):153-8.
23. Tsai C-W, Lin Y-F, Wu V-C, Chu T-S, Chen Y-M, Hu F-C, et al. SAPS 3 at dialysis commencement is predictive of hospital mortality in patients supported by extracorporeal membrane oxygenation and acute dialysis. European journal of cardio-thoracic surgery. 2008;34(6):1158-64.
24. Khwannimit B, Bhurayanontachai R. A comparison of the performance of Simplified Acute Physiology Score 3 with old standard severity scores and customized scores in a mixed medical-coronary care unit. Minerva anestesiologica. 2011;77(3):305-12.
25. Nassar Junior AP, Mocelin AO, Andrade FM, Brauer L, Giannini FP, Nunes ALB, et al. SAPS 3, APACHE IV or GRACE: which score to choose for acute coronary syndrome patients in intensive care units? Sao Paulo Medical Journal. 2013;131(3):173-8.
26. Barie PS, Hydo LJ, Fischer E. Comparison of APACHE II and III scoring systems for mortality prediction in critical surgical illness. Archives of surgery. 1995;130(1):77-82.
27. Brown MC, Crede WB. Predictive ability of acute physiology and chronic health evaluation II scoring applied to human immunodeficiency virus-positive patients. Critical care medicine. 1995;23(5):848-53.
28. Lewinsohn G, Herman A, Leonov Y, Klinowski E. Critically ill obstetrical patients: Outcome and predictability. Critical care medicine. 1994;22(9):1412-4.
29. Sakr Y, Krauss C, Amaral AC, Rea-Neto A, Specht M, Reinhart K, et al. Comparison of the performance of SAPS II, SAPS 3, APACHE II, and their customized prognostic models in a surgical intensive care unit. British journal of anaesthesia. 2008;101(6):798-803.
30. Doerr F, Badreldin AM, Can F, Bayer O, Wahlers T, Hekmat K. SAPS 3 is not superior to SAPS 2 in cardiac surgery patients. Scandinavian Cardiovascular Journal. 2014;48(2):111-9.
31. Tsaousi G, Pitsis A, Ioannidis G, Pourzitaki C, Yannacou-Peftoulidou M, Vasilakos D. Implementation of EuroSCORE II as an adjunct to APACHE II model and SOFA score, for refining the prognostic accuracy in cardiac surgical patients. The Journal of cardiovascular surgery. 2015;56(6):919-27.
32. Peled E, Keren Y, Halachmi S, Soudry M, Zinman C, Kats Y, et al. Patients aged 80 and older undergoing orthopedic or urologic surgery: a prospective study focusing on perioperative morbidity and mortality. Gerontology. 2009;55(5):517-22.
33. Chariyalertsak S, Suriyawongpisal P, Thakkinstain A. Mortality after hip fractures in Thailand. International orthopaedics. 2001;25(5):294-7.
34. Adanır O, Albay C, Beytemür O. Relationship Between Mortality and Timing of Surgery in Elderly Intertrochanteric Hip Fractures. Eur Arch Med Res. 2017;33(1):23-7.
35. Waikar SS, Mount DB, Curhan GC. Mortality after hospitalization with mild, moderate, and severe hyponatremia. The American journal of medicine. 2009;122(9):857-65.
36. Chong CP, Ryan JE, van Gaal WJ, Lam QT, Sinnappu RN, Burrell LM, et al. Usefulness of N-terminal pro–brain natriuretic peptide to predict postoperative cardiac complications and long-term mortality after emergency lower limb orthopedic surgery. The American journal of cardiology. 2010;106(6):865-72.
37. Memtsoudis SG, Ma Y, Chiu YL, Walz JM, Voswinckel R, Mazumdar M. Perioperative mortality in patients with pulmonary hypertension undergoing major joint replacement. Anesthesia & Analgesia. 2010;111(5):1110-6.