Risk Calculators Validation for Elective Major General Surgery

Surgery Clinical Trial

— RCVEMG  

Official title:

Validation of Postoperative Mortality Prediction for Elective Major Surgical Operation With Existing Risk Calculators Based on Preoperative Parameters

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04041076
• Other study ID #: RCVEMG Protocol V2.0
• Status: Recruiting
• Start date: November 1, 2019
• Est. completion date: December 31, 2020

Study information

• Verified date: November 2019
• Source: Chinese University of Hong Kong
• Contact: Carmen KM Lam, MBBS
• Phone: +85290804633
• Email: carmenlam1013[@]gmail.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Nowadays, over 300 million surgical operations take place every year worldwide, which increase at a rate of 33.6% comparing data from 2005 to 2013. According to Surgical Outcomes Monitoring and Improvement Program (SOMIP) reports, which is an Hospital Authority-wide (HA-wide) audit on postoperative outcomes, a growth in major and ultra-major operations performed in our locality is also observed between 2008 and 2016, which leads to an increasing demand of high dependency and intensive care in the postoperative period. With the advancement in surgical technology, increasing surgical complexity and aging population have raised concerns towards perioperative costs and postoperative complications. Therefore, there is a need of an objective tool for risk stratification, which would be useful to guide clinical decision in terms of the magnitude of operation, level of intraoperative monitoring and postoperative placement plan.

Various risk scoring systems have been developed nowadays and each has its own limitations. As nowadays, the calculated risk score is commonly used in shared decision making process with patient and among the perioperative team. Risk calculation solely based on preoperative parameters will be more practical for daily clinical use. Therefore, in this study, the investigators would like to validate the postoperative mortality prediction with the risk calculators that are established merely using preoperative variables. Hopefully this would guide the future risk stratification in patients undergoing elective major surgical operation.

Description:

Nowadays, over 300 million surgical operations take place every year worldwide, which increase at a rate of 33.6% comparing data from 2005 to 2013. According to Surgical Outcomes Monitoring and Improvement Program (SOMIP) reports, which is an Hospital Authority-wide (HA-wide) audit on postoperative outcomes, a growth in major and ultra-major operations performed in our locality is also observed between 2008 and 2016, which leads to an increasing demand of high dependency and intensive care in the postoperative period. With the advancement in surgical technology, increasing surgical complexity and aging population have raised concerns towards perioperative costs and postoperative complications. An international prospective cohort study revealed that globally 1 in 6 patients experienced a complication before hospital discharge and 1 in 35 patients who experienced a complication subsequently died without leaving the hospital. Therefore, there is a need of an objective tool for risk stratification, which would be useful to guide clinical decision in terms of the magnitude of operation, level of intraoperative monitoring and postoperative placement plan.

There are a variety of risk stratification tools available for use in major non-cardiac surgery. Among all, the American Society of Anaesthesiology Physical Status (ASA-PS) evaluation scale is the most commonly used risk evaluation system in the assessment of patients' physical status in the preoperative period. Although ASA-PS is well-validated in previous studies and simple to use, inter-rater reliability and the lack of consideration in the surgical perspective have raised concerns towards the development of risk prediction models to supplement clinical judgements and strengthen operative mortality estimation. In 2013, a qualitative systematic review found that Portsmouth Variation of the Physiological and Operative Score for the enUmeration of Mortality and Morbidity (P-POSSUM) and Surgical Risk Scale (SRS) to be the most reliable multivariate risk scoring systems,, but both were noted to have limitations. P-POSSUM has overcome the issues of risk overestimation and inadequate generalization across various surgical specialties by POSSUM. But the calculation requires 12 physiological and 6 operative variables, some of which requires subjective interpretation e.g. chest X-ray. These makes P-POSSUM labour-intensive for clinical use. Whereas SRS requires fewer data for risk calculation, it has only been validated in a single centre study.

In recent years, newer risk prediction models like the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) model and Preoperative Score to Predict Postoperative Mortality (POSPOM) have been developed to provide a more comprehensive perioperative risk prediction for patients undergoing major operation. ACS-NSQIP model is developed based on high-quality clinical data from ACS-NSQIP and is described as a universal risk calculator, which includes a Surgeon Adjustment Score (SAS) that allows further score modification according to surgical performance. However, owing to the high dependence on preoperative laboratory results, ACS-NSQIP often encounters problems where these parameters are not readily available in emergency situations. POSSOM model involves 17 predictor variables. Together with its excellent discrimination and calibration properties demonstrated in its validation cohort and the easily referable rating system, POSSOM is considered a robust tool for 1-year postoperative mortality prediction. However, further reviews on its external validation are yet available.

In 2014, a new risk stratification tool, Surgical Outcome Risk Tool (SORT) was developed in the UK to predict 30-day mortality after non-cardiac surgery in adults, based on post hoc analysis of data in the Knowing the Risk study from the observational National Confidential Enquiry into Patient Outcome and Death (NCEOPD). SORT is a multivariate risk scoring system, which includes 6 variables: 1) American Society of Anesthesiologists Physical Status (ASA-PS) grade, 2) urgency of surgery, 3) surgical specialty, 4) surgical magnitude, 5) cancer or non-cancer surgery and 6) age.

In 2018, the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator has been developed based on Singapore local data, which makes use of 9 preoperative parameters namely: 1) age, 2) gender, 3) ASA classification, 4) surgical risk group, 5) emergency surgery, 6) anaemia status, 7) red cell distribution width (RDW), 8) ischaemic heart disease, , 9) congestive heart failure for prediction of postsurgical mortality and need for intensive care unit admission.

When the investigators look into each of these existing risk stratification tools, each of the risk calculators possesses its drawbacks when coming into clinical applications. As nowadays, the calculated risk score is commonly used in shared decision making process with patient and among the perioperative team. Risk calculation solely based on preoperative parameters will be more practical for daily clinical use. Therefore, in this study, the investigators would like to validate the postoperative mortality prediction with the risk calculators that are established merely using preoperative variables. Hopefully this would guide the future risk stratification in patients undergoing elective major surgical operation.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 5000
• Est. completion date: December 31, 2020
• Est. primary completion date: December 31, 2020
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

1. patient aged 18 years or over

2. undergoing elective major surgical operation*

3. requiring a planned overnight admission

Exclusion Criteria:

• Patients undergoing day case surgery, obstetric procedures, neurosurgery, cardiac or transplant surgery were excluded.

• Patient were also excluded if any of the key variables were missing

Related Conditions & MeSH terms

• Death
• Surgery

Intervention

Procedure:
• Major surgical operation
Surgical operation with magnitude defined as major or ultra-major

Locations

Country	Name	City	State
Hong Kong	Department of Anaesthesia and Intensive Care, New Territories West Cluster, Hospital Authority	Hong Kong

Sponsors (2)

Lead Sponsor	Collaborator
Chinese University of Hong Kong	Tuen Mun Hospital

Country where clinical trial is conducted

Hong Kong, 

References & Publications (22)

Barnett S, Moonesinghe SR. Clinical risk scores to guide perioperative management. Postgrad Med J. 2011 Aug;87(1030):535-41. doi: 10.1136/pgmj.2010.107169. Epub 2011 Jan 21. Review. — View Citation

Bilimoria KY, Liu Y, Paruch JL, Zhou L, Kmiecik TE, Ko CY, Cohen ME. Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons. J Am Coll Surg. 2013 Nov;217(5):833-42.e1-3. doi: 10.1016/j.jamcollsurg.2013.07.385. Epub 2013 Sep 18. — View Citation

Chan DXH, Sim YE, Chan YH, Poopalalingam R, Abdullah HR. Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a sin — View Citation

Cuvillon P, Nouvellon E, Marret E, Albaladejo P, Fortier LP, Fabbro-Perray P, Malinovsky JM, Ripart J. American Society of Anesthesiologists' physical status system: a multicentre Francophone study to analyse reasons for classification disagreement. Eur J Anaesthesiol. 2011 Oct;28(10):742-7. doi: 10.1097/EJA.0b013e328348fc9d. — View Citation

Davenport DL, Henderson WG, Khuri SF, Mentzer RM Jr. Preoperative risk factors and surgical complexity are more predictive of costs than postoperative complications: a case study using the National Surgical Quality Improvement Program (NSQIP) database. Ann Surg. 2005 Oct;242(4):463-8; discussion 468-71. — View Citation

Devereaux PJ, Sessler DI. Cardiac Complications in Patients Undergoing Major Noncardiac Surgery. N Engl J Med. 2015 Dec 3;373(23):2258-69. doi: 10.1056/NEJMra1502824. Review. — View Citation

Haskins IN, Maluso PJ, Schroeder ME, Amdur RL, Vaziri K, Agarwal S, Sarani B. A calculator for mortality following emergency general surgery based on the American College of Surgeons National Surgical Quality Improvement Program database. J Trauma Acute C — View Citation

International Surgical Outcomes Study group. Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries. Br J Anaesth. 2016 Oct 31;117(5):601-609. doi: 10.1093/bja/aew316. Erratum in: Br J Anaesth. 2017 Sep 1;119(3):553. — View Citation

Kristensen SD, Knuuti J, Saraste A, Anker S, Bøtker HE, Hert SD, Ford I, Gonzalez-Juanatey JR, Gorenek B, Heyndrickx GR, Hoeft A, Huber K, Iung B, Kjeldsen KP, Longrois D, Lüscher TF, Pierard L, Pocock S, Price S, Roffi M, Sirnes PA, Sousa-Uva M, Voudris V, Funck-Brentano C; Authors/Task Force Members. 2014 ESC/ESA Guidelines on non-cardiac surgery: cardiovascular assessment and management: The Joint Task Force on non-cardiac surgery: cardiovascular assessment and management of the European Society of Cardiology (ESC) and the European Society of Anaesthesiology (ESA). Eur Heart J. 2014 Sep 14;35(35):2383-431. doi: 10.1093/eurheartj/ehu282. Epub 2014 Aug 1. — View Citation

Le Manach Y, Collins G, Rodseth R, Le Bihan-Benjamin C, Biccard B, Riou B, Devereaux PJ, Landais P. Preoperative Score to Predict Postoperative Mortality (POSPOM): Derivation and Validation. Anesthesiology. 2016 Mar;124(3):570-9. doi: 10.1097/ALN.00000000 — View Citation

Liao L, Mark DB. Clinical prediction models: are we building better mousetraps? J Am Coll Cardiol. 2003 Sep 3;42(5):851-3. Review. — View Citation

Lupei MI, Chipman JG, Beilman GJ, Oancea SC, Konia MR. The association between ASA status and other risk stratification models on postoperative intensive care unit outcomes. Anesth Analg. 2014 May;118(5):989-94. doi: 10.1213/ANE.0000000000000187. — View Citation

Makary MA, Segev DL, Pronovost PJ, Syin D, Bandeen-Roche K, Patel P, Takenaga R, Devgan L, Holzmueller CG, Tian J, Fried LP. Frailty as a predictor of surgical outcomes in older patients. J Am Coll Surg. 2010 Jun;210(6):901-8. doi: 10.1016/j.jamcollsurg.2010.01.028. Epub 2010 Apr 28. — View Citation

Moonesinghe SR, Mythen MG, Das P, Rowan KM, Grocott MP. Risk stratification tools for predicting morbidity and mortality in adult patients undergoing major surgery: qualitative systematic review. Anesthesiology. 2013 Oct;119(4):959-81. doi: 10.1097/ALN.0b013e3182a4e94d. Review. — View Citation

Older P, Hall A. Clinical review: how to identify high-risk surgical patients. Crit Care. 2004 Oct;8(5):369-72. Epub 2004 Mar 31. Review. — View Citation

Protopapa KL, Simpson JC, Smith NC, Moonesinghe SR. Development and validation of the Surgical Outcome Risk Tool (SORT). Br J Surg. 2014 Dec;101(13):1774-83. doi: 10.1002/bjs.9638. — View Citation

Protopapa KL. Is there a place for the Surgical Outcome Risk Tool app in routine clinical practice? Br J Hosp Med (Lond). 2016 Nov 2;77(11):612-613. — View Citation

Sankar A, Johnson SR, Beattie WS, Tait G, Wijeysundera DN. Reliability of the American Society of Anesthesiologists physical status scale in clinical practice. Br J Anaesth. 2014 Sep;113(3):424-32. doi: 10.1093/bja/aeu100. Epub 2014 Apr 11. — View Citation

Sobol JB, Wunsch H. Triage of high-risk surgical patients for intensive care. Crit Care. 2011;15(2):217. doi: 10.1186/cc9999. Epub 2011 Mar 22. Review. — View Citation

Weiser TG, Haynes AB, Molina G, Lipsitz SR, Esquivel MM, Uribe-Leitz T, Fu R, Azad T, Chao TE, Berry WR, Gawande AA. Estimate of the global volume of surgery in 2012: an assessment supporting improved health outcomes. Lancet. 2015 Apr 27;385 Suppl 2:S11. doi: 10.1016/S0140-6736(15)60806-6. Epub 2015 Apr 26. — View Citation

Weiser TG, Regenbogen SE, Thompson KD, Haynes AB, Lipsitz SR, Berry WR, Gawande AA. An estimation of the global volume of surgery: a modelling strategy based on available data. Lancet. 2008 Jul 12;372(9633):139-44. doi: 10.1016/S0140-6736(08)60878-8. Epub 2008 Jun 24. — View Citation

Yurtlu DA, Aksun M, Ayvat P, Karahan N, Koroglu L, Aran GÖ. Comparison of Risk Scoring Systems to Predict the Outcome in ASA-PS V Patients Undergoing Surgery: A Retrospective Cohort Study. Medicine (Baltimore). 2016 Mar;95(13):e3238. doi: 10.1097/MD.0000000000003238. — View Citation

* Note: There are 22 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	30-day mortality rate	The Rate of Mortality at or within 30 days after the elective major surgical operation	30 days postoperatively
Secondary	1-year mortality rate	The Rate of Mortality at or within 1 year after the elective major surgical operation	1 year postoperatively

External Links

•   Ismail, H., Cormie, P., Burbury, K. et al. Curr Anesthesiol Rep (2018) 8: 375. https://doi.org/10.1007/s40140-018-0300-7