Hyla-Louise Kluyts1, Wilhelmina Conradie2, Estie Cloete3, Sandra Spijkerman4, Oliver Smith5, Ahmed Alli5, Modise Z Koto6, Odisang D Montwedi7, Komalan Govender8, Larissa Cronjé9, Mariette Grobbelaar10, Jones A Omoshoro-Jones11, Nicolette F Rorke12, Philip Anderson13, Alexandra Torborg14, Christella Alphonsus14, Panagiotis Alexandris15, Aunel Mallier Peter16, Usha Singh17, Johan Diedericks18, Busisiwe Mrara19, Anthony Reed20, Gareth L Davies21, Jody G Davids22, Hendrik A Van Zyl23, Vishendran Govindasamy24, Reitze Rodseth25, Roel Matos-Puig26, Kajake A P Bhat27, Noel Naidoo28, John Roos29, Magdalena Jaworska30, Annemarie Steyn31, Johannes M Dippenaar32, R M Pearse33, Thandinkosi Madiba34, Bruce M Biccard35. 1. Department of Anaesthesiology, Dr George Mukhari Academic Hospital, Sefako Makgatho Health Sciences University, Pretoria, Gauteng, South Africa. hyla.kluyts@smu.ac.za. 2. Department of Surgery, Tygerberg Hospital, University of Stellenbosch, Cape Town, Western Cape Province, South Africa. 3. Department of Anaesthesia and Perioperative Medicine, Groote Schuur Hospital, University of Cape Town, Cape Town, Western Cape Province, South Africa. 4. Department of Anaesthesiology, Steve Biko Academic Hospital, University of Pretoria, Pretoria, Gauteng, South Africa. 5. Department of Anaesthesia and Critical Care, Charlotte Maxeke Johannesburg Academic Hospital, University of the Witwatersrand, Johannesburg, Gauteng, South Africa. 6. Department of Anaesthesiology, Dr George Mukhari Academic Hospital, Sefako Makgatho Health Sciences University, Pretoria, Gauteng, South Africa. 7. Department of Surgery, Kalafong Hospital, University of Pretoria, Pretoria, Gauteng, South Africa. 8. Prince Mshiyeni Memorial Hospital, Umlazi, KwaZulu-Natal, South Africa. 9. King Edward VIII Hospital, University of KwaZulu-Natal, Durban, KwaZulu-Natal, South Africa. 10. Edendale Hospital, University of KwaZulu-Natal, Pietermaritzburg, KwaZulu-Natal, South Africa. 11. Department of Surgery, Chris Hani-Baragwanath Academic Hospital, University of the Witwatersrand, Johannesburg, South Africa. 12. Department of Anaesthesiology, RK Khan Hospital, University of KwaZulu-Natal, eThekwini, KwaZulu-Natal, South Africa. 13. Kimberley Hospital Complex, University of the Free State, Kimberley, Northern Cape Province, South Africa. 14. Department of Anaesthesiology, Inkosi Albert Luthuli Central Hospital, University of KwaZulu-Natal, Durban, South Africa. 15. Port Elizabeth Hospital Complex, Port Elizabeth, Eastern Cape Province, South Africa. 16. Klerksdorp/Tshepong Hospital, University of the Witwatersrand, Klerksdorp, North West Province, South Africa. 17. Department of Anaesthesiology, Addington Hospital, University of KwaZulu-Natal, Durban, KwaZulu-Natal, South Africa. 18. Department of Anaesthesiology, Universitas Hospital, University of the Free State, Bloemfontein, Free State, South Africa. 19. Department of Anaesthesiology, Nelson Mandela Academic Hospital, Walter Sisulu University, Mthatha, Eastern Cape Province, South Africa. 20. New Somerset Hospital, University of Cape Town, Cape Town, Western Cape Province, South Africa. 21. Paarl Provincial Hospital, Paarl, Western Cape Province, South Africa. 22. George Regional Hospital, University of Cape Town, George, Western Cape Province, South Africa. 23. Department of Anaesthesiology, Worcester Hospital, Worcester, Western Cape Province, South Africa. 24. Department of Surgery, Grey's Hospital, Pietermaritzburg, KwaZulu-Natal, South Africa. 25. Department of Anaesthetics, Grey's Hospital, University of KwaZulu-Natal, Pietermaritzburg, KwaZulu-Natal, South Africa. 26. General Justice Gizenga Mpanza Regional Hospital, Stanger, KwaZulu-Natal, South Africa. 27. Department of Anaesthesiology, Cecilia Makiwane Hospital, Walter Sisulu University, East London Hospital Complex, Eastern Cape Province, South Africa. 28. Department of Surgery, Port Shepstone Regional Hospital, University of KwaZulu-Natal, Port Shepstone, KwaZulu-Natal, South Africa. 29. Department of Anaesthesia, Mitchells Plain Hospital, Cape Town, South Africa. 30. Helderberg and Karl Bremer Hospitals, University of Stellenbosch, Cape Town, Western Cape Province, South Africa. 31. Department Anaesthesiology, Potchefstroom Hospital, Potchefstroom, North West Province, South Africa. 32. Oral and Dental Hospital, University of Pretoria, Pretoria, Gauteng, South Africa. 33. Royal London Hospital, Queen Mary University of London, London, UK. 34. University of KwaZulu-Natal, Durban, South Africa. 35. Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa.
Abstract
BACKGROUND: Data on the factors that influence mortality after surgery in South Africa are scarce, and neither these data nor data on risk-adjusted in-hospital mortality after surgery are routinely collected. Predictors related to the context or setting of surgical care delivery may also provide insight into variation in practice. Variation must be addressed when planning for improvement of risk-adjusted outcomes. Our objective was to identify the factors predicting in-hospital mortality after surgery in South Africa from available data. METHODS: A multivariable logistic regression model was developed to identify predictors of 30-day in-hospital mortality in surgical patients in South Africa. Data from the South African contribution to the African Surgical Outcomes Study were used and included 3800 cases from 51 hospitals. A forward stepwise regression technique was then employed to select for possible predictors prior to model specification. Model performance was evaluated by assessing calibration and discrimination. The South African Surgical Outcomes Study cohort was used to validate the model. RESULTS: Variables found to predict 30-day in-hospital mortality were age, American Society of Anesthesiologists Physical Status category, urgent or emergent surgery, major surgery, and gastrointestinal-, head and neck-, thoracic- and neurosurgery. The area under the receiver operating curve or c-statistic was 0.859 (95% confidence interval: 0.827-0.892) for the full model. Calibration, as assessed using a calibration plot, was acceptable. Performance was similar in the validation cohort as compared to the derivation cohort. CONCLUSION: The prediction model did not include factors that can explain how the context of care influences post-operative mortality in South Africa. It does, however, provide a basis for reporting risk-adjusted perioperative mortality rate in the future, and identifies the types of surgery to be prioritised in quality improvement projects at a local or national level.
BACKGROUND: Data on the factors that influence mortality after surgery in South Africa are scarce, and neither these data nor data on risk-adjusted in-hospital mortality after surgery are routinely collected. Predictors related to the context or setting of surgical care delivery may also provide insight into variation in practice. Variation must be addressed when planning for improvement of risk-adjusted outcomes. Our objective was to identify the factors predicting in-hospital mortality after surgery in South Africa from available data. METHODS: A multivariable logistic regression model was developed to identify predictors of 30-day in-hospital mortality in surgical patients in South Africa. Data from the South African contribution to the African Surgical Outcomes Study were used and included 3800 cases from 51 hospitals. A forward stepwise regression technique was then employed to select for possible predictors prior to model specification. Model performance was evaluated by assessing calibration and discrimination. The South African Surgical Outcomes Study cohort was used to validate the model. RESULTS: Variables found to predict 30-day in-hospital mortality were age, American Society of Anesthesiologists Physical Status category, urgent or emergent surgery, major surgery, and gastrointestinal-, head and neck-, thoracic- and neurosurgery. The area under the receiver operating curve or c-statistic was 0.859 (95% confidence interval: 0.827-0.892) for the full model. Calibration, as assessed using a calibration plot, was acceptable. Performance was similar in the validation cohort as compared to the derivation cohort. CONCLUSION: The prediction model did not include factors that can explain how the context of care influences post-operative mortality in South Africa. It does, however, provide a basis for reporting risk-adjusted perioperative mortality rate in the future, and identifies the types of surgery to be prioritised in quality improvement projects at a local or national level.
Authors: Bruce M Biccard; Thandinkosi E Madiba; Hyla-Louise Kluyts; Dolly M Munlemvo; Farai D Madzimbamuto; Apollo Basenero; Christina S Gordon; Coulibaly Youssouf; Sylvia R Rakotoarison; Veekash Gobin; Ahmadou L Samateh; Chaibou M Sani; Akinyinka O Omigbodun; Simbo D Amanor-Boadu; Janat T Tumukunde; Tonya M Esterhuizen; Yannick Le Manach; Patrice Forget; Abdulaziz M Elkhogia; Ryad M Mehyaoui; Eugene Zoumeno; Gabriel Ndayisaba; Henry Ndasi; Andrew K N Ndonga; Zipporah W W Ngumi; Ushmah P Patel; Daniel Zemenfes Ashebir; Akwasi A K Antwi-Kusi; Bernard Mbwele; Hamza Doles Sama; Mahmoud Elfiky; Maher A Fawzy; Rupert M Pearse Journal: Lancet Date: 2018-01-03 Impact factor: 79.321
Authors: Sabrina Juran; Magdalena Gruendl; Isobel H Marks; P Niclas Broer; Jose Miguel Guzman; Justine Davies; Mark Shrime; Walter Johnson; Hampus Holmer; Gregory Peck; Emmanuel Makasa; Lars Hagander; Stephanie J Klug; John G Meara; Adrian W Gelb; David Ljungman Journal: Can J Anaesth Date: 2018-11-27 Impact factor: 5.063
Authors: H-L Kluyts; Y le Manach; D M Munlemvo; F Madzimbamuto; A Basenero; Y Coulibaly; S Rakotoarison; V Gobin; A L Samateh; M S Chaibou; A O Omigbodun; S D Amanor-Boadu; J Tumukunde; T E Madiba; R M Pearse; B M Biccard Journal: Br J Anaesth Date: 2018-09-17 Impact factor: 9.166