Validation of the OAKS prognostic model for acute kidney injury after gastrointestinal surgery

Ahmed, W.U.R.; Bhatia, S.; McLean, K.A.; Khaw, R.; Baker, D.; Kamarajah, S.K.; ... ; Robi (2022)

Article / Letter to editor

Background Postoperative acute kidney injury (AKI) is a common complication of major gastrointestinal surgery with an impact on short- and long-term survival. No validated system for risk stratification exists for this patient group. This study aimed to validate externally a prognostic model for AKI after major gastrointestinal surgery in two multicentre cohort studies.Methods The Outcomes After Kidney injury in Surgery (OAKS) prognostic model was developed to predict risk of AKI in the 7 days after surgery using six routine datapoints (age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker). Validation was performed within two independent cohorts: a prospective multicentre, international study ('IMAGINE') of patients undergoing elective colorectal surgery (2018); and a retrospective regional cohort study ('Tayside') in major abdominal surgery (2011-2015). Multivariable logistic regression was used to predict risk of AKI, with multiple imputation used to account for data missing at random. Prognostic accuracy was assessed for patients at high risk (greater than 20 per cent) of postoperative AKI.Results In the validation cohorts, 12.9 per cent of patients (661 of 5106) in IMAGINE and 14.7 per cent (106 of 719 patients) in Tayside developed 7-day postoperative AKI. Using the OAKS model, 558 patients (9.6 per cent) were classified as high risk. Less than 10 per cent of patients classified as low-risk developed AKI in either cohort (negative predictive value greater than 0.9). Upon external validation, the OAKS model retained an area under the receiver operating characteristic (AUC) curve of range 0.655-0.681 (Tayside 95 per cent c.i. 0.596 to 0.714; IMAGINE 95 per cent c.i. 0.659 to 0.703), sensitivity values range 0.323-0.352 (IMAGINE 95 per cent c.i. 0.281 to 0.368; Tayside 95 per cent c.i. 0.253 to 0.461), and specificity range 0.881-0.890 (Tayside 95 per cent c.i. 0.853 to 0.905; IMAGINE 95 per cent c.i. 0.881 to 0.899).Conclusion The OAKS prognostic model can identify patients who are not at high risk of postoperative AKI after gastrointestinal surgery with high specificity.Presented to Association of Surgeons in Training (ASiT) International Conference 2018 (Edinburgh, UK), European Society of Coloproctology (ESCP) International Conference 2018 (Nice, France), SARS (Society of Academic and Research Surgery) 2020 (Virtual, UK).

• All authors: Ahmed, W.U.R.; Bhatia, S.; McLean, K.A.; Khaw, R.; Baker, D.; Kamarajah, S.K.; Bell, S.; Nepogodiev, D.; Harrison, E.M.; Glasbey, J.C.; Borakati, A.; Burke, J.; Drake, T.M.; Bath, M.F.; Claireaux, H.A.; Gundogan, B.; Mohan, M.; Deekonda, P.; Kong, C.; Joyce, H.; McNamee, L.; Woin, E.; Khatri, C.; Fitzgerald, J.E.; Bhangu, A.; Arulkumaran, N.; Duthie, F.; Hughes, J.; Pinkney, T.D.; Prowle, J.; Richards, T.; Thomas, M.; Blanco-Colino, R.; Chapman, S.J.; Pata, F.; Pellino, G.; Sgro, A.; Soares, A.; Elst, T. van; Straten, S. van; Knowles, C.H.; Dynes, K.; Patel, M.; Patel, P.; Wigley, C.; Suresh, R.; Shaw, A.; Klimach, S.; Jull, P.; Evans, D.; Preece, R.; Ibrahim, I.; Manikavasagar, V.; Smith, R.; Brown, F.S.; Teo, R.; Sim, D.P.Y.; Logan, A.E.; Barai, I.; Amin, H.; Suresh, S.; Sethi, R.; Gul, W.; Bolton, W.; Corbridge, O.; Horne, L.; Attalla, M.; Morley, R.; Robinson, C.; Hoskins, T.; McAllister, R.; Lee, S.; Dennis, Y.; Nixon, G.; Heywood, E.; Wilson, H.; Ng, L.; Samaraweera, S.; Mills, A.; Doherty, C.; Belchos, J.; Phan, V.; Lim, M.; Miller, F.A.; Chouari, T.; Gardner, T.; Goergen, N.; Hayes, J.D.B.; MacLeod, C.S.; McCormack, R.; McKinley, A.; McKinstry, S.; Milligan, W.; Ooi, L.; Rafiq, N.M.; Sammut, T.; Sinclair, E.; Smith, M.; Wong, J.; Ablett, A.D.; Tie-Gill, T.; Ramsay, G.; Paola, L. de; McGuckin, S.; Alshakhs, A.; Ahmeidat, A.; Francis, A.A.; Baker, C.; Boulton, A.P.R.; Collins, J.; Copley, H.C.; Fearnhead, N.; Fox, H.; Mah, T.; McKenna, J.; Naruka, V.; Nigam, N.; Nourallah, B.; Perera, S.; Qureshi, A.; Saggar, S.; Sun, L.; Wang, X.; Yang, D.D.; Ali, Z.; Mullarkey, L.; Walshe, R.; Lewis, E.; Berry, B.; Moneim, J.; Mookerjee, S.; Al-hadithi, A.; Caroll, P.; Doyle, C.; Elangovan, S.; Falamarzi, A.; Perai, K.G.; Greenan, E.; Jain, D.; Lang-Orsini, M.; Lim, S.; Ridgway, P.; Laan, S. van der; Arthur, J.; Barclay, J.; Bradley, P.; Edwin, C.; Finch, E.; Hayashi, E.; Hopkins, M.; Kelly, D.; Kelly, M.; McCartan, N.; Ormrod, A.; Pakenham, A.; Christy, S.; Hayward, J.; Hitchen, C.; Kishore, A.; Martins, T.; Philomen, J.; Rao, R.; Rickards, C.; Burns, N.; Copeland, M.; Durand, C.; Dyal, A.; Ghaffar, A.; Gidwani, A.; Grant, M.; Gribbon, C.; Gruhn, A.; Leer, M.; Ojofeitimi, O.; Carroll, L.; Hylands, A.; Delaugere, L.P.; Reveendran, D.; Ahmad, K.; Beattie, G.; Beatty, M.; Campbell, G.; Donaldson, G.; Graham, S.; Holmes, D.; Kanabar, S.; Liu, H.; McCann, C.; Stewart, R.; Vara, S.; Coulter, C.; Ralston, C.; Laverty, L.; Gallagher, P.; Ajibola-Taylor, O.; Andah, E.J.E.; Ani, C.; Cabdi, N.M.O.; Ito, G.; Jones, M.; Komoriyama, A.; Titu, L.; Ahmed, A.; Yeo, Y.Q.; Elliott, D.; Bennett, J.; Mcnamara, M.; Sivarajah, S.; Dunmore, C.; Basra, M.; Gallogly, P.; Harinath, G.; Leong, S.H.; Pradhan, A.; Siddiqui, I.; Zaat, S.; Ali, A.; Galea, M.; Looi, W.L.; Ng, J.C.K.; Farhan-Alanie, M.M.H.; Aitken, G.; Nair, M.; Aly, M.H.; Buari, M.; Atkin, G.; Azizi, A.; Cargill, Z.; China, Z.; Elliot, J.; Jebakumar, R.; Lam, J.; Mudalige, G.; Onyerindu, C.; Renju, M.; Babu, V.S.; Ahmed, K.; Sheikh, Z.; Monks, M.; Lehmann, J.; Rotimi, O.; Hussain, M.; Joji, N.; Lovett, B.; Mownah, H.; Dwyer-Hemmings, L.; Busuttil, A.; Powell, J.; Hensher, C.; Vivian, F.; Ali, B.; Cresswell, B.; Dhillon, A.K.; Dupaguntla, Y.S.; Hungwe, C.; Lowe-Zinola, J.D.; Tsang, J.C.H.; Wcislo, K.; Bevan, K.; Cardus, C.; Duggal, A.; Hossain, S.; McHugh, M.; Scott, M.; Millar, Z.; Hirosue, S.; Ogunmwonyi, I.; Nakakande, D.; Chan, F.; Evans, R.; Gurung, E.; Haughey, B.; Jacob-Ramsdale, B.; Kerr, M.; Lee, J.; McCann, E.; Reid, N.; Kwek, I.; Gaze, H.; Nirmalanantha, A.; Amran, M.A. bin; Foulkes, A.; Jones, N.; Lau, I.S.F.; Hayat, F.; Hodgson, S.; Johnston, R.; Jones, W.; Khan, M.; Linn, T.; Long, S.; Seetharam, P.; Shaman, S.; Smart, B.; Pillai, S.; Khoury, G.; Powell, T.; Maleyko, I.; Sangheli, A.; Ransome, M.; Isse, M.; Aromolaran, O.; Bholah, H.; Anilkumar, A.; Davies, J.; Griffith, J.; Hughes, B.; Islam, Y.; Kidanu, D.; Mushaini, N.; Qamar, I.; Robi
• Date: 2022-01-06
• Journal: BJS Open
• Volume: 6
• Issue: 1
• DOI: doi:10.1093/bjsopen/zrab150
• Link: https://academic.oup.com/bjsopen/article/6/1/zrab150/6530623