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... Show moreBackground 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). Show less
Curtin, D.; Dahly, D.L.; Smeden, M. van; O'Donnell, D.P.; Doyle, D.; Gallagher, P.; O'Mahony, D. 2019
OBJECTIVES Accurate prognostic information can enable patients and physicians to make better healthcare decisions. The Hospital-patient One-year Mortality Risk (HOMR) model accurately predicted... Show moreOBJECTIVES Accurate prognostic information can enable patients and physicians to make better healthcare decisions. The Hospital-patient One-year Mortality Risk (HOMR) model accurately predicted mortality risk (concordance [C] statistic = .92) in adult hospitalized patients in a recent study in North America. We evaluated the performance of the HOMR model in a population of older inpatients in a large teaching hospital in Ireland. DESIGN Retrospective cohort study. SETTING Acute hospital. PARTICIPANTS Patients aged 65 years or older cared for by inpatient geriatric medicine services from January 1, 2013, to March 6, 2015 (n = 1654). After excluding those who died during the index hospitalization (n = 206) and those with missing data (n = 39), the analytical sample included 1409 patients. MEASUREMENTS Administrative data and information abstracted from hospital discharge reports were used to determine covariate values for each patient. One-year mortality was determined from the hospital information system, local registries, or by contacting the patient's general practitioner. The linear predictor for each patient was calculated, and performance of the model was evaluated in terms of its overall performance, discrimination, and calibration. Recalibrated and revised models were also estimated and evaluated. RESULTS One-year mortality rate after hospital discharge in this patient cohort was 18.6%. The unadjusted HOMR model had good discrimination (C statistic = .78; 95% confidence interval = .76-.81) but was poorly calibrated and consistently overestimated mortality prediction. The model's performance was modestly improved by recalibration and revision (optimism corrected C statistic = .8). CONCLUSION The superior discriminative performance of the HOMR model reported previously was substantially attenuated in its application to our cohort of older hospitalized patients, who represent a specific subset of the original derivation cohort. Updating methods improved its performance in our cohort, but further validation, refinement, and clinical impact studies are required before use in routine clinical practice. J Am Geriatr Soc 1-6, 2019. Show less
Mann, G.; Breitling, F.; Vocks, C.; Aurass, H.; Steinmetz, M.; Strassmeier, K.G.; ... ; Zensus, J.A. 2018
