The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Abstract

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. Clinical trial registration: NCT03044899.

South African Paediatric Surgical Outcomes Study: a 14-day prospective, observational cohort study of paediatric surgical patients

“…37 Finally, the differences between risk factors, type, and frequency of perioperative complications between South Africa and the literature from HICs suggest that further prospective studies are needed from LMICs, which may result in the development of a risk prediction tool specific for the LMIC paediatric surgical environments. 38 Only once we understand the risk factors for paediatric surgical morbidity in this environment will we be able to target interventions with potential therapeutic benefit.…”

The African Surgical OutcomeS-2 (ASOS-2) Pilot Trial, a mixed-methods implementation study

“…All patients who had surgery from Monday to Friday of the recruitment week, were risk stratified using the ASOS Surgical Risk Calculator at the time of surgery by the anaesthetist. 5 Any patient with a score of 10 or more, was considered high-risk, and would require increased postoperative surveillance. The pilot trial ran for one week from 7 am on the Monday, to 6.59 am on the following Monday.…”

“…The ASOS Surgical Risk Calculator was developed from the first ASOS data and recently published elsewhere. 5 The primary outcome of the ASOS-2 Trial is inhospital mortality, censored at 30 days.…”

“…5 Patients scoring 10 or more points, were considered high-risk, as they have a predicted incidence of severe complications and death above the average for the ASOS cohort. 5 The protocol required that these patients receive increased postoperative surveillance which included the following components: i) admission to a higher care ward than had been planned prior to risk stratification, ii) an increase in the frequency of postoperative nursing observations, iii) ensuring that the patient is placed in view of the nursing station, and not in a remote location in the ward, or iv) allowing family members to stay with the patient in the ward. The care givers were encouraged to provide as many of the components of the intervention, for as long as possible to the high-risk patients.…”

Implementing risk calculators: time for the Trojan Horse?

“…The authors demonstrate how our colour-deficient colleagues perceive the various class labels, and suggest that the inability to properly perceive accurate colours of the labels might increase errors by these anaesthetists. 1 The authors' recognition of the importance of design for the widest range of users should be applauded, as relatively common traits such as handedness and colour perception have traditionally been omitted in the design of safety interventions. We consider this an opportunity to widen the discussion about human errors, safety systems, and the evaluation of interventions in complex adaptive environments such as healthcare.…”