Real-world evidence (RWE) and randomized control trial (RCT) data are considered mutually complementary. However, compared with RCT, the outcomes of RWE continue to be assigned lower credibility. It must be emphasized that RWE research is a real-world practice that does not need to be executed as RCT research for it to be reliable. The advantages and disadvantages of RWE must be discerned clearly, and then the proper protocol can be planned from the beginning of the research to secure as many samples as possible. Attention must be paid to privacy protection. Moreover, bias can be reduced meaningfully by reducing the number of dropouts through detailed and meticulous data quality management. RCT research, characterized as having the highest reliability, and RWE research, which reflects the actual clinical aspects, can have a mutually supplementary relationship. Indeed, once this is proven, the two could comprise the most powerful evidence-based research method in medicine.
Background Researchers have suggested models to predict the risk of postoperative AKI (PO-AKI), but an externally validated risk index that can be practically implemented before patients undergo noncardiac surgery is needed.
MethodsWe performed a retrospective observational study of patients without preexisting renal failure who underwent a noncardiac operation ($1 hour) at two tertiary hospitals in Korea. We fitted a proportional odds model for an ordinal outcome consisting of three categories: critical AKI (defined as Kidney Disease Improving Global Outcomes AKI stage $2, post-AKI death, or dialysis within 90 days after surgery), low-stage AKI (defined as PO-AKI events not fulfilling the definition of critical AKI), and no PO-AKI.
ResultsThe study included 51,041 patients in a discovery cohort and 39,764 patients in a validation cohort. The Simple Postoperative AKI Risk (SPARK) index included a summation of the integer scores of the following variables: age, sex, expected surgery duration, emergency operation, diabetes mellitus, use of renin-angiotensin-aldosterone inhibitors, baseline eGFR, dipstick albuminuria hypoalbuminemia, anemia, and hyponatremia. The model calibration plot showed tolerable distribution of observed and predicted probabilities in both cohorts. The discrimination power of the SPARK index was acceptable in both the discovery (c-statistic 0.80) and validation (c-statistic 0.72) cohorts. When four SPARK classes were defined on the basis of the sum of the risk scores, the SPARK index and classes fairly reflected the risks of PO-AKI and critical AKI.Conclusions Clinicians may consider implementing the SPARK index and classifications to stratify patients' PO-AKI risks before performing noncardiac surgery.
Systematic discovery and evaluation of the wide spectrum of ADR signals using standard-based observational electronic health record data across many institutions will affect drug development and use, as well as postmarketing surveillance and regulation.
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