Piecewise Analysis of Patient Survival after Onset of AKI CLINICAL JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY Zhang, J. H., Palevsky, P. M., Chertow, G. M., Hartigan, J., O'Connor, T. Z., Guarino, P., Zhou, B. 2013; 8 (10): 1679-1684


AKI affects approximately 2%-7% of hospitalized patients and >35% of critically ill patients. Survival after AKI may be described as having an acute phase (including an initial hyperacute component) followed by a convalescent phase, which may itself have early and late components.Data from the Veterans Affairs/National Institutes of Health Acute Renal Failure Trial Network (ATN) study was used to model mortality risk among patients with dialysis-requiring AKI. This study assumed that the mortality hazard can be described by a piecewise log-linear function with change points. Using an average likelihood method, the authors tested for the number of change points in a piecewise log-linear hazard model. The maximum likelihood approach to locate the change point(s) was then adopted, and associated parameters and standard errors were estimated.There were 1124 ATN participants with follow-up to 1 year. The mortality hazard of AKI decreased over time with inflections in the rate of decrease at days 4, 42, and 148, with the sharpest change at day 42. The daily rate of decline in the log of the hazard for death was 0.220 over the first 4 days, 0.046 between day 4 and day 42, 0.017 between day 42 and day 148, and 0.003 between day 148 and day 365.There appear to be two major phases of mortality risk after AKI: an early phase extending over the first 6 weeks and a late phase from 6 weeks to 1 year. Within the first 42 days, this can be further divided into hyperacute (days 1-4) and acute (days 4-42) phases. After 42 days, there appear to be early (days 42-148) and late (after day 148) convalescent phases. These findings may help to inform the design of AKI clinical trials and assist critical care physicians in prognostic stratification.

View details for DOI 10.2215/CJN.07250712

View details for Web of Science ID 000325268200008