Minjae Kim1,2, Melanie M Wall3, Ravi P Kiran4, Guohua Li5,6. 1. Department of Anesthesiology, Columbia University Medical Center, 622 West 168th Street, PH 5, Suite 505C, New York, NY, 10032, USA. mk2767@cumc.columbia.edu. 2. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA. mk2767@cumc.columbia.edu. 3. Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA. 4. Division of Colorectal Surgery, Department of Surgery, Columbia University Medical Center, New York, NY, USA. 5. Department of Anesthesiology, Columbia University Medical Center, 622 West 168th Street, PH 5, Suite 505C, New York, NY, 10032, USA. 6. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
Abstract
PURPOSE: Risk stratification for postoperative acute kidney injury (AKI) evaluates a patient's risk for developing this complication using preoperative characteristics. Nevertheless, it is unclear if these characteristics are also associated with mortality in patients who actually develop this complication, so we aimed to determine these associations. METHODS: The 2011-15 American College of Surgeons National Surgical Quality Improvement Program was used to obtain a historical, observational cohort of high-risk intraabdominal general surgery patients with AKI, which was defined as an increase in serum creatinine > 177 µmol·L-1 (2 mg·dL-1) above the preoperative value and/or the need for dialysis. Latent class analysis, a model-based clustering technique, classified patients based on preoperative comorbidities and risk factors. The associations between the latent classes and the time course of AKI development and mortality after AKI were assessed with the Kruskall-Wallis test and Cox models. RESULTS: A seven-class model was fit on 3,939 observations (derivation cohort). Two patterns for the time course of AKI diagnosis emerged: an "early" group (median [interquartile range] day of diagnosis 3 [1-10]) and a "late" group (day 9 [3-16]). Three patterns of survival after AKI diagnosis were identified (groups A-C). Compared with the group with the lowest mortality risk (group A), the hazard ratios (95% confidence intervals) for 30-day mortality were 1.79 [1.55 to 2.08] for group B and 3.55 [3.06 to 4.13] for group C. These differences in relative hazard were similar after adjusting for the postoperative day of AKI diagnosis and surgical procedure category. CONCLUSIONS: Among patients with AKI after high-risk general surgery, the preoperative comorbid state is associated with the time course of and survival after AKI. This knowledge can stratify mortality risk in patients who develop postoperative AKI.
PURPOSE: Risk stratification for postoperative acute kidney injury (AKI) evaluates a patient's risk for developing this complication using preoperative characteristics. Nevertheless, it is unclear if these characteristics are also associated with mortality in patients who actually develop this complication, so we aimed to determine these associations. METHODS: The 2011-15 American College of Surgeons National Surgical Quality Improvement Program was used to obtain a historical, observational cohort of high-risk intraabdominal general surgery patients with AKI, which was defined as an increase in serum creatinine > 177 µmol·L-1 (2 mg·dL-1) above the preoperative value and/or the need for dialysis. Latent class analysis, a model-based clustering technique, classified patients based on preoperative comorbidities and risk factors. The associations between the latent classes and the time course of AKI development and mortality after AKI were assessed with the Kruskall-Wallis test and Cox models. RESULTS: A seven-class model was fit on 3,939 observations (derivation cohort). Two patterns for the time course of AKI diagnosis emerged: an "early" group (median [interquartile range] day of diagnosis 3 [1-10]) and a "late" group (day 9 [3-16]). Three patterns of survival after AKI diagnosis were identified (groups A-C). Compared with the group with the lowest mortality risk (group A), the hazard ratios (95% confidence intervals) for 30-day mortality were 1.79 [1.55 to 2.08] for group B and 3.55 [3.06 to 4.13] for group C. These differences in relative hazard were similar after adjusting for the postoperative day of AKI diagnosis and surgical procedure category. CONCLUSIONS: Among patients with AKI after high-risk general surgery, the preoperative comorbid state is associated with the time course of and survival after AKI. This knowledge can stratify mortality risk in patients who develop postoperative AKI.
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