IMPORTANCE: Morphometric assessment has emerged as a strong predictor of postoperative morbidity and mortality. However, a gap exists in translating this knowledge to bedside decision making. We introduced a novel measure of patient-centered surgical risk assessment: morphometric age. OBJECTIVE: To investigate the relationship between morphometric age and posttransplant survival. DATA SOURCES: Medical records of recipients of deceased-donor liver transplants (study population) and kidney donors/trauma patients (morphometric age control population). STUDY SELECTION: A retrospective cohort study of 348 liver transplant patients and 3313 control patients. We assessed medical records for validated morphometric characteristics of aging (psoas area, psoas density, and abdominal aortic calcification). We created a model (stratified by sex) for a morphometric age equation, which we then calculated for the control population using multivariate linear regression modeling (covariates). These models were then applied to the study population to determine each patient's morphometric age. DATA EXTRACTION AND SYNTHESIS: All analytic steps related to measuring morphometric characteristics were obtained via custom algorithms programmed into commercially available software. An independent observer confirmed all algorithm outputs. Trained assistants performed medical record review to obtain patient characteristics. RESULTS: Cox proportional hazards regression model showed that morphometric age was a significant independent predictor of overall mortality (hazard ratio, 1.03 per morphometric year [95% CI, 1.02-1.04; P < .001]) after liver transplant. Chronologic age was not a significant covariate for survival (hazard ratio, 1.02 per year [95% CI, 0.99-1.04; P = .21]). Morphometric age stratified patients at high and low risk for mortality. For example, patients in the middle chronologic age tertile who jumped to the oldest morphometric tertile have worse outcomes than those who jumped to the youngest morphometric tertile (74.4% vs 93.2% survival at 1 year [P = .03]; 45.2% vs 75.0% at 5 years [P = .03]). CONCLUSIONS AND RELEVANCE: Morphometric age correlated with mortality after liver transplant with better discrimination than chronologic age. Assigning a morphometric age to potential liver transplant recipients could improve prediction of postoperative mortality risk.
IMPORTANCE: Morphometric assessment has emerged as a strong predictor of postoperative morbidity and mortality. However, a gap exists in translating this knowledge to bedside decision making. We introduced a novel measure of patient-centered surgical risk assessment: morphometric age. OBJECTIVE: To investigate the relationship between morphometric age and posttransplant survival. DATA SOURCES: Medical records of recipients of deceased-donor liver transplants (study population) and kidney donors/traumapatients (morphometric age control population). STUDY SELECTION: A retrospective cohort study of 348 liver transplant patients and 3313 control patients. We assessed medical records for validated morphometric characteristics of aging (psoas area, psoas density, and abdominal aortic calcification). We created a model (stratified by sex) for a morphometric age equation, which we then calculated for the control population using multivariate linear regression modeling (covariates). These models were then applied to the study population to determine each patient's morphometric age. DATA EXTRACTION AND SYNTHESIS: All analytic steps related to measuring morphometric characteristics were obtained via custom algorithms programmed into commercially available software. An independent observer confirmed all algorithm outputs. Trained assistants performed medical record review to obtain patient characteristics. RESULTS: Cox proportional hazards regression model showed that morphometric age was a significant independent predictor of overall mortality (hazard ratio, 1.03 per morphometric year [95% CI, 1.02-1.04; P < .001]) after liver transplant. Chronologic age was not a significant covariate for survival (hazard ratio, 1.02 per year [95% CI, 0.99-1.04; P = .21]). Morphometric age stratified patients at high and low risk for mortality. For example, patients in the middle chronologic age tertile who jumped to the oldest morphometric tertile have worse outcomes than those who jumped to the youngest morphometric tertile (74.4% vs 93.2% survival at 1 year [P = .03]; 45.2% vs 75.0% at 5 years [P = .03]). CONCLUSIONS AND RELEVANCE: Morphometric age correlated with mortality after liver transplant with better discrimination than chronologic age. Assigning a morphometric age to potential liver transplant recipients could improve prediction of postoperative mortality risk.
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Authors: Peter S Kirk; Jeffrey F Friedman; David C Cron; Michael N Terjimanian; Stewart C Wang; Darrell A Campbell; Michael J Englesbe; Nicole L Werner Journal: J Surg Res Date: 2015-04-30 Impact factor: 2.192
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Authors: Meera N Harhay; Maya K Rao; Kenneth J Woodside; Kirsten L Johansen; Krista L Lentine; Stefan G Tullius; Ronald F Parsons; Tarek Alhamad; Joseph Berger; XingXing S Cheng; Jaqueline Lappin; Raymond Lynch; Sandesh Parajuli; Jane C Tan; Dorry L Segev; Bruce Kaplan; Jon Kobashigawa; Darshana M Dadhania; Mara A McAdams-DeMarco Journal: Nephrol Dial Transplant Date: 2020-07-01 Impact factor: 5.992
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