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Role of sarcopenia and risk assessment for patients undergoing thoracoabdominal aortic surgery
Muhammad A Munir1, Ammar A. Javed1, Muhammad A Faateh2, Ching T. Lin1, Ying W. Lum1, Caitlin W. Hicks1, Christopher Abularrage1, Elliot K. Fishman1, James H. Black H. Black1
1Johns Hopkins Hospital, Baltimore, MD;2Beth Israel Deaconess Medical Center, Boston, MA

Role of sarcopenia and risk assessment for patients undergoing thoracoabdominal aortic surgery Muhammad A. Munir MD1, Ammar A. Javed MD1, Muhammad Faateh MD3, Ching T. Lin MD2, Ying W. Lum MD MPH FACS1, Caitlin W. Hicks MD MS1, Christopher Abularrage MD1, Elliot K. Fishman MD2, James H. Black MD FACS11Division of Vascular Surgery and Endovascular Therapy, Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA2Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA3Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA
Introduction:Management of thoracoabdominal aortic aneurysms (TAAA) presents a challenge for older patients. The rate of postoperative complications remains high, and better tools are required for patient selection to minimize mortality and morbidity. Recent reports have suggested that sarcopenia may be a predictor of patient outcomes. The aim of the current study was to assess the association between sarcopenia and patient outcomes, in patient undergoing TAAA repair.
Methods:Patients undergoing TAAA repair at Johns Hopkins between 2007 and 2019 were included. Sarcopenia was determined using the volume of the psoas muscle index (PMI) on CT imaging. Statistical analysis used Youden's index to identify the optimal cutoff to predict in-hospital mortality. A new predictive model based on factors identified using backward selection (sarcopenia and sex) was developed and its ability to predict in-hospital mortality and complications was compared to the VQI risk calculator (VQI) and VQI risk score class (VQI-class).
Results:A total of 139 patients were included in the study. The mean age was 59.2 18.4 years and 55 (39.6%) patients were male. Seven (5.0%) patients experienced in-hospital death while 98 (70.5%) experienced a post-operative complication. The optimum cutoff for PMI was found to be 8.8 and on logistic regression sarcopenia and sex were associated with in-hospital mortality. The resulting model performed equally well in predicting in-hospital mortality as compared to VQI (AUC: 0.78 vs. 0.61, p=0.190) and better than the VQI-class (0.78 vs. 0.55, p=0.029). As for postoperative complications, similar performance was observed between the proposed model and VQI (AUC: 0.57 vs. 0.66, p=0.227) and the VQI-class (AUC: 0.78 vs. 0.0.61, p=0.190).
Conclusion: Patients undergoing intervention for TAAA are at high risk of mortality and morbidity. The proposed model based on minimal variables performs equally well in predicting risk of postoperative morbidity as compared to VQI and VQI-class, while achieving better prediction of in-hospital mortality as compared to VQI-class category. These findings suggest that sarcopenia assessment may improve patient selection for TAAA repair.
Sarcopenia + Sex vs. VQI (continuous) - In-hospital mortality P=0.190
Sarcopenia + Sex vs. VQI (score) - In-hospital mortalityP=0.029
Sarcopenia + Sex vs. VQI (continuous) Complications P=0.227
Sarcopenia + Sex vs. VQI (score) - Complications P=0.443

Table. Clinicopathological features stratified by PMI (sarcopenia)
VariablesPMI <8.8N = 52 (37.4)PMI ≥8.8N=87 (62.6)P-value
Age, ≥75 years4 (12.5)19 (17.9)0.471
Sex, Female5 (15.6)79 (73.8)>0.001
Race, White21 (65.6)74 (69.2)0.279
Smoking history20 (62.5)65 (60.8)0.858
Diabetes4 (12.5)14 (13.1)0.931
CAD6 (18.8)20 (18.6)0.994
HTN19 (59.4)74 (69.8)0.270
CHF5 (15.6)18 (16.9)0.857
Cardiac surgery7 (21.9)13 (12.2)0.169
COPD10 (31.3)19 (17.8)0.099
Neurological disease9 (28.1)17 (16.9)0.119
CKD6 (18.8)21 (19.6)0.912
PAD4 (12.5)17 (15.9)0.639
Connective tissue disorder9 (28.1)13 (12.2)0.030
Endovascular repair9 (28.1)37 (34.6)0.496
Prior repair15 (46.9)48 (44.9)0.841

Table 2. Performance of proposed model (sarcopenia + Sex) and VQI/ VQI-score in predicting patient outcomes
Study outcomeModel 1Model 2AUCP-value
In-hospital mortalitysarcopenia + SexVQI0.78 vs 0.610.190
In-hospital mortalitysarcopenia + SexVQI-score0.78 vs. 0.550.029
Any postoperative complicationsarcopenia + SexVQI0.57 vs. 0.660.227
Any postoperative complicationsarcopenia + SexVQI-score0.57 vs. 0.620.443

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