Abdominal Aortic Calcification and Surgical Outcomes in Patients With No Known Cardiovascular Risk Factors

Harbaugh, Calista M.; Terjimanian, Michael N.; Lee, Jay S.; Alawieh, A.Z.; Kowalsky, D.B.; Tishberg, L.M.; Krell, Robert W.; Holcombe, Sven A.; Wang, Stewart C.; Campbell, Darrell A.; Englesbe, Michael J.

doi:10.1097/sla.0b013e31826ddd5f

Cited by 37 publications

(24 citation statements)

References 20 publications

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“…6,[8][9][10]14,15 In the third model (All Morphomics and Labs), we included All Morphomics measurements as well as laboratory data.…”

Section: Developing Predictive Models For Cirrhosismentioning

confidence: 99%

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Use of Analytic Morphomics of Liver, Spleen, and Body Composition to Identify Patients at Risk for Cirrhosis

Krishnamurthy¹,

Zhāng²,

Ethiraj³

et al. 2015

Clinical Gastroenterology and Hepatology

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“…6,[8][9][10]14,15 In the third model (All Morphomics and Labs), we included All Morphomics measurements as well as laboratory data.…”

Section: Developing Predictive Models For Cirrhosismentioning

confidence: 99%

“…2,[8][9][10] Briefly, de-identified Digital Imaging and Communications in Medicine (DICOM) files of the CT scans were loaded into the analytic morphomics server. Image processing and analysis were performed by using a semiautomated high throughput methodology with algorithms programmed in MATLAB (MathWorks Inc, Natick, MA).…”

Section: Analytic Morphomicsmentioning

confidence: 99%

Use of Analytic Morphomics of Liver, Spleen, and Body Composition to Identify Patients at Risk for Cirrhosis

Krishnamurthy¹,

Zhāng²,

Ethiraj³

et al. 2015

Clinical Gastroenterology and Hepatology

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“…All available CT scan Digital Imaging and Communication in Medicine files were analyzed using a semiautomated high throughput methodology with algorithms programmed in MATLAB (MathWorks Inc., Natick, MA) as described previously. (13,(16)(17)(18)(19) Our methodology allowed for accurate anatomic indexing of every individual based on the spine. All algorithms involved a combination of user-defined points, automated image processing, and user editing and verification.…”

Section: Morphomics and Body Compositionmentioning

confidence: 99%

Bone mineral density predicts posttransplant survival among hepatocellular carcinoma liver transplant recipients

Sharma

Parikh

Yu³

et al. 2016

Liver Transpl

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Hepatocellular carcinoma (HCC) is a common indication for liver transplantation (LT). Recent data suggest that body composition features strongly affect post-LT mortality. We examined the impact of body composition on post-LT mortality in patients with HCC. Methods: Data on adult LT recipients who received MELD exception for HCC between 2/29/02-12/31/13 and had CT scan anytime 6 months prior to LT were reviewed (N=118). All available CT scan DICOM (Digital Imaging and Communications in Medicine) files were analyzed using a semiautomated high throughput methodology with algorithms programmed in MATLAB®. Analytic morphomics measurements including dorsal muscle group (DMG) area, visceral and subcutaneous fat and bone mineral density (BMD) were taken at the bottom of the 11th thoracic vertebral level. Results: Thirty-two patients (28%) died during the median follow up of 4.4 years. Number of HCC lesions (HR=2.72; P<0.001), BMD (HR=0.90/HU; P=0.03), pre-LT loco-regional therapy (HR=0.34; P<0.001) and donor age (HR=1.05; P<0.001) were the independent predictors of post-LT mortality. DMG area did not affect post-LT survival. Conclusion: In addition to number of HCC lesions and pre-LT loco-regional therapy, low BMD, a surrogate for bone loss rather than DMG area, was independently associated with post-LT mortality in HCC patients. Bone loss may be an early marker of deconditioning that precedes sarcopenia and may affect transplant outcomes.

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“…To our knowledge, this is the first study to explore the effect of ACI on AL after AR of rectal cancer. In previous studies ACI has been shown to be a predictor of adverse cardiovascular events [31,32], and it is associated with postoperative complications [33] and impairment of renal function [34]. An association between calcification of the thoracic aorta and leakage from cervical anastomoses during oesophagostomy [24] has been recently described [24].…”

Section: Discussionmentioning

confidence: 99%

The Aortic Calcification Index is a risk factor associated with anastomotic leakage after anterior resection of rectal cancer

Shen

Shi

et al. 2019

Colorectal Disease

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Aim Anastomotic leakage (AL) is one of the most feared postoperative complications after anterior resection (AR) of rectal cancer. An adequate blood supply at the anastomotic site is regarded as a prerequisite for healing. We hypothesize that the Aortic Calcification Index (ACI) might reflect the severity of atherosclerosis in patients, and thereby be a risk factor for AL. Method AL was investigated retrospectively according to the definition of the International Study Group of Rectal Cancer in 423 rectal cancer patients who underwent anterior rectal resection. The ACI was measured by preoperative abdominal CT scan. The cross‐section of the aorta was evenly divided into 12 sectors, the number of calcified sectors was counted as the calcification score of each slice. Lasso logistic regression and multivariate regression analysis were used to identify risk factors for AL. Results The percentage of AL after AR was 7.8% (33/423); the mortality of patients who sustained a leak was 3.0% (1/33). Patients with a high ACI had a significantly higher percentage of AL than patients with low ACI (11.2% vs 5.6%, P = 0.04). Among patients with AL, a higher ACI was associated with greater severity of AL (the ACI of patients with grade A leakage, grade B leakage and grade C leakage was 0.5% ± 0.2%, 11.5% ± 9.2% and 24.2% ± 21.7%, respectively; P = 0.008). After risk adjustment, multivariate regression analysis showed that a higher ACI was an independent risk factor for AL (OR 2.391, P = 0.04). Conclusion A high ACI might be an important prognostic factor for AL after AR for rectal cancer. Confirmatory studies are required.

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Abdominal Aortic Calcification and Surgical Outcomes in Patients With No Known Cardiovascular Risk Factors

Cited by 37 publications

References 20 publications

Use of Analytic Morphomics of Liver, Spleen, and Body Composition to Identify Patients at Risk for Cirrhosis

Use of Analytic Morphomics of Liver, Spleen, and Body Composition to Identify Patients at Risk for Cirrhosis

Bone mineral density predicts posttransplant survival among hepatocellular carcinoma liver transplant recipients

The Aortic Calcification Index is a risk factor associated with anastomotic leakage after anterior resection of rectal cancer

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