Native T1 Mapping, Extracellular Volume Mapping, and Late Gadolinium Enhancement in Cardiac Amyloidosis: A Meta-Analysis.

OBJECTIVES: This study aimed to compare the diagnostic and prognostic performance of native T1 mapping (T1), extracellular volume (ECV) mapping, and late gadolinium enhancement (LGE) imaging for evaluating cardiac amyloidosis (CA). BACKGROUND: CA is a progressive infiltrative process in the extracellular space that is often underdiagnosed and holds a poor prognosis. Cardiac magnetic resonance (CMR) offers novel techniques for detecting and quantifying the disease burden of CA. METHODS: We searched PubMed for published studies using native T1, ECV, or LGE to diagnose and prognosticate CA. A total of 18 diagnostic (n = 2,015) and 13 prognostic studies (n = 1,483) were included for analysis. Pooled sensitivities, specificities, diagnostic odds ratios (DORs) of all diagnostic tests were assessed by bivariate analysis. Pooled hazard ratios (HRs) for mortality for the 3 techniques were determined. RESULTS: Bivariate comparison showed that ECV (DOR: 84.6; 95% confidence interval [CI]: 30.3 to 236.2) had a significantly higher DOR for CA than LGE (DOR: 20.1; 95% CI: 9.1 to 44.1; p = 0.03 vs. ECV). There was no significant difference between LGE and native T1 for sensitivity, specificity, and DOR. HR was significantly higher for ECV (HR: 4.27; 95% CI: 2.87 to 6.37) compared with LGE (HR: 2.60; 95% CI: 1.90 to 3.56; p = 0.03 vs. ECV) and native T1 (HR: 2.04; 95% CI: 1.24 to 3.37; p = 0.01 vs. ECV). CONCLUSIONS: ECV demonstrates a higher diagnostic OR for assessing cardiac amyloid than LGE and a higher HR for adverse events compared with LGE and native T1. In addition, native T1 showed similar sensitivity and specificity as ECV and LGE without requiring contrast material. Although limited by study heterogeneity, this meta-analysis suggests that ECV provides high diagnostic and prognostic utility for the assessment of cardiac amyloidosis.

Blood transfusion is an independent predictor of morbidity and mortality after hepatectomy.

BACKGROUND: Previous studies have indicated that blood transfusion is associated with increased risk of worse outcomes among patients selected for hepatectomy. However, the independent effect of transfusion has not been confirmed. We hypothesize that blood transfusion is an independent factor that affects outcomes in patients undergoing hepatectomy. MATERIALS AND METHODS: Patients at tertiary care center who underwent hepatectomy between 2006 and 2013 were identified and linked with the American College of Surgeons National Surgical Quality Improvement Program PUF data set. Multivariable logistic regression analysis was used to estimate the effect of blood transfusion on 30-d mortality and morbidity, adjusted for differences in extent of resection and estimated probabilities of morbidity and mortality. RESULTS: Among 522 patients in the study, 48 (9.2%) patients required perioperative blood transfusion within 72 h of resection, and 172 (33%) underwent major hepatectomy. Indications for hepatectomy included metastatic neoplasm (n = 229, 44%), primary hepatic neoplasm (n = 108, 21%), primary extra-hepatic biliary neoplasm (n = 23, 4%), and nonmalignant indications (n = 162, 31%). Eighty-eight (17%) patients had a postoperative morbidity. Blood transfusion was significantly associated with postoperative morbidity (odds ratio [OR] = 4.18, 95% CI = 2.18-8.02, P = 0.0001) and mortality (OR = 14.5, 95% CI = 3.08-67.8, P = 001), after adjustment for the concurrent effect of National Surgical Quality Improvement Program estimated probability of morbidity (OR = 1.15, 95% CI = 0.11-12.2, P = 0.042). The extent of resection was not significantly associated with morbidity (OR = 1.30, 95% CI, 0.74-2.28, P = 0.366) or mortality (OR = 1.14, 95% CI = 0.24-5.50, P = 0.870). CONCLUSIONS: Blood transfusion is a highly statistically significant independent predictor of morbidity and mortality after hepatectomy. Judicious use of perioperative transfusion is indicated in patients with benign and malignant indications for liver resection.

The impact of chronic liver disease on the risk assessment of ACS NSQIP morbidity and mortality after hepatic resection.

BACKGROUND: The American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) risk-adjustment model for patients who require hepatic resection does not include metrics of underlying chronic liver disease. The applicability of the current risk adjustment model is under debate. This study aims to assess the impact of chronic liver disease on the ACS NSQIP estimates of postoperative morbidity and mortality. STUDY DESIGN: This retrospective cohort study included all cases of hepatic resection at our quaternary referral institution between 2006 and 2013. Metrics of chronic liver disease were abstracted and linked with the ACS NSQIP risk-adjustment model estimated probabilities of morbidity and mortality for each case. Sequential general linear models were used to estimate differences in ACS NSQIP probabilities of morbidity and mortality associated with measures of underlying chronic liver disease. RESULTS: A total of 522 hepatic resections were performed during the study period. The patient cohort included 91 patients with fibrosis (17%) and 38 patients with cirrhosis (7%). The mean ACS NSQIP estimated probability of morbidity was 0.24 ± 0.11 and probability of mortality was 0.02 ± 0.02. Fibrosis was associated with increased probability of morbidity (0.26 ± 0.11; P = .019); cirrhosis was also associated with increased probability of morbidity (0.27 ± 0.10; P = .059). Parenchymal liver disease was not associated with increased probability of mortality (all P ≥ .62). Increased probabilities of mortality were associated with diagnosis and extent of resection (both P < .001). CONCLUSIONS: In patients selected for hepatectomy, metrics of chronic liver disease were associated with differences in ACS NSQIP estimated probability of morbidity. Incorporation of metrics of chronic liver disease into the ACS NSQIP targeted hepatectomy modules should improve estimates of risk after hepatic resection.