Dorsal muscle group area and surgical outcomes in liver transplantation.

INTRODUCTION: Better measures of liver transplant risk stratification are needed. Our previous work noted a strong relationship between psoas muscle area and survival following liver transplantation. The dorsal muscle group is easier to measure, but it is unclear if they are also correlated with surgical outcomes. METHODS: Our study population included liver transplant recipients with a preoperative CT scan. Cross-sectional areas of the dorsal muscle group at the T12 vertebral level were measured. The primary outcomes for this study were one- and five-yr mortality and one-yr complications. The relationship between dorsal muscle group area and post-transplantation outcome was assessed using univariate and multivariate techniques. RESULTS: Dorsal muscle group area measurements were strongly associated with psoas area (r = 0.72; p < 0.001). Postoperative outcome was observed from 325 patients. Multivariate logistic regression revealed dorsal muscle group area to be a significant predictor of one-yr mortality (odds ratio [OR] = 0.53, p = 0.001), five-yr mortality (OR = 0.53, p < 0.001), and one-yr complications (OR = 0.67, p = 0.007). CONCLUSION: Larger dorsal muscle group muscle size is associated with improved post-transplantation outcomes. The muscle is easier to measure and may represent a clinically relevant postoperative risk factor.

Management of pediatric urinary tract infections in the emergency department.

Urinary tract infection (UTI) is a common diagnosis in pediatric patients presenting to the emergency department. Although there are several evidence-based guidelines for UTI, they have small variations that can make the workup and management for UTI challenging. This issue reviews the current state of the literature and best practices for the diagnosis and management of UTI in children presenting to the emergency department, including criteria to help the clinician decide whether to test a patient's urine, the best method for urine testing based on the clinical scenario, and how to manage the patient based on the results of urine testing. Also discussed is the best antibiotic choice for specific patients, including the route of administration and duration.

Abdominal aortic calcification and surgical outcomes in patients with no known cardiovascular risk factors.

INTRODUCTION: In the setting of cardiovascular (CV) risk evaluation before major elective surgery, current risk assessment tools are relatively poor for discriminating among patients. For example, patients with clinical CV risk factors can be clearly identified; but among those without appreciated clinical CV risk, there may be a subset with stigmata of CV disease noted during the preoperative radiographic evaluation. Our study evaluated the relationship between abdominal aortic (AA) calcification measured on preoperative computed tomography (CT) imaging and surgical complications in patients undergoing general elective and vascular surgery. We hypothesized that patients with no known CV risk factors but significant aortic calcification on preoperative imaging will have inferior surgical outcomes. METHODS: The study group included 1180 patients from the Michigan Surgical Quality Collaborative (MSQC) database who underwent major general or vascular elective surgery between 2006 and 2009 and who had a CT scan of the abdomen specifically for preoperative planning. AA calcification was measured using novel analytic morphomic techniques and reported as a percentage of the total wall area containing calcification. Patients were divided into cohorts by clinical CV risk and extent of AA calcification. Univariate analysis was used to compare postoperative morbidity between patient cohorts. Multivariate logistic regression analysis was used to compare continuous AA calcification with overall morbidity in patients with no clinical CV risk factors. RESULTS: AA calcification was strongly skewed to the right (53.5% had no AA calcification) and was significantly correlated with age (ρ = 0.43, P < 0.001). Unadjusted univariate analysis of morbidity showed no significant differences in complication rates between patients in the clinical CV risk and significant AA calcification (no known CV risk factor) categories. The clinical CV risk (P < 0.001) and significant AA calcification without CV risk factors (P = 0.009) populations both had significantly more infectious and overall complications than patients with no AA calcification and no clinical CV risk. Multivariate logistic regression confirmed that AA calcification was a significant predictor of morbidity in patients with no clinical CV risk factors (odds ratio = 1.35, P = 0.017). DISCUSSION: This study suggests that AA calcification may be related to progression of CV disease and surgical outcomes. A better understanding of the complex interaction of patient physiology with overall ability to recover from major surgery, using novel approaches such as analytic morphomics, has great potential to improve risk stratification and patient selection.

Morphometric age and mortality after liver transplant.

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.

Surgical site infection and analytic morphometric assessment of body composition in patients undergoing midline laparotomy.

BACKGROUND: Obesity is a known risk factor for surgical site infection (SSI). Our hypothesis is that morphometric measures of midline subcutaneous fat will be associated with increased risk of SSI and will predict SSI better than conventional measures of obesity. STUDY DESIGN: We identified 655 patients who underwent midline laparotomy (2006 to 2009) using the Michigan Surgical Quality Collaborative database. Using novel, semiautomated analytic morphometric techniques, the thickness of subcutaneous fat along the linea alba was measured between T12 and L4. To adjust for variations in patient size, subcutaneous fat was normalized to the distance between the vertebrae and anterior skin. Logistic regression analyses were used to identify factors independently associated with the incidence of SSI. RESULTS: Overall, SSIs were observed in 12.5% (n = 82) of the population. Logistic regression revealed that patients with increased subcutaneous fat had significantly greater odds of developing a superficial incisional SSI (odds ratio [OR] = 1.76 per 10% increase, 95% CI 1.10 to 2.83, p = 0.019). Smoking, steroid use, American Society of Anesthesiologists (ASA) classification, and incision-to-close operative time were also significant independent risk factors for superficial incisional SSI. When comparing subcutaneous fat and body mass index (BMI) as the only model variables, subcutaneous fat significantly improved model predictions of superficial incisional SSI (area under the receiver operating characteristic curve [AUC] 0.60, p = 0.023); BMI did not (AUC 0.52, p = 0.73). CONCLUSIONS: Abdominal subcutaneous fat is an independent predictor of superficial incisional SSI after midline laparotomy. Novel morphometric measures may improve risk stratification and help elucidate the pathophysiology of surgical complications.