Objective The purpose of this study was to determine whether new-onset transient postoperative atrial fibrillation (TPAF) affects mortality rates after abdominal aortic aneurysm (AAA) repair and to identify predictors for the development of TPAF. Methods Patients who underwent open aortic repair or endovascular aortic repair for a principal diagnosis AAA were retrospectively identified using the Healthcare Cost and Utilization Project-State Inpatient Database (Florida) for 2007 to 2011 and monitored longitudinally for 1 year. Inpatient and 1-year mortality rates were compared between those with and without TPAF. TPAF was defined as new-onset atrial fibrillation that developed in the postoperative period and subsequently resolved in patients without a history of atrial fibrillation. Cox proportional hazards models, adjusted for age, gender, comorbidities, rupture status, and repair method, were used to assess 1-year survival. Predictive models were built with preoperative patient factors using Chi-squared Automatic Interaction Detector decision trees and externally validated on patients from California. Results A 3.7% incidence of TPAF was identified among 15,148 patients who underwent AAA repair. The overall mortality rate was 4.3%. The inpatient mortality rate was 12.3% in patients with TPAF vs 4.0% in those without TPAF. In the ruptured setting, the difference in mortality was similar between groups (33.7% vs 39.9%, P = .3). After controlling for age, gender, comorbid disease severity, urgency (ruptured vs nonruptured), and repair method, TPAF was associated with increased 1-year postoperative mortality (hazard ratio, 1.48; P < .001) and postdischarge mortality (hazard ratio, 1.56; P = .028). Chi-squared Automatic Interaction Detector-based models (C statistic = 0.70) were integrated into a Web-based application to predict an individual's probability of developing TPAF at the point of care. Conclusions The development of TPAF is associated with an increased risk of mortality in patients undergoing repair of nonruptured AAA. Predictive modeling can be used to identify those patients at highest risk for developing TPAF and guide interventions to improve outcomes. (J Vasc Surg 2016;63:1240-7.)

Uplift modeling predicts that approximately 40% of patients would benefit from an ASC cleft lip repair. Targeting patients younger than 1 year old, nonsyndromic, with no respiratory or neurologic diagnosis for ASC cleft lip repair, may be a safe and cost-saving endeavor.

No abstract

No abstract

Background: Prostate biopsy (Bx) sampling-based diagnosis of prostate cancer (PCa) has well-described inaccuracy when compared against whole gland analysis upon prostatectomy. Although upgrading of PCa Grade Group (GG) is often described, the occurrence and prognostic implications of downgrading PCa GG at the time of radical prostatectomy (RP) is less understood. Our objective was to evaluate whether downgrading PCa GG at the time of RP was associated with future tumor behavior. Methods:The SEER database was searched from 2010 to 2017 and patients were included if they were assigned pathological grades on both Bx and RP specimen.Patients were stratified into Bx GG > RP GG and Bx GG ≤ RP GG groups, and tumor behavior after treatment was examined. Cox regression was used for the survival analysis.Results: Here, 99,835 patients were included in this study. A total of 18,516 (18.5%) patients encountered downgrading from Bx GG to RP GG. A downgrading of 1 grade occurred in 13,969 (75.4%) of these patients and of 2 or more grades occurred in 4547 (24.6%) patients. A history of higher Bx GG compared with RP GG increased the risk of cancer-specific mortality (CSM) for each given RP GG controlling for age, race, preop prostate-specific antigen level, percentage of positive biopsy cores, and pathologic TNM stages. Specifically, a history of high Bx GG conferred a 45% increased risk of CSM for any given RP GG (hazard ratio = 1.45 95% confidence interval = 1.16-1.82, p < 0.001). Conclusion:A history of higher Bx GG, and hence downgrading at the time of RP, demonstrates some value as a risk-stratification tool for future cancer outcomes after prostatectomy.