Transient left bundle branch block after posture change to the prone position during general anesthesia: A case report

Rationale:The prone position is commonly used in spinal surgery. There have been many studies on hemodynamic changes in the prone position during general anesthesia. We report a rare case of transient left bundle branch block (LBBB) in a prone position.Patient concern:Electrocardiogram (ECG) of a 64-year-old man scheduled for spinal surgery showed normal sinus rhythm change to LBBB after posture change to the prone position.Diagnosis:Twelve lead ECG revealed LBBB. His coronary angio-computed tomography results showed right coronary artery with 30% to 40% stenosis and left circumflex artery with 40% to 50% stenosis. The patient was diagnosed with stable angina and second-degree atrioventricular block of Mobitz type II.Intervention:Nitroglycerin was administered intravenously during surgery. Adequate oxygen was supplied to the patient. After surgery, the patient was prescribed clopidogrel, statins, angiotensin II receptor blocker, and a permanent pacemaker was inserted.Outcome:Surgery was completed without complications. After surgery, the transient LBBB changed to a normal sinus rhythm. The patient did not complain of chest pain or dyspnea.Lesson:The prone position causes significant hemodynamic changes. A high risk of cardiovascular disease may cause ischemic heart disease and ECG changes. Therefore, careful management is necessary.     

Penalized variable selection for accelerated failure time models with random effects

Accelerated failure time (AFT) models allowing for random effects are linear mixed models under the log-transformation of survival time with censoring and describe dependence in correlated survival data. It is well known that the AFT models are useful alternatives to frailty models. To the best of our knowledge, however, there is no literature on variable selection methods for such AFT models. In this paper, we propose a simple but unified variable-selection procedure of fixed effects in the AFT random-effect models using penalized h-likelihood (HL). We consider four penalty functions (ie, least absolute shrinkage and selection operator (LASSO), adaptive LASSO, smoothly clipped absolute deviation (SCAD), and HL). We show that the proposed method can be easily implemented via a slight modification to existing h-likelihood estimation procedures. We thus demonstrate that the proposed method can also be easily extended to AFT models with multilevel (or nested) structures. Simulation studies also show that the procedure using the adaptive LASSO, SCAD, or HL penalty performs well. In particular, we find via the simulation results that the variable selection method with HL penalty provides a higher probability of choosing the true model than other three methods. The usefulness of the new method is illustrated using two actual datasets from multicenter clinical trials.     

Comparison of Cancer Detection Rates Between TRUS-Guided Biopsy and MRI-Targeted Biopsy According to PSA Level in Biopsy-Naive Patients: A Propensity Score Matching Analysis

Background

The purpose of the study was to compare cancer detection rates between 12-core transrectal ultrasound-guided prostate biopsy (TRUS-Bx) and multiparametric magnetic resonance imaging (mpMRI)-guided target prostate biopsy (MRI-TBx) according to prostate-specific antigen (PSA) level in biopsy-naive patients.