Minimally Invasive Treatments for Benign Prostatic Hyperplasia: Systematic Review and Network Meta-Analysis

PurposeTo review and to compare indirectly the outcomes of minimally invasive therapies for the treatment of lower urinary tract symptoms secondary to benign prostatic hyperplasia.Materials and MethodsA literature search via Medline and Cochrane Central databases was completed for randomized control studies published between January 2000 to April 2020 for the following therapies: Rezum, Urolift, Aquablation, and prostatic artery embolization (PAE). Data on the following variables were included: International prostate symptom score (IPSS), maximum urinary flow rate, quality of life, and postvoid residual (PVR). Standard mean differences between treatments were compared through a meta-analysis using transurethral resection of the prostate (TURP) to assess differences in treatment effect.ResultsThere was no significant difference in outcomes between therapies for IPSS at the 3, 6, and 12-month follow ups. Although outcomes for Rezum were only available out to 3 months, there were no consistently significant differences in outcomes when comparing Aquablation versus PAE versus Rezum. TURP PVR was significantly better than Urolift at 3, 6, and 12 months. No significant differences in minor or major adverse events were noted.ConclusionAlthough significant differences in outcomes were limited, Aquablation and PAE were the most durable at 12 months. PAE has been well studied on multiple randomized control trials with minimal adverse events while Aquablation has limited high quality data and has been associated with bleeding-related complications.     

Atrial fibrillation after cardiac surgery: A systematic review and meta-analysis

ObjectiveNew-onset postoperative atrial fibrillation (POAF) after cardiac surgery is common, with rates up to 60%. POAF has been associated with early and late stroke, but its association with other cardiovascular outcomes is less known. The objective was to perform a meta-analysis of the studies reporting the association of POAF with perioperative and long-term outcomes in patients with cardiac surgery.MethodsWe performed a systematic review and a meta-analysis of studies that presented outcomes for cardiac surgery on the basis of the presence or absence of POAF. MEDLINE, EMBASE, and the Cochrane Library were assessed; 57 studies (246,340 patients) were selected. Perioperative mortality was the primary outcome. Inverse variance method and random model were performed. Leave-one-out analysis, subgroup analyses, and metaregression were conducted.ResultsPOAF was associated with perioperative mortality (odds ratio [OR], 1.92; 95% confidence interval [CI], 1.58-2.33), perioperative stroke (OR, 2.17; 95% CI, 1.90-2.49), perioperative myocardial infarction (OR, 1.28; 95% CI, 1.06-1.54), perioperative acute renal failure (OR, 2.74; 95% CI, 2.42-3.11), hospital (standardized mean difference, 0.80; 95% CI, 0.53-1.07) and intensive care unit stay (standardized mean difference, 0.55; 95% CI, 0.24-0.86), long-term mortality (incidence rate ratio [IRR], 1.54; 95% CI, 1.40-1.69), long-term stroke (IRR, 1.33; 95% CI, 1.21-1.46), and longstanding persistent atrial fibrillation (IRR, 4.73; 95% CI, 3.36-6.66).ConclusionsThe results suggest that POAF after cardiac surgery is associated with an increased occurrence of most short- and long-term cardiovascular adverse events. However, the causality of this association remains to be established.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

In Vitro-In Vivo Extrapolation and Hepatic Clearance-Dependent Underprediction

Accurately predicting the hepatic clearance of compounds using in vitro to in vivo extrapolation (IVIVE) is crucial within the pharmaceutical industry. However, several groups have recently highlighted the serious error in the process. Although empirical or regression-based scaling factors may be used to mitigate the common underprediction, they provide unsatisfying solutions because the reasoning behind the underlying error has yet to be determined. One previously noted trend was intrinsic clearance-dependent underprediction, highlighting the limitations of current in vitro systems. When applying these generated in vitro intrinsic clearance values during drug development and making first-in-human dose predictions for new chemical entities though, hepatic clearance is the parameter that must be estimated using a model of hepatic disposition, such as the well-stirred model. Here, we examine error across hepatic clearance ranges and find a similar hepatic clearance-dependent trend, with high clearance compounds not predicted to be so, demonstrating another gap in the field.     

Inactivated influenza vaccine formulated with single-stranded RNA-based adjuvant confers mucosal immunity and cross-protection against influenza virus infection

Influenza vaccination is considered the most valuable means to prevent and control seasonal influenza infections, which causes various clinical symptoms, ranging from mild cough and fever to even death. Among various influenza vaccine types, the inactivated subunit type is known to provide improved safety with reduced reactogenicity. However, there are some drawbacks associated with inactivated subunit type vaccines, with the main ones being its low immunogenicity and the induction of Th2-biased immune responses. In this study, we investigated the role of a single-stranded RNA (ssRNA) derived from the intergenic region in the internal ribosome entry site of the Cricket paralysis virus as an adjuvant rather than the universal vaccine for a seasonal inactivated subunit influenza vaccine. The ssRNA adjuvant stimulated not only well-balanced cellular (indicated by IgG2a, IFN-γ, IL-2, and TNF-α) and humoral (indicated by IgG1 and IL-4) immune responses but also a mucosal immune response (indicated by IgA), a key protector against respiratory virus infections. It also increases the HI titer, the surrogate marker of influenza vaccine efficacy. Furthermore, ssRNA adjuvant confers cross-protective immune responses against heterologous influenza virus infection while promoting enhanced viral clearance. Moreover, ssRNA adjuvant increases the number of memory CD4⁺ and CD8⁺ T cells, which can be expected to induce long-term immune responses. Therefore, this ssRNA-adjuvanted seasonal inactivated subunit influenza vaccine might be the best influenza vaccine generating robust humoral and cellular immune responses and conferring cross-protective and long-term immunity.     

Real-time refinement of subthalamic nucleus targeting using Bayesian decision-making on the root mean square measure.

The subthalamic nucleus (STN) is a major target for treatment of advanced Parkinson's disease patients undergoing deep brain stimulation surgery. Microelectrode recording (MER) is used in many cases to identify the target nucleus. A real-time procedure for identifying the entry and exit points of the STN would improve the outcome of this targeting procedure. We used the normalized root mean square (NRMS) of a short (5 seconds) MER sampled signal and the estimated anatomical distance to target (EDT) as the basis for this procedure. Electrode tip location was defined intraoperatively by an expert neurophysiologist to be before, within, or after the STN. Data from 46 trajectories of 27 patients were used to calculate the Bayesian posterior probability of being in each of these locations, given RMS-EDT pair values. We tested our predictions on each trajectory using a bootstrapping technique, with the rest of the trajectories serving as a training set and found the error in predicting the STN entry to be (mean +/- SD) 0.18 +/- 0.84, and 0.50 +/- 0.59 mm for STN exit point, which yields a 0.30 +/- 0.28 mm deviation from the expert's target center. The simplicity and computational ease of RMS calculation, its spike sorting-independent nature and tolerance to electrode parameters of this Bayesian predictor, can lead directly to the development of a fully automated intraoperative physiological procedure for the refinement of imaging estimates of STN borders.