Do we need a patient surgical class categorization similar to the American Society of Anesthesiologists (ASA) grade?

We aim to enhance the reporting of complications in surgical operations by establishing a classification for patient complexity. Current comorbidity assessment tools are insufficient due to their reliance on physiological parameters. The proposed patient surgical class category (PSCC) aims to address these limitations and enhance results by incorporating relevant aspects of a patient's surgical history.

Molecular Landscape of Pelvic Organ Prolapse Provides Insights into Disease Etiology.

Pelvic organ prolapse (POP) represents a major health care burden in women, but its underlying pathophysiological mechanisms have not been elucidated. We first used a case-control design to perform an exome chip study in 526 women with POP and 960 control women to identify single nucleotide variants (SNVs) associated with the disease. We then integrated the functional interactions between the POP candidate proteins derived from the exome chip study and other POP candidate molecules into a molecular landscape.

A Systematic Review of the Impact of Surgeon and Hospital Caseload Volume on Oncological and Nononcological Outcomes After Radical Prostatectomy for Nonmetastatic Prostate Cancer.

Context: The impact of surgeon and hospital volume on outcomes after radical prostatectomy (RP) for localised prostate cancer (PCa) remains unknown.

Objective: To perform a systematic review on the association between surgeon or hospital volume and oncological and nononcological outcomes following RP for PCa.

Evidence Acquisition: Medline, Medline In-Process, Embase, and the Cochrane Central Register of Controlled Trials were searched.

Two-Stage Testing for Epistasis: Screening and Verification.

Undiscovered gene-to-gene interaction (epistasis) is a possible explanation for the "missing heritability" of complex traits and diseases. On a genome-wide scale, screening for epistatic effects among all possible pairs of genetic markers faces two main complications. Firstly, the classical statistical methods for modeling epistasis are computationally very expensive, which makes them impractical on such large scale.

Intraoperative Adverse Incident Classification (EAUiaiC) by the European Association of Urology ad hoc Complications Guidelines Panel.

Background: A surgical adverse incident (AI) is defined as any deviation from the normal operative course. Current complication-grading systems mostly focus on postoperative events.

Objective: To propose an intraoperative AI classification (EAUiaiC) to facilitate reporting.

Prognostic Value of Biochemical Recurrence Following Treatment with Curative Intent for Prostate Cancer: A Systematic Review.

Context: In men with prostate cancer (PCa) treated with curative intent, controversy exists regarding the impact of biochemical recurrence (BCR) on oncological outcomes.

Objective: To perform a systematic review of the existing literature on BCR after treatment with curative intent for nonmetastatic PCa. Objective 1 is to investigate whether oncological outcomes differ between patients with or without BCR.

Gaining power in multiple testing of interval hypotheses via conditionalization.

In this article, we introduce a novel procedure for improving power of multiple testing procedures (MTPs) of interval hypotheses. When testing interval hypotheses the null hypothesis $P$-values tend to be stochastically larger than standard uniform if the true parameter is in the interior of the null hypothesis. The new procedure starts with a set of $P$-values and discards those with values above a certain pre-selected threshold, while the rest are corrected (scaled-up) by the value of the threshold.

Robin Hood: A cost-efficient two-stage approach to large-scale simultaneous inference with non-homogeneous sparse effects.

A classical approach to experimental design in many scientific fields is to first gather all of the data and then analyze it in a single analysis. It has been recognized that in many areas such practice leaves substantial room for improvement in terms of the researcher's ability to identify relevant effects, in terms of cost efficiency, or both. Considerable attention has been paid in recent years to multi-stage designs, in which the user alternates between data collection and analysis and thereby sequentially reduces the size of the problem.

A powerful and efficient two-stage method for detecting gene-to-gene interactions in GWAS.

For over a decade functional gene-to-gene interaction (epistasis) has been suspected to be a determinant in the "missing heritability" of complex traits. However, searching for epistasis on the genome-wide scale has been challenging due to the prohibitively large number of tests which result in a serious loss of statistical power as well as computational challenges. In this article, we propose a two-stage method applicable to existing case-control data sets, which aims to lessen both of these problems by pre-assessing whether a candidate pair of genetic loci is involved in epistasis before it is actually tested for interaction with respect to a complex phenotype.