University of Zurich

About: University of Zurich is a education organization based out in Zurich, Switzerland. It is known for research contribution in the topics: Population & Transplantation. The organization has 50842 authors who have published 124042 publications receiving 5304521 citations. The organization is also known as: UZH & Uni Zurich.

Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey.

Abstract: Growing demand for health care, rising costs, constrained resources, and evidence of variations in clinical practice have triggered interest in measuring and improving the quality of health care delivery. For a valuable quality assessment, relevant data on outcome must be obtained in a standardized and reproducible manner to allow comparison among different centers, between different therapies and within a center over time.1–3 Objective and reliable outcome data are increasingly requested by patients and payers (government or private insurance) to assess quality and costs of health care. Moreover, health policy makers point out that the availability of comparative data on individual hospital's and physician's performance represents a powerful market force, which may contribute to limit the costs of health care while improving quality.4 Conclusive assessments of surgical procedures remain limited by the lack of consensus on how to define complications and to stratify them by severity.1,5–8 In 1992, we proposed general principles to classify complications of surgery based on a therapy-oriented, 4-level severity grading.1 Subsequently, the severity grading was refined and applied to compare the results of laparoscopic versus open cholecystectomy9 and liver transplantation.10 This classification has also been used by others11–13 and was recently suggested to serve as the basis to assess the outcome of living related liver transplantation in the United States (J. Trotter, personal communication). However, the classification system has not yet been widely used in the surgical literature. The strength of the previous classification relied on the principle of grading complications based on the therapy used to treat the complication. This approach allows identification of most complications and prevents down-rating of major negative outcomes. This is particularly important in retrospective analyses. However, we felt that modifications were necessary, particularly in grading life-threatening complications and long-term disability due to a complication. We also felt that the duration of the hospital stay can no longer be used as a criterion to grade complications. Although definitions of negative outcomes rely to a large extend on subjective “value” appraisals, the grading system must be tested in a large cohort of patients. Finally, a classification is useful only if widely accepted and applied throughout different countries and surgical cultures. Such a validation was not done with the previous classification. Therefore, the aim of the current study was 3-fold: first, to propose an improved classification of surgical complications based on our experience gained with the previous classification1; second, to test this classification in a large cohort of patients who underwent general surgery; and third, to assess the reproducibility and acceptability of the classification through an international survey.

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

The 2007 WHO Classification of Tumours of the Central Nervous System

Abstract: The fourth edition of the World Health Organization (WHO) classification of tumours of the central nervous system, published in 2007, lists several new entities, including angiocentric glioma, papillary glioneuronal tumour, rosette-forming glioneuronal tumour of the fourth ventricle, papillary tumour of the pineal region, pituicytoma and spindle cell oncocytoma of the adenohypophysis. Histological variants were added if there was evidence of a different age distribution, location, genetic profile or clinical behaviour; these included pilomyxoid astrocytoma, anaplastic medulloblastoma and medulloblastoma with extensive nodularity. The WHO grading scheme and the sections on genetic profiles were updated and the rhabdoid tumour predisposition syndrome was added to the list of familial tumour syndromes typically involving the nervous system. As in the previous, 2000 edition of the WHO ‘Blue Book’, the classification is accompanied by a concise commentary on clinico-pathological characteristics of each tumour type. The 2007 WHO classification is based on the consensus of an international Working Group of 25 pathologists and geneticists, as well as contributions from more than 70 international experts overall, and is presented as the standard for the definition of brain tumours to the clinical oncology and cancer research communities world-wide.

The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary.

Abstract: The 2016 World Health Organization Classification of Tumors of the Central Nervous System is both a conceptual and practical advance over its 2007 predecessor. For the first time, the WHO classification of CNS tumors uses molecular parameters in addition to histology to define many tumor entities, thus formulating a concept for how CNS tumor diagnoses should be structured in the molecular era. As such, the 2016 CNS WHO presents major restructuring of the diffuse gliomas, medulloblastomas and other embryonal tumors, and incorporates new entities that are defined by both histology and molecular features, including glioblastoma, IDH-wildtype and glioblastoma, IDH-mutant; diffuse midline glioma, H3 K27M-mutant; RELA fusion-positive ependymoma; medulloblastoma, WNT-activated and medulloblastoma, SHH-activated; and embryonal tumour with multilayered rosettes, C19MC-altered. The 2016 edition has added newly recognized neoplasms, and has deleted some entities, variants and patterns that no longer have diagnostic and/or biological relevance. Other notable changes include the addition of brain invasion as a criterion for atypical meningioma and the introduction of a soft tissue-type grading system for the now combined entity of solitary fibrous tumor / hemangiopericytoma-a departure from the manner by which other CNS tumors are graded. Overall, it is hoped that the 2016 CNS WHO will facilitate clinical, experimental and epidemiological studies that will lead to improvements in the lives of patients with brain tumors.