Necrotizing soft tissue infections - a multicentre, prospective observational study (INFECT) : Protocol and statistical analysis plan

Background: The INFECT project aims to advance our understanding of the pathophysiological mechanisms in necrotizing soft tissue infections (NSTIs). The INFECT observational study is part of the INFECT project with the aim of studying the clinical profile of patients with NSTIs and correlating these to patient-important outcomes. With this protocol and statistical analysis plan we describe the methods used to obtain data and the details of the planned analyses. Methods: The INFECT study is a multicentre, prospective observational cohort study. Patients with NSTIs are enrolled in five Scandinavian hospitals, which are all referral centres for NSTIs. The primary outcomes are the descriptive variables of the patients. Secondary outcomes include identification of factors associated with 90-day mortality and amputation; associations between affected body part, maximum skin defect and Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) score and 90-day mortality; 90-day mortality in patients with and without acute kidney injury (AKI) and LRINEC score of six and above or below six; and association between affected body part at arrival and microbiological findings. Exploratory outcomes include univariate analyses of baseline characteristics associations with 90-day mortality. The statistical analyses will be conducted in accordance with the predefined statistical analysis plan. Conclusion: Necrotizing soft tissue infections result in severe morbidity and mortality. The INFECT study will be the largest prospective study in patients with NSTIs to date and will provide important data for clinicians, researchers and policy makers on the characteristics and outcomes of these patients.</p

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Activated matrix metalloproteinase 8 in serum predicts severity of acute pancreatitis

Objectives: Severe acute pancreatitis (SAP) has high morbidity and mortality but there are no widely accepted predictive biomarkers in clinical use. Matrix metalloproteinases (MMPs) are active in tissue destruction and inflammatory responses. We studied whether serum levels of activated MMP-8 (aMMP8), MMP-9 and their regulators tissue inhibitor of matrix metalloproteinases (TIMP)-1, myeloperoxidase (MPO) and human neutrophil elastase (HNE) could predict the development of SAP. Methods: The study comprised 214 AP patients (revised Atlanta classification: 142 mild, MAP; 54 moderately severe, MSAP; 18 SAP) referred to Helsinki University Hospital. A venous blood sample was taken within 72 h from the onset of symptoms. Serum levels of aMMP-8 were determined using immunofluorometric assay, and those of MMP-9, TIMP-1, MPO and HNE using enzyme-linked immunosorbent assay. AP groups were compared using Jonckheere-Terpstra test and predictive value for SAP was analyzed using receiver operating characteristics (ROC) analysis. Results: Serum aMMP-8 levels were higher in SAP (median 657 ng/ml, interquartile range 542-738 ng/ ml) compared to MSAP (358 ng/ml, 175-564 ng/ml; p < 0.001) and MAP (231 ng/ml, 128-507 ng/ml; p < 0.001). Similar trend was seen with TIMP-1 and MPO. In ROC analysis aMMP-8, MPO and TIMP-1 emerged as potential markers for the development of SAP (areas under ROC curves 0.83, 0.71 and 0.69, respectively). Conclusions: Serum aMMP-8 measured early in the course of AP (within 72 h of symptom onset) predicted the development of SAP. (c) 2021 The Authors. Published by Elsevier B.V. on behalf of IAP and EPC. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Peer reviewe

Fractal-like Distributions over the Rational Numbers in High-throughput Biological and Clinical Data

Recent developments in extracting and processing biological and clinical data are allowing quantitative approaches to studying living systems. High-throughput sequencing, expression profiles, proteomics, and electronic health records are some examples of such technologies. Extracting meaningful information from those technologies requires careful analysis of the large volumes of data they produce. In this note, we present a set of distributions that commonly appear in the analysis of such data. These distributions present some interesting features: they are discontinuous in the rational numbers, but continuous in the irrational numbers, and possess a certain self-similar (fractal-like) structure. The first set of examples which we present here are drawn from a high-throughput sequencing experiment. Here, the self-similar distributions appear as part of the evaluation of the error rate of the sequencing technology and the identification of tumorogenic genomic alterations. The other examples are obtained from risk factor evaluation and analysis of relative disease prevalence and co-mordbidity as these appear in electronic clinical data. The distributions are also relevant to identification of subclonal populations in tumors and the study of the evolution of infectious diseases, and more precisely the study of quasi-species and intrahost diversity of viral populations

Low-dislocation-density GaN from a single growth on a textured substrate

The density of threading dislocations (TD) in GaN grown directly on flat sapphire substrates is typically greater than 10{sup 9}/cm{sup 2}. Such high dislocation densities degrade both the electronic and photonic properties of the material. The density of dislocations can be decreased by orders of magnitude using cantilever epitaxy (CE), which employs prepatterned sapphire substrates to provide reduced-dimension mesa regions for nucleation and etched trenches between them for suspended lateral growth of GaN or AlGaN. The substrate is prepatterned with narrow lines and etched to a depth that permits coalescence of laterally growing III-N nucleated on the mesa surfaces before vertical growth fills the etched trench. Low dislocation densities typical of epitaxial lateral overgrowth (ELO) are obtained in the cantilever regions and the TD density is also reduced up to 1 micrometer from the edge of the support regions

Biomarkers for sepsis: an unfinished journey

none2noneClerico A;Plebani MClerico, A; Plebani, Mari