11. |
- Gero, D., et al.
(författare)
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Defining Global Benchmarks in Bariatric Surgery A Retrospective Multicenter Analysis of Minimally Invasive Roux-en-Y Gastric Bypass and Sleeve Gastrectomy
- 2019
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Ingår i: Annals of Surgery. - : Ovid Technologies (Wolters Kluwer Health). - 0003-4932 .- 1528-1140. ; 270:5, s. 859-867
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To define "best possible'' outcomes for bariatric surgery (BS)(Roux-en-Y gastric bypass [RYGB] and sleeve gastrectomy [SG]). Background: Reference values for optimal surgical outcomes in welldefined low-risk bariatric patients have not been established so far. Consequently, outcome comparison across centers and over time is impeded by heterogeneity in case-mix. Methods: Out of 39,424 elective BS performed in 19 high-volume academic centers from 3 continents between June 2012 and May 2017, we identified 4120 RYGB and 1457 SG low-risk cases defined by absence of previous abdominal surgery, concomitant procedures, diabetes mellitus, sleep apnea, cardiopathy, renal insufficiency, inflammatory bowel disease, immunosuppression, anticoagulation, BMI>50 kg/m(2) and age>65 years. We chose clinically relevant endpoints covering the intra- and postoperative course. Complications were graded by severity using the comprehensive complication index. Benchmark values were defined as the 75th percentile of the participating centers' median values for respective quality indicators. Results: Patients were mainly females (78%), aged 38+/-11 years, with a baseline BMI 40.8 +/- 5.8 kg/m(2). Over 90 days, 7.2% of RYGB and 6.2% of SG patients presented at least 1 complication and no patients died (mortality in nonbenchmark cases: 0.06%). The most frequent reasons for readmission after 90-days following both procedures were symptomatic cholelithiasis and abdominal pain of unknown origin. Benchmark values for both RYGB and SG at 90-days postoperatively were 5.5% Clavien-Dindo grade >= IIIa complication rate, 5.5% readmission rate, and comprehensive complication index <= 33.73 in the subgroup of patients presenting at least 1 grade >= II complication. Conclusion: Benchmark cutoffs targeting perioperative outcomes in BS offer a new tool in surgical quality-metrics and may be implemented in qualityimprovement cycle. ClinicalTrials.gov Identifier NCT03440138
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12. |
- Gloriam, David E., et al.
(författare)
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A Community Standard Format for the Representation of Protein Affinity Reagents
- 2010
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Ingår i: Molecular & Cellular Proteomics. - 1535-9476 .- 1535-9484. ; 9:1, s. 1-10
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Tidskriftsartikel (refereegranskat)abstract
- Protein affinity reagents (PARs), most commonly antibodies, are essential reagents for protein characterization in basic research, biotechnology, and diagnostics as well as the fastest growing class of therapeutics. Large numbers of PARs are available commercially; however, their quality is often uncertain. In addition, currently available PARs cover only a fraction of the human proteome, and their cost is prohibitive for proteome scale applications. This situation has triggered several initiatives involving large scale generation and validation of antibodies, for example the Swedish Human Protein Atlas and the German Antibody Factory. Antibodies targeting specific subproteomes are being pursued by members of Human Proteome Organisation (plasma and liver proteome projects) and the United States National Cancer Institute (cancer-associated antigens). ProteomeBinders, a European consortium, aims to set up a resource of consistently quality-controlled protein-binding reagents for the whole human proteome. An ultimate PAR database resource would allow consumers to visit one online warehouse and find all available affinity reagents from different providers together with documentation that facilitates easy comparison of their cost and quality. However, in contrast to, for example, nucleotide databases among which data are synchronized between the major data providers, current PAR producers, quality control centers, and commercial companies all use incompatible formats, hindering data exchange. Here we propose Proteomics Standards Initiative (PSI)-PAR as a global community standard format for the representation and exchange of protein affinity reagent data. The PSI-PAR format is maintained by the Human Proteome Organisation PSI and was developed within the context of ProteomeBinders by building on a mature proteomics standard format, PSI-molecular interaction, which is a widely accepted and established community standard for molecular interaction data. Further information and documentation are available on the PSI-PAR web site. Molecular & Cellular Proteomics 9: 1-10, 2010.
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13. |
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14. |
- Lim, Lee Ling, et al.
(författare)
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Aspects of Multicomponent Integrated Care Promote Sustained Improvement in Surrogate Clinical Outcomes: A Systematic Review and Meta-analysis.
- 2018
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Ingår i: Diabetes care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 41:6, s. 1312-1320
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Tidskriftsartikel (refereegranskat)abstract
- The implementation of the Chronic Care Model (CCM) improves health care quality. We examined the sustained effectiveness of multicomponent integrated care in type 2 diabetes.We searched PubMed and Ovid MEDLINE (January 2000-August 2016) and identified randomized controlled trials comprising two or more quality improvement strategies from two or more domains (health system, health care providers, or patients) lasting ≥12 months with one or more clinical outcomes. Two reviewers extracted data and appraised the reporting quality.In a meta-analysis of 181 trials (N = 135,112), random-effects modeling revealed pooled mean differences in HbA1c of -0.28% (95% CI -0.35 to -0.21) (-3.1 mmol/mol [-3.9 to -2.3]), in systolic blood pressure (SBP) of -2.3 mmHg (-3.1 to -1.4), in diastolic blood pressure (DBP) of -1.1 mmHg (-1.5 to -0.6), and in LDL cholesterol (LDL-C) of -0.14 mmol/L (-0.21 to -0.07), with greater effects in patients with LDL-C ≥3.4 mmol/L (-0.31 vs. -0.10 mmol/L for <3.4 mmol/L; Pdifference = 0.013), studies from Asia (HbA1c -0.51% vs. -0.23% for North America [-5.5 vs. -2.5 mmol/mol]; Pdifference = 0.046), and studies lasting >12 months (SBP -3.4 vs. -1.4 mmHg, Pdifference = 0.034; DBP -1.7 vs. -0.7 mmHg, Pdifference = 0.047; LDL-C -0.21 vs. -0.07 mmol/L for 12-month studies, Pdifference = 0.049). Patients with median age <60 years had greater HbA1c reduction (-0.35% vs. -0.18% for ≥60 years [-3.8 vs. -2.0 mmol/mol]; Pdifference = 0.029). Team change, patient education/self-management, and improved patient-provider communication had the largest effect sizes (0.28-0.36% [3.0-3.9 mmol/mol]).Despite the small effect size of multicomponent integrated care (in part attenuated by good background care), team-based care with better information flow may improve patient-provider communication and self-management in patients who are young, with suboptimal control, and in low-resource settings.
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15. |
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16. |
- Mayer, Gerhard, et al.
(författare)
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The HUPO proteomics standards initiative-mass spectrometry controlled vocabulary
- 2013
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Ingår i: Database: the journal of biological databases and curation. - : Oxford University Press (OUP). - 1758-0463. ; , s. 009-009
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Tidskriftsartikel (refereegranskat)abstract
- Controlled vocabularies (CVs), i.e. a collection of predefined terms describing a modeling domain, used for the semantic annotation of data, and ontologies are used in structured data formats and databases to avoid inconsistencies in annotation, to have a unique (and preferably short) accession number and to give researchers and computer algorithms the possibility for more expressive semantic annotation of data. The Human Proteome Organization (HUPO)-Proteomics Standards Initiative (PSI) makes extensive use of ontologies/CVs in their data formats. The PSI-Mass Spectrometry (MS) CV contains all the terms used in the PSI MS-related data standards. The CV contains a logical hierarchical structure to ensure ease of maintenance and the development of software that makes use of complex semantics. The CV contains terms required for a complete description of an MS analysis pipeline used in proteomics, including sample labeling, digestion enzymes, instrumentation parts and parameters, software used for identification and quantification of peptides/proteins and the parameters and scores used to determine their significance. Owing to the range of topics covered by the CV, collaborative development across several PSI working groups, including proteomics research groups, instrument manufacturers and software vendors, was necessary. In this article, we describe the overall structure of the CV, the process by which it has been developed and is maintained and the dependencies on other ontologies.
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17. |
- Mueller-Wohlfahrt, H. W., et al.
(författare)
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Terminology and classification of muscle injuries in sport: The Munich consensus statement
- 2013
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Ingår i: British Journal of Sports Medicine. - : BMJ. - 0306-3674 .- 1473-0480. ; 47:6
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Tidskriftsartikel (refereegranskat)abstract
- Objective To provide a clear terminology and classification of muscle injuries in order to facilitate Methods Thirty native English-speaking scientists and team doctors of national and first division Results The response rate of the survey was 63%. The responses confirmed the marked variability in Conclusions A consistent English terminology as well as a comprehensive classification system for What are the new things Consensus definitions of the terminology which is used in the field of muscle
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18. |
- Omenn, Gilbert S., et al.
(författare)
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The 2022 Report on the Human Proteome from the HUPO Human Proteome Project
- 2023
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 22:4, s. 1024-1042
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Tidskriftsartikel (refereegranskat)abstract
- The 2022 Metrics of the Human Proteome from the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 407 (93.2%) of the 19 750 predicted proteins coded in the human genome, a net gain of 50 since 2021 from data sets generated around the world and reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 78 from 1421 to 1343. This represents continuing experimental progress on the human proteome parts list across all the chromosomes, as well as significant reclassifications. Meanwhile, applying proteomics in a vast array of biological and clinical studies continues to yield significant findings and growing integration with other omics platforms. We present highlights from the Chromosome-Centric HPP, Biology and Disease-driven HPP, and HPP Resource Pillars, compare features of mass spectrometry and Olink and Somalogic platforms, note the emergence of translation products from ribosome profiling of small open reading frames, and discuss the launch of the initial HPP Grand Challenge Project, “A Function for Each Protein”.
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19. |
- Omenn, Gilbert S., et al.
(författare)
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The 2023 Report on the Proteome from the HUPO Human Proteome Project
- 2024
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 23:2, s. 532-549
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Forskningsöversikt (refereegranskat)abstract
- Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1–4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.
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20. |
- Orchard, John W., et al.
(författare)
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Sport Medicine Diagnostic Coding System (SMDCS) and the Orchard Sports Injury and Illness Classification System (OSIICS): revised 2020 consensus versions
- 2020
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Ingår i: British Journal of Sports Medicine. - : BMJ PUBLISHING GROUP. - 0306-3674 .- 1473-0480. ; 54:7, s. 397-401
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Tidskriftsartikel (refereegranskat)abstract
- Coding in sports medicine generally uses sports-specific coding systems rather than the International Classification of Diseases (ICD), because of superior applicability to the profile of injury and illness presentations in sport. New categories for coding were agreed on in the International Olympic Committee (IOC) consensus statement: Methods for recording and reporting of epidemiological data on injury and illness in sports 2020. We explain the process for determining the new categories and update both the Sport Medicine Diagnostic Coding System (SMDCS) and the Orchard Sports Injury and Illness Classification System (OSIICS) with new versions that operationalise the new consensus categories. The author group included members from an expert group attending the IOC consensus conference. The primary authors of the SMDCS (WM) and OSIICS (JO) produced new versions that were then agreed on by the remaining authors using expert consensus methodology. The SMDCS and OSIICS systems have been adjusted and confirmed through a consensus process to align with the IOC consensus statement to facilitate translation between the two systems. Problematic areas for defining body part categories included the groin and ankle regions. For illness codes, in contrast to the ICD, we elected to have a taxonomy of organ system/region (eg, cardiovascular and respiratory), followed by an aetiology/pathology (eg, environmental, infectious disease and allergy). Companion data files have been produced that provide translations between the coding systems. The similar structure of coding underpinning the OSIICS and SMDCS systems aligns the new versions of these systems with the IOC consensus statement and also facilitates easier translation between the two systems. These coding systems are freely available to the sport and exercise research community.
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