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- Sartelli, Massimo, et al.
(författare)
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Ten golden rules for optimal antibiotic use in hospital settings: the WARNING call to action
- 2023
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Ingår i: WORLD JOURNAL OF EMERGENCY SURGERY. - 1749-7922. ; 18:1
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Forskningsöversikt (refereegranskat)abstract
- Antibiotics are recognized widely for their benefits when used appropriately. However, they are often used inappropriately despite the importance of responsible use within good clinical practice. Effective antibiotic treatment is an essential component of universal healthcare, and it is a global responsibility to ensure appropriate use. Currently, pharmaceutical companies have little incentive to develop new antibiotics due to scientific, regulatory, and financial barriers, further emphasizing the importance of appropriate antibiotic use. To address this issue, the Global Alliance for Infections in Surgery established an international multidisciplinary task force of 295 experts from 115 countries with different backgrounds. The task force developed a position statement called WARNING (Worldwide Antimicrobial Resistance National/International Network Group) aimed at raising awareness of antimicrobial resistance and improving antibiotic prescribing practices worldwide. The statement outlined is 10 axioms, or "golden rules," for the appropriate use of antibiotics that all healthcare workers should consistently adhere in clinical practice.
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- Leenhardt, R., et al.
(författare)
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A guide for assessing the clinical relevance of findings in small bowel capsule endoscopy : analysis of 8064 answers of international experts to an illustrated script questionnaire
- 2021
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Ingår i: Clinics and Research in Hepatology and Gastroenterology. - : Elsevier BV. - 2210-7401. ; 45:6
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Tidskriftsartikel (refereegranskat)abstract
- Background and aim: Although recommended, the P-score used for assessing the pertinence / relevance of findings seen in small bowel (SB) capsule endoscopy (CE) is based on a low level of knowledge. The aim of this study was to evaluate the clinical relevance of the most frequent SBCE findings through an illustrated script questionnaire. Materials and Methods: Sixteen types of SBCE findings were illustrated four times each in three different settings (occult and overt obscure gastrointestinal bleeding and suspected Crohn's disease), and with a variable number (n = 1/n = 2–5/n ≥ 6), thus providing a questionnaire with 192 scenarios and 576 illustrated questions. Fifteen international experts were asked to rate the finding's relevance for each question as very unlikely (−2) / unlikely (−1) / doubtful (0) / likely (+1) / very likely (+2). The median score (≤−0.75, between -0.75 and 0.75, or ≥0.75) obtained for each scenario determined a low (P0), intermediate (P1) or high (P2) relevance, respectively. Results: 8064 answers were analyzed. Participation and completion rates were 93% and 100%, respectively. In overt or occult OGIB, resultant P2 findings were 'typical angiectasia', 'deep ulceration', 'stenosis', and'blood', whatever their numbers, and 'superficial ulcerations' when multiple. While in suspected CD, consensus P2 lesions were 'deep ulceration' and 'stenosis' whatever their numbers, and 'aphthoid erosions' and 'superficial ulcerations' when multiple. Conclusion: This study establishes a guide for the evaluation of relevance of SBCE findings. It represents a step forward for SB-CE interpretation and is intended to be used as a tool for teaching and academic research.
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- Leenhardt, R., et al.
(författare)
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Key research questions for implementation of artificial intelligence in capsule endoscopy
- 2022
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Ingår i: Therapeutic Advances in Gastroenterology. - : SAGE Publications. - 1756-283X .- 1756-2848. ; 15
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Tidskriftsartikel (refereegranskat)abstract
- Background: Artificial intelligence (AI) is rapidly infiltrating multiple areas in medicine, with gastrointestinal endoscopy paving the way in both research and clinical applications. Multiple challenges associated with the incorporation of AI in endoscopy are being addressed in recent consensus documents. Objectives: In the current paper, we aimed to map future challenges and areas of research for the incorporation of AI in capsule endoscopy (CE) practice. Design: Modified three-round Delphi consensus online survey. Methods: The study design was based on a modified three-round Delphi consensus online survey distributed to a group of CE and AI experts. Round one aimed to map out key research statements and challenges for the implementation of AI in CE. All queries addressing the same questions were merged into a single issue. The second round aimed to rank all generated questions during round one and to identify the top-ranked statements with the highest total score. Finally, the third round aimed to redistribute and rescore the top-ranked statements. Results: Twenty-one (16 gastroenterologists and 5 data scientists) experts participated in the survey. In the first round, 48 statements divided into seven themes were generated. After scoring all statements and rescoring the top 12, the question of AI use for identification and grading of small bowel pathologies was scored the highest (mean score 9.15), correlation of AI and human expert reading-second (9.05), and real-life feasibility-third (9.0). Conclusion: In summary, our current study points out a roadmap for future challenges and research areas on our way to fully incorporating AI in CE reading.
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- Schweinsberg, Martin, et al.
(författare)
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Same data, different conclusions : Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis
- 2021
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Ingår i: Organizational Behavior and Human Decision Processes. - : Elsevier BV. - 0749-5978 .- 1095-9920. ; 165, s. 228-249
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Tidskriftsartikel (refereegranskat)abstract
- In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists' gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for orga-nizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed.
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| 6. |
- Osinski, V., et al.
(författare)
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In vivo liposomal delivery of PPAR alpha/gamma dual agonist tesaglitazar in a model of obesity enriches macrophage targeting and limits liver and kidney drug effects
- 2020
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Ingår i: Theranostics. - : Ivyspring International Publisher. - 1838-7640. ; 10:2, s. 585-601
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Tidskriftsartikel (refereegranskat)abstract
- Macrophages are important regulators of obesity-associated inflammation and PPAR alpha and -gamma agonism in macrophages has anti-inflammatory effects. In this study, we tested the efficacy with which liposomal delivery could target the PPAR alpha/gamma dual agonist tesaglitazar to macrophages while reducing drug action in common sites of drug toxicity: the liver and kidney, and whether tesaglitazar had anti-inflammatory effects in an in vivo model of obesity-associated dysmetabolism. Methods: Male leptin-deficient (ob/ob) mice were administered tesaglitazar or vehicle for one week in a standard oral formulation or encapsulated in liposomes. Following the end of treatment, circulating metabolic parameters were measured and pro-inflammatory adipose tissue macrophage populations were quantified by flow cytometry. Cellular uptake of liposomes in tissues was assessed using immunofluorescence and a broad panel of cell subset markers by flow cytometry. Finally, PPAR alpha/gamma gene target expression levels in the liver, kidney, and sorted macrophages were quantified to determine levels of drug targeting to and drug action in these tissues and cells. Results: Administration of a standard oral formulation of tesaglitazar effectively treated symptoms of obesity-associated dysmetabolism and reduced the number of pro-inflammatory adipose tissue macrophages. Macrophages are the major cell type that took up liposomes with many other immune and stromal cell types taking up liposomes to a lesser extent. Liposome delivery of tesaglitazar did not have effects on inflammatory macrophages nor did it improve metabolic parameters to the extent of a standard oral formulation. Liposomal delivery did, however, attenuate effects on liver weight and liver and kidney expression of PPAR alpha and -gamma gene targets compared to oral delivery. Conclusions: These findings reveal for the first time that tesaglitazar has anti-inflammatory effects on adipose tissue macrophage populations in vivo. These data also suggest that while nanoparticle delivery reduced off-target effects, yet the lack of tesaglitazar actions in non-targeted cells such (as hepatocytes and adipocytes) and the uptake of drug-loaded liposomes in many other cell types, albeit to a lesser extent, may have impacted overall therapeutic efficacy. This fulsome analysis of cellular uptake of tesaglitazar-loaded liposomes provides important lessons for future studies of liposome drug delivery.
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