Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5 Άγιος Νικόλαος
Κρήτη 72100
00302841026182
00306932607174
alsfakia@gmail.com

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Δευτέρα 25 Απριλίου 2022

Epicardial adipose tissue in coronary microvascular dysfunction

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International Journal of Obesity, Published online: 25 April 2022; doi:10.1038/s41366-022-01125-z

Epicardial adipose tissue in coronary microvascular dysfunction
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Molecular Biomarker-Defined Brain Tumors: Epidemiology, Validity, and Completeness in the United States

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Abstract
Background
Selected molecular biomarkers were incorporated into U.S. cancer registry reporting for patients with brain tumors beginning in 2018. We investigated the completeness and validity of these variables, and described the epidemiology of molecularly-defined brain tumor types.
Methods
Brain tumor patients with histopathologically-confirmed diagnosis in 2018 were identified within the Central Brain Tumor Registry of the United States and NCI's Surveillance, Epidemiology, and End Results Incidence databases. The brain molecular markers (BMM) site-specific data item was assessed for coding completeness and validity. 1p/19q status, MGMT promoter methylation, and WHO grade data items, and new ICD-O-3 codes were additionally evaluated. These data were used to profile the characteristics and age-adjusted incidence rates per 100,000 population of molecularly-defined brain tumors with 95% confidence intervals (95%CI).
Results
BMM completeness across the applicable tumor types was 75-92% and demonstrated favorable coding validity. IDH-wildtype glioblastomas' incidence rate was 1.74 (95%CI: 1.69-1.78), as compared to 0.14 for WHO grade 2 (95%CI: 0.12-0.15), 0.15 for grade 3 (95%CI: 0.14-0.16), and 0.07 for grade 4 (95%CI: 0.06-0.08) IDH-mutant astrocytomas. Irrespective of WHO grade, IDH mutation prevalence was highest in adolescent & young adult patients and IDH-mutant astrocytomas were more frequently MGMT promoter methylated. Among pediatric-type tumors, the incidence rate was 0.06 for H3K27M-mutant diffuse midline gliomas (95%CI: 0.05-0.07), 0.03 for SHH-activated/TP53-wildtype medulloblastomas (95%CI: 0.02-0.03), and <0.01 for both C19MC-altered ETMRs and RELA-fusion ependymomas.
Conclusions
Our findings illustrate the success of developing a dedicated, integrated-diagnosis variable, which provides critical molecular information about brain tumors related to accurate diagnosis.
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ONC201 and ONC206: metabolically ClipPing the wings of diffuse midline glioma

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Selumetinib in Children with Neurofibromatosis Type 1 and Asymptomatic Inoperable Plexiform Neurofibroma At Risk for Developing Tumor-Related Morbidity

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Abstract
Background
Selumetinib was recently approved for treatment of inoperable symptomatic plexiform neurofibromas (PNs) in children with neurofibromatosis type 1 (NF1). This parallel phase II study determined the response rate to selumetinib in children with NF1 PN without clinically significant morbidity.
Methods
Children with NF1 and inoperable PNs, which were not yet causing clinically significant morbidity but had the potential to cause symptoms, received selumetinib at 25 mg/m 2 orally twice daily (1 cycle=28 days). Volumetric magnetic resonance imaging analysis and outcome assessments, including patient-reported (PRO), observer-reported, and functional outcome measures were performed every 4 cycles for 2 years, with changes assessed over time. A confirmed partial response (cPR) was defined as PN volume decrease of ≥20% on at least 2 consecutive scans ≥3 months apart.
Results
72% of subjects experie nced a cPR on selumetinib. Participants received selumetinib for a median of 41 cycles (min 2, max 67) at data cut-off. Approximately half of children rated having some target tumor pain at baseline, which significantly decreased by pre-cycle 13. Most objectively measured baseline functions including visual, motor, bowel/bladder or airway function were within normal limits and did not clinically or statistically worsen during treatment.
Conclusions
Selumetinib resulted in PN shrinkage in most subjects with NF1 PN without clinically significant morbidity. No new PN related symptoms developed while on selumetinib, and PRO measures indicated declines in tumor-related pain intensity. This supports that selumetinib treatment may prevent the development of PN related morbidities, though future prospective studies are needed to confirm these results. (ClinicalTrials.gov NCT01362803)
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Renal denervation for atrial fibrillation: a comprehensive updated systematic review and meta-analysis

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Journal of Human Hypertension, Published online: 25 April 2022; doi:10.1038/s41371-022-00700-1

Renal denervation for atrial fibrillation: a comprehensive updated systematic review and meta-analysis
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Effect of vitamin E supplementation in rheumatoid arthritis: a systematic review and meta-analysis

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European Journal of Clinical Nutrition, Published online: 25 April 2022; doi:10.1038/s41430-022-01148-9

Effect of vitamin E supplementation in rheumatoid arthritis: a systematic review and meta-analysis
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Salbutamol for analgesia in renal colic: study protocol for a prospective, randomised, placebo-controlled phase II trial (SARC)

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Renal colic is the pain experienced by a patient when a renal calculus (kidney stone) causes partial or complete obstruction of part of the renal outflow tract. The standard analgesic regimes for renal colic a...
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Management der Ohrmuschelteilamputationen

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Laryngorhinootologie
DOI: 10.1055/a-1792-2194

Ohrmuschelverletzungen zählen zu den selteneren Traumata im Kopf-Hals-Bereich. Aufgrund der komplexen Anatomie des Knorpels und der begrenzten Blutversorgung bedürfen sie einer raschen und strukturierten Behandlung. Für die Behandlung sowohl von leichten Verletzungen als auch von (sub-)totalen Abrissen der Ohrmuschel stehen unterschiedliche Therapieoptionen zur Verfügung. Eine direkte Readaptation einer (sub-)total abgerissenen Ohrmuschel ohne mikrovaskulare Anastomose ist aufgrund des hohen Risikos von Haut- und Knorpelnekrosen nur selten erfolgreich. Mehrzeitige Rekonstruktionen mit Pocket-Methoden sind dagegen gut etabliert. Die vorliegende Arbeit beschreibt einige dieser Ansä tze und demonstriert eine 2-stufige OP-Technik eines Ohrmuschelteilabrisses aus dem eigenen Patientengut.
[...]

Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany

Article in Thieme eJournals:
Table of contents  |  Abstract  |  Full text

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The Impact of the COVID-19 Global Pandemic on Undergraduate Nursing Students' Study of Anatomy and Physiology

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imageThe COVID-19 global pandemic caused major disruptions to the delivery of human Anatomy and Physiology courses to nursing students worldwide. The aim of the current study is to evaluate nursing students' experiences and perceptions of transitioning from a blended to a purely online study mode for first year Anatomy and Physiology courses during the global pandemic. Qualitative and quantitative methodologies were used with a sample of undergraduate nursing students enrolled at a regional Australian university across its three campuses. Descriptive statistical analysis was used to describe the study population. Content a nalysis was used to evaluate the participants' use of resources, experiences, and preferences in studying anatomy and physiology. There were 101 participants recruited in the study. Results indicated that face-to-face study mode (41.86%) was the preferred method of delivery during the global pandemic and participants were having a renewed appreciation for the blended study mode (38.37%). Online study mode was the least preferred (19.77%), with the participants' opinions of this mode of study not altered by the global pandemic. Although the COVID-19 global pandemic shifted the traditional teaching of anatomy and physiology in nursing programs to an online environment, the long-term impacts of this disruption have yet to be ascertained.
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Barriers to Adoption of Electronic Health Record Systems from the Perspective of Nurses: A Cross-sectional Study

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imageThis study report aimed to investigate the barriers to implementation of electronic health record systems from the perspective of nurses. The research data comprised responses from nurses working in a university hospital. Our data collection instruments were the Participant Information Form and EHR Nurse Opinion Questionnaire, which were developed by the researchers. Data analysis was presented as summary statistics, including mean values of variables, standard deviation, frequency, and percentages. A total of 160 nurses participated in the study. The mean age of participants was 30.94 ± 0.59 years, and 77.5% were university graduates. Barriers to adoption of the electronic health record system included high number of patients (82.8%), limited time (79%), lack of knowledge and skills for effective use of the system (22.9%), lack of user-friendly interface and inability to create a common language within the team (17.8%), and attachment to the traditional method (17.2%). Although most nurses thought that the electronic health record system offered some advantages, they reported that factors such as large numbers of patients, limited time, and lack of user-friendly interface hindered its adoption. Innovative strategies should be explored to develop user-friendly designs for electronic health records and to produce solutions for nursing shortages to increase the time allocated for patient care.
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Prediction of Bedridden Duration of Hospitalized Patients by Machine Learning Based on EMRs at Admission

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imageBeing bedridden is a frequent comorbid condition that leads to a series of complications in clinical practice. The present study aimed to predict bedridden duration of hospitalized patients based on EMR at admission by machine learning. The medical data of 4345 hospitalized patients who were bedridden for at least 24 hours after admission were retrospectively collected. After preprocessing of the data, features for modeling were selected by support vector machine recursive feature elimination. Thereafter, logistic regression, support vector machine, and extreme gradient boosting algorithms were adopted to predict th e bedridden duration. The feasibility and efficacy of above models were evaluated by performance indicators. Our results demonstrated that the most important features related to bedridden duration were Charlson Comorbidity Index, age, bedridden duration before admission, mobility capability, and perceptual ability. The extreme gradient boosting algorithm showed the best performance (accuracy, 0.797; area under the curve, 0.841) when compared with support vector machine (accuracy, 0.771; area under the curve, 0.803) and logistic regression (accuracy, 0.765; area under the curve, 0.809) algorithms. Meanwhile, the extreme gradient boosting algorithm had a higher sensitivity (0.856), specificity (0.650), and F1 score (0.858) than that of support vector machine algorithm (0.843, 0.589, and 0.841) and logistic regression (0.852, 0.545, and 0.839), respectively. These findings indicate that machine learning based on EMRs at admission is a feasible avenue to predict the bedridden duration. The extreme gradient boosting algorithm shows great potential for further clinical application.
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Higher Moments Matter for Optimal Balance Weighting in Causal Estimation

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We expand upon a simulation study that compared three promising methods for estimating weights for assessing the average treatment effect on the treated for binary treatments: generalized boosted models, covariate-balancing propensity scores, and entropy balance. The original study showed that generalized boosted models can outperfo rm covariate-balancing propensity scores, and entropy balance when there are likely to be non-linear associations in both the treatment assignment and outcome models and when the other two models are fine-tuned to obtain balance only on first-order moments. We explore the potential benefit of using higher-order moments in the balancing conditions for covariate-balancing propensity scores and entry balance. Our findings showcase that these two models should, by default, include higher order moments and focusing only on first moments can result in substantial bias in estimated treatment effect estimates from both models that could be avoided using higher moments. We expand upon a simulation study that compared three promising methods for estimating weights for assessing the average treatment effect on the treated for binary treatments: generalized boosted models, covariate-balancing propensity scores, and entropy balance. The original study showed that generalized boosted models can outperform covariate-balancing propensity scores, and entropy balance when there are likely to be non-linear associations in both the treatment assignment and outcome models and when the other two models are fine-tuned to obtain balance only on first-order moments. We explore the potential benefit of using higher-order moments in the balancing conditions for covariate-balancing propensity scores and entry balance. Our findings showcase that these two models should, by default, include higher order moments and focusing only on first moments can result in substantial bias in estimated treatment effect estimates from both models that could be avoided using higher mom ents. Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.
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