Αρχειοθήκη ιστολογίου

Αλέξανδρος Γ. Σφακιανάκης
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5
Άγιος Νικόλαος Κρήτη 72100
2841026182
6032607174

Τετάρτη 1 Ιουνίου 2022

Symptom‐based remote assessment in post treatment head and neck cancer surveillance: a prospective national study

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Abstract

Objectives

To report the incidence of locoregional recurrence in HNC patients under surveillance following treatment undergoing symptom-based remote assessment.

Design

A 16-week multicentre prospective cohort study.

Setting

UK ENT departments.

Participants

HNC patients under surveillance following treatment undergoing symptom-based telephone assessment.

Main outcome measures

Incidence of locoregional recurrent HNC after minimum 6-month follow-up.

Results

Data for 1,078 cases were submitted by 16 centres, with follow-up data completed in 98.9% (n=1,066).

Following telephone consultation, 83.7% of referrals had their face-to-face appointments deferred (n=897/1,072). New symptoms were reported by 11.6% (n=124/1072) at telephone assessment; 72.6% (n=90/124) of this group were called for urgent assessments, of whom 48.9% (n=44/90) came directly for imaging without preceding clinical review.

The sensitivity and specificity for new symptoms as an indicator of cancer recurrence were 35.3% and 89.4%, respectively, with a negative predictive value of 99.7% (p=0.002).

Locoregional cancer identification rates after a minimum of 6 months of further monitoring, when correlated with time since treatment, were: 6.0% (n=14/233) <1 year; 2.1% (n=16/747) between 1 and 5 years; and 4.3% (n=4/92) for those >5 years since treatment.

Conclusions

Telephone assessment, using patient-reported symptoms, to identify recurrent locoregional HNC was widely adopted during the initial peak of the COVID-19 pandemic in the UK. The majority of patients had no face-to-face reviews or investigations. New symptoms were significantly associated with the identification of locoregional recurrent cancers with a high specificity, but a low sensitivity may limit symptom assessment being used as the sole surveillance method.

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DNA methylation profiling of central nervous system hemangioblastomas identifies two distinct subgroups

alexandrossfakianakis shared this article with you from Inoreader

Abstract

Hemangioblastomas (HBs) of the central nervous system are highly vascular neoplasms that occur sporadically or as a manifestation of von Hippel–Lindau (VHL) disease. Despite their benign nature, HBs are clinically heterogeneous and can be associated with significant morbidity due to mass effects of peritumoral cysts or tumor progression. Underlying molecular factors involved in HB tumor biology remain elusive. We investigated genome-wide DNA methylation profiles and clinical and histopathological features in a series of 47 HBs from 42 patients, including 28 individuals with VHL disease. Thirty tumors occurred in the cerebellum, 8 in the brainstem and 8 HBs were of spinal location, while 1 HB was located in the cerebrum. Histologically, 12 HBs (26%) belonged to the cellular subtype and exclusively occurred in the cerebellum, whereas 35 HBs were reticular (74%). Unsupervised clustering and dimensionality reduction of DNA methylation profiles revealed two distinct subgroups. Methyl ation cluster 1 comprised 30 HBs of mainly cerebellar location (29/30, 97%), whereas methylation cluster 2 contained 17 HBs predominantly located in non-cerebellar compartments (16/17, 94%). The sum of chromosomal regions being affected by copy-number alterations was significantly higher in methylation cluster 1 compared to cluster 2 (mean 262 vs. 109 Mb, p = 0.001). Of note, loss of chromosome 6 occurred in 9/30 tumors (30%) of methylation cluster 1 and was not observed in cluster 2 tumors (p = 0.01). No relevant methylation differences between sporadic and VHL-related HBs or cystic and non-cystic HBs could be detected. Deconvolution of the bulk DNA methylation profiles revealed four methylation components that were associated with the two methylation clusters suggesting cluster-specific cell-type compositions. In conclusion, methylation profiling of HBs reveals 2 distinct subgroups that mainly associate with anatomical location, cytogenetic profiles and differ ences in cell type composition, potentially reflecting different cells of origin.

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The metacognitive model of rumination and depression in postpartum women

alexandrossfakianakis shared this article with you from Inoreader

Abstract

Objectives

The metacognitive model of rumination and depression (Papageorgiou & Wells, 2003, Cognitive Therapy and Research, 27, 261) postulates that beliefs that perseverative negative thinking, i.e. rumination, will help solve problems contributing to rumination. However, this activates negative beliefs about the uncontrollability and social consequences of ruminations, which exacerbate depression. The metacognitive model has been well-supported but with some inconsistencies in specific pathways. It has also not yet been tested for postpartum depression (PPD). Therefore, this study aimed to examine the relations between the metacognitive model of rumination and depression when applied to PPD symptoms and to compare it with the cognitive model of depression.

Design

This is a cross-sectional study.

Method

Postpartum mothers (N = 603) participated in an online study in their first postpartum year. They completed the Edinburgh Postnatal Depression Scale (EPDS), Postnatal Negative Thoughts Questionnaire (PNTQ), Ruminative Responses Scale (RRS), Positive Beliefs about Rumination Scale (PBRS) and Negative Beliefs about Rumination Scale (NBRS).

Results

A path analysis revealed that the model had an excellent fit to the data. Specifically, positive beliefs about rumination predicted engagement in rumination that, in turn, predicted PPD, both directly and indirectly, through negative beliefs about uncontrollability and the social consequences of rumination. A cognitive model with ruminations as a partial mediator between negative postpartum thoughts and PPD symptoms also had a good fit.

Conclusion

The findings of this study contribute to the understanding of the cognitive and metacognitive mechanisms underlying postpartum depression, which might be similar to depression in general and have important implications for treatment strategies.

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A novel extracorporeal cardiopulmonary resuscitation strategy using a hybrid emergency room for patients with pulseless electrical activity

alexandrossfakianakis shared this article with you from Inoreader

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Whether extracorporeal cardiopulmonary resuscitation (ECPR) is indicated for patients with pulseless electrical activity (PEA) remains unclear. Pulmonary embolism with PEA is a good candidate for ECPR; however...
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Sanguinarine Represses the Growth and Metastasis of Non-small Cell Lung Cancer by Facilitating Ferroptosis

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Mechanistic and biologically based models in epidemiology; a powerful underutilized tool

alexandrossfakianakis shared this article with you from Inoreader
Abstract
Mechanistic and biologically based mathematical models of chronic and behavioral disease processes aim to capture the main mechanistic or biological features of the disease development, and to connect these with epidemiological outcomes. These approaches have a long history in epidemiological research and are complementary to traditional epidemiological or statistical approaches to investigate the role of risk factor exposures on disease risk.In the article by Simonetto et al. (Am J Epidemiol. XXXX;XXX(XX):XXXX–XXXX)), the authors present a mechanistic, process-oriented, model to investigate the role of smoking, hypertension and dyslipidemia on the development of atherosclerotic lesions and their progression to myocardial infarction (MI). Their approach builds on and brings to cardiovascular disease the ideas and perspectives of earlier mechanistic and biologically based models for the epidemiology of cancer and other chronic diseases, providin g important insights into the mechanisms and epidemiology of smoking related MI.We argue that although mechanistic modeling approaches have demonstrated their value and place in epidemiology, they are highly underutilized. We call for efforts to grow mechanistic and biologically based modeling research, expertise and awareness in epidemiology, including the development of training and collaboration opportunities to attract more students and researchers from STEM areas into the epidemiology field.
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