Effect of hypnosis before general anesthesia on postoperative outcomes in patients undergoing minor surgery for breast cancer: a systematic review and meta-analysis

Predicting gene signature in breast cancer patients with multiple machine learning models

AIMS

The aim of this study was to predict gene signatures in breast cancer patients using multiple machine learning models.

METHODS

In this study, we first collated and merged the datasets GSE54002 and GSE22820, obtaining a gene expression matrix comprising 16,820 genes (including 593 breast cancer (BC) samples and 26 normal control (NC) samples). Subsequently, we performed enrichment analyses using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Disease Ontology (DO).

RESULTS

We identified 177 differentially expressed genes (DEGs), including 40 up-regulated and 137 down-regulated genes, through differential expression analysis. The GO enrichment results indicated that these genes are primarily involved in extracellular matrix organization, positive regulation of nervous system development, collagen-containing extracellular matrix, heparin binding, glycosaminoglycan binding, and Wnt protein binding, among others. KEGG enrichment analysis revealed that the DEGs were primarily associated with pathways such as focal adhesion, the PI3K-Akt signaling pathway, and human papillomavirus infection. DO enrichment analysis showed that the DEGs play a significant role in regulating diseases such as intestinal disorders, nephritis, and dermatitis. Further, through LASSO regression analysis and SVM-RFE algorithm analysis, we identified 9 key feature DEGs (CF-DEGs): ANGPTL7, TSHZ2, SDPR, CLCA4, PAMR1, MME, CXCL2, ADAMTS5, and KIT. Additionally, ROC curve analysis demonstrated that these CF-DEGs serve as a reliable diagnostic index. Finally, using the CIBERSORT algorithm, we analyzed the infiltration of immune cells and the associations between CF-DEGs and immune cell infiltration across all samples.

CONCLUSIONS

Our findings provide new insights into the molecular functions and metabolic pathways involved in breast cancer, potentially aiding in the discovery of new diagnostic and immunotherapeutic biomarkers.

Hypnosis support in anaesthesia is rarely used in German anaesthesia departments - a nationwide survey among leading physicians of anaesthesia departments

BACKGROUND

The aim of this study was to investigate whether and to what extent perioperative hypnosis and relaxation techniques are used in German anaesthesia departments, what they are, where any difficulties in their application lie and how great the interest in this type of therapy is. Another research question was to find out whether there are specialist areas in which these methods are used more frequently than in other specialist areas.

METHODS

A descriptive survey was conducted by means of a questionnaire in all hospitals with anaesthesia departments in Germany. 1124 questionnaires were sent out by post. The survey period was five months from 27/02/2023 to 31/07/2023. The clinic directors of all anaesthesiology departments in German hospitals were surveyed.

RESULTS

476 departments (42%) responded by pre-paid envelope. Of these, only 39 (8%) use hypnosis and relaxation techniques perioperatively. These are mostly progressive muscle relaxation, hypnotic trance according to Erickson, calming words and suggestions or the use of virtual reality (e.g. using VR-glasses).

CONCLUSIONS

Hypnosis techniques have been shown in many studies to be effective in increasing patient comfort (less anxiety and stress) and reducing both the need for medication and perioperative pain. The therapy is rarely used in Germany, although once established it can be easily integrated into perioperative procedures. Many departments have shown great interest in the topic. In the interests of patients, a structural change should be considered to promote the use of hypnotic procedures.

Meta-analytic evidence on the efficacy of hypnosis for mental and somatic health issues: a 20-year perspective

Introduction

Documented use and investigation of hypnosis spans centuries and its therapeutic use has received endorsement by multiple medical associations. We conducted a comprehensive overview of meta-analyses examining the efficacy of hypnosis to provide a foundational understanding of hypnosis in evidence-based healthcare, insight into the safety of hypnosis interventions, and identification of gaps in the current research literature.

Methods

In our systematic review, meta-analyses of randomized controlled trials on the efficacy of hypnosis in patients with mental or somatic health problems compared to any control condition published after the year 2000 were included. A comprehensive literature search using Medline, Scopus, PsycINFO, The Cochrane Library, HTA Database, Web of Science and a manual search was conducted to identify eligible reviews. Methodological quality of the included meta-analyses was rated using the AMSTAR 2 tool. Effect estimates on various outcomes including at least three comparisons (k ≥ 3) were extracted and transformed into a common effect size metric (Cohen's d). If available, information on the certainty of evidence for these outcomes (GRADE assessment) was obtained.

Results

We included 49 meta-analyses with 261 distinct primary studies. Most robust evidence was reported for hypnosis in patients undergoing medical procedures (12 reviews, 79 distinct primary studies) and in patients with pain (4 reviews, 65 primary studies). There was a considerable overlap of the primary studies across the meta-analyses. Only nine meta-analyses were rated to have high methodological quality. Reported effect sizes comparing hypnosis against control conditions ranged from d = -0.04 to d = 2.72. Of the reported effects, 25.4% were medium (d ≥ 0.5), and 28.8% were large (d ≥ 0.8).

Discussion

Our findings underline the potential of hypnosis to positively impact various mental and somatic treatment outcomes, with the largest effects found in patients experiencing pain, patients undergoing medical procedures, and in populations of children/adolescents. Future research should focus on the investigation of moderators of efficacy, on comparing hypnosis to established interventions, on the efficacy of hypnosis for children and adolescents, and on identifying patients who do not benefit from hypnosis.

Clinical Trial Registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023395514, identifier CRD42023395514.

The Effects of Complementary Therapies on Patient-Reported Outcomes: An Overview of Recent Systematic Reviews in Oncology

Many patients with cancer make use of complementary medicine alongside conventional medicine, but clinicians in oncology often lack the knowledge to adequately advise patients on the evidence base for complementary therapies. This study aims to provide an overview of recently published systematic reviews that assess the effects of complementary therapies on patient-reported health outcomes in patients with cancer. Systematic reviews, including a meta-analysis of at least two randomized controlled trials, were identified from the PubMed, Embase, Cochrane Library, CINAHL and PsycINFO databases. The methodological quality was assessed with AMSTAR 2. One hundred systematic reviews were included. The results suggest that several complementary therapies can improve health outcomes reported by patients with cancer, such as acupuncture to relieve pain, music interventions to reduce anxiety and yoga to improve cancer-related fatigue. The side effects related to complementary therapy use are generally mild. The results remain inconclusive for some intervention-outcome combinations. Many of the included systematic reviews insufficiently assessed the causes and impact of bias in their interpretation of the results. This overview of systematic reviews can support clinicians in counselling their patients on this topic and provide directions for future research and clinical practice guidelines in the field of complementary medicine.

Hypnoanalgesia: A Bridge Between Neuroscience and Clinical Settings

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