Evaluation of pharmacological interventions in the management of adenomyosis: a systematic review.

PURPOSE: Medical management of adenomyosis largely revolves around symptom management, with very few drugs having received regulatory approval for the disease. However, the level of evidence supporting the use of pharmacological interventions is low, making it difficult to establish their efficacy in the treatment of adenomyosis. Hence, the aim of our systematic review is to identify the strength of evidence currently available and evaluate the effectiveness of different medical interventions in the management of adenomyosis. METHODS: The search was performed in MEDLINE, Embase, Cochrane Library, CENTRAL and ClinicalTrials.gov. Articles published between 1 January 2010 and 30 November 2020 were considered. Randomized controlled trials and observational studies that assessed the efficacy of medical interventions in patients with adenomyosis were included. The quality of the data was analyzed using RevMan 5.3 software. RESULTS: LNG-IUS (levonorgestrel intrauterine system), dienogest and gonadotropin-releasing hormone (GnRH) analogues were effective in reducing pain, uterine volume and menstrual bleeding. However, these data were largely obtained in the non-trial setting and were fraught with issues that included patient selection, short duration of therapy, small sample size, and limited long-term safety and effectiveness data. CONCLUSIONS: Although LNG-IUS, dienogest and GnRH analogues have better evidence for effectiveness in adenomyosis, the need of the hour is to thoroughly evaluate other novel molecules for adenomyosis using well-designed randomized controlled trials.

Attribute Selection Hybrid Network Model for risk factors analysis of postpartum depression using Social media.

BACKGROUND AND OBJECTIVE: Postpartum Depression (PPD) is a frequently ignored birth-related consequence. Social network analysis can be used to address this issue because social media network serves as a platform for their users to communicate with their friends and share their opinions, photos, and videos, which reflect their moods, feelings, and sentiments. In this work, the depression of delivered mothers is identified using the PPD score and segregated into control and depressed groups. Recently, to detect depression, deep learning methods have played a vital role. However, these methods still do not clarify why some people have been identified as depressed. METHODS: We have developed Attribute Selection Hybrid Network (ASHN) to detect the postpartum depression diagnoses framework. Later analysis of the post of mothers who have been confirmed with the score calculated by the experts of the field using physiological questionnaire score. The model works on the analysis of the attributes of the negative Facebook posts for Depressed user Diagnosis, which is a large general forum. This framework explains the process of analyzing posts containing Sentiment, depressive symptoms, and reflective thinking and suggests psycho-linguistic and stylistic attributes of depression in posts. RESULTS: The experimental results show that ASHN works well and is easy to understand. Here, four attribute networks based on psychological studies were used to analyze the different parts of posts by depressed users. The results of the experiments show the extraction of psycho-linguistic markers-based attributes, the recording of assessment metrics including Precision, Recall and F1 score and visualization of those attributes were used title-wise as well as words wise and compared with daily life, depression and postpartum depressed people using Word cloud. Furthermore, a comparison to a reference with Baseline and ASHN model was carried out. CONCLUSIONS: Attribute Selection Hybrid Network (ASHN) mimics the importance of attributes in social media posts to predict depressed mothers. Those mothers were anticipated to be depressed by answering a questionnaire designed by domain experts with prior knowledge of depression. This work will help researchers look at social media posts to find useful evidence for other depressive symptoms.

A peek into the drug development scenario of endometriosis - A systematic review.

PURPOSE AND OBJECTIVE: Endometriosis is a gynaecological disease that is characterised by the presence of endometrium like tissue-epithelium and stroma that develops outside the uterine cavity, which is responsible for pelvic pain and infertility. Even though several medical therapies exist for the treatment of endometriosis, each of the drug class has its own limitations such as cost of treatment, side-effects and its short-term effect on the symptoms of endometriosis. In this review, we have attempted to summarize the current status and challenges of drug development for endometriosis. METHODS: A systematic review was done and all the RCTs were selected from the identified hits. We included studies that explored the usage of therapeutic drugs on endometriosis patients from inception till November 2016. The search term used was 'Endometriosis' using PubMed and Clinicaltrials.gov. For the final analysis, 60 articles were analyzed and we identified the newly emerging drug therapies for endometriosis treatment and have briefed their current status and challenges in drug development for endometriosis. The quality of the selected studies was assessed based on the degree of bias. RESULTS: The current classes of drugs that have shown promising therapeutic results include Gonadotropin- releasing hormone (GnRH) antagonists, aromatase inhibitors (AI), and selective progesterone and estrogen receptor modulators, dopamine receptor-2-agonists and statins. The drugs that failed midway during development include tanezumab, rosiglitazone, infliximab, pentoxifylline, telapristone acetate, asoprisnil and raloxifene. CONCLUSION: From the literature review, it appears that the most promising molecules for the treatment of endometriosis in the near future include elagolix, mifepristone, TAK-385, KLH-2109 and ASP1707 and cabergoline. It remains to be seen if these molecules would succeed large phase 3 clinical trials and overcome the regulatory hurdles to become an essential tool in the gynaecologist's armamentarium against endometriosis.