The effects of smoking on female sexual dysfunction: a systematic review and meta-analysis

Salari, Nader; Hasheminezhad, Razie; Ghaleh, Hadi Esmaeili Gouvarchin; Kiaei, Aliakbar; Shohaimi, Shamarina; Akbari, Hakimeh; Nankali, Anisodowleh; Mohammadi, Masoud

doi:10.1007/s00737-022-01281-1

Cited by 17 publications

(15 citation statements)

References 30 publications

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“…The selected confounders are shown to be associated both with sexual function and cardiovascular health 3,7,28–35 . Age was reported in years.…”

Section: Methodsmentioning

confidence: 99%

“…The selected confounders are shown to be associated both with sexual function and cardiovascular health. 3 , 7 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 Age was reported in years. Relationship happiness was evaluated with the question “How do you consider your current relationship?” and with answer options “very happy”, “fairly happy”, “neither happy nor unhappy”, “fairly unhappy”, and “very unhappy” and dichotomized as happy/unhappy.…”

Section: Methodsmentioning

confidence: 99%

“…The selected confounders are shown to be associated both with sexual function and cardiovascular health. 3,7,[28][29][30][31][32][33][34][35] Age was reported in years. Relationship happiness was evaluated with the question "How do you consider your current relationship?"…”

Section: Confounding Factorsmentioning

confidence: 99%

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Associations between arterial health and sexual function in women aged 60–64 years

Virkkunen,

Kero,

Koivisto

et al. 2024

Acta Obstet Gynecol Scand

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IntroductionFemale sexual dysfunction is very common, but its determinants remain under‐investigated. Vasculogenic impairments are suggested to be related to female sexual dysfunction, but previous literature regarding the association is scarce. This study aims to study the association between arterial health and female sexual function in women in their 60s.Material and methodsThe sample for this cross‐sectional study comprised 117 women (aged 60–64 years) who participated in the Finnish Retirement and Aging study. Arterial health was measured according to the participants' pulse wave velocity, ankle–brachial index, blood pressure, and pulse pressure. Sexual function was measured using the Female Sexual Function Index, which resulted in a total score and six sub‐scores. Associations were examined using multivariable regression analyses, which were adjusted for age, relationship happiness, systemic menopausal hormone therapy and/or local estrogen, smoking, alcohol risk use, body mass index, and depressive symptoms.ResultsHigher diastolic blood pressure was associated with a higher total Female Sexual Function Index score (β = 0.24, 95% confidence interval [CI] 0.07–0.41) and with higher desire (β = 0.02, 95% CI 0.01–0.04), arousal (β = 0.04, 95% CI 0.01–0.08), lubrication (β = 0.04, 95% CI 0.002–0.08), satisfaction (β = 0.03, 95% CI 0.003–0.05), and pain (β = 0.06, 95% CI 0.02–0.10) sub‐scores. Also, higher ankle–brachial index was associated with higher satisfaction sub‐score (β = 2.10, 95% CI 0.44–3.73) and lower pulse pressure was associated with higher orgasm sub‐score (β = 0.03, 95% CI 0.0002–0.06). Other associations between ankle–brachial index and Female Sexual Function Index scores were statistically insignificant, but considering the magnitude the findings may imply clinical significance. Systolic blood pressure and pulse wave velocity were not associated with sexual function.ConclusionsThis study suggested a plausible association between higher diastolic blood pressure and female sexual function, but considering clinical significance our findings suggest an association between higher ankle–brachial index and good sexual function in women in their 60s.

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“…The selected confounders are shown to be associated both with sexual function and cardiovascular health 3,7,28–35 . Age was reported in years.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Associations between arterial health and sexual function in women aged 60–64 years

Virkkunen,

Kero,

Koivisto

et al. 2024

Acta Obstet Gynecol Scand

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“…The RAIN protocol functions in the capacity of a comprehensive review and meta-analysis strategy, utilizing the STROBE method to tackle a specific medical question. [212], [213], [214]…”

Section: Other Treatment Strategymentioning

confidence: 99%

Graph Attention Networks for Drug Combination Discovery: Targeting Pancreatic Cancer Genes with RAIN Protocol

Parichehreh,

Kiaei,

Boush

et al. 2024

Preprint

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BackgroundMalignant neoplasm of the pancreas (MNP), a highly lethal illness with bleak outlook and few therapeutic avenues, entails numerous cellular transformations. These include irregular proliferation of ductal cells, activation of stellate cells, initiation of epithelial-to-mesenchymal transition, and changes in cell shape, movement, and attachment. Discovering potent drug cocktails capable of addressing the genetic and protein factors underlying pancreatic cancer’s development is formidable due to the disease’s intricate and varied nature.MethodIn this study, we introduce a fresh model utilizing Graph Attention Networks (GATs) to pinpoint potential drug pairings with synergistic effects for MNP, following the RAIN protocol. This protocol comprises three primary stages: Initially, employing Graph Neural Network (GNN) to suggest drug combinations for disease management by acquiring embedding vectors of drugs and proteins from a diverse knowledge graph encompassing various biomedical data types, such as drug-protein interactions, gene expression, and drug-target interactions. Subsequently, leveraging natural language processing to gather pertinent articles from clinical trials incorporating the previously recommended drugs. Finally, conducting network meta-analysis to assess the relative effectiveness of these drug combinations.ResultWe implemented our approach on a network dataset featuring drugs and genes as nodes, connected by edges representing their respective p-values. Our GAT model identified Gemcitabine, Pancrelipase Amylase, and Octreotide as the optimal drug combination for targeting the human genes/proteins associated with this cancer. Subsequent scrutiny of clinical trials and literature confirmed the validity of our findings. Additionally, network meta-analysis confirmed the efficacy of these medications concerning the pertinent genes.ConclusionBy employing GAT within the RAIN protocol, our approach represents a novel and efficient method for recommending prominent drug combinations to target proteins/genes associated with pancreatic cancer. This technique has the potential to aid healthcare professionals and researchers in identifying optimal treatments for patients while also unveiling underlying disease mechanisms.HighlightsGraph Attention Networks (GATs) used to recommend drug combinations for pancreatic cancerRAIN protocol applied to extract relevant information from clinical trials and literatureGemcitabine, Pancrelipase Amylase, and Octreotide identified as optimal drug combinationNetwork meta-analysis confirmed the effectiveness of the drug combination on gene targetsNovel and efficient method for drug discovery and disease mechanism elucidationAbstract Figure

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“…The executive protocol for this paper is based on RAIN (Mohammadi et al, 2021). Numerous research studies have employed the RAIN protocol as a framework for investigating various psychological and emotional phenomena (Kiaei et al, 2022(Kiaei et al, , 2023Salari et al, 2023Salari et al, , 2022aSalari et al, , 2022bSalari et al, , 2021.…”

Section: Quality Evaluationmentioning

confidence: 99%

Drug combinations proposed by machine learning on genes/proteins to improve the efficacy of Tecovirimat in the treatment of Monkeypox: A Systematic Review and Network Meta-analysis

Boush

Kiaei

Safaei

et al. 2023

Preprint

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Background: The World Health Organization (WHO) describes Monkeypox as a viral zoonosis, or an animal-to-human virus transmission, with symptoms comparable to those of past smallpox patients but clinically less severe. This study's objective is to assess the results of previous investigations on the best drug combinations for treating Monkeypox. Method: The pharmacological combinations used to treat monkeypox sickness have been researched in two stages for this systematic review and network meta-analysis. To begin with, a certain machine learning technique is used to extract the medication combinations from the researched articles offered on science databases, including Scopus, PubMed, Web of Science (ISI), Science Direct, Embase, and Google Scholar. Second, the tested medicine combinations will have been proven. Results: The results of this study show that the p-value between the proposed drug combination and Monkeypox for scenarios 1 to 5 were 0.108, 0.042, 0.023, 0.018, and 0.015, respectively. Scenario i is the combination of the first i suggested drugs for treating Monkeypox. This has led to a 720 percent increase in the proposed drug combination's efficacy in treating Monkeypox. Conclusion: The suggested drug combination decreases the p-value between MonkeyPox and the genes as potential targets for Monkeypox progression, which leads to an improvement in the treatment of Monkeypox. Therefore, using the right combination of drugs is important in improving the community's health and reducing per capita treatment costs. Keywords: Genes, Biological data, Drug Combination, Systematic Review, Network Meta-analysis, Machine Learning, MonkeyPox.

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The effects of smoking on female sexual dysfunction: a systematic review and meta-analysis

Cited by 17 publications

References 30 publications

Associations between arterial health and sexual function in women aged 60–64 years

Associations between arterial health and sexual function in women aged 60–64 years

Graph Attention Networks for Drug Combination Discovery: Targeting Pancreatic Cancer Genes with RAIN Protocol

Drug combinations proposed by machine learning on genes/proteins to improve the efficacy of Tecovirimat in the treatment of Monkeypox: A Systematic Review and Network Meta-analysis

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