Does menopause hormone therapy improve symptoms of depression? Findings from a specialized menopause clinic.

OBJECTIVE: Depressive symptoms are commonly reported during the perimenopause and in the early postmenopausal years. Although menopausal hormone therapy (MHT) is considered the most effective treatment option for vasomotor symptoms, its effect on mood-related symptoms is less established. This study aims to assess interval change in depressive symptoms after initiation of MHT treatment in women seeking care at a Canadian specialized menopause clinic. METHODS: Women and female-presenting people attending the St. Joseph's Healthcare Menopause Clinic in Hamilton, Ontario, were invited to participate in this study. Participants (n = 170) completed a self-report questionnaire, which included their medical history as well as validated tools for bothersome symptoms at their initial visit. A shortened version was administered at the follow-up visit 3 to 12 months later with the same validated tools. We sought to examine interval changes on the Center for Epidemiological Studies Depression Scale based on type of treatment used and MHT dose, while controlling for relevant demographic variables (smoking, education level, age). RESULTS: There was a high rate of depressive symptoms in those seeking specialized menopause care (62%). MHT use was associated with significantly improved depressive symptoms, both alone and in addition to an antidepressant medication ( P < 0.001). Younger age, lower education attainment, and smoking were all associated with higher depression scores. CONCLUSION: This study supports the use of MHT to improve depressive symptoms experienced by those seeking specialized menopause care. Further investigation into timing of treatment initiation may facilitate a personalized treatment approach to improve quality of life of women in the peri- and postmenopausal years.

The association of depressive symptoms and female sexual functioning in the menopause transition: a cross-sectional study.

OBJECTIVE: Sexual dysfunction is very common among middle-aged females. Several factors are considered to influence sexual functioning, including reproductive aging and associated physiological changes as well as life stressors, mental health, and other socioeconomic influences. The objectives of this study are to evaluate the effect of current depressive symptoms on sexual functioning during menopause and to further analyze whether socioeconomic status, age, and antidepressant usage impact this association. METHODS: Perimenopausal and postmenopausal women aged 40 to 65 years seeking treatment from a specialized menopause clinic completed a self-report survey with the main outcome measure being the 19-item Female Sexual Function Index quantifying sexual dysfunction. We used the 10-item Center for Epidemiological Studies Depression Scale to estimate a major depressive episode. Statistical analyses were completed to assess the potential associations of socioeconomic factors, age, and antidepressant usage. RESULTS: Of the 269 participants, 61.3% met criteria for a major depressive episode and 67.0% had low sexual function. As predicted, women currently experiencing depressive symptoms had a greater risk of low sexual function during perimenopause and postmenopause. Antidepressant usage, low household income, being postmenopausal, and age also predicted low sexual function. CONCLUSIONS: Among perimenopausal and postmenopausal women, current depressive symptoms were associated with low sexual function. A biopsychosocial approach should be considered when exploring effective treatment strategies for sexual concerns among midlife women.

Association of infertility with type and timing of menopause: a prospective cohort study.

STUDY QUESTION: What is the association between past infertility and the type and timing of menopause in midlife women? SUMMARY ANSWER: Women with a history of infertility were more likely to experience surgical menopause overall and had elevated risk of earlier surgical menopause until age 43 years but experienced no differences in the timing of natural menopause. WHAT IS KNOWN ALREADY: Infertility is experienced by 12-25% of women and is thought to reveal a propensity for poor health outcomes, such as chronic illness, later in life. However, little is known about whether infertility is linked with characteristics of the menopausal transition as women age, despite possible shared underlying pathways involving ovarian function and gynecologic disease. STUDY DESIGN, SIZE, DURATION: Secondary analysis of a prospective cohort study of 13 243 midlife females recruited in Phase 1 of the Alberta's Tomorrow Project (Alberta, Canada) and followed approximately every 4 years (2000-2022). PARTICIPANTS/MATERIALS, SETTING, METHODS: Data were collected through standardized self-report questionnaires. History of infertility, defined as ever trying to become pregnant for more than 1 year without conceiving, was measured at baseline. Menopause characteristics were measured at each study follow-up. Menopause type was defined as premenopause, natural menopause, surgical menopause (bilateral oophorectomy), or indeterminate menopause (premenopausal hysterectomy with ovarian conservation). Timing of natural menopause was defined as the age at 1 full year after the final menstrual period, and timing of surgical and indeterminate menopause was defined as the age at the time of surgery. We used flexible parametric survival analysis for the outcome of menopause timing with age as the underlying time scale and multinomial logistic regression for the outcome of menopause type. Multivariable models controlled for race/ethnicity, education, parity, previous pregnancy loss, and smoking. Sensitivity analyses additionally accounted for birth history, menopausal hormone therapy, body mass index, chronic medical conditions, and age at baseline. MAIN RESULTS AND THE ROLE OF CHANCE: Overall, 18.2% of women reported a history of infertility. Past infertility was associated with earlier timing of surgical menopause exclusively before age 43 years (age 35: adjusted hazard ratio 3.13, 95% CI 1.95-5.02; age 40: adjusted hazard ratio 1.83, 95% CI 1.40-2.40; age 45: adjusted hazard ratio 1.13, 95% CI 0.87-1.46) as well as greater odds of experiencing surgical menopause compared to natural menopause (adjusted odds ratio 1.40, 95% CI 1.18-1.66). Infertility was not associated with the timing of natural or indeterminate menopause. LIMITATIONS, REASONS FOR CAUTION: Information on the underlying cause of infertility and related interventions was not collected, which precluded us from disentangling whether associations differed by infertility cause and treatment. Residual confounding is possible given that some covariates were measured at baseline and may not have temporally preceded infertility. WIDER IMPLICATIONS OF THE FINDINGS: Women with a history of infertility were more likely to experience early surgical menopause and may therefore benefit from preemptive screening and treatment for gynecologic diseases to reduce bilateral oophorectomy, where clinically appropriate, and its associated health risks in midlife. Moreover, the lack of association between infertility and timing of natural menopause adds to the emerging knowledge that diminishing ovarian reserve does not appear to be a primary biological mechanism of infertility nor its downstream implications for women's health. STUDY FUNDING/COMPETING INTEREST(S): Alberta's Tomorrow Project is only possible due to the commitment of its research participants, its staff and its funders: Alberta Health, Alberta Cancer Foundation, Canadian Partnership Against Cancer and Health Canada, and substantial in-kind funding from Alberta Health Services. The views expressed herein represent the views of the author(s) and not of Alberta's Tomorrow Project or any of its funders. This secondary analysis is funded by Project Grant Priority Funding in Women's Health Research from the Canadian Institutes of Health Research (Grant no. 491439). N.V.S. is supported by a Banting Postdoctoral Fellowship from the Canadian Institutes of Health Research. H.K.B. is supported by the Canada Research Chairs Program. E.A.B. is supported by an Early Career Investigator Award in Maternal, Reproductive, Child and Youth Health from the Canadian Institutes of Health Research. A.K.S. has received honoraria from Pfizer, Lupin, Bio-Syent, and Eisai and has received grant funding from Pfizer. N.V.S., H.K.B., and E.A.B. have no conflicts of interest to report. TRIAL REGISTRATION NUMBER: N/A.

Prenatal cannabis use and its impact on offspring neuro-behavioural outcomes: A systematic review.

Introduction: Cannabis is a widely used substance in pregnancy, yet there is a paucity of literature addressing the neuro-behavioural consequences for prenatally exposed children. Our systematic review synthesizes currently available data for the impact of prenatal cannabis use on offspring intelligence and cognitive functioning. Methods: MEDLINE, EMBASE, PsychINFO, CINAHL, and Clinicaltrials.gov were searched. Observational studies comparing prenatal cannabis use to controls were included. Offspring neuro-behavioural outcomes were grouped in prespecified domains of (1) intelligence and (2) cognitive functioning. Random-effect models were performed for meta-analyses when at least three studies reported the same outcome. All others were summarized qualitatively. GRADE (Grading of Recommendations, Assessment, Development and Evaluations) framework was used to assess evidence certainty. Results: Of the 1982 reviewed studies (n = 523,107 patients), 28 were included. Significant heterogeneity and cohort redundancy limited meta-analysis. Very low-quality evidence from pooled analyses showed no significant associations between prenatal cannabis exposure and attention [standardized mean difference = -0.27 (95% CI = -0.60 to 0.07)], global intelligence quotient [-0.16 (-0.42 to 0.10)], reading [-0.05 (-0.29 to 0.20)], written comprehension [-0.09 (-0.40 to 0.22)], spelling [-0.04 (-0.26 to 0.17)], and mathematics [-0.01 (-0.15 to 0.13)]. No significant associations were found between prenatal cannabis exposure for all other outcomes. Individual studies reported significant differences between the heavy use groups and non-exposed, although this did not prove to be significant when outcomes were pooled. Conclusions: The current review did not find a clear association between prenatal cannabis use and offspring neuro-behavioural outcomes. However, evidence was low quality and heterogenous. Further prospective investigation is needed to elucidate any potential association between prenatal cannabis use and long-term neuro-developmental outcomes.

Cannabis use during lactation may alter the composition of human breast milk.

BACKGROUND: Cannabis is often used by women to manage symptoms of morning sickness during pregnancy, and postpartum stress and anxiety. While exclusive breastfeeding has been recommended for the first 6 months of an infant's life, the presence of cannabinoids in the milk of cannabis users complicates this recommendation. The objective of this study was to investigate the effect of maternal cannabis use on changes in the levels of macronutrients and bioactive factors in breast milk. METHODS: Milk was collected from women who were 6-8 weeks postpartum and were either using cannabis post-delivery, had used cannabis during pregnancy, or were non-users. Levels of cannabinoids, macronutrients, lactose, and SIgA were assessed in the milk of all subjects. RESULTS: THC was detected in the milk of women who reported cannabis use during lactation (n = 13, median: 22 ng/mL). Carboxy-THC, 11-hydroxy-THC, CBD, and CBN were also detected in the milk of women who used cannabis postpartum. Relative to non-users (n = 17), lactose levels were higher and SIgA levels were significantly lower in the milk of subjects who used cannabis during lactation (n = 14). CONCLUSIONS: The presence of cannabinoids, along with altered lactose and SIgA levels in the milk of cannabis users, may have implications for infant health. IMPACT: Metabolites of cannabis are found in breast milk and can accumulate in higher concentrations with ongoing consumption, which is concerning for potential exposure among infants born to mothers who consume cannabis. This work reports that lactose levels are increased and SIgA levels are decreased in the breast milk of cannabis users, relative to the milk of non-users. Change in levels of lactose and SIgA in the milk of cannabis users may have significant implications on infant health, which must be investigated in the future to better inform mothers.

Impact of lifetime lactation on the risk and duration of frequent vasomotor symptoms: A longitudinal dose-response analysis.

OBJECTIVE: To examine the association between lifetime lactation and risk and duration of frequent vasomotor symptoms (VMS). DESIGN: Prospective cohort. SETTING: USA, 1995-2008. SAMPLE: 2356 parous midlife women in the Study of Women's Health Across the Nation. METHODS: Lifetime lactation was defined as the duration of breastfeeding across all births in months. We used generalised estimating equations to analyse risk of frequent VMS and Cox regression to analyse duration of frequent VMS in years. MAIN OUTCOME MEASURES: Frequent VMS (hot flashes and night sweats) were measured annually for 10 years, defined as occurring ≥6 days in the past 2 weeks. RESULTS: Overall, 57.1% of women reported hot flashes and 43.0% reported night sweats during follow-up. Lifetime lactation was inversely associated with hot flashes plateauing at 12 months of breastfeeding (6 months: adjusted odds ratio [AOR] 0.85, 95% confidence interval (CI) 0.75-0.96; 12 months: AOR 0.78, 95% CI 0.65-0.93) and was inversely associated with night sweats in a downward linear fashion (6 months: AOR 0.93, 95% CI 0.81-1.08; 18 months: AOR 0.82, 95% CI 0.67-1.02; 30 months: AOR 0.73, 95% CI 0.56-0.97). Lifetime lactation was associated with shorter duration of hot flashes and night sweats in a quadratic (bell-shaped) fashion. The association was strongest at 12-18 months of breastfeeding and significant for hot flashes (6 months: adjusted hazard ratio [AHR] 1.35, 95% CI 1.11-1.65; 18 months: AHR 1.54, 95% CI 1.16-2.03; 30 months: AHR 1.18, 95% CI 0.83-1.68). CONCLUSIONS: Longer lifetime lactation is associated with decreased risk and duration of frequent VMS.

Roles of Hormone Replacement Therapy and Menopause on Osteoarthritis and Cardiovascular Disease Outcomes: A Narrative Review.

Osteoarthritis (OA) is a highly prevalent condition characterized by degradation of the joints. OA and cardiovascular disease (CVD) are leading contributors to disease burden worldwide, with a high level of overlap between the risk factors and occurrence of both conditions. Chief among the risk factors that contribute to OA and CVD are sex and age, which are both independent and interacting traits. Specifically, the prevalence of both conditions is higher in older women, which may be mediated by the occurrence of menopause. Menopause represents a significant transition in a women's life, and the rapid decline in circulating sex hormones, estrogen and progesterone, leads to complex physiological changes. Declines in hormone levels may partially explain the increase in prevalence of OA and CVD in post-menopausal women. In theory, the use of hormone therapy (HT) may buffer adverse effects of menopause; however, it is unclear whether HT offers protective effects for the onset or progression of these diseases. Studies have shown mixed results when describing the influence of HT on disease risk among post-menopausal women, which warrants further exploration. The roles that increasing age, female sex, HT, and CVD play in OA risk demonstrate that OA is a multifaceted condition. This review provides a timely consolidation of current literature and suggests aims for future research directions to bridge gaps in the understanding of how OA, CVD, and HT interact in post-menopausal women.

Association of lifetime lactation and age at natural menopause: a prospective cohort study.

OBJECTIVE: The aim of this study was to examine the association between duration of lifetime lactation and age at natural menopause. METHODS: In this prospective cohort study, we analyzed parous premenopausal women in the multiethnic Study of Women's Health Across the Nation who were followed approximately annually for 10 years (1995-2008). Lifetime lactation was defined as the duration of breastfeeding across all births in months. Age at natural menopause was defined as age in years after 12 consecutive months of amenorrhea after the final menstrual period for no other reported cause. We used Cox proportional hazard models to analyze time to natural menopause with age as the underlying time scale. Multivariable models controlled for education, race/ethnicity, parity, smoking, body mass index, and oral contraceptive use. RESULTS: Among 2,377 women, 52.6% experienced natural menopause during follow-up and reported a valid final menstrual period date. The small, crude association between lifetime lactation up to 24 months and later age at natural menopause attenuated to nonsignificance in adjusted models (6 months: adjusted hazard ratio [AHR], 0.96; 95% confidence interval (CI), 0.87-1.06; 12 months: AHR, 0.95; 95% CI, 0.82-1.11; 18 months: AHR, 0.96; 95% CI, 0.82-1.13; 24 months: AHR, 0.99; 95% CI, 0.84-1.16). CONCLUSIONS: Duration of lifetime lactation was not associated with age at natural menopause after controlling for sociodemographic characteristics.

Behavioral interventions for improving sleep outcomes in menopausal women: a systematic review and meta-analysis.

IMPORTANCE: Perimenopausal and postmenopausal women commonly report sleep disruption and insomnia. Behavioral interventions may be safe alternatives for patients who are unwilling to begin pharmacological treatments because of adverse effects, contraindications, or personal preference. OBJECTIVE: The primary objective is to assess the efficacy of behavioral interventions on sleep outcomes among perimenopausal and postmenopausal women, as measured using standardized scales and objective methods (polysomnography, actigraphy). The secondary objective is to evaluate the safety of these methods through occurrence of adverse events. EVIDENCE REVIEW: Searches were performed within MEDLINE (OVID interface, 1946 onward), Embase (OVID interface, 1974 onward), Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, and Web of Science (Core collection) using a search strategy developed in consultation with a health sciences librarian. Title/abstract and full-text screenings were performed in duplicate, and relevant studies were selected based on inclusion and exclusion criteria set to identify randomized controlled trials evaluating the effects of behavioral interventions on sleep quality. Risk of bias assessments were done using the Cochrane Risk of Bias 2 tool, and the Grading of Recommendations Assessment, Development and Evaluation approach was used to assess the certainty of the body of evidence. Data were pooled in a meta-analysis using a random-effects model. FINDINGS: Nineteen articles reporting results from 16 randomized controlled trials were included, representing a total of 2,108 perimenopausal and postmenopausal women. Overall, behavioral interventions showed a statistically significant effect on sleep outcomes (standardized mean difference [SMD], -0.62; 95% confidence interval [CI], -0.88 to -0.35; I2 = 93.4%). Subgroup analyses revealed that cognitive behavioral therapy (SMD, -0.40; 95% CI, -0.70 to -0.11; I2 = 72.7%), physical exercise (SMD, -0.57; 95% CI, -0.94 to -0.21; I2 = 94.0%), and mindfulness/relaxation (SMD, -1.28; 95% CI, -2.20 to -0.37; I2 = 96.0%) improved sleep, as measured using both subjective (eg, Pittsburg Sleep Quality Index) and objective measures. Low-intensity (SMD, -0.91; 95% CI, -1.59 to -0.24; I2 = 96.8) and moderate-intensity exercise (SMD, -0.21; 95% CI, -0.34 to -0.08; I2 = 0.0%) also improved sleep outcomes. No serious adverse events were reported. Overall risk of bias ranged from some concern to serious, and the certainty of the body of evidence was assessed to be of very low quality. CONCLUSIONS AND RELEVANCE: This meta-analysis provides evidence that behavioral interventions, specifically, cognitive behavioral therapy, physical exercise, and mindfulness/relaxation, are effective treatments for improving sleep outcomes among perimenopausal and postmenopausal women.

How are Canadian cannabis dispensaries counselling breastfeeding consumers?

Objectives: This study aimed to identify recommendations given to breastfeeding individuals by Canadian cannabis dispensary employees, since the legalization of recreational cannabis in 2018. Methods: This was a nationwide cross-sectional study conducted from November 2020 to January 2021. A mystery caller approach was used to identify recommendations given to breastfeeding individuals seeking a product for "relaxation." This study was modelled on similar studies which assessed recommendations given to pregnant women looking for cannabis products to manage nausea and vomiting (Vastis V, Shea AK, Vincent S, Metz TD. 275: Are canadian cannabis dispensaries counselling pregnant women appropriately? Am. J. Obstet. Gynecol. 2020;222: S187.(Abst). Lusero I, Paltrow LM, Rosenbloom N. Recommendations from cannabis dispensaries about first-trimester cannabis use Obstet Gynecol 2018;132:781-2.). The primary outcome was the recommendation of a cannabis product. Secondary outcomes included stated benefits of cannabis, recommended discussion with health care provider, length of call, rationale for recommendation, and reported source of information on which the recommendation was based. Results: The majority (79.4%) of employees of the 714 Canadian dispensaries contacted recommended against a cannabis product for "relaxation" while breastfeeding. The recommendations from dispensary employees were often (80%) provided without a specific reason, whereas a minority referenced published research (2%) and opinion (17.6%). Cannabis products were rarely (3.3%) classified as safe in breastfeeding. Approximately 76.6% of dispensary employees recommended contacting a health care provider, while 2.4% recommended against. Conclusions: Although a high proportion of dispensary employees recommended against using a cannabis product during lactation, there were still 20.6% that did recommend use, which contrasts the current public health guidelines and is not supported by the paediatric and obstetric societies. These findings highlight the need for further education about the safety of cannabis products while breastfeeding.

A method for AI assisted human interpretation of neonatal EEG.

The study proposes a novel method to empower healthcare professionals to interact and leverage AI decision support in an intuitive manner using auditory senses. The method's suitability is assessed through acoustic detection of the presence of neonatal seizures in electroencephalography (EEG). Neurophysiologists use EEG recordings to identify seizures visually. However, neurophysiological expertise is expensive and not available 24/7, even in tertiary hospitals. Other neonatal and pediatric medical professionals (nurses, doctors, etc.) can make erroneous interpretations of highly complex EEG signals. While artificial intelligence (AI) has been widely used to provide objective decision support for EEG analysis, AI decisions are not always explainable. This work developed a solution to combine AI algorithms with a human-centric intuitive EEG interpretation method. Specifically, EEG is converted to sound using an AI-driven attention mechanism. The perceptual characteristics of seizure events can be heard using this method, and an hour of EEG can be analysed in five seconds. A survey that has been conducted among targeted end-users on a publicly available dataset has demonstrated that not only does it drastically reduce the burden of reviewing the EEG data, but also the obtained accuracy is on par with experienced neurophysiologists trained to interpret neonatal EEG. It is also shown that the proposed communion of a medical professional and AI outperforms AI alone by empowering the human with little or no experience to leverage AI attention mechanisms to enhance the perceptual characteristics of seizure events.

An EEG analysis framework through AI and sonification on low power IoT edge devices.

This study explores the feasibility of implementation of an analysis framework of neonatal EEG, including ML, sonification and intuitive visualization, on a low power IoT edge device. Electroencephalography (EEG) analysis is a very important tool to detect brain disorders. Neonatal seizure detection is a known, challenging problem. Under-resourced communities across the globe are particularly affected by the cost associated with EEG analysis and interpretation. Machine learning (ML) techniques have been successfully utilized to automate seizure detection in neonatal EEG, in order to assist a healthcare professional in visual analysis. Several usage scenarios are reviewed in this study. It is shown that both sonification and ML can be efficiently implemented on low-power edge platforms without any loss of accuracy. The developed platform can be easily expanded to address EEG analysis applications in neonatal and adult population.

Towards Deeper Neural Networks for Neonatal Seizure Detection.

Machine learning and more recently deep learning have become valuable tools in clinical decision making for neonatal seizure detection. This work proposes a deep neural network architecture which is capable of extracting information from long segments of EEG. Residual connections as well as data augmentation and a more robust optimizer are efficiently exploited to train a deeper architecture with an increased receptive field and longer EEG input. The proposed system is tested on a large clinical dataset of 4,570 hours of duration and benchmarked on a publicly available Helsinki dataset of 112 hours duration. The performance has improved from an AUC of 95.41% to an AUC of 97.73% when compared to a deep learning baseline.

Guideline No. 422c: Menopause: Mood, Sleep, and Cognition.

OBJECTIVE: Provide strategies for improving the care of perimenopausal and postmenopausal women based on the most recent published evidence. TARGET POPULATION: Perimenopausal and postmenopausal women. BENEFITS, HARMS, AND COSTS: Target population will benefit from the most recent published scientific evidence provided via the information from their health care provider. No harms or costs are involved with this information since women will have the opportunity to choose among the different therapeutic options for the management of the symptoms and morbidities associated with menopause, including the option to choose no treatment. EVIDENCE: Databases consulted were PubMed, MEDLINE, and the Cochrane Library for the years 2002-2020, and MeSH search terms were specific for each topic developed through the 7 chapters. VALIDATION METHODS: The authors rated the quality of evidence and strength of recommendations using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. See online Appendix A (Tables A1 for definitions and A2 for interpretations of strong and weak recommendations). INTENDED AUDIENCE: physicians, including gynaecologists, obstetricians, family physicians, internists, emergency medicine specialists; nurses, including registered nurses and nurse practitioners; pharmacists; medical trainees, including medical students, residents, fellows; and other providers of health care for the target population. SUMMARY STATEMENTS: RECOMMENDATIONS.

Directive clinique n° 422c : Ménopause : Humeur, sommeil et cognition.

OBJECTIF: Proposer des stratégies fondées sur les plus récentes données publiées pour améliorer les soins aux femmes ménopausées ou en périménopause. POPULATION CIBLE: Les femmes ménopausées ou en périménopause. BéNéFICES, RISQUES ET COûTS: La population cible bénéficiera des plus récentes données scientifiques publiées communiquées par leurs fournisseurs de soins de santé. Aucun coût ni préjudice ne sont associés à cette information, car les femmes seront libres de choisir parmi les différentes options thérapeutiques, y compris le statu quo, pour la prise en charge des symptômes et morbidités associés à la ménopause. DONNéES PROBANTES: Les auteurs ont interrogé les bases de données PubMed, MEDLINE et Cochrane Library pour extraire des articles publiés entre 2002 et 2020 en utilisant des termes MeSH spécifiques à chacun des sujets abordés dans les 7 chapitres. MéTHODES DE VALIDATION: Les auteurs ont évalué la qualité des données probantes et la force des recommandations en utilisant l'approche d'évaluation, de développement et d'évaluation (GRADE). Voir l'annexe A en ligne (tableau A1 pour les définitions et tableau A2 pour l'interprétation des recommandations fortes et conditionnelles [faibles]). PROFESSIONNELS CONCERNéS: gynécologues, obstétriciens, médecins de famille, internistes, urgentologues, infirmières (autorisées et praticiennes), pharmaciens, stagiaires (étudiants en médecine, résidents, moniteurs cliniques) et autres fournisseurs de soins de santé pour la population cible. DÉCLARATIONS SOMMAIRES: RECOMMANDATIONS.

Directive clinique n° 422c: ménopause: humeur, sommeil et cognition / Guideline No. 422c: Menopause: Mood, Sleep, and Cognition

Proposer des stratégies fondées sur les plus récentes données publiées pour améliorer les soins aux femmes ménopausées ou en périménopause. Les femmes ménopausées ou en périménopause. La population cible bénéficiera des plus récentes données scientifiques publiées communiquées par leurs fournisseurs de soins de santé. Aucun coût ni préjudice ne sont associés à cette information, car les femmes seront libres de choisir parmi les différentes options thérapeutiques, y compris le statu quo, pour la prise en charge des symptômes et morbidités associés à la ménopause. Les auteurs ont interrogé les bases de données PubMed, MEDLINE et Cochrane Library pour extraire des articles publiés entre 2002 et 2020 en utilisant des termes MeSH spécifiques à chacun des sujets abordés dans les 7 chapitres. Les auteurs ont évalué la qualité des données probantes et la force des recommandations en utilisant l'approche d'évaluation, de développement et d'évaluation (GRADE). Voir l'annexe A en ligne (tableau A1 pour les définitions et tableau A2 pour l'interprétation des recommandations fortes et conditionnelles [faibles]). gynécologues, obstétriciens, médecins de famille, internistes, urgentologues, infirmières (autorisées et praticiennes), pharmaciens, stagiaires (étudiants en médecine, résidents, moniteurs cliniques) et autres fournisseurs de soins de santé pour la population cible.