Citations

Objective: To explore potential differences in physical activity and sedentary behavior volumes and patterns among postmenopausal women with and without premenopausal bilateral oophorectomy (PBO). Methods: Women with a history of PBO (n = 50) and age-matched postmenopausal referent women (n = 50) were recruited. Participants wore accelerometers on both ankles for 7 days. Volume metrics of sedentary behavior and physical activity, such as step counts, active time, and sedentary time, as well as the sedentary behavior and habitual physical activity distribution, and accumulation patterns, were quantified from the accelerometer data and compared between groups. Results: Metrics indicating volume of sedentary behavior and physical activity were not statistically different between groups. PBO was significantly associated with higher variability in stepping bout time ( P = 0.022), indicating a potentially more complex walking pattern. In addition, PBO was significantly associated with lower variability in sedentary break time ( P = 0.012), and lower activity time Gini index ( Z = −2.428, P = 0.015). This suggests that women with PBO may have broken up their sedentary time with shorter and less variable activity bouts, and because they had relatively shorter average daily active time, they might be at a higher risk of subsequent adverse health outcomes such as low bone mineral density. Conclusions: Although there were no differences in overall activity volume, some differences in activity patterns emerged between women with PBO and referent women. The study highlights the need for longitudinal research to understand how physical activity and sedentary behavior patterns evolve in postmenopausal women with a history of PBO.

AbstractINTRODUCTIONIdentifying individuals with dementia is crucial for prevalence estimation and service planning, but reliable, scalable methods are lacking. We developed novel set algorithms using both structured and unstructured electronic health record (EHR) data, applying Diagnostic and Statistical Manual of Mental Disorders criteria for dementia case identification.METHODSOur cohort (n = 1082) included individuals aged ≥ 60 with dementia identified through specialist clinics and a comparison group without dementia. Clinicians from Australia and the United States informed predictor selection. We developed algorithms through a biostatistics stream for structured data and a natural language processing (NLP) stream for text, synthesizing results via logistic regression.RESULTSThe final structured model retained 16 variables (area under the receiver operating characteristic curve [AUC] 0.853, specificity 72.2%, sensitivity 80.6%). NLP classifiers (logistic regression, support vector machine, and random forest models) performed comparably. The final, combined model outperformed all others (AUC = 0.951, P < 0.001 for comparison to structured model).DISCUSSIONEmbedding text‐derived insights within algorithms trained on structured medical data significantly enhances dementia identification capacity.Highlights Algorithmic tools for detection of individuals with dementia are available; however, previous work has used heterogeneous case definitions which are not clinically meaningful, and has relied on proxies such as diagnostic codes or medications for case ascertainment. We used a novel, dual‐stream algorithmic development approach, simultaneously and separately modeling a clinically meaningful outcome (diagnosis of dementia according to specialized clinical impression) using structured and unstructured electronic health record datasets. Our clinically grounded case definition supported the inclusion of key structured variables (such as dementia International Classification of Disease codes and medications) as modeling predictors rather than outcomes. Our algorithms, published in detail to support validation and replication, represent a major step forward in the use of routinely collected data for detection of diagnosed dementia.

Abstract The impact of early-life traumatic experiences on late-life morbidity remains partly unknown. We tested the hypothesis that adverse childhood experiences (ACE) and specifically abuse (physical, verbal or emotional, or sexual) experienced during childhood or early adulthood are associated with a higher rate of accumulation of multi-morbidity in women. Here we show strong evidence in support of the hypothesis. We studied 1,026 women aged 21–45 years randomly selected from the general population in Olmsted County, Minnesota and used the Rochester Epidemiology Project medical records-linkage system to measure the rate of development of 18 chronic conditions. The women had a median age of 41 years at inclusion in the study and were followed historically for a median of 21 years. Women with an ACE score ≥ 2 had higher incidence of 10 of the 18 chronic conditions considered separately and an accelerated accumulation of multi-morbidity measured as a score compared to women with ACE score 0. In addition, women exposed specifically to abuse in childhood or early adulthood had accelerated accumulation of multi-morbidity. We excluded the possible confounding effect of socioeconomic status and explored a series of possible mediation events or characteristics. We discuss several possible biological and social or behavioral mechanisms underlying these associations.

BACKGROUND: Patients with arrhythmogenic mitral valve prolapse syndrome are at increased risk for life-threatening ventricular arrhythmias, but studies have been limited by small sample sizes. We sought to assemble an international arrhythmogenic mitral valve prolapse syndrome registry to delineate the clinical, imaging, and treatment characteristics of patients with arrhythmogenic mitral valve prolapse syndrome who survived sudden cardiac arrest (SCA) or had sustained ventricular tachycardia (VT) or ventricular fibrillation. METHODS: In this descriptive registry, we characterized patients with arrhythmogenic mitral valve prolapse syndrome who survived SCA, sustained VT, or ventricular fibrillation. Deidentified data were abstracted locally and combined centrally. RESULTS: We included 148 patients who had SCA or VT/ventricular fibrillation. Patients had a mean age of 43.7±15.4 years; 68% were women, 73% had bileaflet prolapse, 65% had mitral annular disjunction, 67% had nonsustained VT, and 59% had inferolateral T-wave inversions. Syncope (n=54, 48%) and anterolateral T-wave inversion (n=26, 22%) were relatively common. Catheter ablation was performed in 50 (35%) patients for premature ventricular complexes and in 18 (17.7%) patients for VT. Sites of origin for arrhythmias were commonly in the papillary muscles, fascicles, mitral annulus, and inferior/inferolateral left ventricle. CONCLUSIONS: In this international descriptive registry of patients with arrhythmogenic mitral valve prolapse syndrome and SCA, patients were young, women, and had bileaflet mitral valve prolapse, mitral annular disjunction, inferolateral T-wave inversions, and nonsustained VT. A history of syncope and anterolateral T-wave inversions was relatively common in patients who survived SCA or sustained VT/ventricular fibrillation.

AbstractBackgroundPopulation dementia prevalence is traditionally estimated using cohort studies, surveys, routinely‐collected administrative data, and registries. Hospital Electronic Health Records (EHRs) are comprised of rich structured and unstructured (text) clinical data that are underutilised for this purpose.We aimed to develop a suite of algorithms using routinely‐collected EHR data to reliably identify cases of dementia, as a key step towards incorporating such data in prevalence estimation. Towards this, we developed a novel predictive framework integrating data‐science and biostatistical methods.MethodTraining data were sourced via the National Centre for Healthy Ageing (NCHA) Data Platform, a linked, curated, EHR‐derived data warehouse. Individuals within the platform catchment aged >60 years with confirmed dementia were identified through hospital specialist dementia clinics. A comparison group of individuals aged >60years with EHR records without dementia was recruited from the community.A panel of clinical experts (Neurology, Geriatric Medicine) informed variable and concept selection and guided data cleaning efforts within both streams. Algorithms were developed via two work‐streams; a traditional biostatistical approach to fit logistic regression models using structured data elements, and a data science stream used Natural Language Processing (NLP) to fit models to the unstructured (text) parts of the EHR, for the same individuals.ResultOf 568 individuals (362 with dementia), 434 had clinical notes available. In the data science stream using unstructured data, among a range of NLP derived models, the Random Forest classifier performed best in assigning dementia status, with Area Under the Curve (AUC) 0.95, specificity 90.2% and sensitivity 88.4%. In the biostatistics stream, 15 structured variables were included in the final model, covering demographics, health service attendance, medications, and ICD‐10 Codes, with AUC 0.94, specificity 85.9% and sensitivity 85.6%.ConclusionArtificial intelligence techniques applied to unstructured electronic health data and guided by human clinical expertise may be powerful tools in capturing the presence of dementia, at least comparable to traditional techniques using structured data, and conferring practical and scientific advantages for dementia prevalence estimation. Future validation is required in less crisply delineated real‐world settings.

Abstract INTRODUCTION Premenopausal bilateral oophorectomy (PBO) before the age of 46 years is associated with an increased risk of dementia. We investigated the long‐term effects of PBO performed before age 50 years on amyloid beta (Aβ), tau, and neurodegeneration imaging biomarkers of Alzheimer's disease (AD). METHODS Mayo Clinic Cohort Study of Oophorectomy and Aging‐2 participants were divided into early PBO (< 46 years; n = 61), and late PBO (46–49 years; n = 51) groups and were compared to referent women who did not undergo PBO ( n = 119). RESULTS Early PBO was associated with thinner entorhinal cortex ( p = 0.014), higher tau load at higher levels of Aβ load ( Pp = 0.005), higher Aβ load ( p = 0.026), and smaller temporal lobe cortical thickness ( p = 0.022), only at older ages compared to the referent group. DISCUSSION PBO before the age of 46 years is associated with entorhinal cortex thinning, elevated tau at higher Aβ levels, along with an AD‐like pattern of atrophy at older ages. CLINICAL TRIALS REGISTRATION NCT03821857 sex‐specific effects of endocrine disruption on aging and AD. Highlights Premenopausal bilateral oophorectomy (PBO) before the ages of 46 (early PBO) years and ages 46 to 49 (late PBO) years was studied. Early PBO was associated with reduced entorhinal cortex thickness later in life. Early PBO was associated with greater amyloid beta (Aβ) load at older ages. Early PBO was associated with greater Alzheimer's disease pattern of atrophy at older ages. Early PBO was associated with higher tau load at higher Aβ levels.

Abstract Objectives The aims of the study were to identify conditions diagnosed in at least 10% of midlife women living in the US upper midwest and to assess prevalence by age, race, ethnicity, and sociodemographic status. Methods The Rochester Epidemiology Project was used to conduct a cross-sectional prevalence study of 86,946 women between 40 and 59 years residing in a 27-county region of the United States on January 1, 2020. Diagnostic billing codes were extracted and grouped into broader condition categories using the Clinical Classification System Refined. The prevalence of 424 conditions was calculated by age, race, ethnicity, and area deprivation index quartiles. Logistic regression was used to examine associations between participant characteristics and conditions that affected 10% or more of the study population. Results Twenty-eight conditions affected ≥10% of women, and eight conditions increased by ≥45% between the ages of 40 and 59 (disorders of lipid metabolism, hypertension, sleep/wake disorders, thyroid disorders, esophageal disorders, osteoarthritis, tendon and synovial disorders, and menopausal disorders; all test for trend P < 0.01). Black women had a significantly higher prevalence of hypertension and esophageal disorders at all ages (adjusted P values <0.05). Women living in more deprived areas had a significantly higher prevalence of hyperlipidemia, hypertension, sleep/wake disorders, and esophageal disorders (adjusted P values <0.05). Women living in less deprived areas had a significantly higher prevalence of thyroid disorders at age 40 to 44 and menopausal disorders at ages 50 to 59 (adjusted P values <0.05). Conclusions These data suggest that additional attention should focus on Black women and women with a lower socioeconomic status to ensure that common midlife conditions are diagnosed and treated.

Abstract STUDY QUESTION How should premature/primary ovarian insufficiency (POI) be diagnosed and managed based on the best available evidence from published literature? SUMMARY ANSWER The current guideline provides 145 recommendations on symptoms, diagnosis, causation, sequelae, and treatment of POI. WHAT IS KNOWN ALREADY Premature ovarian insufficiency (POI) presents a significant challenge to women’s health, with far-reaching implications, both physically and emotionally. The potential implications include adverse effects on quality of life; fertility; and bone, cardiovascular, and cognitive health. Although hormone therapy (HT) can mitigate some of these effects, many questions still remain regarding the optimal management of POI. STUDY DESIGN, SIZE, DURATION The guideline was developed according to the structured methodology for development of ESHRE guidelines. Key questions were determined by a group of experts and informed by a scoping survey of women and health care professionals. Literature searches and assessments were then performed. Papers published up to 30 January 2024 and written in English were included in the guideline. An integrity review was conducted for the randomized controlled trials (RCTs) on POI included in the guideline. PARTICIPANTS/MATERIALS, SETTING, METHODS Based on the collected evidence, recommendations were formulated and discussed within the guideline development group until consensus was reached. Women with lived experience of POI informed the recommendations in general, and particularly on those on provision of care. A stakeholder review was organized after finalization of the draft. The final version was approved by the guideline development group and the ESHRE Executive Committee. MAIN RESULTS AND THE ROLE OF CHANCE New data indicate a higher prevalence of POI, 3.5%, than was previously thought. This guideline aims to help health care professionals to apply best practice care for women with POI. The recent update of the POI guideline covers 40 clinical questions on diagnosis of the condition, the different sequelae, including bone, cardiovascular, neurological and sexual function, fertility and general well-being, and treatment options, including HT. The list of clinical questions was expanded from the previous iteration of the guideline (2015) based on the scoping survey and appreciation of emerging knowledge of POI. Questions were added on the role of anti-Müllerian hormone (AMH) in the diagnosis of POI, fertility preservation, muscle health, and specific considerations for HT in iatrogenic POI. Additionally, the topic on complementary treatments was extended with specific focus on non-hormonal treatments and lifestyle management options. Significant changes from the previous 2015 guideline include the recommendations that only one elevated FSH &gt;25 IU is required for diagnosis of POI, and guidance that AMH testing, repeat FSH measurement, and/or AMH may be required where there is diagnostic uncertainty. Recommendations were also updated regarding genetic testing, estrogen doses and regimens, use of the combined oral contraceptive and testosterone therapy. Women with lived experience of POI informed the recommendations on provision of care. LIMITATIONS, REASONS FOR CAUTION The guideline describes different management options, but it must be acknowledged that for most of these options, supporting evidence is limited for POI. WIDER IMPLICATIONS OF THE FINDINGS The guideline provides health care professionals with clear advice on best practice in POI care, based on the best evidence currently available. In addition, a list of research recommendations is provided to guide further studies in POI. STUDY FUNDING/COMPETING INTEREST(S) The guideline was developed and funded by ESHRE, American Society for Reproductive Medicine (ASRM), Centre for Research Excellence in Women's Health in Reproduction Life (CRE-WHiRL), and International Menopause Society (IMS), covering expenses associated with the guideline meetings, literature searches, and dissemination of the guideline. The guideline group members did not receive payments. N.P. declared grants from Bayer Pharma (research and consultancy) and NIHR—research POISE; consulting fees from Abbott, Astellas, Bayer, Besins, Lawley, Mithra, Theramex, Viatris; honoraria from Astellas, Bayer, Besins, Gedeon Richter, Theramex, Viatris; support for attending meetings and/or travel from Astellas, Bayer, Theramex, Viatris; President, International Menopause Society, Medical Advisory Committee member, British Menopause Society, Patron Daisy Network. A.J.V. declared grants from Amgen Australia, Australian NHMRC, and Australian MRFF; consulting fees from IQ Fertility; honoraria from the Australasian Menopause Society; participation on a Data Safety Monitoring Board or Advisory Board of Astellas; Board Member of the International Menopause Society (2020 to current) and Past president of the Australasian Menopause Society (2017–2019); R.A.A. declared grants from Roche (Research support, to institution), and participation on a Data Safety Monitoring Board of Bayer. M.C. declared grants from NHI; payments or honoraria from Up-to-Date (as editor/reviewer); Board Member of American Society of Reproductive Medicine, and of American Gynecological and Obstetrical Society. M.D. declared (NIHR—HTA Reference Number: NIHR133461; NIHR—HTA Reference Number: NIHR128757; Action Medical Research and Borne: GN2818) consulting fees from a small personal medical practice, support for attending meetings and/or travel from ESHRE, Bayer and UCLH special Trustees; Participation on the Advisory Board of the British Menopause Society, UKSTORE project, the Progress Educational Trust, and the Turner Syndrome Support Society UK; Leadership or fiduciary roles in the British Fertility Society (Trustee), Elizabeth Garrett Anderson Hospital Charity (chair of Trustees), and the Essex Wynter charitable trust (Trustee). C.E. declared being Chair of a SIG from the Royal Australian College of General Practitioners Integrative Medicine Specific Interest Group and Program Lead for Next Practice Western Sydney Integrative Health. C.H.G. declared grants from Novo Nordisk Foundation (Nos. NNF15OC0016474 and NNF20OC0060610), sygesikringen danmark (No 2022-0189), and the Independent Research Fund Denmark (Nos. 0134-00406 and 0134-00130B); consulting fees from Novo Nordisk, Merck, and Astra Zeneca. S.K. declared grants from Roche diagnostics. A.K. declared grants from NIH R01 5R01HD101475; consulting fees as Medical Reviewer for Flo and for Healthline; honoraria as Medical Consultant for Summus; support for attending meetings from the Reproductive Scientist Development Program; Society for Reproductive Investigation Council Member and Society for Assisted Reproduction Registry/Validation Chair; R.E.N. declared consulting fees from Astellas, Bayer Pharma, Besins Healthcare, Fidia, Theramex; honoraria from Abbott, Astellas, Exeltis, Fidia, Gedeon Richter, Merck & Co, Novo Nordisk, Shionogi Limited, Theramex, Viatris; payment for expert testimony from Vichy Laboratories; Participation in Data Safety Monitoring Board of Advisory board from Astellas and Bayer Healthcare; President elect of the International Menopause Society (IMS). H.T. declared a grant from NHMRC Centre for Research Excellence for women’s health in reproductive life. A.B. declared being chair of the Daisy Network Charity. The other authors have no conflicts of interest to declare. DISCLAIMER This guideline represents the views of ESHRE, ASRM, CRE-WHiRL, and IMS, which were achieved after careful consideration of the scientific evidence available at the time of preparation. In the absence of scientific evidence on certain aspects, a consensus between the relevant stakeholders has been obtained. Adherence to these clinical practice guidelines does not guarantee a successful or specific outcome, nor does it establish a standard of care. Clinical practice guidelines do not replace the need for application of clinical judgement to each individual presentation, nor variations based on locality and facility type. The collaborating societies make no warranty, expressed or implied, regarding the clinical practice guidelines and specifically exclude any warranties of merchantability and fitness for a particular use or purpose. (Full disclaimer available at www.eshre.eu/guidelines.)