Rocca, Walter A

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 >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.)

Abstract Background Body composition can be accurately quantified from abdominal computed tomography (CT) exams and is a predictor for the development of aging-related conditions and for mortality. However, reference ranges for CT-derived body composition measures of obesity, sarcopenia, and bone loss have yet to be defined in the general population. Methods We identified a population-representative sample of 4 900 persons aged 20 to 89 years who underwent an abdominal CT exam from 2010 to 2020. The sample was constructed using propensity score matching an age and sex stratified sample of persons residing in the 27-county region of Southern Minnesota and Western Wisconsin. The matching included race, ethnicity, education level, region of residence, and the presence of 20 chronic conditions. We used a validated deep learning based algorithm to calculate subcutaneous adipose tissue area, visceral adipose tissue area, skeletal muscle area, skeletal muscle density, vertebral bone area, and vertebral bone density from a CT abdominal section. Results We report CT-based body composition reference ranges on 4 649 persons representative of our geographic region. Older age was associated with a decrease in skeletal muscle area and density, and an increase in visceral adiposity. All chronic conditions were associated with a statistically significant difference in at least one body composition biomarker. The presence of a chronic condition was generally associated with greater subcutaneous and visceral adiposity, and lower muscle density and vertebrae bone density. Conclusions We report reference ranges for CT-based body composition biomarkers in a population-representative cohort of 4 649 persons by age, sex, body mass index, and chronic conditions.

Abstract Objective Adrenal adenomas are commonly encountered in clinical practice. To date, population-based data on their impact on cognition, mental health, and sleep are lacking. We aimed to study possible associations between adrenal adenomas and dementia, psychiatric or sleep disorders. Design Population-based cohort study, Olmsted County, MN, 1995-2017. Methods Patients with adrenal adenoma and absent overt hormone excess were age- and sex-matched 1:1 to a referent person without adrenal adenoma. Outcomes were baseline and incident diagnoses of dementia, psychiatric or sleep disorders, assessed using ICD codes. Results Of 1004 patients with adrenal adenomas, 582 (58%) were women, and median age at diagnosis was 63 years. At baseline, and after adjusting for age, sex, education, BMI, and tobacco use, patients with adenoma had higher odds of depression (adjusted odds ratio, aOR: 1.3, 95% CI, 1.1-1.6), anxiety (aOR: 1.4, 95% CI, 1.1-1.8), and substance abuse (aOR: 2.4, 95% CI, 1.7-3.4) compared to referents. During a median follow-up of 6.8 years, and after adjusting for age, sex, socioeconomic status, BMI, tobacco, and substance abuse, patients demonstrated a higher risk of psychiatric and sleep disorders [adjusted hazard ratio (95% CI)]: depression [1.7 (1.3-2.2)], anxiety [1.4, CI (1.1-1.7)], insomnia [1.4 (1.0-1.9)], sleep-related breathing disorders [1.5 (1.1-1.9)], hypersomnias [2.1 (1.0-4.2)], parasomnias [2.1 (1.0-4.2)], and sleep-related movement disorders [1.5 (1.0-2.1)], but not dementia. Conclusions Patients with adenomas demonstrate a higher incidence of psychiatric and sleep disorders, possibly due to the underlying subtle increase in cortisol secretion.

Objective Ceramides have been associated with several ageing-related conditions but have not been studied as a general biomarker of multimorbidity (MM). Therefore, we determined whether ceramide levels are associated with the rapid development of MM. Design Retrospective cohort study. Setting Mayo Clinic Biobank. Participants 1809 persons in the Mayo Clinic Biobank ≥65 years without MM at the time of enrolment, and with ceramide levels assayed from stored plasma. Primary outcome measure Persons were followed for a median of 5.7 years through their medical records to identify new diagnoses of 20 chronic conditions. The number of new conditions was divided by the person-years of follow-up to calculate the rate of accumulation of new chronic conditions. Results Higher levels of C18:0 and C20:0 were associated with a more rapid rate of accumulation of chronic conditions (C18:0 z score RR: 1.30, 95% CI: 1.10 to 1.53; C20:0 z score RR: 1.26, 95% CI: 1.07 to 1.49). Higher C18:0 and C20:0 levels were also associated with an increased risk of hypertension and coronary artery disease. Conclusions C18:0 and C20:0 were associated with an increased risk of cardiometabolic conditions. When combined with biomarkers specific to other diseases of ageing, these ceramides may be a useful component of a biomarker panel for predicting accelerated ageing.

Background: The Rochester Epidemiology Project (REP) medical records-linkage system offers a unique opportunity to integrate medical and residency data with existing environmental data, to estimate individual-level exposures. Our primary aim was to provide an archetype of this integration. Our secondary aim was to explore the association between groundwater inorganic nitrogen concentration and adverse child and adolescent health outcomes. Methods: We conducted a nested case-control study in children, aged seven to eighteen, from six counties of southeastern Minnesota. Groundwater inorganic nitrogen concentration data were interpolated, to estimate exposure across our study region. Residency data were then overlaid, to estimate individual-level exposure for our entire study population (n = 29,270). Clinical classification software sets of diagnostic codes were used to determine the presence of 21 clinical conditions. Regression models were adjusted for age, sex, race, and rurality. Results: The analyses support further investigation of associations between nitrogen concentration and chronic obstructive pulmonary disease and bronchiectasis (OR: 2.38, CI: 1.64–3.46) among boys and girls, thyroid disorders (OR: 1.44, CI: 1.05–1.99) and suicide and intentional self-inflicted injury (OR: 1.37, CI: >1.00–1.87) among girls, and attention deficit conduct and disruptive behavior disorders (OR: 1.34, CI: 1.24–1.46) among boys. Conclusions: Investigators with environmental health research questions should leverage the well-enumerated population and residency data in the REP.

Objectives Obesity is a potentially modifiable risk factor that has been consistently associated with the development and progression of multi-morbidity (MM). However, obesity may be more problematic for some persons compared to others because of interactions with other risk factors. Therefore, we studied the effect of interactions between patient characteristics and overweight and obesity on the rate of accumulation of MM. Methods We studied 4 cohorts of persons ages 20-, 40-, 60-, and 80-years residing in Olmsted County, Minnesota between 2005 and 2014 using the Rochester Epidemiology Project (REP) medical records-linkage system. Body mass index, sex, race, ethnicity, education, and smoking status were extracted from REP indices. The rate of accumulation of MM was calculated as the number of new chronic conditions accumulated per 10 person years through 2017. Poisson rate regression models were used to identify associations between characteristics and rate of MM accumulation. Additive interactions were summarized using relative excess risk due to interaction, attributable proportion of disease, and the synergy index. Results Greater than additive synergistic associations were observed between female sex and obesity in the 20- and 40-year cohorts, between low education and obesity in the 20-year cohort (both sexes), and between smoking and obesity in the 40-year cohort (both sexes). Conclusions Interventions targeted at women, persons with lower education, and smokers who also have obesity may result in the greatest reduction in the rate of MM accumulation. However, interventions may need to focus on persons prior to mid-life to have the greatest effect.

Objectives To compare the agreement between percentile ranks from 4 multi-morbidity scores. Design Population-based descriptive study. Setting Olmsted County, Minnesota (USA). Participants We used the medical records-linkage system of the Rochester Epidemiology Project (REP; http://www.rochesterproject.org ) to identify all residents of Olmsted County, Minnesota who reached one or more birthdays between 1 January 2005 and 31 December 2014 (10 years). Methods For each person, we calculated 4 multi-morbidity scores using readily available diagnostic code lists from the US Department of Health and Human Services, the Clinical Classifications Software, and the Elixhauser Comorbidity Index. We calculated scores using diagnostic codes received in the 5 years before the index birthday and fit quantile regression models across age and separately by sex to transform unweighted, simple counts of conditions into percentile ranks as compared to peers of same age and of same sex. We compared the percentile ranks of the 4 multi-morbidity scores using intra-class correlation coefficients (ICCs). Results We assessed agreement in 181,553 persons who reached a total of 1,075,433 birthdays at ages 18 years through 85 years during the study period. In general, the percentile ranks of the 4 multi-morbidity scores exhibited high levels of agreement in 6 score-to-score pairwise comparisons. The agreement increased with older age for all pairwise comparisons, and ICCs were consistently greater than 0.65 at ages 50 years and older. Conclusions The assignment of percentile ranks may be a simple and intuitive way to assess the underlying trait of multi-morbidity across studies that use different measures.

Abstract Background Delirium is underdiagnosed in clinical practice and is not routinely coded for billing. Manual chart review can be used to identify the occurrence of delirium; however, it is labor-intensive and impractical for large-scale studies. Natural language processing (NLP) has the capability to process raw text in electronic health records (EHRs) and determine the meaning of the information. We developed and validated NLP algorithms to automatically identify the occurrence of delirium from EHRs. Methods This study used a randomly selected cohort from the population-based Mayo Clinic Biobank (N = 300, age ≥65). We adopted the standardized evidence-based framework confusion assessment method (CAM) to develop and evaluate NLP algorithms to identify the occurrence of delirium using clinical notes in EHRs. Two NLP algorithms were developed based on CAM criteria: one based on the original CAM (NLP-CAM; delirium vs no delirium) and another based on our modified CAM (NLP-mCAM; definite, possible, and no delirium). The sensitivity, specificity, and accuracy were used for concordance in delirium status between NLP algorithms and manual chart review as the gold standard. The prevalence of delirium cases was examined using International Classification of Diseases, 9th Revision (ICD-9), NLP-CAM, and NLP-mCAM. Results NLP-CAM demonstrated a sensitivity, specificity, and accuracy of 0.919, 1.000, and 0.967, respectively. NLP-mCAM demonstrated sensitivity, specificity, and accuracy of 0.827, 0.913, and 0.827, respectively. The prevalence analysis of delirium showed that the NLP-CAM algorithm identified 12 651 (9.4%) delirium patients, the NLP-mCAM algorithm identified 20 611 (15.3%) definite delirium cases, and 10 762 (8.0%) possible cases. Conclusions NLP algorithms based on the standardized evidence-based CAM framework demonstrated high performance in delineating delirium status in an expeditious and cost-effective manner.

ABSTRACTBackground: Limited population‐based information is available on the co‐occurrence of dementia and PD. However, projecting the prevalence of PD with and without dementia during the next 50 years is crucial for planning public‐health and patient‐care initiatives.Objectives: The objective of this study was to project the prevalence of PD with and without dementia in the United States by 2060.Methods: We used the Rochester Epidemiology Project medical records‐linkage system to identify all persons with PD with or without dementia residing in Olmsted County, Minnesota, on January 1, 2006. A movement disorders specialist reviewed the complete medical records of each person to confirm the presence of PD. We calculated the age‐ and sex‐specific prevalence of PD with and without dementia and projected U.S. prevalence through 2060.Results: We identified 296 persons with PD with and without dementia on the prevalence date (187 men, 109 women); the overall prevalence increased with age from 0.01% (30‐39 years) to 2.83% (≥90 years). The prevalence of PD without dementia increased with age from 0.01% (30‐39 years) to 1.25% (≥90 years). The prevalence of PD with dementia increased with age from 0.10% (60‐69 years) to 1.59% (≥90 years). The prevalence was higher in men than in women for all subtypes and all age groups. We project by 2060 an approximate doubling of the number of persons with PD without dementia and a tripling of the number of persons with PD with dementia in the United States.Conclusions: The prevalence of PD with and without dementia increases with age and is higher in men than women. We project that the number of persons with PD in the United States will increase substantially by 2060. © 2018 International Parkinson and Movement Disorder Society

ABSTRACTBackground: The prevalence of patients with PD taking antipsychotics is unknown.Objective: To measure the prevalence of patients with PD taking antipsychotics.Methods: We used the medical records‐linkage system of the Rochester Epidemiology Project to study the use of antipsychotic medication in all persons with Parkinson disease in Olmsted County, Minnesota on 1 January 2006.Results: There were 296 patients with PD in Olmsted County on 1 January 2006. The overall prevalence of antipsychotic use was 9.8% (29 of 296); 95.5% (28 of 29) of the patients had dementia when initiating antipsychotics. The most frequent indication (71.4%; 20 of 28) was psychosis or behavior threatening to the patient or others.Conclusions: The prevalence of antipsychotic use in patients with PD is lower than expected from previously reported cumulative incidences. Dementia is highly prevalent in those starting antipsychotics. Most of the patients on antipsychotics had a reasonable risk‐benefit ratio for taking them. © 2017 International Parkinson and Movement Disorder Society