Identifying Predictor Variables for a Composite Risk Prediction Tool for Gestational Diabetes and Hypertensive Disorders of Pregnancy: A Modified Delphi Study.

A composite cardiometabolic risk prediction tool will support the systematic identification of women at increased cardiometabolic risk during pregnancy to enable early screening and intervention. This study aims to identify and select predictor variables for a composite risk prediction tool for cardiometabolic risk (gestational diabetes mellitus and/or hypertensive disorders of pregnancy) for use in the first trimester. A two-round modified online Delphi study was undertaken. A prior systematic literature review generated fifteen potential predictor variables for inclusion in the tool. Multidisciplinary experts (n = 31) rated the clinical importance of variables in an online survey and nominated additional variables for consideration (Round One). An online meeting (n = 14) was held to deliberate the importance, feasibility and acceptability of collecting variables in early pregnancy. Consensus was reached in a second online survey (Round Two). Overall, 24 variables were considered; 9 were eliminated, and 15 were selected for inclusion in the tool. The final 15 predictor variables related to maternal demographics (age, ethnicity/race), pre-pregnancy history (body mass index, height, history of chronic kidney disease/polycystic ovarian syndrome, family history of diabetes, pre-existing diabetes/hypertension), obstetric history (parity, history of macrosomia/pre-eclampsia/gestational diabetes mellitus), biochemical measures (blood glucose levels), hemodynamic measures (systolic blood pressure). Variables will inform the development of a cardiometabolic risk prediction tool in subsequent research. Evidence-based, clinically relevant and routinely collected variables were selected for a composite cardiometabolic risk prediction tool for early pregnancy.

Systematic review and meta-analysis of pregnancy outcomes in women with polycystic ovary syndrome.

Screening for polycystic ovary syndrome (PCOS) in antenatal care is inadequate, largely owing to the lack of clarity around whether PCOS is an independent risk factor for pregnancy complications. This systematic review and meta-analysis include 104 studies and 106,690 pregnancies in women with and without PCOS from inception until 13th July 2022. We report that women with PCOS are younger and have higher body mass index (BMI) around conception and have greater gestational weight gain. The odds of miscarriage, gestational diabetes mellitus, gestational hypertension, pre-eclampsia and cesarean section are higher in women with PCOS. The increased odds of adverse outcomes in PCOS remain significant when age and BMI are matched and when analyses are restricted to high-quality studies. This work informed the recommendations from the 2023 international evidence-based guideline for the assessment and management of polycystic ovary syndrome, emphasizing that PCOS status should be captured in all women who are planning to, or have recently become pregnant to facilitate prevention of adverse outcomes and improve pregnancy outcomes.

Systematic review and meta-analysis of birth outcomes in women with polycystic ovary syndrome.

It is unclear whether polycystic ovary syndrome (PCOS) is an independent risk factor for adverse birth outcomes in the offspring of affected women. Here, we investigate the association of PCOS with birth outcomes in the offspring of women with PCOS overall and by potential confounders. This systematic review and meta-analysis included 73 studies and 92,881 offspring of women with and without PCOS from inception until 13th July 2022. We report that mothers with PCOS are younger and have higher body mass index (BMI) around conception and have greater gestational weight gain. The odds of preterm birth, fetal growth restriction and low birth weight are higher and mean birthweight is lower in PCOS of which a lower mean birthweight and a higher small for gestational age are probably independent of BMI. This work informed the recommendations from the 2023 international evidence-based guideline for the assessment and management of polycystic ovary syndrome, emphasizing that PCOS status should be captured at pregnancy to identify risk and improve birth outcomes in the offspring.

Exercise in the management of polycystic ovary syndrome: A position statement from Exercise and Sport Science Australia.

Polycystic ovary syndrome (PCOS) is the most prevalent endocrine condition amongst females of reproductive age, leading to lifelong cardiometabolic, reproductive, psychological, and dermatologic symptoms as well as a reduced quality of life. Lifestyle interventions, which can include structured exercise programmes delivered by appropriately trained exercise professionals such as clinical exercise physiologists, are considered first-line strategies in PCOS management due to their therapeutic effects on various health outcomes and quality of life. This position statement builds on the 2023 International Evidence-based Guideline for the Assessment and Management of PCOS and describes the role of the exercise professional in the context of the multidisciplinary care team which includes physicians and allied health professionals. This position statement aims to equip exercise professionals with a broad understanding of the pathophysiology of PCOS, how it is diagnosed and managed in clinical practice, and evidence- and consensus-based recommendations for physical activity and exercise in PCOS management. In line with the physical activity recommendations for the general public, individuals with PCOS should aim to undertake between 150 to 300min of moderate-intensity or 75 to 150min of vigorous-intensity aerobic activity per week, or an equivalent combination of both spread throughout the week. Additionally, muscle-strengthening activities on two non-consecutive days per week are recommended to maintain health and prevent weight gain. For further health benefits and to achieve modest weight loss, individuals with PCOS should aim for a minimum of 250min of moderate-intensity or 150min of vigorous-intensity aerobic activity per week, or an equivalent combination of both spread throughout the week, plus muscle-strengthening activities on two non-consecutive days per week. Adolescents with PCOS should aim for a minimum of 60min moderate- to vigorous-intensity activity each day, incorporating muscle- and bone-strengthening activities three times per week. Finally, exercise professionals should consider the significant psychological burden, including weight stigma, and the high prevalence of comorbidities amongst individuals with PCOS and take appropriate measures to deliver safe and efficacious exercise interventions.

Nurses' experiences of hospital-acquired pressure injury prevention in acute healthcare services in Victoria, Australia: A qualitative study using the Theoretical Domains Framework.

We investigated nurses' experiences of hospital-acquired pressure injury (PI) prevention in acute care services to better understand how PI prevention may be optimised. We used the Theoretical Domains Framework to systematically identify barriers and enablers to evidence-based preventive practices as required by the International Guideline. This study was one element of a complex capacity building project on PI surveillance and prevention within the acute health service partners of Monash Partners Academic Health Science Centre, an accredited academic health partnership located in Melbourne, Australia. We adopted a qualitative descriptive design. We interviewed 32 nurses that provided care in intensive care units, general wards and COVID wards of four acute care services. Nurses were recruited from four large acute care services (three public, one private) located in Melbourne. Most of them worked with patients who were at high risk of hospital-acquired PI on a daily basis. Interview transcripts were coded and analysed using thematic analysis guided by the Theoretical Domains Framework. The domains referred to most frequently by all participants included: Knowledge, Skills, Social/Professional Role and Identity, Beliefs about Capabilities, and Environmental Context and Resources. The key barriers discussed by nurses included gaps in nurses' knowledge and skills related to identification and staging of PI, heavy nursing workload and inadequate staffing levels, stigma and self-blame related to PI identification, and exacerbating impacts of the COVID-19 pandemic. Main facilitators discussed were training programmes, nursing audits and feedback, and teamwork. Participants suggested improvements including accessible and tailored training, visual reminders, and addressing heavy workloads and emotional barriers nurses face. Investing in tailored training initiatives to improve nurses' knowledge and organisational changes to address low level staffing and heavy workloads are urgently needed to support nurses in delivering optimal care and preventing hospital-acquired PI.

Development of a risk prediction model for postpartum onset of type 2 diabetes mellitus, following gestational diabetes; the lifestyle InterVention in gestational diabetes (LIVING) study.

AIMS: This study aimed to develop a prediction model for identifying a woman with gestational diabetes mellitus (GDM) at high risk of type 2 diabetes (T2DM) post-birth. METHODS: Utilising data from 1299 women in the Lifestyle Intervention IN Gestational Diabetes (LIVING) study, two models were developed: one for pregnancy and another for postpartum. Key predictors included glucose test results, medical history, and biometric indicators. RESULTS: Of the initial cohort, 124 women developed T2DM within three years. The study identified seven predictors for the antenatal T2DM risk prediction model and four for the postnatal one. The models demonstrated good to excellent predictive ability, with Area under the ROC Curve (AUC) values of 0.76 (95% CI: 0.72 to 0.80) and 0.85 (95% CI: 0.81 to 0.88) for the antenatal and postnatal models, respectively. Both models underwent rigorous validation, showing minimal optimism in predictive capability. Antenatal model, considering the Youden index optimal cut-off point of 0.096, sensitivity, specificity, and accuracy were measured as 70.97%, 70.81%, and 70.82%, respectively. For the postnatal model, considering the cut-off point 0.086, sensitivity, specificity, and accuracy were measured as 81.40%, 75.60%, and 76.10%, respectively. CONCLUSIONS: These models are effective for predicting T2DM risk in women with GDM, although external validation is recommended before widespread application.

Anti-Müllerian hormone as a diagnostic biomarker for Polycystic Ovary Syndrome (PCOS) and Polycystic Ovarian Morphology (PCOM): a systematic review and meta-analysis.

IMPORTANCE: As part of the 2023 International Evidence-based PCOS Guideline, this meta-analysis investigated the inclusion of Anti-Müllerian Hormone (AMH) in the diagnostic criteria for Polycystic Ovary Syndrome (PCOS). OBJECTIVE: A systematic review and three meta-analyses were performed to answer the following three questions: 1) Is AMH effective to diagnose PCOS in adult women? 2) Is AMH effective to diagnose PCOS in adolescents? 3) Is AMH effective to diagnose PCOM? DATA SOURCES: Searches were conducted in six databases until July 31st 2023. STUDY SELECTION AND SYNTHESIS: Eligible studies were those conducted in humans, published in English and reported sensitivity, specificity, and/or area under the curve. Extracted data included study population, age, body mass index (BMI), AMH assay, cut off value of AMH, sensitivity, specificity, and area under the curve (AUC). Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. Random effects model were used to test diagnostic accuracy. MAIN OUTCOMES: Pooled sensitivity and specificity to use AMH for PCOS diagnosis in adults and adolescents, and for detecting PCOM in adults. RESULTS: Eighty-two studies were included. The adult AMH-PCOS meta-analyses (n = 68) showed a pooled sensitivity and specificity of 0.79 [95% CI 0.76; 0.82; I2 = 86%] and 0.87 [95% CI 0.84; 0.89; I2 = 91%]. The adolescent AMH-PCOS meta-analysis (n = 11) showed a pooled sensitivity and specificity of 0.66 [95% CI 0.58; 0.73; I2 = 74%] and 0.78 [95% CI 0.71; 0.83; I2 = 45%]. The adult AMH-PCOM meta-analysis (n = 7) showed a pooled sensitivity and specificity of 0.79 [95% CI 0.72; 0.85; I2 = 94%] and 0.87 [95% CI 0.78; 0.93; I2 = 94%]. CONCLUSION AND RELEVANCE: This study investigated the most profound change in the 2023 International Evidence-based PCOS Guideline, which now recommends AMH for defining PCOM in adults, in accordance with the diagnostic algorithm. AMH alone is insufficient for PCOS diagnosis and is nonspecific for PCOM in adolescents. Multiple factors influence AMH levels and caused heterogeneity and limitations in this study. Consequently, no international cut off value could be recommended, emphasizing the need for research on more individualized cut offs.

Machine Learning Algorithms Versus Classical Regression Models in Pre-Eclampsia Prediction: A Systematic Review.

PURPOSE OF REVIEW: Machine learning (ML) approaches are an emerging alternative for healthcare risk prediction. We aimed to synthesise the literature on ML and classical regression studies exploring potential prognostic factors and to compare prediction performance for pre-eclampsia. RECENT FINDINGS: From 9382 studies retrieved, 82 were included. Sixty-six publications exclusively reported eighty-four classical regression models to predict variable timing of onset of pre-eclampsia. Another six publications reported purely ML algorithms, whilst another 10 publications reported ML algorithms and classical regression models in the same sample with 8 of 10 findings that ML algorithms outperformed classical regression models. The most frequent prognostic factors were age, pre-pregnancy body mass index, chronic medical conditions, parity, prior history of pre-eclampsia, mean arterial pressure, uterine artery pulsatility index, placental growth factor, and pregnancy-associated plasma protein A. Top performing ML algorithms were random forest (area under the curve (AUC) = 0.94, 95% confidence interval (CI) 0.91-0.96) and extreme gradient boosting (AUC = 0.92, 95% CI 0.90-0.94). The competing risk model had similar performance (AUC = 0.92, 95% CI 0.91-0.92) compared with a neural network. Calibration performance was not reported in the majority of publications. ML algorithms had better performance compared to classical regression models in pre-eclampsia prediction. Random forest and boosting-type algorithms had the best prediction performance. Further research should focus on comparing ML algorithms to classical regression models using the same samples and evaluation metrics to gain insight into their performance. External validation of ML algorithms is warranted to gain insights into their generalisability.

Antenatal oral glucose tolerance test abnormalities in the prediction of future risk of postpartum diabetes in women with gestational diabetes: Results from the LIVING study.

OBJECTIVES: To explore associations between type and number of abnormal glucose values on antenatal oral glucose tolerance test (OGTT) with postpartum diabetes in South Asian women diagnosed with gestational diabetes (GDM) using International Association of the Diabetes and Pregnancy Study Groups criteria. METHODS: This post-hoc evaluation of the Lifestyle Intervention IN Gestational Diabetes (LIVING) study, a randomized controlled trial, was conducted among women with GDM in the index pregnancy, across 19 centers in Bangladesh, India, and Sri Lanka. Postpartum diabetes (outcome) was defined on OGTT, using American Diabetes Association (ADA) criteria. RESULTS: We report data on 1468 women with GDM, aged 30.9 (5.0) years, and with median (interquartile range) follow-up period of 1.8 (1.4-2.4) years after childbirth following the index pregnancy. We found diabetes in 213 (14.5%) women with an incidence of 8.7 (7.6-10.0)/100 women-years. The lowest incidence rate was 3.8/100 women years, in those with an isolated fasting plasma glucose (FPG) abnormality, and highest was 19.0/100 women years in participants with three abnormal values. The adjusted hazard ratios for two and three abnormal values compared to one abnormal value were 1.73 (95% confidence interval [CI], 1.18-2.54; p = .005) and 3.56 (95% CI, 2.46-5.16; p < .001) respectively. The adjusted hazard ratio for the combined (combination of fasting and postglucose load) abnormalities was 2.61 (95% CI, 1.70-4.00; p < .001), compared to isolated abnormal FPG. CONCLUSIONS: Risk of diabetes varied significantly depending upon the type and number of abnormal values on antenatal OGTT. These data may inform future precision medicine approaches such as risk prediction models in identifying women at higher risk and may guide future targeted interventions.

Maternal metabolic conditions as predictors of breastfeeding outcomes: Insights from an Australian cohort study.

INTRODUCTION: Breastfeeding represents an important opportunity to optimize health outcomes for both mother and infant, particularly in the context of maternal metabolic conditions such as diabetes and polycystic ovary syndrome. However, evidence suggests that women affected by these conditions breastfeed at reduced rates and durations. Our aim was to use the large, prospective, community-based Australian Longitudinal Study on Women's Health (ALSWH) to conduct an in-depth exploratory analysis of breastfeeding outcomes in Australian women affected by key maternal metabolic conditions. MATERIAL AND METHODS: Data from 12 920 pregnancies to 5605 women from the 1973-1978 birth cohort of the ALSWH were examined. Univariable and multivariable regression using generalized estimating equation models were applied to assess breastfeeding initiation and duration (outcome measures) in relation to key self-reported maternal metabolic diagnoses (pre-gestational type 1 and type 2 diabetes, gestational diabetes, and polycystic ovary syndrome; main explanatory variables). Key sociodemographic and clinical covariates were also considered. RESULTS: Results showed no significant association between specific maternal metabolic diagnoses (pre-gestational or gestational diabetes, or polycystic ovary syndrome) and breastfeeding outcomes. However, maternal body mass index emerged as a key predictor of suboptimal breastfeeding outcomes. Pregnancies affected by maternal obesity were associated with a 2.1-fold increase in the odds of not initiating breastfeeding, after adjusting for other key variables (95% CI 1.67 to 2.60, p < 0.01). Maternal overweight and obesity were, respectively, associated with an adjusted 1.4-fold (95% CI 1.20 to 1.55, p < 0.01) and 1.8-fold increase (95% CI 1.60 to 2.10, p < 0.01) in the odds of a breastfeeding duration less than 6 months. CONCLUSIONS: Maternal obesity, rather than any specific maternal metabolic condition, appears to be a key predictor of breastfeeding outcomes in Australian women.

Learning together for better health using an evidence-based Learning Health System framework: a case study in stroke.

BACKGROUND: In the context of expanding digital health tools, the health system is ready for Learning Health System (LHS) models. These models, with proper governance and stakeholder engagement, enable the integration of digital infrastructure to provide feedback to all relevant parties including clinicians and consumers on performance against best practice standards, as well as fostering innovation and aligning healthcare with patient needs. The LHS literature primarily includes opinion or consensus-based frameworks and lacks validation or evidence of benefit. Our aim was to outline a rigorously codesigned, evidence-based LHS framework and present a national case study of an LHS-aligned national stroke program that has delivered clinical benefit. MAIN TEXT: Current core components of a LHS involve capturing evidence from communities and stakeholders (quadrant 1), integrating evidence from research findings (quadrant 2), leveraging evidence from data and practice (quadrant 3), and generating evidence from implementation (quadrant 4) for iterative system-level improvement. The Australian Stroke program was selected as the case study as it provides an exemplar of how an iterative LHS works in practice at a national level encompassing and integrating evidence from all four LHS quadrants. Using this case study, we demonstrate how to apply evidence-based processes to healthcare improvement and embed real-world research for optimising healthcare improvement. We emphasize the transition from research as an endpoint, to research as an enabler and a solution for impact in healthcare improvement. CONCLUSIONS: The Australian Stroke program has nationally improved stroke care since 2007, showcasing the value of integrated LHS-aligned approaches for tangible impact on outcomes. This LHS case study is a practical example for other health conditions and settings to follow suit.

Cost-effectiveness of diagnosis and treatment of early gestational diabetes mellitus: economic evaluation of the TOBOGM study, an international multicenter randomized controlled trial.

Background: A recently undertaken multicenter randomized controlled trial (RCT) "Treatment Of BOoking Gestational diabetes Mellitus" (TOBOGM: 2017-2022) found that the diagnosis and treatment of pregnant women with early gestational diabetes mellitus (GDM) improved pregnancy outcomes. Based on data from the trial, this study aimed to assess the cost-effectiveness of diagnosis and treatment of early GDM (from <20 weeks') among women with risk factors for hyperglycemia in pregnancy compared with usual care (no treatment until 24-28 weeks') from a healthcare perspective. Methods: Participants' healthcare resource utilization data were collected from their self-reported questionnaires and hospital records, and valued using the unit costs obtained from standard Australian national sources. Costs were reported in US dollars ($) using the purchasing power parity (PPP) estimates to facilitate comparison of costs across countries. Intention-to-treat (ITT) principle was followed. Missing cost data were replaced using multiple imputations. Bootstrapping method was used to estimate the uncertainty around mean cost difference and cost-effectiveness results. Bootstrapped cost-effect pairs were used to plot the cost-effectiveness (CE) plane and cost-effectiveness acceptability curve (CEAC). Findings: Diagnosis and treatment of early GDM was more effective and tended to be less costly, i.e., dominant (cost-saving) [-5.6% composite adverse pregnancy outcome (95% CI: -10.1%, -1.2%), -$1373 (95% CI: -$3,749, $642)] compared with usual care. Our findings were confirmed by both the CE plane (88% of the bootstrapped cost-effect pairs fall in the south-west quadrant), and CEAC (the probability of the intervention being cost-effective ranged from 84% at a willingness-to-pay (WTP) threshold value of $10,000-99% at a WTP threshold value of $100,000 per composite adverse pregnancy outcome prevented). Sub-group analyses demonstrated that diagnosis and treatment of early GDM among women in the higher glycemic range (fasting blood glucose 95-109 mg/dl [5.3-6.0 mmol/L], 1-h blood glucose ≥191 mg/dl [10.6 mmol/L] and/or 2-h blood glucose 162-199 mg/dl [9.0-11.0 mmol/L]) was more effective and less costly (dominant) [-7.8% composite adverse pregnancy outcome (95% CI: -14.6%, -0.9%), -$2795 (95% CI: -$6,638, -$533)]; the intervention was more effective and tended to be less costly [-8.9% composite adverse pregnancy outcome (95% CI: -15.1%, -2.6%), -$5548 (95% CI: -$16,740, $1547)] among women diagnosed before 14 weeks' gestation as well. Interpretation: Our findings highlight the potential health and economic benefits from the diagnosis and treatment of early GDM among women with risk factors for hyperglycemia in pregnancy and supports its implementation. Long-term follow-up studies are recommended as a key future area of research to assess the potential long-term health benefits and economic consequences of the intervention. Funding: National Health and Medical Research Council (grants 1104231 and 2009326), Region O¨rebro Research Committee (grants Dnr OLL-970566 and OLL-942177), Medical Scientific Fund of the Mayor of Vienna (project 15,205 and project 23,026), South Western Sydney Local Health District Academic Unit (grant 2016), and Western Sydney University Ainsworth Trust Grant (2019).

Ethnic differences in physical activity participation when managing gestational diabetes mellitus: a mixed-methods study comparing ethnic Chinese migrants and Australian women.

BACKGROUND: Physical activity is a key component in gestational diabetes mellitus management to optimise glycaemic control and reduce adverse pregnancy outcomes. However, inadequate physical activity during pregnancy is common. Underpinned by a woman-centred pregnancy care model, appropriate strategies targeting patients' cultural needs may facilitate physical activity participation. Ethnic Chinese migrants have a four-fold higher risk of gestational diabetes mellitus than the Australian Caucasian host population. To identify potentially effective disease management strategies to improve physical activity participation, understanding and comparing ethnic Chinese migrants' and Caucasian women's views will provide insights into developing an end-user-informed intervention. AIMS: This study aimed to compare perceptions and practices around physical activity participation during pregnancy between 44 ethnic Chinese migrants and 39 Australian-born Caucasian women with gestational diabetes mellitus. METHODS: This mixed-methods study used in-depth, semi-structured audio-recorded interviews, validated pregnancy physical activity questionnaires and pedometers. Qualitative data were thematically analysed and compared between ethnicities. SPSS (SPSS Inc) was used in quantitative data analysis. Data triangulation was made to identify patterns in participant characteristics, physical activity beliefs and participation. RESULTS: Despite both ethnic groups doing less physical activity than recommended, Chinese participants were less physically active than Caucasian participants. Chinese participants expressed greater safety concerns about physical activity and opted for a more sedentary lifestyle. Data triangulation indicated that non-Australian-born Chinese participants whose husbands were Asian were overcautious about miscarriage risk related to physical activity, which promoted a sedentary lifestyle. Chinese participants suggested individualised, specific physical activity advice on safe physical activity during pregnancy would mitigate their concerns. Caucasian participants reported that digital step measurement technologies motivated their participation in physical activity. CONCLUSION: Different strategies are suggested by Chinese and Caucasian participants to improve physical activity participation to manage gestational diabetes mellitus among ethnic Chinese and Caucasian populations, which will be evaluated in future interventions.

Laser and Light-Based Therapies for Hirsutism Management in Women With Polycystic Ovarian Syndrome: A Systematic Review.

Importance: Hirsutism represents a significant concern for women with polycystic ovary syndrome (PCOS), with deleterious psychological effects warranting acknowledgment and a clear imperative to provide effective management. To our knowledge, this is the first review to exclusively examine the effectiveness of laser and light-based therapies in addressing hirsutism in women with PCOS. Objective: To synthesize the existing literature regarding the effectiveness of laser and light hair reduction therapies, either as stand-alone treatments or in combination with systemic agents, in treating hirsutism for women with PCOS. Evidence Review: A systematic literature review was performed using MEDLINE, Embase, EMCARE, and CINAHL according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. Articles written in English, reporting on patients who met pre-established inclusion criteria were selected. Objective and subjectively measured outcomes relating to the effect of laser or light-based hair reduction therapies on hirsutism were abstracted. Heterogeneity among included studies precluded a meta-analysis, necessitating a narrative synthesis. Findings: Six studies reporting data on 423 individual patients with PCOS who underwent laser or light-based hair reduction therapies were included: 4 randomized clinical trials and 2 cohort studies. Alexandrite laser demonstrated significant improvements in hirsutism severity and psychological outcomes, particularly at high-fluence application. Alexandrite laser was also found to be more effective than intense pulsed light (IPL). The combination of diode laser with either metformin or combined oral contraceptive pill was superior to the application of diode laser alone, just as the addition of metformin to IPL demonstrated superior results to IPL treatment alone. Overall, most interventions were well tolerated. The overall certainty of evidence across all outcomes and comparisons was limited in part due to the observational nature of some studies. Conclusions and Relevance: This systematic review highlights the potential of laser and light hair reduction therapies, both as stand-alone treatments and in combination with other pharmacological agents in PCOS. However, this review was limited by low certainty of the evidence, few studies evaluating effectiveness and safety in those with skin of color, and heterogeneity in outcome assessment. Future studies are needed to provide more robust evidence among diverse individuals with PCOS and hirsutism.

Polycystic ovary syndrome.

Despite affecting ~11-13% of women globally, polycystic ovary syndrome (PCOS) is a substantially understudied condition. PCOS, possibly extending to men's health, imposes a considerable health and economic burden worldwide. Diagnosis in adults follows the International Evidence-based Guideline for the Assessment and Management of Polycystic Ovary Syndrome, requiring two out of three criteria - clinical or biochemical hyperandrogenism, ovulatory dysfunction, and/or specific ovarian morphological characteristics or elevated anti-Müllerian hormone. However, diagnosing adolescents omits ovarian morphology and anti-Müllerian hormone considerations. PCOS, marked by insulin resistance and hyperandrogenism, strongly contributes to early-onset type 2 diabetes, with increased odds for cardiovascular diseases. Reproduction-related implications include irregular menstrual cycles, anovulatory infertility, heightened risks of pregnancy complications and endometrial cancer. Beyond physiological manifestations, PCOS is associated with anxiety, depression, eating disorders, psychosexual dysfunction and negative body image, collectively contributing to diminished health-related quality of life in patients. Despite its high prevalence persisting into menopause, diagnosing PCOS often involves extended timelines and multiple health-care visits. Treatment remains ad hoc owing to limited understanding of underlying mechanisms, highlighting the need for research delineating the aetiology and pathophysiology of the syndrome. Identifying factors contributing to PCOS will pave the way for personalized medicine approaches. Additionally, exploring novel biomarkers, refining diagnostic criteria and advancing treatment modalities will be crucial in enhancing the precision and efficacy of interventions that will positively impact the lives of patients.

Consumer and community involvement in preventive health: current insights and considerations for future best practice.

Consumer and community involvement (CCI) in preventive research and health initiatives is not only encouraged but is expected within a rapidly evolving landscape across health policy, practice and research. Here, we summarise the fundamental principles of CCI, as well as outline the barriers and current developments in working towards best practices at organisational and systems levels. CCI stands at a critical juncture. Best practice emphasises meaningful partnerships with consumers and communities to deliver impactful research and prevention activities, yet complex challenges and systematic barriers remain. We need further evidence to demonstrate both 'what' and 'how' CCI should be best implemented in these settings. We present key considerations for researchers, organisations and systems to catalyse the transition of CCI from mere recognition of its importance to pragmatic and optimum implementation and, ultimately, to systemic reform. These include changes to capacity building, funding structures, equitable engagement and transparent evaluation. These must be underpinned by evidence-based approaches, partnership, trust and broad consensus processes to achieve meaningful and impactful CCI in research and healthcare improvement through a lens of inclusivity.

Impact of bariatric surgery on anthropometric, metabolic, and reproductive outcomes in polycystic ovary syndrome: a systematic review and meta-analysis.

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in females. Modest weight loss improves reproductive and metabolic PCOS features. While lifestyle modifications and pharmacotherapies remain first-line weight loss strategies, bariatric surgery is emerging as a potentially effective treatment. We performed a systematic review and meta-analysis of published literature to examine the impact of bariatric surgery in PCOS to inform the 2023 International PCOS Evidence-based Guidelines. Electronic databases were searched for observational studies and trials comparing pharmacologic or lifestyle treatments to bariatric surgery in women with PCOS or bariatric surgery in women with or without PCOS. Anthropometric, reproductive, hormonal, and metabolic outcomes were included and, where possible, meta-analyzed using random-effects models. Risk of bias and evidence quality were assessed. Ten studies were included involving 432 women with and 590 women without PCOS. Comparisons between bariatric surgery and pharmacologic or lifestyle treatments were only reported in one study each, and most reproductive outcomes were limited to a single study; therefore, meta-analyses could not be performed. Meta-analysis found that women with PCOS experience similar improvements in anthropometric, hormonal, and metabolic outcomes after bariatric surgery compared to those without PCOS. Existing research is limited and of low quality with high risk of bias, especially in comparison to existing PCOS treatments and with respect to reproductive outcomes including pregnancy, highlighting the need for additional studies to inform clinical recommendations.

OptimalMe Program: A Mixed Method Investigation into the Engagement and Acceptability of a Preconception Digital Health Lifestyle Intervention with Individual Coaching for Women's Health and Behaviour Change.

Preconception interventions, specifically addressing general health, lifestyle behaviours and weight management, are limited despite their importance in optimising women's health. The objective of this study is to evaluate the engagement and acceptability of OptimalMe, a digital preconception intervention. Participants, (n = 298) Australian women aged 18-44 with private health insurance planning to conceive within 12 months, received a standardised intervention, including access to a digital healthy lifestyle platform (educational materials, behaviour change activities, and self-monitoring resources), ongoing text messaging, and remotely delivered health coaching (two appointments) with randomised delivery methods (telephone/videoconference). Engagement and acceptability were assessed through mixed method analyses. The results show that 76.2% attended both coaching sessions, with similar participation rates for telehealth (75.2%) and videoconferencing (77.2%) (p = 0.469). All participants logged into the digital platform, with 90.6% accessing educational materials and 91.3% using behaviour change tools. Digital platform engagement declined over time, suggesting potential benefits from additional health coaching support for ongoing participation. The post-intervention evaluation (n = 217 participants) demonstrated that approximately 90% found the digital module engaging, meeting information needs, would recommend the program, and were satisfied with the support. OptimalMe demonstrated positive acceptability and engagement; however, further research is warranted to explore strategies for sustaining engagement with the digital interventions.