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  1. Article ; Online: Editorial: Health considerations across the lifespan for patients with polycystic ovary syndrome.

    Mahalingaiah, Shruthi

    Current opinion in endocrinology, diabetes, and obesity

    2022  Volume 29, Issue 6, Page(s) 513

    MeSH term(s) Female ; Humans ; Polycystic Ovary Syndrome ; Longevity ; Cardiovascular Diseases
    Language English
    Publishing date 2022-10-26
    Publishing country England
    Document type Journal Article
    ZDB-ID 2272017-0
    ISSN 1752-2978 ; 1752-296X
    ISSN (online) 1752-2978
    ISSN 1752-296X
    DOI 10.1097/MED.0000000000000774
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: It's time to include couple-based body mass index counseling in the infertility clinic visit.

    Mahalingaiah, Shruthi

    Fertility and sterility

    2020  Volume 114, Issue 5, Page(s) 971

    MeSH term(s) Body Mass Index ; Counseling ; Female ; Fertility Clinics ; Humans ; Infertility/diagnosis ; Infertility/therapy ; Pregnancy ; Time-to-Pregnancy
    Language English
    Publishing date 2020-10-03
    Publishing country United States
    Document type Editorial ; Comment
    ZDB-ID 80133-1
    ISSN 1556-5653 ; 0015-0282
    ISSN (online) 1556-5653
    ISSN 0015-0282
    DOI 10.1016/j.fertnstert.2020.07.058
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Is there a common mechanism underlying air pollution exposures and reproductive outcomes noted in epidemiologic and in vitro fertilization lab-based studies?

    Mahalingaiah, Shruthi

    Fertility and sterility

    2018  Volume 109, Issue 1, Page(s) 68

    MeSH term(s) Air Pollutants/analysis ; Air Pollution/analysis ; Environmental Exposure/analysis ; Fertilization in Vitro ; Reproduction
    Chemical Substances Air Pollutants
    Language English
    Publishing date 2018-01-03
    Publishing country United States
    Document type Editorial ; Comment
    ZDB-ID 80133-1
    ISSN 1556-5653 ; 0015-0282
    ISSN (online) 1556-5653
    ISSN 0015-0282
    DOI 10.1016/j.fertnstert.2017.10.034
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Optimization of assisted reproductive technology outcomes in patients with polycystic ovarian syndrome: updates and unanswered questions.

    Fitz, Victoria W / Mahalingaiah, Shruthi

    Current opinion in endocrinology, diabetes, and obesity

    2022  Volume 29, Issue 6, Page(s) 547–553

    Abstract: Purpose of review: Narrative review of recent literature on optimization of assisted reproduction technology outcomes in patients with polycystic ovarian syndrome (PCOS).: Recent findings: The key areas of focus include pre cycle treatment with the ... ...

    Abstract Purpose of review: Narrative review of recent literature on optimization of assisted reproduction technology outcomes in patients with polycystic ovarian syndrome (PCOS).
    Recent findings: The key areas of focus include pre cycle treatment with the goal of cohort synchronization, methods of ovulation suppression and trigger medication. There is no definitive evidence that precycle treatment with combined oral contraceptives (COCs) or progestins improve or negatively impact in vitro fertilization outcomes in patients with PCOS. The reviewed evidence supports consideration of progestins as suppression of premature ovulation in patients with PCOS as an alternative to gonadotropin releasing hormone (GnRH) antagonist if a freeze all protocol is planned. There is limited prospective evidence in PCOS populations regarding use of a dual trigger using GnRH agonist and human chorionic gonadotropin (hCG).
    Summary: This review has implications for clinical practice regarding ovarian stimulation protocols for patients with PCOS. We also identified areas of research need including the further exploration of the value of pre cycle COC or progestin use in a PCOS population, also the use of GnRH agonist in combination with hCG in a well defined PCOS population and using GnRH agonist trigger alone as a control.
    MeSH term(s) Female ; Humans ; Polycystic Ovary Syndrome/drug therapy ; Ovarian Hyperstimulation Syndrome/drug therapy ; Ovarian Hyperstimulation Syndrome/epidemiology ; Progestins/therapeutic use ; Prospective Studies ; Contraceptives, Oral, Combined/therapeutic use ; Gonadotropin-Releasing Hormone/therapeutic use ; Ovulation Induction/methods ; Fertilization in Vitro/methods ; Chorionic Gonadotropin/therapeutic use
    Chemical Substances Progestins ; Contraceptives, Oral, Combined ; Gonadotropin-Releasing Hormone (33515-09-2) ; Chorionic Gonadotropin
    Language English
    Publishing date 2022-10-11
    Publishing country England
    Document type Review ; Journal Article
    ZDB-ID 2272017-0
    ISSN 1752-2978 ; 1752-296X
    ISSN (online) 1752-2978
    ISSN 1752-296X
    DOI 10.1097/MED.0000000000000780
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Glucagon-like peptide-1 receptor agonists and safety in the preconception period.

    Minis, Evelyn / Stanford, Fatima Cody / Mahalingaiah, Shruthi

    Current opinion in endocrinology, diabetes, and obesity

    2023  Volume 30, Issue 6, Page(s) 273–279

    Abstract: Purpose of review: Glucagon-like peptide-1 (GLP-1) receptor agonists (RAs) are becoming increasingly popular for the treatment of type II diabetes and obesity. Body mass index (BMI) thresholds at in vitro fertilization (IVF) clinics may further drive ... ...

    Abstract Purpose of review: Glucagon-like peptide-1 (GLP-1) receptor agonists (RAs) are becoming increasingly popular for the treatment of type II diabetes and obesity. Body mass index (BMI) thresholds at in vitro fertilization (IVF) clinics may further drive the use of these medications before infertility treatment. However, most clinical guidance regarding optimal time to discontinue these medications prior to conception is based on animal data. The purpose of this review was to evaluate the literature for evidence-based guidance regarding the preconception use of GLP-1 RA.
    Recent findings: 16 articles were found in our PubMed search, 10 were excluded as they were reviews or reported on animal data. Included were 3 case reports detailing pregnancy outcomes in individual patients that conceived while on a GLP-1 RA and 2 randomized controlled trials (RCTs) and a follow-up study to one of the RCTs that reported on patients randomized to GLP-1 RA or metformin prior to conception. No adverse pregnancy or neonatal outcomes were reported.
    Summary: There are limited data from human studies to guide decision-making regarding timing of discontinuation of GLP-1 RA before conception. Studies focused on pregnancy and neonatal outcomes would provide additional information regarding a safe washout period. Based on the available literature a 4-week washout period prior to attempting conception may be considered for the agents reviewed in this publication.
    MeSH term(s) Pregnancy ; Female ; Animals ; Infant, Newborn ; Humans ; Hypoglycemic Agents/adverse effects ; Glucagon-Like Peptide-1 Receptor/agonists ; Diabetes Mellitus, Type 2/drug therapy ; Glucagon-Like Peptide 1 ; Metformin/adverse effects ; Randomized Controlled Trials as Topic
    Chemical Substances Hypoglycemic Agents ; Glucagon-Like Peptide-1 Receptor ; Glucagon-Like Peptide 1 (89750-14-1) ; Metformin (9100L32L2N)
    Language English
    Publishing date 2023-09-05
    Publishing country England
    Document type Review ; Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2272017-0
    ISSN 1752-2978 ; 1752-296X
    ISSN (online) 1752-2978
    ISSN 1752-296X
    DOI 10.1097/MED.0000000000000835
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Exploring the causes of semen quality changes post-bariatric surgery: a focus on endocrine-disrupting chemicals.

    Magalhaes, Danielly P / Mahalingaiah, Shruthi / Perry, Melissa J

    Human reproduction (Oxford, England)

    2022  Volume 37, Issue 5, Page(s) 902–921

    Abstract: Rapid weight loss promoted by bariatric surgery (BS) can release accumulated lipophilic endocrine-disrupting chemicals (EDCs), making these chemicals systemically available. Men typically have a higher EDC body burden and lose more weight post-BS than ... ...

    Abstract Rapid weight loss promoted by bariatric surgery (BS) can release accumulated lipophilic endocrine-disrupting chemicals (EDCs), making these chemicals systemically available. Men typically have a higher EDC body burden and lose more weight post-BS than women, which may put male BS patients at high risk for testicular toxicity. In this review, we analyze the impacts of BS on semen parameters with a particular focus on the potential effects of EDCs. After BS, serum EDC concentrations progressively increase; and there is evidence that semen parameters deteriorate after BS. Although elevated serum EDC concentrations are associated with inferior sperm parameters, links between semen parameters and EDCs post-BS have not been studied. Understanding these potential associations requires adequately powered studies, particularly within prospective longitudinal cohorts with long-term follow-up for sperm parameters, nutritional status, sex-hormones levels and serum EDC concentrations. Studying BS patients prospectively provides the important opportunity to evaluate dose-response effects of EDC serum concentrations on sperm quality and function. Research is also needed to identify critical chemical exposure periods post-BS to inform reproductive decisions, including consideration of sperm preservation before surgery.
    MeSH term(s) Bariatric Surgery/adverse effects ; Endocrine Disruptors/toxicity ; Female ; Humans ; Male ; Prospective Studies ; Semen ; Semen Analysis
    Chemical Substances Endocrine Disruptors
    Language English
    Publishing date 2022-03-30
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 632776-x
    ISSN 1460-2350 ; 0268-1161 ; 1477-741X
    ISSN (online) 1460-2350
    ISSN 0268-1161 ; 1477-741X
    DOI 10.1093/humrep/deac039
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Evaluation of Menstrual Cycle Tracking Behaviors in the Ovulation and Menstruation Health Pilot Study: Cross-Sectional Study.

    Adnan, Tatheer / Li, Huichu / Peer, Komal / Peebles, Elizabeth / James, Kaitlyn / Mahalingaiah, Shruthi

    Journal of medical Internet research

    2023  Volume 25, Page(s) e42164

    Abstract: Background: Menstrual cycle tracking apps (MCTAs) have potential in epidemiological studies of women's health, facilitating real-time tracking of bleeding days and menstrual-associated signs and symptoms. However, information regarding the ... ...

    Abstract Background: Menstrual cycle tracking apps (MCTAs) have potential in epidemiological studies of women's health, facilitating real-time tracking of bleeding days and menstrual-associated signs and symptoms. However, information regarding the characteristics of MCTA users versus cycle nontrackers is limited, which may inform generalizability.
    Objective: We compared characteristics among individuals using MCTAs (app users), individuals who do not track their cycles (nontrackers), and those who used other forms of menstrual tracking (other trackers).
    Methods: The Ovulation and Menstruation Health Pilot Study tested the feasibility of a digitally enabled evaluation of menstrual health. Recruitment occurred between September 2017 and March 2018. Menstrual cycle tracking behavior, demographic, and general and reproductive health history data were collected from eligible individuals (females aged 18-45 years, comfortable communicating in English). Menstrual cycle tracking behavior was categorized in 3 ways: menstrual cycle tracking via app usage, that via other methods, and nontracking. Demographic factors, health conditions, and menstrual cycle characteristics were compared across the menstrual tracking method (app users vs nontrackers, app users vs other trackers, and other trackers vs nontrackers) were assessed using chi-square or Fisher exact tests.
    Results: In total, 263 participants met the eligibility criteria and completed the digital survey. Most of the cohort (n=191, 72.6%) was 18-29 years old, predominantly White (n=170, 64.6%), had attained 4 years of college education or higher (n= 209, 79.5%), and had a household income below US $50,000 (n=123, 46.8%). Among all participants, 103 (39%) were MCTA users (app users), 97 (37%) did not engage in any tracking (nontrackers), and 63 (24%) used other forms of tracking (other trackers). Across all groups, no meaningful differences existed in race and ethnicity, household income, and education level. The proportion of ever-use of hormonal contraceptives was lower (n=74, 71.8% vs n=87, 90%, P=.001), lifetime smoking status was lower (n=6, 6% vs n=15, 17%, P=.04), and diagnosis rate of gastrointestinal reflux disease (GERD) was higher (n=25, 24.3% vs n=12, 12.4%, P=.04) in app users than in nontrackers. The proportions of hormonal contraceptives ever used and lifetime smoking status were both lower (n=74, 71.8% vs n=56, 88.9%, P=.01; n=6, 6% vs n=11, 17.5%, P=.02) in app users than in other trackers. Other trackers had lower proportions of ever-use of hormonal contraceptives (n=130, 78.3% vs n=87, 89.7%, P=.02) and higher diagnostic rates of heartburn or GERD (n=39, 23.5% vs n=12, 12.4%, P.03) and anxiety or panic disorder (n=64, 38.6% vs n=25, 25.8%, P=.04) than nontrackers. Menstrual cycle characteristics did not differ across all groups.
    Conclusions: Our results suggest that app users, other trackers, and nontrackers are largely comparable in demographic and menstrual cycle characteristics. Future studies should determine reasons for tracking and tracking-related behaviors to further understand whether individuals who use MCTAs are comparable to nontrackers.
    MeSH term(s) Humans ; Female ; Adolescent ; Young Adult ; Adult ; Menstruation ; Cross-Sectional Studies ; Pilot Projects ; Mobile Applications ; Menstrual Cycle ; Ovulation ; Gastrointestinal Diseases ; Contraceptive Agents ; Gastroesophageal Reflux
    Chemical Substances Contraceptive Agents
    Language English
    Publishing date 2023-10-27
    Publishing country Canada
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2028830-X
    ISSN 1438-8871 ; 1438-8871
    ISSN (online) 1438-8871
    ISSN 1438-8871
    DOI 10.2196/42164
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article: Case report of pelvic tuberculosis resulting in Asherman's syndrome and infertility.

    Fowler, Mary Louise / Mahalingaiah, Shruthi

    Fertility research and practice

    2019  Volume 5, Page(s) 8

    Abstract: Approximately one-third of the world's population is infected ... ...

    Abstract Approximately one-third of the world's population is infected with
    Language English
    Publishing date 2019-08-01
    Publishing country England
    Document type Case Reports
    ISSN 2054-7099
    ISSN 2054-7099
    DOI 10.1186/s40738-019-0061-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Data mining polycystic ovary morphology in electronic medical record ultrasound reports.

    Cheng, Jay Jojo / Mahalingaiah, Shruthi

    Fertility research and practice

    2019  Volume 5, Page(s) 13

    Abstract: Background: Polycystic ovary syndrome (PCOS) is characterized by hyperandrogenemia, oligo-anovulation, and numerous ovarian cysts. Hospital electronic medical records provide an avenue for investigating polycystic ovary morphology commonly seen in PCOS ... ...

    Abstract Background: Polycystic ovary syndrome (PCOS) is characterized by hyperandrogenemia, oligo-anovulation, and numerous ovarian cysts. Hospital electronic medical records provide an avenue for investigating polycystic ovary morphology commonly seen in PCOS at a large scale. The purpose of this study was to develop and evaluate the performance of two machine learning text algorithms, for classification of polycystic ovary morphology (PCOM) in pelvic ultrasounds.
    Methods: Pelvic ultrasound reports from patients at Boston Medical Center between October 1, 2003 and December 12, 2016 were included for analysis, which resulted in 39,093 ultrasound reports from 25,535 unique women. Following the 2003 Rotterdam Consensus Criteria for polycystic ovary syndrome, 2000 randomly selected ultrasounds were expert labeled for PCOM status as present, absent, or unidentifiable (not able to be determined from text alone). An ovary was marked as having PCOM if there was mention of numerous peripheral follicles or if the volume was greater than 10 ml in the absence of a dominant follicle or other confounding pathology. Half of the labeled data was used to develop and refine the algorithms, and the other half was used as a test set for evaluating its accuracy.
    Results: On the evaluation set of 1000 random US reports, the accuracy of the classifiers were 97.6% (95% CI: 96.5, 98.5%) and 96.1% (94.7, 97.2%). Both models were more adept at identifying PCOM-absent ultrasounds than either PCOM-unidentifiable or PCOM-present ultrasounds. The two classifiers estimated prevalence of PCOM within the whole set of 39,093 ultrasounds to be 44% PCOM-absent, 32% PCOM-unidentifiable, and 24% PCOM-present.
    Conclusions: Although accuracy measured on the test set and inter-rater agreement between the two classifiers (Cohen's Kappa = 0.988) was high, a major limitation of our approach is that it uses the ultrasound report text as a proxy and does not directly count follicles from the ultrasound images themselves.
    Language English
    Publishing date 2019-12-01
    Publishing country England
    Document type Journal Article
    ISSN 2054-7099
    ISSN 2054-7099
    DOI 10.1186/s40738-019-0067-7
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: Predicting polycystic ovary syndrome with machine learning algorithms from electronic health records.

    Zad, Zahra / Jiang, Victoria S / Wolf, Amber T / Wang, Taiyao / Cheng, J Jojo / Paschalidis, Ioannis Ch / Mahalingaiah, Shruthi

    Frontiers in endocrinology

    2024  Volume 15, Page(s) 1298628

    Abstract: Introduction: Predictive models have been used to aid early diagnosis of PCOS, though existing models are based on small sample sizes and limited to fertility clinic populations. We built a predictive model using machine learning algorithms based on an ... ...

    Abstract Introduction: Predictive models have been used to aid early diagnosis of PCOS, though existing models are based on small sample sizes and limited to fertility clinic populations. We built a predictive model using machine learning algorithms based on an outpatient population at risk for PCOS to predict risk and facilitate earlier diagnosis, particularly among those who meet diagnostic criteria but have not received a diagnosis.
    Methods: This is a retrospective cohort study from a SafetyNet hospital's electronic health records (EHR) from 2003-2016. The study population included 30,601 women aged 18-45 years without concurrent endocrinopathy who had any visit to Boston Medical Center for primary care, obstetrics and gynecology, endocrinology, family medicine, or general internal medicine. Four prediction outcomes were assessed for PCOS. The first outcome was PCOS ICD-9 diagnosis with additional model outcomes of algorithm-defined PCOS. The latter was based on Rotterdam criteria and merging laboratory values, radiographic imaging, and ICD data from the EHR to define irregular menstruation, hyperandrogenism, and polycystic ovarian morphology on ultrasound.
    Results: We developed predictive models using four machine learning methods: logistic regression, supported vector machine, gradient boosted trees, and random forests. Hormone values (follicle-stimulating hormone, luteinizing hormone, estradiol, and sex hormone binding globulin) were combined to create a multilayer perceptron score using a neural network classifier. Prediction of PCOS prior to clinical diagnosis in an out-of-sample test set of patients achieved an average AUC of 85%, 81%, 80%, and 82%, respectively in Models I, II, III and IV. Significant positive predictors of PCOS diagnosis across models included hormone levels and obesity; negative predictors included gravidity and positive bHCG.
    Conclusion: Machine learning algorithms were used to predict PCOS based on a large at-risk population. This approach may guide early detection of PCOS within EHR-interfaced populations to facilitate counseling and interventions that may reduce long-term health consequences. Our model illustrates the potential benefits of an artificial intelligence-enabled provider assistance tool that can be integrated into the EHR to reduce delays in diagnosis. However, model validation in other hospital-based populations is necessary.
    MeSH term(s) Humans ; Female ; Polycystic Ovary Syndrome/diagnosis ; Retrospective Studies ; Artificial Intelligence ; Electronic Health Records ; Luteinizing Hormone ; Algorithms ; Machine Learning
    Chemical Substances Luteinizing Hormone (9002-67-9)
    Language English
    Publishing date 2024-01-30
    Publishing country Switzerland
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, Non-U.S. Gov't
    ZDB-ID 2592084-4
    ISSN 1664-2392
    ISSN 1664-2392
    DOI 10.3389/fendo.2024.1298628
    Database MEDical Literature Analysis and Retrieval System OnLINE

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