Application of machine learning and artificial intelligence in the diagnosis and classification of polycystic ovarian syndrome: a systematic review

IntroductionPolycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity. Artificial intelligence (AI) and machine learning (ML) hold promise in improving diagnostics. Thus, we performed a systematic review of literature to identify the utility of AI/ML in the diagnosis or classification of PCOS.MethodsWe applied a search strategy using the following databases MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, the Web of Science, and the IEEE Xplore Digital Library using relevant keywords. Eligible studies were identified, and results were extracted for their synthesis from inception until January 1, 2022.Results135 studies were screened and ultimately, 31 studies were included in this study. Data sources used by the AI/ML interventions included clinical data, electronic health records, and genetic and proteomic data. Ten studies (32%) employed standardized criteria (NIH, Rotterdam, or Revised International PCOS classification), while 17 (55%) used clinical information with/without imaging. The most common AI techniques employed were support vector machine (42% studies), K-nearest neighbor (26%), and regression models (23%) were the commonest AI/ML. Receiver operating curves (ROC) were employed to compare AI/ML with clinical diagnosis. Area under the ROC ranged from 73% to 100% (n=7 studies), diagnostic accuracy from 89% to 100% (n=4 studies), sensitivity from 41% to 100% (n=10 studies), specificity from 75% to 100% (n=10 studies), positive predictive value (PPV) from 68% to 95% (n=4 studies), and negative predictive value (NPV) from 94% to 99% (n=2 studies).ConclusionArtificial intelligence and machine learning provide a high diagnostic and classification performance in detecting PCOS, thereby providing an avenue for early diagnosis of this disorder. However, AI-based studies should use standardized PCOS diagnostic criteria to enhance the clinical applicability of AI/ML in PCOS and improve adherence to methodological and reporting guidelines for maximum diagnostic utility.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42022295287

Thyroid and male reproduction

Male reproduction is governed by the classical hypothalamo-hypophyseal testicular axis: Hypothalamic gonadotropin releasing hormone (GnRH), pituitary luteinizing hormone (LH) and follicle stimulating hormone (FSH) and the gonadal steroid, principally, testosterone. Thyroid hormones have been shown to exert a modulatory influence on this axis and consequently the sexual and spermatogenic function of man. This review will examine the modulatory influence of thyroid hormones on male reproduction

Quality of Life in Patients with Coronary Artery Disease and Panic Disorder: A Comparative Study

Objectives: The quality of life (QOL) of patients with coronary artery disease (CAD) is known to be impaired. Non-cardiac chest pain referrals are often under-diagnosed and untreated, and there are hardly any studies comparing the QOL of CAD and panic disorder related (non-cardiac) chest pain referrals (PDRC). Methods: We assessed the psychiatric morbidity and QOL of patients newly diagnosed with CAD (n = 40) at baseline and six weeks post-treatment and compared their QOL with patients with PDRC (n = 40) and age- and gender-matched healthy controls (n = 57). Psychiatric morbidity in the CAD group was assessed using the General Health Questionnaire (GHQ12) item, Hamilton Anxiety Scores (HAM-A), and Hamilton Depression Scores (HAMD). QOL measures were determined by the World Health Organization QOL questionnaire (brief) and Seattle Angina Questionnaire. The CAD group was treated with anti-ischemic drugs (nitrates, betablockers), antiplatelet drugs (acetylsalicylsalicylic acid), anticoagulants (low molecular weight heparin, clopidogrel), and managed for risk factors. The PDRC group was treated with selective serotonin reuptake inhibitors and anxiolytics. Results: Patients with panic disorder had a worse QOL than those with CAD and healthy controls in the physical domain and psychological domain (PDRC vs. CAD vs. healthy controls, p < 0.001). In the CAD group, smoking was associated with change in angina stability (p = 0.049) whereas other tobacco products were associated with change in angina frequency (p = 0.044). Psychiatric morbidity was present in 40.0% of patients with CAD. In the PDRC group, a significant correlation of HAM-A scores was noted in the physical (p = 0.000), psychological (p = 0.001), social (p = 0.006), and environment (p = 0.001) domains of QOL. Patients with panic disorder had a significant improvement in anxiety scores after treatment compared to baseline (HAM-A scores difference 21.0 [16.5−25.6]; p < 0.001). Conclusions: Patients in the PDRC group had a worse QOL than those in the CAD and healthy control groups. This highlights the need for careful diagnosis and prompt treatment of panic disorder in these patients to improve their QOL. Additionally, smoking, the use of other tobacco products, and hypercholesterolemia were associated with angina symptoms in patients with CAD

The Thyroid Hormone Axis and Female Reproduction

Thyroid function affects multiple sites of the female hypothalamic-pituitary gonadal (HPG) axis. Disruption of thyroid function has been linked to reproductive dysfunction in women and is associated with menstrual irregularity, infertility, poor pregnancy outcomes, and gynecological conditions such as premature ovarian insufficiency and polycystic ovarian syndrome. Thus, the complex molecular interplay between hormones involved in thyroid and reproductive functions is further compounded by the association of certain common autoimmune states with disorders of the thyroid and the HPG axes. Furthermore, in prepartum and intrapartum states, even relatively minor disruptions have been shown to adversely impact maternal and fetal outcomes, with some differences of opinion in the management of these conditions. In this review, we provide readers with a foundational understanding of the physiology and pathophysiology of thyroid hormone interactions with the female HPG axis. We also share clinical insights into the management of thyroid dysfunction in reproductive-aged women

Prevalence of Diabetes and Hypertension and Their Associated Risks for Poor Outcomes in Covid-19 Patients

Coronavirus disease 2019 (Covid-19) has affected millions of people and may disproportionately affect those with hypertension and diabetes. Because of inadequate methods in published systematic reviews, the prevalence of diabetes and hypertension and associated risks of poor outcomes in Covid-19 patients are unknown. We searched databases from December 1, 2019, to April 6, 2020, and selected observational peer-reviewed studies in English of patients with Covid-19. Independent reviewers extracted data on study participants, interventions, and outcomes and assessed risk of bias, and the certainty of evidence. We included 65 (15 794 participants) observational studies at moderate to high risk of bias. Overall prevalence of diabetes and hypertension was 12% (95% confidence interval [CI], 10-15; n = 12 870; I 2: 89%), and 17% (95% CI, 13-22; n = 12 709; I 2: 95%), respectively. In severe Covid-19, the prevalence of diabetes and hypertension were 18% (95% CI, 16-20; n = 1099; I 2: 0%) and 32% (95% CI, 16-54; n = 1078; I 2: 63%), respectively. Unadjusted relative risk for intensive care unit admission and mortality were 1.96 (95% CI, 1.19-3.22; n = 8890; I 2: 80%; P = .008) and 2.78 (95% CI, 1.39-5.58; n = 2058; I 2: 75%; P = .0004) for diabetics; and 2.95 (95% CI, 2.18-3.99; n = 1737; I 2: 0%; P < .001) and 2.39 (95% CI, 1.54-3.73; n = 3107; I 2: 66%; P < .001) for hypertensives. Neither diabetes (1.50; 95% CI, 0.90-2.50; n = 1991; I 2: 74%; P = .119) nor hypertension (1.48; 95% CI, 0.99-2.23; n = 2023; I 2: 69%; P = .058) was associated with severe Covid-19. In conclusion, the risk of intensive care unit admission and mortality for patients with diabetes or hypertension who developed Covid-19 is increased compared with those without these comorbidities

Scoping review of COVID-19-related systematic reviews and meta-analyses: can we really have confidence in their results?

AIM The aim of this study was to systematically appraise the quality of a sample of COVID-19-related systematic reviews (SRs) and discuss internal validity threats affecting the COVID-19 body of evidence. DESIGN We conducted a scoping review of the literature. SRs with or without meta-analysis (MA) that evaluated clinical data, outcomes or treatments for patients with COVID-19 were included. MAIN OUTCOME MEASURES We extracted quality characteristics guided by A Measurement Tool to Assess Systematic Reviews-2 to calculate a qualitative score. Complementary evaluation of the most prominent published limitations affecting the COVID-19 body of evidence was performed. RESULTS A total of 63 SRs were included. The majority were judged as a critically low methodological quality. Most of the studies were not guided by a pre-established protocol (39, 62%). More than half (39, 62%) failed to address risk of bias when interpreting their results. A comprehensive literature search strategy was reported in most SRs (54, 86%). Appropriate use of statistical methods was evident in nearly all SRs with MAs (39, 95%). Only 16 (33%) studies recognised heterogeneity in the definition of severe COVID-19 as a limitation of the study, and 15 (24%) recognised repeated patient populations as a limitation. CONCLUSION The methodological and reporting quality of current COVID-19 SR is far from optimal. In addition, most of the current SRs fail to address relevant threats to their internal validity, including repeated patients and heterogeneity in the definition of severe COVID-19. Adherence to proper study design and peer-review practices must remain to mitigate current limitations