Hemorrhoidal disease and its genetic association with depression, bipolar disorder, anxiety disorders, and schizophrenia: a bidirectional mendelian randomization study.

BACKGROUND: Hemorrhoids and psychiatric disorders exhibit high prevalence rates and a tendency for relapse in epidemiological studies. Despite this, limited research has explored their correlation, and these studies are often subject to reverse causality and residual confounding. We conducted a Mendelian randomization (MR) analysis to comprehensively investigate the association between several mental illnesses and hemorrhoidal disease. METHODS: Genetic associations for four psychiatric disorders and hemorrhoidal disease were obtained from large consortia, the FinnGen study, and the UK Biobank. Genetic variants associated with depression, bipolar disorder, anxiety disorders, schizophrenia, and hemorrhoidal disease at the genome-wide significance level were selected as instrumental variables. Screening for potential confounders in genetic instrumental variables using PhenoScanner V2. Bidirectional MR estimates were employed to assess the effects of four psychiatric disorders on hemorrhoidal disease. RESULTS: Our analysis revealed a significant association between genetically predicted depression and the risk of hemorrhoidal disease (IVW, OR=1.20,95% CI=1.09 to 1.33, P <0.001). We found no evidence of associations between bipolar disorder, anxiety disorders, schizophrenia, and hemorrhoidal disease. Inverse MR analysis provided evidence for a significant association between genetically predicted hemorrhoidal disease and depression (IVW, OR=1.07,95% CI=1.04 to 1.11, P <0.001). CONCLUSIONS: This study offers MR evidence supporting a bidirectional causal relationship between depression and hemorrhoidal disease.

Present Situation and the Future Development of Web-Based Prenatal Education in China: Cross-sectional Web-Based Survey.

BACKGROUND: Pregnancy serves as an important chapter in the life of women since more attention needs to be paid to both their physical and psychological health during this period. Adequate prenatal knowledge plays a key role in ensuring the health and safety of not only the pregnant women but also their fetuses and the entire family. With the development of information technology, web-based prenatal education has been brought into focus owing to its accessibility to comprehensive information, with high-quality information available to improve the quality of the overall gestation period, labor process, perinatal outcomes, and fetal outcomes. OBJECTIVE: This study aims to investigate the present situation of web-based prenatal education and to predict the future research direction of web-based prenatal education in China, thereby providing insights into improving the quality of health care of pregnant women. METHODS: A national cross-sectional study was conducted on 590,912 pregnant women in 31 provincial administrations of mainland China between August 2018 and August 2019. These pregnant women were initially recruited from local hospitals across the nation during antenatal and postnatal periods via a web-based education school. Demographic information and course completion status (including the categories and the number of courses they completed) of all the participants were collected. RESULTS: A total of 590,912 pregnant women participated in the web-based prenatal education in 2018. Among them, 188,508 (31.90%) participants were excluded because they did not complete any course, while 17,807 (3.01%) actively participated in web-based prenatal education and completed more than 100 courses. There were 5 categories of web-based courses; almost half of the pregnant women attended the courses on first and second trimesters (293,262/590,912, 49.63% and 298,168/590,912, 50.46%, respectively). We found that pregnant women were more concerned about the gestational diet, fetal-related knowledge, and other precautions before the labor. CONCLUSIONS: In the era of digitalization where information is rapidly disseminated, web-based prenatal education could become a more convenient, productive, and effective pathway for pregnant women since it could help them obtain adequate and optimal pregnancy-related information and gain more intellectual awareness about their pregnancy or preparation for pregnancy.

The cost-effectiveness of bivalent, quadrivalent, and nine-valent HPV vaccination in Asia: a systematic review.

PURPOSE: The aim of this study was to systematically review the cost-effectiveness of HPV vaccination in Asia. METHODS: We performed a systematic review of papers indexed in PubMed, Scopus, and Web of Science covering the period from 1 January 2000 to 13 August 2020. RESULTS: Sixteen studies were included in the review. Half of them (8 studies) evaluated the cost-effectiveness of HPV vaccination in high-income countries and regions (HICs) while the other eight studies were set in low- and middle-income countries and regions (LMICs). In HICs, the implementation of bivalent, quadrivalent and nine-valent HPV vaccination was all shown to be cost-effective. Most studies (7/8) also showed that it was cost-effective to implement bivalent, quadrivalent, and nine-valent HPV vaccines in LMICs. However, one study concluded that it was not cost-effective to implement bivalent HPV vaccination in Thailand. CONCLUSION: In general, the implementation of bivalent, quadrivalent and nine-valent HPV vaccination for adolescent girls was cost-effective in both high-income countries and regions and low- and middle-income countries and regions in Asia. Policy makers in HICs could consider expanding the target vaccinated population, while for LMICs it is essential to reduce HPV vaccine price to a level at which the implementation of HPV vaccination is cost-effective.

Factors associated with interest in a long-acting HIV regimen: perspectives of people living with HIV and healthcare providers in four European countries.

OBJECTIVES: A novel long-acting regimen (LAR) of cabotegravir and rilpivirine for HIV treatment requires dosing every 2 months instead of daily. We assessed what proportion of people living with HIV and physicians would be interested in trying and offering LAR respectively and why. METHODS: 688 people living with HIV on treatment, and 120 HIV physicians completed web-based surveys in Germany, Italy, the UK and France during 2019. Balanced description of a hypothetical LAR regarding efficacy, administration and possible side effects were provided. The hypothetical long-acting injections were assumed to be cost-neutral to current daily oral antiretrovirals. Interest of people living with HIV in trying ('very'/'highly') and physicians' willingness to offer ('definitely'/'probably') this LAR in different situations, with perceived benefits/concerns was measured. RESULTS: Of people living with HIV, 65.8% were interested in trying LAR. The majority (~80%-90%) of those with unmet needs felt LAR would help, including those with strong medical needs (malabsorption and interfering gastrointestinal conditions), suboptimal adherence, confidentiality/privacy concerns and emotional burden of daily dosing. Of physicians, percentage willing to offer LAR varied situationally: strong medical need (dysphagia, 93.3%; malabsorption, 91.6%; interfering gastrointestinal issues, 90.0%; central nervous system disorders, 87.5%); suboptimal adherence (84.2%); confidentiality/privacy concerns (hiding medications, 86.6%) and convenience/lifestyle (84.2%). People living with HIV liked LAR for not having to carry pills when travelling (56.3%); physicians liked the increased patient contact (54.2%). Furthermore, 50.0% of people living with HIV perceived LAR would minimise transmission risk and improve their sexual health. The most disliked attribute was scheduling appointments (37.2%) and resource constraints (57.5%) for people living with HIV and physicians, respectively. Physicians estimated 25.7% of their patients would actually switch. CONCLUSION: Providers and people living with HIV viewed the described LAR as addressing several unmet needs. Alternative treatment routes and especially LAR may improve adherence and quality of life.

Coronavirus disease 2019 vaccine response in pregnant and lactating women: a cohort study.

BACKGROUND: Pregnant and lactating women were excluded from initial coronavirus disease 2019 vaccine trials; thus, data to guide vaccine decision making are lacking. OBJECTIVE: This study aimed to evaluate the immunogenicity and reactogenicity of coronavirus disease 2019 messenger RNA vaccination in pregnant and lactating women compared with: (1) nonpregnant controls and (2) natural coronavirus disease 2019 infection in pregnancy. STUDY DESIGN: A total of 131 reproductive-age vaccine recipients (84 pregnant, 31 lactating, and 16 nonpregnant women) were enrolled in a prospective cohort study at 2 academic medical centers. Titers of severe acute respiratory syndrome coronavirus 2 spike and receptor-binding domain immunoglobulin G, immunoglobulin A, and immunoglobulin M were quantified in participant sera (n=131) and breastmilk (n=31) at baseline, at the second vaccine dose, at 2 to 6 weeks after the second vaccine, and at delivery by Luminex. Umbilical cord sera (n=10) titers were assessed at delivery. Titers were compared with those of pregnant women 4 to 12 weeks from the natural infection (n=37) by enzyme-linked immunosorbent assay. A pseudovirus neutralization assay was used to quantify neutralizing antibody titers for the subset of women who delivered during the study period. Postvaccination symptoms were assessed via questionnaire. Kruskal-Wallis tests and a mixed-effects model, with correction for multiple comparisons, were used to assess differences among groups. RESULTS: Vaccine-induced antibody titers were equivalent in pregnant and lactating compared with nonpregnant women (pregnant, median, 5.59; interquartile range, 4.68-5.89; lactating, median, 5.74; interquartile range, 5.06-6.22; nonpregnant, median, 5.62; interquartile range, 4.77-5.98, P=.24). All titers were significantly higher than those induced by severe acute respiratory syndrome coronavirus 2 infection during pregnancy (P<.0001). Vaccine-generated antibodies were present in all umbilical cord blood and breastmilk samples. Neutralizing antibody titers were lower in umbilical cord than maternal sera, although this finding did not achieve statistical significance (maternal sera, median, 104.7; interquartile range, 61.2-188.2; cord sera, median, 52.3; interquartile range, 11.7-69.6; P=.05). The second vaccine dose (boost dose) increased severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G, but not immunoglobulin A, in maternal blood and breastmilk. No differences were noted in reactogenicity across the groups. CONCLUSION: Coronavirus disease 2019 messenger RNA vaccines generated robust humoral immunity in pregnant and lactating women, with immunogenicity and reactogenicity similar to that observed in nonpregnant women. Vaccine-induced immune responses were statistically significantly greater than the response to natural infection. Immune transfer to neonates occurred via placenta and breastmilk.

Maternal tobacco exposure and health-related quality of life during pregnancy: a national-based study of pregnant women in China.

BACKGROUND: With the increase of the number of smokers, tobacco exposure among pregnant women is becoming more and more common. Pregnant women exposed to first-hand smoke and second-hand smoke are susceptible to physiological and psychological health issues has been proved in previous studies. Nevertheless, there are no enough studies focus on the impact of third-hand smoke during pregnancy. This study aimed to assess and compare health-related quality of life for pregnant women with exposure to first-hand smoke, second-hand smoke, third-hand smoke and non-exposure to tobacco in mainland China. METHODS: National-based cross-sectional study is based on a questionnaire survey which collects information including demographics, smoking behaviors and self-evaluation. All questionnaires were delivered and collected from August to September 2019. EuroQol group's visual analog scale and EuroQoL Five-dimension Questionnaire were used to collect data in mainland China. RESULTS: Totally, 15,682 pregnant women were included in this study, among which non-exposure to smoke were 7564 (48.2%), exposed to first-hand smoke, second-hand smoke and third-hand smoke were 89 (0.6%), 2349 (15.0%), and 5680 (36.2%) respectively. Pregnant women without tobacco exposure had the highest EuroQol group's visual analog scale score (mean value = 85.4[SD = 14.0]), while those with first-hand smoke had the lowest score (mean value = 77.4[SD = 22.2]). Among all five dimensions of EuroQoL Five-dimension Questionnaire, there were significant differences of EQ-index among groups with different tobacco exposure in usual activity and anxiety or depression dimensions (p < 0.001). CONCLUSIONS: Third-hand smoke exposure had close relationship with low health-related quality of life in pregnant women. Moreover, second-hand smoke exposure significantly led more problems on mental dimension of pregnant women.

Health-related quality of life in different trimesters during pregnancy.

BACKGROUND: Pregnant women experience physical, physiological, and mental changes. Health-related quality of life (HRQoL) is a relevant indicator of psychological and physical behaviours, changing over the course of pregnancy. This study aims to assess HRQoL of pregnant women during different stages of pregnancy. METHODS: This cross-sectional study was performed using the The EuroQoL Group's five-dimension five-level questionnaire (EQ-5D-5L) to assess the HRQoL of pregnant women, and demographic data were collected. This study was conducted in a regional university hospital in Guangzhou, China. RESULTS: A total of 908 pregnant women were included in this study. Pregnant women in the early 2nd trimester had the highest HRQoL. The HRQoL of pregnant women rose from the 1st trimester to the early 2nd trimester, and dropped to the bottom at the late 3rd trimester due to some physical and mental changes. Reports of pain/discomfort problem were the most common (46.0%) while self-care were the least concern. More than 10% of pregnant women in the 1st trimester had health-related problems in at least one dimension of whole five dimensions. In the whole sample, the EuroQoL Group's visual analog scale (EQ-VAS) was 87.86 ± 9.16. Across the gestational stages, the HRQoL remained stable during the pregnancy but the highest value was observed in the 1st trimester (89.65 ± 10.13) while the lowest was in the late 3rd trimester (87.28 ± 9.13). CONCLUSIONS: During pregnancy, HRQoL were associated with gestational trimesters in a certain degree. HRQoL was the highest in the early 2nd trimester and then decreased to the lowest in the late 3rd trimester due to a series of physical and psychological changes. Therefore, obstetric doctors and medical institutions should give more attention and care to pregnant women in the late 3rd trimester.

Dose-related and contextual aspects of suboptimal adherence to antiretroviral therapy among persons living with HIV in Western Europe.

BACKGROUND: The daily oral dosing requirement for antiretroviral therapy (ART) may be challenging for some people living with HIV (PLWHIV) with comorbid conditions, confidentiality concerns or pill fatigue. We investigated suboptimal adherence from the perspective of PLWHIV and HIV physicians. METHODS: PLWHIV on ART (n = 688) and HIV physicians (n = 120) were surveyed during 2019 in France, Germany, Italy and the UK. Suboptimal adherence was a report the participant missed taking their dose as prescribed 'Sometimes'/'Often'/'Very often'. Physicians' interest in offering a hypothetical long-acting HIV regimen for suboptimally adherent patients was assessed. Descriptive and multivariable analyses were performed (P < 0.05). RESULTS: Of PLWHIV, 23.8% (164/688) reported suboptimal adherence vs. providers' estimated prevalence of 33.6% (SD = 28.8). PLWHIV-reported prevalence of specific suboptimal adherence behaviors were: mistimed dose [16.1% (111/688)]; missed a dose [15.7% (108/688)]; dosed under wrong conditions [e.g. food restrictions, 10.5% (72/688)] and overdosed [3.3% (23/688)]. Odds of suboptimal adherence were higher among those with vs. without a report of the following: dysphagia (AOR = 3.61, 95% CI = 2.28-5.74), stress/anxiety because of their daily dosing schedule (AOR = 3.09, 95% CI = 1.97-4.85), gastrointestinal side effects (AOR = 2.09, 95% CI = 1.39-3.15), neurocognitive/mental health conditions (AOR = 1.88, 95% CI = 1.30-2.72) or hiding their HIV medication (AOR = 1.51, 95% CI = 1.04-2.19). Of providers, 84.2% indicated they Definitely/Probably will offer a hypothetical long-acting HIV regimen 'for patients who have suboptimal levels of adherence to daily oral therapy (50-90%) for non-medical reasons'. CONCLUSIONS: Dysphagia, stressful daily oral dosing schedule, gastrointestinal side effects, neurocognitive/mental health conditions and confidentiality concerns were associated with suboptimal adherence in our study. Adherence support and alternative regimens, such as long-acting antiretroviral therapies, could help address these challenges.

Patients' Preferences for Artificial Intelligence Applications Versus Clinicians in Disease Diagnosis During the SARS-CoV-2 Pandemic in China: Discrete Choice Experiment.

BACKGROUND: Misdiagnosis, arbitrary charges, annoying queues, and clinic waiting times among others are long-standing phenomena in the medical industry across the world. These factors can contribute to patient anxiety about misdiagnosis by clinicians. However, with the increasing growth in use of big data in biomedical and health care communities, the performance of artificial intelligence (Al) techniques of diagnosis is improving and can help avoid medical practice errors, including under the current circumstance of COVID-19. OBJECTIVE: This study aims to visualize and measure patients' heterogeneous preferences from various angles of AI diagnosis versus clinicians in the context of the COVID-19 epidemic in China. We also aim to illustrate the different decision-making factors of the latent class of a discrete choice experiment (DCE) and prospects for the application of AI techniques in judgment and management during the pandemic of SARS-CoV-2 and in the future. METHODS: A DCE approach was the main analysis method applied in this paper. Attributes from different dimensions were hypothesized: diagnostic method, outpatient waiting time, diagnosis time, accuracy, follow-up after diagnosis, and diagnostic expense. After that, a questionnaire is formed. With collected data from the DCE questionnaire, we apply Sawtooth software to construct a generalized multinomial logit (GMNL) model, mixed logit model, and latent class model with the data sets. Moreover, we calculate the variables' coefficients, standard error, P value, and odds ratio (OR) and form a utility report to present the importance and weighted percentage of attributes. RESULTS: A total of 55.8% of the respondents (428 out of 767) opted for AI diagnosis regardless of the description of the clinicians. In the GMNL model, we found that people prefer the 100% accuracy level the most (OR 4.548, 95% CI 4.048-5.110, P<.001). For the latent class model, the most acceptable model consists of 3 latent classes of respondents. The attributes with the most substantial effects and highest percentage weights are the accuracy (39.29% in general) and expense of diagnosis (21.69% in general), especially the preferences for the diagnosis "accuracy" attribute, which is constant across classes. For class 1 and class 3, people prefer the AI + clinicians method (class 1: OR 1.247, 95% CI 1.036-1.463, P<.001; class 3: OR 1.958, 95% CI 1.769-2.167, P<.001). For class 2, people prefer the AI method (OR 1.546, 95% CI 0.883-2.707, P=.37). The OR of levels of attributes increases with the increase of accuracy across all classes. CONCLUSIONS: Latent class analysis was prominent and useful in quantifying preferences for attributes of diagnosis choice. People's preferences for the "accuracy" and "diagnostic expenses" attributes are palpable. AI will have a potential market. However, accuracy and diagnosis expenses need to be taken into consideration.

Preferences for Artificial Intelligence Clinicians Before and During the COVID-19 Pandemic: Discrete Choice Experiment and Propensity Score Matching Study.

BACKGROUND: Artificial intelligence (AI) methods can potentially be used to relieve the pressure that the COVID-19 pandemic has exerted on public health. In cases of medical resource shortages caused by the pandemic, changes in people's preferences for AI clinicians and traditional clinicians are worth exploring. OBJECTIVE: We aimed to quantify and compare people's preferences for AI clinicians and traditional clinicians before and during the COVID-19 pandemic, and to assess whether people's preferences were affected by the pressure of pandemic. METHODS: We used the propensity score matching method to match two different groups of respondents with similar demographic characteristics. Respondents were recruited in 2017 and 2020. A total of 2048 respondents (2017: n=1520; 2020: n=528) completed the questionnaire and were included in the analysis. Multinomial logit models and latent class models were used to assess people's preferences for different diagnosis methods. RESULTS: In total, 84.7% (1115/1317) of respondents in the 2017 group and 91.3% (482/528) of respondents in the 2020 group were confident that AI diagnosis methods would outperform human clinician diagnosis methods in the future. Both groups of matched respondents believed that the most important attribute of diagnosis was accuracy, and they preferred to receive combined diagnoses from both AI and human clinicians (2017: odds ratio [OR] 1.645, 95% CI 1.535-1.763; P<.001; 2020: OR 1.513, 95% CI 1.413-1.621; P<.001; reference: clinician diagnoses). The latent class model identified three classes with different attribute priorities. In class 1, preferences for combined diagnoses and accuracy remained constant in 2017 and 2020, and high accuracy (eg, 100% accuracy in 2017: OR 1.357, 95% CI 1.164-1.581) was preferred. In class 2, the matched data from 2017 were similar to those from 2020; combined diagnoses from both AI and human clinicians (2017: OR 1.204, 95% CI 1.039-1.394; P=.011; 2020: OR 2.009, 95% CI 1.826-2.211; P<.001; reference: clinician diagnoses) and an outpatient waiting time of 20 minutes (2017: OR 1.349, 95% CI 1.065-1.708; P<.001; 2020: OR 1.488, 95% CI 1.287-1.721; P<.001; reference: 0 minutes) were consistently preferred. In class 3, the respondents in the 2017 and 2020 groups preferred different diagnosis methods; respondents in the 2017 group preferred clinician diagnoses, whereas respondents in the 2020 group preferred AI diagnoses. In the latent class, which was stratified according to sex, all male and female respondents in the 2017 and 2020 groups believed that accuracy was the most important attribute of diagnosis. CONCLUSIONS: Individuals' preferences for receiving clinical diagnoses from AI and human clinicians were generally unaffected by the pandemic. Respondents believed that accuracy and expense were the most important attributes of diagnosis. These findings can be used to guide policies that are relevant to the development of AI-based health care.

A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China.

A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.

Online Antenatal Care During the COVID-19 Pandemic: Opportunities and Challenges.

People across the world have been greatly affected by the ongoing coronavirus disease (COVID-19) pandemic. The high infection risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in hospitals is particularly problematic for recently delivered mothers and currently pregnant women who require professional antenatal care. Online antenatal care would be a preferable alternative for these women since it can provide pregnancy-related information and remote clinic consultations. In addition, online antenatal care may help to provide relatively economical medical services and diminish health care inequality due to its convenience and cost-effectiveness, especially in developing countries or regions. However, some pregnant women will doubt the reliability of such online information. Therefore, it is important to ensure the quality and safety of online services and establish a stable, mutual trust between the pregnant women, the obstetric care providers and the technology vis-a-vis the online programs. Here, we report how the COVID-19 pandemic brings not only opportunities for the development and popularization of online antenatal care programs but also challenges.

Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach.

BACKGROUND: In December 2019, a few coronavirus disease (COVID-19) cases were first reported in Wuhan, Hubei, China. Soon after, increasing numbers of cases were detected in other parts of China, eventually leading to a disease outbreak in China. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus, such as its pathogenesis, spread, prevention, and containment. OBJECTIVE: The aim of this study was to collect media reports on COVID-19 and investigate the patterns of media-directed health communications as well as the role of the media in this ongoing COVID-19 crisis in China. METHODS: We adopted the WiseSearch database to extract related news articles about the coronavirus from major press media between January 1, 2020, and February 20, 2020. We then sorted and analyzed the data using Python software and Python package Jieba. We sought a suitable topic number with evidence of the coherence number. We operated latent Dirichlet allocation topic modeling with a suitable topic number and generated corresponding keywords and topic names. We then divided these topics into different themes by plotting them into a 2D plane via multidimensional scaling. RESULTS: After removing duplications and irrelevant reports, our search identified 7791 relevant news reports. We listed the number of articles published per day. According to the coherence value, we chose 20 as the number of topics and generated the topics' themes and keywords. These topics were categorized into nine main primary themes based on the topic visualization figure. The top three most popular themes were prevention and control procedures, medical treatment and research, and global or local social and economic influences, accounting for 32.57% (n=2538), 16.08% (n=1258), and 11.79% (n=919) of the collected reports, respectively. CONCLUSIONS: Topic modeling of news articles can produce useful information about the significance of mass media for early health communication. Comparing the number of articles for each day and the outbreak development, we noted that mass media news reports in China lagged behind the development of COVID-19. The major themes accounted for around half the content and tended to focus on the larger society rather than on individuals. The COVID-19 crisis has become a worldwide issue, and society has become concerned about donations and support as well as mental health among others. We recommend that future work addresses the mass media's actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.

An Innovative Artificial Intelligence-Based App for the Diagnosis of Gestational Diabetes Mellitus (GDM-AI): Development Study.

BACKGROUND: Gestational diabetes mellitus (GDM) can cause adverse consequences to both mothers and their newborns. However, pregnant women living in low- and middle-income areas or countries often fail to receive early clinical interventions at local medical facilities due to restricted availability of GDM diagnosis. The outstanding performance of artificial intelligence (AI) in disease diagnosis in previous studies demonstrates its promising applications in GDM diagnosis. OBJECTIVE: This study aims to investigate the implementation of a well-performing AI algorithm in GDM diagnosis in a setting, which requires fewer medical equipment and staff and to establish an app based on the AI algorithm. This study also explores possible progress if our app is widely used. METHODS: An AI model that included 9 algorithms was trained on 12,304 pregnant outpatients with their consent who received a test for GDM in the obstetrics and gynecology department of the First Affiliated Hospital of Jinan University, a local hospital in South China, between November 2010 and October 2017. GDM was diagnosed according to American Diabetes Association (ADA) 2011 diagnostic criteria. Age and fasting blood glucose were chosen as critical parameters. For validation, we performed k-fold cross-validation (k=5) for the internal dataset and an external validation dataset that included 1655 cases from the Prince of Wales Hospital, the affiliated teaching hospital of the Chinese University of Hong Kong, a non-local hospital. Accuracy, sensitivity, and other criteria were calculated for each algorithm. RESULTS: The areas under the receiver operating characteristic curve (AUROC) of external validation dataset for support vector machine (SVM), random forest, AdaBoost, k-nearest neighbors (kNN), naive Bayes (NB), decision tree, logistic regression (LR), eXtreme gradient boosting (XGBoost), and gradient boosting decision tree (GBDT) were 0.780, 0.657, 0.736, 0.669, 0.774, 0.614, 0.769, 0.742, and 0.757, respectively. SVM also retained high performance in other criteria. The specificity for SVM retained 100% in the external validation set with an accuracy of 88.7%. CONCLUSIONS: Our prospective and multicenter study is the first clinical study that supports the GDM diagnosis for pregnant women in resource-limited areas, using only fasting blood glucose value, patients' age, and a smartphone connected to the internet. Our study proved that SVM can achieve accurate diagnosis with less operation cost and higher efficacy. Our study (referred to as GDM-AI study, ie, the study of AI-based diagnosis of GDM) also shows our app has a promising future in improving the quality of maternal health for pregnant women, precision medicine, and long-distance medical care. We recommend future work should expand the dataset scope and replicate the process to validate the performance of the AI algorithms.

Statin therapy and association with ovarian cancer risk in the New England Case Control (NEC) study.

Statins are widely used to lower blood cholesterol and reduce risk for cardiovascular diseases, but attention has recently focused on a role in cancer prevention or therapy. Here we present data from a large case-control study addressing whether statin use can lower the risk for epithelial ovarian cancer (EOC). Between 1992 and 2008, data including medications used for at least 6 months were collected from 2,040 cases with EOC and 2,100 frequency-matched controls without the disease who participated in the New England Case Control study. We used unconditional logistic regression controlling for matching factors and potential confounders to examine the association between statin use and the risk for EOC. Overall, women who used statins had 32% lower risk of ovarian cancer compared to non-users (Odds ratio (OR) 0.68, 95% Confidence Interval (CI): 0.54-0.85), adjusting for the matching factors and other covariates. The reduced risk was most apparent in women taking a lipophilic statin who began use after age 49, and who had used them 2-4.9 years. Statin use was associated with lower risks for both serous and non-serous histologic subtypes with the strongest effect seen for mucinous and mixed epithelial subtypes. The association became apparent about a decade after the introduction of statins and did not appear to be confounded by indications for use of statins or medications used concomitantly. In this case-control study, statins were found to lower the risk for both serous and non-serous EOC and especially mucinous EOC.

Th17 Inhibitors in Active Psoriatic Arthritis: A Systematic Review and Meta-Analysis of Randomized Controlled Clinical Trials.

BACKGROUND: Several biologics targeting the Th17 pathway have been developed for the treatment of psoriatic arthritis (PsA), a disabling disease with moderate response and an increased incidence of serious infections to first-line biologics (TNF-α antagonists). Th17 inhibitors could replace TNF-α antagonists as first-line biologic agents. We determined the overall treatment effect of Th17 pathway inhibitors compared to placebo or active control on American College of Rheumatology (ACR) 20 response at week 12 (primary objective), risk of infections, discontinuation of treatment due to adverse events, and serious adverse events during the placebo-controlled period (12-24 weeks) in adults with active PsA in published randomized controlled trials. METHODS: The SCOPUS database was searched. The Cochrane risk of bias tool was used for assessing quality. The pooled relative risk (RR) was derived from random effects models. RESULTS: Seven randomized controlled trials were included which randomized 1,718 patients to Th17 inhibitors and 840 to placebo. Patients treated with Th17 inhibitors had an RR of 2.04 (95% CI: 1.79-2.33; p < 0.001) for achieving an ACR20 response at week 12 (I2 = 0%; p = 0.89) compared to placebo-treated patients. There was no evidence of publication bias. The result was consistent for study phase and outcome (ACR50/70), mechanism of action and TNF-α naivety. RR of infections was 1.06 (0.91-1.23), that of candida infections was 3.35 (0.75-14.95), that of serious adverse events was 0.82 (0.42-1.59) and that of discontinuation of treatment was 0.54 (0.31-0.93) among treated versus placebo subjects. No incident cases of tuberculosis were reported. CONCLUSION: In patients with active PsA, biologics targeting the Th17 axis produce a clinically significant improvement in joint disease activity with acceptable safety and tolerability for short-term treatment compared to placebo.

Modeling optimal cervical cancer prevention strategies in Nigeria.

BACKGROUND: This study aims to assess the most efficient combinations of vaccination and screening coverage for the prevention of cervical cancer (CC) at different levels of expenditure in Nigeria. METHODS: An optimization procedure, using a linear programming approach and requiring the use of two models (an evaluation and an optimization model), was developed. The evaluation model, a Markov model, estimated the annual number of CC cases at steady state in a population of 100,000 women for four alternative strategies: screening only; vaccination only; screening and vaccination; and no prevention. The results of the Markov model for each scenario were used as inputs to the optimization model determining the optimal proportion of the population to receive screening and/or vaccination under different scenarios. The scenarios varied by available budget, maximum screening and vaccination coverage, and overall reachable population. RESULTS: In the base-case optimization model analyses, with a coverage constraint of 20% for one lifetime screening, 95% for vaccination and a budget constraint of $1 per woman per year to minimize CC incidence, the optimal mix of prevention strategies would result in a reduction of CC incidence of 31% (3-dose vaccination available) or 46% (2-dose vaccination available) compared with CC incidence pre-vaccination. With a 3-dose vaccination schedule, the optimal combination of the different strategies across the population would be 20% screening alone, 39% vaccination alone and 41% with no prevention, while with a 2-dose vaccination schedule the optimal combination would be 71% vaccination alone, and 29% with no prevention. Sensitivity analyses indicated that the results are sensitive to the constraints included in the optimization model as well as the cervical intraepithelial neoplasia (CIN) and CC treatment cost. CONCLUSIONS: The results of the optimization model indicate that, in Nigeria, the most efficient allocation of a limited budget would be to invest in both vaccination and screening with a 3-dose vaccination schedule, and in vaccination alone before implementing a screening program with a 2-dose vaccination schedule.

Placental transfer dynamics and durability of maternal COVID-19 vaccine-induced antibodies in infants.

Completion of a COVID-19 vaccination series during pregnancy effectively reduces COVID-19 hospitalization among infants less than 6 months of age. The dynamics of transplacental transfer of maternal vaccine-induced antibodies, and their persistence in infants at 2, 6, 9, and 12 months, have implications for new vaccine development and optimal timing of vaccine administration in pregnancy. We evaluated anti-COVID antibody IgG subclass, Fc-receptor binding profile, and activity against wild-type Spike and RBD plus five variants of concern (VOCs) in 153 serum samples from 100 infants. Maternal IgG1 and IgG3 responses persisted in 2- and 6-month infants to a greater extent than the other IgG subclasses, with high persistence of antibodies binding placental neonatal Fc-receptor and FcγR3A. Lowest persistence was observed against the Omicron RBD-specific region. Maternal vaccine timing, placental Fc-receptor binding capabilities, antibody subclass, fetal sex, and VOC all impact the persistence of antibodies in infants through 12 months of age.

SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity.

Pregnancy is a risk factor for increased severity of SARS-CoV-2 and other respiratory infections. The mechanisms underlying this risk have not been well-established, partly due to a limited understanding of how pregnancy shapes immune responses. To gain insight into the role of pregnancy in modulating immune responses at steady state and upon perturbation, we collected peripheral blood mononuclear cells (PBMC), plasma, and stool from 226 women, including 152 pregnant individuals (n = 96 with SARS-CoV-2 infection and n = 56 healthy controls) and 74 non-pregnant women (n = 55 with SARS-CoV-2 and n = 19 healthy controls). We found that SARS-CoV-2 infection was associated with altered T cell responses in pregnant compared to non-pregnant women. Differences included a lower percentage of memory T cells, a distinct clonal expansion of CD4-expressing CD8 + T cells, and the enhanced expression of T cell exhaustion markers, such as programmed cell death-1 (PD-1) and T cell immunoglobulin and mucin domain-3 (Tim-3), in pregnant women. We identified additional evidence of immune dysfunction in severely and critically ill pregnant women, including a lack of expected elevation in regulatory T cell (Treg) levels, diminished interferon responses, and profound suppression of monocyte function. Consistent with earlier data, we found maternal obesity was also associated with altered immune responses to SARS-CoV-2 infection, including enhanced production of inflammatory cytokines by T cells. Certain gut bacterial species were altered in pregnancy and upon SARS-CoV-2 infection in pregnant individuals compared to non-pregnant women. Shifts in cytokine and chemokine levels were also identified in the sera of pregnant individuals, most notably a robust increase of interleukin-27 (IL-27), a cytokine known to drive T cell exhaustion, in the pregnant uninfected control group compared to all non-pregnant groups. IL-27 levels were also significantly higher in uninfected pregnant controls compared to pregnant SARS-CoV-2-infected individuals. Using two different preclinical mouse models of inflammation-induced fetal demise and respiratory influenza viral infection, we found that enhanced IL-27 protects developing fetuses from maternal inflammation but renders adult female mice vulnerable to viral infection. These combined findings from human and murine studies reveal nuanced pregnancy-associated immune responses, suggesting mechanisms underlying the increased susceptibility of pregnant individuals to viral respiratory infections.

SARS-CoV-2 infection elucidates features of pregnancy-specific immunity.

Pregnancy is a risk factor for increased severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory infections, but the mechanisms underlying this risk are poorly understood. To gain insight into the role of pregnancy in modulating immune responses at baseline and upon SARS-CoV-2 infection, we collected peripheral blood mononuclear cells and plasma from 226 women, including 152 pregnant individuals and 74 non-pregnant women. We find that SARS-CoV-2 infection is associated with altered T cell responses in pregnant women, including a clonal expansion of CD4-expressing CD8+ T cells, diminished interferon responses, and profound suppression of monocyte function. We also identify shifts in cytokine and chemokine levels in the sera of pregnant individuals, including a robust increase of interleukin-27, known to drive T cell exhaustion. Our findings reveal nuanced pregnancy-associated immune responses, which may contribute to the increased susceptibility of pregnant individuals to viral respiratory infection.