Hasil untuk "Gynecology and obstetrics"

J. Brandt, O. Hadaya, M. Schuster et al.

Key Points Question What are the top-cited obstetrics and gynecology (OBGYN) articles in the Institute for Scientific Information Web of Science’s Science Citation Index Expanded and how do the articles from nonspecialty journals compare with those published in OBGYN specialty journals? Findings In this cross-sectional bibliometric analysis, search terms from the American Board of Obstetrics and Gynecology’s 2018 certifying examination topics list were used to identify top-cited articles from 1980 to 2018. Compared with top-cited articles published in OBGYN journals, those published in nonspecialty journals covered topics with broad interest to women’s health care professionals, were more frequently cited, and were more likely to be randomized trials. Meaning There are substantial differences between top-cited OBGYN articles published in nonspecialty vs OBGYN journals, which likely reflect the different goals of the journals.

Wei Y, Wang Y, Cao P et al.

Yuxuan Wei,1,2,* Yongli Wang,3,* Peichun Cao,4,* Yuanyuan Gong,1 Jingjing Gong,1 Li Yang,1 Jin Chen,5 Jingli Wang,4 Xiaodan Li1 1Department of Obstetrics and Gynecology, Peking University People’s Hospital, Beijing, People’s Republic of China; 2School of Nursing, Hebei University, Baoding, People’s Republic of China; 3Department of Pediatrics, Peking University People’s Hospital, Beijing, People’s Republic of China; 4Department of Musculoskeletal Tumor Center, Peking University People’s Hospital, Beijing, People’s Republic of China; 5Department of Breast Center, Peking University People’s Hospital, Beijing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiaodan Li, Email lixiaodan@pkuph.edu.cnObjective: To examine the mediating role of medical coping in the relationship between social support and illness uncertainty among patients with malignant tumors, and to explore differences across age groups.Methods: A secondary analysis was conducted using cross-sectional data from 905 hospitalized patients. Patient-reported outcomes were measured using the Mishel Uncertainty in Illness Scale–Adult, the Social Support Rating Scale, and the Medical Coping Modes Questionnaire. Pearson correlation analyses were conducted using SPSS version 25.0, and mediation effects were tested using the PROCESS macro with bootstrap resampling.Results: In the overall sample, medical coping partially mediated the relationship between social support and illness uncertainty (indirect effect: β = 0.177, SE = 0.061, bootstrap 95% CI [0.067, 0.306]). Age-stratified analyses showed a full mediation effect in younger patients (β = 1.362, SE = 0.218, 95% CI [0.875, 1.737]). In contrast, the mediation effects were weaker in middle-aged and older patients, accounting for only 2.96% and 17.65% of the total effect, respectively. These findings indicate that the mediating role of medical coping varies across age groups, with distinct patterns observed among younger, middle-aged, and older patients.Conclusion: In this cross-sectional sample, the results were statistically consistent with an indirect association between social support and illness uncertainty via medical coping, with age-related differences. Younger patients showed a stronger indirect association via coping, whereas middle-aged and older patients showed relatively stronger direct associations between social support and illness uncertainty.Keywords: neoplasms, uncertainty in illness, social support, adaptation, psychological, nursing care

L. Drukker, J. Noble, A. T. Papageorghiou

Artificial intelligence (AI) uses data and algorithms to aim to draw conclusions that are as good as, or even better than, those drawn by humans. AI is already part of our daily life; it is behind face recognition technology, speech recognition in virtual assistants (such as Amazon Alexa, Apple's Siri, Google Assistant and Microsoft Cortana) and self‐driving cars. AI software has been able to beat world champions in chess, Go and recently even Poker. Relevant to our community, it is a prominent source of innovation in healthcare, already helping to develop new drugs, support clinical decisions and provide quality assurance in radiology. The list of medical image‐analysis AI applications with USA Food and Drug Administration or European Union (soon to fall under European Union Medical Device Regulation) approval is growing rapidly and covers diverse clinical needs, such as detection of arrhythmia using a smartwatch or automatic triage of critical imaging studies to the top of the radiologist's worklist. Deep learning, a leading tool of AI, performs particularly well in image pattern recognition and, therefore, can be of great benefit to doctors who rely heavily on images, such as sonologists, radiographers and pathologists. Although obstetric and gynecological ultrasound are two of the most commonly performed imaging studies, AI has had little impact on this field so far. Nevertheless, there is huge potential for AI to assist in repetitive ultrasound tasks, such as automatically identifying good‐quality acquisitions and providing instant quality assurance. For this potential to thrive, interdisciplinary communication between AI developers and ultrasound professionals is necessary. In this article, we explore the fundamentals of medical imaging AI, from theory to applicability, and introduce some key terms to medical professionals in the field of ultrasound. We believe that wider knowledge of AI will help accelerate its integration into healthcare. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Abdolmehdi Behroozi, Chaopeng Shen and, Daniel Kifer

Parametric differential equations of the form du/dt = f(u, x, t, p) are fundamental in science and engineering. While deep learning frameworks such as the Fourier Neural Operator (FNO) can efficiently approximate solutions, they struggle with inverse problems, sensitivity estimation (du/dp), and concept drift. We address these limitations by introducing a sensitivity-based regularization strategy, called Sensitivity-Constrained Fourier Neural Operators (SC-FNO). SC-FNO achieves high accuracy in predicting solution paths and consistently outperforms standard FNO and FNO with physics-informed regularization. It improves performance in parameter inversion tasks, scales to high-dimensional parameter spaces (tested with up to 82 parameters), and reduces both data and training requirements. These gains are achieved with a modest increase in training time (30% to 130% per epoch) and generalize across various types of differential equations and neural operators. Code and selected experiments are available at: https://github.com/AMBehroozi/SC_Neural_Operators

Tanja Auge, Sascha Genehr, Meike Klettke and et al.

Provenance information are essential for the traceability of scientific studies or experiments and thus crucial for ensuring the credibility and reproducibility of research findings. This paper discusses a comprehensive provenance framework combining the two types 1. workflow provenance, and 2. data provenance as well as their dimensions and granularity, which enables the answering of W7+1 provenance questions. We demonstrate the applicability by employing a biomedical research use case, that can be easily transferred into other scientific fields. An integration of these concepts into a unified framework enables credibility and reproducibility of the research findings.

A. Kaan Ata Yilmaz, Abhishek Kulkarni, Ufuk Topcu

In multiplayer games with sequential decision-making, self-interested players form dynamic coalitions to achieve most-preferred temporal goals beyond their individual capabilities. We introduce a novel procedure to synthesize strategies that jointly determine which coalitions should form and the actions coalition members should choose to satisfy their preferences in a subclass of deterministic multiplayer games on graphs. In these games, a leader decides the coalition during each round and the players not in the coalition follow their admissible strategies. Our contributions are threefold. First, we extend the concept of admissibility to games on graphs with preferences and characterize it using maximal sure winning, a concept originally defined for adversarial two-player games with preferences. Second, we define a value function that assigns a vector to each state, identifying which player has a maximal sure winning strategy for certain subset of objectives. Finally, we present a polynomial-time algorithm to synthesize admissible strategies for all players based on this value function and prove their existence in all games within the chosen subclass. We illustrate the benefits of dynamic coalitions over fixed ones in a blocks-world domain. Interestingly, our experiment reveals that aligned preferences do not always encourage cooperation, while conflicting preferences do not always lead to adversarial behavior.

Melissa Blum, Donato DeIngeniis, Daniela K. Shill et al.

Introduction: Rising ambient temperatures threaten vulnerable populations such as pregnant women, with urban populations bearing a greater risk due to the urban heat island effect. Here, we assessed the independent effects of trimester-specific warm season exposure during pregnancy and neighborhood heat vulnerability on maternal outcomes, including gestational diabetes, hypertensive disorders of pregnancy, genitourinary infections, and operative delivery. Methods: This retrospective study analyzed 819 participants from the Stress in Pregnancy Study (2009–2014), a longitudinal birth cohort study in New York City. Generalized linear models examined associations between trimester-specific warm season exposure, New York City Heat Vulnerability Index (ranging 1-5), and adverse maternal outcomes, adjusting for demographics, parity, and substance use. Results: First trimester warm season exposure was associated with increased odds of gestational hypertension (adjusted odds ratio [AOR] 4.50, 95%CI 1.17-17.27), preeclampsia (AOR 4.38, 95%CI 1.51-12.75), and genitourinary infection (AOR 2.27, 95%CI 1.14-4.51). Each unit increase in heat vulnerability index was associated with increased odds of preeclampsia (AOR 1.38, 95%CI 1.05-1.81) and genitourinary infection (AOR 1.32, 95%CI 1.11-1.57). Conclusions: Both early pregnancy warm weather exposure and neighborhood vulnerability independently increased the risk of adverse maternal complications. Our findings provide evidence in support of targeted heat mitigation strategies to limit heat exposure in at-risk communities as climate change progresses.

Haoxing Liu, Fangzhou Shen, Haoshen Qin and et al.

With the rapid development of civil aviation and the significant improvement of people's living standards, taking an air plane has become a common and efficient way of travel. However, due to the flight characteris-tics of the aircraft and the sophistication of the fuselage structure, flight de-lays and flight accidents occur from time to time. In addition, the life risk factor brought by aircraft after an accident is also the highest among all means of transportation. In this work, a model based on back-propagation neural network was used to predict flight accidents. By collecting historical flight data, including a variety of factors such as meteorological conditions, aircraft technical condition, and pilot experience, we trained a backpropaga-tion neural network model to identify potential accident risks. In the model design, a multi-layer perceptron structure is used to optimize the network performance by adjusting the number of hidden layer nodes and the learning rate. Experimental analysis shows that the model can effectively predict flight accidents with high accuracy and reliability.

Elham Baradari and, Ozgur B Akan

Parkinson's disease (PD) is a progressive neurodegenerative disease, and it is caused by the loss of dopaminergic neurons in the basal ganglia (BG). Currently, there is no definite cure for PD, and available treatments mainly aim to alleviate its symptoms. Due to impaired neurotransmitter-based information transmission in PD, molecular communication-based approaches can be employed as potential solutions to address this issue. Molecular Communications (MC) is a bio-inspired communication method utilizing molecules for carrying information. This mode of communication stands out for developing bio-compatible nanomachines for diagnosing and treating, particularly in addressing neurodegenerative diseases like PD, due to its compatibility with biological systems. This study presents a novel treatment method that introduces an Intelligent Dopamine Rate Modulator (IDRM), which is located in the synaptic gap between the substantia nigra pars compacta (SNc) and striatum to compensate for insufficiency dopamine release in BG caused by PD. For storing dopamine in the IDRM, dopamine compound (DAC) is swallowed and crossed through the digestive system, blood circulatory system, blood-brain barrier (BBB), and brain extracellular matrix uptakes with IDRMs. Here, the DAC concentration is calculated in these regions, revealing that the required exogenous dopamine consistently reaches IDRM. Therefore, the perpetual dopamine insufficiency in BG associated with PD can be compensated. This method reduces drug side effects because dopamine is not released in other brain regions. Unlike other treatments, this approach targets the root cause of PD rather than just reducing symptoms.

Alejandro Cuetos and, Bruno Martínez-Haya, José Manuel Romero-Enrique

Discotic colloids give rise to a paradigmatic family of liquid crystals with sound applications in Materials Science. In this paper, Monte Carlo simulations are employed to characterize the low-temperature liquid crystal phase diagram and the vapour-liquid coexistence of discotic colloids interacting via a Kihara potential. Discoidal particles with thickness-diameter aspect ratios $L^*\equiv L/D$=\,0.5, 0.3, 0.2 and 0.1 are considered. For the less anisotropic particles ($L^*$$\ge$0.2), coexistence of a vapour phase with the isotropic fluid and with the columnar liquid crystal phase is observed. As the particle anisotropy increases, the vapour-liquid coexistence shifts to lower temperatures and its density range diminishes, eventually merging with coexistences involving the liquid crystal phases. The $L^*=$\,0.1 fluid displays a rich sequence of mesophases, including a nematic phase and a novel lamellar phase in which particles arrange in layers perpendicular to the nematic director.

Miguel F. Arevalo-Castiblanco, Eduardo Mojica-Nava and, César A. Uribe

We propose a robust adaptive online synchronization method for leader-follower networks of nonlinear heterogeneous agents with system uncertainties and input magnitude saturation. Synchronization is achieved using a Distributed input Magnitude Saturation Adaptive Control with Reinforcement Learning (DMSAC-RL), which improves the empirical performance of policies trained on off-the-shelf models using Reinforcement Learning (RL) strategies. The leader observes the performance of a reference model, and followers observe the states and actions of the agents they are connected to, but not the reference model. The leader and followers may differ from the reference model in which the RL control policy was trained. DMSAC-RL uses an internal loop that adjusts the learned policy for the agents in the form of augmented input to solve the distributed control problem, including input-matched uncertainty parameters. We show that the synchronization error of the heterogeneous network is Uniformly Ultimately Bounded (UUB). Numerical analysis of a network of Multiple Input Multiple Output (MIMO) systems supports our theoretical findings.

Nils Thorm Milman, Thomas Bergholt

Conclusion: Low-dose iron supplementation appears to have no clinically significant GI side effects, as none of the included women presented with GI complaints of such severity that it necessitated either reduction of iron dose, change to an alternative iron formula, or discontinuation of iron supplement. However, ferrous bisglycinate 25 mg iron/day is associated with significantly fewer GI complaints than ferrous fumarate 40 mg iron/day and ferrous sulphate 50 mg iron/day. Ferrous bisglycinate may be preferred for iron prophylaxis, especially in women experiencing GI side effects when taking other conventional iron formulas.

Thao Nguyen, Toshiaki Yoshikawa, Yusuke Ito et al.

Summary: Chimeric antigen receptor (CAR) T cell therapy often causes serious toxicities, such as cytokine release syndrome (CRS), mainly due to interleukin-6 (IL-6) secreted by monocyte lineage cells. Here, we describe a protocol to generate anti-CD19 CAR T cells and quantify human monocyte-derived IL-6 cocultured with CAR T cells and target tumor cells in vitro. We further describe a protocol to generate a humanized mouse model and evaluate CAR T cell-associated plasma IL-6 levels in vivo.For complete details on the use and execution of this protocol, please refer to Yoshikawa et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

G. D. Di Renzo, Jeanne A. Conry, J. Blake et al.

Exposure to toxic environmental chemicals during pregnancy and breastfeeding is ubiquitous and is a threat to healthy human reproduction. There are tens of thousands of chemicals in global commerce, and even small exposures to toxic chemicals during pregnancy can trigger adverse health consequences. Exposure to toxic environmental chemicals and related health outcomes are inequitably distributed within and between countries; universally, the consequences of exposure are disproportionately borne by people with low incomes. Discrimination, other social factors, economic factors, and occupation impact risk of exposure and harm. Documented links between prenatal exposure to environmental chemicals and adverse health outcomes span the life course and include impacts on fertility and pregnancy, neurodevelopment, and cancer. The global health and economic burden related to toxic environmental chemicals is in excess of millions of deaths and billions of dollars every year. On the basis of accumulating robust evidence of exposures and adverse health impacts related to toxic environmental chemicals, the International Federation of Gynecology and Obstetrics (FIGO) joins other leading reproductive health professional societies in calling for timely action to prevent harm. FIGO recommends that reproductive and other health professionals advocate for policies to prevent exposure to toxic environmental chemicals, work to ensure a healthy food system for all, make environmental health part of health care, and champion environmental justice.

P. Iftikhar, Marcela Kuijpers, Azadeh Khayyat et al.

Artificial intelligence (AI) is growing exponentially in various fields, including medicine. This paper reviews the pertinent aspects of AI in obstetrics and gynecology (OB/GYN) and how these can be applied to improve patient outcomes and reduce the healthcare costs and workload for clinicians. Herein, we will address current AI uses in OB/GYN, and the use of AI as a tool to interpret fetal heart rate (FHR) and cardiotocography (CTG) to aid in the detection of preterm labor, pregnancy complications, and review discrepancies in its interpretation between clinicians to reduce maternal and infant morbidity and mortality. AI systems can be used as tools to create algorithms identifying asymptomatic women with short cervical length who are at risk of preterm birth. Additionally, the benefits of using the vast data capacity of AI storage can assist in determining the risk factors for preterm labor using multiomics and extensive genomic data. In the field of gynecological surgery, the use of augmented reality helps surgeons detect vital structures, thus decreasing complications, reducing operative time, and helping surgeons in training to practice in a realistic setting. Using three-dimensional (3D) printers can provide materials that mimic real tissues and also helps trainees to practice on a realistic model. Furthermore, 3D imaging allows better depth perception than its two-dimensional (2D) counterpart, allowing the surgeon to create preoperative plans according to tissue depth and dimensions. Although AI has some limitations, this new technology can improve the prognosis and management of patients, reduce healthcare costs, and help OB/GYN practitioners to reduce their workload and increase their efficiency and accuracy by incorporating AI systems into their daily practice. AI has the potential to guide practitioners in decision-making, reaching a diagnosis, and improving case management. It can reduce healthcare costs by decreasing medical errors and providing more dependable predictions. AI systems can accurately provide information on the large array of patients in clinical settings, although more robust data is required.

H. Chaggara, A. Gahami and, N. Ben Romdhane

In this paper, we derive some explicit expansion formulas associated to Brenke polynomials using operational rules based on their corresponding generating functions. The obtained coefficients are expressed either in terms of finite double sums or finite sums or sometimes in closed hypergeometric terms. The derived results are applied to Generalized Gould-Hopper polynomials and Generalized Hermite polynomials introduced by Szegö and Chihara. Some well-known duplication and convolution formulas are deduced as particular cases.

María Morales-Suárez-Varela, Isabel Peraita-Costa, Alfredo Perales-Marín et al.

Gestation is a crucial life stage for both women and offspring, and outcomes are affected by many environmental factors, including diet. The Mediterranean dietary pattern (MD) is considered a healthy eating pattern that can provide the nutritional requirements of pregnancy. Meanwhile, iron deficiency anemia is one of the most frequent complications related to pregnancy. This study aimed to evaluate how the level of adherence to the MD influences maternal gestational weight gain and specific iron-related maternal biochemical parameters during the pregnancy. Accordingly, an observational, population-based study using data from pregnant women conducted over the entire course of their pregnancy was carried out. Adherence to the MD was assessed once using the MEDAS score questionnaire. Of the 506 women studied, 116 (22.9%) were classified as demonstrating a high adherence, 277 (54.7%) a medium adherence, and 113 (22.3%) a low adherence to the MD. No differences were observed in gestational weight gain among the MD adherence groups but the adequacy of weight gain did vary among the groups, with the proportions of inadequate (insufficient or excessive) weight gain presenting the most notable differences. Total anemia prevalence was 5.3%, 15.6%, and 12.3%, respectively, during the first, second, and third trimesters. For iron-related biochemical parameters, no differences are observed among the adherence groups during pregnancy. With high adherence to the MD as the reference group, the crude odds of iron deficiency diagnosis are significant in the first trimester for both the medium [OR = 2.99 (1.55–5.75)] and low [OR = 4.39 (2.15–8.96)] adherence groups, with deficient adherence to the Mediterranean dietary pattern being responsible for 66.5% (35.5–82.6) and 77.2% (53.5–88.8) of the risk of iron deficiency diagnosis for medium and low adherence, respectively. However, adjusted odds ratios were not significant, possibly due to the small sample size. Our data suggest that MD adherence could be related to gestational weight gain adequacy and that optimal adherence could reduce iron deficiency and/or anemia during pregnancy in the studied population.

Julia R. Varshavsky, Swati D. G. Rayasam, Jennifer B. Sass et al.

Abstract A key element of risk assessment is accounting for the full range of variability in response to environmental exposures. Default dose-response methods typically assume a 10-fold difference in response to chemical exposures between average (healthy) and susceptible humans, despite evidence of wider variability. Experts and authoritative bodies support using advanced techniques to better account for human variability due to factors such as in utero or early life exposure and exposure to multiple environmental, social, and economic stressors. This review describes: 1) sources of human variability and susceptibility in dose-response assessment, 2) existing US frameworks for addressing response variability in risk assessment; 3) key scientific inadequacies necessitating updated methods; 4) improved approaches and opportunities for better use of science; and 5) specific and quantitative recommendations to address evidence and policy needs. Current default adjustment factors do not sufficiently capture human variability in dose-response and thus are inadequate to protect the entire population. Susceptible groups are not appropriately protected under current regulatory guidelines. Emerging tools and data sources that better account for human variability and susceptibility include probabilistic methods, genetically diverse in vivo and in vitro models, and the use of human data to capture underlying risk and/or assess combined effects from chemical and non-chemical stressors. We recommend using updated methods and data to improve consideration of human variability and susceptibility in risk assessment, including the use of increased default human variability factors and separate adjustment factors for capturing age/life stage of development and exposure to multiple chemical and non-chemical stressors. Updated methods would result in greater transparency and protection for susceptible groups, including children, infants, people who are pregnant or nursing, people with disabilities, and those burdened by additional environmental exposures and/or social factors such as poverty and racism.

Jiayi Guo, Yajie Chang, Zhi Zeng et al.

Abstract Background Polycystic ovary syndrome (PCOS) is known to be associated with chronic low-grade inflammation and endometrial dysfunction. Chronic endometritis (CE) is a type of local inflammation that can contribute to endometrial dysfunction in infertile women. Some clinicians recommend screening for CE in women at high risk, such as those with endometrial polyps. However, it is still uncertain whether there is a relationship between PCOS and CE, as well as whether women with PCOS require enhanced screening for CE. This study was to assess the incidence of CE among infertile women with PCOS by hysteroscopy combined with histopathology CD138 immunohistochemical staining of endometrium. Methods A total of 205 patients in the PCOS group and 4021 patients in the non-PCOS group from July 2017 to August 2022 were included in this retrospective study. After nearest-neighbor 1:4 propensity score matching (PSM), 189 PCOS patients were matched with 697 non-PCOS patients. Basic information was recorded. The CE incidence was compared. The risk factors affecting CE incidence were also analyzed. Results No significantly higher CE incidence in infertile women with PCOS were found either in total analysis or after PSM (P = 0.969; P = 0.697; respectively). Similar results were discovered in the subgroup of Body Mass Index (BMI) (P = 0.301; P = 0.671; P = 0.427; respectively) as well as the four PCOS phenotypes (P = 0.157). Intriguingly, the incidence of CE increased as BMI increased in the PCOS group, even though no significant differences were found (P = 0.263). Multivariate logistic regression showed that age, infertility duration, infertility type, PCOS, and obesity were not the independent risk factors affecting CE incidence. Conclusion The incidence of CE in PCOS patients did not significantly increase compared to non-PCOS patients. Similarly, no significant differences in the incidence of CE were observed among different PCOS phenotypes. The current evidence does not substantiate the need for widespread CE screening among PCOS women, potentially mitigating the undue financial and emotional strain associated with such screenings.

A. Poprzeczny, K. Stocking, M. Showell et al.

OBJECTIVE To assess the effectiveness of patient decision aids to facilitate shared decision making in obstetrics and gynecology. DATA SOURCES We searched ClinicalTrials.gov, MEDLINE, CENTRAL, Cochrane Gynaecology and Fertility specialized register, CINAHL, and EMBASE from 1946 to July 2019. METHODS OF STUDY SELECTION We selected randomized controlled trials comparing patient decision aids with usual clinical practice or a control intervention. TABULATION, INTEGRATION, AND RESULTS Thirty-five randomized controlled trials, which reported data from 9,790 women, were included. Patient decision aids were evaluated within a wide range of clinical scenarios relevant to obstetrics and gynecology, including contraception, vaginal birth after cesarean delivery, and pelvic organ prolapse. Study characteristics and quality were recorded for each study. The meta-analysis was based on random-effects methods for pooled data. A standardized mean difference of 0.2 is considered small, 0.5 moderate, and 0.8 large. When compared with usual clinical practice, the use of patient decision aids reduced decisional conflict (standardized mean difference -0.23; 95% CI -0.36, to -0.11; 19 trials; 4,624 women) and improved patient knowledge (standardized mean difference 0.58; 95% CI 0.44 to 0.71; 17 trials; 4,375 women). There was no difference in patient anxiety (standardized mean difference -0.04; 95% CI -0.14 to 0.06; 12 trials; 2,714 women) or satisfaction (standardized mean difference 0.17; 95% CI 0.09 to 0.24; 6 trials; 2,718 women). CONCLUSION Patient decision aids are effective in facilitating shared decision making and can be helpful in clinical practice to support patient centered care informed by the best evidence. SYSTEMATIC REVIEW REGISTRATION PROSPERO International Register of Systematic Reviews, www.crd.york.ac.uk/prospero/89953, CRD42018089953.