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PsyCh Journal Jun 2024The present study aimed to examine the psychological impact of the COVID-19 pandemic on infertile patients. We adopted a comparison design and searched articles... (Review)
Review
The present study aimed to examine the psychological impact of the COVID-19 pandemic on infertile patients. We adopted a comparison design and searched articles published from 1 September 2016 to 31 December 2019 as the control group, while articles published from 1 January 2020 to 31 April 2023 were treated as the pandemic group. Specifically, Web of Science, PubMed, Medline, PsycArticle, CNKI and PsycINFO were searched to identify potential eligible records. Risk of bias was assessed, and random-effects meta-analyses were conducted to estimate the prevalence of specific mental health problems. Forty studies with a total of 19,480 participants were included in the analysis. The pooled prevalence of anxiety in the pandemic group was significantly higher than that in the control group. The depression and stress prevalence in the pandemic group was higher than that in the control group, yet did not reach statistical significance. A subgroup analysis revealed region differences with developed countries exhibiting higher rates of anxiety and depression in the pandemic group, but the result was the opposite in the control group. Physiological factors, psychological factors and social factors correlated with infertile patients' mental health were identified. The COVID-19 pandemic had a significant negative impact on infertile patients' mental health, emphasizing the importance of ways to mitigate the risks during the pandemic.
PubMed: 38894564
DOI: 10.1002/pchj.782 -
Diagnostics (Basel, Switzerland) Jun 2024Bitemark analysis involves the examination of both patterned injuries and contextual circumstances, combining morphological and positional data. Considering the... (Review)
Review
UNLABELLED
Bitemark analysis involves the examination of both patterned injuries and contextual circumstances, combining morphological and positional data. Considering the uniqueness of human dentition, bitemarks caused by teeth on skin or impressions on flexible surfaces could assist in human identification.
AIMS
to investigate the available literature systematically and evaluate the scientific evidence published over the past decade concerning the potential application of bitemark analysis in forensic identification.
METHODS
Two researchers meticulously searched electronic databases from January 2012 to December 2023, including Scopus, PubMed, Web of Science, and the Cochrane Library. Adhering to the PRISMA statement guidelines, this review employed appropriate medical subject headings (MeSHs) and free-text synonyms. Strict inclusion and exclusion criteria were applied during article retrieval.
RESULTS
The findings yielded controversial outcomes. Approximately two-thirds of the articles concluded that bitemark analysis is useful in forensic identification, while the remaining articles did not report statistically significant outcomes and cautioned against relying solely on bitemark analysis for identification.
CONCLUSIONS
The authors assert that bitemark analysis can be a reliable and complementary method for forensic identification, contingent upon the establishment and adoption of a universally accepted global protocol for data collection, processing, and interpretation. Undoubtedly, recent years have witnessed a notable increase in research focused on bitemark identification, driven by the goal of achieving quantitative, objective, reproducible, and accurate results.
PubMed: 38893706
DOI: 10.3390/diagnostics14111180 -
Nutrients May 2024Self-reported measures of height and weight are often used in large epidemiological studies. However, concerns remain regarding the validity and reliability of these... (Review)
Review
Validity of Measured vs. Self-Reported Weight and Height and Practical Considerations for Enhancing Reliability in Clinical and Epidemiological Studies: A Systematic Review.
Self-reported measures of height and weight are often used in large epidemiological studies. However, concerns remain regarding the validity and reliability of these self-reported measures. The aim of this systematic review was to summarise and evaluate the comparative validity of measured and self-reported weight and height data and to recommend strategies to improve the reliability of self-reported-data collection across studies. This systematic review adopted the PRISMA guidelines. Four online sources, including PubMed, Medline, Google Scholar, and CINAHL, were utilised. A total of 17,800 articles were screened, and 10 studies were eligible to be included in the SLR based on the defined inclusion and exclusion criteria. The findings from the studies revealed good agreement between measured and self-reported weight and height based on intra-class correlation coefficient and Bland-Altman plots. Overall, measured weight and height had higher validity and reliability (ICC > 0.9; LOA < 1 SD). However, due to biases such as social pressure and self-esteem issues, women underreported their weight, while men overreported their height. In essence, self-reported measures remain valuable indicators to supplement the restricted direct anthropometric data, particularly in large-scale surveys. However, it is essential to address potential sources of bias.
Topics: Humans; Reproducibility of Results; Self Report; Body Weight; Body Height; Female; Male; Epidemiologic Studies; Adult
PubMed: 38892637
DOI: 10.3390/nu16111704 -
Animals : An Open Access Journal From... May 2024Simulation models are used in various areas of agriculture to better understand the system and assist in decision making. In the beef production sector, a variety of... (Review)
Review
Simulation models are used in various areas of agriculture to better understand the system and assist in decision making. In the beef production sector, a variety of simulation research focusing on various dimensions of the system is available. However, an overview of the available research is lacking. Therefore, a systematic review was conducted to provide an overview of simulation studies of beef production and create an understanding of the simulation approaches used. Scopus, Web of Science, and ProQuest Central research databases were used to search the relevant articles, with the last search conducted in June 2023. Studies that developed or used simulation strategies and used beef cattle as a primary focus of the study were included. The 105 studies included in this review were examined thoroughly to record the authors, year of publication, country of study, type of study, focus area of the study, simulated scenarios, validation methods, and software programs used. There has been growing research interest in simulating beef production systems worldwide, with most studies conducted in North America and Europe. Among these studies, the majority (84.76%, = 89) are biophysical or bioeconomic study types and use deterministic approaches ( = 42). Additionally, most studies have a whole-farm scope (38.09%, = 40) and focus on productivity (51.43%, = 54). Since only less than half of the studies mentioned the validation techniques and software programs used, there is a need to improve the availability of this information to ensure that the models are adopted effectively in decision making.
PubMed: 38891679
DOI: 10.3390/ani14111632 -
Nicotine & Tobacco Research : Official... Jun 2024An increasing number of countries are adopting the tobacco endgame goal. High levels of public support can accelerate momentum towards implementing tobacco endgame...
INTRODUCTIONS
An increasing number of countries are adopting the tobacco endgame goal. High levels of public support can accelerate momentum towards implementing tobacco endgame policies. We aimed to conduct a systematic review of public support for tobacco endgame policies and to examine the geographical distribution of studies, support among key populations (adolescents and young adults, people who smoke), and the association between survey design and support.
METHODS
We searched Embase, PubMed, Scopus, Web of Science, and Google Scholar for studies published from 2013 onwards. Google was used to search the grey literature. The reference lists of included articles were hand-searched. Studies were included if they reported the proportions of people supporting one or more endgame policies. Risk of bias was assessed using the JBI checklist for prevalence studies.
RESULTS
Forty-seven articles were included. Aotearoa/New Zealand and the United States were the countries with the most studies (n=11, respectively). Three-level meta-analyses showed the highest support for mandating a very low nicotine content in tobacco products (76%, 95% CI 61-87%). Meta-regressions were performed to assess the associations of population subgroup and survey design with support levels. The level of support was lower among people who smoke compared to the general population (β range: -1.59 to -0.51). Support for some policies was lower when neutral or don't know response options were included.
CONCLUSIONS
Public support for most tobacco endgame policies was high.
IMPLICATIONS
Assessing public support can assist with progressing tobacco endgame policies. Policies that are widely supported by the public may be more politically feasible to implement. Qualitative studies and trial studies can further inform communication and implementation strategies for tobacco endgame policies.
PubMed: 38890771
DOI: 10.1093/ntr/ntae149 -
European Journal of Obstetrics,... Jun 2024To determine if introducing the Mediterranean diet in pregnancy reduces the incidence of gestational diabetes. (Review)
Review
Introduction of the Mediterranean diet in pregnancy and the incidence of gestational diabetes mellitus: A systematic review of randomised controlled trials and meta-analysis.
OBJECTIVES
To determine if introducing the Mediterranean diet in pregnancy reduces the incidence of gestational diabetes.
STUDY DESIGN
Systematic review and meta-analysis of randomised controlled trials (RCTs). A literature search was conducted using the following databases: MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and CINAHL with no language or date restrictions. Studies were deemed eligible if the population was pregnant women, the intervention was the Mediterranean diet, and the outcome was gestational diabetes. Quality assessment was carried out using the Cochrane risk of bias tool. A random effects model using Revman software was used to pool results, generating a summary risk ratio with 95 % confidence intervals (95 %CI).
RESULTS AND CONCLUSIONS
The search identified three eligible studies. Across the trials, 2348 women were included. Two of the three trials defined the intervention as the Mediterranean diet supplemented with extra virgin olive oil (EVOO) and pistachios, with the control group being Mediterranean diet alone. Meta-analysis of these trials found a significant reduction in the incidence of gestational diabetes in the intervention group compared to the control group (risk ratio=0.71, 95% confidence interval=(0.57, 0.88)). In addition, this was consistent with the results of the remaining eligible trial which defined the intervention as Mediterranean diet and the control as a standard UK diet (risk ratio = 0.71, 95% confidence interval = (0.55, 0.90)). At present evidence is scarce regarding whether adopting a Mediterranean diet reduces the risk of gestational diabetes. A large multi-centre randomised controlled trial is needed to definitively determine the impact of the Mediterranean diet in pregnancy on the incidence of gestational diabetes.
PubMed: 38889571
DOI: 10.1016/j.ejogrb.2024.05.024 -
Sports Medicine (Auckland, N.Z.) Jun 2024Despite widespread use of intensity zones to quantify external load variables in basketball research, the consistency in identifying zones and accompanying intensity...
BACKGROUND
Despite widespread use of intensity zones to quantify external load variables in basketball research, the consistency in identifying zones and accompanying intensity thresholds using predominant monitoring approaches in training and games remains unclear.
OBJECTIVES
The purpose of this work was to examine the external load intensity zones and thresholds adopted across basketball studies using video-based time-motion analysis (TMA), microsensors, and local positioning systems (LPS).
METHODS
PubMed, MEDLINE, and SPORTDiscus databases were searched from inception until 31 January 2023 for studies using intensity zones to quantify external load during basketball training sessions or games. Studies were excluded if they examined players participating in recreational or wheelchair basketball, were reviews or meta-analyses, or utilized monitoring approaches other than video-based TMA, microsensors, or LPS.
RESULTS
Following screening, 86 studies were included. Video-based TMA studies consistently classified jogging, running, sprinting, and jumping as intensity zones, but demonstrated considerable variation in classifying low-intensity (standing and walking) and basketball-specific activities. Microsensor studies mostly utilized a single, and rather consistent, threshold to identify only high-intensity activities (> 3.5 m·s for accelerations, decelerations, and changes-in-direction or > 40 cm for jumps), not separately quantifying lower intensity zones. Similarly, LPS studies predominantly quantified only high-intensity activities in a relatively consistent manner for speed (> 18.0 m·s) and acceleration/deceleration zones (> 2.0 m·s); however, the thresholds adopted for various intensity zones differed greatly to those used in TMA and microsensor research.
CONCLUSIONS
Notable inconsistencies were mostly evident for low-intensity activities, basketball-specific activities, and between the different monitoring approaches. Accordingly, we recommend further research to inform the development of consensus guidelines outlining suitable approaches when setting external load intensity zones and accompanying thresholds in research and practice.
PubMed: 38888854
DOI: 10.1007/s40279-024-02058-5 -
Shock (Augusta, Ga.) Jun 2024While non-norepinephrine vasopressors are increasingly used as a rescue therapy in cases of norepinephrine-refractory shock, data on their efficacy are limited. This...
BACKGROUND
While non-norepinephrine vasopressors are increasingly used as a rescue therapy in cases of norepinephrine-refractory shock, data on their efficacy are limited. This systematic review and meta-analysis aims to synthesize existing literature on the efficacy of Angiotensin II (ATII) in distributive shock.
METHODS
We pre-registered our meta-analysis with PROSPERO (CRD42023456136). We searched PubMed, Scopus, and gray literature for studies presenting outcomes on ATII use in distributive shock. The primary outcome of the meta-analysis was all-cause mortality. We used a random effects model to calculate pooled risk ratio (RR) and 95% confidence intervals (CI).
RESULTS
By incorporating data from 1555 patients included in 10 studies, we found that however all-cause mortality was similar among patients receiving ATII and controls (RR 1.02, 95% CI 0.89 to 1.16, p = 0.81), the reduction in norepinephrine or norepinephrine-equivalent dose at 3 h after treatment initiation was greater among patients receiving ATII (MD -0.06, 95% CI -0.11 to -0.02, p = 0.008), while there were no higher rates of adverse events reported among ATII patients.
CONCLUSIONS
While ATII did not reduce mortality among distributive shock patients, it allowed for significant adjunctive vasopressor reduction at 3 h without an increase in reported adverse events, deeming it a viable alternative for the increasingly adopted multimodal vasopressor for minimizing catecholamine exposure and its adverse events.
PubMed: 38888542
DOI: 10.1097/SHK.0000000000002384 -
Journal of Diabetes Science and... Jun 2024Digital twin is a new concept that is rapidly gaining recognition especially in the medical field. Indeed, being a virtual representation of real-world entities and... (Review)
Review
Digital twin is a new concept that is rapidly gaining recognition especially in the medical field. Indeed, being a virtual representation of real-world entities and processes, a digital twin can be used to accurately represent the patients' disease, clarify the treatment target, and realize personalized and precise therapies. However, despite being a revolutionary concept, the diffusion of digital twins in type 1 diabetes (T1D) is still limited. In this systematic review, we analyzed structure, operating conditions, and characteristics of digital twins being developed for T1D. Our search covered published documents until March 2024: 220 publications were identified, 37 of which were duplicated entries; in addition, 173 publications were removed after inspection of titles, abstracts, and keywords; and finally, 11 publications were fully reviewed, of which 8 were deemed eligible for inclusion. We found that all eight methodologies are not comprehensive multi-scale virtual replicas of the individual with T1D, but they all focus on describing glucose-insulin metabolism, aiming to simulate glucose concentration resultant from therapeutic interventions. In this review, we will compare and analyze different factors characterizing these digital twins, such as operating principles (mathematical model, twinning procedure, validation and assessment) and the key aspects for practical adoption (inclusion of physical activity, data required for twinning, open-source availability). We will conclude the paper listing which, in our opinion, are the current limitations and future directives of digital twins in T1D, hoping that this article can be helpful to researchers working on diabetes technologies to further develop the use of such an important instrument.
PubMed: 38887022
DOI: 10.1177/19322968241262112 -
Survey of Ophthalmology Jun 2024Diabetic retinopathy (DR) poses a significant challenge in diabetes management, with its progression often asymptomatic until advanced stages. This underscores the... (Review)
Review
Diabetic retinopathy (DR) poses a significant challenge in diabetes management, with its progression often asymptomatic until advanced stages. This underscores the urgent need for cost-effective and reliable screening methods. Consequently, the integration of Artificial Intelligence tools presents a promising avenue to address this need effectively. We provide an overview of the current state of the art results and techniques in DR screening using AI, while also identifying gaps in research for future exploration. By synthesizing existing database and pinpointing areas requiring further investigation, this paper seeks to guide the direction of future research in the field of automatic diabetic retinopathy screening. There has been a continuous rise in the number of articles detailing Deep Learning methods designed for the automatic screening of Diabetic Retinopathy especially by the year 2021. Researchers utilized various databases, with a primary focus on the IDRiD dataset. This dataset comprises color fundus images captured at an ophthalmological clinic situated in India. It comprises 516 images that depict various stages of diabetic retinopathy and diabetic macular edema. Each of the chosen papers concentrates on various DR signs. Nevertheless, a significant portion of the authors primarily focused on detecting exudates, which remains insufficient to assess the overall presence of this disease. Various AI methods have been employed to identify DR signs. Among the chosen papers, 4.7% utilized detection methods, 46.5% employed classification techniques, 41.9% relied on segmentation, and 7% opted for a combination of classification and segmentation. Metrics calculated from 80% of the articles employing preprocessing techniques demonstrated the significant benefits of this approach in enhancing results quality. In addition, multiple Deep Learning techniques, starting by classification, detection then segmentation. Researchers used mostly YOLO for detection, ViT for classification and U-Net for segmentation. Another perspective on the evolving landscape of AI models for diabetic retinopathy screening lies in the increasing adoption of Convolutional Neural Networks for classification tasks and U-Net architectures for segmentation purposes;However, there is a growing realization within the research community that these techniques, while powerful individually, can be even more effective when integrated. This integration holds promise for not only diagnosing DR but also accurately classifying its different stages, thereby enabling more tailored treatment strategies. Despite this potential, the development of AI models for DR screening is fraught with challenges. Chief among these is the difficulty in obtaining high-quality, labeled data necessary for training models to perform effectively. This scarcity of data poses significant barriers to achieving robust performance and can hinder progress in developing accurate screening systems. Moreover, managing the complexity of these models, particularly deep neural networks, presents its own set of challenges. Additionally, interpreting the outputs of these models and ensuring their reliability in real-world clinical settings remain ongoing concerns. Furthermore, the iterative process of training and adapting these models to specific datasets can be time-consuming and resource-intensive. These challenges underscore the multifaceted nature of developing effective AI models for DR screening. Addressing these obstacles requires concerted efforts from researchers, clinicians, and technologists to innovate new approaches and overcome existing limitations. By doing so, a full potential of AI may transform DR screening and improve patient outcomes.
PubMed: 38885761
DOI: 10.1016/j.survophthal.2024.05.008