Intergenerational transmission is a crucial aspect of human development. Although prior studies have demonstrated the continuity of psychopathology and maladaptive upbringing environments between parents and offspring, the underlying neurobiological mechanisms remain unclear. We have begun a novel neuroimaging research project, the Transmit Radiant Individuality to Offspring (TRIO) study, which focuses on biological parent-offspring trios. The participants of the TRIO study were Japanese parent-offspring trios consisting of offspring aged 10–40 and their biological mother and father. Structural and functional brain images of all participants were acquired using magnetic resonance imaging (MRI). Saliva samples were collected for DNA analysis. We obtained psychosocial information, such as intelligence, mental health problems, personality traits, and experiences during the developmental period from each parent and offspring in the same manner as much as possible. By April 2023, we completed data acquisition from 174 trios consisting of fathers, mothers, and offspring. The target sample size was 310 trios. However, we plan to conduct genetic and epigenetic analyses, and the sample size is expected to be expanded further while developing this project into a multi-site collaborative study in the future. The TRIO study can challenge the elucidation of the mechanism of intergenerational transmission effects on human development by collecting diverse information from parents and offspring at the molecular, neural, and behavioral levels. Our study provides interdisciplinary insights into how individuals’ lives are involved in the construction of the lives of their descendants in the subsequent generation. Several large cohort studies, such as the Adolescent Brain Cognitive DevelopmentIntergenerational transmission refers to offspring inheriting behaviors and characteristics from parents through genetic and non-genetic pathways . NumerouThe experience of psychopathology or social interactions, as well as the effect of the experience could be inherited by offspring. Intergenerational transmission of trauma effect  means that individuals’ adverse experiences, particularly in their childhood, affect their offspring . AdverseThere are three notable concepts in the exploration of mechanisms of intergenerational transmission: intergenerational neuroimaging, epigenetic inheritance, and genetic nurture. First, intergenerational neuroimaging—a research field that uses brain images as endophenotypes to estimate the mechanisms of intergenerational transmission—is beginning to progress . SeveralOne of the reasons why the mechanisms of intergenerational transmission are unclear, despite the accumulation of previous studies as described above, is the lack of data on fathers. Although some studies examined brain similarities among all patterns of parent–offspring gender combinations  , 40, mosIn the field of neuroimaging, data from both parents and offspring are rarely available. Although birth cohorts and three-generational cohorts have contributed to a wealth of genomic information and physiological indices for parents and offspring, in many cases, brain images are obtained only from parents or offspring. For example, the Norwegian Mother and Child Cohort Study (MoBa)Consequently, for elucidating the mechanisms of intergenerational transmission, it is necessary to collect behavioral indices, brain images, environmental factors, and genetic/epigenetic information on at least two generations of parents and offspring. Hence, we started a novel neuroimaging research project—the Transmit Radiant Individuality to Offspring (TRIO) study—which is subject to biological parent-offspring trios comprising fathers, mothers, and offspring. This study aimed to elucidate the bio-psycho-social mechanism of intergenerational transmission using brain MRI as an endophenotype. We anticipate that the understanding of the role of parental genotype and/or life experiences in the development of personality and risk of mental illness in the subsequent generation would be deepened in this study. The findings of this study will contribute to the growth of effective interventions for individuals’ adaptive development. We hypothesized that: (1) maternal and paternal intergenerational transmissions are established by different mechanisms, and (2) the interaction between the paternal and maternal effects involves intergenerational transmission. The procedure for testing these hypotheses is presented using the effect of the parental experience of childhood maltreatment on offspring development as an example. Hypothesis (1) would be examined by comparing the result of the analyses using father-offspring dyads and mother-offspring dyads. For example, the paternal experience of childhood maltreatment and such experience of mothers may associate with neural and/or behavioral phenotype of offspring in a different way. Hypothesis (2) would be tested by analyzing whether the effect of the maternal experience of childhood maltreatment on offspring’s brain structure is moderated by the paternal childhood experience of being reared, and vice versa.In this paper, we describe the acquiring data content, procedures of data collection, current progress, and future directions of our project.2.2.1.The participants of the TRIO study were parent-offspring trios consisting of three members: a male or female offspring aged 10 (a 5th-grade elementary school student in Japan) to 40 and their biological mother and father. Most previous studies aiming to elucidate the mechanisms of intergenerational transmission have focused on offspring from infancy to adolescence. Therefore, it is unclear whether the effects of intergenerational transmission are observed at any age, or whether they are limited to certain ages . To the 2.2.Each participant received a gift voucher worth 5,000 JPY. The parents were also given a report on brain health of themselves based on hippocampal volume using BrainSuite, developed by CogSmart, Inc. Offspring were given a printed copy of the T1-weighted brain image and a score report from the Wechsler Adult Intelligence Scale Fourth Edition (WAIS-IV)  or Wechs2.3.Advertisements for recruiting participants were published in a local magazine on town information. Additionally, flyers and posters were displayed at universities, high schools, vocational schools, government offices, public facilities, and stores in Sendai. All advertisements included information on the eligibility criteria, an overview of the inspections to be conducted, and the time required along with dates and rewards. A QR code on the advertisement could be scanned to access a website with details of the study. This website allowed applicants to access an application form created using Google Forms, in which applicants and their family members input their name, age, gender, role in the family , phone number, e-mail address, preferred date of participation, and confirmation that they do not meet the exclusion criteria. After reviewing the applicants’ input data, the staff coordinated the date and time of participation by e-mail or phone. If the number of applicants exceeded the targeted number of trios, a waiting list was created. Applicants in this list were requested to participate as soon as additional survey dates were added.2.4.2.4.1.Data were collected at the Institute of Development, Aging, and Cancer of Tohoku University. On the day of the visit, the participants underwent brain MRI, global intelligence test, face morphological scanning, and 2D palm scanning. On the same day, they provided saliva samples and answered the questionnaires. Parents brought the mother and child health handbook and the score reports of their offspring’s physical fitness test. Several questionnaires were administered in this study. To reduce the psychological burden on participants as much as possible, most questionnaires were taken home so that they could be self-administered at the participants’ own pace. In addition, a time schedule for participation was documented on the website to help participants keep a track of the progression of tests in the study. Participants were asked to check the time schedule in advance. Questionnaires taken home were requested to be submitted by post within approximately 2 weeks of the date of participation.The duration of all experiments on the day of participation is approximately 4 h, and the time required to complete the questionnaire test to be taken home is approximately 1 h.2.4.2.Participants were asked to provide the following information through originally formatted questionnaires: educational background , persona2.4.3.Height and weight were measured and recorded before the MRI.All participants answered the Japanese version of the Flinders handedness questionnaire (FLANDERS) , 72 to eParticipants were asked about their current illness under treatment, medications they are currently taking, medical history, history of COVID-19 infection, and history of psychiatric diseases and developmental disorders in relatives, using the original survey form. For participants aged under 15, questions other than those regarding the history of COVID-19 infection were answered by the mother. Female participants also answered questions on the menstrual cycle and the last menses start date.Pubertal status was also assessed for underage participants using the Pubertal Development Scale , 74, a sOnly parents of children aged under 18 were asked to bring their offspring’s score reports from physical fitness tests conducted recently at school. The Physical Fitness Test is an official physical ability test mandated by the Japan Ministry of Education, Culture, Sports, Science, and Technology to investigate the nation’s physical strength and athletic ability, and is administered annually at schools. This test score captures a child’s flexibility and agility. The score reports were scanned by the research staff.2.4.4.To measure global intelligence, participants aged 16 or older completed the WAIS-IV, and those aged 15 or younger completed the WISC-IV. Ten core subtests were conducted to calculate the full-scale intelligence quotient along with four factors . The tests were conducted in a quiet, non-stimulating room, one-on-one with staff familiar with the procedure and participants. The time required to complete the test ranged approximately 60–90 min.2.4.5.Prior to scanning, participants were asked to confirm that they had no metal in their bodies, tattoos, permanent makeup, claustrophobia, nyctophobia, pregnancy, and were not wearing thermal undershirts and contact lenses. Participants’ signatures were obtained for this confirmation.Brain images were acquired using a 3-Tesla dStream Achieva scanner  with a 20-channel headneck coil. Participants wore earplugs and headphones to protect their ears from MRI noise. An emergency buzzer was given to the participants to alert the research staff if any problems occurred during the imaging. The total scan time was approximately 24 min.b-value was set to 1,000s/mm2 for 30 volumes. Sixth, two non-diffusion weighted (b=0) images were acquired with reversed-phase encoding directions (AP and PA) for distortion correction  were obtained using a magnetization-prepared rapid gradient-echo (MPRAGE) sequence. Second, sagittal T2-weighted images (T2WIs) were acquired using a spin-echo sequence. Third, resting-state functional MRI (rsfMRI) was performed using gradient-echo echo-planar imaging (EPI). Each run contained 120 image volumes preceded by 7 dummy volumes, with each volume comprising 45 slices. Participants were asked to stay awake, not think about anything as much as possible, and gaze at the center of the black fixation point on the gantry. Fourth, field maps were acquired for distortion correction using rsfMRI. As the usefulness of each type of distortion correction remains controversial, we obtained two types of field maps: images with a double-echo spoiled gradient echo sequence (GRE-field map) and a pair of spin-echo EPI images with opposite anterior–posterior (AP) and posterior–anterior (PA) phase encoding direction (SE-oppPE-field map) . Fifth, rrection . Details2.4.6.® Discover  following the manufacturer’s protocol. The collected samples were stored at room temperature until DNA extraction was performed. Genomic DNA was extracted from the samples using an Oragene® purifier. Thereafter, the extracted DNA samples were measured for concentration using a Nanodrop 2000  and then stored in a freezer at −30°C. In future research, we plan to use microarrays for single-nucleotide polymorphism (SNP) typing and epigenomic analyses.Saliva samples were collected for genetic/epigenetic analysis using Oragene2.4.7.We used psychological questionnaires to collect information about the participants’ behavioral phenotypes, including mental health problems, well-being, personality traits, and socioemotional competencies. We selected scales for which reliability and validity were confirmed and are widely used internationally.Our first priority was to assess behavioral phenotypes using the same scale for both parents and offspring. However, because it is difficult for children aged under 15 to answer the same questionnaires as adults, we adopted appropriately developed scales for children whenever possible. Moreover, self-administered questionnaires were used unless only parent-administered questionnaires for children were available.The response burden for questionnaires varies by respondents’ age. Children are more likely to be burdened . Therefo2.4.7.1.Participants’ depressive symptoms, subjective happiness, eudaimonic well-being, internalizing/externalizing symptoms, serious trauma, re-experiencing symptoms, loneliness, and fear of COVID-19 were assessed. The names of the questionnaires, number of items, and responses are summarized in The Satisfaction with Life Scale (SWLS) , 140 is The Strengths and Difficulties Questionnaire (SDQ)  was usedThe Posttraumatic Diagnostic Scale (PDS)  was used2.4.7.2.Participants were assessed for the following: extraversion, agreeableness, conscientiousness, neuroticism, openness, temperaments of behavioral inhibition/activation, state and trait anxiety, schizotypal personality, psychotic-like experience, inattention and impulsivity, autistic traits, borderline personality, negative feelings in peer relationships (discomfort in close relationships and abandonment anxiety), emotion regulation strategies, empathic traits, Machiavellianism, narcissism, and psychopathy. The names of the questionnaires, number of items, and choices are summarized in The Ten-Item Personality Inventory (TIPI) , 92, 147The Schizotypal Personality Questionnaire Brief (SPQ-Brief) , 104 wasThe personality questionnaire in the Structured Clinical Interview for DSM-5 personality disorders (SCID-II)  was usedExperience in Close Relationships Relationship-Structure (ECR-RS)  was used2.4.7.3.The definition of environment is broad and includes all “non-genetic” factors . Accordi2.4.7.3.1.We assessed family functioning, family relationships, perceived parenting style, ACEs, satisfaction with marital relationships, and marital conflicts. The names of the questionnaires, number of items, and responses are summarized in Family Adaptation and Cohesion Scales (FACES-III) , 126 werThe Inventory for Character of Intra-Inter Generation in Kinship (ICHIGEKI)  was usedThe Parental Bonding Instrument (PBI) , 129 wasACEs were assessed using several questionnaires. First, the Childhood Trauma Questionnaire (CTQ) , 134 wasQuality Marriage Index (QMI) , 136 wasThe Multidimensional Stress Questionnaire for Couples (MSQ) , 138 wasUsing retrospective questions on their experiences up to adolescence, participants were also asked about the frequency of conversations during mealtimes at home, family members who are home when they return from school, the relationship between the spatial composition of their house and their private room, and their experience of pet ownership and emotional unity with their pets.2.4.7.3.2.We asked participants the following information about their experiences till high school: friendships, relationships with teachers, meeting others who influenced their lives, bullying victimization/perpetration/bystanders, reading, sports, playing a musical instrument, leadership positions, changing schools, living abroad, excitement about nature and the arts, and enthusiasm for a hobby. They were also asked about the elementary, junior high, and high schools that they attended, including the approximate number of students, whether they took entrance exams, and whether they were coeducational schools. Furthermore, we asked about whether they played outdoors or indoors from preschool to elementary school, when they began using cell phones or smartphones, and whether their parents restricted them from using TV, games, or phones. As there are few reliable and validated internationally used scales for the above information, the questions used in the Japanese literature or the survey forms of Japanese public institutions were used as references.As Japan is prone to natural disasters, we asked respondents about the locations of homes they had lived in by age 20 to capture their experiences with natural disasters. Respondents were asked to indicate in which prefecture and municipality and the ages at which they lived in each home. This question was answered by the mother for offspring aged 15 or younger.2.4.7.3.3.To examine the impact of the pre- and postnatal environments on offspring development and intergenerational transmission, we asked mothers about the following information: experience of fertility treatment and artificial abortion prior to conceiving the offspring participating in this study; presence or absence of any perinatal problems such as breech baby; neonatal asphyxia; obstetric complications; perinatal depression; anticipation of childbirth; duration and method of breastfeeding; social support during and after pregnancy; and the frequency of alcohol, caffeine, raw food, and junk food consumption from when the pregnancy was discovered to delivery and from delivery to weaning. Additionally, both mothers and fathers were asked about their smoking habits before, during, and after pregnancy; whether there were smokers around them during their childhood; and whether their working patterns changed due to marriage and childbirth.This study was conducted in Sendai City, Miyagi Prefecture, Japan, where many residents experienced the Great East Japan Earthquake. In particular, participants born between 2008 and 2013 may have experienced an earthquake either prenatally or as infants. Therefore, we asked their parents about the damage caused by the Great East Japan Earthquake. Parents were asked about the prefecture in which they lived at the time of the earthquake, the extent of damage to their household, and whether their relatives were affected.Furthermore, perinatal information was also collected from the Mother and Child Health Handbook, which is issued for women in Japan at the time pregnancy is confirmed and is used during pregnancy and postpartum health checkups. This handbook includes information on the mother’s weight, fundal height, blood pressure, fetal growth at each prenatal checkup, method of delivery, birth weight, infant growth, and developmental milestones up to age 6. We scanned all pages after obtaining the mother’s permission.2.4.7.4.Participants’ lifestyle habits were also evaluated using questionnaires. For participants aged 16 and older (both parents and offspring), physical activity was assessed using the Global Physical Activity Questionnaire (GPAQ) , 159; eaFor offspring aged under 15, physical activity was assessed using the WHO Health Behavior in School-aged Children (HBSC) , 171. Ea2.4.7.5.To examine the effects of intergenerational transmission on phenotypes other than brain structure and function or behavioral traits assessed by questionnaires, we obtained the following measurements: face morphology, ratio of second to fourth digit length (2D/4D ratio), and characteristics of the drawn tree. The brain and face have been reported to share several genetic loci , and fac2.4.7.5.1.Digital facial stereophotogrammetry was used to capture 3D facial surfaces; 3D stereophotogrammetric imaging is a well-established approach for generating dense 3D points that represent the surface geometry of a face using multiple 2D images with overlapping fields of view . Facial 2.4.7.5.2.Brother PRIVIO DCP-J962N  was used to acquire 2D palm scanned images. According to a prior study’s protocol , both ha2.4.7.5.3.A sheet of A4 paper and a 4B pencil were provided to each participant, and they were instructed to “draw a tree on the drawing paper. The purpose is not to see how good or bad you are at drawing, so please draw freely, with little care.” When the participants finished drawing, they were asked to freely describe on the back of the paper what kind of tree they drew and how they felt after drawing it.2.5.Brain images will be preprocessed using the analysis software widely used in this field like FreeSurferr = 0.30, α = 0.05, two-tailed, power = 0.95). Second, we also plan to investigate the association between parental ACEs and offspring’s brain structure or function to present additional knowledge of intergenerational transmission of trauma effect. Linear regression analysis is one of the options for examining these associations ]. Third, we will examine whether the effect of parenting style on offspring’s brain development differs depending on whether there is intergenerational transmission of parenting style. Specifically, we will examine the differences in offspring’s  brain development depending on whether parents’  parenting style toward their offspring is similar to the parenting style they received from their own caregivers  during their childhood. The parenting style of G2 and G1 are assessed using PBI or CRPBI as mentioned above. According to our preliminary analysis performed using different data from the present study, whether positive parenting style (assessed by the care factor in PBI) transmitted between G1 and G2 was related to G3’s cortical thickness with a moderate effect size . In line with this, the sample size required to obtain a moderate effect size by ANCOVA with four groups was calculated to be 279 . From the above, approximately 310 trios would be required to meet the largest samples for the currently planned analysis, assuming that 10% of the samples are excluded due to incomplete or missing data. In addition to the above, other analyses deemed necessary will be performed. For each analysis, if there are missing values, the data from that participant will be excluded from the analysis.One of the major goals of our study is to understand the putative mechanisms of intergenerational transmission, using brain images as endophenotype. To achieve this objective, we consider the following analyses. First, we plan to determine which characteristics in which brain areas are similar between father and offspring and/or mother and offspring, and whether the similarities can be recognized as the neural basis for the intergenerational transmission of behavioral phenotypes. This theme includes a replication of previous studies of intergenerational neuroimaging. In previous studies, parent–offspring brain similarity has often been described using the correlation of the characteristics of brain region of interest (ROI) between parents and offspring , 39, 40.ciations , 198–201In the future, the sample size can be increased further to enable analysis using genetic information. In genetic studies, a family-based design has the advantage that it can eliminate the problems of population stratification . The parAlthough this study is a venturesome project with a different budget and staffing compared to existing large cohorts, we intend to eventually develop this project into a multi-site collaborative study and lead the neuroimaging research of parent–offspring trios.3.3.1.By April 2023, we completed data acquisition from 174 trios. The mean ages of the offspring, mothers, and fathers were 17.55 ± 6.76, 50.18 ± 6.21, and 51.58 ± 7.03, respectively. The numbers of male and female offspring were 85 and 89, respectively. Most participants completed all the surveys, but brain images were partially omitted for some due to unexpected claustrophobia or technical errors of the MRI scanner.3.2.Our study has several strengths. First, we were able to accumulate data on fathers, whereas most previous studies have focused only on mothers and offspring . We deviThis study has some limitations. First, because children aged under 10 were not included in this study, it was not possible to determine when the effects of intergenerational transmission on traits become apparent. This limitation should be addressed through future studies targeting younger children and their parents. Second, as our study used a cross-sectional design, we could not investigate the longitudinal changes in intergenerational transmission effects on the offspring’s lifespan development. Ideally, intergenerational transmission should be investigated when two generations are of the same age, because unapparent traits in youth may appear in middle adulthood . However3.3.The TRIO study is a novel neuroimaging research project that investigated the association between intergenerational transmission and personality development. Our study provides interdisciplinary insights into how individuals’ lives are involved in the construction of the lives of their descendants in the subsequent generation.This study was conducted in accordance with the principles of the Declaration of Helsinki . ApprovaYT supervised the project. IM, RY, and YT designed the study. IM and RY collected the data. IM wrote the manuscript, which was reviewed by RY and YT. All authors contributed to the article and approved the submitted version.This work was funded by a Grant-in-Aid for Young Scientists (Grant no. 22K13809) and Grant-in-Aid for Transformative Research Areas (A) (Grant no. 22H05209) from the Ministry of Education, Culture, Sports, and Technology (MEXT) and the Japan Society for the Promotion of Science (JSPS) to IM. This work was also funded by the Program for the Creation of Interdisciplinary Research from the Frontier Research Institute for Interdisciplinary Sciences, Tohoku University to IM. This work was also supported by JST SPRING (Grant No. JPMJSP2114) awarded to RY. This work was also supported by a Grant-in-Aid for Scientific Research (B) (Grant no. 19H04211) from the MEXT to YT. This work was supported by JSPS KAKENHI Grant Number JP22H04926 and Grant-in-Aid for Transformative Research Areas — Platforms for Advanced Technologies and Research Resources “Advanced Bioimaging Support” for the curation and analysis of neuroimaging data.We used BrainSuite, developed by CogSmart, Inc., as an incentive for the participants. YT was the chief scientific officer of CogSmart, Inc. and has obtained approval from the Conflict of Interest (COI) Management Committee of Tohoku University for his involvement in this study. This study was also supported by the joint research fund of CogSmart, Inc., but these funds have not been used to pay for using BrainSuite.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


To measure the stigma of healthcare providers toward people suffering from mental illness, the Opening Minds Stigma Scale for Health Care Providers (OMS-HC) is a commonly applied instrument. However, this scale has not been thoroughly validated in many European countries, its psychometric properties are still unknown and data on practicing psychiatrists is lacking. Therefore, this multicenter study aimed to assess the psychometric characteristics of the 15-item OMS-HC in trainees and specialists in adult and child psychiatry in 32 countries across Europe.via Email to European adult and child psychiatrists. Parallel analysis was used to estimate the number of OMS-HC dimensions. Separate for each country, the bifactor ESEM, a bifactor exploratory structural equation modeling approach, was applied to investigate the factor structure of the scale. Cross-cultural validation was done based on multigroup confirmatory factor analyses and reliability measures.The OMS-HC was conducted as an anonymous online survey and sent 2/df = 9.760, RMSEA = 0.045 (0.042–0.049), CFI = 0.981; TLI = 0.960, WRMR = 1.200). The average proportion of variance explained by the general factor was high (ECV = 0.682). This suggests that the aspects of ‘attitude,’ ‘disclosure and help-seeking,’ and ‘social distance’ could be treated as a single dimension of stigma. Among the specific factors, the ‘disclosure and help-seeking’ factor explained a considerable unique proportion of variance in the observed scores.A total of 4,245 practitioners were included, 2,826 (67%) female, 1,389 (33%) male. The majority (66%) of participants were specialists, with 78% working in adult psychiatry. When country data were analyzed separately, the bifactor model  showed the best model fit (for the total sample χThis international study has led to cross-cultural analysis of the OMS-HC on a large sample of practicing psychiatrists. The bifactor structure displayed the best overall model fit in each country. Rather than using the subscales, we recommend the total score to quantify the overall stigmatizing attitudes. Further studies are required to strengthen our findings in countries where the proposed model was found to be weak. Unfortunately, stigma affects people with mental illness not only in their daily lives but also when they seek medical care, including mental care, which results in poor physical and mental health of the person , 2. The Developed to evaluate anti-stigma programs for healthcare workers, the Opening Minds Stigma Scale for Health Care Providers (OMS-HC) is one of the most widely used self-report measurements of stigmatizing attitudes worldwide. The authors of the scale created a pool of 50 items that they collected from existing scales and developed new items by consulting people who work in anti-stigma programs for healthcare providers. The pool was reviewed by professionals and people with lived experience, which was followed by cognitive interviewing of healthcare workers, and seven focus groups were held to improve the wording of the scale. Finally, the changes resulted in a reduction to 20 items . The facn = 49, Canada n = 79), and solely one study examined the factor structure of the scale on a psychiatrist sample (Hungary n = 211). Therefore, it is unknown whether the extent of findings could be generalized to the psychiatrist population, which is critical because investigating their stigmatizing attitudes toward people with mental health problems is considered an important and understudied area of research. Based on the current literature, the results are mixed; in some cases, their attitudes have been found to be more favorable, whereas in others they expressed more stigma than that of other healthcare providers  were used to approach a broader population. Investigators distributed the questionnaire by contacting the national psychiatric associations, universities, local hospitals, and health centers and through professional networks, including social media platforms and professional groups’ email lists.2.2.n = 4,245) consisted of trainees and specialists in general adult and child psychiatry from 32 European countries. Not working in psychiatric care and medical student status were the exclusion criteria.The combined total sample , disclosure and help-seeking, with four items , and social distance is measured by five items . Subjects indicate on a 5-point Likert scale the extent to which they identify themselves with the given statements from ‘strongly disagree’ to ‘strongly agree.’ The total scores range from 15 to 75, and the subscales from 6 to 30, 4 to 20, and 5 to 25, respectively. Higher scores reflect a more stigmatizing attitude. Before this study, the psychometric properties of the OMS-HC were investigated in Italy, Hungary, Germany, and Switzerland (German part) in the participating countries, and it was found to be a reliable and valid measurement of the stigmatizing attitudes  was also gathered from them. The 15-item long OMS-HC is a self-report scale, which is conceptualized as an attitude measure comprising three components . Specifically, attitude is measured by six items . All confirmatory factor analyses and ESEM models used diagonally weighted least squares (WLSMV) to find the optimum model for each country. It accounts for standard errors and non-normality in chi-square test statistics for ordinal data. We tested unidimensional, three-factor, and bifactor model fit. We used the following indices to evaluate model fit: chi-square / degree of freedom (χ2/df) (<5.0), root mean square error of approximation , comparative fit index (CFI) and Tucker-Lewis Index (TLI), CFI and TLI  (The percentage (%) and sample size (n) are used to express the demographic data. First, using parallel analysis to compare the progressive eigenvalues from the given data matrix to those of a simulated data matrix created using random data of the same size, we determined the number of elements to be extracted . The Kaioor fit) . Model-boor fit) . Reise aoor fit) . When PUoor fit) . Spearmaoor fit)  and MPluoor fit)  statisti3.n = 4,245 professionals in psychiatry completed the survey. The majority of the participants were female , while young professionals between the ages of 24 and 35 years  were overrepresented in the sample. Most of them worked in adult psychiatry  and inpatient facilities . Working facility of the participants and their years of experience in psychiatry are attached as a A total of p < 0.0001) and the KMO measure of sampling adequacy (0.841) we performed an EFA on the pooled sample to see the factor matrix, the network of the items, and to create an overview of the structure of the scale. To determine the number of factors for extraction, parallel analysis was performed, and the eigenvalues were considered, which identified 3 or 4 different dimensions. As all item loadings were lower on the fourth factor than the other three, therefore, we continued with the three-factor structure that accounted for a sufficient amount of variance .First, based on the suitable Bartlett’s Test of Sphericity , CFI ranged from 0.870 to 1.000 , TLI ranged from 0.732 to 1,084 , and the WRMR ranged from 0.304 to 0.651 . However, the model failed to run in Albania and Swiss French and Swiss Italian languages due to the negative covariance matrices (theta). The absolute index, RMSEA, was moderate in Bulgaria, Cyprus, Greece, Italy, Latvia and Turkey, and it was associated with slightly lower than acceptable relative fit indices, CFI and/or TLI in Azerbaijan, Latvia, Montenegro, and Slovakia. The fit indices for the total sample were within the recommended ranges. Alternatively, the unidimensional and the correlated three-factor models were considered. The M = 0.12, SD = 0.02), the CFI ranged from 0.579 to 0.902 , and TLI ranged from 0.509 to 0.886 . The three-factor model showed a little better fit, with RMSEA ranging from 0.054 to 0.124 , CFI and TLI ranging from 0.726 to 0.966  and 0.669 to 0.959 , respectively. All fit indices indicate that the bifactor ESEM model provides us with the best model fit.A series of confirmatory factor analyses were performed to find the best model fit for the OMS-HC in each participating country. The bifactor ESEM model was found to be superior to the alternative models by showing an acceptable fitting level. This model , which is considered a very high completion rate - especially among psychiatrists ; however, we had no information about the exact number of French or Italian-speaking psychiatrists. Participants could choose the language they were most comfortable with in countries with multiple official languages. Both the Swiss French and Swiss Italian samples were quite small , which exposed them to this type of error. The small sample size was probably the reason behind the Montenegrin and Azeri lower fit indices as well. Consequently, in these countries, thorough exploratory factor analysis is recommended to understand the psychometric properties of the scale. Its investigation on larger and more diverse samples  could also be beneficial, particularly in those countries where the model-fit was poor.Because of the inherent limitations of the simple three-factor structure, we decided to investigate the model further. Our research has demonstrated that the bifactor model provided us with the best approximation of the factor structure of the OMS-HC with a good to acceptable fit in nearly all countries. It seemed superior to alternative models, including the three-factor correlated trait model based on the fit indices. In fact, our model does not contradict the three-factor model; furthermore, it investigates it for a higher-order solution. The three-dimensions are identified as three specific factors, supplemented by a general factor in a hierarchical structure resulting in better model fit. Although it showed a good fit in most countries, the final model failed to run in Albania and on the Swiss-French and Swiss Italian samples due to negative covariance matrices. Despite having a model that fits perfectly by definition, this error message is not unexpected with small sample sizes, in which simulation methods could cause more sampling errors . Moreoveiatrists . In SwitI am more comfortable helping a person who has a physical illness than I am helping a person who has a mental illness.’) found to be weak in Singaporean medical and nursing students  and 13  loaded on different factors than expected in German and Swiss healthcare workers on psychiatric wards  was removed from the scale in a Hungarian study on psychiatrists due to poor loading across all three factors ; they were probably easier to approach with online questionnaires. Thirdly, this study examined a sample consisting solely of psychiatrists. It is uncertain if the findings apply to other healthcare workers, not only for mental healthcare providers. Lastly, most of the data were collected during the COVID-19 period. We have no data on how their attitudes would be without the challenges brought on by the pandemic. It is not yet known whether the pandemic has or not a significant effect on their stigmatizing attitudes; however, the overwhelming workload and the related stress might bring them more challenges than before .5.Our results agree with the three-dimensional structure of the OMS-HC proposed by the scale authors after the modification and abbreviation of the scale to 15 items. In addition, however, we upgraded the investigation of the scale from a first-order factor solution to a bifactor ESEM model, which seemed more appropriate and provided us with better fit indices in a large sample of psychiatrists from several European countries. The model fit was good or acceptable in most nations; however, based on the model-based reliability results, the general factor and the disclosure and help-seeking specific factor explained substantial variance. Consequently, we recommend using the total score of the OMS-HC and probably the disclosure and help-seeking subscale scores rather than other subscales when we would like to measure the stigma in the participating countries.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The study that involved human participants was conducted in accordance with the principles of the Declaration of Helsinki. Participants provided electronic informed consent prior to completing the online survey (by clicking `yes’). The Hungarian core study was approved by the Regional and Institutional Committee of Science and Research Ethics of the Semmelweis University, Budapest, Hungary (SE-RKEB: 189/2019), followed by site approvals in participating countries. The ethics revision process for online survey projects was required in the following countries based on the written statement of the local investigators, and the study was approved by the following ethics committees. Albania: Albanian Medical Ethics Committee (Nr. 303/13). Austria: Ethics Committee of the Medical University of Graz (32-619 ex 19/20). Belarus: Ethical Committee of the Belarusian Psychiatric Association (1/2020), Belgium: Ethics committee of the University Hospital Brussels (2021/011), Croatia: Ethics Committee of the University Hospital Center Zagreb , Cyprus: Cyprus National Bioethics Committee (2020.01.172.), Czech Republic: The Ethical Committee of the Third Medical Faculty, Charles University (11/2020), Estonia: Tartu University Ethics Committee, Tartu, Estonia (322/T-9), Germany: Ethikkommission der Technischen Universität München (679/20S), Greece: University of Ioannina (2638/16-7-2020), Ireland: Royal College of Physicians of Ireland Research Ethics Committee (RCPI RECSAF 134), Malta: Health Ethics Committee (HEC13/2020) Netherlands: Medical Ethics Review Committee of Erasmus Medical Center (MEC-2021-0151), Portugal: Ethical Committee of the Faculty of Medicine, University of Coimbra (CE-136/2020), Serbia: Ethics Committee of the Institute of Mental Health, Belgrade (1060/2094/1), Turkey: Research Ethics Committee of the Ministry of Health Ankara City Hospital (E1/928/2020), and United Kingdom: Pennine Care NHS Foundation.DŐ was the principal investigator of the study and the major contributor to the study design, writing of the manuscript, and data analysis. PS and TM as members of the Hungarian core team, conceived and planned the study and helped in writing the manuscript. SRó being a professional statistician, verified the analytical methods, suggested and developed codes for the BESEM, helped to interpret the results, improved the manuscript with his expert comments, and also supervised the project with ZG. LB, OK, SMö, MW, MA, SB, KB, CC, EC, ED, GG, SG, II, KG, SK, KK, IK, JM, SMa, AM, NN, AP, ATP, EP-C, SRa, PR, JS-V, RS, FS, HK, AH, GA, MV, HY, and NG were essential contributors, planned the local data collection in each of their countries, translated the questionnaire to their local language(s), provided active assistance in the data collection and contributed to the manuscript writing. All authors have read and approved the final version of the manuscript and given their consent for publication.DŐ was awarded the National Youth Talent Award in 2020 and 2021  and the Prominence Award of the Kerpel-Fronius Talent Support Program of Semmelweis University in 2021 (EFOP-3.6.3-VEKOP-16-2017-00009), which covered the expenses of the 1-year account of the online survey platform and the dissemination of the study results at international congresses. SRó was supported by the Károli Gáspár University of the Reformed Church (Grant No. 20754B800).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


ObjectiveTo estimate the multiple direct/indirect effects of social, environmental, and economic factors on COVID-19 vaccination rates (series complete) in the 3109 continental counties in the United States (U.S.).Study design The dependent variable was the COVID-19 vaccination rates in the U.S. . Independent variables were collected from reliable secondary data sources, including the Census and CDC. Independent variables measured at two different time frames were utilized to predict vaccination rates. The number of vaccination sites in a given county was calculated using the geographic information system (GIS) packages as of April 9, 2022. The Internet Archive (Way Back Machine) was used to look up data for historical dates.Methods A chain of temporally-constrained least absolute shrinkage and selection operator (LASSO) regressions was used to identify direct and indirect effects on vaccination rates. The first regression identified direct predictors of vaccination rates. Next, the direct predictors were set as response variables in subsequent regressions and regressed on variables that occurred before them. These regressions identified additional indirect predictors of vaccination. Finally, both direct and indirect variables were included in a network model.Results Fifteen variables directly predicted vaccination rates and explained 43% of the variation in vaccination rates in April 2022. In addition, 11 variables indirectly affected vaccination rates, and their influence on vaccination was mediated by direct factors. For example, children in poverty rate mediated the effect of (a) median household income, (b) children in single-parent homes, and (c) income inequality. For another example, median household income mediated the effect of (a) the percentage of residents under the age of 18, (b) the percentage of residents who are Asian, (c) home ownership, and (d) traffic volume in the prior year. Our findings describe not only the direct but also the indirect effect of variables.Conclusions A diverse set of demographics, social determinants, public health status, and provider characteristics predicted vaccination rates. Vaccination rates change systematically and are affected by the demographic composition and social determinants of illness within the county. One of the merits of our study is that it shows how the direct predictors of vaccination rates could be mediators of the effects of other variables. Vaccination rates, or the percentage of a population that has received recommended vaccinations, are an important indicator of the overall health of a community. The COVID-19 pandemic has emphasized the importance of vaccination in preventing the spread of disease and protecting public health. However, vaccination rates can vary significantly within and between different populations and are often influenced by a range of social determinants [In this context, a growing body of research has examined the impact of social and environmental factors on disparities in COVID-19 vaccination rates . StudiesIn contrast to a traditional approach to mediation analysis, our study uses a data-driven method to identify multiple mediators based on the timing of variable measurement. We investigated what and how these factors, directly and indirectly, affected the vaccination rates in the U.S. Specifically, we relied on an extensive set of demographics, social, economic, and neighborhood factors to examine the multiple mediation effects of social and environmental factors on vaccination rates using a longitudinal observational data.https://archive.org/web/) [We collected data on the demographic, socioeconomic, and environmental characteristics of 3109 counties located in the continental United States that may potentially explain the variation in vaccination rates across the U.S. counties. The primary data for the percentage of the fully vaccinated population (series complete) in the counties were collected from the COVID-19 data tracker coordinated by the CDC. The number of vaccination providers per county was calculated based on the address information of provider sites using geocoding and spatial join functions. The addresses for providers at a past time frame were obtained using the Wayback Machine (rg/web/) . Social,This study examined the direct/indirect impact of the following 34 variables on vaccination rates: number of vaccination Providers, percentage (%) of highschool completion, % of some college education, % of unemployment, income inequality, % of children in poverty, % of children in single parent households, % of life expectancy, median household income, % of residential segregation i.e., non-White vs. White, % of traffic volume, % of home ownership, total population, % below 18 years of age, % over 65, % of non-Hispanic Black, % of American Indian or Alaska Native, % of Asian, % not proficient in English, poverty rate, % of disabilty population, % of female population, % of Hispanic population, % of Native Hawaiian Other Pacific Islander population, % of non-Hispanic Black population, % of non-Hispanic White population, % of Rural population, driving alone to work, injury death, long commute driving, premature age-adjusted mortality, residential segregation Black/White, severe housing cost burden. Table The four demographics that affected vaccination rates are the percentage of residents with American Indians or Alaska Natives, Asian residents, senior residents (≥65 years), and residents with those below/who are 18 years of age. However, the percentage of Black or African American residents was not a direct predictor of vaccination rates.The eight social determinants of illness-affected vaccination rates were the percentage of residents with high school completion, % of residents with some college, % of unemployed residents, % of children in single-parent households, median household income, % of residents living with non-White vs. White segregation, % of residents not proficient in English, % of children in poverty. As expected, the average life expectancy of residents and % of residents with disability affected vaccination rates. Notably, the higher number of vaccination providers in the county was associated with higher vaccination rates.The following variables were included in the regression analysis as independent variables but were not statistically significant in any of the regressions: % of the female population, % of Hispanic residents, % of Native Hawaiian or other Pacific Islander residents, % of non-Hispanic Black/African American residents, % of non-Hispanic White residents, % of residents living in rural areas, % of residents driving alone to work, number of injury/death, length of commute driving, premature age-adjusted mortality, residential segregation Black versus White, and severe housing cost burden.Table Each column indicates one regression. The response variables listed in the first row were regressed on the independent variables listed in the first column. The explained variations in each regression are listed in the second row. Non-zero robust regression coefficients are listed in rows three to the end of the table. Blank cells indicate variables that are not predictive of the response variable.Figure A large percentage of the variation in the vaccination rate (43%) was explained by the factors in our model. One previous mediation study reports that 76% of the variation in vaccination rate was explained . The preThe findings of our study are in general agreement with the findings reported in the literature. For example, our study found that the number of vaccination providers had a moderate effect (regression coefficient of 0.10) on the county’s vaccination rate . PreviouA complex set of demographics were direct predictors of vaccination rates. Asian residents had higher vaccination rates than residents who were not Asian . SimilarWe found that African-Americans had similar vaccination rates as non-African Americans. There is support for our findings in the literature; in particular, previous studies have also shown that COVID-19 vaccine hesitancy decreased more rapidly among African Americans, and over time their vaccination rates exceeded the White population [The age of the population (percentage of seniors and percentage under 18 years) also affected vaccination rates. Previous studies also confirm these relationships ,21. AccoA number of social determinants of illness affected vaccination rates. Previous studies confirm that vaccination rates are lower among vulnerable groups although exceptions exist . Our stuOne of the merits of our study is that it shows how the direct predictors of vaccination rates could be mediators of the effects of other variables. For example, children in poverty rate mediated the effect of (a) median household income, (b) children in single-parent homes, and (c) income inequality. For another example, median household income mediated the effect of (a) percentage of residents under the age of 18, (b) percentage of Asian residents, (c) home ownership, and (d) traffic volume in the prior year. Our findings not only describe the direct but also the indirect effect of variables.In terms of practical implementations, our findings could provide counties with expected rates of vaccination given their characteristics. Counties can then plan programs that can change these characteristics or help them perform better than expected. The study findings would help balance the community level of health disparities; practitioners and policymakers may design and implement data-driven intervention strategies for specific residents.There are some limitations to our study. This study is based on only two waves based i.e., 2020 and 2022. The two-year timeframe may be insufficient for observing the neighborhood or social determinant effects. Future research should be encouraged to use longer-term periods. Our study was limited in variable measurement. Results could be different if other measures are used. In our study, we did not include the effect of political factors on vaccination rates. It is possible that the inclusion of these factors could change study findings.The one certainty with the COVID-19 pandemic is that the parameters of this epidemic change over time. Some factors may have a bigger effect on the vaccination rate than others at a certain period of time. In other words, even the same factors may have a different impact on vaccination rates at different times. To reduce the potential biases in selecting variables, our study examined changes in variables over time. It was able to demonstrate how certain factors play a mediating role and how other factors indirectly affect vaccination rates. A diverse set of demographics, social determinants, and medical and provider characteristics predicted vaccination rates. In epidemiology and the social science field, mediation analysis relied on a solid theoretical foundation called confirmatory factor analysis to design the model. However, one single theory could not explain the complexity of health disparities. We demonstrated how to apply data-driven approaches to better understand the complexity by identifying direct/indirect factors on vaccination disparities across the U.S. counties. The fact that our model explained a large portion of the variation in vaccination rates suggests that we have included the appropriate variables in the model.


Manta was associated with a lower rate of bleeding complications , predominantly minor complications with fewer closure failures , less use of covered stents , and with no difference in the need for vascular surgery compared to the Prostar group . On the other hand, Manta was associated with a higher rate of femoral stenosis  without clinical significance . The Manta and Prostar devices are equivalent in terms of vascular complications. The Manta, compared to the Prostar, is associated with fewer bleeding complications.TAVI requires a large-bore arteriotomy. Closure is usually performed by the suture system. Some studies report a vascular complication rate of up to 21%. MANTA is a recently developed percutaneous closure system dedicated to large caliber vessels based on an anchoring system. Early studies report a lower rate of vascular complications with MANTA devices. This single-center retrospective study included all patients who underwent femoral TAVI at the Brest University Hospital from 20 November 2019 to 31 March 2021. The primary endpoint is the rate of vascular complications (major and minor) pre and post-TAVI procedure. In total, 264 patients were included. There were no significant differences in vascular complications (major and minor) between the two groups (13.6% in the MANTA group versus 21.2% in the PROSTAR group;  Aortic stenosis is the most common valve disease requiring intervention in Europe and the United States, and it increases in frequency in elderly populations, reaching 3–9% of the population after 80 years of age . Severe Most often, TAVI is implanted via the femoral access. The procedure requires the use of a large-caliber approach. Two approaches are classically accepted for the closure of the femoral artery: surgical closure and percutaneous closure with a suture system. However, surgical closure is associated with a longer procedure time, greater blood loss, increased patient discomfort, more sustained anesthesia, increased risk of complications, particularly infectious ones, and slowed down patient ambulation .® Abbot Vascular, Santa Clara, CA, USA; PROSTAR® Abbot Vascular Abbot Park, IL, USA). With these systems, the rate of minor vascular complications varies from 0 to 18.2%, while major complications vary from 0 to 12.2% [In the percutaneous approach, the closure of the access requires dedicated closure systems. The majority of these closure devices are suture systems . The first studies performed with this device showed a low rate of major vascular complications between 0 and 20.9% . Patients who underwent a hybrid procedure with vascular surgery during TAVI, patients under protective safeguard, not affiliated with social security, or unable to give consent were excluded from the present study. Patients included from 20 November 2019 to September 2020 received suture system (Prostar) closure, whereas patients included from September 2020 to March 2021 received Manta closure. Our center decided to change the closing device in September 2020 for several reasons: the Manta device seemed better suited to calcified lesions, no preclosing time was required, and the device was easy to use.Diameter of the common femoral artery (mm);Degree of calcification ;Location of calcifications ;Tortuosity ;Bifurcation height;Size of the femoral shaft .Femoral analyses were performed by preprocedural CT scan. The characteristics of the main access were studied:Location.Size of the shaft.The secondary approach was also studied:All patients were placed on acetylsalicylic acid the day before the TAVI procedure if they were not already receiving long-term treatment. If the patient was already on acetylsalicylic acid, the treatment was continued. If the patient was previously on Clopidogrel or Ticagrelor, the treatment was stopped 5 days before. If the patient was on Direct Oral Anticoagulant (DOA), treatment was stopped 2 days before, while if the patient was on Anti Vitamin K (AVK), treatment was stopped 5 days before with an INR target of 1.5 or less for the procedure. During the procedure, we used unfractionated heparin (UFH) weight-adjusted, and the reversal of anticoagulation was obtained by protamine at the end of the procedure.The TAVI procedure was performed in the presence of two interventional cardiologists, a radiology manipulator, and two nurses under local. During the use of the Prostar system (from November 2019 to September 2020), for organizational reasons, a cardiothoracic and vascular surgeon was present for the closure of the approach. Arterial puncture of the common femoral artery was performed under fluoroscopy after locating the puncture site by pigtail angiographic opacification of the primary approach (via the secondary approach).The Prostar system  between the Manta and Prostar devices at 30 days. Major and minor vascular complications were defined according to the Valve Academic Research Consortium-2 (VARC-2) classification.In-hospital mortality.Type of vascular complications: false aneurysm, arteriovenous fistula arterial dissection, arterial stenosis (>50% reduction in diameter), homolateral lower limb ischemia, bleeding.Bleeding complications: Total, major , and minor .Immediate failure of closure of the approach by the device—defined by the need for additional endovascular or surgical closure per procedure.Length of stay.Study of the risk factors for complications of the approach.The secondary endpoints were the comparison between the two groups:Consent was obtained for each patient. The protocol was carried out in accordance with the Declaration of Helsinki and the rules of good clinical practice.t test was performed. For the comparison of two qualitative variables, a Chi-2 test was performed. For factors favoring vascular complications, a univariate and then multivariate analysis was performed. For the multivariate analysis, only the values for which p was less than 0.05 in the univariate analysis were selected. Redundant data were not selected for the multivariate analysis. A total number of variables not exceeding 10% of the total number of events could be used. Multivariate analysis was performed by multivariate logistic regression. Statistical tests were performed with IBM SPSS Statistics version 25.0, Chicago, IL, USA. A difference is considered significant if a two-sided p was <0.05.Continuous variables are presented with their mean and standard deviation. Categorical variables are presented in absolute (n) and relative (%) values. To compare two quantitative variables, a Student’s Over the period 20 November 2019 to 31 March 2021, 266 patients were eligible. Two patients were excluded because of scheduled vascular surgery concomitant with TAVI. A total of 264 patients were therefore included: 132 patients in the Manta group and 132 patients in the Prostar group .Characteristics of study population are summarized in p = 0.038). The mean ratio of sheath to femoral artery size was 0.83 and was comparable between the two groups (p = 0.098). Calcifications were most often minimal to moderate (75% of cases) and were most often located posteriorly and medially . The femoral bifurcation was high in 9.1% of cases, and iliofemoral tortuosity was most often minimal to moderate (84.1%). The radial approach was the preferred secondary approach (62.9% of cases). The main valve used was the Sapiens 3 valve in 60.7% of cases.The characteristics of femoral access are summarized in p = 0.067).There were no differences in terms of vascular complications of the main approach between the two devices, either for total, major, or minor vascular complications . Howeverp = 0.013), but without difference in the rate of homolateral lower limb ischemia (p = 0.156). There were no differences between the two devices for false aneurysms (p = 0.555), arteriovenous fistulas (AVF) (p = 0.652), and arterial dissections (p = 0.473).When we look precisely at vascular complications , there wp = 0.01). Access bleeding (p = 0.002), mainly due to minor bleeding (p = 0.002), while there was no significant difference between the groups for major bleeding (p = 0.561).Failure to close was more frequent with the Prostar device , while the use of vascular surgery was not significantly different between the two groups (p = 0.652). There was a non-significant trend (p = 0.053) towards a higher transfusion rate in the Prostar group (6% versus 1.5% in the Manta group). There was no difference in the amount of contrast medium used between the two groups (p = 0.537).The use of a covered stent was more frequent with the Prostar system .Intra-hospital mortality related to the TAVI procedure remains relatively rare in this registry, with 0.4% of cases in total. Only one death was observed and was related to a complication of the approach to a false aneurysm with multiple surgical revisions in the Prostar group. There were no significant differences in in-hospital mortality between the two groups (p = 0.001).Post-implantation length of stay was significantly shorter in the Manta group , the ratio sheath to the size of the common femoral artery , Euroscore Logistic , creatinine level , and common femoral artery diameter .Factors associated with a risk of developing a vascular complication are presented in Age, gender, BMI, HBP, degree of calcification, location of calcification, high bifurcation, PAD, platelet count, GFR, and previous anticoagulant therapy were not found to be significantly associated with the risk of developing a vascular complication.p = 0.019), sheath/femoral ratio , and Logistic Euroscore .In multivariate analysis, variables associated with the risk of developing a vascular complication were diabetes .However, creatinine level was not found to be significant in multivariate analysis , although this did not reach significance. (2) A higher rate of bleeding complications was observed with the Prostar device compared to the Manta, predominantly in minor bleeding. (3) A higher rate of femoral stenosis after closure was found in the Manta group, although there were no clinically significant differences between the two groups in terms of homolateral lower limb ischemia.In this single-center retrospective study including 264 consecutive patients (132 patients per group), the main findings were: (1) No significant difference in terms of vascular complications (major and minor) between the two closure devices was found, while there was a trend towards a lower rate of minor vascular complications in the Manta group . However, this difference was not found in the most recent meta-analysis in terms of major and minor bleeding complications [There is a higher rate of bleeding complications in the Prostar group compared to the Manta system in our study, mainly driven by minor bleeding. These results are in line with the Moriyama study , where tications ,30,31,32p = 0.01), which is in line with the literature with suture-based devices [We can speculate that this higher rate of bleeding complications in our study was related to higher immediate closure failure in the Prostar group (13.6% versus 4.5% in the Manta group,  devices ,30,31,32Ratio-sheath to the femoral, which is consistent with the current literature ,34.Euroscore logistic is representative of the patient’s severity.Finally, diabetes mellitus, which was also a risk factor for false aneurysm in the site of femoral access The three independent risk factors of vascular complication were found in our study:In our study, age, gender, BMI, HBP, renal insufficiency, and the degree and location of calcification were not identified as risk factors for vascular complication, which is in line with other studies ,12,24. HThis study has several limitations; firstly, it is a single-center retrospective cohort study, with the usual limitations. The length of stay was shorter in our study in the Manta group, but we cannot exclude a time effect. No comparison with the PROGLIDE device was performed in the present study since it is not routinely used in our center.Therefore, further prospective multicenter randomized controlled studies comparing the Manta with the suture system for closure of the main approach during a TAVI procedure are needed to confirm these results. The use of vascular ultrasound to guide the puncture could be an additional aid to decrease the overall rate of vascular complications, as suggested in some studies ,37.There were no differences in the rates of vascular complications between the Manta and Prostar devices. However, there was a higher rate of bleeding complications in the Prostar group as compared to the manta group, mainly driven by the rate of minor bleeding in the Prostar group and requiring more frequent use of a covered stent. In contrast, the Manta is associated with more non-clinically significant vascular femoral stenosis.


Chlamydia psittaci is the pathogen of psittacosis and infects a wide range of birds and even humans. Human infection occurs most commonly in those with a history of contact with birds or poultry. We describe a case of psittacosis in a human immunodeficiency virus infected patient in Zhejiang Province for the first time. C. psittaci infection was confirmed by nested polymerase chain reaction (PCR) and Real-Time PCR. Phylogenetic analysis revealed that the sequences from the patient’s samples clustered with genotype A in the same branch. Our study highlights the possibility of diagnosing psittacosis in patients with a chronic disease such as HIV-infected patients, and should increase awareness and surveillance of psittacosis in China. Although psittacosis is not a common disease, it has been reported worldwide, including in China, the USA, Europe, and Australia   . Metagenon (PCR) , especiaon (PCR) . In receC. psittaci in an HIV patient in Zhejiang Province.Here, we present a successfully cured case of psittacosis infection in an HIV patient diagnosed by mNGS, nested PCR and Real-Time PCR. To the best of our knowledge, this is the first case of infection caused by 2The patient was a 65-year-old man who had suffered from HIV for 13 years. He was admitted to the hospital on April 6, 2022 with chills and fever after visiting the cemetery on Chinese Tomb Sweeping Day. The highest recorded body temperature was 39.9°C and was accompanied by cough and expectoration, white sticky sputum, no abdominal distension or abdominal pain, pain in the joints and muscles of the body, no loss of smell or taste, no headache or dizziness, no frequent urination or urgency, no diarrhea and no chest pain or hemoptysis.Chest computed tomography (CT) suggested that lung infection foci should be considered on both sides. Therefore, “community acquired pneumonia and AIDS” were diagnosed, and the patient was admitted to the second hospital of Haishu District, Ningbo City, China .4+ T cell counts were greater than 300/UL in a recent routine blood examination. After admission, butravil was prescribed as a replacement to continue antiviral treatment.After the patient was initially infected with HIV 13 years ago, he was regularly treated with lamivudine, zidovudine and nevirapine. Viral load was frequently below the detection limit. However, recently, CDC. psittaci. No sequence reads corresponded to other pathogenic microbes. C. psittaci pneumonia was confirmed by nested PCR and qPCR at the Zhejiang Provincial Center for Disease Control and Prevention (CDC).Blood tests and cultures of anaerobic bacteria were negative, and sputum acid fast bacillus smears were negative. Mycoplasma pneumoniae antibody IgM was positive. Piperacillin/tazobactam, imipenem/cilastatin sodium (from 4 to 11) and voriconazole were given as treatment, but his condition did not improve, so the patient came to Hangzhou Xixi hospital for further diagnosis and treatment. Bronchoalveolar lavage fluid (BALF) was used to perform mNGS, and the results revealed 1082 sequence reads corresponding to C. psittaci 16S rRNA locus tag and nested PCR targeting the major outer membrane protein (ompA) gene as described previous  for the publication of this case report.WY and XY have contributed to original draft preparation of this manuscript. JS, ZY, YY, and JK have contributed to the investigation. LW, ZW, and GS review and edited the manuscript. HY and YS contributed to the project administration. All authors contributed to the article and approved the submitted version.


The accuracy significantly outperformed the conventional frequency-based method with an AUC of 0.740 . Conclusions: Our findings indicate the potential of machine learning and transthoracic impedance measurements for estimating pleural effusion. By incorporating noninvasive and easily obtainable clinical and laboratory findings, this approach offers an effective means of assessing intrathoracic conditions.Background: Transthoracic impedance values have not been widely used to measure extravascular pulmonary water content due to accuracy and complexity concerns. Our aim was to develop a foundational model for a novel system aiming to non-invasively estimate the intrathoracic condition of heart failure patients. Methods: We employed multi-frequency bioelectrical impedance analysis to simultaneously measure multiple frequencies, collecting electrical, physical, and hematological data from 63 hospitalized heart failure patients and 82 healthy volunteers. Measurements were taken upon admission and after treatment, and longitudinal analysis was conducted. Results: Using a light gradient boosting machine, and a decision tree-based machine learning method, we developed an intrathoracic estimation model based on electrical measurements and clinical findings. Out of the 286 features collected, the model utilized 16 features. Notably, the developed model demonstrated high accuracy in discriminating patients with pleural effusion, achieving an area under the receiver characteristic curves (AUC) of 0.905 (95% CI: 0.870–0.940,  There are 64 million heart failure (HF) patients worldwide, including 1.2 million in Japan, and the number of people affected by it is increasing staggeringly ,4. The mPulmonary edema in patients with HF is a representative acute sign of congestion, and is defined as the increase in extravascular water volume . The watOn the other hand, a recent report suggested that a remote monitoring system that collects physical findings can be used to predict clinical worsening and the need for early therapeutic intervention . In addiThe purpose of our study was to longitudinally collect various test results from the time of hospitalization to the discharge of the target patients and build a database. Furthermore, using this database, we aimed to develop a thoracic cavity estimation system that can be conveniently used by applying machine learning. Although we limited our discussion in this paper to the inference of the presence or absence of pleural effusion, we evaluated its predictive accuracy and aimed to build a technical foundation for the early detection of HF in the future.Between July 2021 and March 2022, patients diagnosed with HF or pneumonia and requiring hospital care were consecutively enrolled in this study. The control group consisted of healthy adult volunteers. The diagnosis was finalized by cardiologists based on congestive signs, symptoms, and laboratory findings. The patients with intra-thoracic treatment due to lung tumors, on a ventilator, or with electronic devices, such as cardiac pacemakers, were excluded. inf), the impedance at frequency 0 kHz (Z0), and the frequency at which the reactance was maximized  were measured. The phase angle (PhA) at each frequency and at Fc were also measured. PhA was calculated from the resistance (R) and capacitive reactance (Xc) using the following formula: arctangent (Xc/R) × 180°/π. These data were simultaneously accumulated from the MLT-550N, and the required time was about 4–5 min, including data entry for the subject and attachment of the electrode plate.Hospitalized subjects were evaluated at least twice, at admission and before discharge if symptoms improved. In addition to impedance measurement, imaging studies, including chest CT and X-ray and blood tests, were performed at the time of admission, and chest X-ray and blood tests were performed before discharge. These tests were repeated depending on the clinical course of the hospitalized patients. Physical findings included height, weight and width. Physiological findings included blood oxygen saturation, blood pressure, and pulse. In addition to blood counts, the following were measured: renal function, liver function, and biochemical data. Impedance values were measured via a body composition analyzer  using the multi-frequency BIA (MFBIA) method. The MLT-550N is a BIA device that is commonly used in Japan. This device provides information on body composition using whole-body bioimpedance spectroscopy at 140 electrical frequencies via electrodes . All BIAA total of 507 datasets were incorporated into the database, consisting of 63 patients with HF (including 7 patients with complications of pneumonia), and 82 healthy volunteers. These 507 datasets were included for database construction, with measurements taken from the bilateral axillae and from the right wrist and ankle for the same subject . Discrimfreq) was normalized as the square of each subject’s BDW divided by the impedance at the appropriate frequency (Zfreq), as in the following equation for impedance values:In data input to the machine learning model, missing value handling and feature generation were performed. For test items that are observed in the case of heart failure, we did not input the raw data. Instead, we used the binned features as the input values for machine learning. Weighting was performed based on the clinically obtained useful thresholds , and eacfreq performs a logarithmic transformation to make the distribution closer to a normal distribution. In addition, for subjects whose cumulative data existed, the percentage of weight change from the time of the previous diagnosis was also generated as a feature value  for variables with a non-normal distribution and as mean ± SD for those with a normal distribution. Measurement data were analyzed using the Mann–Whitney U test . Categorical data are expressed as n (%) and analyzed via the Chi-squared test. The DeLong test was used to compare the AUC between models. The tests were two-sided and https://pypi.org/project/lightgbm/2.2.0/ (accessed on 1 July 2023), version 2.2.0) was used as the machine learning model. SHAP (https://pypi.org/project/shap/0.41.0/ (accessed on 1 July 2023), version 0.41.0) was used to interpret the models. SHAP is calculated based on the constructed LightGBM model and an index to explain the machine learning model based on game theory [The data were processed using the packages numpy (version 1.14.3), pandas (version 0.23.0), and scikit-learn (version 0.19.1), which run on the Python (version 3.5.5) programming language. LightGBM  a data input system, (2) a cloud processing system, and (3) an information display system A. On the30, ZI0, and PhA50. The color of the plot helped determine whether a feature value had a positive or negative relationship with the outcome. 50 and Z0. 50, Z0, and our model. The AUC was 0.740 , 0.800 , and 0.905 , respectively. The AUC for Z0 was significantly larger than the conventional Z50 (p < 0.034), and our model had a significantly larger AUC than Z0 (p < 0.001). The AUC of our proposed model combining impedance with various features was significantly larger than the AUC of any model using impedance alone (p < 0.001).The accuracy of our model was compared using only the impedance values Zinf and Z0. However, after normalization, as described in Two of the sixty-three patients required readmission within the study period. In this study, we devised a non-invasive, easy-to-use system for estimating intrathoracic conditions. This system, which employs machine learning, not only supports accurate diagnosis but also allows for continuous data collection in the future. By incorporating readily obtainable test values into our estimations, rather than relying solely on existing impedance values, we were able to achieve greater accuracy.Bioelectrical impedance studies were reported from the 1950s to the 1980s, including by Beker et al. ,29,30. TPrevious studies have described an edema guard monitor, with which measurements can be obtained from outside the body . This deOne of the key points in this study was how to evaluate the measured impedance and resistance with respect to individual body size and gender differences. Okazaki et al. reported that gender and body size, but not age, effected impedance . TherefoNext, we discuss the selection of the frequencies and other electrical parameters used in our model. Multiple frequencies in MFBIA have been reported to provide a more accurate assessment of intracellular and extracellular fluids than single-frequency alternating current BIA ,43,44. SPhysical findings, such as tachycardia, abnormal blood pressure, weight gain, tachypnea, and blood tests, such as renal function, electrolytes, and complete blood, count are also important for diagnosis . In thisFinally, all of the electrical parameters are automatically obtained from the instrument. In addition, each of the other parameters has been turned into an algorithm that allows estimation regardless of the presence or absence of some measurement inputs. The algorithm has been developed based on actual clinical practice, assuming that use of the system and the amount of information available are different in private homes, nursing homes, clinics, and hospitals. Our results were close to those in Compared to traditional risk estimation methods, the strength of machine learning is its ability to detect complex nonlinear relationships and iteratively improve its models with more data, resulting in more accurate estimates and fewer false alarms ,50. ExamAs illustrated in c and PhA values of 0 kHz and 0 degrees, respectively. The reason for this should be investigated in the future. Fourth, our estimation system must be validated in subjects at various pre-diagnostic stages and in healthy subjects. As we move forward with new research, it will be necessary to conduct power analysis and tests of independence to ensure the reliability and generality of our model, thereby strengthening our claims. On the other hand, the fact that many older patients have pleural effusions when they are admitted to the hospital suggests that our system may be useful in clinical practice.This study had some limitations. First, this study was initiated based on our previous research in which we observed changes in impedance values during pleural effusion in pigs, and it aimed to evaluate the presence or absence of pleural effusion. HF is classified into pulmonary congestion, pulmonary edema, and the more advanced condition of pleural effusion. It is necessary for future research to aim at evaluations at earlier stages before the onset of pleural effusion. In this regard, few patients in the present study had only mild congestion. To make predictions about the early stages of heart failure or very mild heart failure, we need more patient data about pulmonary congestion and pulmonary edema. Second, we could not recruit age-matched healthy volunteers at the time of the study due to the impact of a pandemic caused by the SARS-CoV-2 virus, and the control data were collected from healthy people in a relatively younger age group who had a low risk of morbidity. In The system developed in this study has demonstrated the capability to estimate intrathoracic fluid retention with greater accuracy than conventional methods by using transthoracic impedance and other measurements, thereby suggesting its clinical utility. Our system allows for concurrent data collection during estimation. Ultimately, this could enable the development of a highly accurate intrathoracic estimation model based on impedance values using the large datasets we have collected. We have already developed a system to display the severity of pleural effusion; however, a larger sample size is essential for more accurate evaluations, presenting a challenge for future work. We aim to develop a reliable sensitivity algorithm for this approach.