Yet, there are no screening algorithms for this condition. We developed a risk prediction model to guide targeted screening for patients with AS. (2) Methods: We performed a cross-sectional analysis of all echocardiographic studies performed between 2013 and 2018 at a tertiary academic care center. We included reports of unique patients aged from 40 to 95 years. A logistic regression model was fitted for the risk of moderate and severe AS, with readily available demographics and comorbidity variables. Model performance was assessed by the C-index, and its calibration was judged by a calibration plot. (3) Results: Among the 38,788 reports yielded by inclusion criteria, there were 4200 (10.8%) patients with ≥moderate AS. The multivariable model demonstrated multiple variables to be associated with AS, including age, male gender, Caucasian race, Body Mass Index ≥ 30, and cardiovascular comorbidities and medications. C-statistics of the model was 0.77 and was well calibrated according to the calibration plot. An integer point system was developed to calculate the predicted risk of ≥moderate AS, which ranged from 0.0002 to 0.7711. The lower 20% of risk was approximately 0.15 (corresponds to a score of 252), while the upper 20% of risk was about 0.60 (corresponds to a score of 332 points). (4) Conclusions: We developed a risk prediction model to predict patients’ risk of having ≥moderate AS based on demographic and clinical variables from a large population cohort. This tool may guide targeted screening for patients with advanced AS in the general population.  Calcific aortic stenosis (AS) is the most common valvular heart disease in Western countries  and the AS can be readily diagnosed using Doppler echocardiography with accuracy, reasonable cost, and at no risk to the patient. Once reliably diagnosed, it can be treated effectively with interventions that improve survival and quality of life ,7. In thPrevious efforts have not been sufficient to reliably characterize AS risk factors and successfully use them to generate a risk score for general screening recommendations to identify patients with moderate or severe AS. In particular, this was due to the small size of the available cohorts and/or the lack of control groups. Towards this end, we leveraged a large echocardiography database to develop a prediction model to identify patients with AS based on readily available demographic and comorbidity information. This cross-sectional study was conducted at Yale-New Haven Hospital, a tertiary care center in the United States, serving the community of the greater New Haven area and a large fraction of the population of the state of Connecticut . Echocardiography data and electronic health records (EHR) were queried for all patients ≥ 18 years old who had at least one study during the calendar years 2013–2018. These criteria yielded 146,876 studies obtained on 48,524 unique patients. The Institutional Review Board at Yale University approved this study, and individual consent was waived.A series of exclusions led to the final analytic cohort of 38,788 patients, as shown in Patients with ≥ moderate AS were identified using the Doppler echocardiography parameters clinically used to define AS. The most severe value of the following parameters was considered : 2 and or dimensionless valve index (DVI) ≤ 0.5 and or maximum flow velocity (V-max) ≥ 3 m/s, and or mean pressure gradient (PG-mean) ≥ 20 mmHg.Aortic valve area (AVA) ≤ 1.5 cmCandidate variables included demographics , clinical characteristics , medications , and previous interventions including coronary artery bypass graft (CABG), percutaneous coronary intervention (PCI), defibrillator and/or pacemaker implantation. Demographics, BMI, history of smoking, and medications were directly abstracted from the EHR. Comorbidities and interventions were queried in the form of ICD-10 codes .Distribution of patient demographics, comorbidity, and medications between patients with ≥moderate AS and those with no AS were compared by Student’s t-test for continuous variables and by chi-squared test for categorical variables, respectively. Association between the risk of moderate/severe AS and patient demographics, comorbidity, and medications were evaluated using the multivariable logistic regression. The variables included in the regression model were chosen based on stepwise variable selection, optimizing the Akaike Information Criterion (AIC) value.We evaluated the model discrimination ability using the area under the receiver-operator characteristics curve (AUROC), which characterizes model discrimination and ranges between 0 and 1, with a higher value corresponding to better discrimination. AUROC is the proportion of the times patients with an event were accurately classified to have a higher probability of event within all possible pairs of patients with and without an event. Calibration was characterized using continuous calibration plot.p < 0.05 was considered statistically significant. All analyses were carried out using SAS 9.4 .To enhance clinical implementation of the models in assessing patients’ risk of having the disease and, accordingly, the need for echocardiographic testing, we further developed a simple integer scoring system based on the β coefficients for each predictor variable in the logistic regression models. A two-tailed p < 0.0001), more likely to be males, Caucasian race, with higher prevalence of hypertension, dyslipidemia, coronary artery disease (CAD), pulmonary hypertension, heart block (HB), atrial fibrillation (AF), cerebral infarction, peripheral vascular disease (PVD), chronic kidney disease (CKD), diabetes mellitus (DM), dementia, inability to walk, heart failure (HF), dilated cardiomyopathy, pacemaker, defibrillator, PCI, and CABG and were more likely to be on beta-blockers, CCBs, ACEIs, and diuretics , use of aspirin , use of CCBs , use of diuretics , CABG , CAD , dyslipidemia , pulmonary hypertension , cardiomyopathy , HB , AF , CVD , PVD , CKD , DM , chronic liver disease , history of obesity , pacemaker , and heart failure . The risk of having moderate or severe AS decreased with African American race (AA) , races other than Caucasian and AA  and history of dementia  .The models achieved good predictive discrimination with an AUC of 0.77  and wereThe current lack of clinical tools to facilitate targeted screening of the population for patients with increased risk of ≥moderate AS is concerning given the increasing burden of the disease and its association with poor outcomes when diagnosed late or left untreated. Furthermore, timely intervention in this subpopulation can lead to significantly improved quality of life and survival, and therefore, a reliable screening program for AS would have an impact on patient outcomes. This contrasts with other conditions such as abdominal aortic aneurysm and lung cancer, for which successful implementation of nationwide screening programs led to the mitigation of their consequences ,13,14. GMany of the risk factors that showed the importance in the model are shared by other atherosclerotic diseases such as CAD and PAD. According to the model, the risk of advanced AS incrementally increased after age 40, although fast progression and earlier disease onset have been shown in certain groups, including patients with bicuspid aortic valve and patients with chronic kidney disease ,16. AdvaThe model has the potential to be a valuable tool in clinical practice, given its simplification to an integer (points) system and reliance on variables that are readily available in most EHR systems. Yet, implementation of the model in a clinical setting should start with caution as the model has not been validated in prospective studies. The results of the model do not show a certain threshold at which screening should be recommended. A score of 207–235 (predicted risk of 5–10%) can be used as a threshold in the beginning, and further validating studies can help fine-tune it. Starting with a low threshold is reasonable considering the high prevalence of AS and the safety profile of echocardiography without contrast exposure. Additionally, echocardiography as a screening test for AS can be valuable as a screening test for other diseases that are prevalent in this population, such as thoracic aortic aneurysms, by providing information on aortic size. This study has some limitations. It is a single-center study, which might limit the generalizability of the results, even though the cohort is very large and included patients from nearly all backgrounds. However, the model has not been externally validated, and its implication in clinical settings requires caution until its validity is proven by other studies. The study included all comers with ≥moderate AS and the history of previously diagnosed versus incidental finding of AS is unknown, and the effect of such information on the analysis is uncertain. Finally, the study relied on claims data (ICD-10 codes) to assess the presence or absence of comorbidities, and such data are reported to be subject to over- or under-reporting.We developed a risk model to identify patients aged between 40 and 95 years who are at increased risk of having ≥moderate AS based on demographic and clinical characteristics. Discrimination and calibration of the model were good. This prediction rule may guide the targeted screening of patients at increased risk of having advanced AS.


These results suggest that other factors must be accounted for to explain this phenomenon. The different engagement of boys and girls in the coding activities, and/or other motivational and sociocognitive variables, should be explored in future studies.The gender gap in Computer Science (CS) is widely documented worldwide. Only a few studies, however, have investigated whether and how gender differences manifest early in the learning of computing, at the beginning of primary school. Coding, seen as an element of Computational Thinking, has entered the curriculum of primary school education in several countries. As the early years of primary education happen before gender stereotypes in CS are expected to be fully endorsed, the opportunity to learn coding for boys and girls at that age might in principle help reduce the gender gap later observed in CS education. Prior research findings however suggest that an advantage for boys in coding tasks may begin to emerge already since preschool or the early grades of primary education. In the present study we explored whether the coding abilities of 1st graders, at their first experience with coding, are affected by gender differences, and whether their presence associates with gender differences in executive functions (EF), i.e., response inhibition and planning skills. Earlier research has shown strong association between children's coding abilities and their EF, as well as the existence of gender differences in the maturation of response inhibition and planning skills, but with an advantage for girls. In this work we assessed the coding skills and response inhibition and planning skills of 109 Italian first graders, 45 girls and 64 boys, before an introductory coding course (pretest), when the children had no prior experience of coding. We then repeated the assessment after the introductory coding course (posttest). No statistically significant difference between girls and boys emerged at the pretest, whereas an advantage in coding appeared for boys at the posttest. Mediation analyses carried out to test the hypothesis of a mediation role of EF on gender differences in coding show that the gender differences in coding were  With gender differences, or gap, in Science, Technology, Engineering, and Mathematics (STEM) researchers refer to the disparity between boys and girls, or men and women, in performance, achievements, interests or beliefs in the STEM domains. As these gender disparities lead to an underrepresentation of women in higher STEM education and careers  sex-differences in the cognitive abilities underpinning performance in STEM  activities. CT is a set of thinking skills, precursor of CS education, generally understood to comprise four constituents: (1) problem analysis via abstraction and decomposition, to distill core patterns from the original problem, to break it into smaller parts and systematically tackle each of them; (2) algorithmic thinking, to enable the development of predefined re-usable executable procedural tools for solving the given problem and classes of them; (3) evaluation of the outcomes of the solution plan, correcting it where it fails , feeding all of that into (4) generalization, to lift problem-solving methods and solutions to application to similar problems Wing, . Coding The studies that explored gender-related differences in CT or coding have produced contrasting findings. A study by Kožuh et al.  reports Other studies, involving older, fifth to tenth grade, students  exposed to it for the first time  children, all novice to coding, are affected by gender differences. The additional angle we brought into this study is to determine whether any such emerging gender differences associate with gender differences in children's executive functioning (EF), in particular planning and response inhibition, cognitive abilities closely related to problem-solving and CT  children exposed to coding for the first time , assessing whether any such observed differences were mediated by gender differences in planning or response inhibition, measured by standardized planning and inhibition tests . Based on prior studies that demonstrate an association between coding skills and children's inhibition and planning abilities, we regarded inhibition and planning abilities as a potential mediator of the effects of gender on coding skills.One-hundred and nine first-graders aged from 5 to 7 years from schools located in northern Italy were enrolled in the study . Children had no prior experience with coding. They all took part in one-month introductory course to coding at the beginning of the school year, as part of a larger research project : Children's socioeconomic status was estimated based on the level of education of the child's parents (both mother and father), on a scale from 0 (less than primary school) to 4 (college or above), and on the level of parents' occupation, from 1 (unemployed) to 4 . A composite score was calculated as the non-weighed sum of the highest education and occupation score obtained by either parent (mother or father), with maximum score 8.Familiarity with technology: This indicator was gauged by asking parents about children's daily use of personal computer, smartphone, or tablet devices in their home environment. The number of girls and boys that were reported to make daily of any such device was computed and compared by chi-square analyses.The study was approved by the Ethical Committee of the Department of Developmental Psychology at the authors' institution.before  and after  the coding course. This allowed to ascertain whether gender differences in coding or EF were present at any of those moments.Following Sullivan and Bers , in thisCode.org (https://code.org/). The coding environment and tasks proposed by the Code.org platform propose visual block-based programming tasks for beginners. Individual children write their code on that platform by moving code blocks from a toolbox panel into a programming panel, to generate code sequences (programs) whose execution should achieve predefined results. All coding games in Code.org involve the use of coding blocks to instruct a sprite  so that they can reach a target or perform expected actions. Visual and textual informative feedback is provided at every execution in order that children can easily monitor their progress on the screen. Likewise, programming errors are immediately visible to the child. The target not being reached manifests by the sprite crashing against a wall or failing to find a route to the target  and after (T2) the coding lessons. Coding skills were assessed thorough children's ability to solve four coding games on Code.org, under guidance by the experimenter. The assessment started after the practice phase, in which the child familiarized with the Code.org platform and the mouse-based drag-and-drop mechanics necessary to perform the coding tasks. All children were asked to solve four coding problems individually and autonomously. To solve each coding trial, a maximum of three attempts were allowed, after which the trial was counted as failed. Specifically, the assessment involved solving trials 9 (lesson 4), 2 (lesson 5), 3 (lesson 8), 4 (lesson 14) from Code.org . Trial 9 required guiding the Angry bird sprite to proceed in successive steps to reach a given target. Trial 2 involved debugging. Trial 3 required placing blocks in a sequence apt to instruct an artist sprite to draw a target geometric shape. Trial 4 consisted of using repetition loops. All of these exercises were of the same type as those in the coding introductory course.Before starting the assessment, children were invited to practice with two coding games from For each trial, two scores were recorded as measures of children's coding skills:(1) Accuracy: a score of 2 was given if the child successfully solved the problem at the first attempt, 1 when solving it at the second attempt, 0 otherwise;(2) Time spent planning: the seconds elapsed from the moment the child was presented the trial to the moment s/he moved the first code block (which corresponded to starting to write the program). Time spent planning reflects the children's ability to plan their responses in advance and inhibit less mature trial-and-error strategies that are typical of younger children's approach to problem solving Harter, . PlanninPlanning ability was assessed by the Tower of London test  small balls on three vertical sticks of different heights, according to a precise set of rules . The entire test consists of 12 trials of increasing difficulty. All 12 trials were presented with no interruption criteria. As for the coding games, children's performance was scored for:(1) Accuracy: each attempt was scored 1 if the child performed the trial correctly within 1 min, without breaking any rule; 0 otherwise.(2) Planning time: counting from when the trial is shown to the child until when s/he makes the first move.Reliability indices for this test are 0.57 for accuracy scores and 0.71 for planning times  Accuracy: number of errors and self-corrections.(2) Inhibition time: the seconds required to complete the task.r = 0.34, and adequate reliability for inhibition time, r = 0.62. Concurrent validity, computed by correlating the performance on the numerical Stroop and the NEPSY-II verbal response inhibition subtest, is r = 0.44 for accuracy and r = 0.48 for inhibition time.Test-retest reliability and validity are not provided by the manual. Arfé et al.  report mt tests. The different distribution between girls' and boys' use of digital devices  was explored by chi-square tests.Differences between girls and boys in age and SES were examined by independent-samples The data analysis was performed in three steps.t tests were used to test gender differences in coding, planning and response inhibition abilities before and after the coding lessons. Statistical significance was set as p-value < 0.05.Independent-samples Pearson's correlations were run to explore the association between children's coding, planning , and response inhibition skills (performance on the Stroop task) before and after the introductory course to coding. Significant correlations between these abilities is indeed a condition necessary for assuming a mediation effect of children's planning and response inhibition skills on coding . Mediation analyses allow exploring both direct and indirect effects of one variable (A) on another variable (B), where indirect effects refer to the underlying mechanism by which variable A influences variable B through a third (C) mediator variable  as predictor, planning time or accuracy in coding after the course (T2) as criterion variables, and T2 planning time or accuracy on the Tower of London test (ToL), and T2 response inhibition time or errors on the Stroop test as mediators. SES and children's performance on coding, planning (ToL) and inhibition (Stroop) tasks before the course (at T1) were covariates. Confidence interval for each indirect effect was estimated considering both mediators and criterion variables at time 1 and at time 2 .Models a and b, represented in Model a, indirect effects were assessed considering the mediation of planning time on the ToL. Thus, T2 planning time on the ToL was the mediating variable (M). In Model b, the indirect effects were assessed by considering the mediating role of response inhibition time. Thus, T2 inhibition time on the Stroop test was the mediating variable. Similarly, Models c and d, in Model c, T2 accuracy on the ToL was the mediating variable. In Model d, errors in the Stroop test was the mediating variable. The covariates for all models were SES and the children's performance on coding, and planning (ToL) or inhibition (Stroop) tasks at T1. This arrangement allowed testing for the different impact of the learning experience for boys and girls, and to control for SES-related differences.To examine mediation effects, four mediation models were tested: t-tests and chi-square analyses showed that the two groups were equivalent for age, t(107) = −0.55, p = 0.59, SES, t(107) = 1.00, p = 0.32, and familiarity with digital devices: use of computer, χ2 = 0.64, p = 0.42, tablet, χ2 = 0.05, p = 0.81, and smartphone, χ2 = 0.73, p = 0.39.Between-group differences in age, SES, and familiarity with technology are reported in t(107) = 2.60, p = 0.01. However, their results were significantly less accurate, t(107) = −2.12, p = 0.04, than those of boys. The effect sizes, reported in before the coding course was equivalent. No significant differences emerged between girls and boys in planning or response inhibition, neither before nor after the coding course.before (T1) the coding course, r = 0.30, p = 0.001, and after it (T2), r = 0.31, p = 0.001. Planning time in coding correlated significantly with response inhibition times after the coding course, r = 0.29, p < 0.005, but did not show significant associations with children's performance in response inhibition before the course.The correlational analyses, reported in before the coding course (T1), r = 0.36, p < 0.001, and after the course (T2), r = −0.20, p = 0.04. The negative association between planning accuracy (ToL) and accuracy in coding at T2 indicates that after the coding course the children with a better performance on the ToL performed worse in coding. We shall return to this finding in the discussion. Accuracy on the coding games correlated significantly with inhibition errors before the course, at T1, r = –0.25, p < 0.01, and with response inhibition times after the course (T2), r = –0.26, p < 0.01.Accuracy scores on the coding games and the ToL were significantly associated both t-test analyses, it was still possible that children's planning and inhibition skills mediated the effects of gender on coding. The hypothesized mediation relationship was examined by testing the significance of the indirect effects of gender on coding planning time (Models a and b) and on coding accuracy (Models c and d) with ToL planning time or Stroop inhibition time (Models a and b) and accuracy on the ToL or on the Stroop test (Models c and d) as potential mediators.Although no gender-related differences in planning and response inhibition emerged from the The effect, whether direct or indirect, is considered significant if the interval between the upper and lower confidence bounds does not include zero. The four mediation models are reported in Model a, reported in p = 0.02). Planning time in coding tasks before the coding course (T1) has direct effects on children's planning time in coding after the course . Planning time on the ToL at T2 is predicted by planning time on the ToL at T1 and has significant effects on planning time in coding at T2 . However, the indirect effect of gender through this mediator is not significant.An inspection of Model b (before the coding course (T1) have direct effects on children's planning time in coding after the course (T2), respectively B = −2.07, p = 0.04 and B = 0.05, p = 0.02. Inhibition time after the course (T2) is predicted by inhibition time at T1, before the course, and has effects on planning time in coding at T2 . However, the indirect effect of gender through this mediator is insignificant . Planning accuracy on the ToL at T1 predicts accuracy on the ToL at T2 , which does not have significant effects on coding accuracy at T2. The indirect effect of gender through planning accuracy (ToL) is insignificant.In Model d shows a significant effect of inhibition errors at T1, before the course, on inhibition errors after the course (T2) , and a direct effect of gender on coding accuracy after the course (T2) . Again, the indirect effect of gender, through the mediator (inhibition errors at T2) is insignificant.As shown in Overall, gender effects on children's coding emerged immediately after their first experience with coding; yet, although children's planning and response inhibition skills and coding skills were significantly related, gender effects on coding abilities were not mediated by children's planning or response inhibition skills.The study presented in this paper was inspired by prior research  or response inhibition skills . Remarkably, the mediational analyses accounted for the effects of covariates like SES, and performance on the coding and cognitive tasks (planning and response inhibition) before the course. Thus, the observed differences cannot be attributed to these factors either.The results of the mediation analyses clarified that the gender differences observed in coding Some studies have suggested that gender differences in coding may be due to the different strategies or approach to coding problems characteristic of girls and boys  female trainers, observers, assistants, and experimenters. Other studies have shown that STEM gender stereotypes from early childhood to adolescence are not always influenced by the opportunity to interact with counter-stereotypical educators , girls scored slightly better than boys after the course and spent slightly more time planning on the ToL. However, their performance on the coding tasks was lower than for boys. This may suggest that they made a worse use of their cognitive resources than boys, in what would amount to a gender-related effect. Indeed, by-group correlations reveal that the association between coding and planning skills, albeit non-significant, is negative only for girls.Some more words should be spent on the negative association we found between children's accuracy in coding and the ToL after the coding course. This finding was unexpected, particularly considering that the same two measures were significantly and positively associated Planning time and accuracy in coding at T2 were also negatively correlated. Girls spent significantly more time planning in the coding tasks, and yet – as noted above – their accuracy was lower than that of boys. The longer time spent by girls in planning aligns with the findings of other studies, confirming a tendency of girls to be less impulsive and to control more their responses than boys  and their interaction with children's cognitive abilities. We are taking this lesson learned home in the design of future interventions directed to digging further into this important gender-difference problem space.The data presented in this study were collected as part of a larger project focused on the cognitive effects of coding. In the project we did A second limitation of this study is the lack of a qualitative analysis of children's strategies in solving the coding games. As demonstrated by other studies, gender differences could emerge in the way girls and boys approach the coding task (Sullivan and Bers, how they use them, for what goal, learning or leisure, in which way, alone and unassisted or with friends or seniors. Acquiring and analyzing such additional information would help gain a better understanding of children's prior experience with digital technologies in the way to anticipating engagement. The dimensions of engagement entail a social element and a learning element. Both are very important aspects of a wider study into the nature, origin, and mitigations of gender differences in relation to coding and, prospectively to Computer Science.A third and final limitation of the study concerns the lack of a fine-grained analysis of children's engagement in the coding course and of their relationship with digital technology. Engagement is known to be an important component of learning, which may be affected by self-perception over and above ability. Measuring engagement before, during, after the intervention should shed more light on the reasons for the emergence of the surprising results from this research. By the token, measuring familiarity with technologies calls for a finer-grained spectrum than merely considering how often children use digital devices, or which digital devices they use, examining also The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Ethical Committee for the Psychological Research of the University of Padova. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.BA: conception and design of the project, project coordination, paper drafting and revising, and data interpretation. CM: data gathering, coordination of the data gathering, article drafting, and data analyses. LR: guiding the data analysis. TV: article drafting and revising and coordination of the study. All authors contributed to the article and approved the submitted version.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.


The participants were evaluated, before and after the intervention, by the following means: Competitive State Anxiety Inventory-2 (CSAI-2), to measure the pre-competitive anxiety state, i.e., how anxious each athlete felt just before the competition; Brunel Mood Scale (BRUMS), an instrument for early detection of overtraining syndrome; Recovery-Stress Questionnaire for Athletes (RESTQ-Sport), to identify the extent to which each athlete was physically or mentally stressed and the athlete’s current capability for recovery; Athlete Burnout Questionnaire (ABQ), specifically developed for athletes. The IG athletes participated in 12 progressive muscle relaxation sessions, a practice for tensing or tightening a specific muscle until an ideal state of relaxation is reached. Each participant had blood pressure and heart rate measured before and after every session. The CG athletes were evaluated similarly to those in the IG but without relaxation. The results showed statistically significant differences in cognitive anxiety (p = 0.039) and specific stress (p = 0.016) between CG and IG before the intervention; in addition, a significant heart rate decrease (p < 0.01) between IG and CG was noted.The purpose of this study was to evaluate the effects of a progressive muscle relaxation program on psychological  and physiological (blood pressure and heart rate) variables in basketball athletes. Fifty-nine basketball players, aged 14 to 19 years, and members of Bauru Basket team, were recruited for this study and grouped into control group (CG,  Athletes and coaches perceive emotions, particularly performance anxiety, as one of the most important factors that can influence the outcome of a sports competition. Emotions and anxiety in sports are relevant topics that raise many questions and the relationship between them and sports performance is not unanimous in the literature . AnxietyParticipation in competitive sports can be stressful and influence the athlete’s mood and anxiety. This, in turn, affects enjoyment, adherence, and participation in sports. According to Akesdotter et al. (2020) , 19.5% oJacobson’s progressive muscle relaxation is an important ally for various populations among the various intervention techniques used to reduce anxiety, tension, and stress. This technique is recommended in daily tensions related to various factors, such as work, interpersonal relationships, and daily routines. Several studies ,10,11,12Thus, it is necessary to identify appropriate strategies and intervention programs during a competitive season to contribute to reducing the levels of anxiety and stress and improving sports performance ,16,17. TFifty-nine male basketball athletes, aged between 14 and 19 years, from the Under-15, Under-16, and Under-19 basketball teams of Bauru Basket participated in this study. Of the participants, 29 athletes (15.97 ± 1.88 years) constituted the intervention group (IG), that participated in the progressive muscle relaxation program, and 30 athletes (14.33 ± 0.48 years) formed the control group (CG). The sample was chosen for convenience, according to the teams’ availability. The inclusion criteria were having participation equal to, or greater than, 75% of the number of sessions planned in the intervention program, all athletes undergoing the same training program, and not having a history of progressive muscle relaxation training. The IG and CG athletes filled out a demographic evaluation form before the intervention program, consisting of a questionnaire with open and closed questions about the following variables: age, time as a federated athlete, competitive participation time, and training characteristics. The athletes in both groups were evaluated before, and at the end of, the 12 sessions using the following instruments:Competitive State Anxiety Inventory-2-CSAI-II ,19. ThisStress and Recovery Questionnaire for Athletes-RESTQ 76 Sport. This was developed to assess an athlete’s current stress and recovery profile , and wasAccording to the scale ranging from 0 to 6, values above 4 were considered “high,” below 2 were “low,” and between 2.01 and 3.99 were “moderate,” either for specific stress, general stress, or recovery. The scale values were calculated by the mean values of the respective items. High scores on the scales associated with stress activities reflected intense subjective stress, while high scores on the scales associated with recovery reflected many recovery activities. In general, low scores in stress-related areas and high scores in recovery-related areas are considered positive, and vice versa . Initially, the research project was forwarded to the Research Ethics Committee and approved according to the process . Prior to data collection, permission to develop the research was requested from the professionals in charge of the participating team, and the objective and methodology to be used during the study were presented. The participating athletes were informed about the conditions for entering the research and received the standardized instructions and information.The Informed Consent Form (ICF) and the Free and Informed Assent (TALE) for the athletes were previously sent to the parents of the athletes under 18 years of age who agreed to participate in the research. The conditions for participating in the research were the return of the Informed Consent Form, duly signed by parents or guardians, and the Free and Informed Assent signed by the athletes. The athletes over 18 years old agreed to participate in the research by signing the Free and Informed Consent Form. After training, the athletes answered the questionnaires in the university’s classroom, where the training sessions took place.The athletes from the intervention group (IG) participated in 12 sessions with Edmund Jacobson’s (1938) Progressive Relaxation technique, which consisted of retightening (making tense) and relaxing specific muscles until they were all relaxed . To obtaThe intervention group (IG) and the control group (CG) completed all the evaluation instruments, Competitive State Anxiety Inventory-2 (CSAI-II) and Stress and Recovery Questionnaire for Athletes (RESTQ 76 Sport) at two different times, on the previous day at the beginning of the intervention, and on the day after the end of the 12 sessions of progressive muscle relaxation. BRUMS and RESTQ 76 Sport, take about 15 and 20 min to be completed, depending on the familiarity with the questionnaire. Blood pressure (BP) and heart rate (HR) were recorded by using an automated digital . Blood pressure (BP) and heart rate (HR) were measured in a standardized way; three measurements were recorded on the left arm, the cuff was positioned at heart level, the palm of the hand facing up, the back and the forearm were supported, and the legs and feet supported on the floor. During the 12 progressive muscle relaxation sessions, the control group (CG) remained on the court, accompanied by the coach and did not perform any activity. After the end of the intervention period, the CG members were invited to participate in the progressive muscle relaxation program, according to the rules of ethical commitment.p < 0.05. As the data did not meet the normality propositions (p < 0.05), the Mann–Whitney non-parametric test was used to compare the intervention group (IG) with the control group (CG) pre- and post-intervention. The data were analyzed using the software IBM® SPSS® Statistics Version 25, and a p < 0.05 significance level was adopted in all statistical tests.To evidence the internal consistency for each instrument used, Cronbach’s Alpha Coefficient (α) was calculated. Reliability was assessed, as proposed by George and Mallery (2003): excellent (>0.90); good (>0.80); acceptable (>0.70); questionable (>0.60); poor (>0.50); unacceptable (<0.50). For data analysis, the following descriptive statistics were calculated: mean (x); standard deviation (SD); median (Md); and quartiles (Q1-Q3). To verify data normality, an exploratory analysis was performed using the Kolmogorov–Smirnov test, with statistical significance set at Initially, Cronbach’s alpha coefficient was adopted, aiming to estimate the reliability and internal consistency of the instruments used in this study. A total result of Alpha was observed for CSAI-2 (0.60) and RESTQ-76 (0.79); therefore, the results were considered acceptable. As shown in p < 0.05) between the athlete groups (intervention and control). The members of the intervention group (IG) had been federated athletes in the Basketball Federation of São Paulo for a long time. It can be noticed that the IG athletes presented higher frequencies and hours of training per week, compared to the control group (CG).An analysis performed with the Mann–Whitney test  indicatep = 0.038) pre- and post-intervention, comparing IG and CG. However, no statistically significant differences were found in the somatic anxiety and self-confidence domains.The analysis performed with the Mann–Whitney test  showed ap = 0.015). However, there was no statistically significant difference between the groups of athletes for the subscales General Stress , Global Stress ; General Recovery ; Recovery Areas ; and Global Recovery .According to p < 0.05) in six of the 12 sessions. The intervention group had greater differences compared to the control group. This difference was concentrated between the 5th and 10th sessions, suggesting that the effects of progressive muscle relaxation were more pronounced in this time interval. p < 0.05) between the groups. The differences were located in the seventh session for systolic blood pressure , and in session 2  and session 10  for diastolic blood pressure measurements. The same behavior did not occur for blood pressure . Only thThe present study aimed to verify the effects of Jacobson’s progressive muscle relaxation on psychological  and physiological (blood pressure and heart rate) variables in male basketball athletes. Few studies have examined the influence of relaxation techniques in sports environments, and several studies in other areas have emphasized the positive effects of relaxation on psychophysiological variables, justifying the present study .The results obtained showed significant improvement in cognitive state anxiety after the intervention, but somatic state anxiety and self-confidence did not exhibit the same effect. These results partly corroborated studies ,28,29 thThis result was positive, as low levels of cognitive state anxiety are associated with better coping in competitive situations and emotion regulation . Thus, mAthletes showed low levels of cognitive anxiety and somatic anxiety. Although this was not a consistent finding in the literature, some studies ,34 indicSome factors may be related to the low levels of anxiety found, such as male sex, satisfaction in the sports career, and team sports. Rice et al. (2019)  identifiThe athletes in the intervention group (IG) showed higher cognitive anxiety levels than the athletes in the control group (CG). Considering that the IG athletes had more time as federated athletes and participated in more competitions than the CG, these results were contrary to research ,38 that Concerning stress and recovery levels, the data agreed with Codonhato et al. (2018) , who fouA statistically significant difference was observed between IG and CG only for the Specific Stress domain after the intervention, indicating that the relaxation technique may contribute to reducing this variable in athletes. It is worth mentioning that this domain is related to what is perceived specifically in situations related to sports activity: disruption in the interval , emotional exhaustion , and injuries (acute injuries and vulnerability to injuries). Thus, the decrease in Specific Stress levels after the relaxation sessions indicated that the technique could reduce emotional exhaustion and improve athletic recovery.Several studies reinforce the importance of psychological monitoring in athletes associated with traditional physiological markers, such as cortisol, blood pressure, and heart rate ,42,43,44Regarding the physiological effects after progressive relaxation, Bara Filho et al. (2002)  stated tMaimunha and Hashim (2016)  revealedIn this study, only three sessions had significant differences between IG and CG for blood pressure (BP) pre- and post-intervention, and there was no significant effect when comparing the mean between the 12 sessions. The differences were not concentrated in any period, suggesting that muscle relaxation did not affect blood pressure.For heart rate (HR), there was a statistically significant difference pre- and post-intervention when comparing the HR means of the two groups. In six out of 12 sessions, the IG had greater differences than the control group, indicating a decrease in HR. These data corroborated Rissardi and Godoy (2007) , who fouIn this study, the difference between the HR indices was concentrated between the 5th and 10th sessions, suggesting that the intervention effects were more pronounced in this time interval. In Mellado’s (2015)  study, fAs for practical implications, the data from this study suggested that progressive muscle relaxation may be an effective technique to reduce heart rate, cognitive anxiety, and sport-related stress in athletes. This is important because controlling stress and anxiety, having self-confidence, and having relaxation skills are considered indispensable for improving performance during training and competition ,50,51. HDespite the contributions, some limitations should be highlighted. First, the study involved a relatively small sample size. Second, significant differences in age and length of sports experience were found between the intervention and control groups. Therefore, the demographic differences found may have been random. Thus, more studies are needed to better understand the impact of age and time of sports experience on anxiety and stress. Future studies with a randomized clinical trial and larger numbers of participants from various sports that can explore the effects of progressive relaxation after games, and at different stages of the competitive season, are recommended. Jacobson’s progressive relaxation proved to be an effective technique to reduce cognitive anxiety and stress related to sports, which can contribute to the resolution of conflicts existing in the sports context, such as competitions, trips, and overtraining, among others. Furthermore, relaxation effectively reduces heart rate, helping the athlete’s recovery.Studies with larger numbers of participants from various sport modalities that can explore the effects of progressive relaxation after games, and at different stages of the competitive season, are recommended.


Headache accompanying ischemic stroke is considered an independent predictor of neurological deterioration. This meta-analysis aims to estimate the prevalence of ischemic stroke-related headaches and identify its risk factors in China.PubMed, Embase, Cochrane Library database, Web of Science, PsycINFO, and four Chinese databases for the related publications were searched. Two researchers independently selected the literature, extracted the relevant data, and assessed its methodological quality. The meta-analysis applied a random-effects model with R software to calculate the pooled prevalence of ischemic stroke-related headaches in Chinese patients, and to merge the odds ratio (OR) of risk factors. Subgroup analysis, sensitivity analysis, and meta-regression analysis were conducted. Publication bias was assessed by a funnel plot and Egger test.Ninety-eight studies were eligible for inclusion. The overall pooled prevalence of ischemic stroke-related headache was 18.9%. Subgroup analysis showed that the prevalence of ischemic stroke related-headaches was higher among studies using self-report to diagnosis headache , and those focused on age ≥ 55 years , rural settings . There were no significant differences in the headache prevalence between studies in the south and north, and inland and coastal studies. The prevalence of pre onset headache (13.9%) and tension-type headache (15.5%) and was higher compared with other types. History of headache , female gender , midbrain lesions , and posterior circulation stroke  were major risk factors.The prevalence of ischemic stroke-associated headache is high in China. In addition, women, presence of midbrain lesions, posterior circulation stroke and a history of migraine were high-risk factors for ischemic stroke-related headaches. Designing effective interventions to prevent or alleviated headaches is necessary to promote patients’ neurological recovery and quality of life.The online version contains supplementary material available at 10.1186/s12889-022-13917-z. Globally, stroke is the second leading cause of death  and poseHeadaches occur in 6%–44% of people with ischemic stroke . MigrainWith demographic shifts and the rapid growth of China's elderly population, lifestyle habits in China are changing , 20. StuStroke-related headaches are more likely to be a significant cause of disability. The lack of epidemiological and outcome-based studies can limit the understanding and treatment of persistent poststroke headaches. Therefore, this study conducted this systematic review and meta-analysis to understand the prevalence and risk factors for stroke-related headaches in China, including Chinese and English language studies. In addition to estimating the overall prevalence of stroke-related headaches, we hypothesized that there would be differences in the prevalence of headaches based on differences in geographic setting, age, study setting, diagnostic methods, and headaches types. Furthermore, we conducted a meta-regression to explore the impact of the potential covariates such as methodological and economic factors on prevalence estimates. This work provides a strong theoretical basis for policy development on effective prevention and treatment services for this public health concern.This study was registered with PROSPERO (CRD42022328476) and conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA)  guidelinThe following 9 electronic bibliographic databases were searched : PubMed, EMBASE, PsycINFO, Web of Science, Cochrane Library, CNKI, VIP, CBM, and the WanFang database for Chinese Periodicals, by applying a pretested search strategy.Our search strategy employed medical subject heading (MeSH) and natural language text words. The references from the relevant papers or reviews were manually searched for additional studies. In case of missing relevant data from studies, we contacted the authors via email. Finally, all studies that were classified as headache studies among ischemic stroke patients in China were screened. On April 15, 2022, another search was performed on the previously mentioned database to locate the latest studies   that identified the prevalence of headaches in patients with ischemic stroke; studies that were published in English or Chinese language; studies that were published in a peer-reviewed journal or as conference proceedings with complete details. We excluded commentaries, letters, duplicate studies, reviews, and studies with a sample size below 60. Studies were also excluded if the full-text article was unable to be retrieved.First, the Endnote X9 software was used to remove duplicates as well as to facilitate the screening process; second, the titles and abstracts in the non-duplicate papers were screened; and finally, the full texts were read to determine which studies were included/excluded, and the reasons for exclusion were recorded. The literature were independently screened by two researchers (Qi Xie and Qiang Guo) in accordance with the eligibility criteria. Any discrepancies were resolved through consensus or consultation with a third reviewer (Xin-Man Dou).The process of data extraction and quality assessment were conducted in duplicate (Qi Xie and Xinglei Wang) with third-party (Xin-Man Dou) adjudication for disagreements. Data from the included studies were extracted using a standard data extraction form. The following information was collected: first author, year of publication, geographical location (province and area), provincial Gross Domestic Product (GDP) (according to the Chinese government's administrative records), study setting , sample size, numbers of headache events, the characteristics of the study participants, types of headaches, and the diagnosis criteria of headache. If the number of headache events was not reported in the included studies, the proportion reported and the total sample size were used for analyses. To ascertain the risk factors for headache among patients with stroke in China, the odds ratio (OR) and associated 95% confidence intervals (CI) from multiple logistic regression were directly extracted from the included studies.The methodological quality of case–control studies and cohort studies were assessed using the modified Newcastle–Ottawa Scale (NOS) . The cheI2 statistic and formally tested by Cochran's Q statistic. Publication bias was assessed through visual inspection of a funnel plot and the result of the Egger test, considering statistically significant at P < 0.1. The robustness of the pooled estimates was assessed by sensitivity analysis .Meta-analysis was conducted using the meta  package available for the R software (version 4.1.2). Event rates and 95% CI were calculated for each study using the frequency of headaches reported in each study and the total sample size. To identify the risk factors for headache in Chinese ischemic stroke patients, the OR value was merged from the included studies. Based on the heterogeneity of the geographic regions and the variability in screening and diagnostic tools, we considered the random-effects model for meta-analysis as a better choice. A random-effects model was applied to assign weights to each study. Pooled effect sizes and event rates for each study were presented as a forest plot, where the size of each study was proportional to their weights. Statistical heterogeneity was quantified by the P < 0.05 [To explore the sources of heterogeneity, subgroup analyses were applied based on age , geographical setting (area), study setting , methods of diagnosis, and the types of headaches. Moreover, meta-regression analysis was performed to determine whether potential covariates could explain the heterogeneity between studies. Statistical significance was set at P < 0.05 . To undeP < 0.05  for highP < 0.05 .In this study, 13,611 records were searched from the 9 databases and other resources Fig. .Fig. 1Fln = 43) and inland areas (n = 53) were included. The method used for headache determination included a visual analog scale, self-reported, Guidelines for the Prevention and Treatment of Migraine in China, Migraine diagnostic criteria developed by the Collaborative Group on Epidemiological Investigation of Neurological Disorders, Select Committee of the National Institutes of Health, and the International Classification of Headache Disorders. For most of the studies, the source of the study population was single-center  rather than multicenter (n = 6). According to the modified version of NOS scores and the AHRQ scores, 74 studies presented a relatively low risk of bias, whereas the remaining 24 presented a high risk of bias.  (Table p < 0.1) showed the presence of significant publication bias. The results of the sensitivity analysis established that none of the studies had any significant impact on the pooled prevalence of headaches  Table  and Egge95% CI, 8.9%–40.2%), followed by the visual analog scale  and the International Classification of Headache Disorders , and this difference was significant (P < 0.01). The prevalence of headaches did not differ between the southern and northern areas of China (P = 0.92); moreover, it did not differ between the inland and coastal regions (P = 0.94). The prevalence of headaches was the highest among patients with a mean age of ≥ 55 years , followed by those ≤ 18 years of age , and 18 to 55 years of age . This difference was statistically significant (P = 0.02). Studies conducted in mixed settings reported the lowest prevalence of headache  followed by urban settings  and rural settings . This subgroup difference was marginally statistically significant (P = 0.05).Subgroup analysis revealed that studies using self-report for diagnosis produced the highest prevalence of ischemic stroke headache , inland and coastal regions (P = 0.53), provincial GDP (P = 0.39), and the year of publication (P = 0.59) were not significant sources of heterogeneity, whereas the quality assessment scores (P < 0.01) of studies and study setting (P = 0.04) were observed to be significant sources of heterogeneity.Meta-regression analysis showed that the southern and northern areas   but highDespite the availability of diagnostic criteria and classification tools for different headache types, the accurate diagnosis, and management of headache disorders remain challenging for nonexpert clinicians . TherefoRegarding the types of ischemic stroke-related headaches, migraine, pre onset headache (POH), and TTH were common types in the included studies, which was consistent with the results of a previous prospective study on headache at the onset of first ischemic stroke . The pooThe findings from our research indicated that the study setting may influence the incidence of headaches. Patients with ischemic stroke who hailed from urban areas appeared to face less risk for headaches than those from rural areas. First, the distribution of stroke disease burden in China exhibited significant urban–rural differences . The NatIn China, the burden of stroke is geographically distributed as “high in the north and low in the south” and the mortality-to-incidence ratio is the lowest  in economically developed regions, such as the eastern and southern coasts . HoweverFinally, our study revealed that women were independent predictors of the occurrence of ischemic stroke-related headaches, which is consistent with the results of a previous study on migrainous infarction . PrimariOur review is the first meta-analysis on the prevalence of ischemic stroke-related headaches in China. The study has the following strengths: (1) the review was conducted on a large number of participants, ensuring the statistical power and accuracy of the estimates; (2) numerous studies included in the meta-analysis were described in Chinese, hence pooling of these data may be considered valuable to non-Chinese readers and for future studies on ischemic stroke-related headache and the related fields; (3) despite differences in in the demographic characteristics and methods, such as the diagnostic criteria for headache, the sensitivity analysis suggested that our final pooled results are statistically robust. Nevertheless, our study has the following limitations. The potential sources of heterogeneity were explored through subgroup analysis and meta-regression analysis. However, considerable heterogeneity remained in the studies evaluated in the subgroup analysis, as it is usually difficult to avoid heterogeneity in epidemiological studies . In addiThe results from the present study establish that the prevalence of ischemic stroke-associated headaches is high in China. Compared with migraine, migraine with aura (MA), inter ictal headache (IIH) and post ictal headache (PIH), the pooled prevalence of POH and TTH was higher. The prevalence of ischemic stroke related-headaches varied significantly according to the different diagnosis criteria, age, and study settings. However, there were no significant differences in the headache prevalence between studies in the south and north, and inland and coastal studies. Additionally, women, those with midbrain lesions, those with posterior circulation stroke, and patients with a history of migraine were at a higher risk for ischemic stroke-related headaches. The prevalence of stroke is high in China, the country has a large rural population, and headache is associated with the functional recovery of the nervous system. Considering these factors, there is an urgent need for policymakers and healthcare providers at the national and regional levels to implement early screening programs and develop effective prevention and intervention measures.Additional file 1.Additional file 2.Additional file 3.Additional file 4.


Our results showed that the factors affecting depression were 1.74 times for men (95% CI = 1.29–2.24), 1.37 times for older people (95% CI = 1.01–1.87), and 1.66 times for low education (95% CI = 1.21–2.27). Subjects with impairment in daily activities had 1.89 times (95% CI = 1.43–2.52) higher risk. Subjects with moderate physical activity and subjects with economic activity showed a lower risk (95% CI = 0.30–0.73) and 0.52 times (95% CI = 0.30–0.72), respectively, than subjects who did not. We confirmed that the probability of being diagnosed with depression decreased, and the perceived health status was 0.36 times lower (95% CI = 0.22–0.61) than those with good status. Therefore, it is necessary to prepare countermeasures that reflect various aspects in consideration of not only age and gender, but also daily life and emotional state when establishing policies for vulnerable classes such as recipients of basic livelihood.The purpose of this study is to verify the relationship between oral health behaviors and depression and influencing factors on depression to establish strategies that can contribute to improvement of mental health problems such as depression in vulnerable social class recipients. This study is a descriptive correlation study conducted on basic livelihood recipients over the age of 19 who responded to the 6th~7th (2013~2018) National Health and Nutrition Examination Survey. In this study, a total of 2749 people who met the criteria for subject selection were included in final analysis after requesting and downloading their raw data from the National Health and Nutrition Examination Survey through the consent process mandated by the Korea Centers for Disease Control and Prevention. Of the 2749 subjects, 279 were diagnosed with depression, accounting for 10.1% of the total. The collected data were analyzed using  Health disparity across various socioeconomic statuses (SES) has emerged as a serious public health issue not only in developed countries , but alsThe Speenhamland system of the United Kingdom, the Family Assistance Plan of the United States, and the BLSP of South Korea are systems that were implemented in different eras and different countries, but they share the common feature of providing basic income security to the vulnerable socioeconomic class .Economic poverty among BLSP-benefit recipients was found to increase mental health problems and the severity of depression. While the mental health of public welfare recipients has been extensively researched previously, and since the Welfare Reformation in 1996 in the United States, not many studies have examined depression in welfare beneficiaries in particular. Thus, there is a need for further research on the mental health issues affecting welfare recipients .Depression is a mental disorder characterized by a sad mood, low self-esteem, and loss of interest in life. It is a serious disorder that has an impact on overall physical and oral health by disrupting one’s mood and hindering activities of daily living (ADLs), such as working, playing, eating, and sleeping ,7. The nOral health disparities are also evident across socioeconomic classes. A previous study reported that dental caries, periodontal diseases, and tooth loss were more prevalent in adults with low SES and that socioeconomic factors are strongly associated with oral health disparity . This suOral health is the foundation of building a good quality of life and maintaining health from young adulthood to middle adulthood and older adulthood . Of variAlthough many prior studies have attempted to identify the predictors of depression among older adults, middle-aged adults, young adults, and the general population ,20,21,22Thus, this study investigated the association between oral health behaviors and depression and the predictors of depression in BLSP-benefit recipients, to present foundational data for improving mental health problems, such as depression, in the socially vulnerable BLSP-benefit recipients.This study was a descriptive correlational study aiming to examine the association of oral health behavior with depression, and to identify the predictors of depression in BLSP-benefit recipients.The target population of Korea National Health and Nutrition Examination Survey (KNHANES) comprises non-institutionalized Korean citizens residing in Korea. KNHANES is composed of three component surveys: a health interview, health examination and nutrition survey. The health interview and health examination are performed by trained medical staff and interviewers at the mobile examination center. The health interview questionnaire consists of household and individual components .We requested the raw data of the sixth and seventh (2013–2018) KNHANES, as per the Korea Disease Control and Prevention Agency (KDCA) protocol and downloaded the data for analysis.The study population comprised 3342 adults aged 19 years and over who received BLSP benefits and responded to the sixth and seventh (2013–2018) KNHANES. Of these, 2749 individuals who responded to all survey items and had no missing data were selected for the final analysis .With reference to the literature ,25, geneOral health practices included oral health checkups in the past year, use of oral hygiene products , dental preventive treatment, and daily tooth brushing frequency.The Patient Health Questionnaire (PHQ) is a self-reporting questionnaire developed to help detect and diagnose a few mental disorders commonly encountered in primary care settings. It is the most widely used instrument in clinical and research settings . The PHQhttps://knhanes.cdc.go.kr/, accessed on 2 May 2021) after reading the “Rules for KNHANES raw data disclosure and use”.The KNHANES raw data only contain de-identified information, in accordance with the Personal Information Protection Act and Statistics Act. The KNHANES is conducted after review and approval by the KDCA institutional review board (2013-12EXP-03-5C). The official KNHANES data are available for public use. We downloaded the raw data from the KNHANES website  software as follows: Differences in participants’ general characteristics according to depression were analyzed, using number and percentage, or mean and standard deviation, and the chi-square test. Differences in oral health practices according to depression were analyzed with chi-square tests. Predictors of depression were analyzed using multiple logistic regression. Nominal variables were dummy-coded.n = 204, 73.1%), married , and had an elementary school education or less . From the entire study population, 1475 (53.7%) had an elementary school education or less, and 1781 (64.8%) were not economically active. A total of 1972 participants (71.7%) had no problems with ADLs. Among individuals diagnosed with depression, the majority (75.6%) were not economically active, had no problem with ADLs (57.7%), and did not engage in moderate-intensity physical activity (90.0%). Smoking and drinking status and perceived oral health status did not significantly differ according to depression. Most of the participants diagnosed with depression (63.4%) had poor self-rated health.Age differed significantly according to depression. The majority of individuals diagnosed with depression were female (n = 101) in the depression group and 11.8% (n = 292) in the no-depression group (The percentage of participants with PHQ-9 scores indicating mild to severe depression (5–15) was 36.2% . The use of oral hygiene products also differed significantly between the depression group  and the no-depression group  . The mean daily tooth brushing frequency was 2.06 ± 1.22 in the entire study population. The percentage of participants who brushed their teeth three or more times a day significantly differed between the depression group  and the no-depression group   (= 0.006) .2 = 48.01, p < 0.001), and the explanatory power as determined by the Nagelkerke coefficient of determination was 31.7%. Classification accuracy was 89.9%, and a good model fit was established, as the hypothesis that the observed values of the model do not differ from the predicted values was not rejected based on the Hosmer–Lemeshow test .Logistic regression was performed to identify the predictors of depression in BLSP-benefit recipients . In modeThe predictors of depression among BLSP-benefit recipients were identified as age, sex, education, economic activity, moderate physical activity, and self-rated health.In model 1, the odds ratio (OR) for the diagnosis of depression was 1.45 in individuals with an older age , 1.72 for males as compared to females (95% CI 1.29–2.29), 1.81 for people with elementary school or less education as compared to those with middle school or higher education (95% CI 0.36–0.65). Those who do moderate-intensity physical activity were 53% , less likely to be diagnosed with depression as compared to those who do not. There was a 64% reduction for those who were economically active as compared to those who were economically inactive , and 63% reduction for those with good self-rated health as compared to those with poor self-rated health .In model 2, oral health practices  that significantly differed according to depression in the univariate analyses were added to the independent variables used in model 1 . In modeOral health behaviors entered in model 2 did not influence the diagnosis of depression .This study aimed to investigate the association between oral health behaviors and depression and the predictors of depression in BLSP-benefit recipients, to provide a basis for developing interventions for depression in BLSP-benefit recipients, who represent a vulnerable social group, by using the sixth and seventh (2013–2018) KNHANES data sets. As predictors of depression among BLSP-benefit recipients, we identified sex, age, education, ADLs, moderate physical activity, economic activity, and self-rated health.In our study, the risk for the diagnosis of depression was significantly higher among men than women. On the other hand, depressed mood was significantly more prevalent among women in another study on adults using the eighth KNHANES data sets , and majIn the case of the United States, stressful events such as bereavement, medical illness and substance use disorders, or medication were identified as contributing factors to depression . In KoreIn terms of education level, people with an elementary school education or less had a significantly higher risk for depression as compared to those with a middle school or higher education, similar to previous findings that the prevalence of depressive symptoms was higher among the less-educated individuals . This diThose who did not engage in moderate-intensity physical activity were at significantly higher risk of a diagnosis of depression. While a direct comparison is difficult, the experience of depressive mood is significantly higher among people who do not regularly walk in one community . In addiIn addition, the risk for diagnosis of depression was significantly higher among economically inactive individuals. Previous findings that being economically inactive is a predictor of depressive mood , that thIn the present study, oral health practices, namely oral health checkups in the past year, use of oral hygiene products, and tooth brushing frequency were not significant predictors of the diagnosis of depression. A previous study that used the fourth and fifth KNHANES data also found that tooth brushing and oral examination did not influence depressive symptoms in middle-aged adults . On the This study has some limitations. First, this study was a cross-sectional survey using the KNHANES data. Thus, the results do not provide causal implications. Second, self-rated health, perceived oral health status, and moderate physical activity were collected through a self-rated questionnaire. Hence, a possible response bias must be taken into consideration when interpreting the results.Despite these limitations, however, this study was significant in that it attempted to examine the factors that influence the diagnosis of depression in relation to oral health practices in recipients of BLSP benefits, which is a vulnerable social group, and to examine their problems in more depth using nationally, for many years Korea representative data.This study analyzed the data of 2749 BLSP-benefit recipients aged 19 years and over from the sixth and seventh KNHANES data (2013–2018) in order to identify the relationship between oral health practices and depression, as well as predictors of depression in this population with a view to providing a basis for improving both their oral health and mental health. Our study results showed that male sex, old age, low education level, no moderate physical activity, no economic activity, and poor self-rated health predict a diagnosis of depression. Although oral health checkups in the past year, use of oral hygiene products, and toothbrushing frequency were not significant predictors, they did differ between the groups with and without depression. Furthermore, BLSP-benefit recipients with a diagnosis of depression were found not to seek preventive oral treatments. Thus, we propose that the government should continue to promote and educate people on the importance of oral health and should implement strategic interventions to reduce depression in vulnerable social groups. Oral health is closely linked to the living environment, dietary patterns, oral hygiene habits, and knowledge and attitude toward oral hygiene. Since most oral problems can be managed by prevention, programs that promote oral health practices are needed.Since there are various characteristic symptoms of depression according to age, it is important to properly evaluate them. In the case of depression in old age, it is easy to overlook the symptoms of depression, especially in many cases, which are considered to be a process of physical illness and normal aging. Therefore, it is necessary for medical staff to provide assessment through appropriate screening tools for each age group and education and intervention to prevent depression by age group, for national policymakers to come up with strategies for providing jobs that can enhance self-esteem through economic activities for BLSP-benefit recipients with depression. Furthermore, continued, multilateral research is needed to analyze the factors influencing depression in BLSP-benefit recipients using large sample data.


Moreover, the cut-off values for volume and EI were 1801.145 mm3 and 3.835, respectively. The scoring model that was based on multivariate logistic regression coefficients performed better, achieving AUCs of 0.755 ± 0.062 and 0.780 ± 0.061 for the internal validation and validation cohorts, with p values of 0.168 and 0.073 for the Hosmer–Lemeshow test. Conclusions: KPS, extracranial lesion control, tumor volume, and EI had a certain correlation with the treatment response to SRS. Scoring models that are based on these variables can accurately predict the treatment response of patients with BM to SRS, thereby assisting doctors to make an appropriate first treatment strategy for patients with BM to a certain degree. Background: Stereotactic radiosurgery (SRS) is considered a promising treatment for brain metastases (BM) with better healing efficacy, relatively faster treatment time, and lower neurotoxicity, which can achieve local control rates above 70%. Although SRS improves the local control of BM, this may not translate into improvements in survival time. Thus, screening out the key factors influencing the treatment response to SRS, instead of the survival time following SRS, might be of more significance. This may assist doctors when making adjustments to treatment strategies for patients with BM. Methods: This is a retrospective review of 696 patients with BM who were treated with SRS at Huashan Hospital, Fudan University between June 2015 and February 2020. According to the patients’ treatment response to SRS, the patients were divided into an improved group (IG) and a progressive group (PG). The clinical data and magnetic resonance imaging (MRI) performed pre- and post-treatment were collected for the two groups. Five clinical variables , primary tumor type, and extracranial lesion control) and seven radiological manifestations , diffusion weighted imaging (DWI) sequence signal, and enhanced pattern) were selected and compared. A stepwise regression analysis was performed in order to obtain the best prediction effect of a group of variables and their regression coefficients, and finally to build an SRS treatment response scoring model based on the coefficients. The performance of the model was evaluated by calculating the AUC and performing the Hosmer–Lemeshow test. Results: A total of 323 patients were enrolled in the study based on the inclusion and exclusion criteria, including 209 patients in the IG and 114 patients in the PG. In the Chi-square test and  Brain metastases (BM) are the most common intracranial tumors in adults and about 20–40% of patients with cancer have BM during the course of disease . Due to The main concern of previous studies was the factors influencing the survival of patients with BM after SRS treatment ,12,13,14Therefore, we tried to screen out the key clinical variables and radiological manifestations that are significantly associated with the treatment response of patients with BM to SRS by comparing the relevant clinical data and MRI images of patients with improvement and progression after treatment. This may provide some help for doctors when making an appropriate first treatment strategy for patients with BM. Moreover, radiation necrosis and true progression are dramatically similar in both conventional MRI images and clinical manifestations . In orden = 37); (2) surgery or WBRT prior to SRS treatment (n = 29); (3) other concurrent treatments (n = 33); (4) cystic metastases, cranial metastases, and leptomeningeal metastases (n = 45); (5) patients judged as having stable disease after treatment (n = 178); (6) metallic or motion artifacts on MRI images (n = 51). Ultimately, a total of 323 patients were enrolled in the study. Predominant clinical profiles, including gender, age, KPS, primary tumor type, and extracranial lesions control , were recorded. This retrospective study was approved by the institutional review board of Huashan Hospital, Fudan University (KY2021-066) and was conducted in accordance with the Helsinki Declaration. The requirement for written informed consent was waived. The data of patients with BM who received SRS treatment at Huashan Hospital, Fudan University between June 2015 and February 2020 were reviewed. Eligible criteria were as follows: (1) pathologically confirmed primary cancer; (2) no more than four brain metastases confirmed by contrast-enhanced T1-weighted imaging (CE-T1WI) MRI; (3) patients who underwent SRS treatment only; (4) complete acquisition images of pre-treatment and follow-up MRI, including T1-weighted imaging (T1WI), CE-T1WI, T2-weighted imaging (T2WI), and DWI. Patients were excluded if any of the following conditions were met: (1) pathological examination was absent or the diagnosis was combined with another primary cancer . The median radiosurgery volume was 3.27 cm3 and the median margin dose was 17 Gy . The margin dose was generally prescribed at an isodose line level of 40–70%, with a median of 50%. The median time between pre-treatment MRI and SRS treatment was 0 days .All patients underwent SRS treatment using Leksell Gamma KnifeTreatment responses were evaluated based on the pre-treatment MRI and the follow-up MRI approximately 60 days after treatment. According to The Response Assessment in Neuro-Oncology Brain Metastases (RANO-BM) criteria , patientAll MRI examinations were acquired using a 1.5T MRI system  with an 8-channel phased-array head coil before and after SRS treatment. MRI sequences included T1WI, CE-T1WI, T2WI, and DWI, and the total acquisition time per patient was approximately 18 min.All the MRI images were analyzed in consensus by two experienced neuro-radiologists . Radiological manifestations, including location , number, volume, maximum diameter, EI, DWI sequence signal , and enhanced pattern , were assessed. The EI was calculated according to the method proposed by Kim et al. .In this study, a total of 12 clinical and radiological variables were evaluated. The independent variables were sex , age, KPS , primary tumor type (numbered in a certain order), extracranial lesion control , tumor location (numbered in a certain order), tumor number, tumor volume, maximum diameter, EI, DWI sequence signal , and enhanced pattern . Mainstream software  was used for statistical analysis of the clinical variables and radiological manifestations.t-test on the discrete and continuous variables in order to examine the univariate association of the radiological and clinical variables with the SRS treatment response. Statistical significance was set at 0.05 and was used to filter significant variables. The cut-off value for the discrete variable was determined by drawing a ROC curve and by calculating the Youden index. Finally, multivariable logistic regression models were built using the selected variables in order to determine independent predictors for predicting patients’ responses after SRS treatment. Initially, all the variables were included, but the best model was derived using a stepwise logistic regression analysis. The regression coefficient of the best model was used to establish the scoring model. In order to evaluate the discrimination and calibration of the scoring model, the ROC curve was drawn, the AUC was calculated, and the Hosmer–Lemeshow test was performed. First, we performed a univariate analysis by using the chi-square test and 3 to 6780.15 mm3, and the average tumor volume was (1921.67 ± 65.10) mm3. Maximum diameter of the tumor ranged from 0.53 cm to 4.93 cm, with an average of (2.01 ± 0.06) cm. We divided the generation cohort  and validation cohort for the model according to the proportion of treatment responses. There were 193 cases in the generation model (125 cases from the IG and 68 cases from the PG), 65 cases in the internal validation cohort (42 cases from the IG and 23 cases from the PG), and 65 cases in the validation cohort (42 cases from the IG and 23 cases from the PG).A total of 323 patients were included in the study based on the inclusion and exclusion criteria, including 209 patients in the IG and 114 patients in the PG. The patients’ demographic and baseline characteristics are shown in p < 0.05 as the adoption standard, we concluded that KPS, extracranial lesion control, tumor volume, and EI were significant variables.The results from the univariate analysis are shown in In order to process the continuous variables, we first drew the ROC curve for two continuous variables (tumor volume and EI) based on the patients’ treatment response, as shown in We constructed a multivariable logistic regression model based on four variables  in order to determine the coefficients of each variable in predicting patients’ treatment responses, and generated a scoring model, as shown in Based on the scoring model, we scored the cases in the internal validation cohort and the validation cohort, and used the ROC curve and the Hosmer–Lemeshow goodness of fit test to test the discrimination and calibration of the scoring model. As shown in In the Hosmer–Lemeshow test, the data for the internal validation and validation cohorts were divided into 6 groups and 7 groups, respectively. The actual observed values and model predicted values corresponding to the treatment response labels of each group are listed in p values for the internal validation  and the validation cohorts  were both >0.05, which means that there was no significant difference between the predicted value and the observed value. The above analyses showed that our scoring model has good discrimination and calibration ability.The There are many complex factors affecting the treatment efficacy for BM ,22, suchIn this study, the MRI images of patients with BM before SRS treatment and at follow-up (approximately 60 days after treatment) were collected in order to evaluate treatment response. In total, there were 209 patients in the IG and 114 patients in the PG. By comparing the differences in clinical variables and radiological manifestations between the two groups, it was found that KPS, extracranial lesions control, volume, and EI significantly correlated with the treatment response of patients with BM to SRS. KPS is the evaluation standard for the quality of life of patients with cancer and was proposed by Karnofsky from the Eastern Cooperative Oncology Group (ECOG). It was originally used to evaluate whether patients with cancer were able to tolerate chemotherapy . KPS is This study indicated that patient age and gender have little correlation with a patient’s treatment response to SRS, which is similar to the findings from research conducted by Petrovich et al. . AlthougPrevious studies have shown that BM involving important parts of the brain  is closely related to the efficacy of SRS treatment. If SRS treatment was given at a conventional dose, it would inevitably adversely affect the important surrounding neuroanatomical structures. Thus, due to the requirement of preserving nerve function, the radiation dose needed to be reduced in order to reduce the local dose, which in turn affected the efficacy of SRS treatment. In this study, there were only 10 patients with BM involving the brain stem, thalamus, and other important parts. These patients accounted for 3.1% of all the included patients, and no correlation between BM location and treatment response was found. Therefore, more patients with BM involving important neuroanatomical structures need to be enrolled in future research.This study indicated that the number of BM did not significantly correlate with the treatment response to SRS, which was similar to the findings from research conducted by Greto et al. . BhatnagThe findings from a study conducted by Wang et al.  suggesteDWI reflects the Brownian motion of water molecules, which is one of the most important MRI sequences, and hyper-intensity indicates that the motion of water molecules is limited . In thisThe initial treatment for BM patients relies substantially on local therapy (radiotherapy or neurosurgery) , whereasHowever, our study still has some inevitable limitations. First, this was a retrospective study and not a randomized trial, lending to its inherent limitations. Secondly, treatment responses were evaluated based on the pre-treatment MRI and the follow-up MRI approximately 60 days after treatment. Although it met the evaluation requirements of the RANO-BM criteria, it may only represent the short-term treatment response, and follow-up and long-term efficacy analyses are still needed. Thirdly, the gene detection information of the primary tumors was incomplete. This needs to be added in future research. Moreover, multi-centered, prospective, and randomized controlled clinical research on the treatment response of patients with BM to SRS is required.Treatments for BM are changing rapidly, requiring doctors to formulate individualized treatment strategies based on multidisciplinary theories, such as neuro-oncology, radiology, radiotherapy, and pathology, in order to achieve the best treatment efficacy. Valuable clinical variables and radiological manifestations may play an indispensable role in first treatment strategy making. This study indicates that KPS, extracranial lesion control, tumor volume, and the EI for BM patients correlates with the patients’ treatment response to SRS. These findings may assist doctors when making appropriate first treatment strategies for patients with BM.


Background Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that leads to muscle weakness and paralysis. Fatigue is a disabling symptom, frequently reported in ALS, but remains under-investigated in this population. Thus, an accurate investigation of this symptom and possible associated factors in this clinical condition is needed to assist in the establishment of an adequate treatment approach.Objective To investigate the presence of fatigue in individuals with ALS and possible factors correlated with this symptom.Methods Sixty-five individuals with sporadic ALS participated in the present study. Demographic, clinical, and functional aspects were investigated. Evaluations involved the Fatigue Severity Scale (FSS), ALS Functional Scale (ALSRFS-R), and Quality of Life (QoL) questionnaire (ALSAQ-40). Descriptive and correlation analyses were performed with SPSS statistical program for Windows version 19.0 .Results Among the 65 individuals evaluated, 44.6% (n = 29) presented fatigue based on the FSS. The mean fatigue intensity was 5.4 ± 1.2 and only 10.4% used a specific medication for fatigue. Differences between the groups with and without fatigue were found regarding sex (p = 0.049), pain intensity (p = 0.026), functioning (p = 0.004), disease severity (p = 0.029), and QoL (p = 0.000). Fatigue was correlated with pain intensity , muscle strength , functioning , and QoL . No correlations were found with age, time since diagnosis, cramps, or other mobility parameters.Conclusions Fatigue is a common symptom among individuals with ALS and may be present in all stages of the disease. This symptom was correlated with worse functioning, poorer QoL, greater pain intensity, disease severity, muscle weakness, and the female sex in individuals with ALS. Amyotrophic lateral sclerosis (ALS) is a degenerative motor neuron disease characterized by the progressive impairment of upper and lower motor neurons.As the disease progresses, generalized muscle weakness and fatigue occurs, which leads to the loss of movements and a diminished capacity to perform activities of daily living. Besides motor impairment, extramotor manifestations can also occur, such as cognitive and behavioral disorders.The etiology of fatigue in ALS is not fully understood but appears to be multifactorial. The proposed mechanisms include muscle activation disorder, muscle changes resulting from disuse, cardiorespiratory deconditioning, and psychological factors.One characteristic of fatigue in ALS is that the manifestation of weariness or exhaustion is only partially relieved by rest and tends to worsen throughout the day,Despite the impact of fatigue on the lives of individuals with ALS, little is known regarding the possible clinical and functional factors related to its presence,An exploratory cross-sectional study was conducted.The present study involved a convenience sample of 65 individuals with a diagnosis of sporadic ALS according to the Awaji criteriaA questionnaire was used to collect data on sociodemographic and clinical characteristics: age, sex, educational status, comorbidities, medication use, fatigue medication, nonpharmacological treatment for fatigue, hospitalization, ventilation, gastrostomy, pain in the previous week, mobility , use of mobility aids, multidisciplinary approach, time in years since ALS diagnosis, site of onset of symptoms, and use of riluzole.Fatigue was assessed using the Fatigue Severity Scale (FSS), which is a nine-item self-report questionnaire used to investigate the severity of fatigue in the daily life of the respondent. Each statement on the scale is scored from 1 (strongly disagree) to 7 (strongly agree) points. The total is calculated by the average of all items and a score ≥ 4 indicates the presence of fatigue.The Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) was used for the functional assessment. The ALSFRS-R questionnaire uses an ordinal scale to assess capacity and independence on 12 functional activities . Each function is scored from 0 to 4 points and the total ranges from zero (severe dysfunction) to 48 .Muscle strength was measured bilaterally and scored on a scale from 0 to 5 points using the Medical Research Council (MRC) scale. Four upper limb muscles  and four lower limb muscles  were considered. The score of the 16 muscle groups produced an overall strength score ranging from 0 to 80 points,Quality of life was assessed using the ALS Assessment Questionnaire-40 (ALSAQ-40), which is specifically designed to evaluate the QoL of patients with ALS. The AALSAQ-40 addresses five domains that are normally compromised in motor neuron diseases: food, communication, activities of daily living and independence, mobility, and emotional aspects. The score for each domain ranges from 0 to 100. The total score is determined from the sum of the domains and ranges from 0 to 500, with higher scores denoting worse QoL.p < 0.05).Descriptive analysis was performed with the calculation of frequency or measures of central tendency and dispersion, depending on the characteristics of each variable. The Shapiro-Wilk test was used to determine the normality of the data. For the comparison of subgroups according to the presence of fatigue (group with and without fatigue), the multivariate analysis of variance (MANOVA), the Mann-Whitney test, the chi-squared test, or the Fisher exact test was used depending on the variable analyzed. In order to reduce the occurrence of type 1 error, comparisons of quantitative dependent variables were performed using MANOVA. Considering the study design had only two factors, the post hoc analyzes were automatically presented by the software via an independent T-Student test. Either the Pearson or the Spearman correlation test was used to investigate correlations between fatigue and clinical/functional variables, depending on the normality of the data. For the correlation analysis, the variables  were selected when presenting significant differences between the groups with and without fatigue or due to their clinical relevance. All analyses were performed with the aid of IBM SPSS Statistics for Windows version 19.0 . The significance level was set at 5% (n = 29) had fatigue based on the screening test (FSS). The mean reported fatigue intensity was 5.4 (SD = 1.2) and only 10.4% (n = 3) of the individuals with fatigue took specific medications for controlling the condition (bupropion and amantadine). No participants reported undergoing any specific nonpharmacological treatment for controlling fatigue.Among the total of 65 individuals evaluated, 44.6% (p = 0.049), pain intensity (p = 0.026), total ALSFRS-R functional scale score (p = 0.004), level of severity of ALS (p = 0.029), and QoL measured using the ALSAQ-40 (p = 0.000). No significant differences were found for the other variables (The group that reported fatigue was predominantly composed of women (51.7%) and limb onset of ALS (72.4%), with a median of 2 years since the diagnosis (range: 0.7 to 20 years). The clinical and demographic characteristics of the groups with and without fatigue are displayed inriables .p = 0.003), QoL , pain  and muscle strength . No significant correlations were found for the other variables (age and time since diagnosis). Correlations between fatigue intensity and clinical/functional factors are displayed inSignificant correlations, but fair according to Portney et al.,Fatigue is a prevalent symptom among individuals with ALS. Clinically, fatigue is correlated with worse functional capacity, muscle weakness, and poorer QoL, but remains an underexplored symptom in studies and clinical practice.In the present study, 44.6% of the individuals presented fatigue. The frequency of fatigue in individuals with ALS reported in the literature varies greatly. Some studies report similar frequencies to that found in the present investigation, such as 44%In the present study, a significant difference was found between the sexes, with fatigue occurring less in men than women. This difference in prevalence between the sexes has also been found in the general population without a diagnosis of ALS.A fair relationship r = 0.425) was found between fatigue intensity and pain intensity in the present study. Despite being frequent symptoms and often overlooked in clinical practice, little investigation has been made regarding the relationship between these symptoms. was founMuscle weakness was correlated with fatigue in the present sample. We found an inverse relationship between fatigue intensity and muscle strength measured by the MRC scale, and a correlation coefficient of - 0.356. This finding may be related to peripheral mechanisms (associated with muscle strength dysfunction) that contribute to fatigue in ALS.Fatigue was inversely correlated with functioning measured using the ALSFRS-R functional scale . Previous studies have also reported that more advanced stages of the disease  are associated with higher rates of fatigue.Fatigue was related to poorer QoL in the present sample r = 0.481). This finding was expected and has been widely described in previous studies.81. This Despite the negative impact of fatigue, especially in individuals with ALS, the clinical management of this symptom is scarce.The present study has limitations that should be considered, such as the cross-sectional design, the sample composed of patients from a specialized center and the use of a unidimensional instrument for the assessment of fatigue. Longitudinal studies are needed to gain a better understanding of factors associated with fatigue and enable the determination of causality between variables. Moreover, future studies should use assessment tools to investigate the physical and mental components of fatigue independently and thus identify factors associated with central and peripheral fatigue.In conclusion, the present study verified that fatigue was correlated with worse functioning, poorer QoL, greater pain intensity, disease severity, muscle weakness and the female sex in individuals with ALS. Despite being frequent, fatigue is underinvestigated in clinical practice and scientific research involving this population. Considering the prevalence, complexity and consequences of fatigue, further studies are needed to investigate this symptom better and enable more adequate treatment and therapeutic options.