However, at a borderline non-significant way, PR predicts all-cause mortality in a general population of Italian adults. This is supported by the findings demonstrating a significant association between the PR’s domain reflecting a positive acceptance of change and all-cause mortality. Psychological resilience (PR) is the capacity to adapt positively in face of adversity. Its role as an independent protective factor has been acknowledged in recent years. We aimed to test the association of PR with all-cause and cardiovascular disease (CVD) mortality in a general adult population. We performed longitudinal analyses on 10,406 CVD-free individuals from the Moli-Sani cohort (follow up = 11.2 year). PR was assessed by the 25-item Connor and Davidson resilience scale. PR factors were identified through polychoric factor analysis. Associations with mortality were tested using multivariable Cox regressions. Higher levels of PR were associated with reduced all-cause mortality in a model including sex and age . The association decreased after inclusion of socioeconomic, clinical, and behavioral factors into the model . No relation was observed with cardiovascular mortality in the fully adjusted model . An inverse association of Factor 1 (reflecting positive acceptance of change) with all-cause mortality (HR = 0.89; 95%CI 0.82–0.98;  In the epidemiological field this research has been translated in the enquiry of risk factors that promote illnesses and mortality. However, there have been important ramifications in the field, including health promotion [Cardiovascular disease (CVD) remains the leading cause of death and disease burden globally ; in factromotion .Salutogenic orientation, which focuses its attention on salutary factors, i.e., potential factors that can promote health instead of disease [A compelling theory of health promotion is the  disease . In this disease ,6, sense disease ,8, and p disease  have sho disease . In particular, PR can be defined as the capacity of individuals to cope successfully with significant change, adversity, or risk . InitialPR research flourished in psychiatric settings, and questionnaires were initially designed as outcome measurements for psychiatric patients, in particular patients that had suffered trauma. PR research in non-psychiatric/psychologic setting is in its infancy and analyses are mostly explorative. There are only three prospective cohort studies in our knowledge that have investigated PR’s association with cardiovascular health and survival with a longitudinal design. The Swedish military conscription cohort found PR to be associated with lower incidence of stroke, coronary heart diseases, hypertension, diabetes, and heart failure ,17,18,19To fill this knowledge gap, we used data from the general population of the Moli-Sani Study cohort  and tested the hypothesis that higher PR levels in the population are associated with a lower risk of all-cause and CVD mortality. However, we also acknowledge an important limitation from the very beginning: PR nature in general populations may have a different impact on overall health compared to psychiatric populations. General populations most probably have experienced a lesser amount of stress and adversity than their psychiatric counterparts. The Moli-Sani Study is a prospective cohort study of 24,325 men and women randomly recruited from the general population of Molise, a Southern region of Italy. The cohort was established between March 2005 and April 2010 with the main aim of investigating genetic and environmental determinants of non-communicable chronic diseases. Exclusion criteria were pregnancy at the time of recruitment, mental disturbances or decision-making impairments, current poly-traumas or coma, or refusal to sign the informed consent. The Moli-Sani Study was approved by the Ethics Committee of the Università Cattolica del Sacro Cuore  and all participants provided written informed consent. Details of the study have been provided in full elsewhere . Assessmn = 508), missing data on CVD (n = 97), unreliable medical or dietary questionnaires as judged by interviewers (n = 341), and missing data on CVD mortality (n = 9), 10,406 subjects were included in the final analysis.Of the original cohort of 24,325, a random sample of 18,680 participants underwent a psychological examination, of which 11,702 (63%) provided complete information on PR, and thus were included in the present analysis. After further exclusion of subjects with any history of cardiovascular disease , compared to those that underwent psychological examination but were excluded from the present study (n = 6251), were prevalently men, younger, and had lower cumulative socioeconomic disadvantage (CSD). No significant differences were observed for the prevalence of major health conditions nor health behaviours between the two groups   which waThe Moli-Sani Study cohort was followed up for mortality until 31 December 2018. Cause-specific mortality was assessed by the Italian mortality registry, validated by Italian death certificates (ISTAT form) and coded according to the International Classification of Diseases (ICD-9). CVD mortality included deaths from diseases of the circulatory system when the underlying cause of death included ICD9 codes 390–459. 2. Subjects were classified as never-smokers, current, or former smokers (quit at least 1 year ago). History of cardiovascular disease  was self-reported and confirmed by medical records and therapy. History of cancer was self-reported and confirmed by medical records. Participants were expected to have diabetes, hypertension, or hyperlipidaemia if they were receiving disease-specific drugs. Leisure-time physical activity (PA) was expressed as daily energy expenditure in metabolic equivalent task-hours (MET-h/d) for sport, walking, and gardening. Height and weight were measured, and body mass index (BMI) was calculated as kg/mCumulative socioeconomic disadvantage (CSD) over life-course was assessed by a score computed using three childhood socioeconomic factors : (a) avaThe Mediterranean Diet Score, developed by Trichopoulou et al., was used to estimate diet quality as reflected by adherence to the Mediterranean diet . PsycholQuality of life was assessed by using the validated Italian version of the self-administered SF-36 . Analyses were performed on 10,406 individuals that were grouped in quartiles of PR with 2600 subjects in each quartile. Prior data showed that the rate of events  was 0.05. Under the assumption of a 0.05 rate of all-cause mortality events—suggested by previous studies in the Moli-Sani cohort—we were able to detect true hazard ratios (≤0.70 or ≥1.37) in one group in comparison with another, with probability (power) 0.8, at a Type I error probability α = 0.05.For CVD mortality (expected rate 0.015), we were able to detect significant hazard ratios (α = 0.05) ≤0.46 or ≥1.73.Baseline characteristics of the participants according to quartiles of PR are represented as means with standard deviation (±SD) or number and percentages for continuous and categorical values, respectively. Differences in the distribution of baseline covariates according to PR quartiles were calculated using generalised linear models adjusted for age, sex, and energy intake .p value for global test = 0.12).The proportional hazards assumption was assessed using weighed Schoenfeld residuals, and no violation was identified  with 95% confidence intervals (95%CI), and calculated by using Cox proportional hazards models with time-on-study on the time scale and adjusting for baseline age as covariate in the model. Multivariable-adjusted HRs were calculated across quartiles of PR, as well as considering PR as a continuous variable (1 SD increase).Participants contributed person-time until date of death, date of emigration or loss-to-follow-up, or end of follow-up, whichever occurred first. Participants who died from another cause than the one under study were included and censored at the date of the competing death event. In addition to a crude model, we used a Model 1 adjusted for age (continuous) and sex, which was alternately controlled for the following set of factors: (a) Model 1 + clinical factors at baseline ; (b) Model 1 + behavioural factors ; (c) Model 1 + socioeconomic/social factors ; and (d) all factors included simultaneously into the model. n = 402), leisure-time physical activity (n = 78), BMI (n = 2), smoking habit (n = 6), history of cancer (n = 27), diabetes (n = 106), hyperlipidaemia (n = 58), hypertension (n = 52), and psychological assessment (n = 47). We used a multiple imputation technique  to maximise data availability for all variables, avoid bias introduced by not-at-random missing (MNAR) data patterns, and achieve robust results over different simulations (n = 10 imputed datasets). Statistical tests were two-sided, and Bonferroni correction for multiple comparisons was applied to each analysis according to the number of independent tests carried out (see Tables). Data analyses were generated using SAS/STAT software, version 9.4 .Distribution of missing values was as follows: CSD  to infer a reduced number of latent variables from the 25 psychological resilience items assessed through the CD-RISC [varimax  rotation to our population sample , to compute the final factor scores and assess the relevant loadings of each PR item.A polychoric factor analysis (PFA) was performed through the The analysed sample consisted of 5236 women (50.3%) and 5170 men (49.7%), with a mean age of 52.1 year  and an average PR score of 66.8 .People with higher PR were younger, had lower CSD, prevalently lived in urban areas, and were married. Resilient people were more likely to exhibit healthier behaviours, as reflected by higher levels of physical activity and an increased adherence to a Mediterranean diet. Resilient people had also less prevalence of hypertension, lower BMI, and psychological disease .p for trend = 0.029) compared to the first quartile. This association was still significant after adjustment for baseline health conditions, including history of cancer, diabetes, hypertension, hyperlipidaemia, and psychological status . Inclusion of baseline health behaviours into Model 1 slightly attenuated the association of PR (Q4) with all-cause death risk , and was further reduced when CSD, social factors, and residence were entered into model 1 . Inclusion of all factors into the model yielded an HR of 0.80 . There was no significant association between PR and CVD mortality except in the crude model  (Over a median follow-up of 11.2 years (interquartile ranges 10.2–12.1 year), 478 all-cause and 140 CVD deaths were recorded. Cox regression analysis showed that in the model controlled for age and sex (model 1), subjects in the highest quartile of PR were at 22% lower risk of all-cause death  .p value = 0.01) for each SD increment in Factor 1 ; Factor 2 was related to faith and hope ; Factor 3 was related to secure attachment and secure relationships (items 2 and 13); Factor 4 was related to external locus of control and confidence in one’s abilities ; and Factor 5 was related to strengthening effects of stress and self-efficacy  . In a muFactor 1 .p value = 0.11).The same inverse trend of Factor 1 was observed in association with CVD mortality, although statistical significance was not retained . No other substantial sub-group differences were documented, neither in the analysis of PR nor in the stratified analysis of polychoric factors  was associated with a lower risk of all-cause mortality. Overall, results point to a 20% decreased risk of all-cause mortality associated with higher PR, although multivariable adjustment did not retain formal statistical significance. For CVD death risk, the association with PR followed a similar downward trend, without reaching statistical significance. In line with our research hypothesis, baseline PR levels were slightly able to predict mortality in this cohort of 10,406 adults from a general Italian population of adults.The role of PR as an independent predictor of mortality and diseases has not been extensively investigated so far, and the available prospective studies provided mixed results. In particular, the Swedish military conscription cohort, with numerosity ranging from 237,980  to 1,784The second prospective study comes from a cohort of 2765 black American women of post-menopausal age. Results showed no association between CVD events and PR. PR was measured through a modified version of the Brief Resilience Scale (three items) . The bigAmong these three cohorts, the Chinese one resembles our cohort better because it presents both genders from the general population, although PR was assessed with a modified version of the CD-RISC in an ethnically different group compared to the Moli-Sani cohort. Moreover, in cross-sectional studies, resilient populations were found to have an association with better lipid profiles ,32, bettA peculiar characteristic of our study is that we identified individual domains of PR that were then related to the outcomes. This analysis allowed us to see the patterns of item correlation in our cohort, which is very similar to the one found in the original studied population by Connor and Davidson . Factor To the best of our knowledge, this is the first study that investigated the association between PR and mortality for all-cause and CVD mortality in a general population, and used a broad range of variables as adjustment factors; furthermore, we performed a factor analysis of the different PR items and a subsequent Cox regression with the identified factors. This study has significant strengths, including its prospective design, the relatively long follow-up of over 10 years, and the detailed information on several lifestyle and clinical factors to minimise confounding. PR was assessed through one of the better psychometrically and conceptually performing questionnaires in two systematic reviews ,15.Despite the abovementioned strengths, this study has several limitations. A drawback of observational studies is that causality cannot be inferred and even though analyses in this study were controlled for several factors, we cannot fully rule out the potential of residual confounding by unmeasured factors. All data were collected at baseline only, thus changes which possibly occurred over the course of life might have modified the strength of the findings. The CD-RISC, by account of being a questionnaire, is unable to capture the dynamic nature of PR (like most other assessment tools), and due to the loss of the dynamic aspect, our results may be showing just part of the effect that PR may have on health and illness. Additionally, our study design did not include an assessment of traumatic life events that could have better informed the results of the PR score in our population. It is important to mention that PR was not originally designed to be used in a non-psychiatric setting, although several studies have used it outside of psychiatric populations e.g., ,41,42). ,42. 41,4Our study in a large sample of Italian adults shows that, even though in a marginally non-significant way, PR score is associated with all-cause mortality. This conclusion was supported by the finding that Factor 1 (reflecting positive acceptance of change) was associated with a significant decreased risk of all-cause mortality. In a health-promotion framework, finding an association between PR and hard outcomes with mortality is a compelling task. Our findings would give a reason to dig deeper into what makes people resilient, and to find ways of promoting it. In our cohort, the factor associated with positive acceptance of change was associated with lower all-cause mortality; thus, educating subjects to accept change positively would have been an effective health-promotion intervention in this cohort. However, PR differs across cultures and studying PR without knowledge of the adversities the subjects may have faced can only give a snapshot of the effect of PR on health. Future research should consider the different understandings of PR and the different burdens of adversity that their specific populations may have. Thus, to overcome at least some of the limitations of our study, it would be advisable to assess traumatic life events and repeat a PR measurement many times throughout the follow up.


Coronary artery disease (CAD) is a common chronic condition in the elderly. However, the earlier CAD begins, the stronger its impact on lifestyle and costs of health and social care. The present study analyzes clinical and angiographic features and the outcome of very young patients undergoing coronary angiography due to suspected CAD, including a nested case-control study of ≤40-year-old patients referred for coronary angiography. Patients were divided into two groups: cases with significant angiographic stenosis, and controls with non-significant stenosis. Of the 19,321 coronary angiographies performed in our center in a period of 10 years, 504 (2.6%) were in patients ≤40 years. The most common cardiovascular risk factors for significant CAD were smoking , dyslipidemia , and family history of CAD . The incidence of major adverse cardiovascular events (MACE) at follow-up was significantly higher in the cases compared to controls . Three conventional coronary risk factors were directly related to the early signs of CAD. MACE in the long-term follow-up is associated to dyslipidaemia and hypertriglyceridemia. Focusing efforts for the adequate control of CAD in young patients is a priority given the high socio-medical cost that this disease entails to society. Coronary artery disease (CAD) is a chronic condition usually occurring after the sixth decade of life . HoweverThe prevalence of CAD reported in very young people is 1–16% ,12,13,14The scientific evidence about the risk factors and long-term prognosis that predispose patients towards early CAD is currently scarce . AlthougThis study analyses the relevance of cardiovascular risk factors in very young patients presenting CAD, as well as their possibility of experiencing major adverse cardiovascular events (MACE).This single-center, retrospective, nested case-control study in a cohort of patients ≤40 years old referred for the first time to coronary angiography due to clinical suspicion  of CAD, including ACS or stable angina.n = 251) those with angiographically significant coronary stenosis  or any positive invasive fractional flow reserve test in one or more epicardial vessels. In the left main, stenosis ≥50% was considered a significant disease. The control group (n = 157) was defined as patients with non-significant stenosis (<75%). The detailed inclusion and exclusion criteria were as follows.From 1 January 2006 to 31 December 2015, a total of 19,321 coronary angiograms were performed in our hospital, and 504 (2.6%) were in patients ≤40 years old. Overall, 96 of them were excluded, and 408 (2.1%) patients were ultimately included in the study . We defiCases inclusion criteria: Women and men aged between 18 and 40 years. Referred for coronary angiography due to signs or symptoms suggestive of CAD, or a positive ischemia stress test. Presenting at least one angiographically significant coronary stenosis.Controls inclusion criteria: The same as above, but with absence of significant angiographic coronary stenosis.Cases and controls exclusion criteria: Patients with prior coronary revascularization . Referral for coronary angiography for any other non-ischemic cause .This study restricted the inclusion to a population aged ≤40 since the risk of suffering a coronary ischemic event increases significantly in men from 40 years of age, as reported by the Coronary Artery Risk Development in Young Adults Study (CARDIA) group, which described a difference in prevalence of 13.3% vs. 5.5% among patients aged 40–45 years and 33–39 years, respectively . The study population came from a tertiary hospital, a reference center for cardiovascular disease. The information was obtained through the specific database of the Interventional Cardiology Unit, disaggregated by personal data. The follow-up was conducted by database analysis, which was updated by electronic medical records.The variables were defined as: arterial hypertension , diabetes mellitus (existence of a previous diagnosis or the use of hypoglycemic medication), dyslipidemia (existence prior diagnosis or use of lipid-lowering medication), body mass index (BMI) , smoking (current or former smoker), drug use (active of toxic substances recognized by the patient or by laboratory tests), chronic renal failure , peripheral arterial disease  and prior stroke documented in medical history, family history of coronary artery disease , atrial fibrillation (considered as a history of a previous diagnosis or documented ECG), depression (considered as a history of a previous diagnosis or use of antidepressant medication), and congestive heart failure (considered as a history of a previous diagnosis). The MACE definition included death, myocardial infarction, stroke, and new coronary revascularizations (the appearance of one of these events for the first time in each patient).The investigators participating in this study followed the applicable ethical and legal standards. This study was approved by the Regional Research Ethics Committee with registration code 2015/506.2 test, Student t test, or Mann–Whitney U test, as appropriate. To determine the risk combination contribution, a multivariate model was used using binary logistic regression analysis. The cardiovascular risk factors analyzed are given as odds ratios (OR) together with their 95% confidence intervals. Kaplan–Meier curves and the log-rank test were used to compare the time to the occurrence of a combination of events between the two groups of patients. To identify the factors associated with the combination of events tested, a multivariate Cox regression analysis was performed, calculating the hazard ratio (HR) and 95% confidence intervals. To evaluate recurrent events, the Andersen and Gill model was used. For the data analysis, the SPSS program for Windows, version 19, was used. Likewise, the R program, version 3.6.1, and the survival packages for the Andersen and Gill model and finalfit for the figures were used.Descriptive statistics are reported as mean± standard deviation (SD), median with interquartile range (IQR) for continuous variables, and numbers and percentages for categorical variables. A univariable analysis was performed to detect significant differences between the two groups for the primary variables using the Fisher exact test, χp = 0.011). Male gender predominated in the case group, with higher levels of total cholesterol, low-density lipoproteins (LDL), and lower levels of high-density lipoproteins (HDL) compared to the controls. The most common clinical presentation was ACS, with 232 (92.4%) in the case group and 98 (62.4%) in the control group. Patients with multivessel disease were detected in 66 (26.3%) cases. Angiographic and procedural characteristics are listed in The admission clinical characteristics of the patients are shown in The multivariate logistic regression analysis showed that smoking, dyslipidemia, and a family history of CAD were significantly associated with the appearance of early CAD, and high HDL levels were shown to be a protective factor for early CAD .In the case group, the indication of coronary angiography is the same as that of the final diagnosis at hospital discharge . The mosIn the control group, the most common final diagnosis was non-cardiac chest pain in 57 patients (36.3%), myocardial infarction with no obstructive coronary atherosclerosis (MINOCA) in 32 patients (20.4%), pericarditis in 31 patients (19.7%), myocarditis in 28 patients (17.8%), and others in 9 patients (5.8%). The pharmacological treatment of both groups is shown in The mean follow-up time was 4.98 ± 2.1 years  in the case group. In the control group, the mean follow-up time was 5.34 ± 2.3 year . Clinical follow-up was not completed in 14 subjects (3.4%). A total of 70 events were detected, mainly due to the need for new coronary revascularizations. Additionally, new target lesion revascularization was detected in 13 cases. The case group shows a higher incidence of MACE during the follow-up compared to the control group .The survival function for MACE is displayed in p < 0.001) compared to the control group. The risk factors associated with an increased risk of recurrent MACE are dyslipidemia , hypertriglyceridemia , and diabetes . MINOCA patients displayed four times greater risk for MACE recurrence than subjects in the control group .In order to evaluate recurrent events, the model revealed that the risk for MACE recurrence triples annually in the case group ; however, in young subjects with CAD, a direct association has not been strongly described. Due the pathophysiology of this disease, it likely requires long periods of time to induce organ damage. Other studies have reported mixed results regarding the role of hypertension, diabetes, obesity, and drug abuse as triggering factors of CAD in young patients ,17,22. OThe final diagnosis at hospital discharge is varied in the control group, the most common being non-cardiac chest pain, implying no need for any invasive management. However, it would require lifestyle modifications and, in some cases, pharmacological treatment. A current challenge is to perform a more thorough screening, supported by non-invasive tests for the diagnosis of this condition.The objective of pharmacological treatment is to reduce anginal symptoms as well as preventing adverse events, representing one of the pillars of secondary prevention. Significant differences have been found between the two study groups, since they are different clinical diagnoses after coronary angiography. An effort must be made by all health professionals to achieve adequate therapeutic adherence, especially in this young population conditioned by low risk appreciation . The eviDuring a mean follow-up time of >5 years, more repeated events were detected for new coronary revascularizations, similar to in other studies . The morIn our study, non-conventional risk factors for CAD, such as hypertriglyceridemia and left ventricular function, became relevant at follow-up. Patients with high triglyceride levels showed an increased incidence of MACE at follow-up. These data were consistent with our recurrent events model, except for diabetes, which acquires statistical significance for high MACE incidence at follow-up. Focusing efforts on these risk factors could help to achieve a more effective secondary prevention.MINOCA patients had a similar pattern of pharmacological treatment at hospital discharge to the rest of the patients in the control group, in line with other reports ,17. HoweThis study has several limitations. First, the presence of non-traditional cardiovascular risk factors, such as lipoprotein A, hyperhomocysteinemia, and familial hypercholesterolemia, was not analyzed. It is likely that the relationship of prothrombotic diseases with the early appearance of ischemic heart disease could not be assessed due to the lack of data in most patients. Second, due to the nature of our study, selection biases cannot be ruled out. Nonetheless, our study includes a consecutive cohort with the largest sample sizes reported in the literature in this group of patients. In our study, current smokers, dyslipidemia, and familial history of CAD were found to be significantly associated with the existence of severe CAD in patients of ≤40 years. The presence of dyslipidemia and hypertriglyceridemia increases the risk of MACE at long-term follow-up. Focusing efforts on primary prevention and optimal control of these factor is necessary. A detailed genetic analysis of high-risk populations with a family history of CAD must be considered.


A quasi-experimental study was performed on 53 respondents with two sessions of stretching movements and BG + TfH movements of 5 min duration, three times a week for four weeks. Fatigue was measured using a reaction timer and MSCs were measured using a Nordic Body Map questionnaire. Wilcoxon and Mann–Whitney U tests were performed to examine the differences of pre/post and between the intervention group (IG) and control group (CG). A significant difference was found in IG for pre- and post-fatigue (p < 0.001) and MSCs (p < 0.001), while in CG there was no difference in fatigue (p = 0.200) and MSCs (p = 0.086). Significant differences were found between the IG and CG groups in terms of fatigue (p = 0.046), as well as in MSCs (p < 0.001). A significant decrease in MSCs per part body in IG was found on the left wrist, left hand, and left knee. The percentage of MSC severity decreased in all parts of the body, except the right shoulder, left elbow, and right thigh.The purpose of this study was to assess the effect of using a combination of stretching and Brain Gym The garment industry is a labor-intensive industry ,2, formiThe most prevalent garment-sewing operator musculoskeletal complaints involve muscles of the neck, shoulders, arms, elbows, wrists , hands, In a previous study, it was reported that physical exercise can control the risk factors of fatigue ,29 and MBrain Gym (BG) is a simple stretching motion to lengthen muscles in order to maintain balanced mind–body coordination . It is aTouch for Health (TfH) is generally used as a therapy, but also can be performed in stretching movements. Brain Gym and TfH are new methods used in physical stretching to lengthen and strengthen muscles. The selection of BG and TfH is based on their simplicity and ease of movement, as well as the lack of requirements for extra time and energy. These movements were chosen to minimize the risk factors for pain in the garment-sewing operator, from the neck muscles to the feet. The eight TfH movements shown to garment-sewing operators can help overcome problems around the shoulder muscles and strengthen the arm and brain muscles (supraspinatus muscle); flex the spine from the thoracic vertebrae to the lumbar (teres major muscle); support respiratory and lung function; strengthen the scapula (serratus anterior muscle); strengthen the heart and arms (subscapular muscle); optimize kidney function and maintain the lumbar curvature of the spine (psoas muscle); make it easier to move the arm inward, rotate the arm, and move it forward ; optimize pancreatic spleen function; maintain an erect back (latissimus dorsi) and bladder; and stretch the ankle muscles (peroneus muscle) .Garment-sewing operators work 8 h per day with a break time of 1 h, after sewing continuously for 4 h, which causes muscle tension. Activities that require long periods of physical work require rest to recover energy. Pulat  explaineSeveral studies on stretching to reduce fatigue and MSDs have been carried out on workers in sitting positions, such as workers in call centers , office This study used a quasi-experimental design with the intervention group (IG) and the control group (CG). The garment industry was used in this study: the garment industry was willing to permit visits and accept direct interaction with respondents during the COVID-19 pandemic. A total of 53 garment-sewing operators were studied, from the garment industry in Karanganyar Regency, Central Java Province, Indonesia.The garment-sewing operators who participated in this study were female, not pregnant, did not smoke, had not experienced trauma to the bones and muscles, did not take anti-depressant drugs, and used the same machine and sewing materials. Fifty-three garment sewing operators were selected and given an informed consent sheet. Their willingness to be a respondent was assessed, and their personal data were provided as follows: age, years of service, body mass index, blood pressure, and pulse. The operators participated voluntarily. The division of the garment-sewing operator group was carried out by distributing lottery papers assigning respondents to the IG and CG. This resulted in the following group sizes: IG = 27 and CG = 26. The researchers conducting the intervention did not know who was included in the IG or CG.The interventions lasted 5 min for each session (two-session), and took place three times a week for 4 weeks. In the first session, a stretching movement was carried out 2 h after working, before the break time. This consisted of 11 light stretches used to stretch stiff muscles with a count of 2 × 8 . The secThe intervention was performed three times a week for four weeks. The intervention group was guided by a video and was directly monitored by the researcher to maintain the accuracy of the movement. During the intervention period, the IG conducted an intervention program, while the CG continued to work on sewing. The intervention program was divided into stretching and BG + TfH movements, designed and combined by the researcher. The movements were structured and adapted according the garment-sewing operators’ work, to reduce muscle tension from the neck muscles to the feet.The stretching movements focused on stretching the neck, shoulders, upper back, chest, hips, arms, forearm, hands, wrists, fingers, groin, hamstring, lower leg, leg joint, lower limb, and ankle . Every mThe four BG movements were owl movement, horse tide movement, arm activation movement, and gravity glider movement . The eigThe Brain Gym was designed with four movements, consisting of owl movement, arm activation movement, grounder movement, and gravity glider movement. The owl movement consists of grasping the top of one shoulder with the opposite hand and squeezing the muscles firmly. Slowly, the head is turned to look back over the shoulder. Draw the shoulders back, open the chest, and exhale for a count of eight. Continue to squeeze the shoulder as the head is turned to look over the other shoulder, “hooting” as the chest is opened again. “Hoot” again and drop the head toward the chest, keeping the chin tucked in and relaxing the shoulder down and back. The arm activation movement consists of standing with feet parallel and shoulder-width apart. Raise one arm above the head, using the opposite hand to hold it next to the ear. Exhale gently through pursed lips, while activating the muscles isometrically by pushing the raised arm against the other hand. The grounder movement consists of standing with the feet a leg length apart, and hands on the hips. Then, turn the head and right foot to the right, keeping the left foot pointed straight ahead. The torso and pelvis face squarely forward; the head, the bending knee, and the foot of the bent leg face to the side. Bend the right knee and slowly exhale, allowing the knee to extend to the middle of the right foot. Inhale and straighten that leg, then return to an upright position. The gravity glider movement consists of sitting up comfortably on the edge of a sturdy chair and extending the feet, resting on the floor. Keeping the knees relaxed, bend forward and reach out to the front, letting the head move freely. Then, let gravity take over and the arms glide down, and exhale. Inhale upon moving back up.Touch for Health consists of the following: Supraspinatus muscle movements, where both arms move towards the center in a V shape. Teres major muscles movements, with hands on hips and elbows slowly flapping like a chicken, while the shoulders remain steady. Serratus anterior muscle movements consist of the hand positioned straight upward while the thumb moves over the shoulder. Move slowly while taking a deep breath, and then lower the arm while exhaling. Subscapular muscle movements begin with the right and left upper arms in line with the shoulders, with the right forearm above and the left forearm below. Then, slowly swing the arms up and down. In the psoas muscle movements, the hips are steady and the soles of the feet are tilted outward. Legs swing 45° forward, sideways, and then closed. Repeat in a waltz, (count 1-2-3) forward, sideways, close, and forward again. Perform this twice, while alternating the left and right leg. The pectoralis major sternalis muscle movements are performed slowly, like swimming, but the hands are lifted up and out, while saying, “Hore”. The latissimus dorsi movement begins with palms facing outward. Lift the hand outward slowly, like a penguin’s wing. The peroneus muscle movement is similar to kicking a ball, with the sole of the foot moving slowly inward.Fatigue was measured using a reaction timer machine  with an accuracy of ±0.0014 s (k = 2). The garment-sewing operators pressed the mouse button while watching the signal light flash as quickly as possible, using the dominant index finger to avoid arm and elbow motion changes. The signal light was switched on with a varied tempo given by the enumerator. The signal light was shown 20 times to the garment sewing operator, and the results were recorded directly by the enumerator. The examination results in numbers 1–5 and 16–20 were omitted, because they were considered to be within the emerging adjustment and saturation levels. Reaction timer evaluation was used to determine changes in fatigue in garment-sewing operators by comparing the measurement results before and after the intervention.The level of MSCs was assessed by the Nordic Body Map (NBM) questionnaire . The Norp-value was p < 0.05, and a significant difference was seen between the pre- and post-results in each group. The Mann–Whitney U test determined the difference in fatigue results and MSDs between the intervention and control groups. A p-value of <0.05 indicates a difference between the IG and CG.The results of the fatigue evaluation and MSCs were compiled into ratio data. The IBM SPSS Statistics 22  program was used for the statistical evaluation and the measured values of all variables were calculated as the mean, median, min, max, interquartile range (IR), and standard deviation (SD). The variables showed there was not a normal distribution based on the Shapiro-Wilk tests, and the Levene test was applied for homogeneity variances. The differences in the results of pre- and post-fatigue and MSDs were tested using the Wilcoxon test. The Garment-sewing operators were given an approval sheet to ascertain whether they were willing to be a respondent or not, because this research was voluntary. This research was approved by the Health Research Ethics Committee of Sebelas Maret University with the identity number 177/UN27.06.6.1/KEPK/EC/2020.p > 0.05).The 53 garment-sewing operators recruited in this study met the established criteria. Random sampling was used to divide the intervention (IG: 27) and control (CG: 26) groups. The characteristics of the respondents are presented in p < 0.001), and there was a decrease in the mean between pre- and post-values. In contrast, there was no difference in the CG (p = 0.200); an increase was seen between the pre- and post-scores. The intervention and control groups showed significant differences (p = 0.046).The results obtained after the evaluation of the fatigue pre- and post-measurements are shown in p < 0.001), whereas CG without intervention showed an increase, and there was no difference (p = 0.106). The evaluation results of the comparison between IG and CG showed a significant difference (p < 0.001)  .p = 0.008), left hand (p = 0.046), and left knee (p = 0.035), and was constant on the right shoulder (p = 1.000), right lower arm (p = 1.000), and left elbow (p = 1.000). A significant increase in the CG was seen on the bottom (p = 0.032), left elbow (p = 0.011), right elbow (p = 0.021), left upper arm (p = 0.032), right upper arm (p = 0.005), and left ankle (p = 0.013), and was constant on the left shoulder (p = 0.971), right shoulder (p = 1.000), waist (p = 0.976), and left wrist (p = 0.184).Musculoskeletal complaints per body part (pre-post) are shown in There was severity in the upper extremity between the IG and CG (pre-post) are shown in Similar to the upper extremity, a decreased percentage of truncus MSCs severity in the IG extremes was seen in the bottom (−7.5%), buttock (−7.4%), and back (−6.1%). The control group had the highest increase (+12.9%), a decrease in the back and buttock (−2.5%), and constant values in the waist .The comparison of severity in the lower extremity between the IG and CG (pre–post) in The garment-sewing operator’s work week covers 45 h (8 h a day on weekdays and 5 h on Saturday), with a break time of an hour. They work constantly for hours without a coffee break due to the daily production target, which requires that they remain focused. It is difficult for them to take additional break times during working hours.This study assessed the effect of applying a combination of stretching and BG + TfH movements for 5-min sessions for 4 weeks, and found that the results significantly reduced fatigue. A previous study also demonstrated that appropriately designed and supervised 10 min daily stretching programs for 2 months during the work shift are more effective than rest breaks at reducing both musculoskeletal discomfort and physical and mental fatigue in call-center workers . This stA significant reduction in MSCs was seen in the group who received the intervention program. The body parts that experienced a significant decrease were the left wrist, left hand, and left knee. This study shows that sewing work uses dynamic movements that are more dominant in the right muscles from the upper extremities  to the lThe percentage reductions in MSC severity occurred in the left wrist, right and left hand, right wrist, right ankle, right knee, right calf, and right foot. The increasing and constant results in certain muscles are due to their being dominant muscles used in working, such as the left elbow holding the fabric position, the right thigh keeping and adjusting the pedal speed to synchronize it with the hand positioning the fabric, and the right upper arm, which works more dominantly ,19,20. TThe duration and frequency of program interventions from the study of Marangoni et al. , with stMost other studies were carried out over a longer duration ,29,30,39Most studies were interested in strengthening or resistance exercises, including the study of Santos et al.  and AndeThis study has several limitations. First, the small sample size of 53 subjects was the result of difficulties in finding respondents during the COVID-19 pandemic period. Therefore, the results are difficult to generalize and interpret. Second, the length of the intervention period was only 4 weeks; a longer intervention study is needed to confirm the findings and long-term effects. Third, the difficulty of finding time for the intervention and data collection due to the high production targets must be resolved.In conclusion, by comparing the two groups, it was found that the combination of stretching and BG + TfH movements can reduce fatigue and musculoskeletal complaints. Decreased MSCs per body part were found on the left wrist, left hand, and left knee. The percentage of MSCs’ severity decreased in the upper extremities (except for right shoulder and left elbow which were constant), truncus, and lower extremities (except for the increased right thigh).There have been no other studies to date on the provision of stretching and BG + TfH movement interventions for garment-sewing operators. Performing easy and light movements for 5 min twice a day can be beneficial for sewing operators, who work constantly for hours without a coffee break due to their daily production targets, which require them to remain focused. This study is considered a guide for future interventions with the same objective, with a larger sample and longer intervention time.


The effects of extreme temperature on infectious diseases are complex and far-reaching. There are few studies to access the relationship of pulmonary tuberculosis (PTB) with extreme temperature. The study aimed to identify whether there was association between extreme temperature and the reported morbidity of PTB in Shandong Province, China, from 2005 to 2016.A generalized additive model (GAM) was firstly conducted to evaluate the relationship between daily reported incidence rate of PTB and extreme temperature events in the prefecture-level cities. Then, the effect estimates were pooled using meta-analysis at the provincial level. The fixed-effect model or random-effect model was selected based on the result of heterogeneity test.Among the 446,016 PTB reported cases, the majority of reported cases occurred in spring. The higher reported incidence rate areas were located in Liaocheng, Taian, Linyi and Heze. Extreme low temperature had an impact on the reported incidence of PTB in only one prefecture-level city, i.e., Binzhou . While, extreme high temperature was found to have a positive effect on reported morbidity of PTB in Binzhou  and Weihai . Meta-analysis showed that extreme high temperature was associated with a decreased risk of PTB . However, extreme low temperature was no relationship with the reported incidence of PTB.Our findings are suggested that extreme high temperature has significantly decreased the risk of PTB at the provincial levels. The findings have implications for developing strategies to response to climate change.The online version contains supplementary material available at 10.1186/s12879-021-06116-5. Vibrio bacteria [Global climate change is one of the biggest challenges which the world is facing, and the problem is the focus of the global community . It is wbacteria . Accordibacteria , 5, disebacteria , 7 and rbacteria , 9. And bacteria , hand-fobacteria , etc.Pulmonary tuberculosis (PTB), as an infectious disease, threatens human health. Tuberculosis is the leading cause of death due to a single source of infection and one of the world’s top 10 causes of death . GloballThis study aimed to quantify the impact of extreme temperature on PTB in Shandong Province of China, from 2005 to 2016. The results may assist with improving awareness of the impact of extreme temperatures on PTB and could help to developing strategies to fight extreme temperature and climatic change.2 and a permanent resident population of 100.7 million, was selected as the study area. As of 2020, a total of 16 prefecture-level cities , 57 municipal districts, 27 county-level cities, 53 counties and 137 county-level administrative regions in Shandong Province. In 2018, the prefecture-level city of Laiwu was abolished and incorporated into Jinan. Therefore, Laiwu was still studied as a prefecture-level city because the study period was from 2005 to 2016. In Shandong Province, there are differences quality of basic public services in different prefecture-level cities. The three cities with high quality of basic public service are Qingdao, Dongying and Jinan, while the three cities with poor quality of basic public service are Linyi, Liaocheng and Heze [Shandong Province (longitude 114°47.5′-122°42.3′E and latitude 34°22.9′-38°24.01′N), which is located in the lower reaches of Yellow River with Bohai Sea and Yellow Sea in the East with an area of approximate 155,800 kmData of PTB during 2005–2016 in Shandong Province were derived from the China Information System for Disease Control and Prevention. All reported PTB cases were defined based on the diagnostic criteria and principles of management for PTB (WS 288–2008) issued by Ministry of Health of the People’s Republic of China. In China, PTB is a statutory notifiable category B infectious disease. Therefore, physicians in hospitals must report every case of PTB on line within 24 h after the diagnosis. Therefore, we believe that the degree of compliance in disease notification was consistent during the study period.http://data.cma.cn). The variables for our analysis included daily average surface temperature (AST), daily average temperature (AT), daily minimum temperature (DMIT), daily maximum temperature (DMAT), daily average air pressure (AAP), daily minimum air pressure (DMIP), daily maximum air pressure (DMAP), daily average relative humidity (ARH), daily minimum relative humidity (MRH), sunshine duration (SD), daily average wind speed (AWS), daily maximum wind speed (MWS) and daily precipitation (PRE). Demographic data of Shandong Province were downloaded from the Center for Public Health Science Data in China (http://www.phsciencedata.cn/). Economic data and medical expenditure data were collected from Shandong Statistical Yearbooks 2006–2017.Meteorological data from 2004 to 2016 were obtained from the China Meteorological Data Service Center  and meta-analysis was adopted to carry out the risk assessment on PTB caused by extreme temperature events.Firstly, temporal and spatial distributions, which reported morbidity of PTB of 17 prefecture-level cities in Shandong Province from 2005 to 2016, were described. The thematic map of the average annual reported incidence rate of PTB was produced by the ArcGIS 10.4 software. The average annual reported incidence rate was graded by Natural Break (Jenks), which was divided into 4 levels. The Natural Break (Jenks) can identify break points by picking the class breaks that best group similar values and maximize the differences between classes [r > 0.7, one of the two variables was retained by consulting the literature and considered in the GAMs [Secondly, multi-collinearity might lead to multi-collinearity bias in the results, therefore, Spearman correlation coefficients were calculated between the meteorological variables to avoid the effects of multi-collinearity in meteorological variables. If the absolute value of the GAMs . Subsequthe GAMs , so the the GAMs , which wThe GAM is an extension of generalized linear model, which has a wider scope of application, and it handles the complex nonlinear relationship between dependent and independent variables through the form of functions, so that it has great flexibility . GAMs wiYt was the daily number of reported PTB cases in time t. The Log (population) was used in order for the model suitable for reported incidence rate data. Extreme temperature was defined as a categorical variable, with 0, 1 and 2 representing normal temperature, extreme low temperature and extreme high temperature, respectively. Season included spring, summer, autumn and winter, with summer as the reference season. s  was applied for adjust the impact of potential meteorological variables confounding. s (time), s  and s (GDP) were used to control long-term effect, annual medical expenses per capita, GDP per capita. Then, relative risk (RR) and 95% confidence interval (CI) of PTB due to the exposure to extreme temperature were calculate in each model.where Q statistic and I2 value.Finally, extreme temperature effect value of 14 prefecture-level cities obtained by GAMs were summarized through meta-analysis to obtain the final effect value of extreme temperature on the reported morbidity of PTB. The fixed-effect model or random-effect model was selected based on the result of heterogeneity test. Heterogeneity test was assessed using Cochran’s p value less than 0.05.Statistical analyses mentioned above were implemented with the use of R , SPSS 22.0  and Stata 16.0 . GAMs in our analysis were performed using R with the “mgcv” package. Statistical significance was defined as the statistical tests were two-sided, and During the study period, a total of 446,016 PTB cases were notified in Shandong Province. Figure r| > 0.7). Therefore, above meteorological variables were not used in the next GAMs due to multi-collinearity. Strong correlations were detected between ARH and MRH, between AWS and MWS, with the absolute value of r lager than 0.7. The effects of AWS and ARH on PTB had already been demonstrated in previous studies [Figure  studies , 22, so The lag time of each meteorological factor was determined according to the maximum effective CCF. The obtained results of cross-correlation analysis between daily reported incidence rate of PTB and meteorological variables are summarized in Table RRs of extreme temperature on the risk of PTB in each GAM and pooled results are presented in Figs. To our knowledge, this was the first multi-city study to examine the association between extreme temperature events and PTB using a mixed method in Shandong Province. The pooled results confirm that exposure of extreme high temperature was positively associated with decreased risk of daily reported incidence rate of PTB, and no association was found between extreme low temperature and reported morbidity of PTB. Therefore, it is important to equip policymakers with information on the effect of extreme temperature events on PTB to help guide the provision, planning and optimization of PTB control strategies in Shandong Province.The study has confirmed that the reported morbidity of PTB presents seasonal trend, with a peak during the spring of every year (from March to May). Similar seasonal trends of PTB has been reported elsewhere , 24. HowIn our study, the lagged effects of temperature on the reported morbidity of PTB in different prefecture-level cities are different. Some studies have evaluated that there is a potential lagged effect of the temperature on PTB , 28, 29.Mycobacterium tuberculosis of air driven by increasing ultraviolet radiation. Secondly, higher temperature may change human habits and behaviors [Mycobacterium tuberculosis, but also increase the possibility of PTB transmission in winter [We adopted a mixed method-GAM and meta-analysis, which can estimate the relationship between extreme temperature events and PTB at city and provincial levels. In this study, we found that extreme high temperature was associated with a significant decrease in the risk of PTB at provincial level, although only two prefecture-level cities had found an effect of extreme high temperature on PTB. Epidemiological study has demonstrated that extreme temperature could affect the risk of mortality , 32, acuehaviors . Under en winter . Furthern winter , howevern winter . In turnn winter , Zhang en winter  and Tiann winter . In addin winter , which mSome limitations of our study should be acknowledged. Firstly, due to deficiency of meteorological data, three prefecture-level cities of Shandong Province were not included in our study. Secondly, the reported PTB data were from the China Information System for Disease Control and Prevention, and under-reporting bias is inevitable. Thirdly, some confounders like pathogen mutation, individual behaviors, and immune levels have not been considered to control. Hence, further more studies are required to demonstrate the possible associations between extreme temperature and PTB.The results of our study provide evidence that extreme high temperature decrease the risk of reported morbidity of PTB. This study supplied helpful cognition for targeted PTB control and prevention associated with extreme temperature in Shandong Province. Meanwhile, our findings provide more evidence that it is necessary to consider the effect of extreme temperature on human health, and develop strategies to response to climate change.Additional file 1: Figure S1. Sensitivity analysis of the overall pooled extreme high temperature study. Figure S2. Sensitivity analysis of the overall pooled extreme low temperature study.


The prognosis of obstructive colorectal cancer (oCRC) is worse than that of nonobstructive colorectal cancer. However, no previous study has established an individualized prediction model for the prognosis of patients with oCRC. We aimed to screen the factors that affect the prognosis of oCRC and to use these findings to establish a nomogram model that predicts the individual prognosis of patients with oCRC.This retrospective study collected data of 181 patients with oCRC from three medical hospitals between February 2012 and December 2017. Among them, 129 patients from one hospital were used as the training cohort. Univariate and multivariate analyses were used in this training cohort to select independent risk factors that affect the prognosis of oCRC, and a nomogram model was established. The other 52 patients from two additional hospitals were used as the validation cohort to verify the model.p = 0.037, hazard ratio [HR] = 2.872 [1.065–7.740]), N stage , and surgical procedures  were independent prognostic factors of overall survival in patients with oCRC. These factors were used to construct the nomogram model, which showed good concordance and accuracy.Multivariate analysis showed that carcinoembryonic antigen level (Carcinoembryonic antigen, N stage, and surgical method are independent prognostic factors for overall survival in patients with oCRC, and the nomogram model can visually display these results. Colorectal cancer (CRC) is one of the main cancers leading to cancer-related deaths worldwide , 2. InteIn tumor prognosis research, nomogram models employing regression analysis are frequently used. These models are based on multivariate analysis and integrate the results of logistic or Cox regression to a great extent to predict the probability of a certain clinical event in patients along with intuitive graphical presentations. An increasing amount of literature has reported the advantages of these models in predicting tumor recurrence and metastasis, death, and other prognostic outcomes , 9. In cIn this study, we developed a nomogram model based on prognostic factors of patients with oCRC to predict the individual survival rate of these patients.Data of 240 patients with oCRC between 2012 and 2017 were retrospectively collected. The inclusion criteria were as follows: primary CRC confirmed by histology, presence of obstruction, and the availability of complete clinicopathological data. Exclusion criteria were (a) recurrent or multiple primary CRCs, (b) other malignant tumors, (c) inability to undergo surgery due to late staging or poor cardiopulmonary function, and (d) inadequate data. A total of 181 cases were eventually included and analyzed in this study , obstruction site, obstruction type, surgery, TNM staging, histological type at diagnosis, white blood cell count (WBC), neutrophil count percentage (NCP), platelet count, and the levels of albumin, carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), as well as sodium, potassium, calcium, and chloride ions. Cancer staging was based on the 8th edition of the American Joint Committee on Cancer (AJCC)/TNM system.Follow-up assessments of patients were scheduled every 3 months for the first 2 years, every 6 months for the next 3 years, and once a year thereafter. The follow-up assessments included chest and abdominal computed tomography, tumor marker measurements, and endoscopy every 6 months. The last follow-up assessment for the training cohort was performed in May 2017, and the last follow-up assessment for the validation cohort was performed in May 2018. Overall survival (OS) was calculated for the period from the date of treatment initiation to death from any cause. Patients who were lost to follow-up during follow-up or who did not die during the last follow-up were defined as censored.SPSS 21.0 was used for statistical analysis. Categorical variables were expressed in percentages (%) and grouped according to clinical regulations. Chi-square and Wilcoxon rank-sum tests were performed to analyze differences between the training cohort and the validation cohort.p < 0.05 in the univariate analysis. If a significant effect was observed in the Cox model, independent prognostic factors were determined (p < 0.05). The variables of the final model were selected by step-by-step backward regression using the Akaike information criterion.Univariate and multivariate Cox proportional hazards models were used to determine potentially important prognostic factors for the entire cohort. The survival curves were plotted using the Kaplan-Meier method, and the log-rank test was used to compare curves. Multivariate Cox regression analysis was performed on the variables that reached the significance level of http://www.r-project.org/), the nomogram model was constructed. Both internal and external verifications were performed for the nomogram, and the discrimination and calibration of the model were evaluated. The evaluation of discrimination in this article was based on the index of concordance (C-index), i.e., the same number of samples were repeatedly extracted from a given database and then put back, and the internal evaluation of the resolution of the nomogram model was performed in the new sample generated. A C-index of 0.5 indicated that the model had no predictive effect. A C-index of l indicated that the predicted results of the model were completely concordant with the actual results. The closer the C-index was to 1, the better the predicted results of the model. Evaluation of the degree of calibration was based on the calibration plot method, which involved a comparison between the event incidence predicted by the nomogram model and the true incidence. The model aimed to predict the risk value of an event for each patient, arrange these values from low to high, segment the queue, calculate the average predicted risk value  in each segment and the corresponding true risk value (y-axis), obtain the calibration point in each segment, and connect the calibration points of each segment to draw the predicted calibration curve. The better the fit between the predicted calibration curve and the standard curve, the better the conformity of the prediction model. The nomogram matches each variable to the corresponding score, and the sum of the scores of all variables is defined as the total score. By drawing a vertical line from the axis of the total score, the estimated survival probability can be obtained, and the principle for predicting the survival probability is based on regression analysis. p < 0.05 was considered statistically significant.According to the final Cox proportional hazard regression model and by using the rms package in R version 3.4.2 (p = 0.009), M stage (p = 0.004), and TNM stage (p = 0.002) were significantly different between the training and validation cohorts, which might be attributed to the patients’ hospital preferences. In the training cohort, more than half of the patients were men . Most of the patients in the two groups were older adults . Radical resection accounted for 2/3 of the cases , the most common site of obstruction was the right colon , and most patients had chronic incomplete obstruction . In the validation cohort, 16 patients died, with a median follow-up time of 19 months . The 1-year and 3-year OS of the training cohort was 85.0% and 63.5% of that of the validation cohort, respectively, and the OS of the validation cohort was 85.4% and 68.1%, respectively.p = 0.036), CEA (p = 0.003), CA19-9 (p = 0.02), N stage (p < 0.001), M stage (p = 0.001), TNM stage (p < 0.001), and surgical procedures (p < 0.001) were significantly associated with a shorter OS in patients with oCRC , N stage , and surgical procedures  were shown to be important independent prognostic factors for OS (multivariate Cox ratio) in the univariate risk analysis  guidelines show that intestinal obstruction is one of the high-risk factors for recurrence . ColonicTumor biomarkers have been widely used in the diagnosis and post-treatment follow-up of patients with CRC . The latThe AJCC/TNM staging system remains the basic tool for evaluating the prognosis of patients with CRC. In our study, we analyzed the patients according to the TNM staging system. We could clearly demonstrate that lymph node positivity (N stage) was an independent predictor for worse OS. Enciu et al. reported that patients with oCRC showed a greater incidence of lymph node metastasis . PatientFor patients with oCRC, surgical resection which includes radical resection and palliative resection is a beneficial treatment option . Many eaAs a prognostic statistical model, a nomogram can not only visually display the relevant indicators that affect the outcome in multifactor regression analyses but also predict the survival probability through a simple graphical representation, making the prediction simpler and more convenient , 40. TheThis study established and verified a nomogram model that can predict the prognosis of patients with oCRC. The nomogram model, which combines CEA expression, N stage, and surgical procedures, was verified internally and externally as a useful tool for risk assessment. Among these three key parameters, only the operation procedure can be controlled by the surgeon. To prolong the survival of patients with oCRC, efforts should be made to change the surgical method from non-radical resection to radical treatment.


T cell immunoglobulin and ITIM domain (TIGIT) is a recently identified immunosuppressive receptor. The expression levels of TIGIT affect the prognosis of patients with solid tumors. To fully comprehend the role of TIGIT on the prognosis of patients with solid tumors, we conducted a meta-analysis.  We performed an online search of PubMed, Embase, Web of Science (WOS), and MEDLINE databases for literature published till March 31, 2021. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the literature, and Stata 16.0 and Engauge Digitizer 4.1 software were used for data analysis. P < 0.001} and progression-free survival (PFS) . We performed subgroup analysis to explore the source of heterogeneity, colorectal cancer , lung cancer , esophageal cancer , and other cancers . In addition to cancer type, expression location, sample size, and different statistical analysis methods are also considered the possible causes of heterogeneity between studies. Funnel plots suggested no publication bias for OS (P = 0.902), and Egger's test supported this conclusion (P = 0.537).  Our literature search identified eight papers comprising 1426 patients with solid tumors. Increased expression of TIGIT was associated with poor prognosis. High expression of TIGIT was a risk factor for overall survival (OS) {hazard ratio (HR) = 1.66, 95% confidence interval (CI) ,  TIGIT expression was associated with OS and PFS in patients with solid tumors. Patients with elevated TIGIT expression have a shorter OS and PFS, and TIGIT expression could be a novel biomarker for prognosis prediction and a valuable therapeutic target for solid tumors. The global burden of cancer morbidity and mortality is rapidly increasing. By 2020, there are estimated to be 19.29 million new cancer cases and 9.96 million deaths worldwide. It is expected that by 2040, the global burden of cancer will reach 28.4 million cases, an increase of 47% compared with that in 2020 , The immune checkpoint is one of the main causes of immune tolerance. Immunotherapy targeting the classical immune checkpoints of PD-1/PD-L1 and CTLA-4/B7.1/2 has brought hope to patients with tumors. However, in actual clinical applications, only a part of the dominant population has an immune response, and PD-1/PD-L1 immune checkpoint inhibitors are prone to drug resistance and severe adverse effects , 27. TheTIGIT affects the prognosis of cancer patients by inhibiting the function of immune cells through a variety of mechanisms . These aWe showed an association between TIGIT expression and the prognosis of patients with solid tumors, but the prognostic effects of TIGIT on different tumors were inconsistent, which may be due to different characteristics and different expression sites of different tumors. Significant heterogeneity was observed in the two CRC studies, which could be explained by study's methodological design and confounders of clinical covariates. PFS, DFS, and RFS can all predict and reflect clinical benefits, but there are few relevant studies reported at present, and it is impossible to measure the combined HR. Many studies are needed to evaluate the prognostic value of TIGIT.Although we tried our best to conduct a comprehensive analysis, our meta-analysis has certain limitations. Despite the use of subgroup and sensitivity analyses, the origin of the heterogeneity could not be completely traced. Second, all the studies were retrospective, with all subjects being Asian, which does not represent the whole population. Third, the scale of the included studies was small. Some studies include only one kind of cancer, and studies with a larger sample size are required to fully understand the connection between TIGIT and the survival index. Third, although IHC was used in all the studies, the antibodies used were no identical, and the thresholds were not consistent. We should further explore the establishment of a unified threshold. Fourth, the number of studies included in this article was very limited. When the number of included articles is less than 10, the efficiency of Begg's test and Egger's test detection tend to reduce, and as this study included English language articles, publication bias cannot be ruled out. We hope that this meta-analysis not only represents the end point of the study but also begins to pay attention to the value of TIGIT in solid tumors and to look forward to more high-quality studies.Taken together, our findings indicate a significantly increased risk of OS and PFS associated with elevated TIGIT expression. TIGIT appears to be a promising therapeutic target for solid tumors as well as a prognostic predictor, which deserves the attention of researchers and clinicians. Due to the limitations of the number and quality of the included literature, our results need to be interpreted carefully. Further studies are necessary to evaluate the molecular mechanism of TIGIT in patients with solid tumors.


It is well known that diabetes mellitus (DM) affects health-related quality of life (HRQOL) in both younger (aged 18–64 years) and older adults (aged ≥ 65 years). However, to date, no study has compared HRQOL and its predictors between younger and older adults with DM in Indonesia. Such a comparison is important because the results can guide nurses and clinicians to establish evidence-based educational programs that are specific and suitable for patients. Therefore, the aim of this study was to investigate the difference in HRQOL and its predictors in younger and older adults with DM in Indonesia.A cross-sectional study was conducted on 641 patients with type 2 diabetes mellitus (T2DM) who were recruited via simple random sampling from 16 primary health centers in Banyumas Regency, Indonesia. A self-administered questionnaire containing the Summary of Diabetes Self-Care Activities, the DDS17 Bahasa Indonesia, the Beck Depression Inventory II, the Self-Efficacy for Diabetes Scale, the Family APGAR, and the 36-item Short-Form Health Survey was used to measure diabetes self-management (DSM), diabetes distress (DD), depression, self-efficacy, family support, and HRQOL, respectively. Independent t-tests were used to compare the physical component summary (PCS) and mental component summary (MCS) scores between younger and older adults with T2DM. Hierarchical multiple regression analyses were used to examine the factors associated with HRQOL in both groups.PCS scores were significantly different between the two groups. Older adults reported lower PCS scores than younger adults. No differences between the two groups were observed in the MCS scores. The hierarchical multiple regression analysis showed that level of education, employment status, number of diabetes-related complications, DSM, DD, depression, and self-efficacy were significant predictors of HRQOL in younger adults, while income, depression, DD, and self-efficacy were significant predictors of HRQOL in older adults. DD was the strongest predictor of HRQOL in younger adults, and depression was the strongest predictor in older adults.Older adult patients had lower PCS scores than younger adult patients. This study is the first to show that the predictors of HRQOL differ between younger and older adults with T2DM. It provides insights for nurses and clinicians in Indonesia to establish evidence-based, age-specific educational programs. The number of patients with diabetes mellitus (DM) is increasing at an alarming rate. Global cases increased by 211 million between 2000 and 2013 .The number of patients with DM is also increasing in Indonesia. Indonesia has the seventh largest number of patients with DM in the world , with neDM has a significantly negative impact on health-related quality of life (HRQOL) in patients, either directly or because of its complications , 9. AddiAmong demographic variables, age is the most commonly reported predictor of HRQOL. In general, older adults have a worse HRQOL compared with younger adults ; howeverThe variables that have been demonstrated to affect HRQOL in patients with DM are diabetes self-management (DSM), diabetes distress (DD), depression, self-efficacy, and family support , 14–17. A cross-sectional study was conducted on patients with T2DM who were recruited via simple random sampling from 16 primary health centers in Banyumas Regency, Indonesia. The sample size was calculated using a 95% confidence level, prevalence of 13.4%, and absolute precision of 3%. Considering the response rate of 77.4% based on our previous study (unpublished), the total sample size calculated was 641 patients. The inclusion criteria were patients aged 18 or over who had been diagnosed with T2DM by their physician and were willing to sign the informed consent form. The exclusion criteria were patients with physical disabilities, cognitive or neurological impairments, or critical or advanced complications. The clinical data of patients were extracted from their medical records. The selection of a random samples was conducted by using a computer generated random sample (RAND function in Excel) to select 641 patients out of 1747 . The ethical research committee at the Faculty of Health Sciences, Purwokerto, Indonesia, approved this study (059/KEPK/II/2020 (11 February 2020).Demographic and clinical variables related to HRQOL were assessed and studied. Variables were age, gender, marital status, level of education, employment status, income, body mass index (BMI), duration of DM, smoking status, number of diabetes-related complications, fasting blood glucose, presence of hypertension, and type of DM medication.HRQOL was measured using the 36-item Short-Form Health Survey (SF-36), one of the most widely used questionnaires for assessing HRQOL. Other studies have demonstrated that the SF-36 has high validity and reliability –20 and iDSM was assessed using a summary of the diabetes self-care activities measure (SDSCA). This multidimensional instrument that assesses patient behavior in DSM was developed by Toobert et al.  and has Diabetes-related emotional distress was assessed using DDS17 Bahasa Indonesia, which is an Indonesia version of the Diabetes Distress Scale questionnaire . This scThe Beck Depression Inventory II (BDI II) is an instrument for assessing the severity of subjective depressive symptoms . ComposeSelf-efficacy was assessed using the self-efficacy for diabetes scale (SES) from the Stanford Patient Education Research Centre . This quFamily support was assessed using the Family APGAR, which has been widely used to measure perceived family support in five domains: adaptation (A), partnership (P), growth (G), affection (A), and resolve (R) . Other sA statistical evaluation was conducted using SPSS version 22.0 .Descriptive statistics  were used to describe the demographic and clinical characteristics of the patients. Mean, and standard deviation were calculated for continuous data, and percentage values were calculated for discrete data. To identify whether the data were normally distributed, visual inspections of the histograms were performed and the Kolmogorov–Smirnov test was used. We found that the data were normally distributed. To identify differences between younger and older adults in the demographics and clinical characteristics, independent t-tests were used to compare interval variables and chi-square tests were used to compare categorical variables. Differences in HRQOL domains were analyzed using an independent t-test. Separate models were constructed to identify the predictors of HRQOL in younger and older adults. To identify the predictors of HRQOL in younger and older adults, a hierarchical multiple regression analysis was used. In the first block, DSM, DD, depression, self-efficacy, family support, and HRQOL were entered in the analysis. In the second block, demographic variables were jointly entered into the analysis. In the third block, the clinical data were jointly entered into the analysis. Tolerance and variance inflation factors were examined to detect multicollinearity. Tolerance values of less than 0.20 and variance inflation factor values higher than 5 indicated a multicollinearity problem –43.p = 0.032), lower income (p = 0.032), higher BMI (p < 0.001), shorter duration of DM (p < 0.01), fewer diabetes-related complications (p = 0.009), and higher fasting blood glucose levels than older patients (p < 0.01). There were no differences between the groups in employment status, smoking status, presence of hypertension, or type of DM medication used. These demographics and clinical characteristics were controlled in the subsequent analysis.The demographics and clinical characteristics of the patients are presented in Table p < 0.001) and greater role limitation due to physical problems than younger adults (p < 0.001). After controlling for demographics and clinical characteristics, there was no significant difference in MCS scores between younger and older adults. The SF-36 sub-dimension analysis found that older adults had lower social function (p < 0.001) than younger adults.Controlling for demographic and clinical characteristics, the PCS score was significantly lower in older adults than in the younger adults Table . The anap < 0.001). These variables accounted for 29.3% of the variance observed in HRQOL. The tolerance values of the third model ranged from 0.783 to 0.924 (> 0.20), and the variance inflation factor ranged from 1.023 to 1.373 (≤ 5), indicating that the model did not exhibit multicollinearity problems. Therefore, a regression model was deemed appropriate.The predictors of HRQOL in younger adults are shown in Table Predictors of HRQOL in older adults are shown in Table This relatively large-scale cross-sectional study of patients with T2DM was the first study conducted in Indonesia to compare HRQOL between younger and older adults and its associated factors in patients with T2DM. The core finding of this study was that the predictors of HRQOL in younger adults were neither similar to nor different from those in older adults. We found seven predictors of HRQOL in younger adults, and four predictors of HRQOL in older adults. The predictors of HRQOL in younger adults were level of education, employment status, number of diabetes-related complications, DSM, DD, depression, and self-efficacy. The predictors of HRQOL in older adults were income, depression, DD, and self-efficacy. We also found DD to be a stronger predictor than depression in younger adults and depression to be a stronger predictor than DD in older adults. This is the first study to show that predictors of HRQOL in younger and older adults are not similar. This study provides new knowledge for the literature and evidence for nurses and clinicians to establish specific interventions to improve age-specific HRQOL for patients with T2DM in Indonesia.In this study, older patients had a lower PCS scores than younger patients. Our findings differed from those of Trief et al. , who fouSomewhat surprisingly, our MCS results differed from our hypothesis. We found no difference between the MCS of younger and older adults. We also found that MCS scores in both younger and older adults were below those of the general population. This could be explained by the fact that all participants in our study tended to suffer from DD and depression. Most of the younger adults in this study had had DM for between one and five years. Thus, they might still be adapting to diabetes management. Another study showed that difficulty in following diabetes management could result in DD in adult patients . In oldeOur study found that both DD and depression were predictors of HRQOL, however, in younger adults, DD was a stronger predictor than depression, and in older adults, depression was a stronger predictor than DD. Many other studies have found that depression and DD affect HRQOL –52. HoweIn this study, DSM was one of the predictors of HRQOL in younger adults but not in older adults. Our findings were not in accordance with those of Huang and Hung  who repoSelf-efficacy was found to be a predictor in both younger and older adults. DM patients with good self-efficacy means that they have confidence in their abilities to manage diabetes and influence disease outcomes . Our stuIn this study, demographic variables that were found to be predictors of better HRQOL in younger adults were level of education, employment status, and number of diabetes-related complications. These results correspond with those of previous studies –60. We aWith this study, we identified predictors of HRQOL in younger and older T2DM patients in Indonesia. This study adds to the growing body of evidence that the predictors of HRQOL in younger and older patients are different. Based on our study findings, several actions should be taken. First, government and health clinicians should pay more attention to the physical and mental health of diabetic patients since this can affect HRQOL. Second, nurses and clinicians should create educational programs designed to improve DSM and patients’ mental health in order to be able to manage DD and depression. Future studies are needed to evaluate the effectiveness of the implementation of educational programs in improving HRQOL.This study had several limitations. First, since it was a cross-sectional study, no causal relationship could be drawn between the variables. Second, the study was conducted in Banyumas Regency and thus any extrapolation of the results to the rest of the Indonesian population should be carried out with caution. Third, we used the widely used QOL scale (SF-36] rather than a specific scale for HRQOL. Thus, there is a need for future research using a more specific scale. Finally, most patients in our study were female. While this could be perceived as a limitation, it does, however, represent the situation in Indonesia, since most DM patients in Indonesia are female.Despite its limitations, our study also has strengths. First, it involved a large number of patients with DM in Indonesia. We had a high response rate and were able to form a representative sample regarding sociodemographics. Second, we used scales that have been validated in Indonesian settings. Third, this study was the first to examine the differences in HRQOL and its predictors in younger and older adults in T2DM patients in Indonesia. Therefore, the results of this study are critical for nurses and clinicians in Indonesia wanting to establish specific interventions to improve HRQOL in both groups. This study provides a foundation for further empirical studies on intervention methods to improve HRQOL based on the predictors we identified in both younger and older adults. There is a need for a larger, longitudinal study to assess the effects on HRQOL in patients who undergo specially designed programs.This study is the first to compare HRQOL between younger and older adults and its associated factors in patients with T2DM in Indonesia. It provides evidence for nurses and clinicians in Indonesia to develop new approaches to improve HRQOL in both younger and older DM patients. The main findings of our study were the predictors of HRQOL in younger adults were neither similar to nor different from those in older adults. We found seven predictors of HRQOL in younger adults, and four predictors of HRQOL in older adults. The predictors of HRQOL in younger adults were level of education, employment status, number of diabetes-related complications, DSM, DD, depression, and self-efficacy, while the predictors of HRQOL in older adults were income, depression, DD, and self-efficacy. The strongest predictor of HRQOL in younger adults was DD, while the strongest predictor of HRQOL in older adults was depression. Nurses and clinicians should design educational programs for patients with DM to improve DSM, as well as to improve mental health to overcome DD and depression.


The CTL group was divided according to the iron treatment received: without iron treatment , treated only with iron sulfate or EPO , and treated with both iron sulfate and EPO . The RT group followed the same pattern: , , and . RT consisted of 24 weeks/3 days per week at moderate intensity of full-body resistance exercises prior to the hemodialysis section. The RT group, regardless of the iron treatment, improved iron metabolism in older individuals with ESRD. These results provide some clues on the effects of RT and its combination with EPO and iron sulfate in this population, highlighting RT as an important coadjutant in ESRD-iron deficiency.We sought to investigate the effects of resistance training (RT) combined with erythropoietin (EPO) and iron sulfate on the hemoglobin, hepcidin, ferritin, iron status, and inflammatory profile in older individuals with end-stage renal disease (ESRD). ESRD patients ( End-stage renal disease (ESRD) patients often present impaired intestinal absorption of dietary iron, blood losses, and low-grade chronic inflammation, which can lead to difficulties in achieving adequate iron status ,2. This This adverse scenario motivates physicians and researchers to seek alternative and non-pharmacological treatments to counteract the adverse events related to ESA therapy and iron supplementation. A recent study from our laboratory outlined the positive effects of resistance training (RT) on iron deficiency in ESRD patients, suggesting this training model as an adjunct treatment for anemia . In our Attempting to answer this question, we sought to investigate the effects of RT combined with EPO and iron sulfate on the hemoglobin, hepcidin, ferritin, iron status, and inflammatory profile in older individuals with ESRD. We hypothesized that RT would enhance the effects of EPO and iron sulfate in this population. If confirmed, such findings might point to RT as an important adjunct therapy for iron deficiency that may work together with therapy involving erythropoiesis-stimulating agents.n = 76) and the resistance training group .This study is part of a large trial . Brieflyn = 19), treated only with iron sulfate or EPO , and treated with both iron sulfate and EPO . The RT groups followed the same pattern , , , as described in Here, we stratified the patients into six subgroups according to the iron treatment received. The CTL group was divided as follows: without iron treatment . It must be diluted in 100 mL of saline solution and infused within 15 min, according to the manufacturer. A study demonstrates its safe use in shorter administration times, up to 5 min, without increasing adverse reactions.Venous blood samples were obtained at baseline, and after 24 weeks of training, to measure the iron metabolism status and inflammatory profile. All analyses were described elsewhere .p < 0.05. All statistical analyses were performed using SPSS Statistics for Windows, version 22.0 (released 2013) , and GraphPad Prism for Windows, version 8.0.0 .Initially, normality and homogeneity of data were verified using the Shapiro–Wilk and Levene tests, respectively. A three-way ANOVA 2 × 2 × 3 (Group × Time × iron treatment) was performed to compare groups. Deltas (post-pre) were obtained from all groups and compared using a two-way mixed ANOVA 2 × 3 (group × iron treatment) followed by Tukey’s post-hoc. Results were considered significant at Subjects that completed the RT protocol did not present adverse effects. Baseline characteristics are displayed in p > 0.05). RT increased hemoglobin from baseline in all groups. Only the RT group treated with EPO + IRON presented higher hemoglobin in relation to the CTL group treated with EPO + IRON. Serum iron increased in relation to baseline and the CTL groups. Ferritin only decreased from baseline. The RT group presented a decrease in hepcidin in relation to baseline and in relation to the CTL group that received the same iron therapy, as described in Patients from the CTL group did not display changes in iron, hemoglobin, ferritin, and hepcidin after this six-month assessment in all iron treatment groups  that RT is an effective treatment for improving serum iron parameters in elderly patients with ESRD and (2) that conventional use of ESA + iron in this population is more effective in combination with RT. Interestingly, as RT alone improved serum iron availability, it may provide the opportunity to remove ferrous sulfate and its associated disturbances from the treatment in this population. This would limit iron accumulation and, in theory, further reduce hepcidin, as suggested by the greater reduction in hepcidin in the RT—none group compared to the RT—IRON + EPO group. Furthermore, although the small sample size did not allow us to perform this analysis, the combination of RT + ESA is probably the most promising treatment for lowering hepcidin levels. This combination would reduce the activation of the two main pathways of hepcidin synthesis: the JAK/STAT3 pathway, by lowering inflammation (RT effects), and the BMP/SMAD pathway, by increasing erythropoiesis activity and sequestering erythroferrone BMP2/6 ligands ,12.According to the results found by Agarwal et al. , non-hemAnemia and iron deficiency is a common complication of hemodialysis patients ,2,3,5. BAnemia leads to reduced quality of life, fatigue, dyspnea, and impaired cognitive capacity. Furthermore, it is associated with a greater risk of adverse cardiovascular events and mortality. Therefore, these conditions usually end up leading to a greater number of hospitalizations, with increased costs for the health system. In Brazil, it is estimated that 133,464 patients were on dialysis in 2018, and the use of EPO was part of the treatment of more than 80% of these patients. The annual cost of treatment for anemia in patients with chronic kidney disease can reach US $3241.65 dollars, while the minimum monthly wage for Brazilian citizens is around US $222 dollars, leading to an economic burden for the treatment of anemia [The present manuscript had an important limitation: the study did not control for the time of iron supplementation or EPO, which might influence the dependent variables. We recommend further studies to control for this condition. As this study is an additional analysis of a larger trial , it was We conclude that regardless of the iron treatment, RT could improve hemoglobin, iron, ferritin and hepcidin in older individuals with ESRD. These novel findings provide some clues on the combined effect of RT plus EPO and iron sulfate in this population. Moreover, RT alone may also be an effective strategy to improve iron metabolism in hemodialysis patients. Therefore, it is rational to infer that the application of RT programs should be strongly recommended in dialysis care. This would improve the prognosis of several ESRD patients, especially those with iron deficiency and anemia. Further studies are needed to determine whether the treatment with EPO and iron sulfate is more effective in treating iron deficiency and anemia when combined with exercise training in patients with ESRD.