This study was performed to assess the value of quantitative analysis of enhanced computed tomography (CT) values in the differential diagnosis of bladder cancer and cystitis glandularis (CG). t-test.  Eighty patients with bladder masses (39 with CG and 41 with bladder cancer) who underwent enhanced CT were retrospectively reviewed. The CT enhancement values of the lesion and normal bladder wall in the arterial phase, venous phase, and delayed phase were measured. The relative enhancement CT values  in the arterial phase, venous phase, and delayed phase were also calculated. The pathological results were used as the gold standard, and the area under the curve (AUC), sensitivity, and specificity were calculated for the six groups of quantitative indicators . We performed the leave-group-out cross-validation method to validate the accuracy, AUC, sensitivity, and specificity. The differences in accuracy, AUC, sensitivity, and specificity among the six groups of quantitative indicators were compared by the P < 0.05).  In a combined analysis of the AUC, sensitivity, and specificity performance, the best indicator was the arterial-phase relative enhancement CT value with a cut-off of 25.85 HU . We used the 100-times leave-group-out cross-validation method to validate the accuracy, AUC, sensitivity, and specificity. Arterial-phase relative enhancement CT values showed the highest AUC and accuracy among the six groups, with statistical significance ( Quantitative analysis of enhanced CT is of great clinical value in the differential diagnosis of CG and bladder cancer. Cystitis glandularis (CG) is a proliferative and metaplastic disorder of the bladder mucosa with an incidence of 0.1% to 1.9% in the general population , 3. On c2.The examination protocol was approved by the institutional medical ethics committee, and informed consent was obtained from all patients. Eighty patients with pathologically proven CG and bladder cancer from July 2003 to January 2017 were retrospectively analyzed. The inclusion criteria were performance of an enhanced CT scan, confirmation of the definitive diagnosis by postoperative pathology, and no performance of catheterization. The exclusion criteria were other malignant tumors or serious diseases, a history of urological surgery, poor-quality enhanced CT images, and a lesion area of <20 mmIn total, 39 patients with CG (34 men and 5 women) were included in the study. Their mean age was 56 ± 14 years . Additionally, 41 patients with bladder cancer (34 men and 7 women) were included. Their mean age was 65 ± 15 years .CT scans were performed using a standard CT protocol for the pelvis. Eighty patients underwent CT scanning after intravenous injection of 80 to 100 ml iopromide 300. CT images were acquired in the arterial phase (30 s after injection), venous phase (50–80 s after injection), and delayed phase (5–30 min after injection). The acquisition parameters were a tube voltage of 120 to 140 kV and tube current of 180 to 200 mAs. All 80 patients underwent cystoscopy or a bladder operation to treat the bladder masses within 1 week after the imaging examination.Two radiologists who had more than 6 years of experience and who had not been informed of the clinical and histopathological findings independently reviewed the images in consensus. The imaging characteristics were analyzed with respect to location , shape , size, margins (well-defined or ill-defined), and attenuation. Signs of extramural infiltration, calcification, necrosis or cyst degeneration, and regional lymph node metastasis were classified as present or absent. Attenuation in the tumors and bladder wall was measured in Hounsfield units (HU) on contrast CT. For evaluation of size, the greatest single dimension of each lesion was measured.2 oval regions of interest were manually drawn by one radiologist on the image to encompass most of the lesion. We detected the CT value of the lesion with avoidance of blood vessels, artifacts, tumor stalks, necrosis, and margins. Each lesion was measured three times in different areas, and the average CT value was used for the statistical analysis to avoid measurement errors. The relative enhancement CT value was calculated as the enhancement CT value of the lesion minus the enhancement CT value of the normal bladder.Attenuation in the lesions and bladder wall on CT images was measured. For evaluation of the lesions, >20 mmχ2 test. Continuous data are presented as mean and standard deviation and were analyzed by Student's t-test. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic accuracy of the arterial-, venous-, and delayed-phase enhancement CT values and relative enhancement CT values in the lesion for the differential diagnosis of CG and bladder cancer. ROC curves were used to determine the sensitivity and specificity and extrapolate the optimum cut-off value for CG versus bladder cancer. The differences in the area under the curve (AUC) of the six groups of quantitative indicators  were compared by the Z test. A two-tailed P value of <0.05 was considered statistically significant. We used open-source software  to perform the leave-group-out cross-validation (LGOCV) method to validate the accuracy (ACC), AUC, sensitivity, and specificity. The differences in ACC, AUC, sensitivity, and specificity of the six groups of quantitative indicators  were compared by Student's t-test.The data were statistically analyzed with SPSS version 17.0 . Categorical data were analyzed with the P = 0.284–0.945). However, statistically significant differences were found in age, shape, margins, regional lymph node metastasis, and extramural infiltration between CG and bladder cancer (P = <0.001–0.047).The patient-related and morphologic enhanced CT characteristics of CG and bladder cancer among the 80 patients are listed in P < 0.001).The enhanced CT values of CG  and bladZ = 0.550–1.934, P = 0.0531–0.5820). The differential diagnostic efficacy of the relative enhancement CT values in the arterial phase was the best indicator in comprehensive consideration of the AUC, specificity, and sensitivity performance .The results of the ROC analysis of the enhancement CT values and relative enhancement CT values in the arterial, venous, and delayed phases for the efficacy of differential diagnosis between CG and bladder cancer are shown in P < 0.05). Although the arterial-phase relative enhancement CT values also showed relatively high sensitivity and specificity, the differences among the six groups were not statistically significant (P > 0.05)  .The etiology and pathogenesis of CG are unclear. CG is caused by metaplasia of transitional epithelium to glandular epithelium. Additionally, some authors have reported that these masses can progress to bladder adenocarcinoma –8. PatieThe results of this study showed no statistically significant differences in sex, location, tumor size, calcification, or necrosis or cyst degeneration between CG and bladder cancer. However, statistically significant differences were found in age, shape, margins, regional lymph node metastasis, and extramural infiltration between CG and bladder cancer. A lobulate or papillary shaped bladder lesion with ill-defined margins in an older patient may be the features that differentiate bladder cancer from CG. However, these features cannot serve as differential diagnostic criteria because in clinical practice, all of these features overlap between the two conditions. Extramural infiltration and regional lymph node metastasis might serve as differential diagnostic criteria because they only occur in bladder cancer. Additionally, according to a previous study, extramural infiltration into an intact muscle layer is a feature that differentiates CG from urothelial carcinoma . HoweverThis study showed that the degree of enhancement of six groups of quantitative indicators in patients with CG was lower than that in patients with bladder cancer, which may be related to the blood supply of CG and bladder cancer. In contrast to malignant tumors, CG exhibits proliferative changes of the bladder mucosa, such as epithelial crypts, submucosal masses of epithelial cells (von Brunn's nests), and subepithelial fluid-filled cysts associated with cystitis cystica . AlthougIn the present study, an ROC curve analysis was used to perform a quantitative analysis of six groups of data: the enhanced CT values and relative enhanced CT values of CG and bladder cancer in the arterial phase, venous phase, and delayed phase. The AUC of the relative enhanced CT value in the arterial phase was the largest. However, the AUCs of the relative enhanced CT values in the arterial phase, venous phase, and delayed phase were not significantly different. We used the LGOCV method to validate the AUC, ACC, sensitivity, and specificity. The results showed that the relative enhanced CT value in the arterial phase had the best performance and AUC and ACC had statistic difference between six groups. Thus, the relative enhancement value in the arterial phase was the best indicator . This may have been because the degree of arterial enhancement mainly depends on the microvascular density  , and theThis study has some limitations. First, the sample size was small, and the results require further verification by expanding the sample and including multiple centers. Second, the scan time in the delayed phase had a wide range (5–30 min after injection). Finally, this study only focused on the difference in CT values between CG and bladder cancer, and the differential diagnosis between bladder cancer and other benign bladder lesions, such as chronic bladder inflammation or bladder malakoplakia, needs to be further studied.Quantitative analysis of enhanced CT values was valuable for the differential diagnosis of CG versus bladder cancer.


Mild cognitive impairment (MCI) is generally regarded as a prodromal stage of Alzheimer’s disease (AD). In coping with the challenges caused by AD, we analyzed resting-state functional magnetic resonance imaging data of 82 MCI subjects and 93 normal controls (NCs). The alteration of brain functional network in MCI was investigated on three scales, including global metrics, nodal characteristics, and modular properties. The results supported the existence of small worldness, hubs, and community structure in the brain functional networks of both groups. Compared with NCs, the network altered in MCI over all the three scales. In scale I, we found significantly decreased characteristic path length and increased global efficiency in MCI. Moreover, altered global network metrics were associated with cognitive level evaluated by neuropsychological assessments. In scale II, the nodal betweenness centrality of some global hubs, such as the right Crus II of cerebellar hemisphere (CERCRU2.R) and fusiform gyrus (FFG.R), changed significantly and associated with the severity and cognitive impairment in MCI. In scale III, although anatomically adjacent regions tended to be clustered into the same module regardless of group, discrepancies existed in the composition of modules in both groups, with a prominent separation of the cerebellum and a less localized organization of community structure in MCI compared with NC. Taking advantages of random forest approach, we achieved an accuracy of 91.4% to discriminate MCI patients from NCs by integrating cognitive assessments and network analysis. The importance of the used features fed into the classifier further validated the nodal characteristics of CERCRU2.R and FFG.R could be potential biomarkers in the identification of MCI. In conclusion, the present study demonstrated that the brain functional connectome data altered at the stage of MCI and could assist the automatic diagnosis of MCI patients. Alzheimer’s disease (AD), a neurodegenerative disease, represents the most common type of dementia . The preTheoretically, the human brain can be represented as a “connectome,” a large-scale network of interconnected regions that provides the anatomical substrate for neural communication, functional processing, and information integration . Brain cGraph metrics of the functional brain network are found to be informative to characterize MCI patients . In pracMoreover, the past decades witness the increasing growth in clinical use of artificial intelligence. Machine learning approaches are found to be quite useful for discriminating MCI patients from normal controls (NCs) . Some reIn this study, we retrospectively analyzed resting-state fMRI (rs-fMRI) data derived from 82 MCI patients and 93 NCs from ADNI. Brain functional networks were constructed from rs-fMRI data, and the network metrics were analyzed from three scales. Both cerebral and cerebellar regions were covered in the construction of the graph. A weighted network was used in order to keep the information in the functional connectivity (FC). Furthermore, graph metrics were then combined to train and validate an automatic model on MCI and NC subjects. Our primary goal was to investigate the alterations of network properties that occurred at the stage of MCI and to find out whether the analysis of functional network can assist the accurate diagnosis of MCI patients.1 Participants in ADNI were included in the present study if they met the following criteria: (i) ages between 55.0 and 80.0; (ii) scanning with parameters of repetition time of 3,000 ms, echo time of 30 ms, flip angle of 80° or 90°, slices of 48, and voxel size of 3.31 mm × 3.31 mm × 3.31 or 3.44 mm × 3.44 mm × 3.40 mm; (iii) available records of their cognitive and behavioral assessments, comprising scores from the 13-item AD assessment scale (ADAS13), clinical dementia rating scale sum of boxes (CDRSB), Mini-Mental State Examination (MMSE), and frequently asked questions (FAQ); (iv) head motions <1.5 mm and 1.5°; (v) mean fractional displacement head motion values <0.2 mm; and (vi) satisfying MRI quality control and excluding unclear spatial normalization pictures. The demographics and clinical characteristics of the participants are illustrated in In this study, rs-fMRI data derived from 82 MCI patients and 93 NCs were obtained from the ADNI database.2) and the toolbox for Data Processing and Analysis of Brain Imaging (DPABI3) , data preprocessing was conducted with the help of Data Processing Assistant for Resting-State fMRI Advanced Edition (version 4.3), which is based on Statistical Parametric Mapping  . First, (DPABI3) , 2018, a(DPABI3)  was adop(DPABI3)  map on t(DPABI3)  and furtith and jth ROIs were denoted as Xi and Xj, respectively. The absolute Pearson correlation coefficient between Xi and Xj, denoted as rij and calculated by Formula (1), was used in the present study to evaluate the FC between the two ROIs.Time series derived from the Xi and Xj, respectively. Given a total of N ROIs, a symmetric matrix w with N∗N elements can be obtained by evaluating the FC values over all the possible ROI pairs, as shown in Formula (2):Here, w were then set to 0. In this way, for each individual, a fully connected, undirected, and weighted network was obtained by regarding each ROI as a node and w as the adjacent matrix. We also constructed group-level networks based on the individual adjacent matrix for MCI patients and NCs, respectively. That is, the element wij of the group-level network is the average value of wij in each individual graph within a certain group. Such a group-level network summarizes FC maps on average over all subjects within the group and captures the connectivity backbone of the group , characteristic path length (L), global efficiency (GE), and small worldness  were investigated in this study. In scale II, the regional nodal characteristics regarding the global hubs were assessed qualitatively on the group-level networks obtained across the sparsities ranging from 5 to 50%. The betweenness centrality of a node i (denoted as bci) in the group-level network was calculated and normalized as BCi = bci/ < bci >, where < bci > is the average betweenness of all nodes. BCi measures the importance of node i over information flow between other nodes throughout the network, and the regions with high values of BCi are usually identified as hubs. Some studies identified hubs as nodes with BCi larger than 1.5  as independent variables, was used to evaluate whether there is significant difference of network metrics between both groups. Moreover, gender was controlled as concomitant variable in the logistic regression analysis. p < 0.05 was considered as an indicator for significant difference.Statistical evaluations were conducted using R program (version 4.0.2). For cross-sectional comparisons of demographic and clinical characteristics between the MCI and NC groups, the normality of the data was first evaluated by Lilliefors test. The Fisher’s exact test was applied to categorical variables (only gender here), and Wilcoxon rank sum test or bc) network metrics for each subject, resulting in 124 features under each sparsity. Considering the classification scenario with high-dimensional features and low-size samples, we hereby proposed a two-layer random forest approach for the task, with the first layer for feature selection and the second for classification. Such an approach was implemented on Python 3.7 with the widely used scikit-learn library  error . In the For the second layer, two hyperparameters of the random forest, i.e., the number of trees in the forest and the maximum depth of the tree, were fine-tuned. Specifically, a five-fold grid search was embedded in an outer loop to fulfill a 10-fold nested cross-validation (CV) for evaluating the performance of the classifier, i.e., the accuracy, sensitivity, specificity, and area under receiver operating characteristic curve (AUC). Nested CV was demonstrated to produce robust and unbiased performance estimates regardless of sample size .C, L, GE, and SW were calculated and compared for the MCI and NC groups across sparsities ranging from 5 to 50%, with steps of 1%. The results are illustrated in C was found at any sparsities (L (or GE) was observed in MCI across almost all the sparsities  and clinical characteristics  by pooling all participants together. The values of C were shown to be associated negatively with MMSE and positively with CDRSB, ADAS13, or FAQ scores  was used to evaluate the association between global network metrics . However, when integrated with network metrics, improved accuracies can be achieved across all the sparsities , the right lobule VIIB of the cerebellar hemisphere (CERE7b.R), and IOG.R.The highest accuracy (91.4%) was achieved when we used the top 10 discriminative features  in MCI patients. We further observed positive correlation  between nodal bc of CRECRU2.L and MMSE score across 40 out of 46 sparsities (average correlation coefficient over these sparsities was 0.19), and negative correlation between nodal bc of CERCRU2.R and ADAS13 scores . The MMSE is the best known and the most common used short screening tool of AD for providing an overall measure of cognitive impairment in clinical, research, and community settings  and IOG.R. FFG is thought to be a key structure for functionally specialized computations of high-level vision such as face perception, object recognition, and reading . Katja WThe present study confirms the existence of modular organization in human brain networks, even in MCI patients. We detected four modules for each group. For both groups, although discrepancies existed in their composition of modules, some common features can be found in the modular structure. Such features might throw light on the basis of two fundamental aspects of the human functional brain network, i.e., the functional segmentation and integration. On the one hand, anatomically adjacent ROIs tend to be clustered into the same module, which might be the foundation of the functional segmentation of the brain network. On the other hand, those ROIs, whose anatomical neighbors were involved into a different module, are likely to act as bridges to connect different modules and to be identified as global hubs in the whole network. Such a phenomenon should contribute to the functional integration and the existence of small-worldness property of the brain network.The prominent alteration of the modular structure in MCI (compared with NC) occurs in the cerebellum, with its ROIs grouped into two modules. Another obvious change in the modular structure in MCI occurs in the medial prefrontal cortex, especially the orbitofrontal cortex (OFC). In previous studies, the OFC has been found to be involved in sensory integration, in representing the affective value of reinforcers, and in decision making and expectation . In the In clinical practice, the MCI diagnosis mainly depended on concerns of the cognition changes from the patient, knowledgeable informant, or according to a skilled clinician’s observation . NeuropsIn this study, we investigated the alterations of brain functional network in MCI. Although small-world properties, global hubs, and modular structures were observed in both groups, network metrics significantly changed in MCI when compared with NC. The role of cerebellar regions, especially the Crus II of cerebellar hemisphere, were found to be associated with the cognitive impairment in MCI patients and discriminative in the identification of MCI. Although network metrics were demonstrated to provide useful information to assist the diagnosis of MCI in clinical practice, future investigation is required to clarify the association between these alterations and the underlying pathological mechanism of MCI.Moreover, the sex factor was controlled in the statistical analysis to evaluate the group difference of network metrics or their association with clinical characteristics in scales I and II. Because the modular structure of each group was computed at group level, the findings in scale III are hereby descriptive, which suggests that we cannot statistically assess whether they are partly contributed by sex difference. Given our observation that sex contribution to scales I and II is trivial, we speculate that the descriptive modular structure is not contributed by sex difference. Future study on a larger sample is thus in favor of the validation of our findings, especially those in scale III.http://adni.loni.usc.edu/.Publicly available datasets were analyzed in this study, which can be found at: The studies involving human participants were reviewed and approved by the institutional review board of each participating center in the ADNI study. Each participant provided signed informed consent before the study. All methods were carried out in accordance with relevant guidelines and regulations. The current study analyzed de-identified data from the ADNI database, and did not involve a research protocol requiring approval by the relevant institutional review board or ethics committee.FH, JW, JQ, and AY designed this study. LZ and ZY analyzed the data. LZ, FH, and HN wrote the article. 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.


Quitting smoking and participation in cardiac rehabilitation (CR) are effective strategies in reducing morbidity and mortality. However, little is known about the predictors of quitting smoking in those who attend CR. This study aimed to determine the sociodemographic and clinical factors associated with the likelihood of CR attendees who are quitting smoking. Data from the UK National Audit of Cardiac Rehabilitation (NACR) database, between April 2013 and March 2016, were used. Smoking status is categorized as smokers and quitters, assessed by patient self-report. The study used patient demographics, cardiovascular risk factors, comorbidities, and physical and psychosocial health measures. Binary logistic regression was performed to identify the predictors of quitting smoking among CR attendees. Of the 3290 patients who started CR and were entered into the NACR database, 2052 were continued smokers  and 1238 were quitters . The median duration of CR was 9 weeks. Compared to smokers, the quitters were younger, weighed more, were less anxious and depressed, and were more likely to be employed. Single patients had 0.60 times lower odds (95% CI 0.43 to 0.82) of quitting smoking than patients with partners, and low-risk patients had 1.71 times higher odds (95% CI 1.12 to 2.62) of quitting smoking than high-risk patients. Increasing number of comorbidities and depression scores were associated with decreasing likelihood of quitting. This study highlights the routine factors that determine smoking cessation outcomes, which could inform the delivery of CR to better help patients to quit smoking. Smoking is a major risk factor for cardiovascular disease (CVD) and one of the biggest threats that the world has ever faced, being the cause of death of more than 8 million people per year . The recA meta-analysis of 12 cohort studies estimated that mortality in patients who continue to smoke after myocardial infarction (MI) is 20% and suggested that smoking cessation is associated with a significant decrease in mortality . A retroStronger evidence comes from a 15-year follow-up of Dutch patients who underwent coronary bypass surgery [Smoking is a major preventable risk factor for the development of non-communicable diseases, including cardiovascular, respiratory diseases, and cancers . QuittinCardiac rehabilitation (CR), a comprehensive intervention offered to patients with CVD, is a structured multidisciplinary intervention designed to target risk factors and psychosocial wellbeing and supports smoking cessation in attempts to improve or maintain psychosocial wellbeing ,9,14. PaAlthough extensive research was carried out on CR, little is known about the factors that are associated with patients quitting smoking among CR participants. There is substantial evidence that the demographic characteristics associated with quitting smoking include gender ,19, age www.cardiacrehabilitation.org.uk/nacr/downloads.htm), and the data quality is checked by a member of the NACR team. The audit is voluntary, supports direct entry of data within a secure online system, and collects local program-level data for those who are referred to and undergo CR. It includes details of a patient’s initiating event, treatment type, risk factors, drugs, patient demographics, and post-CR clinical outcomes. The NACR has approval to collect anonymized patient data for a range of clinical variables, without explicit consent from individual patients, for the purposes of audit and research under Section 251 of the NHS Act 2006 [The analyses were conducted using individual patient data collected electronically in the National Audit of Cardiac Rehabilitation (NACR). The NACR is a web-based registry of CR in the UK, funded by the British Heart Foundation. Practitioners involved in CR delivery electronically enter data on eligible patients who are referred for CR into the individual patient dataset, according to a data dictionary  and follow-up (post-CR). There were no exclusion criteria.Never smokedEx-smokerStopped smoking since eventCurrently smoking.Smoking status in the NACR database is recorded with information obtained by patient self-report questionnaires . Patientcontinued smokers, if they were current smokers in both the pre- and post-CR assessments.ex-smokers, if they were current smokers at the pre-CR assessment and stopping smoking status at the post-CR assessment.From the smoking status record, pre- and post- for each CR patient, patients were defined, for the purposes of this research, as:2), and waist (cm). The sociodemographic data collected includes age, gender, marital status, work status, and ethnicity.Numerous past studies used a variety of baseline characteristics to assess the difference between continued smokers and quitters ,32,33,34Comorbidities are any of the 19 commonly associated conditions that the patients who undergo CR have, such as angina, diabetes, and cancer. These comorbidities are routinely collected by the NACR and reported in the national statistical report . Risk stTo evaluate the role of social deprivation, the study included the English Index of Multiple Deprivation (IMD) Lower Layer Super Output Areas (LSOA) deprivation deciles, which linked to the NACR . These dp < 0.05 was considered to be statistically significant.All analyses were performed in the IBM Statistical Package for Social Sciences (SPSS) software Version 26 . Smoking status was valued as 1 for quitters and 0 for smokers. Frequency tables were generated to categorize CR patients as smokers and quitters, according to their recorded pre- and post-CR smoking status. Analyses were conducted using all available data from CR attendees to minimize selection bias. Continuous variables are shown as mean (standard deviation (SD)) and categorical variables as frequencies (percentage).t-test for continuous variables or chi-square test for categorical variables. Cohen’s d test was used as a measure of the effect size to indicate the mean difference between two groups in standard deviation units [2 test for association was conducted between baseline sociodemographic and clinical characteristics of smokers and quitters participating in CR [Descriptive statistics were used to describe and compare a variety of sociodemographic and baseline characteristics between smokers and quitters, among CR attendees in the UK. Both continuous and categorical variables were used, depending on the method of data collection in the NACR. Differences in baseline characteristics were then compared using independent-sample on units . In adding in CR . Phi andng in CR . Binary ng in CR .The NACR cohort included 130,961 patients who started CR during the research period. A total of 48,820 (37.3%) had a missing smoking status. Overall, 91.4% of patients who started CR and had a smoking status recorded were classified as non-smokers .Of the 49,725 patients who had their smoking status recorded pre- and post-CR, 46,435 (93.4%) were classified as non-smokers , 2052 (4.1%) as continued smokers , and 1238 (2.5%) as ex-smokers . The median duration of CR was 9 weeks. For the purposes of this research, patients were categorized as either continued smokers or quitters .The mean baseline characteristics of smokers and quitters are summarized in t-test was run to determine whether sociodemographic and clinical characteristics differed between smokers and quitters Anxiety scoreDepression scoreThe following characteristics were considered in the final model to identify CR attendees who quit smoking:A binary logistic regression was performed to ascertain the effects of the baseline characteristics on the likelihood that CR attendees quit smoking .2(10) = 59.32, p < 0.0001), explained 9.3% (Nagelkerke R2) of variance in smoking status, and correctly classified 64.7% of cases. Sensitivity was 25.5%, specificity was 87.6%, positive predictive value was 54.5%, and negative predictive value was 66.9%. The Hosmer–Lemeshow test in the final model was not statistically significant (p = 1.00), indicating that the model was an appropriate fit.The logistic regression model was statistically significant , and more severe depression were less likely to quit smoking during CR. Age, comorbidities, cardiovascular risk, marital status, work status, weight, HADS anxiety and depression scores expressed statistically significant differences between continued smokers and quitters. Compared to continued smokers, quitters were younger, weighed more, had fewer comorbidities, lower cardiovascular risk, were less anxious and depressed, were more likely to have a partner and be employed. No meaningful differences in gender, social deprivation, or physical activity were observed.There was no gender difference in the likelihood of quitting smoking according to the results of this research. Previous research found that demographic characteristics are associated with quitting smoking; however, few such differences were identified by this research. For example, quitting smoking had no relationship with gender and being female was not predictive of quitting smoking. This was similar to the findings of numerous studies ,48,49,50n = 1489) were aged >65 years, whereas 908 (27.60%) of the 3290 patients included in the analysis reported here were aged ≥65 years old, giving a more appropriate sample size for the regression analysis. The results reported by Jampaklay et al. were also consistent with those of Li et al. and Osler and Prescott in Asia and Western Europe, respectively [On the other hand, a longitudinal study of the 2000 Thai adult smokers from the International Tobacco Control Southeast Asia survey, with over four years of follow-up, found that age was a strong independent predictor of quitting smoking, as older age was associated with increased success of quitting smoking [ectively ,19,20. Jectively , compareSingle patients had 0.60 times lower odds of quitting smoking than patients with partners. Marital status was identified as a major predictor of quitting smoking. This was similar to the findings of the British Household Panel Survey from 1991 to 2000, in which marital status was an important sociodemographic predictor of quitting smoking ; the finPatients with multiple comorbidities had decreased odds of quitting smoking; in contrast, low-risk patients were associated with higher odds of quitting smoking than high-risk patients. Holtrop et al. found that the presence of comorbidities in CVD patients was not associated with quitting smoking . HoweverPatients with a higher HADS depression score had decreased odds of quitting smoking. This was in line with the finding of a meta-analysis of 42 trials by Hitsman et al., in which major depression had a moderate adverse effect on quitting smoking . This fiThe findings showed that identification of characteristics that predict quitting smoking among CR attendees is highly desirable, as this could help match smokers with strategies that are more likely to help them quit, identify smokers who might need more intensive treatment , and make the most of healthcare resources. Programs designed to encourage smokers to quit might need to account for factors related to partner support as part of an existing prevention program, to encourage smokers to quit. A more wide-ranging CR offer and tailored intervention is suggested to help smokers quit, as the research findings highlight that CR programs need to prioritize patients with multiple comorbidities, high cardiovascular risk, more severe depression, and no partner(s). In future trials, it would be useful to pay increased attention to the recruitment of patients who are more representative of the broader CVD population, including those at higher risk and with major comorbidities. Clinical and research efforts should be directed towards improving the rate of smoking cessation in patients with CVD.The strength of this study lies in the use of an observational approach based on routinely collected patient data, and the use of a large dataset taken from routine clinical practice and representing a CR intervention with a median duration of nine weeks.Retrospective observational studies have known limitations in terms of data capture and the quality of the 230 CR programs in the UK—according to the 2019 NACR report, only 189 (82%) programs entered data electronically to the NACR. Although it can be argued that there is enough data to be representative and carry out a reliable analysis, future work should aim to achieve greater capture of available data across the UK. Although CR programs are encouraged to provide complete patient records, a proportion of patient data was expected to be missing due to non-completion of patient records. On the basis of the NACR data, 68.6% of all patients who started CR did not have a post-CR assessment recorded, which might have affected the representativeness of the research sample.A limitation of the study was the use of self-reported data to determine smoking status, which might be subject to recall and social desirability biases. The self-reported smoking status was not validated with a biochemical marker. Some relevant factors that influenced quitting smoking were missing from the analysis, due to high levels of missing data—variables with more than 60% missing values were eliminated from the dataset  and some might not have been collected in the NACR. Some characteristics known to influence quitting smoking in the literature were not collected by the NACR, such as motivation to stop smoking, number of cigarettes per day, proportion of smokers in the household, and exposure to warning labels ,22,27.Patients with high cardiovascular risk, multiple comorbidities, no partner(s), and more severe depression were less likely to quit smoking during CR. This research highlights routine factors that determine smoking cessation outcomes and that could inform the delivery of CR to better help patients in quitting smoking.


M age = 10.97; SD = 0.74) completed a battery of questionnaires. An adjusted structural equations model was obtained . A direct and negative relationship was obtained between cybervictimization and self-concept and between cybervictimization and school anxiety. In addition, a direct and positive relationship was found between aggressiveness and self-concept and between aggressiveness and school anxiety. Indirect relationships were not found between the variables. The study’s findings demonstrate that the variables of self-concept and school anxiety are directly related to cybervictimization and that the improved psychoemotional adjustment of the youngest students may help to prevent the risk of being victimized over the Internet.The rapid increase in cases of cybervictimization amongst children has led researchers to examine the psychoemotional factors related to cyberbullying behavior, in an attempt to prevent and minimize its impact. The objective of this study was to establish and contrast the fit of an explanatory model on cybervictimization based on its relationship with self-concept, aggressiveness, and school anxiety using a structural equations analysis. A total of 542 Spanish students aged 10–12 ( The widespread use of the Internet by children and adolescents has revolutionized access to information, leisure and entertainment, communication, etc. . HoweverCyberbullying has become one of the most frequent psychosocial problems of childhood and adolescence  having pCyberbullying has devastating effects on all of these roles, but especially on the victims . Victim Self-concept is defined as a set of hierarchically organized perceptions held by an individual, which are based on their experience and relationships with the environment and that are influenced by support and assessments of other significant individuals and by attributions of the individual’s own behavior . Self-coAs for its relationship with cybervictimization, past studies have associated a poor self-concept with being cyberbullied by peers in preadolescent and adolescent samples ,27. AlonSimilarly, studies using structural equations models have offered similar results. Jenkins and Demeray  found thBushman and Anderson  define aIn general, aggressive behavior has been negatively related to personal adjustment and self-concept during adolescence ,34. AlonAs for its relationship with cyberbullying, while past studies have associated high levels of aggressiveness with the role of the bully ,37 and tSchool anxiety consists of a set of symptoms grouped together as cognitive, psychophysiological, and motor-based responses of a subject in academic situations that are perceived as threatening . TherefoAs for its relationship with cyberbullying, the limited empirical evidence existing supports a positive relationship between anxiety and cybervictimization. Delgado, Escortell, Martínez-Monteagudo, and Aparisi , in a stAs seen in the reviewed studies, cyberbullying causes major harm to its victims. Most of the studies use adolescent samples, despite the fact that the scientific literature has shown that cyberbullying also takes place during late childhood ,54,55. TTherefore, and given the many unanswered questions remaining in this area with regard to primary education students, this work proposes to define and contrast a structural equations model to analyze the relationship between self-concept, aggressiveness, school anxiety, and cybervictimization in students aged 10–12.Based on previously reviewed studies, it is expected that self-concept will be negatively associated with cybervictimization (Hypothesis 1). Moreover, it is anticipated that aggressiveness will be positively related to cybervictimization (Hypothesis 2), and that school anxiety will also be positively associated with cybervictimization (Hypothesis 3). Finally, self-concept is expected to negatively relate to aggressiveness (Hypothesis 4) and school anxiety (Hypothesis 5), and aggressiveness is expected to positively relate to school anxiety (Hypothesis 6).M = 10.97; SD = 0.74), of which, 50.2% were male and 49.8% were female. The distribution according to grade was 273 (52.8%) 5th graders and 269 (47.2%) 6th graders. A χ2 test was performed to analyze the homogeneity of the sample, considering sex and grade, finding no statistically significant differences between the four sex x grade groups .After probabilistic sampling of the public and private schools of the Alicante (Spain) province, a total of six primary education schools participated in the study. The sample consisted of a total of 542 students aged 10–12 . The psychometric studies performed by the original authors confirm an appropriate internal consistency (α = 0.91) and a factorial structure that explains 40.15% of the construct variance [Cybervictimization. The Screening of Harassment among Peers (SHP)  questionvariance . Similarvariance ,58. The never; 4 = always). Psychometric characteristics were analyzed in the original study with a sample consisting of 309 students aged between 8 and 12 [School anxiety. The School Anxiety Inventory for Primary Education (SAI)  is an in8 and 12 . The coeno; 4 = yes), distributed over seven subscales: Physical ability , Physical appearance , Relationship with peers , Relationship with parents , Self-concept in language , Self-concept in mathematics , and General self-concept . Marsh [Self-concept. The Self-Description Questionnaire (SDQ-I)  is an in). Marsh  develope). Marsh . The Spa). Marsh  using a Aggressiveness. The Aggression Questionnaire (AQ)  consistsAfter an interview with directors and school counsellors from the selected schools, intended to inform them of the study objectives and request the relevant permission, an authorization was requested from the parents of the minors in order to request their signed informed consent. Tests were carried out collectively and voluntarily, in two class sessions, ensuring participant anonymity and confidentiality. The study researchers, along with the students’ teachers, were present during questionnaire completion in order to clarify any potential doubts and to ensure the correct development in its implementation. All standards on research conducted on humans were respected, in accordance with the ethical principles of the Helsinki Declaration, and were approved by the University’s Ethics committee (UA-2018-02-21).IBM SPSS  statistical software was used to perform the basic descriptive analyses and Pearson correlation coefficients. For analysis of the potential relationships existing between study variables, a structural model was designed to establish the relationships between the constructs intervening in the study. These data were calculated using the IBM AMOS 23 program to obtain the covariance matrix of the examined variables. The program is useful for these analyses, since the main study constructs are made up of various observed variables . After vThe complete structural equations model consists of 16 observed variables and three latent variables to measure the indicators see . In thisSelf-concept acts as an exogenous variable and influences seven indicators: Physical ability (SDQHF), Physical appearance (SDQAF), Relationship with peers (SDQRC), Relationship with parents (SDQRP), Self-concept in language (SDQL), Self-concept in mathematics (SDQM), and General self-concept (SDQG). Aggressiveness also acts as an exogenous variable, influencing four indicators: Hostility (AQH), Verbal aggression (AQV), Anger (AQA), and Physical aggression (AQP). School Anxiety as an exogenous variable influences four indicators: Anxiety related to assessment and academic failure (SAIF1), Anxiety related to victimization (SAIF2), Anxiety related to social assessment (SAIF3), and Anxiety related to scholastic punishment (SAIF4). On the other hand, School Anxiety also acts as an endogenous variable, receiving the effect of Self-concept and Aggressiveness. In addition, Cybervictimization receives the influence of Self-concept, Aggressiveness, and School Anxiety, thereby acting as an endogenous variable.Bootstrap analysis was also used to estimate the 95% confidence intervals with bias correction for the direct and indirect effects of School Anxiety on the association between Self-concept and Cybervictimization, as well as between Aggression and Cybervictimization.p indicate a good model fit. However, normalized adjustment indices were also calculated, which are not sensitive to sample size. Therefore, the Comparative Fit Index (CFI) is considered acceptable for values exceeding 0.90 and excellent for values exceeding 0.95. The Normalized Fit Index (NFI) should be greater than 0.90. The value of the Incremental Fit Index (IFI) is considered acceptable for values exceeding 0.90 and excellent for values higher than 0.95. Finally, the Root Mean Square Error of Approximation (RMSEA) is considered acceptable if lower than 0.08 and excellent if lower than 0.05.To verify the compatibility of the proposed model and the empirical data obtained, verification of the model’s fit was performed. Goodness of fit was calculated using diverse indices proposed by Marsh . In the In total, 31.7% of the students affirm that they have been cyberbullied on at least one occasion during the past year. The most frequent cybervictimization behaviors were as follows: receiving offensive or insulting messages via mobile phone or the Internet (16.6%), having their blog or email passwords stolen (9.3%), being defamed over the Internet (8.5%) and receiving anonymous calls to frighten them (8.3%) or receiving messages containing threats or blackmail over the mobile phone (6.1%). p . This index, however, cannot be interpreted in this standardized manner, and there is also the problem of its sensitivity to sample size [The proposed structural equations model revealed a good fit in all of the assessment indices. The Chi-squared test revealed a significant value of ple size . Therefop < 0.001), which are positive and direct, amongst all of the Self-concept dimensions. In addition, there are positive and direct relationships between Aggressiveness and its dimensions (p < 0.001), as well as between School anxiety and the indicators making it up (p < 0.001), with all of the associations being positive and direct.In p < 0.001, with direct and positive relationships. As for Self-concept, relationship with peers (r = 0.93) is the indicator having the highest coefficient, followed by relationship with parents (r = 0.86), physical appearance (r = 0.84), physical ability (r = 0.82), Self-concept in language and general self-concept (r = 0.77) and, ultimately, Self-concept in mathematics (r = 0.62), having the lowest levels. For Aggressiveness, the greater association was found in anger (r = 0.77), followed by verbal aggression (r = 0.81), hostility (r = 0.80) and with a lower association, physical aggression (r = 0.77). Finally, the factors that best make up School Anxiety are anxiety related to academic assessment (r = 0.76) and anxiety related to social assessment (r = 0.74).Upon analyzing the factorial loads of the indicators corresponding to latent variables, it may be observed that they all have statistically significant differences at a level of p < 0.001). Therefore, Self-concept is negatively and directly related to Cybervictimization (r = −0.82). Along the same lines, the relationship between School Anxiety and Cybervictimization is negative and direct (r = −0.11), with no statistically significant association being found between Aggressiveness and Cybervictimization (p = 0.186). Finally, a direct and negative relationship has also been observed between Self-concept and School Anxiety (r = −0.14) and a direct and positive relationship is seen between Aggressiveness and School Anxiety (r = 0.49). Statistically significant indirect effects have not been observed (p > 0.05) between Aggressiveness and Cybervictimization (r = −0.053) and between Self-Concept and Cybervictimization (r = 0.015) through School Anxiety. Therefore, School Anxiety does not act as a mediator in the cited relationships.In addition, significant associations are observed between the variables . However, our results did not support this hypothesis. Evidence is contradictory to that of other past studies that have found that aggressiveness, in the form of anger, is directly related to cybervictimization ,42,43. TAs for school anxiety, the results suggest the existence of a negative and significant association between the variables, thereby rejecting hypothesis 3. These results are contrary to those of past studies, which have situated high anxiety as a variable that explains cybervictimization ,51, possOn the other hand, self-concept is shown to be positively related to aggressiveness, and therefore, hypothesis 4 was not supported. The results are contradictory to those of Esteve et al. , who affSelf-concept has been found to be negatively associated with school anxiety, confirming hypothesis 5. These findings are consistent with Gonzálvez et al. , who shoThe positive and significant relationship between aggressiveness and school anxiety is in line with past studies, and thereby confirms hypothesis 6. Therefore, as suggested by past works, students with a moderate profile and high level of school anxiety declared to have suffered from more episodes of scholastic violence , as wellIn general, the structural equations model created adjusted adequately and explained 67% of the cybervictimization phenomenon, based on two latent variables: self-concept and school anxiety. Both self-concept and school anxiety acted as protective factors against electronic bullying. In addition, it has been shown that the interaction between aggressiveness, self-concept, and school anxiety is significant, but the latter does not act as a mediating variable for aggressiveness with regard to cybervictimization.This study has various limitations, mainly the limited number of works on cybervictimization in primary school education, which hinders the comparison of its results with those of past studies. In addition, given the study’s cross-sectional design, it is impossible to establish causal relationships. Therefore, new research lines are available for longitudinal studies that may offer information over time. Finally, there is a lack of consensus in terms of defining the cyberbullying concept, making it necessary to update the same, given the constant advances taking place in the ICT. Finally, it is important to note that the study focuses only on the role of victim, which does not allow us to assess the possible relationship between the variables and the other figures involved in cyberbullying.This study offers novel and relevant information on the study of cyberbullying, specifically in the explanation of the role of the cybervictim. On one hand, it demonstrates the existence of cybervictimization at early ages, and, on the other hand, it highlights the risk and protection factors that explain being bullied with ICT. Specifically, minors having higher levels of self-concept may be more protected from becoming online victims. Additionally, high levels of school anxiety may also explain lower participation, suggesting that some scientific conclusions referring to secondary students may not be fully applicable to younger students. In addition, aggressiveness was not found to be an explanatory variable for cybervictimization, although it did have a direct relationship with self-concept, revealing that, at these young ages, being a bully may be related to having a positive self-image which, at the same time, may decrease the risk of being cybervictimized. In addition, aggressiveness positively explained the high scores received on school anxiety. All of this reinforces the need to conduct prevention campaigns during later years of primary school education to promote self-concept, so as to ensure better psychological adjustment and personal competence, helping youth develop an adjusted scheme of themselves and thereby empower them in the face of potential cyberbullying situations. In addition, it also offers relevant information about the variable aggressiveness and school anxiety, as well as the relationship between both, with great relevance to the study of psychosocial variables in minors in order to contribute to an integral development and enhance their well-being.Considering the most significant findings, this study opens new lines of research that include the other roles participating in the dynamics of cyberbullying, that is, bullies, bystanders, and bully-victims, in order to create differentiated profiles of each role that guide in the development of effective prevention and intervention programs in the fight against cyberbullying. In addition, it would be necessary to specify which dimensions of each variable are more related to the dynamics of each role, in order to specify the lines of action as much as possible, as well as to replicate the study with students of different educational levels.


We report the case of a 3-years-old boy who developed severe hyponatremia and unconsciousness during an episode of Kawasaki disease (KD). He was diagnosed with cerebral salt-wasting syndrome (CSWS), which has not previously been reported as a complication of KD. He was diagnosed with KD with fever and four clinical signs and received intravenous immunoglobulin (IVIG) on the day after onset. Hyponatremia had been observed, and it worsened after IVIG. At first, syndrome of inappropriate antidiuretic hormone secretion (SIADH) was suspected, but his hyponatremia did not improve by restriction of water intake. The patient's consciousness level decreased along with the worsening hyponatremia. Electroencephalography revealed abnormal electrical discharge concordant with acute encephalopathy. Laboratory data showed hypouricemia with high fractional excretion of uric acid (FEUA), in addition to a negative balance of both Na and water. We diagnosed KD complicated with CSWS. The patient improved promptly with appropriate Na supplementation and water correction. Cerebral salt-wasting syndrome (CSWS), a complication associated with central nervous system (CNS) diseases, is known to cause hyponatremia and dehydration due to excessive discharge of Na and free water . HyponatA 3-years-old boy was brought to our hospital by his parents because of fever, conjunctival congestion, and rash on the body, all of which appeared the previous day. He did not have any pertinent medical or family history.At the outpatient clinic, his body temperature was high, and bilateral conjunctival congestion, reddened lips, bilateral cervical lymphadenopathy, and erythema all over the body were noted. Even though the duration of the fever was only 2 days, KD was strongly suspected due to the other symptoms present, and he was hospitalized for treatment.SD), and his weight was 13.4 kg (−0.1 SD). Body temperature was 39.3°C, pulse rate 153/min, and blood pressure 106/64 mmHg. Other principal signs of KD such as erythema of palms and soles or redness at the BCG inoculation site were not observed. Thoracoabdominal physical findings were normal, and capillary refill time was <2 s.On admission, his height was 96.7 cm  for the left main trunk, 1.6 mm (Z score – 0.36) for the left anterior descending branch, 1.5 mm (Z score – 0.09) for the circumflex brunch, and 2.2 mm (Z score + 1.25) for the right coronary artery. Aortic and mitral valve regurgitation and pericardial effusion were not observed.Chest roentgenogram showed no heart enlargement or pleural effusion. There were no abnormalities in the electrocardiogram. The largest coronary artery inner diameters by echocardiogram were 1.8 mm (Intravenous immunoglobulin (IVIG) treatment and oral aspirin were started on day 2 under the diagnosis of KD . The fevHis consciousness was estimated as Glasgow Coma Scale 12 . Although dehydration was not clearly evaluated, the intake/output balance of water and Na was negative, urine Na was 140.1 mEq/L, plasma osmotic pressure was 263 mOsm/kg, and urine osmotic pressure was 641 mOsm/kg. In addition, renin–aldosterone did not increase. On day 6, in addition to the correction of water balance, hypertonic saline was started to correct Na.Although the brain magnetic resonance imaging (MRI) did not show abnormalities on day 7, the electroencephalogram (EEG) showed diffuse slowing of the background activity, and acute encephalopathy was considered on day 8 . Since tCSWS is a syndrome based on CNS disorders in which inappropriate Na loss in urine causes a decrease in fluid volume and hyponatremia. It is known to occur in connection with head surgery, head trauma, or subarachnoid hemorrhage, but in recent years, CSWS associated with meningitis, encephalitis, and encephalopathy have been reported , 6. The In our case, consciousness was impaired during treatment of KD, and although the brain MRI was normal, EEG showed generalized slowing of the background activity. Bladder and rectal disturbance was also recognized as a sign of encephalopathy. It is considered that encephalopathy caused suppression of the efferent sympathetic nervous system to the kidney, suppression of the renin–angiotensin system, and loss of Na and uric acid in the proximal tubules together with the decrease in extracellular fluid volume. Furthermore, humoral factors such as BNP may suppress the renin–angiotensin system and antagonize vasopressin in collecting ducts, possibly accelerating the development of CSWS.When diagnosing CSWS, differentiation from SIADH is essential because distinctly different treatments are required for each condition. CSWS requires water correction and Na loading, while SIADH requires water restriction, and an incorrect diagnosis may worsen either condition. Despite the differences of pathogenesis, with loss of Na and water in CSWS and dilution of serum by water retention in SIADH, both conditions exhibit hyponatremia and have similar laboratory findings. In both conditions, serum osmotic pressure decreases, and urine osmotic pressure increases, while urine Na elevates. Plasma antidiuretic hormone (ADH) levels may also elevate in CSWS; however, it usually takes a few days to get these results. The presence or absence of dehydration and the intake/output balance of Na and water are more useful in differentiating between CSWS and SIADH. Since CSWS patients lose both Na and water, their balances become negative; extracellular fluid decreases, and patients become dehydrated. In SIADH, intake/output balance of Na and water is equal or positive, and extracellular fluid increases due to the increase in ADH.While the presence or absence of dehydration is an important index for diagnosing CSWS in the early stage of the disease, it is difficult to evaluate the amount of extracellular fluid in children. Measurement of extracellular fluid volume using radioisotope dilution is considered to be effective in terms of accuracy but is not practical in clinical use . Also, BIt is reported that changes in serum uric acid level and fractional excretion of uric acid (FEUA) are useful for differential diagnosis , 13. TheIn recent years, there have been sporadic reports of conditions similar to CSWS without CNS disease, and the concept of the disease is changing to renal salt-wasting syndrome . AlthougAll datasets presented in this study are included in the article/supplementary material.Written informed consent was obtained from the minor(s)' legal guardian/next of kin for the publication of any potentially identifiable images or data included in this article.MO, JF, TNot, TNog, and MM were responsible for patient care. MO and MA prepared the draft manuscript. IM gave conceptual advices. All authors critically reviewed and approved the final manuscript.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.


Accumulating evidence links nut consumption with an improved risk of metabolic syndrome (MetS); however, long-term trials are lacking. We examined the effects of a daily dose of walnuts for two years on MetS in a large elderly cohort. A total of 698 healthy elderly participants were randomly assigned to either a walnut supplemented or a control diet. The participants in the walnut group were provided with packaged walnuts  and asked to incorporate them into their daily habitual diet. The participants in the control group were asked to continue with their habitual diet and abstain from eating walnuts and other tree nuts. Intake of n-3 fatty acid supplements was not permitted in either group. Fasting blood chemistries, blood pressure, and anthropometric measurements were obtained at baseline and at the end of intervention. A total of 625 participants  completed this two-year study (90% retention rate). Triglycerides decreased in both walnut (−0.94 mg/dl) and control (−0.96 mg/dl) groups, with no significant between-group differences. There was a non-significant decrease in systolic and diastolic blood pressure in the walnut group  and no change in the control group. Fasting blood glucose decreased by ~1 point in both the walnut and control groups. There were no significant between-group differences in the development or reversion of MetS. In conclusion, supplementing the diet of older adults with a daily dose of walnuts had no effect on MetS status or any of its components, although the walnut group tended to have lower blood pressure. Metabolic syndrome (MetS) is a cluster of risk factors that increases an individual’s risk of developing cardiovascular disease (CVD) and type-2 diabetes mellitus (T2DM) . The coeThe worldwide prevalence of MetS ranges from 20 to 30% of the adult population . In the Diet and exercise have been proposed as the main strategies for the prevention of MetS . ConcernWe had a unique opportunity to examine the effects of walnuts on MetS over a two-year trial in a free-living healthy elderly population participating in the Walnuts and Healthy Aging (WAHA) study. We were primarily interested in determining the incidence and reversion rates of MetS in addition to assessing the effect of walnuts on individual MetS components.2], had uncontrolled diabetes or hypertension, or were allergic to walnuts were excluded from the study. This study is a secondary data analysis within the WAHA study, a two-year, dual center, randomized clinical trial examining the effects of daily walnut consumption on age-related cognitive decline and macular degeneration . In briePrior to randomization, subjects who met eligibility criteria completed a three-day food record and filled in a physical activity questionnaire. Subjects were then randomized to either the walnut or control group. Those in the walnut group were provided with packaged walnuts equivalent to approximately 15% of their daily energy needs, to incorporate into their daily habitual diet. Walnut dosage was determined utilizing the World Health Organization energy needs equation for adults >60 y . Based oBody mass index (BMI) was calculated from height and weight, which were collected at baseline and at end of study. Height was measured with a wall-mounted stadiometer. Body weight was determined with a digital precision scale. Blood pressure was measured at baseline and at scheduled bimonthly clinic visits using an Omron BP762 Series blood pressure cuff. A total of three blood pressure measurements were obtained at three-minute intervals and the mean of the last two measurements was recorded ,25. Over2 in men and ≥ 27.2 kg/m2 in women could be used as surrogate measures to define central obesity in the absence of waist circumference data [MetS was defined according to the harmonized criteria of the Adult Treatment Panel III (ATP III), which requires the presence of at least three of the following five components for diagnosis: (a) abdominal obesity (waist circumference) larger than 102 cm for men and 88 cm for women; (b) triglyceride levels of 150 mg/dL or higher, or taking fibrate medication; (c) HDL-C of less than 40 mg/dL for men and 50 mg/dL for women; (d) blood pressure of 130/85 mmHg or higher, or taking antihypertensive drugs; and, (e) fasting blood sugar of 100 mg/dL or higher, or taking antidiabetic medications [nce data .The participants visited the research center bi-monthly throughout the two-year study period, during which they were provided with a two-month supply of walnuts, depending on group assignment. Further, the research dietitian assessed participants for subjective compliance to study protocol, potential side effects, and offered motivation to encourage retention. Those in the walnut group were provided with extra walnuts to take family needs into consideration. Quarterly educational group activities were offered to participants in the control group to improve retention, since no active intervention was provided to them. Objective compliance to the intervention was determined by using nutrient analysis from dietary recalls and by assessing the red blood cell content of ALA, a fatty acid characteristic of walnuts , as propDietary intake was assessed while using five unannounced 24-hour diet recalls (LLU) or three-day food records that were obtained every six months (BCN) over the two years of the study. Participants answered an abbreviated version of the Minnesota Leisure Time Physical Activity Questionnaire to evaluate their level of physical activity, which has been previously validated in the United States  and SpaiThe subjects in both groups were classified as either having or being free of MetS at baseline and at two years. The MetS incidence rate was computed among those who were free of MetS at baseline and developed MetS during the two years of follow-up. Additionally, the reversion rate was computed after two years among those who were classified as having MetS at baseline but were free of MetS after follow-up.Marginal logistic models using generalized estimating equations (GEE) were used to compare the effect of supplementing the diet with walnuts for two years (compared to control) on the prevalence of MetS. Logistic regression was used to evaluate MetS development or reversion after 2 years among the walnut treatment and control groups. Center, sex, age, weight, physical activity, smoking status, and hypolipidemic, antihypertensive, and antidiabetic drug use were added to the models to account for potential confounding by these factors.P < 0.05. All analyses were performed using Statistical Analysis System .Chi-square contingency tests were used to compare the categorical and qualitative variable distributions between the intervention and control groups. Mixed linear models were used to investigate changes in blood pressure, BMI, HDL-C, triglycerides, and fasting blood glucose, accounting for both within person (time effect) and between treatment effects adjusting for baseline status of MetS and relevant demographics. Statistical significance was achieved at t-tests to compare means across groups, skewness and kurtosis measurements were assessed in tests for normality. For mixed linear models on changes in MetS components, the assumption of normality was assessed by a visual inspection of residual plots and normal probability plots. A log-transformation was applied when residuals were right-skewed. For such outcomes, differences of adjusted means on the log scale were back-transformed, yielding mean ratios. When applying n = 299 and BCN, n =326); mean age = 69.1; 67% female. While the retention rate of the study was 90%, seventy-three participants  dropped out due to loss to follow-up, voluntarily left study, health issues , wish to eat walnuts, digestive intolerance to walnuts, and death (n = 1) that were unrelated to the study interventions. The dropouts were not significantly different from completers. As for completers, there were no significant differences between the walnut and control groups regarding baseline characteristics. P < 0.05). The walnut group showed a greater decrease in systolic  and diastolic  blood pressure as compared with the control group. We evaluated the incident and reversion rate of each component of MetS, but we did not find any significant difference in any of the parameters. Therefore, we only report the continuous variables that are presented in P = 0.56; walnut = 1.25, 95% CI, 0.89–1.75, P = 0.19) without significant between-group differences (P = 0.62). We found no difference in the results between men and women. Therefore, P = 0.40). When compared to the control, the walnut group showed increased odds of developing MetS . Additionally, the two-year time period did not significantly alter the results for reversion and incident rates. It is worth mentioning that running the analysis without controlling for body weight did not change the results among all models. We have performed the analysis considering the location of the study. However, we found no significant difference in outcomes of metabolic syndrome and its individual outcomes between the USA and Spain cohorts. Therefore, data from both locations were combined to obtain more statistical power.The results of our study indicated that supplementing the diet of older adults with a daily dose of walnuts and no other dietary advice for two years resulted in neither an adverse effect on development of MetS nor its reversion. Even so, we observed a trend towards a beneficial effect of walnut consumption on blood pressure, a finding that has been reported in previous nut studies ,32,33,34P = 0.34) [We did not see a beneficial effect of walnut consumption on other components of MetS . Our findings are similar to those of a six-week randomized trial in Korea that found no significant difference in BMI, waist circumference, systolic blood pressure (systolic BP), HDL-C, triglycerides, and blood glucose between a control diet and a diet that was enriched with 30 g/day of mixed nuts  . The pos = 0.34) . This co = 0.34) .P = 0.3) [P < 0.01) but not men [Overall, our study showed that, when compared to a control diet, a walnut-enriched diet for two years resulted in no significant between-group differences in the development or reversion of MetS. Similar findings have been reported in other studies ,39,48. AP = 0.3) . A randoP = 0.3) . AnotherP = 0.3) . Additio not men . The one not men . P = 0.02) [Moreover, cross-sectional studies have shown that increasing nut consumption is associated with a decreased prevalence of MetS ,50 and i = 0.02) . A crossAlthough there are no clear reasons for the null findings that were observed in our study, we speculate several factors that could explain the results. First and foremost, previous studies have shown that elderly individuals tend to lose lean body mass and gain fat over time ,52,53, aSupplementing the diet of older adults with a daily dose of walnuts at 15% of energy resulted in no adverse effect on MetS or any of its components. A trend towards a beneficial effect in blood pressure was observed in the walnut group. Therefore, incorporating walnuts into the habitual diet of healthy elderly might lead to a favorable modification of risk factors that are associated with chronic diseases. Although the role of walnuts in modifying MetS components favorably needs further investigation, it is reasonable to recommend the inclusion of walnuts to the habitual diet of healthy elderly given that walnuts have been shown to lower the risk for CVD ,44 and i


To develop the medication literacy scale for patients with hypertension, and to test the reliability and validity of the scale.The initial draft of the scale was formulated based on the operationalization of medication literacy with four core elements of knowledge, attitude, skill, and practice, and was developed through procedures of literature review, interviews to hypertensive patients, and research group discussion. Expert panel meeting, interviews, and pre-test on the initial draft of the scale to 10 hypertensive patients, as well as a two iterations of expert feedback were used to form a primary medication literacy scale for pilot investigation and item selection. In this study, 260 patients with hypertension in Changsha city of China were purposively selected to conduct a pilot survey using the primary medication literacy scale. After item selection by a series of statistical analysis method and item re-wording according to patients’ feedback, the scale was revised to form a formal investigation scale with four domains and 37 items. A formal investigation was carried out on 650 patients with hypertension selected purposively in a tertiary general hospital and two community health service centers in Changsha city of China. The reliability and validity of the scale were analyzed.2/df=2.629, GFI=0.804, AGFI=0.777, RMR=0.012, IFI=0.746, RMSEA=0.066, PNFI=0.599, PCFI=0.689), which indicated an acceptable model fit.Finally, the formal scale consists of four domains on knowledge, attitude, practice and skills, 11 sub-factors and 37 items in total. The scale-level content validity index (S-CVI/Ave) of this scale was 0.968, and the I-CVI for each item ranged from 0.833 to 1.000, indicating a good and acceptable content and face validity. The Cronbach’s α coefficient was 0.849 for the overall scale and ranged from 0.744 to 0.783 for domains. The Pearson’s correlation coefficients between domains and the total scale were ranging from 0.530 to 0.799. Besides, the Pearson’s correlation coefficient among domains of the scale ranged from 0.157 to 0.439. The Spearman-Brown split-half reliability coefficient was 0.893 for the total scale and ranged from 0.793 to 0.872 for domains. The test-retest reliability coefficient of the total scale was 0.968 and ranged from 0.880 to 0.959 for domains. Four domains of knowledge, attitude, skill, and practice were identified through the exploratory factor analysis and confirmatory factor analysis from each domain. The total explained variation of domains for the overall scale was 51.420%. Eleven sub-factors for domains were extracted through respective exploratory factor analysis from each domain, and the total explained variation of sub-factors for its belonging domain were ranging from 56.111 to 64.419%. The confirmatory factor analysis showed the fit indices of the four-domain model were as follows (χThe medication literacy scale for hypertensive patients has good reliability and acceptable validity, which is suitable and acceptable for evaluating the medication literacy level of hypertension patients in China. In the future, further construct and model fit validation and English translation with appropriate adaptation of this whole scale are required, so that this scale can be further validated and applied worldwide. Medication safety problem has always been the focus of healthcare providers and public health community scholars. Researches across the globe reported that there were certain safety problems in medication taking process for hypertensive patients . This pret al. developed the first Chinese medication literacy measure for general population mainly based on evaluating patients’ abilities and skills to interpret medication information sheets or instruction labels of prescription or non-prescription medicines  type of information necessary for optimal and safe use of medication, 2) skills and abilities, 3) format of information, and 4) the outcomes and goals of medication literacy. In this four elements, type and format of information that is necessary for optimal and safe medication use was emphasized. The medication related information is always appearing on doctor’s prescription sheets or on medication instruction labels inserted in the pill boxes in China. Therefore, it is very important that patients can read, understand and calculate according to the information on the medication instruction labels and prescription sheets. It is feasible and applicable to involve print information for medicines in assessing patients’ skills of using medication and it is also very important. Furthermore, patients’ skills, e.g., how to interpret medication labels such as dosing and measurements was also emphasized in the development of medication literacy measure . In addiedicines . Medicatalculate . TherefoKnowledge for medication specific for patients with certain kinds of disease was also incorporated in the concept of pharmacotherapy literacy and medication literacy . TherefoOne of the clusters representing identified in the international consensus study of the concept of medication literacy is the outcomes and goals of medication literacy . OptimalSafe and correct self-medication was a leading contributor to the optimal blood pressure control for hypertensive patients . For hypHowever, there is a dearth of specific medication literacy scale for hypertensive patients currently, although several medication literacy measurements for general population have been found . PharmacHence, based on previous literature research and operationalized elements of medication literacy, a specific assessment scale of medication literacy for Chinese hypertensive patients has been developed in the present study, and four domains of knowledge, attitude, skill, and practice were included, the reliability and validity test were also performed.An initial draft of the scale (52 items) was developed through literature review, hypertensive patient interview, and house group discussion in research group. Subsequently, the initial drafted item pool was assessed in an expert panel meeting, applied in a pre-test performed to 10 hypertensive patients and the feedback was recorded to remove or revise items. Therefore, a primary medication literacy scale with 41 items was reached. In addition, another two items were excluded according to feedbacks and ratings of a two-round expert consultation. Finally, the 39-item primary scale was used to conduct a pilot study with 260 hypertensive patients. After item selection with several statistical analysis, an ultimate medication literacy scale with 4 domains and 37 items was completed. The flow chart of the scale development procedure and the detailed final 37-item scale has been attached as Knowledge-Attitude-Practice model , health Based on the concept of medication literacy and its four core elements, the operationalized framework of medication literacy for hypertensive patients with four domains of knowledge, attitude, skill, and practice was identified. Firstly, we established an indicator system of medication literacy for hypertensive patients based on the operationalized four core elements. Then the initial item pool of this scale was developed based on this indicator system accordingly.Methods for development of initial item pool:Related literature review of existing researches about instruments for assessing medication literacy level of general population or some other disease-specific population, some items were extracted and adapted from these existing medication literacy questionnaires or scales. Some of the items were formulated referring to existing measurements for assessing hypertension treatment adherence and to those studies on medication use for hypertensive patients.The results of interviews on hypertensive patients’ antihypertensive medication taking and hypertension disease management. All items were developed based on the four core elements of hypertensive patients’ medication literacy of knowledge, attitude, skill, and practice.Then, after research group discussion, an initial draft of the scale with 52 items was reached through the above procedures.An expert panel meeting was convened, related experts specialized in cardiovascular research and pharmaceutical research were invited to examine the clarity of drafted items as well as each item’s relevance and appropriateness to its belonging construct. Some inappropriate items were removed or revised and some highly relevant extra items suggested by experts were supplemented;Interview and pre-test of the initial drafted scale to 10 hypertensive patients: after items were revised according to the advises in expert panel meeting, the revised initial drafted scale from above were applied to the interviews performed to 10 recruited hypertensive patients. The questions as well as suggestions put forward by interviewed patients on each item of the revised initial drafted scale were recorded, according to which complex items with technical words that were hard to understand by patients were revised;Focus group discussion: the advices of expert panel meeting and the results of pre-test interviews for hypertensive patients were integrated and synthesized through discussion by research group, resulting in a 41-item scale after appropriate revisions to items and 11 items removed. Furthermore, there were another two items being removed according to suggestions generated from a two-round expert consultation. Therefore, a primary medication literacy scale for hypertensive patients involving 39 items was accomplished.Six experts have been also invited to participate in a two-round expert consultation to appraise on the construct and items of the primary medication literacy scale with 39 items in this study. Based on every expert’s understanding of the definition and connotation of hypertensive patients’ medication literacy, as well as its four core elements, constructive amendments, and item suggestions were required to be given. Therefore, supplements, expurgations, and revisions to some items or contents have been made accordingly.Inclusion criteria for experts: a. with over 10 years of work experience in the cardiovascular department; b. with doctoral degree or above; c. at least with professional title of associate professor or with deputy director or above; d. experts who master in the development and psychometric assessment of a scale; e. experts who were interested in this research and willing to offer advices or suggestions. Finally, two clinical pediatric professionals, two nursing professionals specialized in hypertension management and psychometric assessment on scale, and two pediatric pharmaceutical professionals were involved.*)  . Therefo*) , items w*) . SignifiPurposive sampling method was applied, and a total of 260 hypertensive patients collected from a tertiary hospital and a community health service center in Changsha city of China were participated in this pilot survey. The primary medication literacy scale with 39 items was used as investigation tool. Inclusion criteria were as follows: Patients who a. were diagnosed as hypertension according to the 2016 revised version of guidance for hypertension prevention and treatment in China, which is systolic BP>=140 mmHg or diastolic BP>=90 mmHg; b. have been on antihypertensive treatment and taking antihypertensives for at least 2 weeks, these included both those newly diagnosed and being treated with antihypertensive medication for a short period of time and those who were already on antihypertensive medication treatment for a longer period of time; c. aged over 18 years old; d. can communicate with others and have the ability of reading and comprehension; e. were willing to participate in this study and signed the consent forms; exclusion criteria were as follows: patients who a. were diagnosed as psychologically and mentally ill by ICD or have been on a mental pharmacotherapy; b. have severe or acute hypertension or other uncontrolled cardiovascular and cerebrovascular diseases such as heart failure in New York Heart Association Class III or IV, or unstable angina; c. have dementia or cognitive impairment, severe diseases of other organs or systems, such as cancer; d. were with hearing and communication disability.In the process of the investigation, the problems of item understanding and wording as well as construct of the primary assessment scale were checked again, and questions about the clarity and accuracy of the expression of each item were recorded.Meanwhile, collected data were statistically analyzed using IBM SPSS 25.0 for item selection. After item selection based on the results of a series of statistical analysis, a complete and final medication literacy scale can be developed. During the period of questionnaire investigation, participants’ timely feedback on items or the whole questionnaire was focused on and improvements were made. Items that were questionable or confusing for participants were given appropriate revision.In this pilot survey, out of the 260 distributed questionnaires, a total of 252 completed questionnaires were collected back and checked validity. The response rate was 96.60%. Statistical analysis methods for item selection were used. Item discrimination of t-test, Cronbach’s alpha (α) were calculated to remove or revise items.Methods for item selection:Item discrimination analysis: total scores of collected questionnaires were listed in sequence of numeric value from high to low, among which 27% of the collected questionnaires with high total scores from the highest one were defined as high score group, 27% of the collected questionnaires with low total scores from the lowest one were defined as low score group, then scores of each item in two groups was tested difference using independent t-test method. Items with scores that have no significant difference between in high score group and in low score group were excluded.r < 0.3 were removed (P < 0.05). Considering the specialty practicalities, appropriate item remove and revisions were made.Correlation coefficient method: the Pearson’s correlation coefficients were calculated, including those between each item and its belonging domain, between each item and the overall scale, as well as the Pearson’s correlation coefficient between each domain and the whole scale. Items with Pearson’s correlation coefficient In formal investigation stage of this research, purposive sampling method was used. Four hundred hypertensive patients were collected from inpatient and outpatient departments of a tertiary hospital in the city of Changsha, China, 250 hypertensive patients were collected from two community health service centers in Changsha city of China from April to June, 2016. Therefore, a total of 650 eligible hypertensive patients participated in this investigation. Out of the 650 distributed questionnaires, 637 were collected back and checked completion and validity. The response rate was 98.00%. Among these participants, they aged from 18 to 90 years old, and the average age of them was (57.49 ± 15.12) years; in addition, 336 out of 637 participants were male (52.7%), 542 has been married (85.0%), 149 participants had an education level of primary school or below(23.4%); 462 participants were employed (72.5%); 220 (34.5%) participants have been diagnosed as hypertension for more than 10 years; 421 (66.1%) participants had a family history of hypertension  and the content validity index of the whole scale (S-CVI/Ave) . The calConstruct validity of this scale was assessed by conducting exploratory factor analysis to identify its constructs and to assess whether data was grouped as anticipated. Confirmatory factor analysis was conducted to confirm the identified constructs and principal components with related indices.2/df), the goodness-of-fit (GFI), absolute goodness-of-fit (AGFI), root-mean-square error of approximation (RMSEA), and standardized root mean square residual (SRMR) were calculated. In addition, incremental fit indices (IFI), parsimony fit index including parsimony normed fit index (PNFI), parsimony comparative fit index (PCFI) were also noted  values. A value of at least 0.7 was considered satisfactory internal reliability . SpearmaThis research scale measured medication literacy level of hypertensive patients across four domains namely knowledge about hypertension disease, treatment, and antihypertensive medication, attitude, skill, and practice for medication administration. For items in domains of knowledge and skill, answering right for each item scores 1, and answering wrong or answered “I don’t know” scores 0. A response option of 5-point Likert scale for each item in attitude domain was used , in which scores of 1.0, 0.75, 0.5, 0.25, 0 were applied accordingly. In the practice domain, a response option of 5-point Likert scale was also applied for each item , and scores of 1.0, 0.75, 0.5, 0.25, 0 were also used accordingly. In addition, there were five items in the attitude domain and one item in practice domain scoring reversely. The summed total score on this 37-item scale ranged from 0 to 37, with higher scores indicating higher medication literacy level.An initial entry pool of 52 items was established in this study at the beginning. Then, a scale with 41 items was developed after 11 items were excluded through expert panel meeting, interviews, and pre-test to several patients as well as the focus group discussion. Subsequently, the primary medication literacy scale for hypertensive patients with 39 items for pilot survey has been formed after 2 items being excluded according to suggestions generated from the two-round expert consultation. Finally, two items with low discrimination were excluded after analysis of item discrimination and correlation coefficient method on the collected data from pilot survey. . After pilot study and item selection analysis, the final and formal medication literacy scale for hypertensive patients has been accomplished, and 4 domains with 37 items were identified. Knowledge domain (K) includes 9 items, attitude domain (A) involves 8 items, skill domain (S) has 7 items, and practice domain (P) has 13 items.Based on the feedback of the two-round expert consultation, two items in the attitude domain were removed. The results of the expert consultation also showed that the individual authority coefficient of each expert ranged from 0.79 to 0.97, the integrated authority coefficient of all experts was 0.92, indicating that the appraisements and suggestions generated from this expert panel were relatively authorized and can be trusted. The active coefficient for all experts in two rounds of expert consultation was 1, which means that each expert in this consultation stage was willing and active to participate to appraise on this scale.* values  of each item in this scale ranged from 0.833 to 1.000, which were all > 0.78 ; the S-CExploratory factor analysis (EFA) was conducted. Principle component analysis with Varimax rotation was employed to analyze the construct and factor structure of this scale and of each domain. Two hundred and fifty-seven collected questionnaires were randomly abstracted from total questionnaires of 637 to conduct the exploratory factor analysis for the scale. Sampling adequacy and factorability of a correlation matrix were evaluated. Kaiser–Mayer–Olkin (KMO) test for the overall scale and its four domains indicated that the sample size for this scale were adequate with values of 0.715 for the scale, and of 0.765, 0.766, 0.713, and 0.808 for its domains, i.e., KMO > 0.7 , BartletThe results of EFA showed that four components with eigenvalues > 1.0 were identified . Items wAccording to factor loadings for 37 items in the present study, 37 items contributed to four components respectively. However, in our results, the factor loadings of 37 items for its belonging components were not so good. Suboptimal item factor loadings for anticipated domains for 37 items in this sample were generated, the total explained variance of four components for the overall scale in our sample was 51.42% .2/df was 2.629, i.e., < 3. Therefore, all indices except IFI, GFI, and AGFI, meet the fitting requirements, demonstrating that the four-domain model had acceptable factorial validity in current sample , indicating an average to strong association between the scale and its domains was identified. The Pearson’s correlation coefficients among domains ranged from 0.157 to 0.439 (P < 0.01) , confirming the consistency of the scale and its subscales (domains) over time . In thisThis is the first study to develop a self-reporting medication literacy scale specific for hypertensive patients (MLSHP), which is also aimed at exploring the psychometric properties of MLSHP in Chinese hypertensive patients. Though, there were several existing medication literacy scales for general population. For example, Medication Literacy Assessment Scale in Spanish and English (MedLitRxSE) , which iIn the EFA of the present study, we identified four domains of knowledge, attitude, skill, and practice as anticipated, however, the factor loadings of items for the whole scale in each factor (domain) were not optimal. Therefore, we continued to do a sub-factor extraction from four domains. It turned out that 11 sub-factors have explained the variances for its belonging domains in a good way. The 11 sub-factors were exactly consistent with the indicator system of medication literacy for hypertensive patients we initially established. Firstly, the indicator system was generated based on the operationalized four core elements of medication literacy, the initial item pool was subsequently formulated based on the indicator system.CFA was conducted to test the goodness-of-fit for the identified four-domain model. All indices except IFI, GFI, and AGFI meet the fitting requirements. GFI, AGFI, IFI were 0.804, 0.777, 0.746, which were all near to 0.9. we considered that the four-domain model had acceptable factorial validity in current sample but the model fit still needs to be further confirmed.In addition, the standardized factor loadings and the latent correlations among factors (domains) testified that the four domains are not only relative independent but also correlated with each other, which was consistent with the anticipated relationship among four operationalized elements in the present study. Due to four domains of this scale were correlated with one another to some extent, we suggested that future study could also focus on conducting a path analysis among four operationalized elements of knowledge, attitude, skill, and practice, in order to figure out a specific interaction path among four elements and find the mechanism that how these four operationalized elements correlate or interact with each other.In the present study, content and face validity as well as construct validity were measured. Results showed that good content and face validity of this newly developed medication literacy scale for hypertensive patients was satisfactory, indicating that the items of this scale was appropriate to its domains as well as to its whole scale and consensus of experts on items were achieved.In this study, the internal consistency of this scale was measured. The Cronbach’s α coefficient of the overall scale for 37 items was 0.849. This was higher than the Cronbach’s alpha value reported by ChMLM scale among general population in Taiwan , i.e., 0In addition, this scale demonstrated a high acceptability among hypertensive patients with a response rate of 96.6 and 98%. Therefore, this newly developed scale is easy to use and fill in, which is pragmatic and applicable in assessing hypertensive patients’ medication literacy in China.The strengths established in this study: this is a new and the first specific patient-reported outcomes instrument for hypertensive patients; the developed scale in this study is proved with high patient acceptability, a rigorous and scientific procedure of measurement purification. In addition, greatly satisfied reliability, content validity, convergent and discriminate validity of this newly developed scale was confirmed.Limitations: the data collected was self-reported by patients, there is a key problem about the subjectivity of patients’ response to this medication literacy scale. Therefore, the quality and accuracy of the data collected in this study might be compromised. In addition, the construct validity for this medication literacy scale was not satisfactory enough according to the EFA results of the whole scale and the suboptimal indices of GFI, AGFI, and IFI in the CFA, i.e., < 0.9. Therefore, further study on this scale is still necessary in order to re-confirm the construct validity of the overall scale. The validation of this newly developed medication literacy scale for hypertensive patients in other sample of population in China is still needed, may be with some minor adaptations for items. Besides, English translation and validation and adaptation is also required for its international utilization.A newly self-reporting medication literacy scale for hypertensive patients was developed in Chinese language. The measurement property of this scale has been established, in which good reliability and acceptable validity were confirmed, suggesting its appropriateness and applicability to measure medication literacy level for Chinese hypertensive patients. Future study will be focused mainly on three aspects: first, further validation and adaptation of this scale, mainly on construct and model fit validation, is still needed; second, English translation is needed, so that this scale application can be further validated and adapted worldwide; finally, large-scale investigation of hypertensive patients’ medication literacy in China based on this scale is needed, so associated factors of hypertensive patients’ medication level could be found.All datasets generated for this study are included in the article/The studies involving human participants were reviewed and approved by the Ethics Committee of the Third Xiangya Hospital. The patients/participants provided their written informed consent to participate in this study.AL was in charge of the whole design. ZZ and SS were in charge of the paper writing and data collection. YD, ZS, FZ and SD made contributions to the statistical data analysis and data collection.This study was supported and funded by the Youth Program of National Natural Science Foundation of China (Project Grant Number: 71603290).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.