Nurses assigned to more than 15 patients were less likely to report a favorable practice environment , perceived lower person-centered care , and rated lower patient safety . Person-centeredness mediates the effect of nurse work environment dimensions on quality and patient safety. Medical and surgical nurses, working in a healthy environment, had a high level of person-centeredness, which, in turn, positively affected the reported outcomes. The function of person-centeredness was to complement the effects of the nurse work environment on care outcomes. Improving the nurse work environment (task-oriented) with a high level of person-centeredness (patient-oriented) was a mechanism through which future initiatives could improve nursing care and prevent patient harm.This study aims to explore the potential mediation role of person-centeredness between the effects of the work environment and nurse reported quality and patient safety. A quantitative cross-sectional survey collected data from 1055 nurses, working in medical and surgical units, in twelve Malaysian private hospitals. The data collection used structured questionnaires. The Hayes macro explored the mediation effect of person-centeredness between the associations of work environment dimensions and care outcomes, controlling nurses’ demographics and practice characteristics. A total of 652 nurses responded completely to the survey (61.8% response rate). About 47.7% of nurses worked 7-h shifts, and 37.0% were assigned more than 15 patients. Higher workload was associated with unfavorable outcomes. Nurses working in 12-h shifts reported a lower work environment rating (3.46 ± 0.41,  To Err is Human, the problem was not bad people in health care, but good people were working in inadequate systems that needed to be made safer [The provision of high-quality and safe patient care is a complex process. Nurses in the medical and surgical units frequently experience uncertain work practices that adversely affect their practice and patient care. Work practices in these units are numerous and challenging, and nurses are working in a complex work environment and dealing with patients with a variety of physical and psychological demands. Hence, providing satisfactory care for them is a significant concern. In their report de safer . Researcde safer ,3,4,5. Ade safer ,7. Howevde safer .Adverse events are an international concern. For example, in the United States, adverse events are the third leading cause of death . EvidencThe global health agenda of the next decade is to provide universal coverage with high-quality, safe, and person-centered care . ResearcThe Practice Environment Scale of the Nursing Work Index (PES-NWI) recognizes a professional practice environment as comprising five main dimensions: (1) nurse participation in hospital affairs, (2) nurse foundation for quality of care, (3) nurse manager’s ability and leadership support, (4) staffing and resource adequacy, and (5) nurse-physician relationship . PreviouIn the last decade, a growing literature has explored the relationships of the work practices environment and nurse reported quality and patient safety. Interestingly, most of this literature has explored the direct association of practice work environment and nurses’ reported outcomes. For instance, nurses who reported higher perceived quality and safety worked in a positive practice environment ,15,16. ETheoretically, this study proposed a model based on the Donabedian Theory for healthcare quality and incorporating the Systems Engineering Initiative for Patient Safety (SEIPS) model ,26. The In addition to these theories, introducing clinical and experiential quality concepts was required for a better understanding of human interactions with a work system. Clinical quality refers to task focus quality , and these refer to structural quality. In contrast, experiential quality refers to the patient-oriented quality to achieve patients’ preferences , which mPerson-centered care refers to engaging patients and their families in the process of care by providing effective communication and education of the treatment consequences and nutritional guide . Person-Few studies have used person-centeredness as a mediator ,12. ThesA cross-sectional study explored the potential mediating effect of person-centeredness between the relationship of nurse practice environment and nurse reported quality and patient safety. The study respondents were licensed nurses registered under the Malaysian Ministry of Health (MOH) in the medical and surgical units in Malaysian private hospitals. Malaysia is a constitutional monarchy federal country located in Southeast Asia with 14 states. The MOH operates the healthcare system in Malaysia, consisting of public and private hospitals. Hospitals in the private sector in Malaysia are part of international health systems for the provision of high-quality care for patients and citizens.Private hospitals were the study setting because of substantial adverse events that have been reported , and MalThis research used multi-stage stratified random sampling. This technique offered the opportunity for nurses from various states, hospital sizes, and shifts to be part of the sample. The criterion for hospital inclusion was those hospitals recognized by the Malaysian Association of Private Hospitals. Of the fourteen Malaysian states, only Perlis and Terengganu states have no private hospitals. Hospitals were stratified based on their respective sizes  in the remaining 12 states . A total of 10 hospitals were chosen from each stratum using simple random sampling. Stratifying a sample of organizations based on the size will ensure that each one had an equal chance of being selected. As a result, hospitals were stratified based on hospital size from small to large hospitals. Furthermore, all licensed nurses from all working shifts were invited to be part of this study.Medical and surgical ward nurses in twelve hospitals, in twelve Malaysian States, participated in the study to examine the mediation effect of person-centeredness between the relationships of practice environment dimensions and nurses reported quality and adverse events. Incident reports, patient records, and the Global Trigger tool, developed by Institute of Healthcare Improvement, are the most frequent instruments for tracking and measuring adverse occurrences in hospitals. In hospitals, however, only 10 to 20 percent of adverse events are documented, and 90 to 95 percent of those do not result in patient impact . FurtherStructural quality reflects the care setting features, such as resources , staff qualifications, and organizational governance . In thisProcess quality refers to the actual treatment process during the hospitalization . ProcessOutcome quality refers to the consequences of the treatment processes and procedures . It is tPatient safety is preventing patient harm or hospital-acquired conditions . HospitaNurses’ characteristics, such as nationality, age, gender, level of education, race, marital status, total years of experience, and experience in the current ward served as controls in the data analysis. Additionally, the study accounted for practice characteristics, including hospital size, accreditation and teaching status of hospitals, their total working hours in the last working shift, and the total number of patients under their care as controls in the study. Previous research used these characteristics as control variables with a significant relation to care outcomes in previous research .Appropriate ethical approvals were obtained from the ethical committee of hospitals that agreed to participate in the research. Furthermore, approvals from the original authors were granted to use the study instruments, including Lake to use PES-NWI for the nurse practice environment and the Planetree and Picker Institute for person-centeredness. The informed written consent forms were obtained from all nurses, which randomly selected from a variety of working shifts voluntarily participated in this study.After ethical approval was received from the hospitals, data were collected between January and March 2015. The data collection used structured questionnaires. The corresponding author visited nursing departments and nurse managers of medical and surgical wards in twelve hospitals and then explained the study’s aim and methods. Participation in the survey was voluntary, and the respondents provided their informed consent. They were assured that data were only for research purposes and would be confidential. The survey took place for two or three times at a place depending on the work shift available in the hospital. The managers have assisted the survey, in distributing and explaining the necessary actions to be done during answering the questionnaires. There were cases, where the managers of the hospital willingly to receive the questionnaires and did the data collection in-house, the researcher just came back to receive the questionnaires. All participants returned the survey in a sealed envelope. The survey collected data from 1055 nurses working in medical and surgical units.Factor analysis and Cronbach’s alpha coefficient assessed the validity and reliability of the variables. Factor analysis was assessed by Kaiser–Meyer–Olkin (KMO) value and loading factor of the study items, and items with a factor loading of more than 0.50 were retained for further data analysis. The PES-NWI composite mean value was 3.57 with KMO value = 0.88, and Cronbach’s alpha = 0.87 and were more than the recommended value of 0.60 for validity and reliability ,46. CronThe data analysis used the Statistical Product and Service Solution (SPSS) software version 21 . Descriptive statistics illustrated the demographics and practice characteristics of nurses. Analyses of the t-tests and one-way ANOVA identified the relationship of nurses’ work environment, perceived person-centeredness, nurses’ rated quality, and patient safety to their demographic and practice characteristics.A variety of methods examined the mediation effects. This study used the SPSS Hayes macro method to examine the mediation effect of person-centeredness, as it provides multiple and straightforward mediations to explore the indirect processes . FurtherOf the 1055 registered nurses in the medical and surgical wards in the 12 participating hospitals, a total of 652 nurses responded completely to the survey, representing a 61.8% response rate. Responses were checked for outliers, and before the main analysis, outliers must be eliminated . At the The demographic characteristics see  indicatep < 0.05) and nurses with more than 15 years of total experience . Moreover, higher rates of quality of care  and a higher perception of person-centered care  were associated with being married. In comparison, Malay nurses perceived a better work environment , and rated higher quality  and safer care  than Chinese nurses.p < 0.01) and 8-h  shifts reported a higher perceived work environment compared to those working a 12-h shift . Furthermore, higher perceptions of person-centered care were reported among nurses in 7-h  and 8-h  shifts compared to those in 12-h shifts .More than two-thirds of the nurses worked 7-h (47.7%) and 8-h (17.5%) shifts across the sample. Nurses in 7-h , perceived lower person-centered care , and rated lower patient safety  compared to those assigned less than five patients in their last working shift. Similarly, nurses assigned 11–15 patients  perceived lower person-centeredness compared to those assigned less than five patients . Thus, nurses caring for more than 11 patients were less likely to integrate patient preferences.Interestingly, more than one-third of the nurses cared for more than 15 patients (37.0%) in their last work shift. Further, around one-quarter of nurses cared for 11–15 patients (24.0%), which indicated a high patient-to-nurse ratio that might jeopardize care outcomes. Nurses assigned more than 15 patients were less likely to report a favorable work environment ; nurse foundation for quality ; nurse manager’s ability and leadership support ; nurse-physician relationship . Further, nurse participation in hospital affairs , nurse manager’s ability and leadership support , and the nurse-physician relationship significantly influenced patient safety .The c′ paths of the Hayes Macro regression models explored the direct effect of nurse work environment subscales on perceived quality and patient safety, controlling the effect of nurse demographics and practice characteristics with the presence of a mediator, as shown in Greater participation in hospital affairs was related to 35% and 26% for improved quality and patient safety, respectively. The ability of a nurse manager and leadership support were associated with a 9% and 11% improvement in quality and patient safety, respectively. Further, a strong nurse-physician relationship was significantly associated with a 26% and 20% improvement in quality and patient safety, respectively. Being trained and engaging nurses with quality development programs was associated with a 29% improvement in quality, while it was not associated with patient safety. The study mediation analysis explains this inconsistency.To better understand how the nurse practice environment affects quality and patient safety, the mediation effect of person-centered care, between the relationship of hospital nurses’ work environment dimensions and nurses’ perceived quality and patient safety, was explored. Four models are shown for each outcome in The results revealed that the confidence interval of the indirect effect of nurse participation in hospital affairs (95% CI = 0.10 to 0.20), nurse foundation for quality of care (95% CI = 0.16 to 0.30), nurse manager’s ability and leadership support (95% CI = 0.08 to 0.18), and nurse-physician relationship (95% CI = 0.12 to 0.25) do not include zero. Therefore, person-centeredness mediates the relationship of nurse work environment dimensions on the quality of care. Further, concerning patient safety, the data analysis results revealed a significant mediation effect of person-centered care as the confidence interval of the indirect effect of nurse participation in hospital affairs (95% CI = 0.09 to 0.19), nurse foundation for quality of care (95% CI = 0.17 to 0.32), nurse manager’s ability and leadership support (95% CI = 0.07 to 0.16), and nurse-physician relationship (95% CI = 0.10 to 0.23) do not include zero. The direct effect of c′ paths of the relationships was significant; thus, partial mediation occurred. The direct effect of the nurse foundation, for quality of care on patient safety, was no longer significant with the presence of a mediator, indicating that full mediation has occurred.The signs of a x b x c′ baths are positive, indicating that the mediator is a complementary mediator . Nurses 2 values indicate that the study models, of the mediation effect of person-centeredness, explained about one-third of the variances of nurse-rated quality of care and one-quarter of the variances of nurse-rated patient safety at the p < 0.001 level of significance.The results indicated the greater participation in hospital affairs was associated with a 27% improvement in person-centered care, which, in turn, indirectly improves the quality of care by 15% and patient safety by 13%. Being a trained and engaged nurse, with quality development programs, was associated with a 41% improvement in person-centered care, which, in turn, led to an improved quality of care by 22% and patient safety by 24%. Nurse Manager’s ability and leadership support was associated with a 19% improvement in person-centered care, which, in turn, led to an improvement of quality of care by 12% and patient safety by 11%. Further, a strong nurse-physician relationship was significantly associated with a 31% improvement in person-centered care, which, in turn, indirectly improved the quality of care by 18% and patient safety by 16%. The RThis study provides evidence from the healthcare system in Malaysia, specifically from the private sector, which had complained about a high number of adverse events. The study results were supported and contributed to the Donabedian theory and SEIPS model ,26. HencThe results presented the associations of nurses’ demographics and practice characteristics in relation to the nurse work environment, person-centeredness, quality, and patient safety. Senior nurses, in terms of age and years of experience, perceived a high quality of care. The fact that they have high patient responsibilities and more substantial experience could explain that they have greater work expectations and perceived higher quality of care . FurtherIn support of previous studies, the practice characteristics of this study indicated that nurses with a high workload, in terms of duty length and patient ratio, perceived a less preferable practice environment, were less likely to integrate patient preferences, and more likely to come across adverse events in their respective units. Previous studies have indicated that a larger number of patients per nurse and working longer shifts were negatively associated with practice outcomes ,55,56.The Hayes Macro regression models provide meaningful results that can afford insights into the importance of the nurse work environment in enhancing person-centered care and, consequently, improving quality and patient safety. The first result indicated that nurse participation in hospital affairs indirectly affects the quality and patient safety through person-centeredness. This means that nurses with greater participation in hospital affairs have a higher degree of person-centeredness, which, in turn, improves both quality and patient safety.Previous studies support these findings. Per the American Association of Critical-Care Nurses (AACN) report (2005), ensuring effective staff participation, as well as patient and family education, is required to improve quality and patient safety. Nurses with high participation and involvement have high practice and clinical outcomes ,58. SimiThe second result indicated that person-centeredness significantly mediates the effect of a nurse’s foundation for the quality of care on both the quality and patient safety. Simultaneously, the c′ path of the effect of a nurse’s foundation for the quality of care indicates a significant and positive effect on the quality of care and an insignificant effect on patient safety. This explains the inconsistency in previous studies. The nurse work environment dimensions were inconsistently related to care outcomes ,22, and According to the AHRQ, nurse managers should engage more nurses in quality improvement programs, continuous education, and training for improving quality and patient safety . For insThe third result indicated that person-centeredness mediates the effect of a nurse manager’s ability, leadership, and support on both quality and patient safety. Nurses with a skilled and supportive leader have a higher degree of person-centeredness to integrate patient preferences, which, in turn, improves both quality and patient safety. Previous literature has reported that trained and skilled leaders are required to improve the quality and patient safety ; enhanceThe fourth result indicated that the nurse-physician relationship indirectly affects quality and patient safety through person-centeredness. Nurses with a strong relationship with collegial physicians have a higher degree of person-centeredness, which, in turn, improves both quality and patient safety. Previous studies support these findings. Hence, high nurse-physician collaboration reduces adverse events and promotes safety ,67. An iThe study was completed in 2015; the data reported, herein, were dated. This was a result of co-authors passing away since the manuscript was completed. The surviving authors updated the references and the theories supporting the study model. Because the study variables are interpersonal interactions in a work system, they are less likely to be affected by time. Furthermore, this study was a cross-sectional survey in Malaysian private hospitals at one point in time. Therefore, it is difficult to establish the causality between the study variables and generalize the study results. The study design limited the ability to assert a causal relationship between the nurse work environment, perceived person-centeredness, and nurse reported quality and patient safety. In addition, the study sample limited the ability to generalize the results, as it is conducted in Malaysia, and data collected from nurses in private hospitals represents 5.7% of the Malaysian private hospitals and 3.0% of total nurses in the private hospitals in Malaysia. However, as the quantitative approach suggests that generalization is possible, the findings in this report can be referred to as reliable, taking into consideration the randomness process of data collection that offers a reliable sample to represent the population. The multi-stage random sampling method ensures all nurses have an equal chance to be included in the study, thus makes the findings presentable.Furthermore, important potential variables, such as nurse burnout, stress, fatigue, and nurse reported intention to leave were not explored and should be included in future work to understand the mediation role of person-centered care better. Additionally, the direct effect c′ paths of nurse reported quality and safety were significant, indicating that other mediators could be used for future research . The stuThe study provides new insights into nursing research and practice; it is the first study of its kind that adds to the increasing literature concerning the mediation role of person-centeredness between the effect of practice work environment on quality and patient safety. The findings provide significant promises of the importance of maintaining a healthy work environment in the provision of high person-centered care, improving the quality of care, and reducing patient harm. Nurses with a high workload were less likely to report a positive work environment, less likely to integrate patient preferences, and more likely to encounter adverse events. Policymakers need to re-evaluate nurses’ assignments and staffing levels in Malaysian private hospitals to maintain staffing adequacy and reduce their workload.Moreover, the findings underscore that maintaining a work practice environment that focuses on task quality, in which nurse managers focus on the nurses’ performance by engaging them in hospital affairs, provide training in quality development programs, leadership support, and maintain collegial relationships help in improving person-centered care. This, in turn, improves the quality of care and patient safety. Therefore, nurse managers must balance task-oriented and patient-oriented leadership to simultaneously improve staff and patient care outcomes.The function of person-centeredness, in the study, was to complement the work environment’s impact on care outcomes. Therefore, a nurse manager should sustain a healthy work environment by enhancing nurses’ engagement and participation in hospital affairs to increase person-centeredness, which, in turn, improves the outcomes of care. They should involve nurses in new policies and procedures; encourage them to adopt the evidence-based practices of the current clinical research into their clinical practices. Furthermore, nurse managers should maintain trained and educated nurses for improving quality and patient safety for strengthening a healthy work environment of nurses. Therefore, they should channel resources to develop programs of support for nurses, training and learning to improve the skills of nurses and potential future nurse leaders, maintaining the communication and teamwork among care providers, and instilling a culture of person-centeredness to design a human-centered system for improving both quality and patient safety.


As a country with one-fifth of the global population, China has experienced explosive growth in ischaemic stroke (IS) burden with significant ethnic and geographic disparities. The aim of this study was to examine the differences in potentially modifiable risk factors for ischaemic stroke among the Han population and two ethnic minorities (Tujia and Miao).A case-control study was conducted with 324 cases of first-ever ischaemic stroke from the hospitals of the Xiangxi Tujia and Miao Autonomous Prefecture and 394 controls from communities covering the same area between May 1, 2018, and April 30, 2019. Structured questionnaires were administered, and physical examinations were performed in the same manner for cases and controls. Univariate and multivariate logistic regression analyses with adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were used to examine the association between risk factors and ischaemic stroke. An additive model was used to study the interaction between the modifiable risk factors and ethnicity with R software.Higher high-sensitivity C-reactive protein levels , higher monthly family income , increased frequency of hot pot consumption , diabetes mellitus , a higher apolipoprotein (Apo)B/ApoA1 ratio , hypertension  and moderate-intensity physical activity  were associated with ischaemic stroke. There was an additive interaction between the ApoB/ApoA1 ratio and ethnicity in the Tujia and Miao populations with first-ever ischaemic stroke .This is the first case-control study examining modifiable risk factors for ischaemic stroke among the Han population and two ethnic minorities (Tujia and Miao) in China. Some differences were observed in the impact of risk factors among these ethnic groups. Our results may help interpret health-related data, including surveillance and research, when developing strategies for stroke prevention.The online version contains supplementary material available at 10.1186/s12889-021-11115-x. Ischaemic stroke (IS) occurs when a vessel supplying blood to the brain is obstructed, and IS accounts for 69.6 and 77.8% of the total stroke incidence and prevalence in China, respectively . With thAccording to the Framingham Heart Study, stroke incidence in the US has declined over time; however, the cohort was predominantly Caucasian , and theAccording to the sixth national population census in 2010, the Miao (9.43 million) and Tujia (8.35 million) minorities were ranked as the fifth and seventh largest minority groups, respectively, but few reliable data are available to identify the differences in risk factors for IS among the Tujia, Miao, and Han populations. This study aimed to investigate the differences in the risk factors for IS among the Tujia, Miao, and Han populations and their additive interactions with ethnicity in the Xiangxi Tujia and Miao Autonomous Prefecture and to provide new insights into the risk factors, prevention and management strategies for IS among the Tujia, Miao, and Han ethnicities.A case-control design was utilized for this study. The study was carried out in Xiangxi Tujia and Miao Autonomous Prefecture, located in western Hunan Province and adjacent to Hubei and Guizhou Provinces, where people of Tujia and Miao constitute 80% of the total population of 2.98 million. We calculated the sample size for an unmatched case-control study based on the assumption as follows: α = 0.05, β = 0.2, OR = 2.0 (the minimum odds ratio (OR) of DM, which is one of the most important risk factors for IS), and a two-sided test. The exposure rate of DM in the control group was estimated as 15% based on other epidemiological studies in China, and the required minimum sample was found to be 277. Therefore, 324 IS patients and 394 controls were recruited to ensure logistic regression model validity, since some statisticians recommend an even more stringent “rule of thumb” of 20 samples per independent variable , and 15 Participants were recruited between May 1, 2018, and April 30, 2019, from all 8 counties of the Xiangxi Tujia and Miao Autonomous Prefecture . All participants were residents who had lived in Xiangxi for more than 5 years. The case group included all IS patients who were admitted to the First Affiliated Hospital of Jishou University and all 8 County People’s Hospitals of the Xiangxi Tujia and Miao Autonomous Prefecture within 5 days of symptom onset, a 72 h hospital stay and a discharge diagnosis of first-ever IS. IS patients were defined as having “rapidly developing clinical signs of focal  disturbance of cerebral function, lasting more than 24 h or leading to death with no apparent cause other than that of vascular origin” according to the World Health Organization (WHO) clinical criteria . ComputeControls were community-based from all 8 counties of Xiangxi and had no history of stroke. The age distribution of the controls was the same as that of IS patients. There was at least 1 control for every recruited case. The exclusion criteria for controls were identical to those described for cases.The study was approved by the ethics committees of the Xiangya School of Public Health Central South University (XYGW-2018-26). All participants, or their proxy respondent, provided written informed consent before participating in the study.According to the Trial of Org 10,172 in Acute Stroke Treatment (TOAST) criteria , IS was Waist and hip circumferences were measured in the standing and supine positions. If patients were unable to stand because of disability, these measurements were completed only in the supine position . FastingThis study focused on whether the effects of traditional risk factors for IS are different among different ethnic groups, which will be of great importance for the development of population-specific measures to prevent IS among different ethnic groups. This study mainly compares Tujia, Miao and Han with each other.Statistical analyses were performed with IBM SPSS Statistics for Windows  and R for Windows (Version 4.0.3). All statistical tests were two-sided.P < 0.10, and adjusted ORs and 95% CIs were calculated. The Breslow-Day test was used for the homogeneity of the association between modifiable risk factors and IS by ethnicity [P < 0.05, we detected the biological interaction between the modifiable risk factor and ethnicity. Three measures of biological interaction—the relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP), and the synergy index (SI) [First, we performed a comparison between case and control groups using chi-squared tests and calculated univariate ORs and 95% confidence intervals (CIs) for all dichotomized or multinomial risk factors. Second, binary multivariable logistic regression was applied, with backward stepwise (likelihood ratio) variable removal at the level of thnicity . If P < dex (SI) —with cordex (SI) . A RERI dex (SI) . The namThe study included 324 patients and 394 controls, with ages ranging from 22 to 80 years. Descriptive characteristics of the patients, including age, sex, TOAST classification, and NIHSS score, are reported in Table Table P < 0.05)  Table .Table 3Sex, age, ethnicity and all 15 risk factors that showed a significant association with IS in the univariate comparisons were included in the binary multivariate logistic regression analysis. In the entire population, six significant risk factors for first-ever IS included (in decreasing order of risk) a higher hs-CRP level, a higher monthly family income, an increased frequency of hot pot consumption, DM, a higher ApoB/ApoA1 ratio, and HT. Moderate-intensity physical activity was significantly associated with a reduced risk of IS Table .Table 400 = 1. In the R program, the function used a general linear model to estimate ORs with 95% CIs from a logistic regression model. Then, we used the epi.interaction function to calculate additive interactions by means of RERI, AP and SI with 95% CIs. The results of the interaction analysis showed that there was a biological interaction between the ApoB/ApoA1 ratio and ethnicity in the Tujia and Miao populations. The risk of IS related to the ApoB/ApoA1 ratio was significantly higher in the Tujia population  than in the Miao population   [Consistent with previous studies, our findings showed that HT and DM were significant risk factors for IS , 37. HT  = 0.02) . LimitedIn the multivariate analyses in our study, the ApoB/ApoA1 ratio was a stronger risk predictor of IS than hyperlipidaemia, the WHR and HDL-C levels. An elevated ApoB/ApoA1 ratio mirrors an adverse imbalance between proatherogenic and antiatherogenic lipoprotein particles, which may result in enhanced atherosclerotic burden , 42. TheIn our study, we also found that higher monthly family income and increased frequency of hot pot consumption were significantly associated with IS. Hot pot is a local cuisine in the Tujia and Miao ethnic populations, and it appears on tables all year round in the Xiangxi Tujia and Miao Autonomous Prefecture. The broth of the Tujia and Miao-style hot pot is always chock-full of Sichuan peppercorns, chili pepper, and sour pickles. Moreover, most of the ingredients are salted or pickled foods, such as pickled fish, pork and chicken. Hot pot was first identified as an important risk factor for IS, and further research is needed to clarify the mechanism. A recent study demonstrated that moderate-to-vigorous physical activity doses equivalent to meeting the current recommendations attenuate or effectively eliminate the association between sitting and all-cause and cardiovascular disease (CVD) mortality risk among the least physically active adults , similarOur study has several potential limitations. First, after controlling for the possible confounding variables (age and sex) by multivariable logistic regression, there may be some potential confounding factors, such as exposure to indoor and outdoor pollution, stress at work and home, social support, and life events, that have not been taken into account. Second, our sample size may be inadequate to provide reliable information in subgroup analysis (in different ethnicities) and interaction analysis. Third, the OR from a case-control study is less precise than relative risk (RR) from a cohort study, so the use of OR in the additive interaction model was inferior to RR.This study also has some strengths. Our study included the unique ethnic customs of Tujia and Miao populations as risk factors, such as local cuisine, which may add substantial information to other commonly modifiable risk factors.In conclusion, we provide the first evidence of ethnic variations among the Han, Tujia, and Miao populations in the effect of risk factors for IS in the Xiangxi Tujia and Miao Autonomous Prefecture. Therefore, we propose multidimensional IS prevention approaches among diverse populations, encompassing the population, community, health system, and individual levels. Racial and ethnic categories may help interpret health-related data, including surveillance and research, and are important in ensuring that IS prevention programmes remain generalizable to diverse populations.Additional file 1. Questionnaire for controls and patients with first-ever ischaemic stroke.Additional file 2: Table S1: The name and value of variables in univariate analysis and multivariate logistic regression analysis.


However, the limited sensitivity of 31P MRSI hampers its broader application at clinical field strengths. This study aimed to identify the additional value of 31P MRSI in patients with glioma at ultra-high B0 = 7T, where the increase in signal-to-noise ratio may foster its applicability for clinical research. High-quality, 3D 31P MRSI datasets with an effective voxel size of 5.7 ml were acquired from the brains of seven patients with newly diagnosed glioma. An optimized quantification model was implemented to reliably extract an extended metabolic profile, including low-concentrated metabolites such as extracellular inorganic phosphate, nicotinamide adenine dinucleotide [NAD(H)], and uridine diphosphoglucose (UDPG), which may act as novel tumor markers; a background signal was extracted as well, which affected measures of phosphomonoesters beneficially. Application of this model to the MRSI datasets yielded high-resolution maps of 12 different 31P metabolites, showing clear metabolic differences between white matter (WM) and gray matter, and between healthy and tumor tissues. Moreover, differences between tumor compartments in patients with high-grade glioma (HGG), i.e., gadolinium contrast-enhancing/necrotic regions (C+N) and peritumoral edema, could also be suggested from these maps. In the group of patients with HGG, the most significant changes in metabolite intensities were observed in C+N compared to WM, i.e., for phosphocholine +340%, UDPG +54%, glycerophosphoethanolamine −45%, and adenosine-5′-triphosphate −29%. Furthermore, a prominent signal from mobile phospholipids appeared in C+N. In the group of patients with low-grade glioma, only the NAD(H) intensity changed significantly by −28% in the tumor compared to WM. Besides the potential of 31P MRSI at 7T to provide novel insights into the biochemistry of gliomas in vivo, the attainable spatial resolutions improve the interpretability of 31P metabolite intensities obtained from malignant tissues, particularly when only subtle differences compared to healthy tissues are expected. In conclusion, this pilot study demonstrates that 31P MRSI at 7T has potential value for the clinical research of glioma.Phosphorus magnetic resonance spectroscopic imaging ( As such, 31P MRS(I) has been applied to patients with glioma for some time in several studies at clinical field strengths B0 ≤ 3 T and has recently been shown to potentially predict therapy response via phospholipid metabolites  via phospholipid metabolites  at ultra-high fields (UHF) B0 ≥ 7T may foster the clinical applicability of 31P MRSI by allowing the spatial resolution to be increased within clinically-relevant measurement times and/or by enabling the detection of even lower-concentrated metabolites. Additionally, the improved spectral resolution at higher fields leads to an increased specificity in metabolite assignment. In this regard, as an example, the improved tissue pH determination via the separate detection of intra- (Pi) and extracellular inorganic phosphate (ePi) pools at UHF  the detection of novel tumor markers and (II) the improved interpretability of results via increased spatial resolution. For this purpose, we acquired 3D 31P MRSI datasets in a small cohort of patients with newly diagnosed glioma at B0 = 7T with effective voxel sizes of 5.7 ml that enabled a good separation of individual tissues. A robust, optimized quantification model was implemented to extract an extended 31P metabolic profile from these datasets, including low-concentrated metabolites such as ePi, NAD(H), and UDPG, a signal attributed to mobile phospholipids (MPL), as well as a background signal underlying the phosphomonoester (PME) resonances. This model enabled high-resolution 3D maps of 12 different 31P metabolites to be generated, which were analyzed for regional differences in the individuals, not only between healthy and diseased tissues, but also between diseased tissue compartments. Finally, a group analysis revealed the most interesting changes that indicate malignant tissues.The aim of this study is to identify the additional value of Seven patients with newly diagnosed adult-type diffuse gliomas  for morphological imaging. All subjects have tolerated well the total examination duration of ~65 min.The examinations utilized the high-resolution etail in . In shorancement  via adiaTR = 8.5 s, TI = 2.4 s, TE = 135 ms, nominal resolution = (0.9 mm)2, slice thickness = 5 mm] and gadolinium contrast-enhanced 3D T1-weighted MPRAGE  images, both required for tumor segmentation.Prior to the 7T examination, all patients underwent clinical routine imaging on a 3T MR scanner . Clinical imaging included acquisition of multislice T2-weighted FLAIR  in addition to the prefitting result.As in the earlier study , quantif31P MRSI datasets , GPC, Glycerophosphoethanolamine (GPE), Phosphocholine (PC), Phosphoethanolamine (PE), Pi and ePi, as well as UDPG, MPL, and 2,3-Diphosphoglycerate (DPG). UDPG was modeled as pseudo-doublet, based on the findings in  of . Further note that within each (pseudo-)multiplet, equal dampings were constrained to each resonance. Finally, the inorganic phosphate resonances were modeled in this study utilizing linear relations based on the findings in , the sum of its constituents was calculated: NAD(H) = NAD+ + NADH. To enable the comparison to 31P quantification models not explicitly accounting for UDPG, ePi, and DPG  and phosphodiesters , i.e., PC-to-PE, GPC-to-GPE, and GPC-to-PE, suggesting to discriminate the IDH mutation status according to the findings of Esmaeli et al. .Applied to the processed MRSI datasets, the main quantification step yielded 3D intensity maps (in [a.u.]) for the individual  fields, ], the foi et al. . FinallyNote that the quantified metabolite intensities were not transformed to concentration values due to the unknown spatial variation in the required physical quantities, i.e., local T1 times for the individual metabolites and local B1 values.1H images.Regions-of-interest (ROI) were defined and processed in the Medical Imaging Interaction Toolkit (MITK)  using th3D ROIs of tumor tissue were defined on the 3T clinical MRI data co-registered to the morphological 7T images. For the data acquired in patients with high-grade glioma , the whole tumor volume (WTV) was segmented into central necrosis (NEC), gadolinium contrast enhancement (GDCE), and peritumoral edema (ED). In case of the patients with low-grade glioma , only the WTV ROI was segmented, defined as the volume of the T2-FLAIR hyperintense signal alteration. In addition, healthy tissue ROIs were defined manually on the morphological 7T images in WM  and a region with high content of GM  in all subjects, with care taken to define those ROIs always in equivalent regions  and ratios in each subject was performed in MATLAB and is reported as mean and standard deviation within each ROI. For the group analysis, six groups were defined and included the following numbers of ROI means: thirteen for each the WM and GM groups  + seven contralateral ROIs from patients), two for the WTV group of the patients with LGG, four for the WTV, four for the ED, and five for the combined GDCE/NEC (C+N) groups of the patients with HGG. The exclusion of the ROI means one of the patients with HGG from the WTV and ED groups based on the fact that in this patient no well-separated edema voxels were present HGG5 in .31P spectra of high quality were obtained throughout the whole brain. 31P spectra from a patient with a LGG (astrocytoma WHO 2) and another patient with a HGG (glioblastoma). Besides the typical signals observed in brain parenchyma arising from higher-concentrated metabolites, like PCr, ATP, GPC, GPE, Pi, and PE , and in particular UDPG could be quantified reliably in peripheral voxels of healthy tissue, as well as in most central brain voxels. Extraction of the background signal in the PME region, i.e. DPG, was also possible throughout the brain. Although a prominent MPL resonance was not observed in LGG or healthy tissues, maps could be extracted that represent a quantification of parts of the spectral baseline around 2 ppm. In coherence with the spectra in i), PC, PE and UDPG, and a reduction of PCr, ATP, GPC and GPE. The strong increase in MPL intensity in this case was related to the appearance of a well-resolved MPL resonance in the tumor spectra , and reductions of 45 and 29% for GPE and ATP, respectively. The other metabolite intensities showed only insignificant changes : + 6%, GPC: −25%, DPG: +5%). Note that the deviations of the corresponding ED ROI medians from the WM medians were generally smaller and the WTV ROI medians line up in between the ED and C+N medians.With regard to the patients with LGG, the only significant change was observed for NAD(H), with a reduction of the median in the WTV ROI by 28% compared to the median of WM (taken as the reference). In the patients with HGG on the other hand, several significant changes could be observed, with the C+N ROI median deviating strongest from the WM median (given in the following). The most extreme change was observed for PC, increasing by 340%, which also led to a strong change in the PC-to-PE ratio, increasing by 174% . The other extreme increase was given for MPL, which however was not quantifiable since it was typically not detectable in WM. Further significant changes were the increase in UDPG by 54%, an increase by 37% of total P31P MRSI at an ultra-high B0 of 7T to a small cohort of patients with glioma to investigate the additional value provided by multiple metabolite maps for clinical research of brain tumors. As with this pilot study we aimed to assess what could be in principle possible at 7T, we decided to apply our recently proposed examination protocol with 51 min acquisition duration for 31P MRSI of the human brain  is lower, and the total Choline intensity  is higher in WM compared to GM, as observable in high-resolution metabolite maps e.g. in (31P studies of patients with brain tumors (i in tumor tissue (here the C+N ROI in patients with HGG) compared to healthy tissues. The increase in tPi intensity was dominated by the extracellular contribution, which is in line with our earlier observations , it is reasonable to assume that the observed variations are mainly reflecting concentration changes, since otherwise unrealistic changes in T1 times should have occurred under the applied sequence parameters. To finally prove this and also to improve comparability between studies, however, efficient T1- and B1-mapping techniques for 31P MRSI of the human brain would be required enabling the estimation of concentrations.The analysis of these maps revealed the metabolic heterogeneity of the individual tissue types cf. , 3, 7. Aan brain –27, we o e.g. in . Our resn tumors , 29, 30,rvations   intensity was observed in LGG tissues, whereas increased UDPG and MPL intensities were observed in HGG tissues. Note that although not proving significant in the group analysis, an increase in ePi intensities was also observed in the spectra of LGG tissues  our recently published, highly robust quantification method for datasets , refinedevidence , 21, speevidence  as a potevidence , thus alevidence  is in lievidence –4, whereevidence  (deoxygeevidence . In thisi and FWHM > 30 Hz for ePi), leading to an inability to clearly separate the intensities of the intra- and extracellular compartment. These situations occurred in some of the tumor voxels, and was most probably associated with changes in microscopic susceptibility and a stronger heterogeneity in tissue pH , could also be considered as reliable and robust, the individual intensities were not due to their still limited SNR, which prevented a robust analysis of the redox potential RX within this study.The parameters for the quantification model described in issue pH . Neverthissue pH , as well31P MRSI datasets of the human brain at 7T highly reasonable, and thereby, also provides an additional value for the application to patients. Note that although the focus of this study were the metabolite intensities, the extended quantification model also improves the interpretation of tissue pH estimates by separating the individual inorganic phosphate contributions  values of 31P MRSI at 7T provide an added value to the interpretation of data obtained from brain tumors, as it allows to select spectra belonging more specifically to a certain tissue type, being important to analyze subtle metabolic differences. This improvement in specificity might become of increasing importance in the future, as a recent study , being typically too close to the borders of the tumor ROIs.To account for the observed variability, we defined the range of values considered to be normal for our study cohort , UDPG, MPL, and PC  have the potential to provide novel insights into the biochemistry of gliomas 1H MRS showed an increase in some UDPG species in glioma cells as a response to cisplatin treatment  and UDPG intensities.Besides its potential to assess the redox potential in tumor tissue, the NAD(H) intensity reflects the general availability of redox equivalents for energy generation. In our cohort, the mean NAD(H) intensities were reduced in both patients with LGGs, bearing mutant IDH1, while the patients with HGGs (4 of 5 with wildtype IDH) appeared to show normal values of NAD(H) . Interesreatment , thus, rreatment . In thisvia the quantification model also in this study  compared to healthy tissues as a marker indicating malignant tissue. In accordance with this, we observed increased PME and reduced PDE intensities in patients with aggressive HGGs , 6D, 7, in vivo demonstrated the potential to discriminate wildtype and mutant IDH species. A recent clinical study of 31P MRSI in patients with glioma at 3T  and UDPG, the reduction in SNR would have to be compensated by a reduction in spatial resolution to at least (1.5 cm)3 nominal voxel volume (effective voxel volume of about 10 ml) to obtain approximately the same data quality as shown in this study. In these ways, measurement time could be reduced to clinically more relevant time scales while still maintaining a reasonable spatial resolution for separating individual tissues and a reliable quantification, e.g., on the order of 10 ml voxels in 20 min, fostering the applicability of 31P MRSI in patients with glioma at 7T.Although the detailed analysis of such strategies is beyond the scope of this paper, and must be investigated in future studies, some coarse prospects can already be given here: shortening the measurement time to 20 min for the given acquisition and processing scheme  would reduce the SNR by about 35%, which is well-tolerable for the high-intensity resonances like PCr, ATP, PDEs, PE, and P31P MRSI at 7T has the potential to add value to the clinical research of glioma. The sensitivity and spectral resolution available at UHF in combination with an optimized quantification model enables the reliable mapping of an extended 31P metabolic profile in patients that could provide novel insights into tumor biochemistry in vivo. This includes low-concentrated metabolites like NAD(H) and UDPG, which might generate information of diagnostic and therapeutic relevance, as well as improved estimates for PMEs, which might affect metabolite ratios typically used as tumor markers in a beneficial way. Moreover, the attainable small effective voxel sizes on the order of 10 ml enable a meaningful separation of spectra from different tissue types, like cerebral WM and GM, as well as subsegments in larger-sized tumors. This improves the interpretability of 31P metabolite intensities obtained from malignant tissues—in particular when only subtle differences compared to healthy tissues are expected as it presumably is the case for LGGs—that being potentially diluted by partial volume effects with healthy tissues showing a large physiologic variability in metabolite intensities. Although the applied MRSI protocol of long duration is currently of limited practical use, we pointed out that further optimization of data acquisition and processing techniques will bring the anticipated value easily into the reach of clinically applicable timeframes on the order of 20 min. With this, the required studies on larger cohorts of patients with brain tumors will become feasible, which will finally enable to assess the full clinical value of this technique.Altogether, this pilot study on a small patient cohort demonstrates that The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Ethics Committee of the Medical Faculty of the University of Heidelberg. The patients/participants provided their written informed consent to participate in this study.AK, NW, and DP contributed to the conception and design of the study and to the data acquisition. AK, NW, VF, JB, SG, and DP performed the data analysis. AK, VF, JB, and SG contributed to the method development. H-PS, ML, and PB coordinated the project. DP supervised the study. AK wrote the first draft of the manuscript. All authors contributed to critical manuscript revision, read, and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Due to difficulty in early diagnosis of Alzheimer’s disease (AD) related to cost and differentiated capability, it is necessary to identify low-cost, accessible, and reliable tools for identifying AD risk in the preclinical stage. We hypothesized that cognitive ability, as expressed in the vocal features in daily conversation, is associated with AD progression. Thus, we have developed a novel machine learning prediction model to identify AD risk by using the rich voice data collected from daily conversations, and evaluated its predictive performance in comparison with a classification method based on the Japanese version of the Telephone Interview for Cognitive Status (TICS-J). We used 1,465 audio data files from 99 Healthy controls (HC) and 151 audio data files recorded from 24 AD patients derived from a dementia prevention program conducted by Hachioji City, Tokyo, between March and May 2020. After extracting vocal features from each audio file, we developed machine-learning models based on extreme gradient boosting (XGBoost), random forest (RF), and logistic regression (LR), using each audio file as one observation. We evaluated the predictive performance of the developed models by describing the receiver operating characteristic (ROC) curve, calculating the areas under the curve (AUCs), sensitivity, and specificity. Further, we conducted classifications by considering each participant as one observation, computing the average of their audio files’ predictive value, and making comparisons with the predictive performance of the TICS-J based questionnaire. Of 1,616 audio files in total, 1,308 (81.0%) were randomly allocated to the training data and 308 (19.1%) to the validation data. For audio file-based prediction, the AUCs for XGboost, RF, and LR were 0.863 , 0.882 (95% CI: 0.840–0.924), and 0.893 (95%CI: 0.832–0.954), respectively. For participant-based prediction, the AUC for XGboost, RF, LR, and TICS-J were 1.000 (95%CI: 1.000–1.000), 1.000 (95%CI: 1.000–1.000), 0.972 (95%CI: 0.918–1.000) and 0.917 (95%CI: 0.918–1.000), respectively. There was difference in predictive accuracy of XGBoost and TICS-J with almost approached significance (p = 0.065). Our novel prediction model using the vocal features of daily conversations demonstrated the potential to be useful for the AD risk assessment. Identifying individuals at risk for Alzheimer’s disease (AD) in the prodromal phase might lead to early detection and alleviation of the burden of AD among patients and caregivers –5. Due tThe neurophysiology of AD provides a perspective for further improving AD risk prediction. AD patients represent the degree of deficits in specific cognitive constructs: neurophysiologic change following the progression of AD  can lead to changes in sensory perception and motor symptoms, resulting in impairment of spontaneous speech –19. A stThe purpose of the present study is to 1) develop a novel machine learning prediction model to identify AD risk using only vocal features collected from daily conversations via telephone, and 2) evaluate the predictive performance of the model by comparing results of multiple machine learning algorithms with conventional cognitive tests. We believe that if the developed model using daily conversation voice data can accurately predict AD risk, it will have a significant impact on early detection and diagnosis among the general older adult population in that we can guide those who are in the earliest stages of AD to engage in care-seeking behavior.The present study is a retrospective analysis of voice data and conventional cognitive test data among individuals ages 65 and older who participated in a program aimed at dementia prevention in a Japanese local city. Using these data, we developed prediction models and compared predictive accuracy with that of a conventional cognitive test. The present study was approved by the Institutional Review Board of Kyoto University (examination number: R2721). This paper adhered to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis statement (TRIPOD), which was proposed for the reporting of predictive models .The data in the present study was gathered from Hachioji City, Tokyo in the spring of May 2020 . The total population was 576,608 as of August 1, 2020. The study population included residents in the city aged 65 or older who agreed to participate in a telephone conversation program, with an Artificial Intelligence (AI) computer program, aimed at improving healthy diet, physical activity, and social participation for prevention of dementia. The city recruited both HC and AD patients: For HC, participants were those who, after receiving an invitation letter about the program from Hachioji City via mail , voluntarily agreed to participate. Of the 1,000 people contacted, 103 agreed to participate (10.3%). For AD patients, participants were those who volunteered or whose families agreed to participate after an in-person invitation to the program from Hachioji City, and who currently used a day service center (a welfare facility designed to care for senior citizens with AD). Among 400 patients, 53 agreed to participate (13.2%). Thus, the final number of participants for HC and AD patients were 103 and 53, respectively .The dementia prevention program conducted by the city consisted of a telephone conversation with AI that covered the following contents: 1) assessment of cognitive function based on the Japanese version of the Telephone Interview for Cognitive Status (TICS-J)   the results of the assessment of cognitive function with a questionnaire based on TICS-J, 2) voice data of participants, especially the 1-minute talk portion, and 3) a binary variable indicating whether they were an HC (0) or AD (1) patient. Whereas we got one result of TICS-J based questionnaire for each participant, we obtained multiple recordings of the 1-minute talk for each participant because the telephone conversation program consisted of 1–2 months of daily weekday telephone conversations, resulting in multiple recording files for each participant, with an average of 13.1 (Standard deviation: 7.6). The data-processing steps, as well as other processes in the present study, are shown in th ed. (DSM-5) [Our study consisted of 99 HC and 24 AD patients. As stated above, HC and AD patients were recruited in different ways. Whereas HC patients were recruited via mail, AD patients were recruited in person given the difficulty of explaining the program. AD patients were previously diagnosed using National Institute on Aging-Alzheimer’s Association (NIA-AA) criteria  and/or t (DSM-5)  before tThe voice data used for model prediction were collected through the telephone conversation program: each participant was asked to have a nested conversation with an AI computer program. The conversation consisted of a greeting, a task that asked the participant to describe what he or she did yesterday with as much detail as they could in one minute, and closed with recommendation of health behavior and scheduling of the next call. The participant’s response to the task was the only part of the conversation recorded and used for future analysis. The reason we used this one-minute task is that in many validated questionnaires for screening of dementia like MMSE, memory and the ability to express one’s thoughts are crucial elements that have high discriminating ability in screening for dementia .After recording, vocal features were extracted using the open software tool PRAAT . PRAAT hWe developed three machine-learning prediction models, applying the extreme gradient boosting (XGBoost) , random In short, XGBoost is an ensemble of classification and regression trees (CART) . A classRF is an ensemble-based method that uses multiple decision trees like XGBoost, but it is different in that RF computes predictive scores by averaging the vote for each tree, iterating over all trees in the ensemble . Each trLR is a commonly used statistical method for a variety of classification tasks . LR emplIn addition to machine learning models, we developed the scoring model using the TICS-J based questionnaire, assessing the cognitive function of participants through telephone interviews . TICS-J We needed to consider the fine-tuning of several parameters when adopting XGBoost, RF, and LR. The parameters for our prediction models were set through a grid search, a method for optimization of parameters using combinations of each parameter. We trained 10 different models with 90% of the training data and tested them with the remaining 10% for each grid search process. The results of the grid search for the prediction models are shown in We carried out two types of model comparison: one based on ‘audio-based prediction’, and the other on ‘participant-based prediction’.First, we made a comparison between models with machine-learning  using each audio file as one observation. We evaluated the predictive performance of the developed models by describing the receiver operating characteristic (ROC) curve, calculating the areas under the curve (AUCs), sensitivity, and specificity. Subsequently, we compared the predictive performance of developed models using the chi-squared test proposed by DeLong . We deteSubsequently, we made a comparison between models with machine-learning  and the TICS-J based questionnaire using each participant as one observation. As stated above, we yielded 1,465 and 151 audio files for HC and AD patients with averages of 15.8±5.9 and 5.0±6.2 files for each participant, respectively. By regarding each audio file as one observation, our development of the prediction models made a tacit assumption that each audio file is independent in terms of vocal characteristics, which is not actually the case. Although we made sure that the audio file of the same participant would not be included in both the training data and validation data, it raised a potential problem. Thus, as a further evaluation of our prediction models, we conducted additional analysis to measure the predictive accuracy for each participant, not for each audio file. Although limited sample size meant that we could not develop a model based on each participant, we instead conducted a participant-based prediction by computing the average of the predictive value among their multiple audio files, and used this for the validation data. We already described this concept in Our final participants consisted of 99 HC and 24 AD patients, yielding 1,465 and 151 audio files for each group. Of 1,616 audio files in total, 1,308 (81.0%) were randomly allocated to the training data and 308 (19.1%) to the validation data. Among those, 123 (9.4%) of the training data and 28 (9.1%) of the validation data were audio files of AD patients . On a paThe predictive performance of developed machine-learning models built for each audio file are represented in Subsequently, the predictive performance of developed machine-learning models and cognitive test (TICS-J based questionnaire) built for each participant are represented in The machine learning models we developed, which were based on models built for each audio file, did well at classifying the audio files of AD and HC patients. Further, when the average of the predicted values of each audio file was summarized for each participant, the XGBoost model demonstrated performance comparable to cognitive tests, with almost approached significance.Our finding is in line with previous studies. There is growing consensus that the presence of language deficits could be a part of clinical manifestation of AD and MCI, and suggestion that assessment of language production might be able to represent a unique opportunity for early detection of AD . There hOur prediction models averaging the predictive value of each audio file for each participant showed even stronger performance than those built for each audio file. Although we need to interpret this result with caution, it might have potential for further robust prediction of AD by obtaining multiple audio files of daily conversations for each participant. Nevertheless, we are currently not sure if this method of compressing predictive values by arithmetic mean is appropriate for predicting AD risk in datasets other than those we already obtained. Although this idea, averaging the multiple predictive value of each weak learner, is widely accepted as a part of machine-learning algorithm such as random forest , furtherThe findings of our study can create the opportunity for building new tools to identify AD risk by using only vocal features obtained from daily conversations via telephone, as a pre-screening method among the general population. It might enable and drive early detection and diagnosis of dementia, including AD, in the sense that the tool can be used not only by healthcare professionals in a clinical setting, but also the general population at home. As internet and mobile technology further improves, our prediction model can also be easily installed on a variety of user interfaces, such as websites, mobile apps, or the Internet of Things (IoT). Indeed, there have been several recent research assessments of cognitive health showing remarkable accuracy, based on machine learning algorithms using data from smart homes or smartphones , 47. GivThere are several limitations to our study. First, the outcome variable we used was binary (AD or HC), ignoring various features among AD patients. For example, speech characteristics may differ between advanced AD patients and MCI patients. Future research is expected to build prediction models for both advanced AD and MCI based on more detailed diagnostic information. Second, our small sample size to some extent limited our predictive power. Third, the quality of audio differed depending on the participants and time, raising the possibility that this affected the performance of the prediction models. Fourth, the questionnaire based on TICS-J that was used to assess cognitive function was conducted between the AI computer program and participants; the limited speech recognition ability of the AI computer program can affect the validity of obtained results. Fifth, we only relied on superficial vocal features such as pitch, intensity, etc. in the analysis, raising the possibility of loss of information and insufficient audio feature extraction. Further research could include natural language processing of speech content and sentence structure analysis in order to reduce information loss and increase model prediction performance. In practice, this device could be helpful to use as a gatekeeper of early diagnosis of AD through potential patients’ daily life. For the final diagnosis, it is necessary to also consider other symptoms, along with medical doctors’ judgements.Prediction models based on machine learning algorithms that use only vocal features from daily conversations showed strong predictive performance of AD risk, and were compatible with existing cognitive tests. This opens the possibility of developing new accessible, low-cost pre-screening tools for AD risk among the general population, outside a clinical setting.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


The adjusted OR of dementia for BPPV was 1.14 . In subgroup analyses according to age and sex, males had higher ORs of dementia for BPPV. BPPV increases the risk of dementia in the 60 years of age or older population.The aim of the present study was to estimate the risk of dementia in patients with benign paroxysmal positional vertigo (BPPV), using a population cohort. Data from the Korean National Health Insurance Service-National Sample Cohort for the population ≥60 years of age from 2002 to 2013 were collected. A total of 11,432 individuals with dementia were matched for age, sex, income, region of residence, hypertension, diabetes, and dyslipidemia with 45,728 individuals comprising the control group. The crude (simple) and adjusted odds ratios (ORs) of dementia in BPPV patients were analyzed using non-conditional logistic regression analyses. Subgroup analyses were conducted according to age and sex. A history of BPPV characterized 5.3%  of the dementia group and 2.6%  of the control group ( A cross-sectional study reported that patients with cognitive impairment, such as mild cognitive impairment and Alzheimer’s dementia, show a high risk of vestibular dysfunction . The vesBenign paroxysmal positional vertigo (BPPV) is the most common cause of vestibular vertigo in elderly individuals ; approxiBoth direct and indirect mechanisms may underlie the association between BPPV and dementia. With regard to a direct mechanism, an increased risk of falls in patients with BPPV may result in a high risk of head trauma and physical inactivity, which predispose these patients to dementia ,12. The We hypothesized that BPPV could increase the risk of dementia. We searched the PubMed and Embase databases using the key words “BPPV” and “dementia” and included all entries until September 2021 in our search. We identified only one population cohort study that reported an increased risk of dementia in patients with BPPV . HoweverThe Ethics Committee of Hallym University (2014-I148) approved the use of the data. The need for written informed consent was waived by the Institutional Review Board.This matched case–control study relied on data from the Korean National Health Insurance Service-National Sample Cohort (NHIS-NSC). The Korean NHIS selects samples directly from the database of the entire population to prevent non-sampling errors . For thiAs all Korean citizens are assigned a 13-digit resident registration number that is retained from birth to death, exact population statistics can be determined from the resulting database. All Koreans must enroll in the NHIS. The 13-digit resident registration number is used by Korean hospitals and clinics to register individual patients in the medical insurance system. Therefore, the risk of overlapping medical records is minimal, even if a patient moves from one place to another. Moreover, all medical treatments in Korea can be tracked, without exception, using the HIRA  system. In Korea, a notice of death must be submitted to an administrative entity before a funeral can be held. The cause and date of death are recorded in the death certificate, which is prepared by a medical doctor.Among the 1,125,691 individuals with 114,369,638 medical claim codes, those diagnosed with dementia were included in the study. Dementia was defined based on a diagnosis of Alzheimer’s disease (G30) or dementia in Alzheimer’s disease (F00). To ensure the accuracy of the diagnosis, only those participants treated at least twice were included in the study. The reliability of the dementia diagnosis is described in the Supplemental Digital Content.The study population consisted of 13,102 dementia patients diagnosed between 2002 and 2013. BPPV was diagnosed based on ICD-10 codes (H811) and at least two treatments for this condition between 2002 and 2013.The dementia patients were matched 1:4 with members of a control group selected from the original population  and consisting of individuals never diagnosed with dementia between 2002 and 2013. The matches were processed for age, sex, income, region of residence, and a medical history of hypertension, diabetes, or dyslipidemia. To prevent bias in the selection of matched participants, control-group participants were sorted by first assigning them a random number, which was then used in their selection, beginning with the highest and ending with the lowest number. It was assumed that the relation to the index date of the matched control participants was the same as that of each matched participant with dementia. Therefore, a person in the control group who died before the index date was excluded. Dementia participants for whom a sufficient number of matching control participants could not be identified were excluded (n = 1158), as were participants younger than 60 years of age who had been previously diagnosed with dementia (n = 514). In the young population, dementia is rare and often has a specific underlying etiology. Finally, using 1:4 matching, 11,432 dementia patients and 45,728 controls were included in the study . HoweverAll variables including age, income level, region of residence, and comorbidities were based on the index date. Six age groups were defined according to 5-year intervals, ranging from 60–64 to 85+ years of age. Income groups were initially divided into 41 classes  but then re-categorized into five classes, ranging from lowest (class 1) to highest (class 5). Sixteen regions of residence were defined according to administrative district. These regions were regrouped as urban  and rural .The prior medical histories of the patients and controls were evaluated using ICD-10 codes. To ensure the accuracy of the diagnoses, hypertension (I10 and I15), diabetes (E10–E14), dyslipidemia (E78), and head trauma (S00–S09) were regarded as present if treated at least twice, and Meniere’s disease (H810), ischemic heart disease (I24 and I25), and cerebral stroke (I60–I63) strokes as present if treated at least once.p value < 0.05 was considered to indicate statistical significance. The analyses were conducted using SPSS v. 22.0 .Chi-square tests were used to compare the general characteristics of the dementia and control groups. The odds ratio (ORs) of BPPV for dementia was analyzed using unconditional logistic regression analysis together with crude (simple) and adjusted  models and calculating 95% confidence intervals (CIs). Age, sex, income, region of residence, hypertension, diabetes mellitus, and dyslipidemia were stratified in a conditional logistic regression model. For the subgroup analyses, participants were divided with respect to age , sex, income, region of residence, hypertension, diabetes, dyslipidemia, ischemic heart disease, stroke, Meniere’s disease, and head trauma. Two-tailed analyses were conducted. A p < 0.001, A history of BPPV was documented in 5.3%  of the dementia patients vs. 2.6% of the controls .The OR for BPPV was higher in the dementia group than in the control group . According to the medical histories, the subgroups with histories of hypertension, diabetes, or dyslipidemia, and no histories of ischemic heart disease, stroke, Meniere’s disease, or head trauma demonstrated increase in the OR for BPPV in dementia patients  [A previous population cohort study also reported an increased risk of dementia in patients with BPPV  . However< 0.001) . FurtherBPPV may represent an initial manifestation of degenerative nervous system changes. Vestibular and macular degeneration may lead to otoconial detachment; studies have reported neuronal degenerative changes of the saccular macula in patients with BPPV ,25. DegeComplications of BPPV, including falls, inactivity, and reduced social activity may contribute to the risk of dementia in patients with BPPV. BPPV is an important contributor to falls in the elderly population . In a reShared pathophysiological mechanisms between BPPV and dementia may affect the risks associated with both conditions. A recent study observed that vestibular-system ischemia increased the risk of BPPV  and thatOur study also highlighted the higher risk of dementia in men with BPPV. A previous study reported that education level, social activities, and alcohol consumption interact with sex to affect cognitive function  and may The present study was based on nationwide representative data, the validity of which was verified by a previous study . The NatFollowing are the limitations of our study. BPPV was diagnosed by a physician in patients who were treated at least twice for the condition. However, BPPV was not categorized based on severity and subtypes. Various pathophysiological conditions, including cupulolithiasis, canal switch, and re-entry phenomenon are associated with BPPV . The diaBPPV was related with an increased risk of dementia in patients ≥ 60 years of age. This association of BPPV with dementia was valid in patients with male sex, low income, rural residence, and medical histories of hypertension, diabetes, and dyslipidemia. The possible links of BPPV with dementia need to be considered when managing patients with BPPV.


Currently, it maintains a close-to-full coverage on bacterial and fungal carbohydrates up to the year 2020. The CSDB web-interface provides free access to the database content and dedicated tools. Still, the number of these tools and the types of the corresponding analyses is limited, whereas the database itself contains data that can be used in a broader scope of analytical studies. In this paper, we present CSDB source data files and a self-contained SQL dump, and exemplify their possible application in glycan-related studies. By using CSDB in an SQL format, the user can gain access to the chain length distribution or charge distribution (as an example) in a given set of glycans defined according to specific structural, taxonomic, or other parameters, whereas the source text dump files can be imported to any dedicated database with a specific internal architecture differing from that of CSDB.The Carbohydrate Structure Database (CSDB,   The broad usage of glycomic databases and associated software tools has been recently reported8. Similar to other data-related scientific branches, glycoinformatics heavily depends on high-quality data repositories. In the last decades, several such repositories have been developed. They include a historical CCSD project 9; Glycosciences.DB 11; UniCarbKB 12; KEGG Glycan (glycan-related data from the Kyoto Encyclopedia of Genes and Genomes)13; Japan Consortium for Glycobiology and Glycotechnology 14; and CSDB 15, to name a few.Glycoinformatics is a relatively new research branch, which provides the scientists with various means of accessing, processing and handling all sorts of carbohydrate-related dataSuccessful application of any database depends not only on the quality and completeness of its data, but also on the capabilities and user friendliness of its interface. Thus, most of the chemical and biological databases, including carbohydrate ones, are equipped with a web interface. However, in many cases the source database files contain much more data than those accessible via the Internet, because the frontend interfaces and the backend tools behind them are usually designed to serve only the most popular and demanded user queries.http://csdb.glycoscience.ru/) is a free curated repository, which stores various types of data  on glycans of bacterial, fungal and plant origins15. One of the most significant characteristics of CSDB is its completeness15. Currently, it provides a close-to-full coverage on bacterial and fungal carbohydrates up to the year 2020. The fungal coverage has been achieved in 2021 and has not been reported elsewhere.The Carbohydrate Structure Database , which currently covers GTs from the three most studied non-animal model species 25.CSDB is supplied with a web interface, which provides free access to the CSDB content and dedicated data analysis and simulation tools. These tools include coverage statistics, monomeric residue properties, multiparametric analysis of distribution of carbohydrate structural elements among taxa26 for further import to an external triplestore.According to user feedback, citing and access log analysis, the above-listed CSDB instruments are most demanded in routine research on natural carbohydrates. However, the number of these tools and the types of the corresponding analyses is limited, whereas the database itself contains data that can be used in a broader scope of analytical studies. For example, by using the existing database in an SQL format, the user can gain access to the chain length distribution or charge distribution in a given set of glycans, which can be defined according to specific structural, taxonomic, or other parameters. In their turn, the source text dump files can be potentially imported to any dedicated database with a desired internal architecture differing from that of CSDB Fig. . In thisorganisms.tax_group - bacteria, archaea, fungi, plant, protista, animal, mammal, human, etc.main_link.tax_group - the same as above .conformations.methods - MM3-2000, MMFF-94, GLYCAM, AMBER, CHARMM36, OPLS-AA, PDB.conformations.solvent - none, GB, STIL, TIP3P, etc.compounds.unit_type - chem, biol, sbiol, oligo, mono, homo, cyclo, fragment, motif.link_types.link_type - glycosidic, amidic, amine, diester, carbon-carbon, etc.disease.attr_name (attributes) - ICD code, Life stage, Sex.gtr.molecule role - O-antigen, CPS, EPS,core, lipid A, GPI, N-glycan, O-glycan, C-glycoside, etc.in vivo, indirect, semi-direct, in vitro, in silico, suggested.gtr.confirmed - publication_specific.synthesis - chemical, enzymatic, fragmentary, biosynthesis, etc.nmr_solvents.unit - %, vol %, M, mkM, etc.external_resources.resource - CA, PubChem, GlycomeDB, CCSD, US patent, GlyTouCan, etc.CSDB stores data in a MySQL relational database. For structures, the connection table approach is used, where nodes are monosaccharide and other residues, and vertices are bonds with elimination of water. Relationships between the data from scientific publications and their indices are visualized in Fig. The data are imported from main text dumps (see below), with a few exceptions, the detailed description of which are beyond the scope of this paper.27  generated automatically by a dedicated postprocessor of molecular dynamics trajectories simulated by the CAT software . Generation of these files is automatized and implemented at the CSDB calculation server; ca. 20–30 new files are completed monthly. Currently, there are 2597 data files available for download at http://csdb.glycoscience.ru/jsmol/confmap_data/minima/, including those imported from the GlycomapsDB29 database.The conformation map subdatabaseThe Glycosyltransferase subdatabase .A vocabulary of supported monomeric residues, their atomic properties, stereo codes, and their records in WURCSperformed by a human expert);Retrieval of abstracts and meta-data from the acknowledged bibliographic databases , Scopus (Elsevier), and NCBI PubMed) by using dedicated search queries (performed by a human expert);Preliminary examination of the retrieved abstracts and selection of candidate articles for annotation  (performed by a human expert);Acquisition of full texts of the selected publications and secondary examination ;Selection of publications containing the carbohydrate or derivative structures that match the database scope (see the criteria below) (performed by a human annotator);Retrieval of the relevant information from the published data (performed by a human annotator);Encoding of the information in the strict format in a text dump file (see below) ;Various error detection routines, correction of annotation errors, and tracking of errors in publications ;Temporary upload of the resulting dump into a service shadow of the database and subsequent checking for errors detectable in the database context only  ;Approval of the dump file and its merging with the main dump, which serves as a backup of the database;Update of the database content from the main dump .The CSDB database is supplemented with data by means of retrospective analysis and annotation of scientific literature. The annotation procedure includes the following steps:The structure contains at least one carbohydrate residue (except nucleic acids studied in genomic or transcriptomic context);The glyco moiety of the structure is established in this or previous publications with the degree of unambiguity sufficient to derive most of its monomeric composition and at least a half of its linkages, and residue configurations;The structure is associated with an unambiguously specified biological source (taxon), and this taxon belongs to prokaryotes, plants, fungi or protista.To match the database scope, an article must contain at least one explicit or implicit molecular structure that meets any of the following criteria:The primary structure or its conformation is elucidated;A motif of the structure is suggested;Various properties of the structure, including its biological activity, are studied;Synthesis or modeling of the structure is described;The structure is reassigned to another taxon;The biological role or other properties of the structure are referenced or reviewed.The carbohydrate structure can be published explicitly  or implicitly . The structure is considered present in a publication if any of the following conditions is met:The structure was extracted from a biological source ;The structure is a part of a larger natural molecule, and this part is discussed separately (e.g. O-glycan moiety of a glycoprotein);The structure is synthetic and is identical to a natural structure (or differs from it only by an aglycon);The structure was obtained as a sample by modification or degradation of a natural structure, e.g. as a result of the analytical procedures;The structure was produced outside the organism by an enzyme from this organism, and: (i) was reported elsewhere to be present in this taxon; or (ii) its precursor was reported elsewhere to be present in this taxon or to be consumed by this taxon; or (iii) its precursor was reported elsewhere to be present in the host organism infected by this taxon.The association of a given structure with a biological source (taxon) implies any of the following:Except for derived content, such as oligosaccharide conformation maps, the CSDB is imported from human-readable text files called “dump files”. The main CSDB dump file is manually filled and appended by a team of annotators, who perform the search for matching scientific literature and its analysis. Before import, the dumps undergo automated syntactic validation and manual data quality control by another team of curators. Data correction and content updates are performed on the main dump file.:), after which the field content is provided. Line breaks inside the field are not allowed. The detailed explanation of the fields is given in Online-only Table The main CSDB dump file is a UTF-8 text backup of the database and a reference file for all the database content. The dump file contains records separated by two blank lines; the main dump contains all the CSDB records. Lines starting with the symbol # are comments for annotators and are not processed. Every record is a unique combination of a molecular structure and a paper, in which this structure is discussed. These data are appended by other annotations, such as biological context, etc. The record consists of 44–47 lines, one line per field. The line starts with the field name followed by colon : (TS = (carbohydrate* OR *saccharide) AND TS = (Proteus) AND PY = (1996–2000)). The paper itself32 is open-access available at the publisher web-site (https://febs.onlinelibrary.wiley.com/doi/full/10.1046/j.1432-1327.2000.01041.x).As an example, we provide a step-by-step description of the annotation procedure for one of the CSDB records , TI (title), JN , PY (publication year), VL (volume and issue), PG (pages), and RL . The additional fields EA (corresponding author e-mail), AD (author affiliations), AB (abstract) and KW (keywords) were also completed. (See the corresponding fields in Online-only Table 33), ST2 , SL  and CC (compound classes/roles) were completed. The fields ST3 (polymerization degree), AG (aglycon information), MF (molecular formula), and 3D  were irrelevant or unknown and were therefore left empty. , KD , and TAX , which refers to the Proteus penneri species; it is given in parentheses, because there is no separate record for strain 63 in the NCBI Taxonomy, but a TaxID exists for a higher rank on the tree of life, namely species). The additional field DSS  was also completed in accordance with the International Classification of Diseases, version 11.The fields related to the biological source of the structure were completed: SO , NMRC (13C NMR assignment), NMRS , and NMRT . , NMRH , U2 (record submission date), U3 , RR (IDs of related CSDB records), and DB . , on the enzymes processing the structure (EI), on its biological activity (BA), biosynthesis (BG), and chemical synthesis (SY). There is also no trivial name of the compound (NC). Online-only Table For annotation, we use full texts of articles from publisher web sites (open-access papers), the Zelinsky Institute subscriptions and library, and requests to the authors if allowed by a publisher license. We do not provide the access to full texts themselves.34:The following data described in this paper are publicly availableText dump for prokaryotic carbohydrates: bcsdb_2021dec06.txt;Text dump for fungal carbohydrates: fcsdb_2021dec06.txt;Text dump for plant carbohydrates: pcsdb_2021dec06.txt;Self-contained CSDB backup (for import using MySQL): CSDB_2021dec23_full.sql;Supplementary data (Tables S1 and S2) used to prepare plots in Fig. 4;Supplementary code used for generation of data in Tables S1 and S2 (needs a running instance of the CSDB database).The text dump files are subject to update biennially.ca. 100 types of data errors and suspicious data combinations. Manual verification of the data is performed by human experts; it allows revealing logical and factual errors that cannot be detected automatically33. The most widespread type of errors found in CSDB are those imported from other databases, e.g. CCSD .The dump files are subject to machine error checking upon import. The quality of the CSDB data is maintained by automatic detection of ca. 2000 errors imported from other databases (primarily CCSD) and ca. 350 errors in structures and NMR spectrum assignment in original publications were found. In the latter case, when the errors could be corrected without additional experimental studies, corrections were suggested. At that, the original erroneous structure was stored in the ST1ORIG field. This field is also provided when a particular structure is revised in later publications. Users can send an error correction request via a dedicated from (a link to this form is available for each database entry at the CSDB web site).According to manual error checking of the CSDB dumps, 36. A distribution of glycosidic linkages in oligomeric  to the size of the structural unit. It allows estimation of the density of charged groups  in a glycan. A detailed description of the sampling and deriving of the statistic data is provided in Tables S1 and S2 . These two examples visually demonstrate differences and similarities between prokaryotic and eukaryotic organisms in terms of their carbohydrate architecture. Due to a close-to-complete coverage on published carbohydrate structures from bacteria and fungi, the presented distributions provide valid scientific information on the studied glycans from these organisms.For illustrative purposes, we carried out an analysis of the current distribution of carbohydrate structures in CSDB in accordance with their antennarity Fig.  and net Of note, the Data Records include a self-contained CSDB image; however, we would like to note that the usage of this image is less flexible for utilizing the data being reported since it implies the same database format as the one already implemented in CSDB.