Nephrolithiasis is a common complication of primary hyperparathyroidism (PHPT), and the recurrence of nephrolithiasis in patients with PHPT is also an urgent concern. What is worse, there is a scarcity of recommended evaluation to predict the risk of nephrolithiasis recurrence in patients with PHPT. This study was aimed to develop and validate a nomogram to facilitate risk assessment in patients with PHPT.A total of 197 patients with PHPT were retrospectively included in this study from September 2016 to August 2021. Patients’ demographic data, blood test parameters, urinalysis, stone parameters, and surgical intervention were collected. Extracted variables were submitted to a least absolute shrinkage and selection operator (LASSO) regression model. A nomogram was built and validated according to the area under the curve (AUC) value, calibration curve, and decision curve analysis.According to the LASSO regression and logistic regression analyses, five predictors were derived from 22 variables: creatinine, uric acid, bilateral stone, multiplicity, and surgery. The AUC and concordance index of the training cohort and validation cohort were 0.829 and 0.856, and 0.827 and 0.877, respectively. The calibration curve analysis and the decision curve analysis showed that the nomogram had an adequate prediction accuracy.We built a useful nomogram model to predict the risk of nephrolithiasis recurrence in patients with PHPT. This would assist clinicians to provide appropriate advices and managements for these patients. Primary hyperparathyroidism (PHPT) is the third most common endocrine disease after diabetes mellitus and thyroid disorders, with an incidence of approximately 65.5 and 24.7 individuals per 100,000 in women and men, respectively . ParathyIt has been reported that about 10% of the patients had pre-existing nephrolithiasis at the time of diagnosis of PHPT . MoreoveThe main objective of this study was therefore to identify the significant predictive factors for nephrolithiasis recurrence in patients with PHPT and to develop and validate a nomogram to facilitate risk assessment. This would assist clinicians to provide appropriate advices and managements for these patients.This study was approved by the Ethics Committee of the Fifth Affiliated Hospital of Sun Yat-sen University (No. K73-1). Data were retrospectively obtained from the medical records between September 2016 and August 2021 at the Fifth Affiliated Hospital of Sun Yat-sen University. All patients were diagnosed as nephrolithiasis with PHTH. PHTH was defined as PTH level > 69 pg/ml with a normal or elevated albumin-adjusted calcium , 12. TheData on the following parameters were collected: sex, age, BMI, medical history (hypertension and diabetes mellitus), blood test parameters , urinalysis , stone parameters , and intervention . Albumin-adjusted calcium level was calculated as follows: corrected calcium (mmol/L) = measured calcium (mmol/L) +  × 0.02).Patients were followed up every 3–6 months, with a range of 3–64 months and a mean follow-up of 25 months. Recurrence of nephrolithiasis was the primary endpoint, which was defined as a new kidney stone on ultrasound and/or CT scan occurring more than 30 days after intervention.www.r-project.org) were used for data analysis. Parameters were described as mean ± SD. When comparing the baseline characteristics, chi-square test or Fisher’s exact test was performed for categorical variables and Wilcoxon signed-rank test for quantitative variables. Modeling time to recurrence of nephrolithiasis was performed using Kaplan–Meier survival analysis. A p-value < 0.05 was considered to be statistically significant.SPSS 19.0  and R software  regression model for data dimensionality reduction and feature selection. Then, independent risk factors associated with recurrence of nephrolithiasis were selected using the logistic regression analysis, and a nomogram was built in the training cohort. A receiver operating characteristic (ROC) curve was subsequently drawn on the basis of predictive factors, and the sensitivity and the specificity were evaluated using the area under the curve (AUC) value. The concordance index (C-index) was used to evaluate the discrimination ability of the nomogram. Calibration curve and decision curve analysis were performed to examine the performance characteristics and assess the clinical benefits. Finally, the validation cohort was used to validate the nomogram constructed in the training cohort.A total of 197 patients were included in the current study, with 105 men and 92 women. According to the ratio of 7:3, 140 patients were randomly assigned into the training cohort and 57 patients in the validation cohort. The clinical characteristics of patients in the training cohort and the validation cohort are summarized in After surgical intervention, 59 patients had at least one recurrent episode of nephrolithiasis. Overall recurrence rate of nephrolithiasis was 29.9%. To screen out the independent predictors, all variables were preliminarily analyzed using LASSO analysis in the training cohort. Five potential predictors were derived from 22 variables Figure 2A nomogram was then constructed on the basis of the abovementioned five predictive factors for nephrolithiasis recurrence in the training cohort Figure 3Nephrolithiasis is a common disease in the general population, with an estimated prevalence of 10%–15% , 14. ThiPHPT is a common endocrine disease characterized by hypercalcemia, which leads to a high incidence and recurrence rate of nephrolithiasis. Mollerup and Lindewald found that the recurrence rate of nephrolithiasis within 5 years was 30% in patients with PHPT . SimilarAlthough with high recurrence rate of nephrolithiasis in patients with PHPT, no prediction model for nephrolithiasis recurrence in patients with PHPT has been reported to date. In the present study, a nomogram for risk prediction of nephrolithiasis recurrence in patients with PHPT was developed and validated. The final model was based on five predictors: creatinine, uric acid, bilateral stone, multiplicity, and surgery. The AUC and C-index of the training cohort and validation cohort were 0.829 and 0.856, and 0.827 and 0.877, respectively. Both the AUC and C-index value suggested that the nomogram could provide good prediction. This model would be helpful to provide appropriate advices and managements for patients with PHPT.p < 0.001). In addition, bilateral stone was also one of the predictive factors . These findings indicate that stone burden is a key predictor for nephrolithiasis recurrence of patients with PHPT.Stone burden is widely used for determining the management of urolithiasis. For kidney stones, evaluation of stone burden has shown to be a predictor of the clinical outcome of different surgical treatments, including flexible ureteroscopy and PCNL , 23. RecExtracorporeal shock wave lithotripsy (ESWL), PCNL, and retrograde intrarenal surgery (RIRS) are the three major treatments for nephrolithiasis. With simple anesthesia requirement and being an outpatient surgery, ESWL is a choice with better patient acceptance. However, a lower stone free rates in patients after ESWL was identified when the effectiveness was investigated , 29. SevUric acid is the end product of purine metabolism, and high level of serum uric acid (SUA) is associated with several health disorders, including diabetes, cardiovascular diseases, metabolic syndrome, and cancer. A clear association has been identified between SUA and nephrolithiasis . PTH couThere are certain limitations in the present study. First, although with a relatively good prediction accuracy, our study was retrospectively designed in a single center and lacked an external population to validate the predictive model. Second, studies have showed some potential variables that are related to nephrolithiasis recurrence, such as 24-h urine collection and parathyroidectomy. The results of existing research studies are contradictory , 35–37, In conclusion, we built a useful nomogram model to predict the risk of nephrolithiasis recurrence in patients with PHPT. This would assist clinicians to provide appropriate advices and managements for these patients.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by the Ethics Committee of the fifth affiliated hospital of Sun Yat-sen University (No. K73-1). The patients/participants provided their written informed consent to participate in this study.YZ, YT, and YD designed the concept of the study. YZ, XC, and DJ collected and analyzed the data. XW, JX, and HQ critically revised the analysis. YZ wrote the draft manuscript. All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.This study was supported by the Guangdong Medical Research Foundation (No. A2021358 to YZ) and the Natural Science Foundation of Guangdong Province (No. 2019A1515012116 to YD).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The literature is limited on the impact of neighborhood parks on quality of life (QoL) and the mechanism linking them.In this paper, we applied the structural equation model to data from a cross-sectional sample of 650 participants in low-income communities of New York City, we examined the associations of neighborhood park use vs. park perception and QoL, and whether these associations were mediated through self-reported perceived stress. We also examined whether park use mediated the relationship between park perception and QoL.β = 0.08, 95% confidence interval (CI): 0.02, 0.15, p = 0.02), but this relationship was not mediated by self-reported stress. Park perception was more strongly associated with QoL than park use , and this was partly mediated by self-reported stress  and, to a lesser extent, by park use .We found that park use had a significant but weak association with QoL (standardized Having well-perceived parks appears to be an important factor for QoL independent of park use, suggesting that quality parks may benefit everyone in a community beyond park users. This strengthens the argument in favor of increasing park investment as a strategy to improve population wellbeing. Quality of life (QoL) is increasingly put forward as a key health outcome measure in its own right, as the notion of wellbeing is increasingly recognized as more than economic wealth or the absence of clinical disease . The EurParks and green space are thought to play an important and positive role in health outcomes, including in QoL, especially in urban environments –14. WhilIn addition to studies that focus on the frequency of park use or proximity to parks in relation to QoL, an emerging body of research shows that subjective perceptions of parks may be an important consideration. For instance, higher QoL has been associated with more positive perceptions of neighborhood open spaces , area grOne possible pathway linking park exposure to QoL may be perceived stress. Several studies have demonstrated that parks could play a role in reducing stress , 24. ForIn light of the fact that QoL has not been well-studied in relation to park exposure variables, and that there is lack of clarity on the relative role of park use vs. park perception and the mechanism connecting these to health outcomes, this paper sought to address these gaps through a cross-sectional structural equation modeling (SEM) study. We also tested the mediational effect of perceived stress and whether park use mediated the association between park perception and QoL. We used data from predominately low-income minority communities in New York City (NYC), a population that has been understudied in the built environment literature.We used baseline data from the Physical Activity and Redesigned Community Spaces (PARCS) Study, conducted across 54 community parks throughout NYC during 2016-18 . PARCS iIndividual-level data in the PARCS Study were obtained from residents that lived within a 0.3-mile Euclidean buffer around each neighborhood park. All participants were recruited by convenience sampling. They were over 18 years old, lived in the study neighborhoods for at least 2 years, intended to stay in the neighborhood for at least 4 years, spoke English, Spanish or Chinese, and had no mobility limitations. At baseline, participants responded to a survey on park perception and usage and psychosocial and community wellbeing. Only participants who provided consent were enrolled in the study. The study was approved by the City University of New York Institutional Review Board.QoL was operationalized using a 9-item scale with Likert response options from the public health surveillance wellbeing scale . It was The 9 items of the scale captured 3 major domains of wellbeing: mental (5 items), social (2 items), and physical health (2 items). The items related to satisfaction with life, clear sense of purpose, and feeling accomplished were rated on a 5-point Likert scale, ranging from 1 = “strongly disagree” to 5 = “strongly agree.” Feelings of cheerfulness and hopelessness in the last 30 days were rated between 1 = “none of the time” to 5 = “all the time.” Items on satisfaction with one's energy level, family, friends, and social life were rated on a scale of 1 (very dissatisfied) to 10 (very satisfied). Lastly, self-reported overall health was rated between 1 (excellent) to 5 (poor). The feeling of hopelessness and self-reported health status were reverse coded so that higher values meant higher QoL for all items.To assess the frequency of park use, we adopted 2 questions from Veitch et al. [test-retest intraclass correlation (ICC) = 0.79–0.85] . The oriFor individual-level park perception, we used a set of 10 survey questions developed by Veitch et al. (test-retest ICC = 0.36–0.72) . Items wTo assess stress, we used the Perceived Stress Scale (10 items) by Cohen et al.  . The scaParticipants self-reported age (years), sex , household income , and race/ethnicity .We conducted a multiple-mediation analysis using an SEM with complete cases. SEM provides an advantage since the models include specific and accumulative associations between different variables and evaluate multiple mediators effects simultaneously in a single model . Additiop-value were reported. To validate the fitness of the SEM, χ2 values, the Comparative Fit Index (CFI), the Tucker-Lewis Index (TLI), and the root-mean-square error of approximation (RMSEA) were used. We considered a model acceptable when the CFI and TLI were 0.90 or greater and the RMSEA value was 0.06 or less.In addition to the direct effect of park use and park perception on QoL, we evaluated 3 mediation pathways:  (1) the n = 1,354). We chose FIML over the other imputation methods since it provides better estimates for SEM  approach to impute the missing values for those participants who had answered at least one but not all of the survey questions and re-ran the SEM with the larger sample  had a mean age of 38.8 ± 11.8 years, half (53.4%) had an annual household income below $20,000, and 81.7% were women. Latinos constituted 48.8% of the sample, while 38% were Black (Participants in the sample (re Black . On an aMeans and standard deviations of underlying factors of the latent constructs of QoL and park perception are shown in 2 = 420.87 (187), TLI = 0.93, CFI = 0.95, and RMSEA = 0.04. The model explained 47.1% of the variance in QoL. p = 0.02), with no significant mediation through self-reported stress . In Pathway #2, park perception had a direct association with QoL  and a significant indirect association that was partially mediated through self-reported stress . In Pathway #3, park perception also had a significant indirect association with QoL that was mediated through park use . Similar results were found when SEM was performed with multiple imputations for missing values in the larger sample . The final SEM showed a good model fit with χTo our knowledge, this is the first study to examine the role of park use and park perception on QoL and to explore the mechanisms that may underlie these relationships. Park perception had a stronger association with QoL than park use. In addition, the association of park perception with QoL was mediated through self-reported stress to a greater extent than through park use. Although the model tested was relatively parsimonious, it explained nearly half of the variance in QoL.The significant association between park use and QoL in our study was corroborated by prior research in urban settings showing that visits to parks or green space improved mental and physical health . Of noteThat perception of parks may play a larger role in QoL than actual park use, as indicated from the SEM. This suggests that having quality parks in a neighborhood may confer benefits to the wellbeing of local residents even if they do not engage in frequent park use. Although this is a new finding, the National Recreation and Park Association previously conducted a survey on the perception and use of local recreation and park services among Americans and showed that even non-users of parks believed that having a local park, playground, or open space in their neighborhood was important to their personal and community wellbeing . In anotvia the mediation of stress. However, in a virtual reality experiment, it was reported that parks and urban green space reduced stress levels through olfactory, audio, and visual sensory stimulation  to measure progress and prosperity. However, GDP does not capture environmental and social wellbeing or the degree to which people are satisfied with their living conditions , 57–61. In general, urban green space shares a complex relationship with health. It is inversely associated with the prevalence of non-communicable diseases related morbidity, and mortality , 62–64, This study could be beneficial to urban planners and policymakers looking to revitalize or future-proof urban environments. Currently, there is a rise in investment in urban green space to create more equitable parks, with special attention paid to building new parks or renovating existing parks in low-income neighborhoods . It is eThe primary limitation of our study is that it was cross-sectional. Therefore, caution should be taken in inferring causality. Future longitudinal studies could be helpful to examine cause-and-effect and to determine if our findings hold over time. Second, our study did not examine the multiple pathways that parks could influence QoL. However, this paper sets the stage for future research that can account for the diverse synergistic framework described by the World Health Organization . In addiNevertheless, our study also has many strengths. First, in light of the issue of environmental and health equity, we specifically undertook our study in low-income, minoritized communities, making an important contribution to the limited literature on the topics of parks and QoL in underserved populations. In addition, the use of SEM in this area of inquiry was novel and allowed us to test the effect of multiple pathways involving latent constructs simultaneously , 35. LasIn conclusion, we showed that both the perception and frequency of use of parks are important to QoL. However, our findings also suggest that having quality parks in a neighborhood could be broadly beneficial to community residents, even beyond frequency of use. This finding strongly supports the investment in community parks, as all residents may benefit from such investment, not just regular park users. In addition, our study showed that stress reduction may be an important mechanism for the effect of park perception on QoL, but that it may not play a role in associations between park use and QoL. Nonetheless, our model suggests that this explanation may be incomplete, and more research is needed to further elucidate the ways in which park perception and park use contribute to QoL. With parks and QoL both at the forefront of policy discussions in the US and around the world, this study demonstrates that these two factors are indeed connected and suggests that strategic investment in public parks can play a critical role in reducing inequities and improving the wellbeing of all residents.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 City University of New York Institutional Review Board (#2016-0248). The patients/participants provided their written informed consent to participate in this study.HK: methodology, software, formal analysis, data curation, writing—original draft, and visualization. EF: writing—original draft. KW: supervision. KE and JD: writing—review and editing. LT: writing—review and editing and funding acquisition. TH: conceptualization, methodology, writing—review and editing, supervision, and funding acquisition. All authors contributed to the article and approved the submitted version.


In recent years, there has been increasing interest in studying differences in recipient sex in renal disease treatment, access to renal replacement therapy, and subsequent outcomes. Our aim was to find out whether there are differences in outcomes after renal transplantation between female and male kidney transplant recipients in our series, particularly in adults under 60 years of age during long-term follow-up.n = 1,101) to compare graft survival depending on the sex of the recipient in the entire series and patients < 60 years of age (n = 687) during long-term follow-up.This was a retrospective study of our kidney transplant series (p = 0.040). Pre-transplant sensitization  and donor age  were the independent variables associated with graft failure.We observed no association between recipient sex and graft survival throughout the series, regardless of recipient sex. However, adult female recipients under 60 years of age had lower graft survival than male recipients (per se was not related to graft failure, but the greater immunological risk in women and more frequent use of expanded criteria donors in female recipients under 60 years of age were the main factors related to their poorer graft survival. Further studies and new strategies are needed to identify these differences and develop the best approach to address them.Female recipients younger than 60 years of age had lower graft survival than male recipients, although there were no gender differences in graft or patient survival in the overall study population. Recipient sex  There is growing evidence that there are inequalities in various aspects of kidney disease, such as the burden of kidney disease, access to renal replacement therapies (RRT), or their subsequent development, in relation to the gender of the recipient –3. A higSeveral authors and large registries have found no difference in survival between men and women after kidney transplantation, although the effect of the recipient’s sex on graft survival has been disputed in several studies , 4, 6. TWe performed a retrospective analysis on 1,101 adult deceased and living donor kidney transplant recipients at our hospital from January 2000 to January 2019. None of them was a multi-organ transplant. The allocation process during the period of analysis was not based on a computer algorithm but the independent decision of the nephrology staff. Patients gave signed consent for the use of their clinical and personal data for educational and research purposes. Data were taken from our kidney transplant database, which includes variables on donor and recipient demographics, kidney function, infections, cardiovascular disease, development of cancer, and graft failure or death and includes all patients transplanted since the start of our kidney transplant program. All data were extracted from each patient’s medical records and entered into the database by trained personnel. The data were kept confidential in accordance with Spanish law and the Declaration of Helsinki.We analyzed the demographic characteristics of the recipients, such as sex, age, dialysis modality , dialysis time (in months), re-transplantation, previous HLA sensitization, pre-transplant comorbidities such as hypertension (HTN), diabetes mellitus (DM), smoking habits or ischemic cardiomyopathy, body mass index (BMI), and end-stage renal disease (ESRD) etiology. Donor demographics such as sex, age, type of donor brain death donor (DBD), donor after circulatory death , cerebrovascular death, HTN, and serum creatinine were analyzed. Duration of cold ischemia (hours), immunosuppressive treatment (tacrolimus), delayed graft function (DGF), acute rejection (AR) during the first 6 months diagnosed by biopsy, etiology of graft failure, and patient death were also studied.Initially, we considered HLA sensitization in patients with PRA higher than 10% and, after 2012, in patients with anti-HLA higher than 1,500 MFI (Luminex techniques).The immunosuppressive regimen included therapy with a standard dose of a calcineurin inhibitor (tacrolimus or cyclosporine), m-Tor inhibitors (sirolimus or everolimus), mofetyl mycophenolate, or sodium mycophenolate, and steroids in a decreasing dosage. Induction treatment with interleukin-2 receptor antagonist was used in non-extended criteria donors and low immunological risk patients. Thymoglobulin in reduced doses (two to three doses of 1.25 mg/kg every other day) was used for induction in the case of extended criteria donors with a high risk of DGF and a maximum cumulative dose of 6 mg/kg in those patients with high immunological risk .t-test was used to compare the quantitative variables that were normally distributed, and the Mann-Whitney test was used for the non-normally distributed ones. Normality was tested with the Shapiro-Wilk test and the Bartlett test. Graft survival according to recipient sex was calculated using the Kaplan-Meier method, and the null hypothesis was tested using the Log-rank test.Initially, a descriptive analysis of donor and recipient demographics and post-transplant variables was performed. Qualitative variables were described with absolute frequencies and percentages. Quantitative variables were summarized as the mean and standard deviation. A bivariate analysis to compare donor and recipient characteristics as well as the post-transplant variables, depending on the recipient sex, was performed. Associations between qualitative variables were evaluated by Fisher’s exact test. Based on the recipient sex, the Student’s Additionally, Cox regression models were used to evaluate the time to graft failure depending on recipient and donor characteristics. The following were considered as possible explanatory variables in the model: sex, age, BMI, pre-transplant HLA-sensitization, donor sex and age, cardiovascular disease as the cause of donor death, cold ischemia time, and AR episodes in the first 6 months after transplantation. Goodness-of-fit of the models was evaluated by calculating their concordance, that is, the degree to which the models distinguish between patients at higher risk and lower risk . The score test was used to verify the proportional risk assumption . All theP-values less than 0.05 (two-tailed) were considered statistically significant.R software version 4.0.5  was used to perform statistical analysis. The whole study population included 1,101 kidney transplant recipients with a mean follow-up of 7.2 ± 5.9 years (interquartile range: 2 – 11.1), of whom 435 (39.5%) were female recipients and 666 (60.5%) were male recipients.p = 0.014). The main causes of death were cardiovascular diseases and cancer  and infectious diseases, with no statistical differences  was worse in female recipients than in male recipients only during the first 4 years of the follow-up (p < 0.05).The distribution of patients depending on their age at the time of transplantation resulted as follows: 404 patients older than 60 years (37.1%) and 685 patients < 60 years (62.9%). Recipients < 60 years were 277 (40.4%) women and 408 (59.6%) men. In the bivariate analysis, no age differences were found between female and male recipients at the time of transplantation . ESRD dip = 0.037) later in the follow-up period, from the seventh year onward (p = 0.003) (p = 0.027), followed by donor age  (p < 0.001). No differences in graft survival were found between sensitized patients transplanted with grafts from younger donors and non-sensitized recipients transplanted with grafts from donors older than 60 years (p = 0.845). Patient survival was similar in both men and women    . Recipie= 0.017) . We anal= 0.850) , as was In this study, we found that there are differences in graft survival between women and men in patients younger than 60 years, unlike in the older population. This fact led us to consider the need to develop different strategies to improve outcomes in this high-risk population.Numerous differences related to the gender of the recipient have been described in the medical literature. First, the prevalence of CKD is higher in women than in men , a fact We designed this study to investigate whether post-transplant outcomes differ among men and women in our single-center cohort of renal transplant recipients. The ratio of female to male transplanted patients in our series was similar to that described in other studies, with almost 40% of female patients and 60% of male patients, supporting the differential need for RRT according to the gender of the recipient  and rarely extended to other geographical locations or health systems –24, 26. However, our study has allowed us to learn about the state of this issue in our center, where deceased donors are our main source of kidneys, with a high proportion of donors with expanded criteria, and these results could be representative of other transplant programs with similar characteristics and allocation policies to ours. The most important question for us is how to improve graft survival in adult female recipients younger than 60 years. In our opinion, we need protocols that include pre-transplant and post-transplant measures. Before transplantation, sensitized patients should be enrolled in specific programs to achieve the best HLA compatibility, such as the National Priority Allocation System for Hypersensitized Patients based on virtual crossmatching, which has shown excellent results in cadaveric donor transplantation in Spain and the development of similar programs at the regional level . DesensiIn summary, no differences in graft and patient survival were found in the overall study population depending on the sex of the recipient, but the group of female recipients younger than 60 years had lower graft survival at longer follow-up than the male recipients. HLA sensitization and older donors were the main risk factors for poorer graft survival, with both factors being more pronounced in young female recipients. In female recipients younger than 60 years, strategies to improve outcomes are needed to avoid allocation bias and differences in graft survival depending on the gender of the recipient. These differences could be underestimated. Therefore, multicenter and high-quality studies are needed to improve our knowledge of this problem, find the best approach to avoid it, and, finally, improve our outcomes in long-term follow-up.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study.AS, EG, and JK participated in the research design, the writing of the manuscript, the performance of the research, and in the data analysis. SB, CC, and VE participated in the research design and the writing of the manuscript. JP and PM analyzed the data. BV, MG, and EC made the figures and revised the manuscript. AA drafted and revised the manuscript. All authors approved the final version of the manuscript.


There is a cumulative risk of 20–40% of developing brain metastases (BM) in solid cancers. Stereotactic radiotherapy (SRT) enables the application of high focal doses of radiation to a volume and is often used for BM treatment. However, SRT can cause adverse radiation effects (ARE), such as radiation necrosis, which sometimes cause irreversible damage to the brain. It is therefore of clinical interest to identify patients at a high risk of developing ARE. We hypothesized that models trained with radiomics features, deep learning (DL) features, and patient characteristics or their combination can predict ARE risk in patients with BM before SRT.N = 1,404) and a validation cohort (N = 237) from a separate institute. From each lesion in the training set, radiomics features were extracted and used to train an extreme gradient boosting (XGBoost) model. A DL model was trained on the same cohort to make a separate prediction and to extract the last layer of features. Different models using XGBoost were built using only radiomics features, DL features, and patient characteristics or a combination of them. Evaluation was performed using the area under the curve (AUC) of the receiver operating characteristic curve on the external dataset. Predictions for individual lesions and per patient developing ARE were investigated.Gadolinium-enhanced T1-weighted MRIs and characteristics from patients treated with SRT for BM were collected for a training and testing cohort . On a patient level, a combination of radiomics features, DL features, and patient characteristics obtained the best performance . The DL model achieved an AUC of 0.64 and recall of 0.85 per lesion and an AUC of 0.70 and recall of 0.60 per patient.Machine learning models built on radiomics features and DL features extracted from BM combined with patient characteristics show potential to predict ARE at the patient and lesion levels. These models could be used in clinical decision making, informing patients on their risk of ARE and allowing physicians to opt for different therapies. Brain metastases (BM) are the most common intracranial malignancies, accounting for more than 50% of all brain tumors and occurring in 10 to over 40% of patients with solid malignancies . BM occuEven though most of the healthy brain is spared from high doses of radiation, a major shortcoming of SRT is a chance of high toxicity in the immediate surrounding tissues, which may lead to adverse radiation effects (ARE) such as radiation necrosis (RN), subacute edema, structural changes in the white matter, and vascular lesions . ARE areUnfortunately, the  symptoms of ARE and TP are usually indistinguishable. Furthermore, the appearances of ARE and TP are very difficult to discern through qualitative radiological imaging, requiring multiple successive magnetic resonance images (MRI), specialized MRI sequences such as perfusion-weighted or MR spectroscopy, and trained experts to evaluate the findings , 20. TheSRT requires routine pretreatment MRI for accurate target volume delineation. This imaging provides a source of non-invasively acquired information about BM and brain phenotypes that could be investigated for their potential to determine before treatment which patient has a high risk of developing ARE. The early identification of these patients is an unmet clinical need which may help in clinical decision making by informing the patients of the risk of ARE, the early risk stratification of patients that may develop ARE, and the consideration of ARE risk mitigating strategies such as deferring radiotherapy for central nervous system-penetrant systemic therapy.Advanced quantitative medical image analysis methods such as radiomics and deep learning (DL) extract large amounts of imaging features and associate these with biological and/or clinical outcomes using machine learning (ML) techniques –26. ThusWe hypothesize that models trained with radiomics features, DL features, and patient characteristics or a combination thereof can predict the occurrence of ARE in patients with BM, both lesion specific and patient specific.https://irb.ucsf.edu) and Cantonal Ethics Committee Zurich approval with waiver of informed consent was obtained.All data from patients with BM treated with SRT between 1997 and 2017 for which imaging, outcome data, and patient data were available were collected retrospectively from the University of California—San Francisco (UCSF) medical center’s picture archiving and communication system. Available imaging data, outcome data, and patient data of all patients with BM treated with SRS/SRT between 2014 and 2019 at the University Hospital Zürich (USZ) were collected retrospectively. The data included clinical and biological information for both the patient and the lesion. The eligibility criteria included radical treatment for metastatic brain cancer using Gamma Knife SRS for the UCSF patients and SRS/FSRT for the USZ patients. The inclusion of patients was regardless of the number of BM, but pathohistological or imaging-based confirmation of ARE during the follow-up was required in addition to pathohistological confirmation of the primary tumor. For the USZ cohort, in case of imaging-based suspicion of RN, positron emission tomography imaging was additionally used to exclude TP. The effort obtained ethical approval for observational research using anonymized linked care data for supporting medical purposes that are in the interests of individuals and the wider public. UCSF Institutional Review Board  and testing (30%) while maintaining the ratios of events to non-events equal in both groups. The USZ dataset was used as an independent external validation dataset, All images were axial gadolinium-enhanced T1-weighted MRI acquired prior to the treatment of BM. All included lesions were three-dimensionally delineated for curative Gamma Knife SRS treatment purposes for the UCSF cohort and for curative SRS/FSRT purposes for the USZ cohort according to local protocols by an experienced radiation oncologist. To perform segmentations of the brain and the ventricles on the entire dataset, an atlas-based segmentation strategy was chosen. To create the atlas in the MIM software package , 50 randomly chosen MRI were manually segmented by an expert radiologist.Bias-field correction was performed in the MIM software package using the N4 algorithm, which required brain segmentations . A bias Following the bias correction, all remaining pre-processing, feature extraction, model training, and evaluation were performed in Python (version 3.7). The different Python packages used during this study can be found in 3 voxels using the “sitkBSpline” interpolator to correct for differences in pixel size and slice spacing. The choice for voxel dimensions was made based on majority ruling, as it was found that most patients had a pixel spacing of ~1 mm. To achieve isotropic voxels, the choice for resampling in the z-direction was also chosen as 1 mm. Pixel intensity values were resampled to a fixed number of 64 bins, as the number of gray levels was found to affect the interchangeability of MRI radiomics features, and a fixed bin number of 64 has been found recommended in previous studies (Feature extraction was performed according to the Image Biomarker Standardization Initiative (IBSI) guidelines –44 on th studies –44.A total of 106 IBSI features were extracted from each segmentation. The features were extracted from the BM segmentations of the pre-processed images and can be divided into first-order intensity, histogram statistics, shape, and texture features. A full list and a description of the features can be found in the PyRadiomics documentation  model was used for RFE and ARE prediction. A description of the XGBoost architecture and the methodology to determine the optimal hyperparameters for the trained models can be found in the -5, which updated the learning rate during training, and used for loss function binary cross-entropy. This model produced a score ranging from 0 to 1, indicating the estimated probability that a lesion develops ARE. The area under the curve (AUC) of the receiver operating characteristic (ROC) was monitored on the test dataset. The ROC displays the discriminative performance of a model expressed through the sensitivity and specificity as the threshold for binary classification is shifted. The AUC of the ROC is a metric from 0 to 1, where 1 means that the model has perfect predictive performance and 0.5 is equivalent to guessing. To limit the imbalance of the outcomes to affect the model training, the model was only trained on lesions for those patients who had at least a single ARE and tested on the scans of the patients who had ARE in the test dataset. To combine DL and radiomics, the last fully connected layer consisting of 256 features obtained after training the model was extracted. These features were then used to train a ML model similarly to using radiomics features and used in models combining radiomics features and patient characteristics.An Xception three-dimensional model was trained and tested on the same datasets as the handcrafted radiomics-based model. Xception is the extreme version of an Inception model , which uAs the training and testing datasets contained patient characteristics not available in the external validation dataset, any feature not overlapping between these datasets was dropped. The list of the remaining features was as follows: primary tumor location, primary tumor histology, primary tumor controlled, extra-cranial metastases presence, patient age, patient sex, SRS to the same location, prior external beam radiotherapy (EBRT), prior radiosurgery (RS), neurological symptoms, headaches, seizures, hypertension, diabetes, connective tissue disorder, Karnofsky performance score (KPS) status, prescription dose, and isodose lines. For XGBoost to be able to handle categorical variables, one-hot encoding was performed on two categorical clinical features (primary tumor location and primary tumor histology).i.e., each column). Then, over multiple iterations, each data column with missing values will be predicted using all the data except for the rows containing the missing values in question. This process is repeated over several iterations.Missing values were imputed using MissForest. MissForest is an imputation algorithm that uses RandomForest to train a model on the non-missing data for each feature with missing values to predict the missing values. In the first iteration, all values are set to the mean value present for each variable . For the radiomics-based model, the results were reported on the full train dataset and the entire test dataset. For the DL model, the results were reported on the balanced train dataset (which served to train the different DL models) and the full test dataset.To determine which method ensured best performance for the radiomics-based and DL models, models were trained on the three different pre-processed datasets, and the best AUC of the ROC on the testing set was used to determine the best pre-processing methods for ML and DL separately. The 95% confidence intervals (CI) displayed on the ROC curves were obtained using bootstrapping , median age (P = 0.03), KPS status (P < 0.01), and the number of lesions per patient at treatment (P < 0.01) were found. Furthermore, the proportions of primary tumor  were different between the datasets, and the data from USZ did not have kidney, GI, sarcoma, or other types of primary locations that were present in the UCSF dataset. For the histology of the primary tumor, only the melanoma histology subtype was found to be present in a significantly different proportion.A total of 1,404 patients with 7,974 lesions from UCSF and 237 patients with 646 lesions from USZ were included. The best AUC on the test dataset for the radiomics-based models was found using the “harmonization” normalization, with an AUC of 0.76 (CI of 0.70–0.81), compared with 0.75 (CI of 0.70–0.80) and 0.73 (CI of 0.67–0.79) for the “minimalist” and “standardization” methods, respectively.The best AUC on the test dataset for the DL models was found using the “standardization” normalization, with an AUC of 0.72 (CI of 0.66–0.78), compared with 0.63 (CI of 0.57–0.70) and 0.65 (CI of 0.58–0.71) for the “minimalist” and “harmonization” methods, respectively. We calculated the AUC and CI for each model combination on the external validation dataset. The DL model, built on images pre-processed with the “standardization” method, achieved an AUC of 0.64 (CI of 0.50–0.76). The model built on radiomics features, extracted from the images pre-processed with the “harmonization” method, achieved an AUC of 0.73 (CI of 0.63–0.83). The model was built on 20 features selected through RFE. The combination of radiomics and DL features achieved the highest combination of balanced accuracy and recall of 0.67 (CI of 0.56–0.76) and 0.80 (CI of 0.62–0.96), respectively, of the externally validated models for predictions per lesion. For a patient-level prediction, the DL model achieved an AUC of 0.70 (CI of 0.56–0.80) and that of the radiomics model an AUC of 0.72 (CI of 0.60–0.83). A combination of radiomics and DL achieved an AUC 0.71 (CI of 0.57–0.83), that of a combination of radiomics and patient characteristics an AUC of 0.71 (CI of 0.59–0.81), and that of a combination of radiomics features, DL features, and patient characteristics an AUC of 0.72 (CI of 0.58–0.84). The model combining radiomics features, DL features, and patient characteristics achieved the highest combination of balanced accuracy and recall of 0.65 (CI of 0.55–0.74) and 0.84 (CI of 0.65–1.00), respectively, of the externally validated models for predictions per patient. The DL model predictions and the radiomics-based model predictions per lesion agreed for 32% of the external dataset. For the per-patient classification, the DL model predictions and the radiomics combined with clinical feature-based model predictions agreed for 19% of the external dataset. Because the number of patients for which the models agreed was low , no CI could be derived. Patients with BM treated with SRT are at risk of developing ARE, such as RN. Early identification of these patients can help in clinical decision making. The MRIs required for SRT planning provide an opportunity to identify these patients through quantitative imaging methods. In this large-scale study, ML models that can successfully predict ARE were trained on T1-weighted MR imaging features from secondary brain tumors treated with SRT. As no consensus to harmonize MR images within and between centers exists, multiple methods were tested for the DL and ML pipeline, resulting in two optimal pre-processing methods (“harmonization” for the ML pipeline and “standardization” for the DL pipeline). A ML model trained with radiomics features combined with DL features yielded the highest predictive performance, with a combination of ROC AUC, balanced accuracy, and recall of 0.71, 0.67, and 0.80, respectively. At the patient level, the best-performing ML model was clearly a combination of radiomics, clinical , and DL features achieving the highest predictive performance (AUC of 0.72), a balanced accuracy of 0.65, and recall of 0.84.i.e., using only those predictions that agreed on the outcome) did not improve predictive performance for the lesion-level prediction (AUC of 0.67) nor the binary prediction . However, using this method, the highest recall of 0.90 was achieved, making this method very robust in detecting true positives.Performing an aggregate prediction , if the risk of ARE outweighs the possible benefits of SRT  of 1,404 patients in training and testing and 646 lesions (3.1% ARE) of 237 patients in the external validation. This provides a large volume of data for our models to train on, ensuring that it covers the wide variability found between patients. In addition, the inclusion of an external validation is another strength, especially seeing the general lack of one in most other studies investigating ARE. This ensures that the reported result is not too optimistic and shows that our model can be generalizable to populations from a different hospital in a different country and even with different treatments from the training and testing sets. While the difference in treatment between the training (exclusively SRS) and external validation (a mix of SRS and FSRT) may induce variability due to small differences in treatment planning for these methods, literature has shown that these methods carry the same risk of ARE and were therefore considered interchangeable , 17, 19.n = 20). This is because of the large imbalance in outcomes for both ARE and tumor failure. One of the major problems that may arise from this imbalance is a skewed view of predictive performance. However, this was addressed in the present study through multiple measures. The DL model was trained on a balanced subset of the data that only included patients that suffered at least 1 ARE. For ML, the XGBoost model was trained while scaling the weights of positive and negative classes and the respective proportion of the labels. Finally, through analysis of the confusion matrix, precision recall curves, and recall metric, we ensured that the performance of the model was not entirely driven by labeling the data as the majority class.The large confidence interval on the external validation is partially due to the low number of positive findings in this dataset , treatment is one of the primary factors. In this study, multiple-dose-treatment-related variables have been included, such as prior treatments to the same patients as well as dose variables and the volumes encompassing certain dose levels. However, a more thorough “dosiomics” analysis would probably improve the prediction of ARE. Liang et al.  describeRadiomics is able to predict lesions at a high risk of ARE, especially when combined with DL features. When predicting ARE on a patient level, the highest performance was found using a combination of radiomics, DL, clinical, and treatment-related features. These models could potentially be used to aid clinical decision making for patients with BM treated with either gamma knife or EBRT.olivier.morin@ucsf.edu (for the data from UCSF); Nicolaus.Andratschke@usz.ch (for the data from USZ).The corresponding author does not own the datasets used (acquired with DTAs). Requests to access the datasets should be directed to The studies involving human participants were reviewed and approved by the cantonal ethics committee Zurich and University of California San Francisco (UCSF) Institutional Review Board (IRB). Written informed consent from the participants’ legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.MB and SK performed all the ML/DL analysis and wrote the manuscript. SK, MV, SB, and OM collected and curated the imaging and patient data from UCSF. SP helped with the ML/DL analysis and study design. HW supervised the progression of the project and the writing of this article and guaranteed the integrity of the analysis and results presented. AC and MV helped with the ML analysis. JT, JK, and NA collected the imaging and patient data from USZ. LH and SB aided with the clinical aspects of the study. PL and OM devised the project’s aim and supervised the progression of the project. All authors contributed to the article and approved the submitted version.The research project has been partially funded by the Clinical Research Priority Program “Artificial Intelligence in Oncological Imaging” of the University of Zurich. PL, HW, MB, SK acknowledge financial support from ERC advanced grant (ERC-ADG-2015 n° 694812 - Hypoximmuno), the European Union’s Horizon 2020 research and innovation programme under grant agreement: MSCA-ITN-PREDICT n° 766276, CHAIMELEON n° 952172, EuCanImage n° 952103 and IMI-OPTIMA n° 101034347.LH: none related to the current manuscript, outside of current manuscript: research funding Roche Genentech, Boehringer Ingelheim, AstraZeneca, Takeda ; advisory board: BMS, Eli Lilly, Roche Genentech, Pfizer, Takeda, MSD, Merck, Novartis, Boehringer Ingelheim, Amgen, Janssen ; speaker: MSD, Lilly (institution); travel/conference reimbursement: Roche Genentech (self); mentorship program with key opinion leaders: funded by AstraZeneca; fees for educational webinars: Benecke, Medtalks, VJOncology (self), high5oncology (institution); interview sessions funded by Roche Genentech, Bayer, Lilly (institution); local PI of clinical trials: AstraZeneca, Novartis, BMS, MSD, Merck, GSK, Takeda, Blueprint Medicines, Roche Genentech, Janssen Pharmaceuticals, Mirati; PL: none related to the current manuscript; outside of current manuscript: grants/sponsored research agreements from Radiomics SA, Convert Pharmaceuticals and LivingMed Biotech. He received a presenter fee (in cash or in kind) and/or reimbursement of travel costs/consultancy fee (in cash or in kind) from Radiomics SA, BHV, Varian, Elekta, ptTheragnostic/DNAmito, BMS, and Convert pharma. PL has minority shares in the companies Radiomics SA, Convert pharmaceuticals, Comunicare, and LivingMed Biotech, and he is co-inventor of two issued patents with royalties on radiomics (PCT/NL2014/050248 and PCT/NL2014/050728), licensed to Radiomics SA; one issued patent on mtDNA (PCT/EP2014/059089), licensed to ptTheragnostic/DNAmito; one non-issued patent on LSRT (PCT/ P126537PC00), licensed to Varian; three non-patented inventions (softwares) licensed to ptTheragnostic/DNAmito, Radiomics SA and Health Innovation Ventures and two non-issued, non-licensed patents on Deep Learning-Radiomics . He confirms that none of the above entities or funding sources were involved in the preparation of this paper.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Analyzing the entire sample, we found a positive correlation between FVC and a negative correlation between FEV1/FVC with fat mass markers. At the same time, inspiratory capacity, expiratory reserve volume, and peak expiratory flow were correlated with lean body mass markers. In addition, participants with obesity presented a lower dysanapsis index. In conclusion, children and adolescents with obesity showed increased FVC and reduced FEV1/FVC. Our findings are possibly related to the increase in fat mass, not to lean body mass. We hypothesize that these findings are associated with the dysanaptic growth pattern, which is higher in obesity, evidenced by the reduction of the dysanapsis index.Lung function in children and adolescents with obesity must consider the coexistence of two complex and related phenomena: obesity and growth. The assessment of body composition can identify changes in respiratory dynamics arising, exclusively or jointly, from adiposity and lean body mass. This study aimed to compare pulmonary function and the dysanapsis indices of children and adolescents without asthma, with and without obesity, considering body composition, pubertal development, and physical activity practice. We performed a cross-sectional study with 69 participants, 41 (59.42%) of whom have obesity. All participants carried out spirometry and the assessment of, respectively, body composition by dual-energy X-ray absorptiometry, vital signs, pubertal development, and physical activity practice. In our data, the group with obesity had higher values of forced vital capacity (FVC) and lower values of the ratio between forced expiratory volume in one second and FVC (FEV Obesity is a chronic dysfunction that interferes with multiple systems of the human body, including the respiratory system and pulmonary function ,2,3. TheBoth obesity and growth act in the development of systems. For this reason, in the analysis of the pulmonary function of individuals with and without obesity, one must consider the transformations of the body during childhood and puberty . Recent The interpretation of pulmonary function and growth in obesity is even more complex in the presence of diseases. The literature frequently associates the pulmonary function of children and adolescents with obesity and asthma since they present prevalence with parallel trajectories over the years and inflammatory and immunological aspects, and their causality relationship is not yet well defined ,21,22,23Thus, this study aimed to compare the pulmonary function and dysanapsis indices (DIs) of children and adolescents without asthma, with and without obesity, considering their body composition, pubertal development, and physical activity practice.Non-smoking participants without asthma, according to the International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire , of bothParticipants with obesity do follow-up in the outpatient clinic of obesity in children and adolescents of the Clinical Hospital of the University of Campinas (Unicamp) and receive multidisciplinary guidelines regarding the practice of physical activity and healthy eating. Participants of the control group volunteered to take part in the assessments, seeking the service after disclosure in social networks.The participants and those responsible for them received prior guidance for participants to attend the study location with light clothes, without metals (such as buttons or zippers), and having only a light meal six hours before the evaluations. Participants were told not to perform strenuous physical activity in the 24 h prior to the assessments. In the study, sex and ethnicity (race) were obtained by interview.2), and systolic (SBP) and diastolic (DBP) blood pressure were measured. The anthropometric data were used to calculate the body mass index (BMI)—weight/height2—and its distribution in the percentiles and z-score, following the criteria of the World Health Organization (WHO) for individuals up to 19 years /3 /3 .TM Pneumo , integrated with JLab version 5.20 , following the specifications of the European Respiratory Society (ERS) and American Thoracic Society (ATS) [1); (iii) FEV1/FVC; (iv) expiratory reserve volume (ERV); (v) average expiratory flow (FEF25–75%); (vi) peak expiratory flow (PEF); and (vii) inspiratory capacity (IC). FVC, FEV1, FEV1/FVC, and FEF25–75% were analyzed by z-score and percentile, using the references from Quanjer et al. (2012) from the software of the Global Lung Initiative. Pulmonary function was assessed in the spirometer MasterScreenty (ATS) . The parThe absolute values of pulmonary function markers were used in the calculation of the DI, proposed by Mead (DI1) (1980), to quantify the ratio between lung and airway size. DI was calculated by the ratio between forced expiratory flow at 50% (FEF50%) of the FVC, FVC, and elastic recoil pressure at 50% of the FVC (Pst 50%) by the formula: DI1 = FEF50%/(FVC × Pst 50%) . The PstBody composition was measured by dual-energy X-ray absorptiometry (DXA) in the equipment iDXA  with fan beam detectors. The data were processed and analyzed in enCoreTM (2011), version 13.6 , with the inclusion of the absolute value and normality adjustment for age, sex, and ethnicity (race). Some of the participants with obesity exceeded the area of assessment of DXA; thus, the whole-body technique with mirroring of the left arm was used to standardize the measures without a bias between the techniques. The DXA markers assessed were: (i) fat mass and lean body mass ; (ii) total body mass; (iii) total fat percentage; and (iv) fat-free mass.This study collected data considering the practice of scheduled and unscheduled physical activities by applying the international physical activity questionnaire (IPAQ) . AccordiThe descriptive analysis is presented by relative and absolute frequencies for categorical data and mean ± standard deviation and median (25th percentile and 75th percentile) for the data with the numerical distribution. The following techniques evaluated the normality of the numerical data: (i) analysis of descriptive measures for central trend; (ii) graphic method ; and (iii) method by statistical testing : Kolmogorov–Smirnov and Shapiro–Wilk tests.t-test for independent samples, depending on the data distribution. The same statistical tests were applied to compare the distribution of the numerical data according to sex in each group (obesity versus control group). Pearson correlation and Spearman correlation tests were used in the correlation analysis, depending on the data distribution. In the comparison between categorical variables, Fisher’s exact and chi-square tests were applied. The association between the groups with and without obesity—the control group (independent variable) and the numeric markers (dependent variable) for the two groups—was examined by the Mann–Whitney U test for independent samples or by a The statistical analysis was performed in the Statistical Package for the Social Sciences . The analyses considered the alpha value of 0.05. No technique was used to handle the adjustments for “missing data”. All the data were collected from all participants for the measures of pulmonary function and body composition.p < 0.05). In addition, ethnic (race) differences between the groups were found (p = 0.038). There were no significant differences in DI2 (p = 0.065) between groups; however, participants from the obesity group presented lower DI1 (p = 0.031). 2 were equal between the groups. p = 0.138)/pubic hair (p = 0.089), and no difference was found between the groups with and without obesity.p > 0.05). Trunk fat mass and BMI-z had a CC = 0.791 (p < 0.001), while trunk lean mass and BMI-z had a CC = 0.153 (p = 0.214). Android fat mass and BMI-z had a CC = 0.816 (p < 0.01), while android lean mass and BMI-z had a CC = 0.196 (p = 0.109). Gynoid fat mass and BMI-z had a CC = 0.750 (p < 0.01), while gynoid lean mass and BMI-z had a CC = 0.163 (p = 0.184). Finally, total fat mass and BMI-z had a CC = 0.775 (p < 0.001), while total lean mass and BMI-z had a CC = 0.154 (p = 0.209). When we analyzed correlation data considering the division by groups with and without obesity (control group), we found only a weak correlation between trunk fat mass and BMI-z  and between android fat mass and BMI-z , both in the group of participants with obesity.Considering the entire sample, we found a strong/moderate positive correlation between BMI-z and fat mass markers . Howeverp = 0.006), android , gynoid , total , and fat percentage ), FVC percentile , android , gynoid , total , and fat percentage ), and FEV1/FVC z-score , android , total , and fat percentage ). p = 0.006), android , gynoid , total , and fat-free mass ), ERV , android , gynoid , and fat-free mass ), and PEF , android , gynoid , total , and fat-free mass ) ) .p = 0.033)) and PEF , android , gynoid , and total ). At the same time, we found significant correlations between lean mass and IC , android , gynoid , total , and fat-free mass ), and PEF , android , gynoid , total , and fat-free mass ) (p = 0.045)), and we also found significant correlations between lean mass markers and FVC z-score , total , and fat-free mass ), FVC percentile , total , and fat-free mass ), and ERV ) , we found different results. In the group with obesity, the significant correlations with fat mass markers were with IC ) . In the  0.018)) .p = 0.002) and percentile (p = 0.03)) and lowered FEV1/FVC (z-score (p = 0.02) and percentile (p = 0.049)) ) . p < 0.001).p = 0.05; android: p = 0.033; gynoid: p = 0.044; total: p = 0.028; and fat-free mass: p = 0.023).Nevertheless, when considering the differences in lean mass markers between groups, the differences remain significant only in the female group, as is shown in In the analysis of anthropometric data, it is interesting to note that BMI-z was an accurate variable to assess the adiposity of participants. The literature points to numerous limitations regarding the use of BMI since it quantifies mass and not fat and may overestimate and classify as overweight or obese individuals with high lean mass ,34. HoweAlthough the relationship between obesity and physical inactivity is clear, no difference was found between participants with and without obesity for physical activity practice. We believe this finding is related to three possibilities: (i) a small sample size with a high probability of type II error ; (ii) a group with obesity receiving multidisciplinary outpatient follow-up with physical educators who emphasize the importance of physical activities—individuals with obesity are in the process of transition of life habits, and possibly for this reason there was no difference in the practice of physical activity among children and adolescents with and without obesity; and (iii) high prevalence of physical inactivity or irregular activity among children and adolescents, whether obese (56.1%) or not 42.9%), a fact already discussed in the literature ,36,37,38.9%, a faThe increase in SBP, DBP, and MBP between the groups, even though these are statistically equal regarding height and age, shows a possible overload of the cardiovascular system in obesity. Excess adipose tissue increases metabolic demands; for this reason, the body requires more blood supply, with a concomitant increase in cardiac activity . The desObesity also presented a greater RR value. The increased metabolic demand, mentioned earlier, implies a greater need for oxygen, with the consequent need for greater lung volume. However, the increased fat deposition, especially around the thorax and abdomen, generates a mechanical barrier that hinders thoracic expandability, and this could explain why an individual with obesity requires more respiratory incursions per minute ,45.1/FVC. Analyzing the entire sample, we have found that FVC was positively correlated with fat mass  and that FEV1/FVC was negatively correlated with the mentioned markers, except gynoid fat mass. Other variables correlated with muscular strength and were assessed by lean body mass markers  with IC and PEF. This study conducted a comparative analysis of pulmonary function and body composition by DXA, which allowed us to verify more accurately the respiratory variables related to obesity. When comparing groups, we found that individuals with obesity had significantly higher values in FVC and, consequently, significantly lower values in FEVHowever, when we analyzed the correlations grouping the sample with and without obesity, these differences did not hold. We believe that the sample size, after the group division, could interfere with the power of statistical analysis.1/FVC and a negative correlation with fat mass measures. According to the literature, this finding was present in studies with children and adolescents and was not found in adults [Another fact that stood out was the positive correlation between FVC and fat mass markers; in the comparison between the groups, this variable was higher in participants with obesity. This group also presented the lowest FEVn adults ,15,22,461/FVC, and FEV1 with no difference in participants with obesity directs the findings to the dysanaptic pattern in this group of individuals. Within this perspective, some previous studies justified findings similar to dysanapsis of the airways, which is the disproportionate growth between the pulmonary parenchyma and the airways, with an increase in lung volume different from the increase in the caliber of the airways . This gr1/FVC is related to adiposity and not to an increase in strength of participants with obesity, because of early maturation, as was discussed in the literature [One of the differences of our study was the exclusion of participants with asthma, differing from previous studies associating asthma and obesity, even if independent. In addition, the body composition analysis has allowed us to confirm that the increase in FVC and reduction in FEVterature . This anThe body composition analysis was a differential to understand the pulmonary function of children and adolescents with and without obesity, basing its clinical applicability in the pediatric area, especially in the care of individuals with obesity, since obesity and growth are complex phenomena that can occur concurrently. It is important to note that differences in body composition can result in lung function implications. As we observed, both boys and girls with obesity had significantly higher fat markers, as expected. However, girls with obesity also had significantly higher lean mass markers when compared to girls without obesity. Studies show that obesity can contribute to the early onset of puberty in girls ,50,51,52To the best of our knowledge, this is the only study that established a correlation between lean body mass and fat mass variables with the pulmonary function of children and adolescents without asthma.The present study had some limitations. The number of participants may have been insufficient to identify the differences between both DIs. In addition, we did not analyze the correlations between groups with and without obesity considering sex differences because the subgroups would be too small, compromising the relevance of the statistical analysis. 1/FVC. The findings are related to the increase in fat mass, with no relation to lean body mass. We hypothesize that these findings are associated with the dysanaptic growth pattern, which is higher in obesity, evidenced by the reduction of dysanapsis index.We conclude that the relationship between obesity and pulmonary function in children and adolescents is complex and that it is essential to reduce the confounding biases, to understand which changes are obesity-related and which are growth-related. Participants with obesity showed increased FVC and reduced FEV


Women from Asian and western countries have vastly different ages of onset of breast cancer, with the disease tending to occur at an older age in the West. Through an investigation of the patterns of old-onset breast cancer (OBC) in Korean women, we aimed to identify the characteristics of Korean OBC and evaluate whether these patterns are changing in relation to increasing westernization.This study retrospectively evaluated 102,379 patients who underwent surgical treatment of primary breast cancer between January 1, 2000 and December 31, 2013 in Korea. We used hospital -based breast cancer registry and analyzed data from these patients using multiple linear regression analysis to compare the characteristics and chronologically changing patterns between OBC (70 years of age or older) and non-OBC (40–69 years of age) patients in Korea.A total of 6% of the 102,379 patients had OBC. Overall, OBC had more favorable biological features, such as a higher incidence of luminal A subtype, than did non-OBC, except for a higher incidence rate of triple-negative breast cancer (TNBC). However, OBC also presented with a higher overall disease stage, including higher T and M stages. Although the incidence rates of both OBC and non-OBC have increased overtime, the relative proportion of OBC patients has slightly increased, whereas that of non-OBC has slightly decreased. The increase in the incidence of both OBC and non-OBC was primarily due to the luminal A subtype.Based on a hospital-based registry, overall, Korean OBC had favorable biological features but showed a higher rate of TNBC and advanced cancer stages. The incidence trend of breast cancer in Korea is slowly shifting toward an older age at onset, largely due to the luminal A subtype. Our results may provide novel insights into OBC in Asia, and aid in the development of optimal management of the disease in Asia.Retrospectively registered. Currenly, breast cancer is the most prevalent among other famale malignancies globally , 2. BecaRegarding breast cancer, Asia faces more rapid increases in the incidence rate than does the West . In 2020We intended to assess the features of breast cancer in elderly Korean women and determine the variations in the incidence and subtypes of OBC over time. Finally, we also intended to evaluate the future trends in OBC in Korea.http://registry.kbcs.or.kr/ecrf/login.php), which was estalished by the Korean Breast Cancer Society (KBCS) 〔11〕. More than100 instituions with over 400 beds each volountarilly took part in this registry 〔11〕. In 2013, it was assumed that this registry would reflect over 65% of new breast cancer cases detected in Korea  or silver [SISH] in situ hybridization methods). IHC reults of zero or 1+ (week) HER2 staining were considered to have a negative HER2 status, whereas those with 3 + (strong) HER2 staining were considered to have a positive. For cases with 2+  HER2 staining, FISH or SISH results that determined the the final HER2 expression; cases with positive FISH or SISH results were considered as HER2-positive, whereas those with negative FISH or SISH results were considered as HER2-negative. Cases with missing FISH or SISH results were determined as having an unknown HER2 status.According to the status of hormone receptor and HER2 expression, patients were classified into four breast cancer subtypes. These subtypes included ‘luminal A’: postive-ER and/or PR and negative-HER2; ‘luminal B’: positive-ER and/or PR and positive- HER2; ‘triple negative breast cancer (TNBC)’: negative - ER and PR and negative -HER2; ‘HER2’: negative-ER and PR and postive–HER2.This study attained an approval from the Instituional Review Board of Haeundae Paik Hospital . The KBCS anonymized and de-identified personal information from the records for the protection of patient privacy.For this analysis, we excluded male patients, patients aged less than 40 years, those with a histopathology of lobular carcinoma in situ, phyllodes tumor, sarcoma and lymphoma, cases without data on age, types of surgery, pathological stages, and those diagnosed prior to the year 2000 owing to their questionable reliability. Patients younger than 40 years of age were excluded from the non-OBC group because young-age breast cancer (under 40 years of age) is reported to have dissimilar clinicopathological characteristics compared with older-age breast cancer (age 40 years and older) . In addiBased on this dataset, we compared between the OBC and non-OBC groups to assess the features of OBC and examine chronological changes in incidence rates of OBC. To assess chronological changes in subtypes, we performed subset analysis of 76,349 cases having accurate data on status of ER, PR, and HER2 expression.p values were calculated for multiple comparison tests. Estimates of the frequency and incidence of each subtype were derived by the slope of the regression line, which represents the annual rate of change in the frequency and incidence. For all statistical analyses, SPSS version 24.0 was used, and p values less than 0.05 were idenified as having statistial significance.Regarding comparison between the OBC and non–OBC groups, clinicopathological features presented as categorial variables were compared using Fisher’s exact or Chi-squared test. However, those presented as continous variables were compared using Mann-Whitney U or independent test. A large amount of data on clinicopathological variables were missing, and the missing data were excluded from the analysis. To check the normality of the distribution, we used the Shapiro-Wilk test. To compare changes in the frequencies, incidences, and proportions with time among different age and subtype groups, we performed multiple linear regression test and checked interaction effects between variables regarding changes. Bonferroni-corrected Of a total of 102,379 patients, 6.0% had OBC. A comparison of the OBC and non-OBC data is shown in Tables p < 0.001 for all). The frequency and incidence rates of OBC increased more radiply than did the non-OBC and total breast cancer . The proportion of OBC cases neared 4% in 2000. And this low proportion of OBC cases increased annually to 7.6% in 2013.The frequencies and incidence rates of total breast cancer, non-OBC, and OBC significantly increased with time . In descending order of numerical value, the frequencies of subtypes were estimated as 33.36 , 8.25 (TNBC), 5.40 (HER2), and 4.31 , respectively. In addition, their incidence were estimated as 0.000133 , 0.000033(TNBC), 0.000021 (HER2), and 0.000017 , respectively. Of all the subtypes, the incidence of the luminal A subtype increased the fastest, and the associated rate of increase was four to eight times higher than that of the other subtypes (p < 0.001).We assessed how the frequency and incidence have changed with time according to the subtype within each age group. In the OBC group, both the frequency and incidence of all subtypes significantly increased with time .In the non-OBC group, both the frequency and incidence of all the subtypes significantly increased with time  in Korea. However, the increase rate was steeper in OBC than non-OBC; consequently, the relative proportion of OBC has increased slowly over time. Assuming that the current trend persists, the relative proportion of OBC will eventually proceed toward the values reported in western countries.This hospital-based database study showed that, in Korea, OBC has clinicopathological characteristics that are distinct from those of non-OBC, and that the incidences of total breast cancer, OBC, and non-OBC have continuously increased in the country. Noticeably, the increase in the incidence of OBC was slightly steeper than that of non-OBC in Korea; as a result, the proportion of OBC has been slowly increasing. The increase in the incidence of the luminal A subtype of breast cancer predominantly contributed to the increase in the incidence of both OBC and non-OBC, whereas increases in the incidence of other subtypes were relatively less evident.In 2012, in the developed world, the ratio of female patinets with breast cancer at age ≥ 70 years accounted for 32.1% of all female patients with breast cancer at age ≥ 40 years . In 2015In this study, OBC in Korea showed favorable biological features, except for the higher proportion of TNBC cases; however, there were discordantly advanced stages. OBC is considered to be different from non-OBC , 16. GenDiscrepancies between favorable biological features and advanced stages in OBC can be partly explained by an altered biological environment related to aging, which facilitates rapid disease progression, and also by society-related mechanisms such as the exclusion of elderly people from screening, or the notion of OBC being less aggressive, leading to diagnostic delays and the provision of proper care . Along wExisting literature on OBC demonstrates great heterogeneities in terms of cancer stage, size, grade, and lymph node status at presentation, and clinical results in elderly women relative to their younger counterparts , 16, 37.The distribution of breast cancer subtypes greatly fluctuates because of the complex effects of both age and race/ethnicity –45. RegaIn previous California-based studies, age did not significantly increase the risks of the TBNC and HER2 subtypes among Asian/Pacific Islander women , 49. HowOur data, derived from the hospital-based voluntary cancer registry (KBCR), provide more specific information on patient and tumor characteristics, surpassing those derived from the nationwide obligatory cancer registry (KCCR). Nevertheless, the presence of selection bias cannot be ruled out. First, it cannot be guaranteed that KBCR data are fully representative of the actual breast cancer status in Korea. In fact, a period from 2000 to 2013, the proportions of OBC according to two major registry data were 6.0%  in the KBCR, and 8.1%  in the nationwide cancer registry . Table 3In conclusion, based on a hospital-based database in Korea, although OBC in Korea was associated with favorable biological features, it showed a greater rate of the TNBC subtype and advanced disease stage. Currently, the Korean society continues to undergo popolution aging, and, accordingly, older Korean women ≥70 years old increasingly experienced breast cancer. Therefore, the management of breast cancer in this particular age group is expected to emerge as an urgent clinical issue in the near future. To lay the foundation for the management of OBC in Korea, there is a need for a comprehensive understanding of the disease’s characteristics, including the associated tumor biology and differences from non-OBC. Future studies should focus on this. Our results may provide novel insights into OBC in Korea, and aid in the development of optimal management of the disease in the country.


Osteosarcoma is a common bone sarcoma that occurs in childhood and adolescence. Although research on non-coding RNAs (ncRNAs) of osteosarcoma has been developed rapidly in recent years, a specific bibliometric analysis on this topic has not yet been performed. The bibliometric analysis aims to summarize knowledge atlas, research hotspots, and emerging trends and to provide researchers with new perspectives in further studies.All publications regarding ncRNAs of osteosarcoma published from 2000 to 2021 were retrieved from the Web of Science Core Collection. Quantitative indicators including the number of publications and citations, H-index, and journal citation reports were analyzed by using Excel 2019 and R software. VOSviewer and CiteSpace were used to analyze the cooperation among countries/institutions/journals/authors and the co-occurrence of keywords, keywords bursts, and references.R2 = 0.999). The most prolific country and institution were China (2260) and Shanghai Jiao Tong University (134), respectively. Professors Wang W and Liu W contributed the most to this field. The keywords were stratified into six clusters: Cluster 1 (apoptosis and growth), Cluster 2 (cancer and progression), Cluster 3 (microRNAs and downregulation), Cluster 4 (genes and differentiation), Cluster 5 , and Cluster 6 (metastasis). The long non-coding RNAs and circular RNAs have been considered as an important research hotspot in the near future.A total of 3206 publications were extracted. A significant growth trend in the annual number of publications over the past 22 years is revealed (This study offers a scientific perspective on ncRNAs of osteosarcoma and provides researchers with valuable information to understand the knowledge structure and to identify emerging trends in this field. Osteosarcoma is the most common primary bone tumor in children and adolescents, which occurs most frequently in the metaphysis of long bones, especially in the distal femur, proximal tibia, and humerus . There aOsteosarcoma is derived from bone-forming mesenchymal cells with aberrant activation of oncogenes and inactivation of tumor suppressor genes –11. AparIn this study, bibliometrics can be used for the quantitative analysis of hotspots in the literature. The main objectives of this study were to summarize the current status of and reveal future developing trends in the knowledge domain of ncRNAs on osteosarcoma. It is more crucial to propose research frontiers and potential hotspots in the near future.Literature data on ncRNAs of osteosarcoma were identified and downloaded from the Science Citation Index Expanded (SCI-Expanded) of the Web of Science Core Collection (WoSCC) database. Medical Subject Heading (MeSH) was applied in the search. Language was limited to English; literature types were limited to original article and review. The timespan for data retrieval was 2000 to 2021.The scientific literature was searched with the following search strategy: (osteosarcoma OR ‘osteogenic sarcoma’) AND (‘long non-coding RNA’ OR ‘lncRNA’ OR ‘long ncRNA’ OR ‘ncRNA’ OR ‘non-coding RNA’ OR ‘miRNA’ OR ‘microRNA’ OR ‘miRNAs’ OR ‘circRNA’ OR ‘circular RNA’ OR ‘ceRNA’ OR ‘competing endogenous RNA’ OR ‘piRNA’ OR ‘Piwi-interacting RNA’). All data utilized in this study were downloaded from known databases, and no ethical approval was required.The process of data searches was conducted on a separate day and by two authors independently. All collected data were saved as 'plain text' with the basic information by using the function of 'export' in WoSCC; the basic information in each publication was collected including published date, title, source journal, author, country/region, institution, funding sources, abstract, keywords, number of citations, and Hirsch index (H-index). The Hirsch index (H-index) is used to quantify an individual’s scientific research output and measure his or her citation impact .The abovhttps://www.vosviewer.com/documentation).To obtain a more comprehensive analysis, three bibliometric tools, including an R software package ('bibliometrix') and two software packages, were used to conduct this research. Firstly, the bibliometrix package in R 4.0.3 was used to convert and analyze automatically the bibliographic information of the included publications and included the distribution of countries/regions, years of publication, and source journals. Furthermore, academic cooperation networks between countries/regions were conducted. Then, VOSviewer 1.6.16 and CiteSpace 5.7.R5 were further used for mapping and visualization of the bibliometric networks of included publications. VOSviewer is one of the frequently and freely available bibliometric tools for constructing and viewing bibliometric maps . In thishttp://cluster.ischool.drexel.edu/cchen/citespace/CiteSpaceManual).In addition to VOSviewer software, we also used another bibliometric software, called CiteSpace, which is a Java-based scientometrics research software package that is used to analyze and visualize the hot spots and research frontiers in the scientific literature of a discipline or knowledge domain in a certain period , 27. In R software (version 4.03) and Microsoft Excel 2019 were used for descriptive statistical analysis, data fitting, and plotting graphs of publications including the number of publications per year, original countries/regions, authors, journals, institutions, H-index, and funding agencies. The growth rate of publications over time was computed according to the previously described calculation formula .y=1.147×10-9*x4 – 9.259x,R2 = 0.999). From 2000 to 2021, the average growth rate of publications was 33.25%.After removing 120 unqualified publications, a total of 3206 publications obtained from the WoSCC including 2960 articles and 246 reviews met the inclusion criteria from 2000 to 2021. Most of the 3206 publications concerning ncRNAs of osteosarcoma were distributed among 38 active countries/regions, among which the top 10 countries in terms of literature volume accounted for 2636 (82.22%) publications. Specifically, China had published the most publications with 2260 (70.49%) articles/reviews, followed by the USA , Japan , Italy , Korea , Australia , Iran , France , Spain , and the United Kingdom ; the abovementioned is shown in The top 10 institutions involved in this field are demonstrated in Oncology Letters (JIF 3.111) has published the greatest number with 120 papers, accounting for 3.74% of the publications, followed by Molecular Medicine Reports (JIF 3.423) and European Review for Medical and Pharmacological Sciences (JIF 3.784) with 99 and 93 papers, respectively. According to the JCR 2022 standards, the top 10 most active journals were classified as Q1 in 1, Q2 in 2, and Q3 in 4. Oncotarget, PLOS One, Cancer Research, Tumor Biology, and Biochemical and Biophysical Research Communications, which possessed the top five maximum nodes with TLS.In total, 4879 journals were involved in this research field. The top 10 most prolific journals are listed in The reference co-citation relationship was visualized in a co-citation network. In general, the weighted average silhouette value  and the modularity value  are two indicators to evaluate the significance of clustering, and if the S value is over 0.7 and the Q value is over 0.3, the cluster is efficient and convincing. In this study, the mean value of S equals 0.9204 and that of Q equals 0.7567, indicating the rationality of this clustering strategy. As shown in The keyword co-occurrence analysis largely determined developing trends, related hot topics, and tracing scientific development. Only keywords with a minimum of 10 occurrences were included in the analysis. Of all 8084 keywords, 396 keywords met the criterion. Based on the research categories of these keywords, VOSviewer software divided these keywords into several major clusters with different colors. As illustrated in the network visualization map of Our study examined the patterns of research on ncRNAs of osteosarcoma by using bibliometric and visualized analysis. Through the formula of model fitting curve in this study, the number of studies is demonstrating exponential growth and undergoing tremendous expansion in this field. The number of scientific outputs in this field has been increased from 2 in 2000 to 417 in 2021, and 3016 (94.07%) of the total publications were published in the last 10 years. The increasing trend was similar to the increasing global incidence of osteosarcoma in recent years . It was Among the 53 countries/regions that participated in the publication of studies in this domain, China was the most productive country, which also published the most articles in cooperation with many countries and was far ahead of the second-ranked USA. These results indicated that China might have a significant impact on the research in this field and possess the strongest collaborations worldwide. In terms of research institutions, a total of 2311 institutions contributed to the publications on ncRNAs of osteosarcoma; however, all the top 10 most influential institutions were from China. Notoriously, the research and development on ncRNAs of osteosarcoma required a large amount of both human and financial resources, which reflected the comprehensive strength of a country. It is proven again that China had made considerable progress in this field despite being a developing country. Among the top 10 funding agencies, China, the USA, and Japan divided up themselves and, meanwhile, the economic aggregates of the three countries are among the top three in the world.Biochemical and Biophysical Research Communications had the topmost H-index, followed by Oncotarget and Biomedicine & Pharmacotherapy. The top 10 journals with the most publications were affiliated with the USA and some Western European countries. The Chinese had played a significant role in the advancement of biological processes and scientific research on ncRNAs of osteosarcoma. China had no top international journals in this field yet.The H-index is an important indicator to quantify and standardize the scientific output and academic status of a researcher, which combines a researcher’s total number of publications and number of citations . ResearcReference co-citation analysis was also an important parameter analysis to assess the research focuses in a certain field. In this study, the total 15 major clusters and their corresponding labels were demonstrated in the co-citation network map. As shown in Keyword co-occurrence analysis was a significant bibliometric method that could provide the knowledge network map and the indicator of frontier topics. In addition to this, VOSviewer software can assign different colors to all the included keywords based on their average year of appearance. It can be seen that most of the research studies prior to 2019 mainly focused on the biological function of osteosarcoma  and its metastasis. However, except for some known miRNAs, long non-coding RNAs and circular RNAs gradually gained attention afterward.44. Moreover, some ncRNAs were associated with both osteosarcoma and digestive system tumors .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.


P < 0.05). Premature birth, low birth weight, and foetal loss were significantly rarer in the intervention group than in the non-intervention group . The comparison of MP with routine blood coagulation biochemical examination found that the MP detection system of Beijing Yes Medical Devices Co., Ltd., had similar sensitivity as thromboelastogram. Still, it was significantly better than the routine biochemical indicators (P < 0.01). Based on MP parameters, early anticoagulant treatment with low-molecular-weight heparin or low-dose aspirin in pregnant women with hypercoagulability can effectively prevent the occurrence of PE and significantly improve the prognosis of both mothers and infants.This study investigated the implication of monitoring hypertensive disorders in pregnancy (HDP) to prevent preeclampsia (PE) in pregnant women of advanced maternal age. Between January 2016 and April 2021, 262 consecutive pregnant women aged ≥40 years were recruited. Extensive monitoring of hypertensive disorders in pregnancy, including blood hypercoagulability screening and subsequent interventions, was performed in 129 pregnant women in our university hospital. The remaining 133 patients from other centres, who did not receive antenatal maternal pregnancy screening and preventive intervention during the same period, constituted the non-intervention group enabling comparison to mimic a trial. The incidences of hypertensive disorders, mild and severe PE, eclampsia, and chronic hypertension complicated by PE in the intervention group were significantly lower than in the non-intervention group (10.08 versus 20.30%, 8.52 versus 18.80%, 7.75 versus 21.05%, 0 versus 3.01%, and 3.86 versus 15.04%, respectively;  Untreated hypertensive disorders in pregnancy (HDP) increase maternal and perinatal mortality ; 4The incidence of HDP in pregnant women is approximately 5–12%, and HDP is one of the major causes of morbidity and mortality in pregnant women and perinatal infants . AlthougIn recent years, the role of epigenetic changes in the development of PE has been suggested, such as altered expression of selective miRNAs, which may play a vital role in both placenta-induced diseases, such as PE and FGR ,15. WithBased on the principle of elastic tubes in haemodynamics, according to which the amount of cardiac output mainly depends on the arterial waveform and pulse pressure difference, and the shape of the pulse wave reflects the specific changes in elasticity of human peripheral resistance blood vessels and blood viscosity, Cong et al.  used theSome scholars have concluded, from comparisons of the values of uterine artery S/D, PI, and RI at 20–24 weeks of gestation, that 22–24 weeks is the best time to predict PE, and after that, appropriate interventions should be taken to prevent it . HoweverNew England Journal of Medicine by Rolnik et al. [In the present study, early pregnancy blood hypercoagulability screening and intervention for pregnant women with advanced maternal age yielded significantly better maternal and infant outcomes than controls without such intervention. This finding is in line with a study published in the k et al. . Their mk et al. ,27. Low-k et al. ,29,30.LMWH is heparin fragments obtained by chemical decomposition or enzymatic cleavage of unfractionated heparin. The molecular weight of LMWH ranges from 4,000 to 6,500 µ. LMWH is an antithrombin-dependent thrombin inhibitor. It shows a stable dose–effect relationship in the body, and it is large enough that it does not pass to the placenta and has no teratogenic effect on the foetus. In addition to the anticoagulation and inhibition of platelet aggregation, LMWH can play anti-inflammatory, antiapoptotic, and antithrombotic roles and can protect vascular endothelial cells; it can reduce blood viscosity, improve placental function, increase foetal blood supply, and increase foetal intrauterine reserve capacity, thereby promoting the foetal growth . As earlThe findings of Paolino et al. showed that foetal loss was related to the decline in Treg cells . Early sThe present study has some limitations. A small number of cases were analysed in this study, which might account for the difference in induced abortions due to missed foetal abnormalities between the intervention group and the non-intervention group. The two groups of pregnant women were not enrolled simultaneously, so the results may also have certain deviations. We mimicked a trial by comparing patients referred to a tertiary university hospital with those referred to municipal hospitals without randomisation. This may have introduced a selection bias towards our intervention group’s high-risk and more complex cases. The latter may have resulted in underestimating the benefit of early screening and preventive measures. A large-sample, multicentre, double-blind, randomised controlled trial is needed to confirm further – at a higher level of evidence – the superiority of the application of the MP system for early screening of the hypercoagulable state of pregnant women of advanced maternal age and for guiding medication to prevent the occurrence of PE and its complications.To conclude, the MP monitoring system can be used to detect a hypercoagulable state in advanced-age pregnant women before the presence of clinical signs and symptoms of HDP. MP is non-invasive, easy to use, and low cost. Stratified management and stratified anticoagulant therapy based on MP monitoring results can effectively prevent the occurrence of HDP in older pregnant women predisposed to hypercoagulability and foetal FGR, and premature birth and loss. It noticeably improved maternal–neonatal prognoses. In addition, MP has higher sensitivity for monitoring hypercoagulability than traditional clinical and biochemical indicators. This approach is expected to yield better results, especially for pregnant women of poor socioeconomic status and those living in remote areas, where considerable benefits are expected of early MP application.