Background and Objectives: Currently, the worldwide incidence of major amputations in the general population is decreasing whereas the incidence of minor amputations is increasing. The purpose of our study was to analyze whether this trend is reflected among orthopaedic patients treated with lower extremity amputation in our orthopaedic university institution. Materials and Methods: We conducted a single-center retrospective study and included patients referred to our orthopaedic department for lower extremity amputation (LEA) between January 2007 and December 2019. Acquired data were the year of amputation, age, sex, level of amputation and cause of amputation. T test and Chi² test were performed to compare age and amputation rates between males and females; significance was defined as p < 0.05. Linear regression and multivariate logistic regression models were used to test time trends and to calculate probabilities for LEA. Results: A total of 114 amputations of the lower extremity were performed, of which 60.5% were major amputations. The number of major amputations increased over time with a rate of 0.6 amputation/year. Men were significantly more often affected by LEA than women. Age of LEA for men was significantly below the age of LEA for women . Main causes leading to LEA were tumors (28.9%) and implant-associated complications (25.4%). Implant-associated complications and age raised the probability for major amputation, whereas malformation, angiopathies and infections were more likely to cause a minor amputation. Conclusions: Among patients in our orthopaedic institution, etiology of amputations of the lower extremity is multifactorial and differs from other surgical specialties. The number of major amputations has increased continuously over the past years. Age and sex, as well as diagnosis, influence the type and level of amputation. Even though lower extremity amputation (LEA) is one of the oldest surgical techniques, dating back to the time of Hippokrates and beyond, it is still part of daily routine for many surgical specialties .Causes leading to LEA differ between countries and geographic regions. In the western world, up to 75% of all LEAs are associated with diabetes mellitus (DM) and peripheral arterial disease (PAD) ,3,4. In In orthopaedic surgery, LEA is also an important part of the surgical practice. In our daily routine, despite the trend to minimal and less-invasive operation techniques, there is an impression that the importance of lower limb amputations, especially of major amputations, had been increasing. As the population is getting older and patients are often multimorbid with a complex surgical history, the options for surgical treatment sometimes are limited to the most radical one, i.e., an amputation. Nevertheless, the main causes leading to LEA in orthopaedic patients tend to be a result of main diagnoses other than DM and PAD. As those diagnoses represent only a small number, regarding the overall population, they are excluded in the existing population-based studies. In the existing literature, no data exist about demographics, etiology and especially time trends of amputations in orthopaedic patients, which are not mainly due to DM and PAD. Therefore, it is unclear if the general trend of decreasing major amputation rates can also be assumed for orthopaedic patients. The purpose of this study was to analyze the demographics and etiology for LEA in a collective of orthopaedic patients. Our hypothesis was that, contrary to the general trend, the number of amputations, especially major amputations, had been increasing over time. The results of this single-institution study may be used as a possible indicator for trends in this surgical discipline.The present study is a single-center retrospective study. A total of 106 patients treated between 2007 and 2019 were included.We retrospectively analyzed all digital patient-records of our orthopaedic hospital from amputated patients. To identify these patients, we searched for amputation-specific surgical codes (operating procedure keys (OPS): 5-864.0-9, 5-864.a/x/y, 5-865.0-9 and 5-865.x/y according to the classification of the “German Billing System for Inpatients” (DRG)). All patients who underwent any LEA between January 2007 and December 2019 were included in the study. Year of amputation, age, sex, level of amputation  and main diagnosis leading to amputation were collected and analyzed. Revisions on the same limb and on the same level of amputation were excluded from the analysis. Any additional amputation on the same patient was counted as separate amputation. As major amputations we defined amputations proximal to, or through the ankle joint, whereas minor amputation was defined as any amputation distal to the ankle joint. Causes for amputations were determined by the main diagnosis directly leading to the amputation according to the DRG system. Secondary diagnoses were not included. Following causes for amputation were classified: tumor, implant-associated complications , angiopathies (DM- and PAD-related), malformation, infection (without implant- and DM/PAD-associated infections) and others . All data used for analysis were part of the routine medical documentation. Ethical approval was waived by the local Ethics Committee of University of Würzburg in view of the retrospective nature of the study (Protocol number 20210125 02).p < 0.05. To test time trends for major and minor amputations, linear regression was used, followed by likelihood ratio test to test for statistical significance. To calculate probabilities for LEA, multivariate logistic regression models were performed using age, level of amputation and indication as variables. A commercially available and a free statistical software program ) were used for statistical analysis and data visualization.Results are shown as means and standard error of the mean (S.E.M.). T test and Chi² test were performed to compare age and amputation rates between males and females; significance was defined as p = 0.015) and the age at amputation was significantly younger for men than for women   were major and 39.5% (n = 45) were minor amputations. Of these, 61.4% (n = 70) of the patients were male, 38.6% (n = 44) were female. Men were significantly more often affected by LEA than women (= 0.021) . Main causes leading to LEA were tumors (28.9%) and implant-associated complications (25.4%), followed by angiopathies (21.1%), malformations (9.6%), infections (9.6%) and others (5.3%) . All impIncreasing age significantly raises the probability of a major amputation, especially of a transfemoral amputation or an exarticulation of the hip .Time trend from 2007 to 2019 shows a significantly increasing number of major amputations (on average 0.6 new major amputations per year) and an almost constant number of minor amputations at the same time (on average 0.04 new minor amputations per year) . In this retrospective single-center analysis, we showed that in a cohort of orthopaedic patients, etiology of amputations of the lower extremity is multifactorial and differs from other surgical specialties. Most common diagnoses leading to LEA in our collective of patients are tumors and implant-related complications, in contrast to the worldwide leading position of PAD/DM-related amputations ,3. Age aMost patients needing LEA in our population were males. Various studies have demonstrated that male sex is a risk factor for amputation, in the diabetic as well as in the non-diabetic population ,17,18,19Average age for amputation in our study is at 58.7 years. Other studies show 10 to 15 years’ higher mean values ,11,20. TNevertheless, increasing age has been shown to be a risk factor for major amputation, especially transfemoral amputation and exarticulation of the hip. This finding in our collective is also in line with other studies ,11. CurrMost studies from Europe and other “western countries” have shown declining rates for major amputations ,11,12,13According to a recent publication from Kröger et al., a decrease of major amputation rates has been observed in Germany between 2005 and 2014, whereas the overall number of amputations has increased by 3.5%. After exclusion of tumors and other musculoskeletal diseases, the increase of LEA is only 1.1% , which iIn the USA, Kalbaugh et al. have shown a change of indications leading to amputation between 2006 and 2016 . The numIn our population, the increase of major amputations referred to an increase of implant-related complications. The number of primary total joint replacements in Germany has been at a constant high level in previous years , thus leOur study has several limitations. We analyzed only a small group of patients which were treated in our institution. Therefore, this sample might not be representative for orthopaedic patients in general due to selection bias. In Germany, LEA are performed by several surgical disciplines. Thus, possible confounders could be regional structural conditions like the specialization of our hospital, the availability of specialized vascular surgeons within reach, as well as changes in procedures or surgical staff. Thus, data represent only a cohort of orthopaedic patients and cannot easily be generalized to the German population. A population-based analysis would be necessary, but using diagnoses and procedure codes from hospital or insurance data makes it difficult if not impossible to differentiate certain groups in the way we did. Nevertheless, musculoskeletal tumors remain rare diseases and consequently, amputations due to tumors are even more sparse. Consequently, in that context, the number of patients reported in this study is not small for a single institution. A good way to enlarge the study population would be a multi-center analysis. Because the study population was small, we did not perform age and sex adjustment. Thus, changes in the absolute number of amputations might be due to changes in the affected age groups. Nevertheless, the impact on hospitals and health care systems remains the same.Among patients in our orthopaedic institution, etiology of amputations of the lower extremity is multifactorial and differs from other surgical specialties. The number of major amputations has increased continuously over the past years. Age and sex, as well as diagnosis, influence the type and level of amputation.


Statistics involved paired t-tests and agreement analysis by the Bland-Altman method. BIA underestimated the percent body fat (%BF) by 5.56% and overestimated Fat-Free Mass (FFM) by 2.90 kg. A strong positive correlation between both technologies was found for FFM (r = 0.980) and the %BF (r = 0.932), but the disagreement was statistically significant (p < 0.001). Although DXA and BIA seem to correlate, these technologies are not congruent. Therefore, the risk of (mis)interpretation and bias is clear with BIA, potentially impacting the nutritional planning of clinical dietitians and the further results of its patients.Bioimpedance (BIA) is the most frequently used technology for body composition assessment at a daily clinical level, mostly due to its low price and user-friendly operation. However, many doubts persist regarding its physiological meaning and applicability. The present study aimed to compare one BIA system and the Dual-Energy X-ray Absorptiometry (DXA) for the characterization of body composition in a previously selected cohort of healthy adult participants. A descriptive observational cross-sectional study included a final sample of 121 participants, 93 women and 28 men, with a mean age of 28.26 ± 9.72 years old and a mean body mass index (BMI) of 22.68 ± 3.13 kg/m Overweight and obesity have become a public health issue, especially over the last decades . DefinedBody composition assessment is crucial to identify nutritional status and possible risks  and is rThe objective of the present analysis was to compare the %BF and FFM assessed through the BIA and DXA devices and analyze their agreement in an adult population.2, with a classification of normal weight according to WHO guidelines   . In all t-test. Bland-Altman . The significant differences and correlations between the FFM and %BF values provided by DXA and BIA were analyzed with the paired d-Altman  was perfThe demographic characteristics according to sex are described in p < 0.001).In both cases, the correlation between methods was positive, with a high correlation in FFM and %BF for the general population . The meaThe purpose of the present study was to compare DXA and BIA evaluations on %BF and FFM in a healthy population with a wide age range of adults. Our results have shown that both instruments are strongly correlated regarding FFM and %BF, with statistically significant differences between instruments involving wide limits of agreement, in line with recent reports ,27. By cThere is a growing interest in the use of BIA to assess body composition in multiple settings, including research. The arguments are obvious when using BIA, ranging from portability, ease of use, cost, and lack of radiation, to practical operation. However, BIA results are critically affected by multiple assumptions based on predictive equations that condition the instrument estimations and their applicability ,29, and p < 0.001), confirming that BIA and DXA are dissimilar types of equipment for %BF and FFM assessment. Further studies and expanded experimental design are needed to better understand BIA’s physiological significance and its application to body composition studies. Concluding, the risk of (mis)interpretation and bias that can occur with this type of BIA equipment means that it is not the perfect option for body composition assessment, potentially impacting the nutritional planning of clinical dietitians and further results of its patients. It is important to alert professionals to the need to implement the best clinical procedures in body composition assessment.Our study consistently confirms the presence of relevant estimation errors with BIA compared to DXA in the presence of a strong positive correlation between the two instruments. The Bland-Altman analysis also has shown that these techniques were discordant (


Transfusion was the most popular journal, and Blood was the most cited journal. Using various analyses, including co-cited analysis, historiography analysis, citation burst analysis, and factorial analysis, we pointed out and discussed contributing publications. According to occurrence analysis, co-word biclustering analysis, landform map, thematic evolution, and thematic map, we believe that “activation,” “p-selection,” “CD36 deficiency,” “gene-frequencies,” “CD109,” “HPA-1,” and “beta (3) integrin” may become new trends in PTR research. The outcome of our bibliometric analyses has, for the first time, revealed profound insights into the current state and trends in PTR research. The systematic analysis provided by our study clearly demonstrates the field's significant advancements to all researchers who are interested in a quick and comprehensive introduction to the field.Platelet transfusion refractoriness (PTR) is common in patients with hematology and oncology and is becoming an important barrier in the treatment of thrombocytopenia and hemorrhage. Bibliometrics is an effective method for identifying existing research achievements, important breakthroughs, current research hotspots, and future development trends in any given field. In recent years, research on PTR has received increasing attention, but a bibliometric analysis of this field has not yet been reported. In this study, we applied bibliometrics to analyze the existing literature on PTR research over the past 17 years. On November 1, 2021, we began a publications analysis of PTR research using the Science Citation Index Expanded of the Web of Science Core Collection with collection dates from 2004 to 2021. This research aimed to summarize the state of PTR research using Bibliometrix to identify connections between different elements  using VOS viewer analyses to visualize key topics and trends in PTR research using Cite Space and gCLUTO. The results of all 310 studies showed that the annual number of publications focused on PTR is steadily increasing, with the United States of America and Japan making significant contributions. We noted that the research group led by Dr. Sherrill J. Slichter was prominent in this field, while Estcourt Lise may become the most influential newcomer.  Platelet transfusion is needed in the treatment of several diseases. It is particularly important for the prevention of thrombocytopenia and hemorrhagic manifestations in patients with hematology and oncology . Platele9/L or a percentage platelet recovery of <30% within 60 min post-transfusion  AND transfusion) OR ((“transfusion refract*” OR “transfusion clear*” OR “transfusion ineffect*” OR “transfus* thrombocytopenia”) AND (platelet OR thrombocyte)) from January 1, 2004, to November 1, 2021. The search result comprised a list of publications that included the search words in the title, abstract, or keywords. No additional restrictions, such as publication type or language, were applied. The total number of publications in our research database was 348, whereas 18 publications with intersections with other research fields and a minimal intersection with PTR, were excluded. The complete records of the results were transferred to Bibliometrix , VOS viewer , Cite Space , GraphPad Prism , Bibliographic Item Co-Occurrence Matrix Builder (BICOMB v.2.01) and Graphical Clustering Toolkit (gCLUTO v.2.1.1) for further analyses.We accessed the Web of Science Core Collection database, limited to Science Citation Index-Expanded, using the following search terms: “platelet transfusion refractThe software package in R 4.1.0 (Bibliometrix) was used to automatically convert and analyze bibliographic information from the selected publications. To assess publication quality by a particular author, we analyzed key information, including the number of publications, citations in the research area, publication h-index value, and m-index value. The h-index correlates well with peer assessment and can predict future academic success . Since tVOS viewer (1.6.16) includes three types of maps—network, coverage, and density visualization; and can help visualize the co-author analysis of countries/institutions/authors, co-citation analysis of journals/references, citation analysis of literature, and co-occurrence analysis of keywords. In VOS viewer maps, different spheres represent different elements, such as countries/regions, journals, and references. While the number of publications or co-occurrence frequency is represented by the size of the spheres, the relationship between the elements is represented by a line between two spheres. The thickness of the line clearly reflects the strength of the relationship between two different elements .Cite Space (5.8. R1), used to construct the dual-map overlay for journals and detect references with strong citation bursts, is an application for visualizing and analyzing trends and patterns in the scientific literature .BICOMB2.01 and gCLUTO2.1.1 are used as a tool to classify all keywords. CLUTO is a software package for clustering low and high-dimensional datasets and for analyzing the characteristics of the various clusters.P < 0.05. GraphPad Prism (v.8.0.1) was used for statistical analysis and to create figures.The Pearson correlation coefficient was used to evaluate the correlation between two variables. Statistical significance was set at P < 0.0001). Using curve fit, we mapped the relationship between total publications and the publication year (R2 = 0.6792)  . The ide 0.6792) . In addiThe top ten most productive authors, based on the number of publications, are listed in Our analysis identified 56 authors for their co-authorship, and all authors had more than three publications and ten citations, which implied the high quality of their publications. Among these authors, we mapped a set of 11 authors who were inter-connected .n = 16, 5.16%).The publications in our database involved 481 organizations, with 19 institutions having more than five publications and 10 citations. We analyzed these 19 institutions to show the collaborations between them. Seven institutions were not connected to each other and were excluded . The sixGlobal contributions to PTR research are shown on a world map according to the number of articles published, which directly shows the number of publications from different countries using different colors . Higher The co-authorship analysis identified 18 countries with more than five publications, and three countries, which were not connected with each other, were excluded . The topTransfusion  had the most publications, followed by Blood  and Vox Sanguinis . The number of PTR-related publications in these journals steadily increased over time  of the ten journals in hematology is the top research area in the PTR field.In total, 310 articles were published in 108 journals. We considered the Journal Impact Factor and Journal Citation Reports (JCR) as important parameters for measuring the various journals. The journal impact factor is a measure of the citations of articles in a specific journal, and it is intended to gauge the importance of a journal in its particular field. First, we listed the top ten most popular journals for publishing articles on PTR . Transfuver time , particuBlood had the largest number of citations (534 citations), followed by Transfusion (430), British Journal of Haematology (332), Cochrane Database of Systematic Reviews (181), and Vox Sanguinis (157). Although the total number of citations of articles published in JCR's top quartile does not show obvious advantages, the number of CPP is higher than that of journals in other partitions. These findings highlight the value of the JCR in identifying influential articles in this field.Moreover, Transfusion , Blood , British Journal of Haematology , Vox Sanguinis  and New England Journal of Medicine  are the top five co-cited journals. We also tried to assess the core sources of PTR research knowledge. Through Bradford's law analysis, we identified Transfusion, Blood, Vox Sanguinis, Transfusion and Apheresis Science as the core journals in PTR research.Twenty-eight journals were highlighted in our study for documents that were co-cited in more than 50 publications . TransfuBlood; 73 citations; total strength, 224 times), McFarland J. , Hod E. , Doughty H. A. , and Pertz Ld .Significantly, there were 11 references co-cited in more than 30 articles . The 11 Blood; 73 LCS, 301 GCS), Hod E. , Slichter S. J. , Pavenski K. , and Seftel M.D. .We analyzed historical citations to identify significant publications that contributed to research development . Figure British Journal of Haematology by Stanworth et al. The citation burst of this article lasted from 2017 to 2021. Six among the top seven publications with citation bursts that ended in or after 2015 were selected for discussion regarding the latest topics in PTR research.Citation burst detection identifies publications that receive particular attention in a specific period of time . The minAs the focus on different topics will greatly affect the number of citations, total citation analysis will cause some articles with high contributions and high citations to be lost. Therefore, using 40 keywords, we used factorial analysis to include more articles and highlight articles related to key topics. Multiple correspondence analysis and multidimensional scaling was performed in factor analysis, which can classify factors that underlie different topics, sorted into different clusters. Multiple correspondence analysis is one of the most widely used data dimensionality reduction algorithms, which can be considered as an extension of simple correspondence analysis in low-dimensional graphics . ConnectVOS viewer was used to generate a keyword map that marked phrases mentioned in the titles and abstracts of the publications. Multiple occurrences in a single publication were counted as one event. To clarify the results of the analysis, we merged synonyms. Using co-occurring analysis, which is a statistical analysis method for standardized keywords extracted from publications, all 30 keywords that occurred more than ten times were distributed across four areas, which are shown in different colors, with the node size representing the frequency of occurrence . KeywordBICOMB and gCLUTO are tools to classify all keywords shown in hot spots . All terTo better understand the evolution of the research focus in PTR, we mapped keywords in A thematic map was used to determine the significant topics in PTR research  Figure . The minHere, we combined network visualizations with bibliometric analyses to describe the present situation of PTR research; analyze the contributions of countries, institutions, journals, and authors to this field; and predict topics for continued research interest in the coming years. Since 2004, the annual publication output in the field has shown a steady growth trend .Author analysis is based on the h-index and m-index, which are widely used to measure an author's importance . The h-iTransfusion, the most productive journal, and Blood, the most cited journal with the highest CPP, are the most influential journals in PTR, and both are American journals. These results all indicate that the United States is the leader in PTR research, with Japan making a significant impact. We suggest that scholars should pay close attention to the articles from these authors, countries and journals to keep abreast of the cutting-edge research in this field.The most productive author, the author with the highest CPP and h-index, was Sherrill J. Slichter, who leads a research team  and is the leading scholar in the PTR field. Based on the m-index results, the most impactful newcomer to the field was Lise Estcourt  and her research group. The United States has the largest number of publications (94 articles) and total citations , and the fourth CPP rank (18.82). Although the total number of publications (33 articles) and total citations (361) both ranked second, Japan had the highest CPP (30.08). Furthermore, seven of the top ten institutions with the largest number of publications are from the United States, which further confirms the influence of the United States in this field. To establish an objective and complementary knowledge base of PTR research, we used four bibliographic methods to identify the most significant publications. Co-cited articles  are two n = 73), and Hod E. et al.  introduced the definition of PTR and described the predominant cause of platelet refractoriness, including transfusion service factors (n = 37) revealed that platelet-specific antibodies encountered in patients who underwent multiple transfusions were mostly anti-HPA-1b and anti-HPA-5b.The topics of these articles include PTR identification, prevention, and underlying mechanisms, as well as management of blood production and patients. The publication of Forest and Hod , Slichte factors . and ant factors , 18, 48, factors , 49, 50  factors . In fact factors  (n = 37)in vivo experiments in mice, Pavenski et al.  reported that about 25–70% of multiple transfused patients had a PTR experience. Comparatively, Pertz et al. (n = 31) revealed that crossmatched platelets must be performed frequently, as platelet has a shelf life of only 5–7 days (n = 82) discussed leukocyte reduction, which blocks the direct pathway by the removal of the donor antigen-presenting cells 5–7 days , leading5–7 days  n = 82)2n = 31) ng cells  because ng cells . Patientng cells   of the platelet and complement system. One proposed mechanism suggests that when platelets are transfused to refractory patients with incompatible antigens, antibodies can induce platelet activation, then active modulation and passive opsonization of platelets combine to attract phagocytes , 77. AnoAlthough bibliometrics is useful for research performance analysis, it has some limitations. First, analysis is performed based on the publications collected from a database, which means that it might not be comprehensive. Second, citation analysis is a significant part of bibliometric analysis, which supports quantifiable items. This type of analysis is based on a theoretical assumption that scientific quality has a simple linear relationship with citation counts . HoweverTransfusion and Blood have played significant roles in PTR research which is undergoing a period of development and has attracted increasing attention from researchers. With this bibliometric analysis, we can quickly learn, establish, and summarize simple knowledge such as base data, including the mechanisms of PTR, testing methods, and several prevention methods of PTR. Moreover, keywords and topics, such as “activation”, “p-selection”, “CD36 deficiency”, “gene-frequencies”, “CD109,” “HPA-1”, and “beta (3) integrin” may become, or maintain as, the popular topics and trending areas of PTR research. The development of PTR mechanism research and algorithms that can be used in diagnosis and management will be useful in preventing PTR. The study of PTR has a wide scope for further investigation, and we believe that our analysis, which is an initial foray into summarizing the existing research in this area using bibliometrics, provides a valuable reference for clinical researchers and practitioners interested in PTR research.Our bibliometric analysis of the present literature on PTR revealed that the United States, with the highest number of publications, and Japan, with the highest CPP, have a significant impact on research direction in the PTR field and play important roles in PTR-related research. Further, the research group led by Sherrill J. Slichter is prominent in the PTR field, while the research group led by Lise Estcourt may become the most influential newcomer. The original contributions presented in the study are included in the article/YL and YZ performed statistical analysis and wrote the manuscript. DC participated in data collection and verification. YF contributed to review and editing. All authors contributed to manuscript revision, read, and approved the submitted version.This study was funded by Nation Natural Science Foundation of China (No. 81970169).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.


Using the above five indicators, a nomogram prediction model was built for URI occurrence in patients with ITP within half a year after diagnosis, and the results showed an AUC, a sensitivity, and a specificity of 0.936 (95% CI: 0.878-0.983), 0.942, and 0.865, respectively. The nomogram model was internally verified by the bootstrap method for 500 self-sampling times, and the prediction of the calibration curve was in high consistency with the real results. External validation of the nomogram model resulted in an AUC, a sensitivity, and a specificity of 0.890 (95% CI: 0.757-0.975), 0.949, and 0.727, respectively. The nomogram model of URI in ITP patients within half a year after diagnosis based on logistic regression analysis has good discrimination and prediction accuracy. This provides important guidance value for individualized prediction of URI in ITP patients.The risk factors of upper respiratory tract infection (URI) within 6 months after diagnosis in patients with idiopathic thrombocytopenic purpura (ITP) were analyzed, and the nomogram model was established and verified, with 242 and 50 ITP patients as the training and validation set, respectively. The patients were followed up for six months after the diagnosis of ITP. The clinical data of patients were collected, and the risk factors of URI in ITP patients within six months after diagnosis were analyzed using univariable, followed by multivariable logistic regression. Among the 242 ITP patients in the training set, 52 cases (21.49%) had URI, including 24 cases of viral infection, 11 cases of Mycoplasma pneumoniae infection, and 17 cases of bacterial infection. Logistic regression analysis showed that advanced age, use of glucocorticoid, smoking history, platelet count, serum CRP level, and lymphocyte subsets CD Primary immunologic thrombocytopenic purpura (ITP) accounts for about 30% of all bleeding disorders , and itsA nomogram integrates relevant risk factors and visualizes risk values . Based oA training set and a validation set, which included 242 ITP patients visited the Hechi People's Hospital between January 2019 and June 2020 and 50 ITP patients admitted between July 2020 and December 2020, respectively, were set up. Inclusion criteria for training and validation sets were as follows: (1) meet the clinical diagnostic criteria of “Chinese Expert Consensus on Diagnosis and Treatment of ITP in Adults 2016 Edition” , no less3+, CD4+, CD8+, B lymphocyte, and platelet counts.The Hospital Information System (HIS) was used to collect and summarize the clinical information of ITP patients on admission, including gender, age, drinking history , smoking history (smoking more than 100 cigarettes or cumulative smoking of more than six months), pathogens, combined anemia, glucocorticoids, splenectomy therapy, rituximab, serum C-reactive protein (CRP) levels, natural killer (NK) cells, lymphocyte subpopulations CDAll cases were followed up for half a year, and the follow-up was conducted in the form of outpatient review. Patients visited the hospital for reexamination every 1 month after discharge. According to the diagnostic criteria of acute upper respiratory tract infection , the patt-test conducted intergroup comparisons. The categorical variables was represented by n (%), and the chi-square test or rank-sum test conducted intergroup comparisons. Univariate and multivariate logistic regression were employed to identify prognostic factors of patients. URI risk in ITP patients within six months after diagnosis was analyzed using the logistic regression model, based on which a nomogram prediction model was built. The discriminative ability of the model was evaluated by calculating the area under the curve (AUC) and 95% confidence interval (CI), and internal validation with 500 iterations of bootstrap was used to evaluate the calibration effect through unreliability tests and calibration curves. R software  was used. A P value <0.05 was interpreted as statistical significance.SPSS 23.0 analyzed the original data. Continuous variables that obeyed the normal distribution were denoted by (mean ± standard deviation), and 4+ and CD8+ between infected and noninfected groups (P < 0.05), as shown in Among the 242 ITP patients in the modeling set, 52 had URI, accounting for 21.49%, including 24 cases of viral infection, 11 cases of Mycoplasma pneumoniae infection, and 17 cases of bacterial infection. Statistically significant differences were present in age, use of glucocorticoid, smoking, platelet count, serum CRP level, and lymphocyte subsets CD4+ and CD8+ were all risk factors for URI in patients with ITP within half a year after diagnosis (P < 0.05).The dependent variable was the occurrence of URI  within six months after diagnosis of ITP patients, and the independent variables were the statistically significant features in P = 0.075) indicates that the prediction model has a good calibration ability. The mean absolute error (MAE) of the calibration curve from 500 samplings by the bootstrap method was 0.013, indicating that the occurrence risk predicted by model is in good agreement with the actual occurrence risk  was used to externally validate the model, and an AUC of 0.890 (95% CI: 0.757-0.975), a sensitivity of 0.949, and a specificity of 0.727 were determined , demonstWith complex pathogenesis, ITP is generally believed to be linked to the reduction of platelet production and the excessive clearance of platelets by macrophages . Studies4+ and CD8+ were all influencing factors of ITP patients developing uppersickness within half a year after diagnosis. Elderly patients are often accompanied by other underlying diseases and may take a variety of drugs at the same time, resulting in a decline in body function and body resistance. Therefore, for elderly patients, follow-up should be strengthened, and preventive measures should be taken. For smokers, it is necessary to inform them of the dangers of smoking and instruct them to quit smoking. Because long-term smoking can easily lead to abnormal lung function in patients, the longer smoking time is, the easier it is to increase the risk of secondary respiratory tract infection in patients with ITP [Among the 242 ITP patients, URI occurred in 52 cases, with an incidence rate of 21.49%, which was basically consistent with the results of domestic and foreign studies . In thiswith ITP . In the with ITP . On the with ITP . Kimura with ITP  analyzed4+ and CD8+ subsets according to surface markers [4+ and antigen stimulates B cells to secrete plasma cells, and the CD4+ T cells in some ITP patients are destroyed, resulting in decreased cellular immune function, which may increase the risk of URI [4+ level was statistically significant in the multivariate analysis, consistent with previous studies. CD8+ is a subset of cytotoxic cells or suppressor cells, an increase in the number indicates that the immune function is inhibited, and it is easy to cause a URI [CRP level is an important indicator for judging URI. When the body is injured or infected, the level of CRP will rise rapidly, and it will fall back quickly after the patient's condition improves . CRP lev markers . The synk of URI . In thisse a URI . Platelese a URI . Studiesse a URI  that resse a URI . For pat4+, CD8+, and internal verification was performed. The results showed that the model AUC = 0.936, sensitivity = 0.942, and specificity = 0.865 suggest that the nomogram model has better discriminative ability. After being verified by the validation set data, the predicted value of the model has a high consistency with the actual value, indicating that it has a good predictive ability. The limitation of this study is that this study is a single-center study, not a multicenter large-sample epidemiological survey. The data are from the same medical center, and there may be case selection bias. In the follow-up research work, this research group plans to cooperate with other centers to use its clinical data to further improve and improve the predictive value of the model.Most of the previous research models are presented in the form of formulas, and the calculation process is complicated; not only there is the risk of calculation errors but also the workload of medical workers is increased. A good model should be effective, practical, and simple. The nomogram model can evaluate the prognosis intuitively, concisely, and accurately, which helps medical staff make better clinical decisions. Besides, the nomogram can uniquely reveal the correlation between relevant risk factors and outcome events . In this4+ and high CD8+ T cells were all risk factors for URI in patients with ITP within half a year after diagnosis. Based on logistic regression analysis, the nomogram model of the onset of symptoms in ITP patients within half a year after diagnosis has good discrimination and prediction accuracy. It can provide guidance for clinically accurate and personalized prediction of ITP patients.Advanced age, use of glucocorticoid, smoking history, low platelet count, high CRP level, and low CD


This study investigated the relationship between eye frailty and physical, social, and psychological/cognitive weaknesses among older adults in Japan. The participants were 192 community-dwelling older adult women. We measured handgrip strength, walking speed, and skeletal muscle mass; additionally, their physical, social, and psychological/cognitive frailties were surveyed using questionnaires. Eye frailty self-checks were used to assess eye frailty. Exploratory and confirmatory factor analyses were employed to verify the validity of the eye frailty self-checks. Eye frailty prevalence and related factors were investigated by conducting a binomial logistic regression analysis, with eye frailty as the dependent variable. The factor analysis results showed that a model could be constructed with the two factors of visual acuity or contrast and visual field. The model’s goodness of fit was acceptable, supporting the validity of the self-checking construct. The Kihon checklist was the only variable with a significant relationship to eye frailty. Regarding the relationship between eye frailty and subordinate items of the Kihon checklist, social withdrawal , cognitive function , and depressed mood  were significant. Eye frailty can be considered a factor reflecting the existence of social and psychological/cognitive frailties. The concept of “frailty” is important for early detection and response to conditions that inhibit the healthy life expectancy of older adults. There are different ways of thinking about frailty, such as the phenotype model  and the In recent years, the relationship between age-related decline in sensory function and frailty has been the focus of much attention . Among tEye frailty is a conceptualization of the changes in visual function with aging. According to the Japan Ophthalmology Awareness Council , it is aThe participants for this study were recruited from those who voluntarily participated in a care prevention project publicly implemented by the city of Otawara, Tochigi Prefecture, from June 2021 to January 2022. The project was recruited through a city newsletter, and 225 older adults  voluntarily participated in this study. Men and participants with missing data were excluded, and a total of 192 women (mean age: 79.2 ± 7.2 years) were included in the analysis.We collected age information and measured height and weight as basic information. Regarding physical function, body composition was measured using handgrip strength, usual walking speed, and the bio-electrical impedance analysis (BIA) method. For handgrip strength, the handgrip strength values were measured using a handgrip strength meter , and the maximum value was considered. For the usual walking speed, the typical time to cover a 4 m walking path was measured twice using a stopwatch, and the fastest value was considered. For body composition measurement, the limb skeletal muscle mass was measured using a multi-frequency body composition meter , and divided by the square of the height to obtain the skeletal muscle mass index (SMI), which was used as the input value.Participants’ frailty status was comprehensively assessed using physical frailty, social frailty, and the Kihon checklist. Physical frailty was defined by Fried’s phenotype, and the Revised Japanese Cardiovascular Health Study (Revised J-CHS) was used, and the criteria were as follows: those who had one or two of the following five items: weight loss, muscle weakness, fatigue, walking speed, and physical activity were classified as physical pre-frail, and those with three or more items were classified as physical frailty . Social The questionnaire proposed by the Japanese Council for Eye Health Care Awareness was used to assess eye frailty, and participants who answered “Yes” to two or more of the 10 questions were considered to have eye frailty .We verified the validity of the 10-item eye frailty self-check construct. First, the correlation matrix between the items of the eye frailty self-check was obtained using Spearman’s rank correlation analysis. Subsequently, we conducted exploratory factor analysis using the maximum likelihood method and Promax rotation to construct the model and determine the number of factors and model. In the model, the superordinate concept was eye frailty, and the obtained factors were independent subordinate concepts. The exclusion of items in the model configuration was also avoided to the extent possible, considering the independence and importance of the individual questions. Therefore, items with a factor loading of 0.2 or more were retained. The number of factors was determined based on the Kaiser Guttman criterion—that is, factors with eigenvalues of 1.0 or higher were retained. Next, we constructed a model using the factors derived from the exploratory factor analysis and attempted a confirmatory factor analysis using structural equation modeling. Indicators for the model’s goodness of fit involved calculation of the comparative fit index (CFI), and root mean square error of approximation (RMSEA). A CFI of 0.9 or more ,22 and RThis study calculated the prevalence of eye frailty among the older adults surveyed. Participants were divided into two groups according to eye frailty. Furthermore, an unpaired t-test was used to clarify the differences in physical function between the groups, and compare participants’ age, height, weight, body mass index (BMI), Skeletal Muscle mass Index (SMI), calf circumference, handgrip strength, and usual walking speed. The differences in the prevalence of physical and social frailty and the number of people who experienced falls according to the presence or absence of social frailty were verified using a χ2 test.To investigate the relationship between the presence or absence of eye frailty, physical function factors, and physical and social frailties, we set the two groups of “eye frailty” and “healthy” as the dependent variables; for independent variables, we set age, height, BMI, SMI, calf circumference, handgrip strength, usual walking speed, Kihon checklist, revised J-CHS, social frailty criteria by Makizako et al. , and theThe Kihon checklist includes 25 questions concerning the living conditions of older adults and their physical function, social status, and psychological/cognitive weakness . It covep-value of Bartlett’s test of sphericity was <0.001, and the validity of factor analysis was confirmed. When estimating commonality, it was confirmed there were no items with commonality exceeding one.The results of Spearman’s rank correlation analysis are shown in Analysis results showed the following: for the first factor, items 1, 2, 3, 5, 6, 7, and 9 had high factor loadings and expressed the factor representing “visual acuity or contrast sensitivity.” For the second factor, items 4, 8, and 10 had high factor loadings and expressed the factor representing the “visual field.” A moderate correlation (r = 0.609) was found between the first and second factors .The model was constructed with eye frailty as the superordinate concept and the two factors obtained by exploratory factor analysis as the subordinate concept. Structural equation model results showed CFI = 0.973, AGFI = 0.936, RMSEA = 0.037 and SRMR = 0.042 . The patp = 0.02) exhibited a significant decrease in the eye frailty group.Of the 192 participants, 143 (74.5%) were classified as having eye frailty . Comparip < 0.001 in model χ2 test). The OR of the Kihon checklist was 1.385 [95% confidence interval (CI): 1.160–1.654]. The Hosmer-Lemeshow test results of this model showed the goodness of fit at p = 0.951, with a discriminative predictive value that lay between the predicted value and measured value of 76.6%.Binomial logistic regression analysis was conducted to analyze the presence or absence of eye frailty, physical function factors, and the strength of the relationship with physical and social frailty . The Kihp < 0.001 in model χ2 test). The OR was 2.437 (95%CI: 1.145–5.188) for social withdrawal, 2.047 (95%CI: 1.051–3.984) for cognitive function, and 1.820 (95%CI: 1.163–2.848) for depressive mood. The Hosmer-Lemeshow test results of this model showed the goodness of fit at p = 0.907, with a discriminative predictive value that lay between the predicted value and measured value of 77.1%.We conducted a further binomial logistic regression analysis to verify the relationship between the presence or absence of eye frailty and the subordinate seven items of the Kihon checklist . Social This study conducted assessed the visual function of community-dwelling older adults using the eye frailty self-check. The percentage of those judged to have eye frailty based on positive responses to two or more items among the total 10 items was 74.5%; thus, approximately three-quarters of the sample had some concerns with their visual function in daily life situations. There are no previous reports on the prevalence of eye frailty; however, a systematic review by Bourne et al.  in 2017 Although eye frailty is a relatively new concept, it has long been known that age-related declines in visual acuity and contrast sensitivity are related to frailty, and the diseases that cause them include cataract, glaucoma, and age-related macular degeneration ,24,26. AWe also analyzed the relationship between the presence or absence of eye frailty and participants’ physique, physical and social frailty, Kihon checklist, and fall history. Results showed that only the Kihon checklist had a significant relationship. The OR was 1.385, and the 95%CI was 1.160–1.654; a one-unit increase in a Kihon checklist item resulted in the probability of eye frailty increasing by 1.385. The Kihon checklist has seven domains as subordinate items, and the three domains .Next, we conducted a binomial logistic regression analysis of the relationship between the presence or absence of eye frailty and the seven subordinate domains of the Kihon checklist. Results showed that social withdrawal , cognitive function , and depressed mood  were significant related factors. Comparison of the OR showed that social withdrawal, reflecting social frailty, was the most significantly related, followed by cognitive function and depressive mood, which correspond to psychological and cognitive frailty, respectively.Previous research has reported that social withdrawal reflects social frailty, and that cognitive function and depressive mood are items corresponding to psychological or social frailty. Fujiwara et al.  suggesteThis study’s results verified the validity of the eye frailty self-check construct as a screening method for evaluating the decrease in visual function with aging, finding that it has acceptable validity. Furthermore, eye frailty showed a significant relationship with the Kihon checklist and a relationship with the subordinate items of social withdrawal, cognitive function, and depressed mood. Thus, eye frailty can be considered a factor that reflects the presence of social frailty and psychological and cognitive frailty among community-dwelling older adults. Gobbens et al. proposed the integral conceptual model of frailty  and showThere are several limitations to this study. First, participant recruitment was conducted as part of a city-sponsored health check-up program, so information on participants’ educational and social backgrounds was not available. Second, because of the large gap in the number of men and women participants in the health screening program, only women participants were included in this study for analysis. The results may differ between men and women, who have many differences in physiology, lifestyle, and social activities. Furthermore, the results of the Eye Frailty Self-Check were based on self-report, and no expert assessment of visual acuity, contrast sensitivity, or visual field was available. Additionally, there was no information on diseases that lead to visual impairment, such as glaucoma, diabetic retinopathy, or age-related macular degeneration, making it impossible to distinguish which ophthalmologic diseases are responsible. Finally, it should be recognized that many issues need to be addressed for clinical application, such as the identification accuracy of the eye frailty checklist and the calculation of cutoff values. However, we believe that we were able to demonstrate an association with confinement, cognitive function, depressive mood, and the possibility of screening for risk leading to these conditions.The validity of the eye frailty self-check was demonstrated, and the prevalence of eye frailty among community-dwelling older adults was 74.5%, with a high association with social withdrawal, cognitive function, and depressive mood in the Kihon check list. We believe that this preliminary study provides a basis for further research on the characteristics of older adults with eye frailty and its relationship to physical and social frailty and cognitive-mental aspects.


Those who scored less than 3 (moderately) were assigned to the “mild” group (n = 35), and those scoring higher were in the “moderate” group (n = 72). Three machine learning algorithms were applied to classify the “mild” group from the “moderate” group. The classification achieved 78% accuracy, a precision of 85%, a recall of 90%, and an F1 score of 87% for distinguishing those people reporting mild from moderate walking and balance difficulty. This study demonstrates that machine learning models can reliably be applied to instrumented walkway data and distinguish severity of self-reported impairment in people with MS.Machine learning can discern meaningful information from large datasets. Applying machine learning techniques to raw sensor data from instrumented walkways could automatically detect subtle changes in walking and balance. Multiple sclerosis (MS) is a neurological disorder in which patients report varying degrees of walking and balance disruption. This study aimed to determine whether machine learning applied to walkway sensor data could classify severity of self-reported symptoms in MS patients. Ambulatory people with MS ( Machine learning is a valuable tool for dealing with enormous amount of data and discovering new knowledge from that data, which has been widely employed in gait detection and analysis from various types of sensors, including videos, inertial measurement unit (IMU), surface electromyography, and insoles , raw walkway sensor data were collected from the Health Innovation Team in MS (HITMS) project, which studies the health of people with MS in Newfoundland and Labrador, Canada  rating by the MS neurologist were extracted from health records. Those patients with EDSS scores of higher than 6.5, who could not walk, were excluded. Thus, data from 107 patients were included. Their EDSS scores range from 0 to 6.5, and their average EDSS score was 2.11 ± 1.89.The replies to a subset of eight MSIS-29 questions on how patients felt about their walking, balance, and movement  were useA set of gait features was extracted from the raw sensor data based on footprints from each pass. These included 21 features, foot type/length/width/area, unsigned toe angle, step/stride length, step/stride width, base width, step/stride time, step/stride velocity, single/double support time, stance time, toe direction, hull area, base of support (BOS) area, line of progression (LOP) deviation angle. The details regarding each parameter and how they were extracted from the walkway sensor data were described previously  Cox, , supportLR provides a probability for the target class between 0 and 1 to describe the relationship between the input variables and one or more output targets. The input value x is fitted into the logistic function, whereby the weights or coefficient values are adjusted to predict the output value y.SVM has the capability to work with high-dimensional data. SVM attempts to define a hyperplane boundary in an N-dimensional space, where N is the number of input features. SVM is supposed to determine the optimal plane that best separates the classes.XGB is a distributed gradient boosting machine learning library. Applied to an ensemble of weak prediction models, the gradient boosting algorithm trains data with these weak learners forces the poor performance learners to learn to increase their prediction score, and finally combines them into one accurate prediction algorithm.A standard grid search method was used to choose the best hyperparameters. The hyperparameter options and the optimal hyperparameters for each model described in Grouped 5-fold cross-validation strategy was employed to evaluate the model result  using Delong test  is significantly lower (p < 0.005) than those of XGB (78%) and SVM (77%); there is no significant difference between the accuracies of XGB and SVM. Similarly, LR has significantly lower recall (70%) and f1-score (76%) values than those of XGB  and SVM , with no significant differences between XGB and SVM. There was no significant difference between the precision values of the three models. However, the Delong test shows there are significant differences between means of AUC of all three models (p < 0.0001), with XGB being the best (98.1%), SVM (96%), and LR (79.6%). The reason the AUC values of all three models are higher than model accuracies could be that the optimized decision thresholds were chosen for calculating AUCs  of self-reported (and combined) gait and balance problems using binary class models. Future research should explore expanded ratings, such as mild, moderate, and severe, or divide self-reported mobility problems based on whether the problem relates to gait or balance. Thus, more novel features would be explored, including pressure distribution of the foot, which could potentially be helpful for classification . The patients/participants provided their written informed consent to participate in this study.WH: experiment design, data analysis and interpretation, and paper drafting and editing. OC: experiment design and data analysis and interpretation. MP and XJ: research concept design, paper revision, and funding support. CN, MW, SB, and AC: subject recruitment, data collection and extraction, and data cleaning. All authors contributed to the article and approved the submitted version.This work was supported in part by Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery , the Canada Research Chairs Program (MP Grant No. 950-230457), Canada Foundation for Innovation (MP Project No. 33621), Canadian Institutes for Health Research (MP Grant No. 169649).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 frequency of food intake was assessed by food-frequency questionnaire, while changes in taste perception were assessed using the taste desire and enjoyment change questionnaire. The change in total body weight was also assessed. Results: A significant decrease in the intake frequency of bread and crackers (p < 0.001), dairy products and fats (p < 0.001), sweets and snacks (p < 0.001) and soft drinks (p < 0.001), and a significant increase in the frequency of vegetable and fruit consumption (p < 0.001) were observed at 12 months after SG in both genders. On the contrary, we found no significant changes in the frequency of meat and fish intake in females (p = 0.204), whereas a significant change was found in males (p = 0.028). Changes in perceived taste intensity of fatty foods (p = 0.021) and tart foods (p = 0.006) for females and taste of bitter foods for females and males  were found. Regarding the change in food desire for both genders, there was a decrease in the desire for sweet, fatty, and salty foods, whereas there was an increasing trend in the desire for tart foods, especially for females. Significant reduction in total body weight and BMI was observed in both genders at the time of follow-up. Conclusions: Based on our findings, we are able to support the evidence that changes in taste, desire, and enjoyment of taste are very common after SG, with a reduced preference for food with high sugar and fat content and an increased postoperative preference for low-sugar and -fat foods. However, further investigation is needed to clarify this issue. The molecular, hormonal, and central mechanisms underlying these changes in taste perception need to be further elucidated, as they could identify new targets able to modify obesogenic eating behavior, opening up a novel personalized therapeutic approach to obesity.Obesity is a well-recognized global health problem, and bariatric surgery (BS)-induced weight reduction has been demonstrated to improve survival and obesity-related conditions. Sleeve gastrectomy (SG) is actually one of the most performed bariatric procedures. The underlying mechanisms of weight loss and its maintenance after SG are not yet fully understood. However, changes to the taste function could be a contributing factor. Data on the extent of the phenomenon are limited. The primary objective was to assess, through validated questionnaires, the percentage of patients who report an altered perception of post-SG taste and compare the frequency of intake of the different food classes before SG and after 1 year follow-up. The secondary objective was to evaluate the total body weight change. Materials and Methods: We prospectively investigated the changes in food choice and gustatory sensitivity of 52 patients  12 months after SG. The mean initial weight and body mass index (BMI) were 130.9 ± 24.7 kg and 47.4 ± 7.1 kg/m Taste is one of the factors responsible for eating rate, as it is related to the duration of oral exposure to food, and thereby, it affects satiation . The senIt is unclear under which mechanisms taste sensitivity may influence macronutrient intake. Macronutrients interact through a variety of oral sensing mechanisms to convey signals about the quantity and quality of the ingested nutrients, contributing to the efficient metabolism and disposal of such nutrients. Understanding the range of oral sensibilities in human beings and how it is influenced by genetic and environmental variables may lead to important insights into the role of taste in food intake regulation and metabolism, and therefore, in the etiopathogenesis of obesity. The development of obesity is associated with a significant reduction in taste buds ,5,6 and Obesity is a well-recognized global health problem, and bariatric surgery (BS)-induced weight reduction has been demonstrated to improve survival and obesity-related conditions . Indeed,After SG, patients are known to change their food preferences, suggesting a change in the underlying physiological responses to food . This haA few studies measured the effect of SG and other bariatric procedures on taste detection. Eight of them examined the effect of the BS on sweet taste, three on sour taste, six on salty taste, two on savory taste, and three on bitter taste ,22,23,242 or ≥35 kg/m2 with obesity-related comorbidities and age between 18 and 65 years. In total, 52 patients were included in the study.A single-center prospective cohort study was conducted on a cohort of patients with obesity who received SG between May and September 2020. In agreement with the interdisciplinary European guidelines on metabolic and bariatric surgery , inclusiThe primary objective was to assess, through validated questionnaires, the percentage of patients who report an altered perception of post-SG taste and compare the frequency of intake of the different food classes before SG and after 1 year follow-up. The secondary objective was to evaluate the total body weight change.+ times per day. A response of 0 indicated no change. The Taste Desire and Enjoyment Change Questionnaire [To measure the patients’ habitual food intake before and after 1 year of SG, a questionnaire was constructed by the research team based on the macro areas of the EPIC—Food Frequency Questionnaire  Supplem. To ensuionnaire   and height (cm) were determined under standard conditions . Height was measured using a Seca 206 mechanical measuring tape . Body weight (BW) was assessed by a Seca 869 flat digital scale . BW evaluation was performed at baseline and repeated by the same nutritionist during the follow-up. Body mass index (BMI) was calculated by dividing body weight (BW) by heightt-tests for continuous variables were performed to compare the change in food intake of female and male patients before and after the year of intervention. A response of zero in the items on change in food intake indicated no change in eating habits, so a series of one-sample t-tests were used to test whether the responses were significantly different from zero. A series of box plots with gender difference were used to show changes in food intake before and after one year from SG. Poisson regression analyses were performed to calculate significant predictors of taste, desire, and enjoyment on the measured variable. Incidence rate ratios (IRRs) and their 95% confidence intervals (CI) were used in the Poisson regression models to measure the independent associations between the different variables and the outcomes of interest. Multivariate analysis graphs were used to show the degree of change in taste, desire, and enjoyment between females and males . For all analyses, two-sided p-values of 0.05 or less were considered statistically significant. Data analyses were conducted using STATA Software .Descriptive statistics were used to summarize patients’ characteristics, and the responses to all items were shown with absolute and relative frequencies for categorical variables and mean and standard deviation for continuous variables. Paired Student’s p < 0.001; p < 0.001, respectively), dairy products and fats , sweets and snacks , and soft drinks . At 12 months after SG, there was a statistically significant increase in the frequency of vegetable and fruit consumption in both genders . There were no significant changes in the frequency of meat and fish intake between before and 1 year postoperative in females (p = 0.204), whereas a significant change was observed in males (p = 0.028).All 52 patients completed the study. p = 0.021), tart foods , and bitter food  for females and taste of bitter food for males . Regarding the change in the desire for food flavors for both genders, there was a decrease in the desire for sweet, fatty, and salty foods, whereas there was an increasing trend in the desire for tart foods, especially for females. Poisson regression results revealed that the statistically significant predictors of %TWL were, for females, the desire for tart foods with a protective incidence ratio , while for males, the desire for bitter tastes had a protective incidence ratio . The decrease in perception of enjoyment for sweet was greater in males than in females, whereas decrease in enjoyment for fatty was greater for females than for males. There was an increase in perception of enjoyment for bitter foods for both genders but more so in females. Results from the Poisson regression model showed that by %TWL, several variables were statistically significant for females, including decreased enjoyment of sweet foods , pleasure of salty foods , pleasure of bitter foods  protective factors, whereas for males, decreased pleasure of spicy foods  was a risk factor.p < 0.001 and p < 0.001, respectively).As expected, we observed significant improvement in BW and BMI at 1 year after SG  systems, which may work to fine tune body metabolism in response to dietary exposure to taste stimuli. The endocannabinoid system regulates “on demand” the production and degradation, by specific pathways, of arachidonic acid derivatives, N-arachidonoylethanolamide  and 2-arachidonoylglycerol (2-AG), and their high-affinity cannabinoid receptors (CB) 1 and CB 2 . These rGustatory stimulation by palatable foods induces dopamine release in the mesolimbic reward pathway connecting the ventral tegmental area (VTA) to the nucleus accumbens (NAc) within the ventral striatum. Sensory stimuli from taste buds are transmitted as signals through the solitary nucleus and in the upper medulla to other brainstem nuclei important for food intake and digestion . This neWe acknowledge some limitations, including the low number of patients and the lack of a control group. Furthermore, we are conscious that the assessment of the changes in taste perception and of the frequency of food intake by other techniques, such as constant stimuli, two-alternative forced choice, three-alternative forced choice, and Burghart taste strip test, could be more accurate. However, the obtained results on the changes in taste perception and on the frequency of food intake assessment by validated questionnaires appeared to be reliable and reproducible.SG is characterized by a postoperative change in taste and preference for foods. However, further investigation is needed to clarify this issue. As a future prospective point of view, the molecular, hormonal, and central mechanisms underlying these changes in taste perception need to be further elucidated, as the characterization of changes in gustatory perception and liking, and the associated endocrine-metabolic-molecular variations, will allow identifying the mechanisms underlying dietary preferences and related metabolic changes characteristic of patients after SG. Furthermore, these data could identify new targets able to modify obesogenic eating behavior, opening up a novel personalized therapeutic approach to obesity.


Objectives: To create a novel preoperative prediction model based on a deep learning algorithm to predict neoplasm T staging and grading in patients with upper tract urothelial carcinoma (UTUC). Methods: We performed a retrospective cohort study of patients diagnosed with UTUC between 2001 and 2012 at our institution. Five deep learning algorithms  were used to develop a preoperative prediction model for neoplasm T staging and grading. The Matthews correlation coefficient (MMC) and the receiver-operating characteristic curve with the area under the curve (AUC) were used to evaluate the performance of each prediction model. Results: The clinical data of a total of 884 patients with pathologically confirmed UTUC were collected. The T-staging prediction model based on CNN-BiGRU achieved the best performance, and the MMC and AUC were 0.598 (0.592–0.604) and 0.760 (0.755–0.765), respectively. The grading prediction model [1973 World Health Organization (WHO) grading system] based on CNN-BiGRU achieved the best performance, and the MMC and AUC were 0.612 (0.609–0.615) and 0.804 (0.801–0.807), respectively. The grading prediction model [2004 WHO grading system] based on BiGRU achieved the best performance, and the MMC and AUC were 0.621 (0.616–0.626) and 0.824 (0.819–0.829), respectively. Conclusions: We developed an accurate UTUC preoperative prediction model to predict neoplasm T staging and grading based on deep learning algorithms, which will help urologists to make appropriate treatment decisions in the early stage. Upper tract urothelial carcinoma (UTUC) is a relatively rare group of tumours, accounting for 5–10% of urothelial carcinomas . HoweverIf the pathologic characteristics of the tumour can be accurately predicted from routine clinical data before surgery, this information may improve the urologist’s strategy for the treatment of the disease. Predicting the stage and grade of the tumour may influence the choice of the first treatment for patients with UTUC and whether it should involve conservative treatment, RNU, RNU with lymph node dissection, or neoadjuvant systemic chemotherapy. The appropriate selection of patients for individualized treatment is beneficial in managing UTUC .In recent years, prediction tools based on deep learning algorithms have developed rapidly, especially in the field of oncology. Although there have been some multivariate models based on preoperative information to predict the pathological features of postoperative UTUC ,8,9, no Therefore, the purpose of our study was to construct a preoperative prediction model for UTUC based on five deep learning algorithms to predict the staging and grading of UTUC to guide clinical decision-making.This analysis was reported according to the TRIPOD  guidelines, a reporting specification for predictive models of disease diagnosis and prognosis . A flow We retrospectively collected the clinicopathological data of UTUC patients (884 cases) who underwent RNU surgery at Peking University First Hospital from 2001 to 2012. Patients in this study met the following inclusion criteria: (1) UTUC confirmed pathologically after surgery; (2) no distant metastasis. The following patients were excluded: (1) UTUC with metastases before RNU and (2) patients with previous contralateral UTUC. In addition, cases with incomplete data were excluded. Follow-up data were obtained by reviewing the clinical and pathological databases at our institution. Overall survival (OS) was calculated from the date of surgery to the date of all-cause death.The information collected included medical record information and auxiliary test results. Preoperative information on UTUC patients included general information, past history, personal history, laboratory tests, and auxiliary examinations. Laboratory tests included haematology tests, coagulation tests, and biochemical examinations. Auxiliary examinations included, but were not limited to, the presence of hydronephrosis, tumour site, tumour location, and longest diameter of the tumour. Cases with incomplete data were excluded.For feature selection, we first manually removed some features that were obviously irrelevant to the prediction results, such as the case ID. Subsequently, Xgboost  was used to perform feature-correlation analysis to filter out features with low correlation to the prediction results, while the literature review was combined with the screening to retain the important features. The features were then modelled separately using deep learning models to compare their impact on the prediction results. By comparing and analysing different feature combinations, forty-four features were ultimately screened out .The endpoint indicators predicted by the model were the specific staging and grading of UTUC. We treated the prediction results of the model as a discrete classification problem due to a lack of reliable weighting references for different T-stages or gradings and simplified the development of models. Information on the staging and grading of UTUC was obtained by the pathologic evaluation of postoperative samples. Clinical samples were obtained by experienced urologic oncologic surgeons using a standardized RNU approach, including resection of the full length of the kidney and ureter and the adjacent portion of the bladder cuff. All surgical samples were processed according to standard pathology procedures. Tumour staging was evaluated according to the 2002 Union for International Cancer Control (UICC) TNM classification of malignancies. There are two different clinical grading systems for UTUC at this time: the 1973 World Health Organization (WHO) classification and the 2004 WHO classification. No consensus has been made on which classification should supersede the other, and both are recommended in the European Association of Urology guidelines . Tumour Data were randomly split into training and test sets at a ratio of 8:2 using random functions in Python. The training set was used to generate the prediction model, and the test set was used to estimate the model’s accuracy. To improve the ability to generalize and balance the different classes, the SMOTE algorithm was employed to counter the class imbalance. By combining the oversampling of the minority class and the undersampling of the majority class, SMOTE can achieve a better classifier performance .We used five newer deep learning models that have been proposed in recent years in the biomedical field to predict neoplasm staging and grading in patients with UTUC, including CGRU, BiGRU, CNN-BiGRU, CBiLSTM, and CNN-BiLSTM.CGRU is a multilabel classifier based on deep CNN. CNNs are a unique class of neural network models designed to identify hidden patterns and relationships in large datasets. GRU uses two gates: an update gate and a reset gate. The reset gate determines the amount of past information to be forgotten, while the update gate determines which information to keep and not to keep .In the BiGRU network, the input vector (forward) and the corresponding reverse version (backwards) are fed into two GRUs, and the combination of the forward hidden-state output and the reverse hidden-state output is the output of the network .CNN-BiGRU can automatically measure and assign weights to different leads based on their contributions. In short, the CNN module exploits interrelated features between leads and extracts differentiated spatial features. In addition, the BiGRU module extracts the underlying temporal features within each lead. The spatial and temporal features from these two modules are fused as global features for classification .CBiLSTM is a two-channel hybrid neural network model based on CNN and BiLSTM. CNN and BiLSTM extract features from the original data and then connect them and map them to a fully connected layer. BiLSTM consists of two independent LSTM neural networks with a specific network structure consisting of an input gate structure and an output gate structure. The gates only restrict the direction of the information flow, and the LSTM affects the state of the RNN one at a time through the gate structure .The CNN-BiLSTM neural network framework involves feature-extraction using a pretrained convolutional network and then feeds the feature vectors to a bidirectional long- and short-term memory network to capture the temporal features of the data . The preThe hyperparameters were adjusted during model construction to construct high-quality models, such as the number of layers and hidden cells, learning rate, learning rate decay, dropout rate, batch size, and epoch.Considering the class imbalance that often occurs in biomedical datasets, we used the Matthews correlation coefficient (MCC), which is a more-reliable statistical rate in binary classification evaluation, to assess the model’s ability . The rechttps://www.python.org/, accessed on 14 July 2022) was used for deep learning analysis. Other analyses were performed with R statistical software version 3.4.1 . p < 0.05 was considered as statistically significant.Continuous variables were expressed as the interquartile range. Pearson’s chi-squared test was conducted to analyse unordered categories data. Linear-by-linear association was used for ordinal data. A normality test was used for continuous data, and Student’s T test was used for data conforming to normal distribution. The log-rank test was used to compare the difference in survival curves between groups. Python 3.8.1 for Windows (p < 0.05).A total of 884 patients with UTUC were finally included in this study. The patients’ median  age was 69  years old. Among the T-staging of tumours, Ta, T1, T2, T3, and T4 stage accounted for 2.7%, 34.2%, 33.8%, 27.1%, and 2%, respectively. Among the G stages of tumours, G1, G2, and G3 accounted for 2.8%, 56.1%, and 41.0%, respectively. The mean follow-up time of the patients was 70.3 months. The clinical and pathological characteristics of patients with UTUC are summarized in n = 707) and 20% the test set (n = 177). There were no statistically significant differences in the characteristics between the two sets (p > 0.05)  . To solv−8, and batch size = 16.Through multiple rounds of training and manual debugging, the final critical hyperparameters of the deep learning models were as follows: learning rate = 0.001, Adam = True, optim momentum value = 0.9, weight decay = 1 × 10The ROC curves for the neoplasm T staging and grading of different deep learning models are shown in UTUC is a relatively rare tumour of the urinary tract for which RNU is the standard of treatment. For patients assessed as low-risk, nephron-sparing treatments such as endoscopic ablative treatments may be appropriate . In the Our study used multiple deep learning algorithms to construct a preoperative prediction model for UTUC for the first time. It achieved AUCs of 0.760, 0.804, and 0.824 for tumour T staging (CNN-BiGRU), tumour grading based on the 1973 WHO classification (CNN-BiGRU), and tumour grading based on the 2004 WHO classification (BiGRU), respectively, demonstrating a better prediction performance. These results indicate that the deep learning model has a good application value as a preoperative prediction model in patients with UTUC. Previously, other investigators published tools of UTUC to predict muscle-invasive disease and/or nonorgan-confined disease. Deep learning models have been widely used in many fields, such as environmental atmosphere prediction and financial-risk models. They have been rapidly developed in the medical field in the recent years . Deep leThere are some potential limitations in our study. First, as a deep learning model, cases in the test set are still insufficient, and further samples need to be included in the future to improve the model’s performance. Second, it is necessary to validate this in a multicentre or international cohort model soon. In addition, since the deep learning model is a “black box” model and some computational principles are challenging to explain, we will consider developing a visualization program in the future to facilitate clinical promotion and application.In contrast to the traditional multivariate model, we have developed an accurate UTUC preoperative prediction model to predict neoplasm T staging and grading based on deep learning algorithms, which will help urologists to make appropriate treatment decisions in the early stage.


Drug-resistance is a significant clinical issue in persons with epilepsy. In the past few years, many studies have been published investigating the management of drug-resistant epilepsy (DRE); however, no systematic and quantitative evaluation of this research has been performed. Therefore, a bibliometric analysis was conducted to demonstrate the current status of DRE research and to reflect the trends and hotspots within the field.We retrieved publications on DRE published between 2011 and 2021 from the Science Citation Index Expanded of the Web of Science Core Collection. All articles related to DRE were included in this study. VOSviewer, R software, and CiteSpace were used to perform bibliometric research.Epilepsy & Behavior and Epilepsia ranked first as the most prolific and co-cited journals, respectively. The keywords “cannabidiol”, “neuromodulation”, “seeg” and “perampanel” revealed recent research hotspots. The top 100 most cited papers were classified into eight main topics, of which pharmacotherapy, disease mechanisms/pathophysiology, and neuromodulation were the three most important topics.A total of 3,088 original articles were included in this study. The number of publications on DRE has continued to increase over the past 11 years. The USA published the most papers with the highest number of citations and H-index. The National Institutes of Health and the University of Toronto were the most prolific funding agency and affiliation, respectively. This analysis of bibliometric data demonstrated that DRE has always been a topical area of research. The mechanisms of epilepsy and therapies have been the focus of DRE research, and innovative antiseizure medications and surgical approaches are fast-developing research trends. Epilepsy is one of the most prevalent and disabling chronic neurologic diseases, with 60 million patients globally and 125,000 deaths per annum . The faiThe management of DRE has become one of the biggest challenges in clinical epilepsy practice. In the current era of the emergence of novel medication and technology, quantitative analyses are needed to provide an overview of incremental improvement, helping researchers capture the status, trends, and hotspots of DRE research.Bibliometric analysis is a method to quantitatively analyze publications, using mathematical and statistical methods . BibliomIn this study, VOSviewer, R software, and CiteSpace were used to build a network of countries, affiliations, co-authors, co-occurrent keywords, bibliographic coupling analysis, co-citations, and references with citation bursts. We further analyzed the 100 most cited publications in this area between 2011 and 2021 to highlight evidence-based studies in the field. The purpose of our article was to systematically and visually describe and analyze DRE research, as well as to provide researchers with meaningful insight into future directions related to the mechanisms and management of DRE.The Web of Science (WoS) core collection Science Citation Index Expanded (SCI-expanded) database  was utilized to conduct bibliometric analysis. To avoid deviations, two researchers (Xiao-Jun Ni and Han Zhong) independently performed the literature search on a single day February 10, 2022) and determined the eligibility of potential articles. The publication period was set between 2011 and 2021. The search strategy was derived from a systematic review , 2022 an. Among tThe online analysis function of the WoS core database was used to extract basic information on the included publications, including annual, national, institutional, and individual numbers of publications (NOP), the number of citations not including self-citations (NOC), and the top 100 cited publications. The H-index is an integrated indicator used to assess the academic achievements of a researcher, a journal, an institution, or a nation or region and predict future scientific contribution, unifying productivity and impact by finding the appropriate threshold that connects NOP with NOC. Journal impact factors were obtained from the 2021 Journal Citation Reports. The Bibliometrix package (version 3.0) in R software  was used to describe the relationship networks between countries . BibliomBased on the search strategy, 5,509 publications on DRE were identified between 2011 and 2021. We excluded 125 publications not published in English. A total of 2,296 publications, including 1,360 meeting abstracts, 545 review articles, 185 letters, 143 editorial materials, and 65 other forms, were also removed because of non-pre-defined article types. Ultimately, 3,088 original studies were retained in quantitative analysis. A total of 90 countries/regions contributed to DRE research. The top 10 most productive affiliations are shown in Between 2011 and 2021, a total of 14,147 authors have published relevant research papers. The 11 most productive authors are shown in Epilepsy & Behavior  ranked first, followed by Epilepsia , Epilepsy Research , and Seizure . Applying Bradford's Law, Epilepsy & Behavior, Epilepsia, Epilepsy Research, and Seizure ranked first among all sources in the field of DRE .A total of 528 journals had published papers on DRE. d of DRE . Among tKeywords provided by the authors of the publication with an occurrence of over 15 times in the WoS core database were included in the analysis. Among 5,287 keywords, 99 met these criteria. The three most frequent keywords were “epilepsy” , “epilepsy surgery” , and “refractory epilepsy” . “epilepsy” had a strong link to “seizure”, “epilepsy surgery”, “children”, “antiepileptic drug” and “vagus nerve stimulation”. Additionally, “drug-resistant epilepsy”, “seizure”, “children”, “antiepileptic drug”, “vagus nerve stimulation”, “ketogenic diet”, “intractable epilepsy” and “status epilepticus” were other keywords with a total link strength greater than 200 ,B. As shEpilepsy & Behavior was the most representative journal.Bibliographic coupling analysis weighs links between papers that have cited the same literature. Epilepsia had the highest number of co-citations , followed by Neurology , Epilepsy & Behavior , Epilepsy Research , and Seizure . Journals with over 200 co-citations were used to develop the co-citation network. As illustrated in Epilepsia had an active co-citation relationship with Neurology, Epilepsy & Behavior, Epilepsy Research, and Brain.The co-citation network emphasizes research themes closely associated with a specific field. Co-citations represent how frequently two papers are cited together by other papers and may be considered as a knowledge base for a specific field . Given tEpilepsia, an official journal of the International League Against Epilepsy (ILAE). Relationships between the topics and subtopics of the aforementioned articles were established , and “ILAE classification of the epilepsies: Position paper of the ILAE Commission for Classification and Terminology” (strength = 19.63). These cited papers are landmark documents in this field, which effectively standardized the definition and classification of epilepsy, and provided a foundation for subsequent studies.Citation burst detection can reveal research trends and novel topics that are rapidly gaining attention in a specific area. Epilepsia is the most influential journal in this field owing to the number and importance of publications.In the current study, we conducted a bibliometric analysis to provide an overview of developmental trends and hotspots in research on DRE from the SCI-expanded database, using a variety of bibliometric tools. Due to many leading affiliations, funding agencies, and researchers, the USA made the most important contribution to this particular research field. As the predominant research teams in Asian countries, China, India, and Japan must make more efforts to conduct innovative research to increase the impact. Regarding journals, As seen in the analysis of the top 100 most cited publications, the most influential studies were clinical studies. These studies analyzed the diagnosis of DRE, disease characteristics and screening, and multiple treatments such as medication, surgery, neuromodulation, and dietary therapies.For a long time, the definition of DRE was not unified and potentially conflicting, varying among studies. The study with the highest number of co-citations and the strongest citation bursts was published in 2010 by the ILAE, which delivered a formal consensus on the definition of DRE . Only onAlthough DRE patients do not receive two medication regimens, trying other ASMs remains the primary treatment option. From 2011 to 2021, a series of clinical trials on newer third-generation ASMs have been published. Perampanel was approved for treating partial-onset seizures in 2012 and primary generalized tonic clinic seizures in 2016. A pooled analysis demonstrated a significant reduction in seizure frequency –20. EsliThe current choice of ASMs can be described as empirical and based primarily on the patient's demographic profile, seizure type, comorbidity, concomitant medication, and adverse drug reaction. Exploration of pharmacogenomics in epilepsy may help to predict drug responses and improve effectiveness and tolerability. Genetic variations of drug transporters may be associated with a higher risk of DRE . ATP-binvia a fiber probe inserted through a twist drill hole with the advantage of ablating difficult-to-reach epileptogenic regions. A multicenter cohort study including 234 patients who underwent LITT for mesial temporal lobe epilepsy demonstrated that Engel I outcome was achieved in 58% of patients at both 1 and 2 years after LITT. A single-center study including pediatric patients with drug-resistant lesional epilepsy showed that Engel class I outcome was achieved in 41% patients , deep brain stimulation (DBS), responsive neurostimulation (RNS), and non-invasive methods including transcutaneous VNS and transcranial stimulation. Neuromodulation is considered a palliative treatment, that only some patients might benefit from for longer than 12 months . VNS wasThe closed-loop responsive neurostimulation system was designed to abort possible impending seizures by monitoring the electrocorticogram at the seizure focus and delivering short bursts of high-frequency electrical stimulation. The acute and sustained efficacy and safety of the RNS system were confirmed in a long-term study (mean 5.4 years). The median percent seizure reduction rate ranged from 44 to 66% over 1–6 years post-implant . A 9-yeaKetogenic dietary therapy has been used since the 1920's, mainly in pediatric patients with severe and refractory epilepsy. In the past decade, owing to the availability of broader dietary options and the expansion of the target population, the ketogenic diet has received renewed attention. The efficacy of the ketogenic diet has been well-established in children with various seizure types and epileptic syndromes. Children given ketogenic diets may be up to six times more likely to achieve a 50% or greater reduction in seizure frequency and up to three times more likely to become seizure-free than children given the usual care . HoweverBased on the bibliometric analysis of the literature in DRE, we provide a comprehensive and objective insight into the global status and hotspots in this field. However, this study has some limitations. First, only articles written in English from the SCI-expanded database were included. Second, some emerging significant papers and trends may not have been captured due to a low number of citations. Despite these limitations, this study provides insight into research from the last decade in this special field, demonstrating that there is sustained and intense interest in identifying the mechanisms of DRE and developing various antiseizure therapies to improve the outcome of patients with DRE.Epilepsy & Behavior, Epilepsia, Epilepsy Research, and Seizure were the most productive journals, of which Epilepsia published many papers with several citations. The bibliometric data can make important contributions to our understanding of the advancement of DRE management.This bibliometric analysis has demonstrated that DRE has always been a hot area of research. The USA is the most influential and productive country, with extensive co-operation with other leading countries. The original contributions presented in the study are included in the article/X-JN and HZ performed the data search and drafted the manuscript. Y-XL performed the software. Z-CG and H-WL revised and approved the final manuscript. All authors made substantial contributions to the conception and design of this study. All authors contributed to the article and approved the submitted version.This work was supported by the Clinical Research Innovation and Cultivation Fund of Ren Ji Hospital (RJPY-LX-008) and Research Project of Drug Clinical Comprehensive Evaluation and Drug Treatment Pathway (SHYXH-ZP-2021-001).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. 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