The purpose of this study was to evaluate the differences in the patient-reported functional outcomes, and graft failure in revision ACL reconstruction using quadriceps tendon (QT), Hamstring tendon (HT) and bone-patellar tendon-bone (BPTB) autografts.Between 2010 and 2020, 97 patients who underwent revision ACL reconstruction  met the inclusion criteria. Pre-injury and at 2-year postoperatively patients were evaluated for patient-reported functional outcomes; Lysholm knee score, Tegner activity level and VAS  for pain; and graft failure. Patient-reported outcomes and graft failure were compared between the QT, HT and BPTB groups. The patients with graft failure were not included for outcome analysis at 2-years of follow-up.All three revision groups with QT, HT and BPTB autograft did not differ significantly in terms of age, sex, time from injury to surgery, concomitant injuries and single-stage or double-stage procedures (n.s.). No significant difference was found in the pre-injury patient-reported outcome; Lysholm knee score, Tegner activity and VAS for pain (n.s.) between the three groups. At the 2-year follow-up functional outcomes improved in all three groups and all the patients returned to pre-injury activity level; however, no significant difference was found in functional outcomes at the 2-year follow-up between the three groups (n.s.). Graft failure occurred in 4 (10%), 5 (19%) and 3 (10%) patients of QT, HT and BPTB groups, respectively. However, the rate of failure did not differ significantly between groups.All three autografts  demonstrated satisfactory patient-reported outcomes in revision ACL reconstruction. Compared with QT and BPTB grafts, HT graft showed a higher tendency for failure rates. With the increasing incidence of revision ACL reconstruction, surgeons should be aware of all the available graft options. The findings of this study will assist the surgeons in the graft selection for revision ACL reconstruction.Level III. Various patient-related factors such as age, sex, and tibial slope; surgeon-related factors such as graft size, graft type, and tunnel placement; other factors such as activity level, concomitant injuries, and timing of return to sport are associated with retear rates after ACL surgery , 7. GrafHamstring tendon (HT) and bone-patellar tendon-bone (BPTB) are the two most commonly used grafts and both grafts provided satisfactory outcomes , 16, 29.In recent years, Quadriceps tendon (QT) graft has gathered enthusiasm due to lower donor site morbidity than HT and BPTB, lower failure rate than HT, greater mean cross-sectional area compared to BPTB and greater load to failure compared to other grafts , 20, 28.However, as far as the authors’ knowledge, no study is available that compares the functional outcome and graft failure with QT, HT and BPTB autograft in revision ACL reconstruction. Thus, the purpose of this study was to evaluate the differences in the patient-reported functional outcomes, and graft failure in revision ACL surgery using QT, HT and BPTB autografts. The hypothesis was that all three grafts would have similar functional outcomes but higher graft failure would be associated with HT compared to QT and BTBP in revision ACL reconstruction. The findings of this study will assist the surgeons in the graft selection for revision ACL reconstruction.The study was performed at Gelenkpunkt—Sports and Joint Surgery, FIFA Medical Centre of Excellence and approved by the ethics committee of the Medical University of Innsbruck (AN2015-0050). Prospectively collected data were obtained from an ACL registry. Patients were included in the study if they fulfilled the following inclusion criteria: revision ACL reconstruction using QT, HT, BPTB autograft; age 18–55 years; and a minimum of 2-year follow-up. The exclusion criteria were: primary ACL reconstruction; contralateral knee injuries; utilization of allograft or graft other than QT, HT, BPTB; inflammatory arthritis or osteoarthritis; less than 2-year of follow-up and conditions that might interfere with the standard postoperative rehabilitation protocol.Pre-operative CT (computed tomography) scan with 3D reconstruction was performed for all the patients to determine femoral and tibial tunnel positions, tunnel widening and tunnel convergence. The present study followed the classification for ACL revision published by Fink et al. . Based oIn most cases, a rectangular femoral tunnel was used . BesidesBetween 2010 and 2020, 97 patients who underwent revision ACL reconstruction  met the inclusion criteria. All surgeries were performed by two fellowship-trained knee specialists. Patients were specifically asked to fill out the questionnaire considering their pre-injury state (just before failure of primary reconstructed ACL), during the first week of revision surgery for the baseline functional scores. Similarly, patients were evaluated at a 2-year follow-up for Lysholm knee score, Tegner activity level and VAS  for pain; and graft failure. Patient-reported outcomes and graft failure were compared between the QT, HT and BPTB groups. The patients with graft failure were not included for outcome analysis at 2-years of follow-up.α level with p = 0.05, a power of 80%, and an effect size of 0.20 it was estimated that 63 subjects would be needed in order to detect a statistically significant difference in Lysholm knee score. The sample size calculation was performed with the use of the G-Power software .A priori power analysis was performed to determine the appropriate sample size for the study. Considering an p value less than 0.05 was indicative of statistically significant differences. The statistical analysis was performed with XLSTAT (Addinsoft SARL) software packages.Data were retrieved and organized using an Excel sheet . Categorical variables were expressed in numbers and percentages (%). Continuous variables were expressed by average and standard deviation (SD). The normal distribution of variables was verified through Shapiro–Wilk test. Variables were not normally distributed therefore; nonparametric tests were used for the comparison of variables. Specifically, the Mann–Whitney test was used for unpaired samples, when analyzing the variables between pre-injury level and follow-up in each group. The Kruskal–Wallis test was used to analyze continuous variables between groups. The chi-square statistic test was used to determine differences in nominal data between groups, with Yates correction applied when the frequency of observations was below 5. A Demographic details and characteristics of the study population can be found in Table . All thrp = 0.01 and p = 0.04). Although improvement was noted in Lysholm score in either QT and HT groups, it did not reach statistical significance at a 2-year follow-up (n.s.) . Similarly, VAS for pain also improved and reach to pre-injury level in all three groups. No significant difference was noted in VAS at 2-year compared to the pre-injury level (n.s.) in QT and HT groups. However, in BPTB groups VAS improved significantly at 2-year follow-up compared to pre-injury level. Graft failure occurred in 4 (10%), 5 (19.2%) and 3 (9.7%) patients of QT, HT and BPTB groups respectively. However, the rate of failure did not differ significantly between groups (n.s).The most important findings of this study were that after revision of ACL reconstruction satisfactory improvement was noted for patient-reported functional outcomes  in all the groups. No difference was found in functional outcomes between the three groups at the final follow-up. All the patients returned to the pre-injury activity level. A tendency for higher graft failure was noted with HT (19.2%) than QT (10%) or BPTB (10%) grafts. To the best of the author’s knowledge, this is the first study comparing all three autografts; QT, HT and BPTB for revision ACL reconstruction.The incidence of ACL reconstruction is increasing over the past few decades. Excellent results after primary ACL reconstruction allow the patients to participate in highly demanding activities such as jumping, cutting, deceleration, and pivoting sports . These aIn the present study, the Lysholm, Tegner activity levels and VAS for pain scores improved and reached pre-injury levels in all three groups. No significant difference was noted in patient-reported outcomes between the three groups at a 2-year follow-up. Mouarbes et al.  noted noInterestingly, a significant improvement from pre-injury to final follow-up was seen in the BPTB group. In their recent study, Yumashev et al.  also fouThe choice of graft in revision ACL reconstruction may be limited based on previously used grafts and it depends on various factors such as age, level of sports activities, previous tunnel position, tunnel enlargement, graft used in primary ACL surgery and surgeon’s preference , 21. GraGraft choice influences graft failure . MulticeThe current study found a higher tendency of graft failure with HT than with QT and BPTB autograft, although the graft failure rate was not significant between the 3 groups. Both QT and BPTB have a higher graft diameter and strength compared to an HT graft which may explain the higher failure rate of HT grafts . In theip < 0.001) in 2015–2020 compared to 2010–2014.QT autografts are used far less commonly than HT and BPTB grafts . One of In the current study, graft failure was similar in QT and BPTB groups. In their meta-analysis, Riaz et al.  reportedThere are a few limitations of the present study. The first and the most important limitation is the small sample size, that underpowered to identify any difference in functional outcomes and graft failure. Revision ACL reconstruction is a less frequently performed procedure than primary reconstruction. Second, this was a retrospective analysis of patient-reported subjective outcome measures; however, all data were collected prospectively. A prospective study considering objective scores along with subjective scores should be conducted.The clinical relevance of the present study lies in the fact that the incidence of revision ACL reconstruction is increasing and surgeons should be aware of all the available graft options. QT autograft is the least studied and least used graft compared to other grafts, especially for revision ACL reconstruction. Many surgeons do not even consider the QT as a possible graft option when discussing with the patients. Promising clinical results continues to emerge concerning the viability of QT autograft in revision ACL reconstruction. Based upon the findings of this study surgeon can counsel and advise the patient regarding the graft choice for revision ACL reconstruction.All three autografts  demonstrated satisfactory patient-reported outcomes in revision ACL reconstruction. Compared with QT and BPTB grafts, HT graft showed a higher tendency for failure rates. With the increasing incidence of revision ACL reconstruction, surgeons should be aware of all the available graft options. The findings of this study will assist the surgeons in the graft selection for revision ACL reconstruction.


COVID-19 is a newly recognized illness with a predominantly respiratory presentation. Although initial analyses have identified groups of candidate gene biomarkers for the diagnosis of COVID-19, they have yet to identify clinically applicable biomarkers, so we need disease-specific diagnostic biomarkers in biofluid and differential diagnosis in comparison with other infectious diseases. This can further increase knowledge of pathogenesis and help guide treatment. Eight transcriptomic profiles of COVID-19 infected versus control samples from peripheral blood (PB), lung tissue, nasopharyngeal swab and bronchoalveolar lavage fluid (BALF) were considered. In order to find COVID-19 potential Specific Blood Differentially expressed genes (SpeBDs), we implemented a strategy based on finding shared pathways of peripheral blood and the most involved tissues in COVID-19 patients. This step was performed to filter blood DEGs with a role in the shared pathways. Furthermore, nine datasets of the three types of Influenza  were used for the second step. Potential Differential Blood DEGs of COVID-19 versus Influenza (DifBDs) were found by extracting DEGs involved in only enriched pathways by SpeBDs and not by Influenza DEGs. Then in the third step, a machine learning method  was utilized to narrow down the number of SpeBDs and DifBDs and find the most predictive combination of them to select COVID-19 potential Specific Blood Biomarker Signatures (SpeBBSs) and COVID-19 versus influenza Differential Blood Biomarker Signatures (DifBBSs), respectively. After that, models based on SpeBBSs and DifBBSs and the corresponding algorithms were built to assess their performance on an external dataset. Among all the extracted DEGs from the PB dataset , 108 unique SpeBD were obtained. Feature selection using Random Forest outperformed its counterparts and selected IGKC, IGLV3-16 and SRP9 among SpeBDs as SpeBBSs. Validation of the constructed model based on these genes and Random Forest on an external dataset resulted in 93.09% Accuracy. Eighty-three pathways enriched by SpeBDs and not by any of the influenza strains were identified, including 87 DifBDs. Using feature selection by Naive Bayes classifier on DifBDs, FMNL2, IGHV3-23, IGLV2-11 and RPL31 were selected as the most predictable DifBBSs. The constructed model based on these genes and Naive Bayes on an external dataset was validated with 87.2% accuracy. Our study identified several candidate blood biomarkers for a potential specific and differential diagnosis of COVID-19. The proposed biomarkers could be valuable targets for practical investigations to validate their potential. Detecting and monitoring the disease as early as possible is paramount to preventing progression. COVID-19 shares overlapping signs, symptoms, laboratory findings and imaging features with other respiratory viruses, which might complicate its diagnosis, treatment, and prognosis2. Recently, the under-detection of many infectious diseases has increased, which is somewhat due to the prevalence of a novel coronavirus2. Influenza, a contagious viral disease-causing respiratory illness, shared similar clinical manifestations to COVID-19. Fever, cough, rhinitis, sore throat, headache, shortness of breath, and myalgia are some of these similar symptoms4. Different subtypes of the influenza A virus, including H1N1, H3N2, and influenza B as a seasonal influenza virus, are currently circulating among individuals5. The co-occurrence of influenza and COVID-19 may increase in the year’s cold months. Both viruses are spread from person to person primarily by airborne droplets6. Failures in differential detection of COVID-19 may result in higher hospitalization rates, prolonged stay in intensive care units, and an increased chance of death in patients8.The novel coronavirus  was first identified at the end of 2019 and has rapidly spread worldwide. It causes severe acute respiratory syndrome and can lead to pneumonia10. Furthermore, RT-qPCR can have a high rate of false-negative results due to the low virus load in individuals, which can also change over time, as well as incorrect sampling. This makes it essential to use host-specific biomarkers as a complementary tool to ensure accurate diagnosis of presence or type of infection in at-risk hosts13.Searching for the virus-specific genetic materials via real-time quantitative polymerase chain reaction (RT-qPCR), so far, is the most reliable method for the detection of coronavirus. However, the procedure of RT-qPCR on virus-specific genetic materials is unable to distinguish between active infection and colonization but host-response biomarkers are able to do that15. Therefore, transcriptomics can be used effectively to identify COVID-19 affected host transcriptional signatures, paving the way for the creation of novel diagnostic biomarkers and therapeutic strategies12. To find virus-specific transcriptional signatures, it is also necessary to comprehend the host response to COVID-19 infection in comparison to other respiratory infections16. Although several candidate gene biomarkers have been proposed so far, none of them were successful for an efficient diagnosis and particularly differential diagnosis of COVID-19 in samples.Numerous tissues, including respiratory epithelial cells, nasopharynx, colonocytes, and whole blood or plasma samples, have recently seen significant changes to the host transcriptome following COVID-19 infection7. So, in order to identify COVID-19 potential Specific Blood Differential expressed genes (SpeBDs), we implemented a strategy based on finding shared pathways of peripheral blood (PB) and the most involved tissues in COVID-19 patients ) to filter blood DEGs based on playing a role in those shared pathways. Furthermore, potential Differential Blood DEGs of COVID-19 versus influenza (DifBDs) were identified by extracting DEGs involved in only enriched pathways by SpeBDs and not by influenza DEGs. Then, a machine learning method (feature selection) was utilized to narrow down the number of SpeBDs and DifBDs and find the most predictive combination of DEGs. This step was performed to select potential COVID-19 Specific Blood Biomarker Signatures (SpeBBSs) and COVID-19 versus influenza Differential Blood Biomarker Signatures (DifBBSs), respectively. Then the models based on the SpeBBSs or DifBBSs and the corresponding algorithms were validated on an external dataset. Accuracy (ACC), Area under curve (AUC) and Matthews Correlation Coefficient (MCC) were calculated to measure the power of machine learning models constructed by considering SpeBBSs and DifBBSs. Different steps of this experiment are demonstrated in Fig. In the present study, we hypothesized that novel and potentially more specific blood biomarkers of a disease could be identified by searching for the DEGs involved in the common pathways between blood and the major organs affected by the disease. We validated this hypothesis using machine learning methods and found that these potential biomarkers included signatures that could accurately differentiate COVID-19 from Influenza blood samples17. Also, the differential expression analysis (DEA) data of the BALF source was obtained from Zhou et al.’s18 and Li et al.’s study19. In addition, datasets of the three types of Influenza  were used to discover DifBDs. Table For finding SpeBDs, transcriptomic profiles of COVID-19 infected versus control samples from PB and three sources related to the respiratory system, the most involved tissues in COVID-19, were considered, including Lung Tissue (Lung), Nasopharyngeal Swab (Swab), and Bronchoalveolar Lavage Fluid (BALF). Datasets of PB, Lung, and Swab sources were obtained from GEO databasehttps://usegalaxy.org/)20. Quality control was executed with FastQC (version 0.11.8). The reads were aligned to the human reference genome file  using HISAT2 (version 2.1.0) with default parameters. The reads mapped to the human reference genome were counted using featureCounts Galaxy Version 2.0.1 and default parameters.Among RNAseq datasets of COVID-19, GEO raw data of GSE155241 , the results of DEA of the sources with more than one dataset (BALF and Lung) were integrated using the Venn diagram. While, in the cases of Swab and PB sources, only one dataset was related to each of them, and plotting the Venn diagram was not required.The RNAseq count files of this study and all other RNAseq datasets of COVID-19  independently. Enriched pathways with adjusted p-value < 0.05 were considered significant. After that, common pathways of each Swab, BALF, and Lung source with PB were found, and the DEGs that had enriched those common pathways in PB were extracted. These DEGs were considered as SpeBDs.The pathway enrichment analysis by the Reactome database in Enrichr web-based toolIn order to find DifBDs, the pathway enrichment analysis for the three types of influenza  was performed independently by the Reactome database of Enrichr. The pathway enrichment analysis for the SpeBDs was performed as well. A pathway was considered significant if the adjusted p-value was smaller than 0.05. Then, a Venn diagram was constructed including the significant pathways of SpeBDs, H1N1, H3N2, and B. Significant specific pathways of COVID-19 that were not enriched in any of the influenza types were selected. After that, the SpeBDs of COVID-19 that had enriched those pathways were extracted. These DEGs were considered as DifBDs.26.RapidMiner Studio as a powerful tool for biomarker discovery was registered (version 9.7) and utilized to extract and validate biomarker signature from SpeBDs and DifBDsIn this study a two-step machine learning approach was implemented, first we employed four classifiers  to supervise the wrapper feature selection method and extract the best combination of biomarkers from the feature selection dataset . In the next step, the models based on optimal subset of biomarkers and the corresponding algorithms  were validated on the validation dataset . The logic behind this strategy was that the algorithm applied to supervise a wrapper method has had the best performance ability for a subset of features, among other probable combination of features. So we can use that algorithm for building a model (biomarker panel) based on the corresponding features (SpeBBSs or DifBBSs) and test the model on an external dataset to validate the model. The purpose of employing four classifiers in this study was to get four subsets of genes and build four models and biomarker panels. In this way, we had the chance to consider four biomarker panels with a high classification power and introduce the best one, as our minimal biomarker panel.28. So, we decided to choose a small set of most predictive biomarker signatures from SpeBDs to be introduced as COVID-19 potential Specific Blood Biomarker Signatures (SpeBBSs) and from DifBDs to be introduced as COVID-19 versus influenza Differential Blood Biomarker Signatures (DifBBSs). In order to do that, we applied a machine learning method (feature selection) using the Optimize Selection (forward selection type) operator implemented in Rapid Miner. The Forward Selection is a kind of wrapper feature selection approach. Here, we employed four classifiers  to supervise the wrapper method and extract the best combination of biomarkers from the feature selection dataset.A biomarker panel containing a less number of genes would be more practical to test in a clinical assayThe Forward Selection strategy initially uses only one attribute . Additional attributes are added until there is no more performance gain by adding an attribute.29. The Optimize Selection (Brute Force) operator examines all possible combinations of the attribute sets to select the most relevant attribute. This method is not applicable in the case of high-dimensional data due to its comprehensive examination30. The evolutionary algorithm selects the most relevant attributes of the dataset using evolutionary algorithms, e.g. genetic algorithm (GA). Backward Elimination starts with all features and it removes the worst feature in each step30. We tried using Optimize Selection (Evolutionary) and Optimize Selection (Backward Elimination) operators of Rapid Miner but these algorithms represented lower performances with the low number of features compared to the Forward Selection strategy. The purpose of feature selection in this study is to select a small set of biomarker signatures because such a panel would be more clinically applicable. We, therefore, chose to use Optimize Selection (Forward Selection) operator that has a higher performance in selecting a small set of biomarker signatures.Rapid Miner provides several other methods for feature selection including Brute Force, Evolutionary algorithm, Backward Elimination, and many other methods31, which included peripheral blood samples of healthy people and COVID-19 infected patients. Table The count values of SpeBDs were extracted from dataset GSE166190 and Bibert et al.’s dataset-AThe rlog function of the package DESeq2 was used to convert the raw counts to normalized logarithmic counts. The dataset was then transposed (samples in rows and SpeBDs genes in columns), and after conversion of disease status to binominal  input dataset for machine learning was prepared. After that, the two-step machine learning procedure was used to narrow down the SpeBDs for obtaining SpeBBSs ) and validating the SpeBBSs ). In each phase, the five indicators  were calculated for the feature selections and models constructed by the four algorithms.31, which included peripheral blood samples of Influenza and COVID-19 infected patients. The sample size and platform properties of these datasets are listed in Table The count values of DifBDs were extracted from dataset GSE161731-B and Bibert et al.’s dataset BThe ten-fold cross-validation strategy was employed to evaluate the performance of constructed models in this study. In ten-fold cross-validation, the input (samples) is divided into ten equal parts. One of the ten parts is retained as the test data set. The other parts are used as inputs of the training subprocess. Cross-validation is repeated ten times and every time one of the subsets plays the role of the test dataset. The ten results are then averaged to obtain a single result.The performance of classification was obtained in terms of four common measurements. These measurements were Accuracy (ACC), Sensitivity (Sen), Specificity (Spe), the Mathews correlation coefficient (MCC), and area under the curve (AUC). The first four were calculated using true-positive (TP), true-negative (TN), false-positive (FP), and false-negative (FN) indicators by the formula. And AUC was calculated by plotting a ROC curve.25. Also, we used AUC, which is a standard parameter and a threshold-independent measure. AUC is the area under the ROC curve generated by plotting sensitivity or true positive rate against false positive rate.When datasets are imbalanced in evaluating binary classification problems, MCC gives more information than other measures like accuracy because it considers the balance ratios of the four measures . The accuracy score can be misleading since it does not fully consider the size of the four classes of measurements in its final calculation. However, we provided this indicator as the most intuitive evaluation metric. The MCC value is between − 1 and 1. 1 is MCC of a model with the best performance. 0 is like a random prediction, and − 1 indicates a complete discrepancy between reality and predictionThe following parameters were set for the four classifiers of this study:k-NN: K: 5; Weighted vote: true; Measure types: MixedMeasures; Mixed measure: MixedEucideanDistance. Random Forest: Number of trees: 100; Criterion: gain_ratio; Maximal depth: 10; Voting strategy: confidence vote; Guess subset ratio: true. SVM: Kernel type: Dot; C: 0.00; Convergence epsilon: 0.001; Lpos: 1.0; L neg: 1.0; epsilon: 0.0; Epsilon plus: 0.0; epsilon minus: 0.0. Naïve Bayes : Laplace correlation parameter was set to true.The DEA between COVID-19 and Healthy PB samples of dataset GSE161731-A , duplicated DEGs were removed, and 108 unique SpeBDs were obtained Fig. . A complIn order to obtain DEGs of Influenza H1N1, the four related datasets including GSE111368-A, GSE90732, GSE68310-A, and GSE61821-A were integrated. DEA resulted in 309 upregulated and 208 downregulated, a total of 517 DEGs. These DEGs were enriched in 79 significant pathways Tables  and S11.To obtain DEGs of Influenza H3N2, three datasets including GSE61754, GSE29385, and GSE61821-B were integrated. The results of DEA were 1139 DEGs including 854 upregulated and 285 downregulated genes. The DEGs were enriched in 11 significant pathways Tables  and S13.Also, the two datasets of Influenza B (GSE111368-B and GSE68310-B) were integrated, and the DEA resulted in 976 DEGs including 512 upregulated and 464 downregulated genes. The pathway enrichment analysis for these DEGs resulted in 186 significant pathways Tables  and S15.Finally, a Venn diagram of significantly enriched pathways of influenza H1N1, H3N2, B, and SpeBDs was plotted Fig. A. EightyIn order to select the best subset of SpeBDs to be introduced as SpeBBSs, a feature selection method was applied using an external dataset containing SpeBDs (GSE166190). Then, these biomarker signatures were validated on another external dataset . All the four classifiers used for evaluating the performance of the feature selection method indicated high robustness levels in terms of AUC and ACC (ACC higher than 92.86% and AUC higher than 86.10% on the feature selection dataset). Also the models based on these algorithms and the SpeBBSs had ACCs higher than 90.77% and AUCs higher than 96.30% on the validation dataset. Feature selection using Random Forest provided the highest ACCs and AUCs  . Then, these biomarker signatures were validated on another external dataset . The forward selection method using all four classifiers had ACCs higher than 97.87% and AUCs higher than 95.00% on the feature selection dataset. Models built based on them and the corresponding DifBBSs, represented higher than 82.4 ACCs and higher than 83.60% AUCs on the validation dataset  are indeed needed to get specific biomarkers for diseases, this strategy can help to find the potential specific blood biomarkers before comparing the DEGs of our desired disease against the rest of the diseases one by one. SpeBDs were extracted from the overlapping pathways between PB and respiratory system-related samples  of Covid-19 patients. The extracted 108 SpeBDs enriched 152 significant pathways that, as we expected, are involved in multiple pathways in the immune system, such as classical antibody-mediated complement activation, FCGR activation, creation of C4 and C2 activators, initial triggering of complement, role of phospholipids in phagocytosis, complement cascade, regulation of actin dynamics for phagocytic cup formation, immune System, immunoregulatory interactions between a Lymphoid and a non-Lymphoid cell, FCERI mediated NF-kB activation, viral mRNA Translation, FCERI mediated Ca + 2 mobilization33.Gene expression profiles of the disease-involved cells are not practical in the diagnosis of diseases. Rather, such profiles might be valuable for selection of limited number of potential protein biomarkers which can be detected via common techniques in biofluid samples. From both basic and clinical perspectives, comprehending the associations between blood biomarkers and the pathogenic states and processes in the tissues affected by the disease could be a great help in selecting the right molecule as potential biomarker. Therefore, in this study, we considered the overlapping pathways between peripheral blood and the central involved body system in COVID-19 in order to identify the disease’s novel and potential specific blood biomarkers34. Upregulated IGKC and IGLV3-16 expression may be involved in the differentiation of B lymphocytes into immunoglobulins-secreting plasma cells, which could play an important role in the pulmonary immune response35. SRP9 is a component of the signal recognition particle (SRP) complex, involved in targeting secretory proteins to the rough endoplasmic reticulum membrane35. The SRP proteins also have a role in the virus-host responses. Based on an experiment, the 7SL RNA component of the SRP interacts with SARS-CoV-2, and upon binding, the viral proteins disrupt SRPs function, thus inhibiting protein trafficking to the cell membrane36. Moreover, it was shown that the uncleaved SRP9 could increase the translation elongation arrest and allows translocation, including the insertion of transmembrane domains . This process can finally lead to frameshifts in the translation process37.In the next step, a machine learning method (feature selection) was utilized to narrow down the number of SpeBDs and find the most predictive combination of them to select SpeBBSs. The five indicators  were calculated to measure the power of machine learning models constructed by SpeBBSs. Consequently, feature selection using Random Forest selected IGKC, IGLV3-16, and SRP9 as SpeBBSs with the highest classification power. And the constructed model based on this algorithm and SpeBBSs also validated this biomarker panel on an external dataset. Interestingly, the involvement of these biomarker proteins was previously shown by some studies. Immunoglobulin kappa constant, IGKC, encodes the constant domain of kappa-type light chains for antibodies and Immunoglobulin lambda variable 3-16, IGLV3-16, encodes the variable domain of lambda-type light chains of antibodies. Immunologically, plasma cells are responsible for synthesizing antibodies and have been identified as possibly producing virus-neutralizing antibodies in COVID-19In the next part, another pathway-based strategy was applied to obtain DifBDs. 87 DifBDs were extracted from the 83 pathways enriched by SpeBDs but not by Influenza H1N1, H3N2, and B DEGs. The most important of these pathways involves classical antibody-mediated complement activation, FCGR activation, activators, initial triggering of complement, FCERI mediated NF-kB activation, binding and Uptake of Ligands by Scavenger, complement cascade, regulation of actin dynamics for phagocytic cup formation, role of phospholipids in phagocytosis and mobilization. It can be seen that a number of non-specific pathways have been removed from the previous 152 pathways.38. There is a significant interaction between the native β1 integrins expressed on human and mouse pulmonary epithelial cells and the S-protein of SARS-CoV-240. The critical role of β1 integrins in mediating cellular adhesive interaction with the SARS-CoV-2 S-protein have recently shown in studies39. As FMNL2 involves in the regulation of β1-integrin traffic and function41, it is possible that as COVID-19 progress, FMNL2 regulation shifts from cell-to-cell adhesion to cell-to-substitute adhesion.Then, DifBBSs were selected from 87 DifBDs using a feature selection approach. The five indicators of ACC, AUC, MCC, Sen and Spe were calculated to measure the power of machine learning methods and models constructed by DifBBSs. Accordingly, the feature selection by the best classifier (the Naive Bayes) selected FMNL2, IGHV3-23, IGLV2-11, and RPL31 as DifBBSs. These DifBBSs along with the Naive Bayes were validated on an external dataset as a biomarker panel with the highest performance. Formin-like protein 2, FMNL2, is a formin-related protein from a family of large proteins with multidomain that play an essential role in controlling a cytoskeletal organization44. RPL31  is a member of ribosomal proteins (RPs). One direct evidence of ribosomal heterogeneity comes from ribosomopathy, caused by defective RPs and/or rRNAs. In a study, the putative role of ribosomal heterogeneity in COVID-19 susceptibility and severity is investigated as an important role45. Furthermore, recent studies showed RPL31 as a diagnostic biomarker for this infection8.IGHV3-23 (Immunoglobulin Heavy Variable 3-23) and IGLV2-11 (Immunoglobulin Lambda Variable 2-11) belong to a cluster of genes in the immunoglobulin (Ig) structure. During acute phase infection in COVID-19, these two variable chains are parts of top frequent paired heavy and light chain clonotypes that are identified in the repertoire of more general clonotypesConducting the pathway analyses based on a manually curated aggregate of multiple data sources can be the limitation of the present work. On the other hand, the reliability of the findings is maintained by a promise with known mechanisms and between the expression profiling data from different datasets.In summary, to find potential specific biomarkers for diagnosis of COVID-19, we focused on disease pathways, which include multiple pathways that can vary between different disease-related compartments. Consequently, more works that simultaneously analyze multiple mechanisms in peripheral blood and inflamed tissues are required. By the way, our findings shed a light on some pathways and molecules which can be valuable candidates for more investigations. Moreover, investigating differential biological pathways in similar diseases can help us identify differential diagnostic biomarkers for diseases. The present study identified several candidate biomarkers for specific detection of COVID-19 and differential diagnosis compared to influenza strains in blood. Further practical studies are necessary to validate these combinatorial biomarkers.Supplementary Information.


This cohort study assesses the association of sociodemographic differences with quality of life in deaf and hard-of-hearing children and adolescents in the US. Therefore, we sought to assess the association of sociodemographic differences with QOL in DHH children.Hearing loss (HL) is the most common congenital sensory disorder, with 1 in 500 children born deaf or hard-of-hearing (DHH) in the US every year.STROBE) reporting guidelines were followed. The eAppendix in We conducted a retrospective cohort study of patients with permanent HL seen at our tertiary care center from 2014 to 2022. Patients aged 7 to 12 years received the 26-question HEAR-QL Measurement for Children survey, and patients aged 13 to 18 years received the 28-question HEAR-QL Measurement for Adolescents survey. Higher HEAR-QL scores equate to higher hearing-related QOL. Total and subdomain scores were assessed as outcomes. We performed descriptive statistics, as well as linear and multivariable regression. The Strengthening the Reporting of Observational Studies in Epidemiology  were of a race other than White, 124 (42%) identified as Hispanic, 110 (37%) had parents whose primary language was not English, and 206 (69%) were publicly insured. The mean (SD) overall area deprivation index (ADI) ranking was 3.92 (3.1), signifying that 60.8% of Census block groups in California are less socioeconomically disadvantaged than our study population.A total of 583 HEAR-QL surveys were completed by pediatric patients with HL. Of those, 299 patients met inclusion criteria and had complete data for analysis. Sociodemographic factors in For univariable analyses , gender,ADI ranking was negatively associated with QOL on multivariable analysis . For theThe findings of this cohort study suggest that race and ethnicity and neighborhood disadvantage are associated with hearing-related QOL in DHH children. The neighborhood association was seen most broadly in children older than 13 years. Limitations include response bias and inability to know the underlying modifiable factors that neighborhood vulnerability and what non-Hispanic White and Asian race and ethnicity are proxies for in their associations with QOL. Future studies should elucidate these modifiable factors to enable multidisciplinary health care teams to provide more tailored HL care and improve QOL in DHH children.


Targeted therapy and chemotherapy are the mainstays of treatment to improve the survival of patients with metastatic colorectal cancer (mCRC). When RAS and BRAF genes are normal, a molecular target treatment with an anti-EGFR antagonist is prescribed. Anti-EGFR antagonists induce skin responses in 50–70% of patients. There is an ongoing debate about whether the severe skin reactions brought on by anti-EGFR antagonists are associated with overall survival (OS) and progression-free survival (PFS). mCRC patients who received anti-EGFR therapy between October 2017 and October 2018 were retrospectively evaluated. Treatment with an anti-EGFR medication in the first-line setting was significantly associated with OS and PFS. In grades 1 and 2, there was no difference in the incidence of acne between males and females, although in grades 3 and 4, males were at a higher risk than females. In this study, skin toxicity did not predict the effectiveness of the anti-EGFR medication.p < 0.001) and PFS (p < 0.001). There was no significant difference in the incidence of acne between males and females in grades 1 and 2, while males have a greater risk in grades 3 and 4 than females . Skin toxicity was not a predictor of anti-EGFR treatment response in this investigation.The primary treatment for metastatic colorectal cancer (mCRC) consists of targeted therapy and chemotherapy to improve survival. A molecular target drug with an anti-epidermal growth factor receptor (EGFR) antagonist is recommended when the RAS and BRAF genes are normal. About 50–70% of patients using anti-EGFR antagonists will experience skin reactions. Some studies have shown that severe skin reactions caused by anti-EGFR antagonists may be linked to overall survival (OS) and progression-free survival (PFS), but the results are still uncertain. These data of mCRC patients who underwent anti-EGFR therapy between October 2017 and October 2018 were analyzed retrospectively. A total of 111 patients were included in this study. The survival results showed that gender, age, body mass index, primary tumor site, and recurrence did not significantly affect OS and PFS. However, the first-line anti-EGFR inhibitor treatment was significantly associated with OS ( In 2020, 1.93 million new diagnoses of colorectal cancer (CRC) were given, making it the fourth most common cancer in the world, and the third leading cause of cancer-related deaths ,5,6. TheApproximately 50–70% of patients with metastatic CRC have a wild-type RAS gene, and anti-EGFR antagonists are recommended based on evidence in treating CRC worldwide . HoweverThe skin reactions not only cause psychological and symptomological distress because of the changes in appearance, but also affect patients’ quality of life . The manInformation on the relationship of OS and PFS with anti-EGFR antagonist-induced skin reactions is limited and contentious. In the present study, we aimed to investigate the association of OS and PFS with anti-EGFR antagonist-induced skin reactions according to age and gender.We conducted a retrospective analysis by reviewing the clinicopathological data and the follow-up outcomes of mCRC patients who received anti-EGFR therapy at the Colorectal and Oncology Division at the Chang Gung Memorial Hospital of Linkou Branch between October 2017 and October 2018 . The InsPatients who met the following criteria were enrolled: (a) histologically confirmed colorectal adenocarcinoma; (b) metastases (stage IV CRC) or recurrent CRC after curative resection determined by imaging or pathologically; (c) underwent chemotherapy combined with anti-EGFR therapy and received at least two to four treatment doses; and (d) physical performance was less than 60 on the Karnofsky Performance Status Scale (KPS) . PatientBaseline characteristics included age, gender, body mass index (BMI), KPS, primary tumor location, line of therapy, chemotherapy after surgery, and recurrence. Results of EGFR expression, including composite score (cite the reference) and skin reactions, were also collected. All patients receiving anti-EGFR therapy had regularly scheduled outpatient clinic visits or admissions and were assessed for treatment response by CT scans of the chest or abdomen every 3 months, or serum tumor markers. The treatment response assessment used the Response Evaluation Criteria in Solid Tumors ,21,22.The outcome measures for efficacy endpoints were PFS and OS in this study. PFS was defined as the interval from the first anti-EGFR treatment to the first progression, death, or final follow-up date. OS was defined as the interval from the first anti-EGFR treatment to the date of death or last follow-up.p-values were two-sided. The characteristics of baseline EGFR expression, results of the composite scores, and Anti-EGFR Skin Reactions were analyzed with categorical variables, presented as frequencies and proportions, and were compared using the 2 test. Continuous variables are expressed as means and standard deviations and were analyzed using the Student t-test and One-Way ANOVA test. Survival was analyzed using the Kaplan–Meier method. Cox proportional hazards regression analysis was used to calculate hazard ratios (HRs) with 95% confidence intervals.All analyses were conducted using SPSS Statistics v.26 . An α level of 0.05 was considered statistically significant, and all Between October 2017 and October 2018, 111 patients with mCRC underwent anti-EGFR treatment and were included in this study. The demographics and clinical characteristics are listed in In this study, EGFR expression was identified in 102 of 111 individuals. The results of the composite score, which is the product of the positive grade multiplied by the labeling-intensity score, are presented in p < 0.001) and PFS (p < 0.001).p-value of 0.001 (The average OS for patients who received anti-EGFR inhibitor therapy as the first-line was 38.9 (SD ± 2.644) months, and the average OS for patients who received anti-EGFR inhibitor therapy as the third-line was 19.8 (SD ± 2.333) months, with a of 0.001 a. First-of 0.001 b.There was no statistically significant difference between OS and PFS and the assessment of the EGFR composite score, skin responses, and paronychia .p < 0.001)  .The mean age of the 23 patients with grade 0 acne was 66.7 (SD ± 14.138); the number of patients with acne grades 1–2 was 72, with a mean age of 59.1 (SD ± 11.712); the number of patients with acne grades 3–4 was 16, with a mean age of 46.9 (SD ± 10.329). The results revealed that skin acne was more severe in individuals with lower mean ages and vice versa. p-value = 0.041)  . In part= 0.041) b.p = 0.818). Likewise, there was no statistically significant difference in the incidence rate of paronychia across genders  (Age had no significant impact on the severity of anti-EGFR inhibitor-induced paronychia (= 0.746) .p < 0.001).The receiver operating characteristic (ROC) curve elucidating the prediction of age and skin acne greater than grade 2 is shown for the entire cohort of patients. As displayed in This study demonstrated that skin toxicity is not a predictor of OS and PFS in patients with metastatic colorectal cancer treated with anti-EGFR inhibitors. Most patients treated with anti-EGFR inhibitors experienced only mild paronychia and skin reactions ranging from grades 0 to 2. Furthermore, regardless of gender, age, BMI, primary tumor site, recurrence, composite score, skin response, or paronychia, only the first-line treatment being an anti-EGFR inhibitor administered for mCRC had a significant influence on OS and PFS. The research examined the effects of gender, age, and acne severity in patients treated with anti-EGFR inhibitors and found that male patients and younger age groups were more likely to experience a higher incidence of severe acne due to the treatment. This result emphasizes the importance of considering individual patient characteristics when administering anti-EGFR inhibitors to reduce the risk of adverse skin reactions. Moreover, the study shows that male patients have a higher incidence of grades 3–4 acne than females. The evidence indicates that a higher incidence of skin rashes in males might be attributed to the effects of a lack of skincare, male hormones, and the secretion of anti-EGFR antibodies in sweat .Nonetheless, some other research has reached the opposite conclusion. It is not uncommon in a clinical setting for physicians to presume that a patient’s anti-EGFR medication-induced sensitive skin inflammatory response is a predictor of survival or effectiveness of disease treatment, or even that more severe skin reactions are more likely to survive than minor symptoms. A post hoc analysis from the CAVE mCRC study demonstrated that the occurrence of grade 2–3 skin toxicity is a strong predictor of patient outcome . The FIRThis study showed that patients younger than 70 and male had a higher incidence of severe cetuximab-induced skin reactions, which is comparable with the findings of previous studies ,28. PatiAlthough anti-EGFR inhibitors have a remarkable survival rate for mCRC patients with wild-type RAS, the associated skin toxicity and physical and mental image change negatively impact the quality of life ,31,32,33Based on the results mentioned above, we offer a few potential explanations for why the link between skin toxicity and PFS and OS in patients with mCRC receiving anti-EGFR inhibitors is still unclear. Firstly, the inconsistency could result from ethnic variances in skin characteristics and geography-related variations. Furthermore, the intensity of an anti-EFGR inhibitor-induced skin reaction may vary depending on the research study due to a variety of known and unknown confounders, including age, sex, and other factors. Additionally, the severity of skin toxicity might be lessened if pre-emptive skin care interventions differ based on the studies and the patient administering anti-EGFR therapies ,14.This study has several limitations. First, this retrospective study may introduce unavoidable biases. Second, the confounding factors influencing skin toxicity may not be properly adjusted, even with multivariable analysis. Third, the hot and humid climate on Taiwan’s subtropical island may affect skin toxicity during treatment. Fourth, personal skin-care habits should have an impact on the development of skin toxicity. Fifth, this study utilized a pre-emptive approach in initiating anti-EFGR inhibitors to instruct patients on how to take care of their skin, which could have altered the outcomes. Pre-emptive interventions include giving oral antibiotics, promoting proper skin care, emphasizing washing and moisturizing, sun protection, a balanced diet and stress management, enhancing self-confidence in one’s appearance, and supporting adherence to treatments.Despite the limitations of this study, it also presents crucial insights and valuable information that can be used to inform future research and clinical practice. One common misconception among clinicians is that severe skin acne in patients receiving anti-EGFR inhibitors indicates better treatment outcomes and improved survival rates, which have been widely circulated and followed by some practitioners. The current study effectively refutes this misconception and provides clear evidence that severe acne caused by anti-EGFR inhibitors is, in fact, a sign of adverse reactions to the medication. The study’s findings highlight the importance of monitoring patients for skin reactions during anti-EGFR inhibitor treatment and the need for individualized treatment plans that account for patient characteristics, such as age and gender. By dispelling this fallacy, the research contributes to the expanding body of the literature on the use of anti-EGFR inhibitors and highlights the significance of evidence-based medicine in clinical practice.In conclusion, despite the limitations of a single-institute retrospective study, our findings did not show skin toxicity as a predictor of response to anti-EGFR treatment. Most patients with skin reactions after the pre-emptive strategy who received an anti-EGFR inhibitor had milder grades of colorectal cancer in this study. Only the use of an anti-EGFR agent as a first-line treatment for metastatic colorectal cancer significantly influenced survival results. More robust methods with larger sample sizes may yield a more reliable outcome.


At six-month follow-up, 8 participants  had new-onset diabetes, corresponding to an incidence of 3 new cases of diabetes per 100 person-years. In conclusion, the incidence of elevated blood pressure and diabetes among Tanzanians with HIV is higher than what has been reported in high-income settings.Data describing the incidence of hypertension and diabetes among people with HIV in sub-Saharan Africa remain sparse. In this study, adults with HIV were enrolled from a public clinic in Moshi, Tanzania (September 2020—March 2021). At enrollment, a survey was administered to collect information on comorbidities and medication use. Each participant’s blood pressure and point-of-care glucose were measured. Baseline hypertension was defined by blood pressure ≥140/90 mmHg or self-reported hypertension at enrollment. Baseline diabetes was defined by self-reported diabetes or hyperglycemia (fasting glucose ≥126 mg/dl or random glucose ≥200 mg/dl) at enrollment. At 6-month follow-up, participants’ blood pressure and point-of-care glucose were again measured. Incident hypertension was defined by self-report of new hypertension diagnosis or blood pressure ≥140/90 mmHg at follow-up in a participant without baseline hypertension. Incident diabetes was defined as self-report of new diabetes diagnosis or measured hyperglycemia at follow-up in a participant without baseline diabetes. During the study period, 477 participants were enrolled, of whom 310 did not have baseline hypertension and 457 did not have baseline diabetes. At six-month follow-up, 51 participants  had new-onset hypertension, corresponding to an incidence of 33 new cases of hypertension per 100 person-years. Participants with incident hypertension at 6-month follow-up were more likely to have a history of alcohol use (90.2% vs. 73.7%, OR = 3.18, 95% CI:1.32–9.62,  Sub-Saharan Africa (SSA) remains the epicenter of the HIV epidemic, accounting for 70% of the global burden of HIV , 2. WithRecent studies from across SSA have examined the feasibility of leveraging established HIV care infrastructure to screen for and treat chronic NCD comorbidities among PLWH –11. HoweDespite the preliminary evidence that supports integrating NCD screening with HIV care , more daParticipants were enrolled from a government funded clinic at Majengo Care and Treatment Center (MCTC) in Moshi, Tanzania. MCTC provides approximately 1200 adults (approximately 900 women and 300 men) from Moshi and nearby rural areas with routine outpatient HIV care and ART. In northern Tanzania the prevalence of hypertension and diabetes among a random, community-based sample of adults was 28% and 6% in 2014, respectively , 20.Between September 2020 until March 2021, patients over 18 years of age presenting to MCTC for routine HIV care were approached by local research assistants and offered enrollment. Patients were approached consecutively for enrollment while they were waiting for care at MCTC. There were no exclusion criteria, however patients were not eligible for re-enrollment if they had already been enrolled in the study during a prior visit to MCTC.All participants provided informed consent. Trained study staff administered surveys to collect information on comorbid medical conditions, medication use, and lifestyle behaviors. Each participant’s blood pressure, height, weight and glucose were measured at enrollment. Height was measured manually with the patient supine; weight was measured manually with a scale. The GlucoPlus Blood Glucose Monitoring System  measured point-of-care glucose; the value was determined to be either fasting glucose if participants reported only having consumed water earlier in the day or random glucose if they reported having consumed any food or drink that day. The Beurer BM40 automatic blood pressure monitor  measured participant blood pressure according to international guidelines : particiParticipants followed-up with the research team during their routine 6-month visit to MCTC. At this time, research assistants measured participants’ blood pressure and point-of-care glucose again. All blood pressures at baseline and follow-up were measured on the same arm using the same sized cuff to maximize comparability.2; calculated from participants weight and height measured at enrollment. Overweight was defined as BMI ≥25 kg/m2 and ≤30 kg/m2. Patients with recent HIV RNA viral load < 200 copies/ml were considered to be virologically suppressed. Participants with any self-reported formal secondary school education were considered to have secondary education. Those with any self-reported myocardial infarction (MI) or stroke in a first-degree relative were considered to have a family history of MI or stroke. Participants also self-reported lifestyle behaviors, including tobacco use, alcohol use, fruit and vegetable consumption and sedentary lifestyle, which was defined by the WHO guidelines as <150 minutes of moderately vigorous exercise per week [Hypertension was defined in accordance with World Health Organization guidelines for hypertension management . Hyperteper week .Participants with baseline hypertension and baseline diabetes were excluded from incidence calculations. Incident hypertension was defined as measured systolic blood pressure ≥140mmHg at six-month follow-up, measured diastolic blood pressure ≥90mmHg at six-month follow-up, or self-report of new diagnosis of hypertension at six-month follow-up among participants without baseline hypertension. Incident diabetes was defined as random glucose ≥200 mg/dl at six-month follow-up, fasting glucose ≥126 mg/dl at six-month follow-up, or self-report of new diagnosis of diabetes at six-month follow-up among participants without baseline diabetes.The primary study outcome was the incidence of hypertension and diabetes among participants without baseline hypertension or diabetes (respectively) over a 6-month period. Patients lost to follow-up were excluded from the analysis. Ninety-five percent confidence intervals were constructed around point estimates for hypertension and diabetes incidence rates using the Poisson distribution. Univariate analyses were performed to compare characteristics among participants who developed hypertension and diabetes compared to participants who did not: Welch’s t-test was used for continuous variables, Pearson’s chi-squared was used for categorical variables, and the Fischer’s exact test was used when expected cell count < 5. A multivariate logistic regression, including variables with positive univariate association (p<0.10) with age and sex forced into the model, was performed to identify predictors of incident hypertension and diabetes among participants. The statistical analyses were performed using R suite. Sample size calculations for this study are reported elsewhere , 25, 26.This study received ethics approval from the Tanzania National Institute for Medical Research and the institutional review board at Duke Health. This study had minimal level of risk and written informed consent was provided by all participants prior to enrollment. Authors did not have access to any information that could have identified participants during or after the study.A total of 501 patients seeking routine care at MCTC were approached for study participation, of whom 500 (99.8%) consented and were enrolled in the study; of these, 477 participants completed six-month follow-up. At six-month follow-up, 51 participants  without baseline hypertension met the study definition for incident hypertension, including 49 participants with measured elevated blood pressure at follow-up, 1 participant who reported an interim diagnosis of hypertension, and 1 participant with both measured elevated blood pressure and a self-reported interim diagnosis of hypertension. This results in an incidence of 33 new cases  of hypertension per 100 person-years. Among the 51 participants with incident hypertension, the median (IQR) systolic blood pressure was 142 (138–149) mmHg and the median (IQR) diastolic blood pressure was 91 (84–96) mmHg.At six-month follow-up, 8 participants  without baseline diabetes or hyperglycemia at the initial visit developed incident diabetes, including 2 with measured hyperglycemia at follow-up, 3 with a self-reported interim diagnosis of diabetes, and 3 with both measured hyperglycemia and self-reported interim diagnosis of diabetes. This results in an incidence of 3 new cases  of diabetes mellitus per 100 person-years.p = 0.008) and were older  compared to participants without hypertension at the 6-month follow-up. No other participant characteristics were associated with incident hypertension, including HIV duration or ART duration.Univariate associations between participant characteristics at baseline and incident hypertension are presented in Univariate associations between participant characteristics and incident diabetes were not assessed since only eight participants developed incident diabetes during the study follow-up period.This study is among the first to assess the 6-month incidence of elevated blood pressure and diabetes among PWH in Tanzania. Of participants without baseline hypertension, nearly 1 in 6 PWH developed elevated blood pressure in 6 months. Older participants and those with a history of alcohol use were more likely to develop elevated blood pressure compared to participants without hypertension. We also observed a handful of cases of incident diabetes.In our cohort, we found the incidence of elevated blood pressure among PWH to be 33 (95% CI: 25–43) per 100 person-years, which is somewhat higher than what has been reported in other studies of hypertension incidence from SSA and high-income settings. Prior studies in Uganda, Ethiopia, South Africa, Ghana, and elsewhere in Tanzania reported the incidence of new hypertension among PWH to be between 5.4 to 32 per 100 person-years –30. In gIn addition to traditional risk factors, factors specific to HIV may also contribute to hypertension in PWH. For example, there appears to be a clear association between treated HIV and hypertension compared to untreated HIV , 34. YetIn our cohort, we found the incidence of diabetes among PWH to be 3 (95% CI: 1–6) per 100 person-years, similar to the results of prior studies in SSA: a recent systematic review found that incident diabetes among PWH in SSA to be between 0.4 and 6 per 100 person-years . In highThis study had several limitations. First, we only recruited participants from those engaged in routine HIV care in Tanzania, so our findings might not be generalizable to those not engaged in HIV care, including those with undiagnosed HIV and those with untreated HIV. Secondly, our study might be underpowered in detecting all associations between participant characteristics and incident hypertension. Additionally, the 6 month follow up time period may not have been long enough to fully understand the correlates associated with incident hypertension or diabetes. Thirdly, we defined incident hypertension by a single blood pressure measurement at follow-up; multiple blood pressure measurements on multiple occasions would have provided a more accurate measure of incident hypertension, as recommended by international guidelines. Follow-up blood pressures were measured on only one occasion to accommodate the study timeline and the existing six-month follow-up system at MCTC, and reliance on a single blood pressure measurement may have resulted in over-estimation of incident hypertension. However, a recent study in Kenya found that the sensitivity and specifity of a single blood pressure measurement >140/90 mmHg for detecting hypertension was 80% and 84%, respectively, when compared to ambulatory blood pressure monitoring . AssuminIn conclusion, we found a relatively high 6-month incidence of elevated blood pressure and diabetes among PWH in Tanzania. These findings call attention to the need for more robust NCD screening mechanisms among PWH in Tanzania and suggest that screening for hypertension and diabetes should be done frequently in this population. More research is needed to understand the mechanism of hypertension and diabetes risk among PWH in SSA and to develop interventions to target the burden of these NCDs and their associated risk factors in this population.S1 Checklist(DOCX)Click here for additional data file.S1 Data(XLSX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.


Background: Patients with advanced or recurrent endometrial cancer (EC) have limited treatment options following platinum-based chemotherapy and poor prognosis. The single-arm, Phase I GARNET trial (NCT02715284) previously reported dostarlimab efficacy in mismatch repair–deficient/microsatellite instability–high advanced or recurrent EC.Objectives: The objective of this study was to compare overall survival (OS) and describe time to treatment discontinuation (TTD) for dostarlimab (GARNET Cohort A1 safety population) with an equivalent real-world external control arm receiving non-anti-programmed death (PD)-1/PD-ligand (L)1/2 treatments .Methods: Propensity scores constructed from prognostic factors, identified by literature review and clinical experts, were used for inverse probability of treatment weighting (IPTW). Kaplan-Meier curves were constructed and OS/TTD was estimated (Cox regression model was used to estimate the OS-adjusted hazard ratio).Results: Dostarlimab was associated with a 52% lower risk of death vs real-world treatments . IPTW-adjusted median OS for dostarlimab (N=143) was not estimable  versus 13.1 months  for real-world treatments (N = 185). Median TTD was 11.7 months  for dostarlimab and 5.3 months  for the real-world cohort.Discussion: Consistent with previous analyses, patients treated with dostarlimab had significantly longer OS than patients in the US real-world cohort after adjusting for the lack of randomization using stabilized IPTW. Additionally, patients had a long TTD when treated with dostarlimab, suggesting a favorable tolerability profile.Conclusion: Patients with advanced or recurrent EC receiving dostarlimab in GARNET had significantly lower risk of death than those receiving real-world non-anti-PD-(L)1/2 treatments. Endometrial cancer (EC) is the fourth most common cancer among women in developed countries, and its incidence is steadily increasing.Approximately 25% of EC tumors are mismatch repair–deficient (dMMR)/microsatellite instability–high (MSI-H).The efficacy and safety of dostarlimab in patients with dMMR/MSI-H advanced or recurrent EC was assessed in the single-arm Phase I GARNET trial (NCT02715284).An external control arm study uses external data to create a comparator arm for clinical evaluation and applies statistical methods to evaluate the effectiveness of an intervention against the external control.The primary objective of this study was to compare overall survival (OS) of patients with dMMR/MSI-H advanced or recurrent EC treated with dostarlimab in the GARNET trial versus real-world patients with advanced or recurrent EC receiving current treatment paradigms. To achieve this, an external control arm of real-world patients was built using the Flatiron Health database, which contains real-world individual patient data from the US. In addition to OS, the time to treatment discontinuation (TTD) was assessed as an exploratory objective.GARNET is an ongoing multicenter, single-arm, open-label Phase I clinical trial of dostarlimab monotherapy in adult patients with advanced solid tumors. Cohort A1 of Part 2B of the trial included patients with dMMR/MSI-H advanced or recurrent EC who had progressed on or after no more than 2 prior lines of systemic chemotherapy (with ≥1 line of PBCT) and were then treated with dostarlimab. The Flatiron Health database (described in more detail in the following section) allows selection of real-world patients with inclusion/exclusion criteria matched as closely as possible to GARNET, creating an external real-world control arm and mimicking a 2-arm parallel design. Patient-level longitudinal data were available for both the GARNET trial cohort and the real-world cohort. The GARNET trial was performed in accordance with the principles of the Declaration of Helsinki, Good Clinical Practices, and all local laws.The analysis data set for the GARNET arm consisted of the safety population from Cohort A1 of GARNET. The first subject-first visit took place on May 8, 2017, and the data cut-off was November 1, 2021, at which point enrollment in Cohort A1 was completed. The GARNET analysis data set  included participants with dMMR/MSI-H advanced or recurrent EC who received any amount of dostarlimab, regardless of follow-up time at data cut-off (N = 153 patients). Patients in GARNET who had received anti-PD-(L)1/2 therapy as subsequent anticancer therapy following dostarlimab (n = 6) were excluded. Study locations for GARNET were the US, Canada, Denmark, Czech Republic, France, Italy, Poland, Spain, and the United Kingdom. The index date was defined as the day that patients received the first dose of dostarlimab.To construct an external control arm, this study used the nationwide Flatiron Health EHR-derived de-identified database. The Flatiron Health database is a longitudinal database, comprising de-identified patient-level structured and unstructured data, curated via technology-enabled abstraction.Inclusion and exclusion criteria applied to the Flatiron Health Endometrial Cancer Cohort were matched as closely as possible to inclusion and exclusion criteria for GARNET. Patients were required to be at least 18 years of age at the time of advanced or recurrent EC diagnosis and to have received no more than 2 oncologist-defined, rule-based lines of systemic chemotherapy for advanced or recurrent EC, including at least 1 line of PBCT. They must also have received an additional oncologist-defined, rule-based line of therapy (LOT) following PBCT, which was classed as the index therapy . They were also required to have an Eastern Cooperative Oncology Group (ECOG) performance status (PS) of 0-1 at index. Anti-PD-(L)1/2 treatments  have received approval for the treatment of dMMR/MSI-H solid tumors (including EC) from the US and the EU regulatory authorities in the last 5 years.The index date for the real-world cohort was defined as the date of initiation of the post-platinum regimen  and must have occurred between January 1, 2013, and August 31, 2018.The precise date was determined algorithmically; a patient’s potential eligible treatment pattern for up to 2 lines was identified, which could be (a) 1L PBCT only; (b) 1L and 2L PBCT; (c) 1L non-PBCT and 2L PBCT; or (d) 1L PBCT and 2L non-PBCT. For scenarios (a), (c), and (d), the index date was defined as the start date of the initiating LOT (index therapy) following the eligible treatment pattern. In scenario (b), where a patient had 2 PBCT LOTs, they could conceivably be assigned to scenario (a) or (b) at the point at which they were eligible for dostarlimab. These patients were randomly assigned to either (a) or (b) and the index date was determined accordingly. As patients enrolled in GARNET at the current point in their treatment journey and the real-world study was retrospective, this random assignment ensured that the patient journey on PBCT closely mirrored potential entry points into GARNET.The primary endpoint for comparison in this study was OS, defined as the interval between the index date and the date of death by any cause. Patients who did not die after the index date were censored at the latest date of follow-up (both cohorts) or data cut-off .The exploratory endpoint, TTD, was calculated as the duration from the start to the end of index therapy. Patients were censored if the patient died, was lost to follow-up, or was still on therapy. Patients in the real-world cohort were assumed to be either lost to follow-up or still on therapy if there was no evidence of confirmed structured activity during a period of 120 days after the last drug episode for the treatment of interest.A targeted literature review was conducted in May 2020 to identify prognostic variables associated with survival in EC. Following consultation with a panel of physicians on the prognostic variables derived from literature review, the following prioritized prognostic factors were identified based on clinical relevance: race, age, ECOG PS, histology, International Federation of Gynecology and Obstetrics (FIGO) stage, body mass index, and grade of disease at initial EC diagnosis. MMR/MSI status was also identified as a prioritized prognostic factor, but these data were not consistently available in the Flatiron cohort. As highlighted earlier, however, there is conflicting evidence on the prognostic value of MMR/MSI status.To control for the lack of randomization inherent to external control arm studies, treatment effectiveness was calculated using inverse probability of treatment weighting (IPTW).An alternative adjustment method, propensity score matching (PSM), was applied to the unadjusted data set and used as a sensitivity analysis for the stabilized IPTW–adjusted results. Matching was based on the greedy nearest neighborhood matching without replacement method, using the same propensity score model built for IPTW. A 1:2 matching  was used to account for the imbalance in sample size between the 2 cohorts.Following adjustment by PSM or stabilized IPTW, OS and TTD were compared between cohorts. Kaplan-Meier analysis was used to describe the distribution of OS and TTD by cohort. Weighted Kaplan-Meier curves were created following stabilized IPTW adjustment for the main analysis and after PSM adjustment for the sensitivity analysis. The adjusted hazard ratio (HR) was obtained for OS of dostarlimab compared with real-world treatments using a weighted Cox regression model following stabilized IPTW adjustment for the main analysis and following PSM adjustment for the sensitivity analysis. The proportional hazards assumption was checked graphically by means of log cumulative hazard plots for the covariate and by Schoenfeld residual plots. To assess if the proportional hazards assumption was met (non-constant hazards), an interaction between time and the study variable was also added to the Cox models as a time-dependent covariate. All data summaries and analyses were performed using SAS Version 9.4 or higher.Figure S1). Patient baseline characteristics for the GARNET trial cohort (N = 147) and the real-world cohort (N = 185) before stabilized IPTW are summarized in Table 1 (see Table S1 for detailed FIGO stage breakdown). Patients in the GARNET trial cohort were similarly aged to those in the real-world cohort , had a similar proportion of patients with advanced disease at diagnosis , and a similar proportion of patients with ECOG PS 1 . A slightly higher percentage of patients had endometrioid histology in the GARNET trial cohort compared with the real-world cohort . A larger proportion of patients in the GARNET trial cohort were white compared with the real-world cohort . Baseline and prognostic characteristics of the study populations after stabilized IPTW are also summarized in Table 1.After applying all additional inclusion and exclusion criteria to the Flatiron Health Endometrial Cancer Analytic Cohort, the study included 185 patients diagnosed with advanced or recurrent EC from January 1, 2013, to August 31, 2018 , pegylated liposomal doxorubicin monotherapy (10.3%), and bevacizumab (8.6%).A total of 62 different index regimens were received by patients in the real-world cohort. Regimens received by at least 1% of patients are summarized in Figure S2). When interaction between time and study was added to the Cox proportional hazards regression model, the interaction term was not statistically significant (P = .515), so it is reasonable to assume that the proportional hazards assumption was valid. This was supported by the Schoenfeld residual plot and log-cumulative hazard plot . Median OS after stabilized IPTW adjustment remained longer for patients treated with dostarlimab (N = 143) compared with patients receiving real-world non-anti-PD-(L)1/2 treatment regimens . Analysis of stabilized IPTW-adjusted survival rates indicated that there was a larger proportion of patients in the GARNET trial cohort surviving compared with the real-world cohort at 6, 12, 18, 24, 36, and 48 months (Table 3). Accordingly, patients treated with dostarlimab had a 52% lower hazard of death compared with patients receiving real-world non-anti-PD-(L)1/2 treatments  . The interaction term was not statistically significant after stabilized IPTW adjustment (P = .146). However, the P value for the global Schoenfeld test was <.1 and the log-cumulative hazard plot showed some crossing of curves at the beginning, indicating a potential violation of the proportional hazards assumption and suggesting that the hazard ratio for the study variable should be interpreted with caution .Prior to adjustment, median OS was not estimable (NE)  for patients in the GARNET trial cohort compared with 11.1 months in the real-world cohort . Accordingly, patients treated with dostarlimab had a 54% lower hazard of death compared with patients receiving real-world non-anti-PD-(L)1/2 treatments  . The interaction term was not statistically significant after PSM adjustment (P = .687), and both the Schoenfeld residual plot and log-cumulative hazard plot suggested that the proportional hazards assumption is likely to hold .The sensitivity analysis based on PSM gave similar results, with the median OS being longer for patients treated with dostarlimab compared with patients receiving real-world non-anti-PD-(L)1/2 treatment regimens  . TTD following adjustment with stabilized IPTW was also longer for patients treated with dostarlimab than for patients treated with real-world regimens . The sensitivity analysis using PSM gave similar results, with patients receiving dostarlimab having a longer PSM-adjusted TTD compared with patients receiving real-world treatment .Unadjusted TTD was longer for patients treated with dostarlimab compared with patients in the real-world cohort 1/2 treatments in patients with advanced or recurrent EC who had progressed after no more than 2 prior lines of systemic chemotherapy (with ≥1 line of PBCT) in the US. An external control arm was constructed using patient-level data from the Flatiron Health database, which is derived from EHRs throughout the US. Patient-level data allows the best adjustment for selection bias resulting from lack of randomization in external control arm real-world evidence studies.In this study, patients treated with dostarlimab had significantly longer OS than patients in the real-world cohort after adjusting for the lack of randomization by means of stabilized IPTW. This is consistent with previous analyses showing that dostarlimab-treated patients with advanced or recurrent EC had increased OS when compared with patients treated with the chemotherapy doxorubicinA sensitivity analysis was conducted for OS and TTD, using PSM as an alternative to stabilized IPTW. For both outcomes, PSM results supported those found using stabilized IPTW, with significantly longer OS and TTD seen in the GARNET trial cohort compared with the real-world cohort.This study has several strengths and limitations. Despite the availability of patient-level data for both cohorts, there is always the possibility that differences in data collection or other unmeasured confounding variables could contribute to observed differences in treatment effect between the GARNET trial cohort and the real-world cohort. Data from EHRs, such as those included in the Flatiron Health database, are used for billing and clinical practice management and are not primarily designed for research purposes. In particular, the Flatiron data set analyzed in this study did not contain progression or response variables assessed according to Response Evaluation Criteria in Solid Tumors (RECIST) criteria (as in GARNET). Consequently, the ability to evaluate progression or response-related outcomes is limited. Further, ECOG PS was unknown for some patients in the Flatiron database; to align with GARNET eligibility criteria (requiring an ECOG PS of 0 or 1), patients with unknown ECOG PS were excluded from the real-world cohort. However, as missing ECOG PS data are likely to be due to administrative errors, we would not expect this to bias composition of the real-world cohort or impact the study results. The LOT defined by Flatiron may also not reflect the exact treatment path. Comparability of certain variables, such as prior surgery and radiation, is limited by underreporting, so these were consequently not used in propensity score models for this analysis. There were also fewer non-white patients in the GARNET trial cohort compared with the external control arm; this may reflect the international nature of the GARNET trial in contrast to the US-based Flatiron Health database as well as a widespread issue with inclusion of racial and ethnic minorities in cancer clinical trials.While the time period considered for the start of index therapy in the real-world cohort  overlaps with the enrollment period for GARNET , they do not align completely as the period for the external control arm was expanded to generate a sufficient sample size for analysis. The majority of chemotherapies  currently used to treat advanced or recurrent EC were already available and/or recommended during the indexing period for the real-world cohort, with bevacizumab being the only new commonly-used therapy.Both stabilized IPTW and PSM models were adjusted for endometrioid versus non-endometrioid histology. More specific histological subtypes  within the non-endometrioid category could not be included in the statistical models as the sample size for each individual non-endometrioid histological subtype was insufficient and the reporting of subtypes differed across the cohorts. Discrepancies in the number of patients with different non-endometrioid histological subtypes between the GARNET trial cohort and the real-world cohort is a potential confounding variable for this analysis.Finally, this analysis only evaluated non-anti-PD-(L)1/2 treatments. Another anti-PD-1 antibody, pembrolizumab, was approved in the US for use in dMMR/MSI-H solid tumors (including EC) towards the end of the Flatiron enrollment period (May 2017).By comparing the GARNET trial cohort to a real-world external control arm from a multicenter oncology database in the US, this study found that patients with advanced or recurrent EC receiving dostarlimab had significantly better survival outcomes than patients receiving currently available non-anti-PD-(L)1/2 treatments. This finding still held true after adjusting for potential imbalances in baseline and prognostic factors and after sensitivity analyses using different statistical techniques. Overall, these findings suggest that dostarlimab monotherapy could bring additional clinical benefits to patients with advanced or recurrent EC who progress on or after PBCT. This could help inform treatment decisions in clinical practice and could also inform other healthcare decision makers when considering patient access to more efficacious treatments for patients with advanced or recurrent dMMR/MSI-H EC.DataAccess@flatiron.com to determine licensing terms. GSK makes available anonymized individual participant data and associated documents from interventional clinical studies that evaluate medicines, upon approval of proposals submitted to https://www.gsk-studyregister.com/en/. To access data for other types of GSK sponsored research, for study documents without patient-level data and for clinical studies not listed, please submit an enquiry via the website.The data that support the findings of this study have been originated by Flatiron Health, Inc. These de-identified data may be made available upon request and are subject to a license agreement with Flatiron Health; interested researchers should contact


Given the increasing incidence of early-onset Alzheimer disease, strategies for early diagnosis and swift treatment interventions are crucial for mitigating cognitive problems in women and middle-aged individuals who face a high risk of cognitive impairment.This study aimed to assess the effectiveness of individual cognitive training programs based on virtual reality (VR), a nonpharmacological intervention, on cognitive function and depression in middle-aged women at risk of cognitive impairment. It used VR technology, which has recently been recognized as a promising tool.We administered a VR-based cognitive training program for 30 minutes daily, twice a week, for 12 weeks (24 sessions). This study included middle-aged women residing in older adults’ welfare facilities in G-gu, Busan, from May to August 2021. A total of 60 participants were randomly divided into the training (n=30) and control (n=30) groups. Cognitive and depressive functions were assessed using the Korean versions of the Montreal Cognitive Assessment (K-MoCA), Digit Span Test (DST), Korean-Color Word Stroop Test (K-CWST), and Short Form of the Geriatric Depression Scale (SGDS-K) before the intervention. The training group underwent a VR-based cognitive training program, whereas the control group was educated to maintain regular daily activities. The same assessments were performed 12 weeks after treatment.P<.01), indicating substantial cognitive improvement. Similarly, the mean DST forward scores increased significantly from 6.97 (SD 1.10) to 7.90 , suggesting enhanced short-term auditory memory and attention. The mean DST backward scores also showed a significant improvement from 4.10 (SD 0.71) to 4.77 . Notably, the mean SGDS-K scores decreased significantly from 3.97 (SD 2.51) to 2.13 , indicating a reduction in depression within the training group.A comparison of the mean scores before and after K-MoCA in the training group revealed a significant increase from 24.87 (SD 2.62) to 27.50 (SD 1.70; The VR-based cognitive training programs significantly enhanced cognitive function and reduced depression in middle-aged women. Consequently, these programs are considered beneficial nonpharmacological cognitive training interventions for middle-aged women at high risk of cognitive impairment.UMIN Clinical Trials Registry UMIN000049752; https://tinyurl.com/z5du989z Cognitive aging begins in middle-aged women, leading to a decline in processing speed and memory, particularly in postmenopausal women. Additionally, the risk of estrogen loss and neurological decline following menopause is increased during this period, subsequently elevating the susceptibility of middle-aged women to Alzheimer disease compared with men ,2. AlzheRecent investigations into early-onset Alzheimer disease (EOAD) have revealed a lack of domestic research on nonpharmaceutical approaches to EOAD, underscoring the pressing need for further research owing to the insufficient verification of long-term effects . Given tNovel virtual reality (VR)–based technologies have emerged to enhance the efficacy of cognitive training. This technology immerses the user in virtual environments and transmits various visual, auditory, and sensory stimuli through a head-mounted display (HMD) . VR is aVR-based cognitive training harnesses multiple senses, uses engaging gaming formats, drives strong motivation, and improves cognitive function. These interventions have demonstrated favorable outcomes, particularly in memory, executive function, and various cognitive domains ,11. NoneConsequently, this study sought to ascertain the effectiveness of VR-based individual cognitive training programs, which fall under the umbrella of nonpharmacological interventions, in addressing cognitive function and depression among middle-aged women at high risk of cognitive impairment. This endeavor has leveraged VR technology, which has recently been recognized as a promising tool in this context.For 12 weeks, from May to August 2021, the objectives and methodology of this study were presented at 3 older adults’ welfare facilities situated in G-gu. The recruitment of participants involved the issuance of recruitment notices to middle-aged women 40-65 years old who expressed a voluntary willingness to participate and met specific selection criteria. The inclusion criteria included individuals who (1) visited organizations and centers, (2) had no physical disabilities, (3) were able to read and write for evaluation, (4) had the ability to understand the purpose of this test and voluntarily agreed by signing the consent form, or (5) had a Mini-Mental State Examination (MMSE) score of 24-28 points. Patients (1) who had difficulty wearing an HMD and operating controller equipment owing to severe or unstable physical conditions and who had medical conditions that may interfere with the completion of clinical trials, (2) with other degenerative brain diseases or mental illnesses such as depression, (3) with drug and alcohol addiction, and (4) with hearing and vision impairment that could not be evaluated effectively were excluded. After determining the appropriate number of participants, based on the effect size calculated in previous studies involving VR-based cognitive training, only 34 patients in each group exhibited significant improvements in cognitive function [This study used a pre-post experimental design with a randomized control group to assess the impact of VR-based individual cognitive training programs on cognitive function and depression in middle-aged women. Middle-aged women between the ages of 40 and 65 years who voluntarily expressed interest in participating and met the specified selection criteria were recruited. Participants were randomly allocated to either the experimental group (n=30) or the control group (n=30) using block randomization facilitated by SAS programming (SAS Institute), maintaining an equal 1:1 ratio. The VR cognitive training program was structured as a comprehensive cognitive function training regimen. The experimental group participated in a VR-based individual cognitive training program twice a week for 12 weeks, with each session lasting 30 minutes. The participants in the control group were instructed to continue their regular daily activities and cognitive training throughout the study . AssessmThe VR system was used to assess the participants’ cognitive function and enhance the areas of cognitive deficiency through a VR-based cognitive training program. The assessment encompassed persistent attention, selective attention, working memory, and depth perception, all of which were conducted in a VR environment  and 3.The visual cognitive assessment test was conducted in a VR environment and comprised 2 phases: memory and recall. During the memory phase, participants were instructed to freely explore a 3D space and memorize the types and locations of objects within that space. Subsequently, in the recall phase, the participants were presented with a scene in which some of the objects from the memory phase had disappeared, and their challenge was to identify and reposition the objects they had observed in their original locations.After a cognitive evaluation involving the adaptation of the Corsi block-tapping test to VR, participants were asked to recall a sequence of cubes displayed on the screen as they lit sequentially . This taAs part of the cognitive evaluation, 2 passages were presented to analyze participants’ reading patterns. Participants were free to read and interact with the passages.In the cognitive evaluation involving multiple balls of the same shape, several balls were illuminated with different colors. Subsequently, the balls were blinked and moved about, and the participants were tasked with tracking the balls that were illuminated in different colors without missing any. Participants then transitioned to sessions in both 2D and 3D settings to observe any differences between the 2 and select the illuminated balls while at rest.Participants were required to make selections based on the order of proximity to the balls dispersed in space or the order of proximity to the balls as perceived in terms of depth. The outcomes of these selections were examined.Building on the cognitive evaluation conducted immediately after the object location assessment, the participants were tasked with identifying items that were not present in the initial beach scene .The VR-based cognitive training program was administered for 30 minutes per individual over 24 sessions. It was specifically designed to prevent dementia and enhance cognitive function ,15. VR-bBusan Seagull Content: This program focuses on improving attention and executive functions. Participants were trained to spot crows flying amid seagulls.Firework Content: Geared toward enhancing working memory, this program tasked individuals with recalling a sequence in which fireworks exploded.Changed Love-House Content: Designed to enhance spatial memory, this program involved individuals in finding items within a changing room.Coupled Seagull Content: To improve visuospatial skills, this program challenged participants to simultaneously catch birds with both hands.Bird’s Poo Seagull Content: Targeting visuospatial function improvement, which required participants to catch crows with one hand while shielding themselves against flying bird excrement.The VR-based cognitive training program was personalized to match each participant’s cognitive function by adjusting the difficulty level accordingly .Cognitive function was assessed using the MMSE-2nd edition, adapted for use with older adults in Korea, based on the original MMSE developed by Folstein et al  and KangDepression was assessed using the SGDS-K, an adaptation designed to evaluate depression in older adults based on the Geriatric Depression Scale, originally developed by Yesavage et al  and Cho t test for continuous variables. A paired t test was used to assess changes in cognitive function and depression status in middle-aged women before and after the implementation of the VR-based individual cognitive training programs. Additionally, we conducted a repeated 2-way ANOVA to ascertain the average differences between the 2 groups. The significance level was set at P<.05 in all analyses.SPSS  was used for statistical analysis of all data. Descriptive statistics, including mean (SD), were used to summarize the dependent variables within each group. A frequency analysis was conducted using descriptive statistics to compare the general characteristics of the study participants. The general characteristics of the participants were analyzed using an independent This study was approved by the institutional review board of Inje University .The study consisted of female participants, with a mean age of 55.17 (SD 5.81) years in the training group and 55.53 (SD 5.66) years in the control group. In the training group (n=30), 4 (13%) participants had diabetes, whereas in the control group (n=30), 2 (7%) participants had diabetes. High blood pressure was observed in 5 (17%) participants in the training group and 6 (20%) participants in the control group. Education levels averaged 12.7 (SD 2.65) years in the training group and 12.63 (SD 2.87) years in the control group. The selection criteria, as measured by the MMSE scores, were mean 26.8 (SD 1.16) points in the training group and mean 26.1 (SD 1.56) points in the control group. Notably, there were no significant differences in general characteristics between the 2 groups . RegardiChanges in cognitive function and depression before and after the VR-based individual cognitive training programs are presented in This study investigated the impact of VR-based individual cognitive training programs on cognitive function and depressive symptoms in middle-aged women at risk of cognitive impairment. After the VR-based cognitive training programs conducted before and after this study, the scores in the training group showed a significant improvement compared with those in the control group on both the K-MoCA and DST assessments, confirming a noteworthy difference.Previous research suggests that VR-based cognitive training is effective in delaying or preventing dementia among middle-aged individuals at high risk of developing the condition. This efficacy can be attributed to its ability to strengthen the cognitive reserve in the brain and stimulate neuroplasticity ,25. MoreConventional rehabilitation training can become monotonous and uninspiring, potentially reducing the participants’ ability to concentrate on training. Conversely, game-based cognitive training, as implemented in this VR program, effectively bolsters concentration by making the training more engaging and enjoyable.In addition, the VR measurement system used for VR-based cognitive evaluations provides immediate visual feedback on cognitive function scores and areas of cognitive deficiency, thereby enhancing immersion and motivation within the VR environment. This domain-specific cognitive training intervention is believed to play a pivotal role in improving cognitive function.Visual and auditory attention are essential for performing cognitive tasks. VR-based cognitive training interventions enhance connectivity between the frontal and occipital brain regions by engaging in temporal and spatial functions, resulting in heightened realism, presence, and immersion . ConsequIn the SGDS-K test, conducted to evaluate depressive symptoms after the intervention, scores in the training group exhibited a significant reduction compared with those in the control group, indicating a substantial difference. Previous research has demonstrated that behavioral activation and physical activity can lead to a reduction in depressive symptoms .In this study, HMDs were used to induce immersion by aligning head movements in the direction of gaze. Furthermore, the continuous upper-limb movement facilitated by the controller expands the range of motion, contributing to increased physical activity. VR technology offers immediate feedback, fosters enjoyment, and piques interest, thereby enhancing the participants’ motivation for rehabilitation. Consequently, the competitive and cooperative dynamics observed among participants during gaming activities were effective in reducing depression as they promoted motivation.The VR-based cognitive training program, designed as an engaging gaming experience in a virtual environment, is expected to motivate participants by immersing them in an alternative reality. This approach encourages physical activity and behavior, potentially alleviating the symptoms of depression.This study has some limitations. First, it focused exclusively on women, and the sample size was relatively small, limiting the generalizability of the results. Moreover, individual variations in cognitive aging among middle-aged women do not account for all potential factors contributing to dementia risk. Conditions such as high blood pressure and diabetes can negatively affect various cognitive functions, including reaction time, processing speed, and working memory evaluation , and areThis study aimed to examine the impact of VR-based individual cognitive training programs on cognitive function and depression in middle-aged women to address the risk of cognitive impairment. The findings of this study confirmed the effectiveness of VR-based cognitive training programs in enhancing cognitive function and reducing depression in middle-aged women at risk of cognitive impairment. This nonpharmacological cognitive training program is considered beneficial for improving cognitive function and alleviating depression in this population. This offers a promising avenue for early prevention of cognitive impairment in middle-aged women facing such risks.