17 research outputs found

    Current status of treatment and disease burden of a cohort of hemophilia B in China

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    ObjectiveHemophilia B is a rare X-chromosome linked hereditary bleeding disorder. Patients require lifelong treatment and it is costly, but there is a lack of research in China on the treatment and burden for this group. Our aim was to review the actual treatment pattern of hemophilia B patients in China, and describe the financial burden and other disease burden from the patient’s perspective.MethodsUsing data collected by the Beijing Hemophilia Home Care Center, descriptive statistics were made on the sociodemographic characteristics and treatment of patients. The annual drug costs were calculated according to the actual factor dosage and price.ResultsDuring the study period, 29.9% of the patients only received on-demand treatment, while the rest of the patients received varying numbers of prophylaxis treatment. The total cost of clotting factors for 341 patients in one year was 16.0 million CNY (2.5million),with46990.8CNY(2.5 million), with 46990.8 CNY (7283.7) per patient. The drug cost of prophylaxis was significantly higher than that of on-demand treatment. The amount of prothrombin complex concentrates used by patients was the largest, more than 5 times of recombinant coagulation factor IX. Based on the average annual wage and average working time of Chinese employees in 2021, the average annual wage loss of HB patients reached 31544.2 CNY ($4889.4). The results of the questionnaire showed that 77.1% and 65.3% of patients had chronic pain and acute pain of different frequencies.ConclusionThe level of prophylaxis for Chinese patients is low; safer and more effective recombinant drugs are not widely available. Patients also face a high burden of drug costs, as well as indirect costs that cannot be underestimated. Therefore, continued efforts are needed to improve the quality of life of patients by reducing their financial burden and promote standardized treatment

    Mapping the Peds QLTM 4.0 onto CHU-9D: a cross-sectional study in functional dyspepsia population from China

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    ObjectiveThe study aims to develop a mapping algorithm from the Pediatric Quality of Life Inventory™ 4. 0 (Peds QL 4.0) onto Child Health Utility 9D (CHU-9D) based on the cross-sectional data of functional dyspepsia (FD) children and adolescents in China.MethodsA sample of 2,152 patients with FD completed both the CHU-9D and Peds QL 4.0 instruments. A total of six regression models were used to develop the mapping algorithm, including ordinary least squares regression (OLS), the generalized linear regression model (GLM), MM-estimator model (MM), Tobit regression (Tobit) and Beta regression (Beta) for direct mapping, and multinomial logistic regression (MLOGIT) for response mapping. Peds QL 4.0 total score, Peds QL 4.0 dimension scores, Peds QL 4.0 item scores, gender, and age were used as independent variables according to the Spearman correlation coefficient. The ranking of indicators, including the mean absolute error (MAE), root mean squared error (RMSE), adjusted R2, and consistent correlation coefficient (CCC), was used to assess the predictive ability of the models.ResultsThe Tobit model with selected Peds QL 4.0 item scores, gender and age as the independent variable predicted the most accurate. The best-performing models for other possible combinations of variables were also shown.ConclusionThe mapping algorithm helps to transform Peds QL 4.0 data into health utility value. It is valuable for conducting health technology evaluations within clinical studies that have only collected Peds QL 4.0 data

    Association of pharmaceutical care barriers and role ambiguity and role conflict of clinical pharmacists

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    Objectives: This study aimed to understand current status of pharmaceutical care barriers and explore the impact of them on the role ambiguity and role conflict of clinical pharmacists in secondary and tertiary hospitals in mainland China.Methods: The Chinese version of Role Conflict and Role Ambiguity Scale was used to measure clinical pharmacists’ role ambiguity and role conflict. A questionnaire for clinical pharmacists’ pharmaceutical care barriers was established to determine whether clinical pharmacists encounter barriers. Multiple linear regression model was used to analyze the influence of various pharmaceutical care barriers on the role ambiguity and role conflict of clinical pharmacists.Results: 1,300 clinical pharmacists from 31 provinces were eventually included. The results revealed that commonly perceived barriers to pharmaceutical care by clinical pharmacists include the lack of financial compensation and dedicated time for pharmaceutical care. Barriers such as clinical pharmacists’ unawareness of the importance of pharmaceutical care increase the degree of clinical pharmacists’ role conflict. And the lack of financial compensation for pharmaceutical care decreases the degree of role ambiguity, while barriers such as the lack of dedicated time for pharmaceutical care, the failure to standardize the service procedures and contents of related documents in healthcare institutions increase the degree of role ambiguity.Conclusion: Increased focus on enhancing financial compensation, responsibility cognition, education and training, and greater consideration of institutional factors could help clinical pharmacists better manage their work environments and provide higher-quality pharmaceutical care

    Table_1_Mapping health assessment questionnaire disability index onto EQ-5D-5L in China.DOCX

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    ObjectiveThis research aimed to develop the more accurate mapping algorithms from health assessment questionnaire disability index (HAQ-DI) onto EQ-5D-5L based on Chinese Rheumatoid Arthritis patients.MethodsThe cross-sectional data of Chinese RA patients from 8 tertiary hospitals across four provincial capitals was used for constructing the mapping algorithms. Direct mapping using Ordinary least squares regression (OLS), the general linear regression model (GLM), MM-estimator model (MM), Tobit regression model (Tobit), Beta regression model (Beta) and the adjusted limited dependent variable mixture model (ALDVMM) and response mapping using Multivariate Ordered Probit regression model (MV-Probit) were carried out. HAQ-DI score, age, gender, BMI, DAS28-ESR and PtAAP were included as the explanatory variables. The bootstrap was used for validation of mapping algorithms. The average ranking of mean absolute error (MAE), root mean square error (RMSE), adjusted R2 (adjR2) and concordance correlation coefficient (CCC) were used to assess the predictive ability of the mapping algorithms.ResultsAccording to the average ranking of MAE, RMSE, adjR2, and CCC, the mapping algorithm based on Beta performed the best. The mapping algorithm would perform better as the number of variables increasing.ConclusionThe mapping algorithms provided in this research can help researchers to obtain the health utility values more accurately. Researchers can choose the mapping algorithms under different combinations of variables based on the actual data.</p

    Identification of Heat Responsive Genes in <i>Brassica napus</i> Siliques at the Seed-Filling Stage through Transcriptional Profiling

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    <div><p>High temperature stress results in yield loss and alterations to seed composition during seed filling in oilseed rape (<i>Brassica napus</i>). However, the mechanism underlying this heat response is poorly understood. In this study, global transcription profiles of 20 d-old siliques of <i>B. napus</i> were analyzed after heat stress using a Brassica 95k EST microarray. The up-regulated genes included many <i>HSF</i>/<i>HSP</i> transcripts and other heat-related marker genes, such as <i>ROF2</i>, <i>DREB2a</i>, <i>MBF1c</i> and <i>Hsa32</i>, reflecting the conservation of key heat resistance factors among plants. Other up-regulated genes were preferentially expressed in heat-stressed silique walls or seeds, including some transcription factors and potential developmental regulators. In contrast, down-regulated genes differed between the silique wall and seeds and were largely tied to the biological functions of each tissue, such as glucosinolate metabolism in the silique wall and flavonoid synthesis in seeds. Additionally, a large proportion (one-third) of these differentially expressed genes had unknown functions. Based on these gene expression profiles, <i>Arabidopsis</i> mutants for eight heat-induced <i>Brassica</i> homologous genes were treated with different heat stress methods, and thermotolerance varied with each mutation, heat stress regimen and plant development stage. At least two of the eight mutants exhibited sensitivity to the heat treatments, suggesting the importance of the respective genes in responding to heat stress. In summary, this study elucidated the molecular bases of the heat responses in siliques during later reproductive stages and provides valuable information and gene resources for the genetic improvement of heat tolerance in oilseed rape breeding.</p></div

    Differentially expressed genes with unknown functions in the heat-stressed SW and seed organs.

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    <p>(A) Venn diagram indicating the numbers of unknown genes conserved and not conserved with <i>Arabidopsis</i> that were detected in the SW or seeds. (B) Cellular components of 502 genes with unknown functions that were conserved with <i>Arabidopsis</i> based on GO analysis in TAIR (<a href="http://www.arabidopsis.org/" target="_blank">http://www.arabidopsis.org/</a>).</p

    List of genes (<i>Hsf</i> and <i>Hsp</i> genes excluded) exhibiting more than 10-fold changes in expression in both the SW and seeds (Group I).

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    a<p>Locus name in the genome of <i>A. thaliana.</i></p>b<p>Fold change (FC) was expressed as the ratio of normalized expression of heat treatment to control.</p

    Statistical analysis of functional classifications for differentially expressed genes with different patterns.

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    <p>A-F show the average fold-change and abundance in different functional categories of up-regulated genes in group I (A), group II (C) and group III (E) and the same parameters for the down-regulated genes in group I (B), group II (D) and group III (F). Dark-gray and light-gray bars represent the genes with unknown functions that were conserved (Bin 35a) and not conserved (Bin 35b), respectively, with <i>Arabidopsis</i>. Arrows in black indicate the important functional categories that had the most abundant genes (usually with large alterations); arrows in gray indicate the important functional categories that had less abundant genes but usually contained genes that had been dramatically altered or abundant moderately altered genes. The two large open boxes in A-F indicate the common categories in corresponding samples.</p

    qRT-PCR validation of differential expression.

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    <p>Relative expression levels of 18 up-regulated genes were detected in the SW and seeds sampled at 24 h (A and B) and 48 h (C and D) after heat treatment. 10 down-regulated genes, of which 5 involving glucosinolate metabolism and another 5 associated with flavonoid synthesis were analyzed in the SW (E) and seeds (F) at 24 h after treatment respectively. Two genes may responsible for lipid synthesis were also detected in seeds (G). (H) Correlation of the gene expression ratios obtained from qRT-PCR and microarray data. The qRT-PCR log<sub>2</sub> value of the expression ratio (y-axis) has been plotted against the value from the microarray (x-axis). The results of all the tested genes were listed in detail in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0101914#pone.0101914.s012" target="_blank">Table S9</a>. Data were collected from three biological replicates and three technical replicates for each sample.</p

    Expression characteristics of heat-stressed siliques.

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    <p>Correlation analysis of the SW (A) and seed (B) transcriptomes after 24 h and 48 h recovery times. (C) Venn diagrams showing the intersection of differentially expressed transcripts in the heat-stressed SW and seed. (D) Comparison of increased or decreased transcripts in different samples. Abbreviations: 24 U/48 U and 24 D/48 D indicate up-regulated and down-regulated genes after the 24 h/48 h recovery times either in the SW or seeds.</p
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