1.Development and Initial Validation of the Multi-Dimensional Attention Rating Scale in Highly Educated Adults.
Xin-Yang ZHANG ; Karen SPRUYT ; Jia-Yue SI ; Lin-Lin ZHANG ; Ting-Ting WU ; Yan-Nan LIU ; Di-Ga GAN ; Yu-Xin HU ; Si-Yu LIU ; Teng GAO ; Yi ZHONG ; Yao GE ; Zhe LI ; Zi-Yan LIN ; Yan-Ping BAO ; Xue-Qin WANG ; Yu-Feng WANG ; Lin LU
Chinese Medical Sciences Journal 2025;40(2):100-110
OBJECTIVES:
To report the development, validation, and findings of the Multi-dimensional Attention Rating Scale (MARS), a self-report tool crafted to evaluate six-dimension attention levels.
METHODS:
The MARS was developed based on Classical Test Theory (CTT). Totally 202 highly educated healthy adult participants were recruited for reliability and validity tests. Reliability was measured using Cronbach's alpha and test-retest reliability. Structural validity was explored using principal component analysis. Criterion validity was analyzed by correlating MARS scores with the Toronto Hospital Alertness Test (THAT), the Attentional Control Scale (ACS), and the Attention Network Test (ANT).
RESULTS:
The MARS comprises 12 items spanning six distinct dimensions of attention: focused attention, sustained attention, shifting attention, selective attention, divided attention, and response inhibition.As assessed by six experts, the content validation index (CVI) was 0.95, the Cronbach's alpha for the MARS was 0.78, and the test-retest reliability was 0.81. Four factors were identified (cumulative variance contribution rate 68.79%). The total score of MARS was correlated positively with THAT (r = 0.60, P < 0.01) and ACS (r = 0.78, P < 0.01) and negatively with ANT's reaction time for alerting (r = -0.31, P = 0.049).
CONCLUSIONS
The MARS can reliably and validly assess six-dimension attention levels in real-world settings and is expected to be a new tool for assessing multi-dimensional attention impairments in different mental disorders.
Humans
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Adult
;
Male
;
Attention/physiology*
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Female
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Middle Aged
;
Reproducibility of Results
;
Young Adult
;
Psychometrics
2.Construction and validation of an in-hospital mortality risk prediction model for patients receiving VA-ECMO:a retrospective multi-center case-control study
Yue GE ; Jianwei LI ; Hongkai LIANG ; Liusheng HOU ; Liuer ZUO ; Zhen CHEN ; Jianhai LU ; Xin ZHAO ; Jingyi LIANG ; Lan PENG ; Jingna BAO ; Jiaxin DUAN ; Li LIU ; Keqing MAO ; Zhenhua ZENG ; Hongbin HU ; Zhongqing CHEN
Journal of Southern Medical University 2024;44(3):491-498
Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.
3.Construction and validation of an in-hospital mortality risk prediction model for patients receiving VA-ECMO:a retrospective multi-center case-control study
Yue GE ; Jianwei LI ; Hongkai LIANG ; Liusheng HOU ; Liuer ZUO ; Zhen CHEN ; Jianhai LU ; Xin ZHAO ; Jingyi LIANG ; Lan PENG ; Jingna BAO ; Jiaxin DUAN ; Li LIU ; Keqing MAO ; Zhenhua ZENG ; Hongbin HU ; Zhongqing CHEN
Journal of Southern Medical University 2024;44(3):491-498
Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.
4.The underlying logic, innovative thinking and research paradigm of antiviral medicinal chemistry
Shuo WANG ; Bao-hu LI ; Shu-jing XU ; Yang ZHOU ; Jin-fei YANG ; Xin-yong LIU ; Peng ZHAN
Acta Pharmaceutica Sinica 2024;59(7):1916-1931
Antiviral drug research and development is an important research direction in the current and future biomedical field. The research and development of antiviral drugs not only requires the application of new strategies and new technologies, but also requires the complementary advantages and close cooperation of project teams. Based on the latest progress in this field and the author's drug research practice, this paper summarizes the underlying logic, innovative thinking and research paradigm of antiviral medicinal chemistry.
5.Targeting the chromatin structural changes of antitumor immunity
Li NIAN-NIAN ; Lun DENG-XING ; Gong NINGNING ; Meng GANG ; Du XIN-YING ; Wang HE ; Bao XIANGXIANG ; Li XIN-YANG ; Song JI-WU ; Hu KEWEI ; Li LALA ; Li SI-YING ; Liu WENBO ; Zhu WANPING ; Zhang YUNLONG ; Li JIKAI ; Yao TING ; Mou LEMING ; Han XIAOQING ; Hao FURONG ; Hu YONGCHENG ; Liu LIN ; Zhu HONGGUANG ; Wu YUYUN ; Liu BIN
Journal of Pharmaceutical Analysis 2024;14(4):460-482
Epigenomic imbalance drives abnormal transcriptional processes,promoting the onset and progression of cancer.Although defective gene regulation generally affects carcinogenesis and tumor suppression networks,tumor immunogenicity and immune cells involved in antitumor responses may also be affected by epigenomic changes,which may have significant implications for the development and application of epigenetic therapy,cancer immunotherapy,and their combinations.Herein,we focus on the impact of epigenetic regulation on tumor immune cell function and the role of key abnormal epigenetic processes,DNA methylation,histone post-translational modification,and chromatin structure in tumor immunogenicity,and introduce these epigenetic research methods.We emphasize the value of small-molecule inhibitors of epigenetic modulators in enhancing antitumor immune responses and discuss the challenges of developing treatment plans that combine epigenetic therapy and immuno-therapy through the complex interaction between cancer epigenetics and cancer immunology.
6.Risk factors and survival of EBV-infected aplastic anemia patients after haploid allogeneic hematopoietic stem cell transplantation
Xin-He ZHANG ; Jia FENG ; Zheng-Wei TAN ; Yue-Chao ZHAO ; Hui-Jin HU ; Jun-Fa CHEN ; Li-Qiang WU ; Qing-Hong YU ; Di-Jiong WU ; Bao-Dong YE ; Wen-Bin LIU
Chinese Journal of Infection Control 2024;23(10):1228-1235
Objective To analyze the risk factors and survival status of Epstein-Barr virus(EBV)infection in pa-tients with aplastic anemia(AA)after haploid allogeneic hematopoietic stem cell transplantation(Haplo-HSCT).Methods Clinical data of 78 AA patients who underwent Haplo-HSCT in the hematology department of a hospital from January 1,2019 to October 31,2022 were analyzed retrospectively.The occurrence and onset time of EBV viremia,EBV-related diseases(EBV diseases),and post-transplant lymphoproliferative disorders(PTLD)were ob-served,risk factors and survival status were analyzed.Results Among the 78 patients,38 were males and 40 were females,with a median age of 33(9-56)years old;53 patients experienced EBV reactivation,with a total inci-dence of 67.9%,and the median time for EBV reactivation was 33(13,416)days after transplantation.Among pa-tients with EBV reactivation,49 cases(62.8%)were simple EBV viremia,2 cases(2.6%)were possible EBV di-seases,and 2 cases(2.6%)were already confirmed EBV diseases(PTLD).Univariate analysis showed that age 1<40 years old at the time of transplantation,umbilical cord blood infusion,occurrence of acute graft-versus-host disease(aGVHD)after transplantation,and concurrent cytomegalovirus(CMV)infection were independent risk fac-tors for EBV reactivation in AA patients after Haplo-HSCT.Multivariate analysis showed that concurrent CMV in-fection was an independent risk factor for EBV reactivation in A A patients after Haplo-HSCT(P=0.048).Ritu-ximab intervention before stem cell reinfusion was a factor affecting the duration of EBV reactivation(P<0.05).The mortality of EBV viremia,EBV diseases,and PTLD alone were 8.2%,50.0%,and 100%,respectively.The 2-year overall survival rate of patients with and without EBV reactivation were 85.3%,and 90.7%,respectively,difference was not statistically significant(P=0.897).However,patients treated with rituximab had 2-year lower survival rate than those who did not use it,with a statistically significant difference(P=0.046).Conclusion EBV reactivation is one of the serious complications in AA patients after Haplo-HSCT,which affects the prognosis and survival of patients.
7.Influencing factors of viral RNA shedding time in patients with SARS-CoV-2 infection
Xin ZOU ; Ke XU ; Qigang DAI ; Jianguang FU ; Songning DING ; Yin WANG ; Shenjiao WANG ; Haodi HUANG ; Jianli HU ; Yang ZHOU ; Xiang HUO ; Qingxiang SHANG ; Changjun BAO
Chinese Journal of Experimental and Clinical Virology 2023;37(3):296-302
Objective:To understand the relationship between the RNA shedding time of SARS-CoV-2 infected persons and the single nucleotide mutation of the virus, the population of infected persons, underlying diseases and other factors, so as to provide more clues for the study of SARS-CoV-2 infection dynamics.Methods:The data of epidemiology, clinical manifestations, and underlying diseases of infected persons in a cluster epidemic of COVID-19 in Jiangsu province from July to September 2021 were collected. Nasopharyngeal swab samples of cases were collected, and the whole genome of the virus was sequenced by second-generation sequencing technology. The online analysis platform was used to judge the virus type and analyze the mutation site, and Cox proportional risk model was used to analyze the relationship between the RNA shedding time of SARS-CoV-2 and various research factors.Results:There were 350 persons who finally obtained the whole genome sequence of the virus in this COVID-19 outbreak, of which 60.3% were female, the median age was 49 years old (interquartile range, IQR: 37-65 years old)), and the median time of virus shedding was 33 days ( IQR, 26-44 days). The whole-genome sequencing analysis showed that compared with the Wuhan reference strain sequence, the infected persons’ sequence had 34~41 nucleotide mutation sites, belonging to VOC/Delta variant (B.1.617.2 evolutionary branch), and C346T, C1060T, T2803C, T7513C, A29681C were the main single nucleotide polymorphisms (SNPs) of this epidemic. Cox regression analysis showed that age, underlying disease, clinical classification, vaccination, SNP T2803C and T7513C had an impact on the RNA shedding time of SARS-CoV-2. The adjusted multivariate Cox regression result showed that age [ HR=0.73, 95% CI (0.55, 0.95)] and T7513C [ HR=0.37, 95% CI (0.18, 0.77)] were still the risk factors for the extension of SARS-CoV-2 RNA shedding time. Conclusions:This study analyzed the effects of the individual factors and viral single nucleotide variations on the time of viral RNA shedding. Those who were older, suffered from hypertension, had more severe clinical symptoms, were not vaccinated or incompletely vaccinated, and had T7513C mutation in the infected virus, had a risk of a long RNA shedding time of SARS-CoV-2, which should be given special attention and follow-up after rehabilitation.
9.Analysis on the secondary attack rates of SARS-CoV-2 Omicron variant and the associated factors.
Qing Xiang SHANG ; Ke XU ; Qi Gang DAI ; Hao Di HUANG ; Jian Li HU ; Xin ZOU ; Li Ling CHEN ; Ye WEI ; Hai Peng LI ; Qian ZHEN ; Wei CAI ; Yin WANG ; Chang jun BAO
Chinese Journal of Preventive Medicine 2023;57(10):1550-1557
Objective: To evaluate the secondary attack rates of the SARS-CoV-2 Omicron variant and the associated factors. Methods: A total of 328 primary cases and 40 146 close contacts of the SARS-CoV-2 Omicron variant routinely detected in local areas of Jiangsu Province from February to April 2022 were selected in this study, and those with positive nucleic acid test results during 7 days of centralized isolation medical observation were defined as secondary cases. The demographic information and clinical characteristics were collected, and the secondary attack rate (SAR) and the associated factors were analyzed by using a multivariate logistic regression model. Results: A total of 1 285 secondary cases of close contacts were reported from 328 primary cases, with a SAR of 3.2% (95%CI: 3.0%-3.4%). Among the 328 primary cases, males accounted for 61.9% (203 cases), with the median age (Q1, Q3) of 38.5 (27, 51) years old. Among the 1 285 secondary cases, males accounted for 59.1% (759 cases), with the median age (Q1, Q3) of 34 (17, 52) years old. The multivariate logistic regression model showed that the higher SAR was observed in the primary male cases (OR=1.632, 95%CI: 1.418-1.877), younger than 20 years old (OR=1.766, 95%CI: 1.506-2.072),≥60 years old (OR=1.869, 95%CI: 1.476-2.365), infected with the BA.2 strain branch (OR=2.906, 95%CI: 2.388-3.537), the confirmed common cases (OR=2.572, 95%CI: 2.036-3.249), and confirmed mild cases (OR=1.717, 95%CI: 1.486-1.985). Meanwhile, the higher SAR was observed in the close contacts younger than 20 years old (OR=2.604, 95%CI: 2.250-3.015),≥60 years old (OR=1.287, 95%CI: 1.052-1.573) and exposure for co-residence (OR=27.854, 95%CI: 23.470-33.057). Conclusion: The sex and age of the primary case of the Omicron variant, the branch of the infected strain, case severity of the primary case, as well as the age and contact mode of close contacts are the associated factors of SAR.
Humans
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Male
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Middle Aged
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Young Adult
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Adult
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COVID-19/epidemiology*
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Incidence
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SARS-CoV-2
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Logistic Models

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