Automated Author ProfileLiu, Yanqing
Liu, Yanqing
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 27.3 (sum of 50 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Authors
- Li, Teng ;
- Yang, Can ;
- Tang, Haitao ;
- Liu, Xiaojie ;
- Liu, Yanqing ;
- Wang, Shenghao ;
- Xing, Guangzong ;
- Lin, Qianqian ;
- Wu, Qi ;
- Dang, Yangyang
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Authors
- Li, Teng ;
- Yang, Can ;
- Tang, Haitao ;
- Liu, Xiaojie ;
- Liu, Yanqing ;
- Wang, Shenghao ;
- Xing, Guangzong ;
- Lin, Qianqian ;
- Wu, Qi ;
- Dang, Yangyang
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Authors
- Sang, Mengjie ;
- Liu, Yanqing ;
- Liu, Guokui ;
- Dang, Yangyang
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Authors
- Sang, Mengjie ;
- Liu, Yanqing ;
- Liu, Guokui ;
- Dang, Yangyang
Longer and more detailed description of this file
Authors
- Cui, Guonan ;
- Yang, Yanchun ;
- Bai, Lulu ;
- Liu, Yanqing ;
- Gong, Zhihui ;
- Sun, Yuze ;
- Wang, Xu ;
- Bao, Junjie ;
- Li, Shuyu ;
- Zhu, Chengjun
Although suboptimal platelet transfusion (PT) response in critically ill patients with thrombocytopenia remains a challenge in clinical practice. This study aimed to investigate PT response during intensive care unit (ICU) stay among thrombocytopenic patients without underlying hematologic disease. This retrospective single-center analysis included thrombocytopenic patients without primary hematologic disorders who received PT in ICU between June 2021 and December 2023. Clinical and laboratory variables were analyzed using a generalized linear mixed-effects model (GLMM), with the results visualized through a nomogram. The 28-day survival curves, stratified by receiving single or multiple PT episodes, were established using the Kaplan–Meier method. Suboptimal PT response was observed in 522 episodes (77.9%, 522/670) and in 291 patients (79.9%, 291/364). The GLMM identified sepsis, splenomegaly, mechanical ventilation, higher APACHE II score, and longer time interval of post-PT platelet count as independent predictors of suboptimal response, while higher white blood cell count at ICU admission and the PT episode number in ICU were independently protective. A nomogram based on these seven variables demonstrated good predictive performance. Suboptimal PT episodes were associated with higher red blood cell and fresh frozen plasma requirements. The 28-day survival probability was significantly higher in the single transfusion group with optimal response versus the suboptimal response. Repeat PT may enhance the PT response and survival. Suboptimal PT response was associated with increased RBC and FFP transfusion requirements. The established nomogram demonstrated strong predictive accuracy and may provide a practical tool for optimizing PT practices in the ICU.
Authors
- Ge, Hanyu ;
- Liu, Yanqing ;
- Li, Tongyu ;
- Lv, Rui ;
- Wang, Jieyi ;
- You, Wei ;
- Song, Danni ;
- Hu, Shilin ;
- Zhao, Feng ;
- Fan, Heng ;
- Lv, Dingfeng
Although suboptimal platelet transfusion (PT) response in critically ill patients with thrombocytopenia remains a challenge in clinical practice. This study aimed to investigate PT response during intensive care unit (ICU) stay among thrombocytopenic patients without underlying hematologic disease. This retrospective single-center analysis included thrombocytopenic patients without primary hematologic disorders who received PT in ICU between June 2021 and December 2023. Clinical and laboratory variables were analyzed using a generalized linear mixed-effects model (GLMM), with the results visualized through a nomogram. The 28-day survival curves, stratified by receiving single or multiple PT episodes, were established using the Kaplan–Meier method. Suboptimal PT response was observed in 522 episodes (77.9%, 522/670) and in 291 patients (79.9%, 291/364). The GLMM identified sepsis, splenomegaly, mechanical ventilation, higher APACHE II score, and longer time interval of post-PT platelet count as independent predictors of suboptimal response, while higher white blood cell count at ICU admission and the PT episode number in ICU were independently protective. A nomogram based on these seven variables demonstrated good predictive performance. Suboptimal PT episodes were associated with higher red blood cell and fresh frozen plasma requirements. The 28-day survival probability was significantly higher in the single transfusion group with optimal response versus the suboptimal response. Repeat PT may enhance the PT response and survival. Suboptimal PT response was associated with increased RBC and FFP transfusion requirements. The established nomogram demonstrated strong predictive accuracy and may provide a practical tool for optimizing PT practices in the ICU.
Authors
- Ge, Hanyu ;
- Liu, Yanqing ;
- Li, Tongyu ;
- Lv, Rui ;
- Wang, Jieyi ;
- You, Wei ;
- Song, Danni ;
- Hu, Shilin ;
- Zhao, Feng ;
- Fan, Heng ;
- Lv, Dingfeng
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Authors
- Liu, Yanqing ;
- Tang, Haitao ;
- Sang, Mengjie ;
- Li, Teng ;
- Liu, Guokui ;
- Meng, Lingqiang ;
- Lin, Qianqian ;
- Dang, Yangyang
Longer and more detailed description of this file
Authors
- Cui, Guonan ;
- Yang, Yanchun ;
- Bai, Lulu ;
- Liu, Yanqing ;
- Gong, Zhihui ;
- Sun, Yuze ;
- Wang, Xu ;
- Bao, Junjie ;
- Li, Shuyu ;
- Zhu, Chengjun
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Authors
- Li, Teng ;
- Wang, Yue ;
- Liu, Yanqing ;
- Liu, Guokui ;
- Meng, Lingqiang ;
- Zheng, Yongshen ;
- Dang, Yangyang