Table of Content

20 May 2024, Volume 19 Issue 5

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Challenges and Opportunities in Clinical Prediction Models

GU Hongqiu

2024, 19(5):  481-487.  DOI: 10.3969/j.issn.1673-5765.2024.05.001

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Clinical prediction models can predict individual outcomes or risks based on effect evidence obtained from the population, serving as a powerful tool linking evidence-based medicine and precision medicine. With the continuous advancement of data measurement, storage, interoperability, and analytical techniques, the application prospect for clinical prediction models is becoming increasingly clear. However, it also faces many problems and challenges. This paper aims to provide an overview of the fundamental concepts, application scenarios, current dilemmas, and development opportunities of clinical prediction models.



Clinical Prediction Model Methodology

GU Hongqiu

2024, 19(5):  488-488. 

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Sample Size Estimation for the Development and Validation of Clinical Prediction Models

JIANG Yingyu, GU Hongqiu

2024, 19(5):  489-495.  DOI: 10.3969/j.issn.1673-5765.2024.05.002

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The application of clinical prediction models in the medical field is receiving increasing attention. Reasonable and sufficient sample size is of great importance to the feasibility and quality assurance of prediction model research. Based on this, this paper summarized the strategies for sample size estimation in the development and validation of clinical prediction models, outlined the key issues that should be paid attention to in sample size estimation, and also discussed the problems related to insufficient sample size, to help researchers estimate the sample size reasonably and improve the quality of clinical prediction model research.

Common Clinical Prediction Statistical Models and SAS Implementation

YANG Kaixuan, GU Hongqiu

2024, 19(5):  496-505.  DOI: 10.3969/j.issn.1673-5765.2024.05.003

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The application of clinical prediction models in medical research is becoming increasingly widespread. To achieve good predictive performance, selecting the correct model is crucial. Regarding the choice of prediction model, the type of prediction outcome plays a decisive role. This paper, from the perspective of data types, divided outcomes into continuous variables (normal distribution, skewed distribution), categorical variables (binary, nominal, ordinal), and time-to-event variables (with or without competing risks), introducing the characteristics of different types of outcomes, the model types, examples and SAS programs to serve as a reference for researchers to develop prediction models.

A Brief Introduction of Statistical Analysis Strategy and Charts for the Development and Validation of Clinical Prediction Models

DU Kejin, GU Hongqiu

2024, 19(5):  506-514.  DOI: 10.3969/j.issn.1673-5765.2024.05.004

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The presentation of statistical charts plays a crucial role in improving the quality of clinical prediction model research. This paper categorized statistical charts in clinical prediction models into four aspects: describing basic information, reporting model information, evaluating model performance, and demonstrating model application, accompanied by a brief overview of statistical chart templates.

Presentation of Clinical Prediction Models

JIN Aoming, GU Hongqiu

2024, 19(5):  515-519.  DOI: 10.3969/j.issn.1673-5765.2024.05.005

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A prediction model is a statistical model used to predict the probability of an individual with a target event or to predict the outcome value. Visualization of prediction model results is an essential part of the whole process of developing a prediction model. A good presentation of a prediction model can not only make the prediction results more readable and interpretable, but also determine its use and convenience to a large extent. This paper provided a detailed introduction to various forms of prediction model presentation and reported their advantages and disadvantages. Combining clinical prediction model research on cerebrovascular disease, this paper introduced the application of each presentation in cerebrovascular disease research through research examples.



Application Prospect of Clinical Prediction Models in Medical Insurance Payment

CHEN Qibai, ZENG Yin

2024, 19(5):  520-523.  DOI: 10.3969/j.issn.1673-5765.2024.05.006

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Advancing the reform of medical insurance payment methods is not only a necessity for the high-quality development of medical insurance, but also a requirement for alleviating the burden of people’s medical expenses and enhancing their well-being. In recent years, China has made positive progress in the reform of diversified and composite medical insurance payment methods, which has also raised higher requirements for the management of medical insurance funds and medical institutions. Against the backdrop of health big data, clinical prediction models have been maturely applied in areas such as drug trials, demonstrating good capabilities in quantitatively assessing the risk level of patients’ diseases and the intensity of medical resource consumption. This paper aims to draw lessons from international experiences in medical insurance risk adjustment mechanisms and risk prediction models, explore the feasibility of applying clinical prediction models to diagnosis related groups and medical insurance reimbursement risk adjustment under the reform of medical insurance payment methods, and provide corresponding references for further improving the quality of medical institution services and enhancing the efficiency of medical insurance fund utilization.

Development and Validation of a Prediction Model of In-Hospital Neurological Deterioration for Patients with Minor Acute Ischemic Stroke

YI Luo, JIANG Yingyu, MENG Xia, JIANG Yong, WANG Yongjun, GU Hongqiu

2024, 19(5):  524-531.  DOI: 10.3969/j.issn.1673-5765.2024.05.007

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Objective  To develop a prediction model of in-hospital neurological deterioration for patients with minor acute ischemic stroke (AIS), and to provide scientific basis for stratified in-hospital management. 
Methods  Patients with minor AIS (defined as NIHSS score≤5) enrolled in the China national stroke registry Ⅲ (CNSR Ⅲ) and arriving within 24 hours from onset while without taking rt-PA intravenous thrombolysis or endovascular treatment were selected as the study subjects. The derivation cohort was consisted of 2256 patients enrolled from 2015 to 2016, and the validation cohort was consisted of 1775 patients enrolled from 2017 to 2018. The predictors were finally determined by LASSO regression and reviewing of previous studies. In-hospital neurological deterioration was defined as 4 points or more increase in NIHSS score at discharge compared with the NIHSS score at admission. A logistic regression model was used to develop the prediction model. Discrimination and calibration were evaluated using C statistic and the Brier score, respectively.
Results  A total of 4031 patients were included in the study, with 58(2.6%) of 2256 patients from the derivation cohort and 63(3.5%) of 1775 patients from the validation cohort encountered in-hospital neurological deterioration. The population characteristics were similar between the two cohorts. The prediction model was developed based on 9 predictors, including age, gender, smoking, systolic blood pressure, IL-6, hs-CRP, NIHSS score on admission, diabetes mellitus and infarction pattern. The C statistic for the model was 0.69 (95%CI 0.62-0.76) in the derivation cohort and 0.73 (95%CI 0.67-0.80) in the validation cohort. The Brier score of the model was 0.025 in the derivation cohort and 0.033 in the validation cohort.
Conclusions  This study developed a prediction model for the risk of in-hospital neurological deterioration for patients with minor AIS based on routine hospitalization data, and the prediction model achieved acceptable levels of discrimination and calibration, yet the extrapolation needs to be further verified by external data.




Analysis of Influencing Factors and Construction of Prediction Models for Pulmonary Infection after Minimally Invasive Intracranial Hematoma Removal in Patients with Intracerebral Hemorrhage

LI Chenhong, JIANG Chenli, WANG Jinhui, HUANG Sheng

2024, 19(5):  532-538.  DOI: 10.3969/j.issn.1673-5765.2024.05.008

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Objective  To investigate the influencing factors of pulmonary infection during hospitalization after minimally invasive intracranial hematoma removal in patients with intracerebral hemorrhage (ICH) and construct a prediction model, in order to provide guidance for medical staff to evaluate the risk of postoperative pulmonary infection in ICH patients and develop prevention strategies. 
Methods  ICH patients who underwent minimally invasive intracranial hematoma removal at the Department of Neurosurgery, Suzhou Ninth Hospital Affiliated to Soochow University from January 2018 to July 2023 were continuously included. The ICH patients were divided into pulmonary infection group and non-pulmonary infection group according to whether they had pulmonary infection during hospitalization. The clinical data of the two groups were compared. Multivariate logistic regression analysis was used to explore the influencing factors of pulmonary infection after minimally invasive intracranial hematoma removal in ICH patients, and the logistic regression model was constructed. At the same time, the gradient boosting machine (GBM) algorithm of R was used to construct a GBM prediction model for pulmonary infection after minimally invasive intracranial hematoma removal in ICH patients. The prediction efficiency of the two models was analyzed by ROC curve and compared by Delong test. 
Results  A total of 297 ICH patients who underwent minimally invasive intracranial hematoma removal were included in the study. Among them, 52 cases (17.5%) occurred pulmonary infection during postoperative hospitalization. Multivariate analysis showed that malnutrition (OR 2.737, 95%CI 1.249-5.998, P=0.012), tracheotomy (OR 2.716, 95%CI 1.296-5.690, P=0.008), and indwelling gastric tube (OR 3.521, 95%CI 1.724-7.193, P<0.001) were independent risk factors for pulmonary infection in ICH patients after minimally invasive intracranial hematoma removal. High preoperative GCS score (OR 0.622, 95%CI 0.515-0.752, P<0.001) and oral care (OR 0.105, 95%CI 0.028-0.390, P<0.001) were protective factors. According to ROC curve analysis, the AUC of the logistic regression model was 0.837, and the AUC of the GBM prediction model was 0.861. Delong test showed that the efficiency of GBM prediction model was better than that of logistic regression model (Z=2.318, P=0.021). 
Conclusions  Malnutrition, tracheotomy and indwelling gastric tube were the risk factors of pulmonary infection in ICH patients after minimally invasive intracranial hematoma removal, while high preoperative GCS score and oral care were protective factors. The efficiency of GBM model based on the above indicators was better than logistic model.




Relationship between Lipoprotein(a) and Unstable Carotid Atherosclerotic Plaque

LI Shiyu, ZHANG Xing, HU Wenli

2024, 19(5):  539-544.  DOI: 10.3969/j.issn.1673-5765.2024.05.009

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Objective  To investigate the relationship between lipoprotein(a) [Lp(a)] and unstable carotid atherosclerotic plaque.
Methods  Patients with ischemic cerebrovascular disease (including ischemic stroke, TIA and chronic cerebral ischemia) who were hospitalized in the Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University from January to December 2022 were retrospectively included. All patients completed Lp(a) test and carotid ultrasound examination. According to the plaque echo characteristics of carotid ultrasound, the patients were divided into unstable plaque group and stable plaque group. The upper limit of normal Lp(a) level (30 mg/dL) was selected as the critical value. Multivariate logistic regression was used to analyze the effect of elevated Lp(a) level on unstable carotid atherosclerotic plaque. In addition, the effect of Lp(a) on unstable carotid atherosclerotic plaque at different levels of LDL-C was analyzed with LDL-C level of 1.8 mmol/L as the critical value.
Results  A total of 747 eligible patients were enrolled in this study, including 484 males (64.8%), with a median age of 66 (58-72) years. Univariate analysis showed that patients in the unstable plaque group was older, with higher proportions of male, history of hypertension, diabetes mellitus and stroke, and higher levels of Lp(a), Hcy and glycosylated hemoglobin. Multivariate logistic regression analysis showed that elevated Lp(a) was an independent risk factor of unstable carotid atherosclerotic plaque (OR 1.65, 95%CI 1.02-2.68, P=0.04). Subgroup analysis showed that Lp(a) had no significant effect on unstable carotid atherosclerotic plaque when LDL-C<1.8 mmol/L (OR 1.41, 95%CI 0.34-5.93), but there was no interaction between the LDL-C and Lp(a) levels on unstable carotid atherosclerotic plaque.
Conclusions  Elevated Lp(a) was associated with unstable carotid atherosclerotic plaque. However, at low LDL-C levels, the effect of elevated Lp(a) on unstable carotid atherosclerotic plaque was not significant.




Risk Factors of Early Neurological Deterioration of Patients after Minimally Invasive Surgery in Supratentorial Hypertensive Intracerebral Hemorrhage

DING Zeyu, JI Zeqiang, WU Jianwei, KANG Kaijiang, ZHAO Xingquan

2024, 19(5):  545-551.  DOI: 10.3969/j.issn.1673-5765.2024.05.010

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Objective  To analyze the risk factors of early neurological deterioration (END) after minimally invasive surgery of patients with supratentorial hypertensive intracerebral hemorrhage (ICH). 
Methods  This study was a retrospective case study. Supratentorial hypertensive ICH patients who had undergone minimally invasive surgery in the Emergency Neurology Department, Beijing Tiantan Hospital, Capital Medical University from October 2018 to December 2022 were continuously included. Patients’ demographic characteristics and clinical information, as well as imaging information like hematoma volume, location, and peri-hematoma perfusion, were recorded. The evaluation criteria of END was that the NIHSS score increased by≥4 points or the GCS score decreased by≥2 points within 24 hours after surgery. The variables with statistically significant  differences selected by univariate analysis were incorporated into the binary logistic regression model (regression method) to analyze the independent risk factors affecting the END of patients. At the same time, the ROC curve of independent risk factors was plotted and the AUC was calculated. De Long test was used to compare the prediction ability of different independent risk factors. 
Results  A total of 157 patients were enrolled, with an average age of (57.1±13.1) years. END occurred in 20 patients (12.7%). Multivariate logistic regression analysis showed that preoperative hematoma volume (OR 1.024, 95%CI 1.001-1.047, P=0.043) and postoperative hematoma expansion (OR 41.605, 95%CI 7.405-233.765, P＜0.001) and preoperative hypoperfusion volume (OR 1.011, 95%CI 1.002-1.020, P=0.012) could independently predict the occurrence of END. The AUC, sensitivity, and specificity of ROC for preoperative hypoperfusion volume were 0.921, 0.824,  and 0.891. The cut-off value was 119.0 mL. De Long test indicated that the prediction efficacy of preoperative hypoperfusion volume was better than that of preoperative hematoma volume and postoperative hematoma expansion (P<0.05). 
Conclusions  Preoperative hypoperfusion volume was independently correlated with END of patients after minimally invasive surgery in supratentorial hypertensive intracerebral hemorrhage. The greater the hypoperfusion volume, the higher the risk of END.




Hot Spots and Trends in Stroke and Blood-Brain Barrier Research from 2001 to 2023: A Bibliometric-Based Study and Knowledge Graph Analysis

GU Zheng, JIANG Hailun, WU Mingfen, ZHAO Zhigang, SUN Aning

2024, 19(5):  552-562.  DOI: 10.3969/j.issn.1673-5765.2024.05.011

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Objective  A bibliometric analysis of the literature related to stroke and the blood-brain barrier was conducted to obtain a research map, explore hotspots and trends, and provide references for clinical treatment and research.
Methods  The literature related to stroke and blood-brain barrier from 1 January 2001 to 28 February 2023 was explored in the Web of Science core database. Using bibliometrics, CiteSpace V6.1.R6 was used to analyze the distribution of years, countries/regions, research institutions/system, authors, publications, cited literature, keywords and research trends. 
Results  A total of 5028 papers were included after screening, with an overall upward trend in the number of published papers. The United States had the most research on this topic, followed by China’s mainland and Germany. Most of the top 10 research institutions/system were from the United States, France and China, with strong collaboration between countries/regions and research institutions/system. Among the authors, Chopp Michael from the United States ranked first with 49 papers. Among the research trends, ischemic stroke, miR-126 in non-coding RNA, blood-brain barrier dysfunction and drug delivery were the hot spots in the last three years. 
Conclusions  Blood-brain barrier and stroke are inextricably linked. The dysfunction and repair mechanism of blood-brain barrier during stroke, the circulation biomarkers released by blood-brain barrier and the use of blood-brain barrier opening time to increase drug absorption are worthy of further study.


Research Progress on Correlation between Stroke and Alcohol Use Disorder

LIAO Jia, QUAN Fengying

2024, 19(5):  563-572.  DOI: 10.3969/j.issn.1673-5765.2024.05.012

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Alcohol use disorder, as the fifth largest risk factor worldwide, is an important component of stroke prevention. In recent years, a large number of epidemiological and clinical studies have shown that there is a correlation between alcohol and stroke. Alcohol can affect cardiovascular and cerebrovascular health through various ways, resulting in stroke and even death. At the same time, some studies have shown that there may be different associations between alcohol and stroke, light drinking may be a cardiovascular and cerebrovascular protective factor, and moderate and heavy drinking may induce and aggravate stroke. This paper analyzed the current prevalence of stroke complicated with alcohol use disorder, reviewed the possible pathogenesis of alcohol use disorder affecting the incidence of stroke, and summarized alcohol intake monitoring biomarkers and treatments related to alcohol use disorder, in order to further explore the correlation between stroke and alcohol use disorder and provide ideas for clinical diagnosis and treatment.

Research Progress of Tirofiban Combined with Mechanical Thrombectomy in the Treatment of Acute Ischemic Stroke

ZHENG Guomin, LIANG Zhigang, ZHANG Zhen

2024, 19(5):  573-578.  DOI: 10.3969/j.issn.1673-5765.2024.05.013

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In acute ischemic stroke patients with large vessel occlusion, mechanical thrombectomy can improve the hemodynamic status and clinical symptoms within the effective time, but mechanical thrombectomy is often associated with vascular re-occlusion, which affects the prognosis of patients. Platelet glycoprotein Ⅱb/Ⅲa (GP Ⅱb/Ⅲa) receptor antagonists prevent vascular re-occlusion by inhibiting the last common pathway of platelet aggregation. At present, the effects of GP Ⅱb/Ⅲa receptor antagonists on the clinical outcome during the perioperative period of mechanical thrombectomy in ischemic stroke remain controversial. This paper reviewd the efficacy and safety of tirofiban, a GP Ⅱb/Ⅲa receptor antagonist, in the treatment of vascular re-occlusion after mechanical thrombectomy in acute ischemic stroke. It was found that tirofiban combined with mechanical thrombectomy was safe for the treatment of acute ischemic stroke, but its therapeutic effectiveness still needs to be confirmed by standardized clinical research evidence.

Research Progress on the Role of Platelet Activation in Acute Cerebral Infarction

ZHANG Jiancun, WANG Xinxing, TONG Haibo

2024, 19(5):  579-585.  DOI: 10.3969/j.issn.1673-5765.2024.05.014

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Acute cerebral infarction is a common ischemic cerebrovascular disease and is closely related to platelet activity. Platelet activity has significant impact on occurrence, development, treatment and prognosis of acute cerebral infarction. Mean platelet volume (MPV)and platelet distribution width (PDW) are two important indicators that reflect platelet activity. Platelets with larger volume are considered to have higher activity for they can secrete more thrombosis factors and express more P-selections and platelet glycoprotein Ⅱb/Ⅲa receptors. Activated platelets increase PDW by protruding pseudopodia of varying sizes. Thus, both high MPV and PDW are the indications of platelet activation. This paper reviewed the effects of platelet activation on the occurrence, development and prognosis of acute cerebral infarction, in order to provide references for the subsequent study of the relationship between platelet activity and acute cerebral infarction.

Continuous Care Needs of Stroke Patients Based on the APP: A Qualitative Study

WU Meiru, CHEN Yitong, LIU Xingchi, WANG Shijie, DENG Yongmei

2024, 19(5):  586-591.  DOI: 10.3969/j.issn.1673-5765.2024.05.015

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Objective  To understand the continuous care needs of stroke patients based on the application (APP), and to provide effective continuous care services for such patients and their families.
Methods  Semi-structured interviews were conducted on 8 stroke patients and 4 family members who had used the APP. The data were sorted and analyzed by means of qualitative study phenomenological analysis. Also, the themes of “Internet +” continuous care needs and the feelings and suggestions of using the “stroke care clinic based on the APP” were extracted. 
Results  The subjects of respondents’ needs for “Internet +” continuous care were: physical rehabilitation guidance, drug-related knowledge, understanding the reimbursement process, video health education, home care guidance, control of risk factors, and home delivery of drugs. The respondents’ feelings and suggestions about using “stroke care clinic based on the APP” were as follows: willing to use the Internet care clinic, easy to use, timely response, time-saving, and professional. 
Conclusions  The “Internet +” continuous care clinic based on the APP should be optimized to improve the continuous care program for stroke patients and improve the medical quality of stroke.


Application of Hierarchical and Progressive Teaching in the Training of the National Stroke Vascular Ultrasound Demonstration Center

LIU Yumei, DU Liyong, LEI Na, PAN Xijuan, XING Yingqi

2024, 19(5):  592-596.  DOI: 10.3969/j.issn.1673-5765.2024.05.016

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Objective  To explore the training effect of hierarchical and progressive teaching mode on continuing educational physicians in the field of vascular ultrasound. 
Methods  A total of 124 physicians studying in Vascular Ultrasound Department of Xuanwu Hospital, Capital Medical University from January 2021 to March 2023 were included. They were divided into the single technique group and the integrated technique group based on their mastery of vascular ultrasound and TCD technology at the beginning. After 6 months of training with hierarchical and progressive teaching mode, the theoretical and operational assessments were examed. 
Results  There was no significant difference in theoretical assessment scores and operational assessment scores between the single technique group and the integrated technique group when enrolled. After the training with hierarchical and progressive teaching, the theoretical assessment scores [(83.8±6.9) points vs. (65.2±9.6) points, P<0.001] and operational assessment scores [(93.2±4.5) points vs. (91.4±4.3) points, P<0.001] of the single technique group were significantly improved. The theoretical assessment scores of the integrated technique group were improved as well [(86.9±7.7) points vs. (67.7±6.4) points, P<0.001]. 
Conclusions  Research showed that the hierarchical and progressive teaching mode has good teaching effect and high teaching satisfaction for continuing educational physicians in the field of vascular ultrasound.


Application of Blending Learning Model in Training Teaching of Hyperbaric Oxygen for Postgraduates Major in Neurology

REN Ziqi, LIU Yaling, LIU Yanfang, WANG Wenjuan, WANG Cong, YU Qiuhong

2024, 19(5):  597-600.  DOI: 10.3969/j.issn.1673-5765.2024.05.017

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Objective  To explore the effect of blending learning model in training teaching of hyperbaric oxygen (HBO) for postgraduates majoring in neurology. 
Methods  Postgraduates who major in neurology and work as interns in the Department of HBO from April to December 2023 were enrolled in this study. After sending out questionnaires to investigate the basic situation and needs of postgraduates, the blending learning model was applied to teach theoretical knowledge and practical operations of HBO, and the total credit hours were 40. Exams and questionnaires were used to evaluate the teaching effect. 
Results  A total of 15 neurology postgraduates were included in the study. According to the questionnaire, 13 (86.67%) neurology postgraduates hoped to take HBO as an elective course. After adopting the blending learning model, all 15 neurology postgraduates passed the exam, and the score was (93.53±3.14) points. During the course, the awareness rates of HBO definition and mechanism in these postgraduates increased from 40.00% (6 cases) to 100% (15 cases) (P=0.0003), and the awareness rates of HBO indications and contraindications increased from 33.33% (5 cases) to 93.33% (14 cases) (P=0.0003). Besides, 12 postgraduates (80%) were  aware of HBO treatment regimens. The satisfaction rating of these postgraduates was 100% (15 cases). 
Conclusions  Blending learning model can effectively enhance the teaching level of HBO, and enable the postgraduates who major in neurology to master the knowledge of HBO more effectively.


Analysis and Countermeasures of Peer Review Opinions of a Neuro-Characteristic Medical Institution Applying for National Natural Science Foundation of China in the Field of Nervous System from 2020 to 2023

WU Jingjing, ZOU Lijuan, SHANG Jing, WANG Hao, LI Yiying, DENG Liuli

2024, 19(5):  601-606.  DOI: 10.3969/j.issn.1673-5765.2024.05.018

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Objective  To analyze the peer review feedback of the non-funding of the National Natural Science Foundation of China (NSFC) in the field of nervous system at Beijing Tiantan Hospital, Capital Medical University, and put forward countermeasures to provide references for peers. 
Methods  The content analysis method was employed to examine the peer review opinions of youth and general projects, which were not approved by NSFC in the field of nervous system from 2020 to 2023. A total of 867 expert opinions from 289 programs were categorized and analyzed. 
Results  A total of 1219 reasons for not being funded were analyzed in this paper. It was found that among the youth and general projects, the five expert opinions with the highest mention rate and proportion were: “unreasonable research plans” (32.65%/85.12%), “insufficient research foundation” (18.54%/54.33%), “insufficient innovation” (15.67%/51.21%), “insufficient basis for project approval” (8.37%/30.10%) and “insufficient scientific and clinical value” (7.88%/28.72%). The mention rate and proportion of “insufficient innovation” (the mention rate: 17.13% vs. 13.84%; the proportion: 53.75% vs. 48.06%), “detailed problems” (the mention rate: 6.50% vs. 3.87%; the proportion: 23.13% vs. 15.50%) in youth projects were slightly higher than that in general projects. The mention rate of “the miss-selection of scientific problem” (4.28% vs. 4.06%) and the proportion of “insufficient summary of key scientific viewpoint” (24.38% vs. 23.26%) were also slightly higher in youth projects, but only the mention rate of “detailed problems” (χ2=4.322, P=0.038) was statistically significant between the two items. The expert consensus analysis showed that the top three feedback were consistent with the top three results above.  
Conclusions  The problems in the peer review feedback of the hospital’s unfunded projects mainly focused on three aspects: “unreasonable research plans” “insufficient research foundation” and “insufficient innovation”. To improve the quality of the application forms and increase the rate of successful applications, many measures can be taken, including conducting multidimensional application training and detailed guidance to help applicants improve the scheme design; setting up incubation funds and strengthening the management of ongoing research projects, as well as other multi-channel supports to strengthen the research foundation; and promoting interdisciplinary integration to expand the research fields and ideas, and enhance the ability of source innovation.