To systematically analyzed the reporting status of core elements in publicly available clinical practice guideline(hereafter referred to as "guideline") protocols published domestically and internationally over the past decade, identified existing problems, and provided evidence to inform the standardized writing and publication of future guideline protocols.

This study explores methodological issues in the design， evaluation， and reporting of randomized controlled trials （RCTs） under the concept of "syndrome dominating disease". The discussion focuses on key aspects including the adaptability of trial design， the screening of research participants， the standardization of syndrome differentiation， the balance between intervention individualization and standardization， the integration of multi-dimensional outcome measures， and the limitations of existing evaluation and reporting tools when applied to this type of research， along with corresponding recommendations and future perspectives. Regarding research design， it is recommended to select or draw upon innovative design concepts such as basket trials and subgroup-based dynamic/static parallel-group designs， in order to innovate the design format of RCTs. Meanwhile， criteria for participant screening， TCM syndrome differentiation， and disease classification should be standardized. The balance should be appropriately achieved between intervention individualization and standardization， and a multidimensional assessment system encompassing TCM syndromes， disease-specific outcomes， and patient-reported outcomes should be established. For risk of bias assessment and research reporting， it is recommended，to develop specialized assessment and reporting tools based on existing instruments， in order to standardize the assessment and reporting of study findings. Future research may further explore the potential applications of artificial intelligence in the study design， risk-of-bias assessment， and reporting quality assessment of RCTs based on the "syndrome dominating disease" model， with a particular focus on methodological optimization， data integration， and enhancement of research quality.

This study explores methodological issues in the design， evaluation， and reporting of randomized controlled trials （RCTs） under the concept of "syndrome dominating disease". The discussion focuses on key aspects including the adaptability of trial design， the screening of research participants， the standardization of syndrome differentiation， the balance between intervention individualization and standardization， the integration of multi-dimensional outcome measures， and the limitations of existing evaluation and reporting tools when applied to this type of research， along with corresponding recommendations and future perspectives. Regarding research design， it is recommended to select or draw upon innovative design concepts such as basket trials and subgroup-based dynamic/static parallel-group designs， in order to innovate the design format of RCTs. Meanwhile， criteria for participant screening， TCM syndrome differentiation， and disease classification should be standardized. The balance should be appropriately achieved between intervention individualization and standardization， and a multidimensional assessment system encompassing TCM syndromes， disease-specific outcomes， and patient-reported outcomes should be established. For risk of bias assessment and research reporting， it is recommended，to develop specialized assessment and reporting tools based on existing instruments， in order to standardize the assessment and reporting of study findings. Future research may further explore the potential applications of artificial intelligence in the study design， risk-of-bias assessment， and reporting quality assessment of RCTs based on the "syndrome dominating disease" model， with a particular focus on methodological optimization， data integration， and enhancement of research quality.

The aim of this updated guideline is to provide comprehensive recommendations for the management of gout in patients with common comorbidities, such as chronic kidney disease(CKD), cardiovascular disease(CVD), diabetes, osteoarthritis(OA), and gastrointestinal disorders. This guideline was developed by a multidisciplinary expert panel consisting of specialists in endocrinology, rheumatology, nephrology, cardiology, gastroenterology, and methodology. The development process adhered to standard methodologies, including PICO(population, intervention, comparator, and outcomes) question deconstruction, systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation(GRADE) for evidence and recommendation evaluation, Delphi voting, and expert consensus. The guideline presents 26 evidence-based recommendations addressing 7 clinical questions for patients with hyperuricemia and gout in the context of comorbidities. Key recommendations include the maintenance of strict serum urate targets, particularly for patients with CKD stage≥3, chronic gouty arthritis, and OA, in order to prevent disease progression. In patients with CVD or diabetes, intra-articular triamcinolone is preferred over systemic glucocorticoids. Prioritized anti-inflammatory treatments for patients with CKD, gastrointestinal diseases and OA are recommended. The guideline also introduces emerging therapies, such as interleukin-1 inhibitors and selective urate transport inhibitors, as potential treatment options for refractory cases. The update offers a comprehensive, patient-centered approach to managing gout, particularly in individuals with associated comorbidities. Multidisciplinary collaboration and emerging new treatments and evidence ensure the optimization of the recommendations.

To develop a guideline terminology system and promote its standardization, thereby enhancing medical staff's accurate understanding and correct application of guidelines.

OBJECTIVE To evaluate the quality of evidence in the systematic evaluation/meta-analysis of traditional Chinese medicine （TCM） for diabetes retinopathy （DR） based on the GRADE system. METHODS Chinese and English databases were searched to obtain the relevant studies of systematic evaluation/meta-analysis of traditional Chinese medicine in the treatment of DR. The search time was from the establishment of each database to January 13th， 2024. According to the inclusion and exclusion criteria， literature screening was conducted. After extracting relevant information from the included literature， the GRADE system was used to evaluate the quality level of the evidence body in the included studies， and the evidence of the outcome indicators was integrated and summarized. RESULTS A total of 51 studies were ultimately included， encompassing 135 outcome indexes. Among these， 19 indicators （14.1%） were of high quality， 87 （64.4%） were of medium quality， 26 （19.3%） were of low quality， and 3 （2.2%） were of very low quality. Overall， the evidence quality of the outcome indicators in the included studies was medium to low quality. The integrated results of evidence on the efficacy of outcome indexes showed that compared with conventional Western medicine， calcium dobesilate or placebo， TCM had significant advantages in improving overall efficacy， reducing bleeding spot area， reducing macular foveal thickness， and increasing visual improvement rate. In addition，the combination of TCM and conventional Western medicine or calcium dobesilate was significantly more effective than using conventional Western medicine or calcium dobesilate alone. CONCLUSIONS The overall quality of the evidence in the systematic evaluation/meta-analysis study on the treatment of DR with TCM is medium to low quality. Based on existing research findings， TCM demonstrates good clinical efficacy in the treatment of DR.

The aim of this updated guideline is to provide comprehensive recommendations for the management of gout in patients with common comorbidities, such as chronic kidney disease(CKD), cardiovascular disease(CVD), diabetes, osteoarthritis(OA), and gastrointestinal disorders. This guideline was developed by a multidisciplinary expert panel consisting of specialists in endocrinology, rheumatology, nephrology, cardiology, gastroenterology, and methodology. The development process adhered to standard methodologies, including PICO(population, intervention, comparator, and outcomes) question deconstruction, systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation(GRADE) for evidence and recommendation evaluation, Delphi voting, and expert consensus. The guideline presents 26 evidence-based recommendations addressing 7 clinical questions for patients with hyperuricemia and gout in the context of comorbidities. Key recommendations include the maintenance of strict serum urate targets, particularly for patients with CKD stage≥3, chronic gouty arthritis, and OA, in order to prevent disease progression. In patients with CVD or diabetes, intra-articular triamcinolone is preferred over systemic glucocorticoids. Prioritized anti-inflammatory treatments for patients with CKD, gastrointestinal diseases and OA are recommended. The guideline also introduces emerging therapies, such as interleukin-1 inhibitors and selective urate transport inhibitors, as potential treatment options for refractory cases. The update offers a comprehensive, patient-centered approach to managing gout, particularly in individuals with associated comorbidities. Multidisciplinary collaboration and emerging new treatments and evidence ensure the optimization of the recommendations.

Objective:To analyze 80 strains of Streptococcus pneumoniae by using whole-genome sequencing technology, including serotype characteristics, drug resistance genes, carriage of virulence genes, multilocus sequence typing (MLST), and relatedness between strains. Methods:Whole-genome sequencing was performed on Streptococcus pneumoniae. Serotypes, resistance genes, virulence genes, and sequence typing (ST) were analyzed in conjunction with the CARD database, the NCBI database, the VFDB database, and the PubMLST website. The strains were compared by using KSNP4 based on the analysis of single-nucleotide polymorphisms (SNPs). An evolutionary tree was constructed with the IQ-TREE software and beautified by using EvolView software. Results:Of all 80 Streptococcus pneumoniae strains, serotypes 19F, 19A, 14 and 23F were predominant, 30 strains were from cases of invasive pneumococcal disease (IPD) and 50 strains were from cases of non-invasive pneumococcal disease (NIPD). The virulence genes psaA, nanB, lytA, lytC, and ply were detected in all cases, while cps4 A, cps4 B, and hysA were detected in 98.75% of cases, and nanA was detected in 90.00%, rrgA and rrgB showed statistical differences between IPD and NIPD( P<0.05). The resistance genes patA, patB, tetM, pmrA, PBP1 b, RlmA( II), and ermB were detected in all cases, while PBP1 a was detected in 98.75% of cases. There was a statistically significant difference between IPD and NIPD for mefA and msrD( P<0.05). MLST analysis of 80 strains of bacteria showed that the ST types were mainly ST271, ST320, ST876, ST81, in which seven new ST types were emerged; the phylogenetic tree could be divided into three branches, The dominant ST types of the strains with serotypes 14, 23F, 19F, and 19A were ST876, ST81, ST271, and ST320, respectively. Conclusions:The study finds that the main serotypes of the 80 strains are 19F, 19A, 14 and 23F. The strains have more varieties of virulence genes, resistance genes and high carriage of some genes; rrgA, rrgB and mefA, msrD differ between IPD and NIPD. ST-types are characterised by diversity and new ST-types are constantly emerged. A correlation exists between serotypes and systemic evolution in the phylogenetic analyses, with each serotype contains its own dominant ST-types.

Expert evidence, expert opinion, and expert consensus are frequently mentioned and used in the process of guideline development. However, due to the lack of clear definitions and standards, there is confusion and misuse among the three in practice. This paper clarifies the meanings, current status, differences, and connections of expert evidence, expert opinion, and expert consensus in the development of guidelines, aiming to provide a reference for guideline developers in China.

Generative artificial intelligence (GAI) refers to AI technology capable of generating new content such as text, images, or audio from training data. GAI tools not only demonstrate rapid and efficient potential in literature screening, data extraction, and literature appraisal in systematic reviews, but can also be used for guideline evaluation and dissemination, enhancing the readability and promotion efficiency of guidelines. However, the accuracy of content generated by GAI tools, the rationality of cited evidence, the level of evidence, and the reliability of data still need verification. Additionally, data privacy protection and ethical issues are challenges that need to be addressed. This article aims to overview the current status of GAI tools in the formulation, evaluation, dissemination, and implementation of guidelines, explore the feasibility and new models of GAI tools in the field of guidelines, and improve the efficiency and quality of guideline formulation to better serve guideline developers and users.