Blood standardization is a crucial means of promoting the healthy and sustainable development of China's blood industry. The construction of a blood standard system serves as the foundational work for blood standardization. To facilitate the continuous improvement of blood standardization efforts, this paper begins by describing the current status and analyzing the issues within China's blood standard system. Through systematic research, it proposes a framework for constructing a blood standard system and offers revision recommendations for its enhancement. Based on the first five editions of the blood standard system developed by Sub-Committee of Blood Standards of National Committee of Health Standards, this study further refines the revision and detailed construction of the standards framework—the primary task in establishing the blood standard system. It provides specific guidance for both the construction and application of the blood standard system. This work serves as a reference and basis for the reasonable and standardized formulation and revision of blood standards, as well as for the management and implementation of blood standardization efforts.

Transfusion safety monitoring and learning provide a mechanism for identifying transfusion risks, enabling medical institutions to implement intervention measures, to reduce transfusion risks, and ultimately to improve patient safety. Recently, in response to ongoing challenges in transfusion safety, the UK Serious Hazards of Transfusion (SHOT) integrated and transformed the recommendations scattered in previous annual reports, and released the Standards for Transfusion Safety. This document specifies standards and requirements/criterion in eight key areas, including transfusion safety, transfusion information technology and equipment, supporting staff to work safely, staff education and training, safety culture, patients as safety partners, haemovigilance and risk management, and governance. The issue and implementation of the Standards marks a significant transformation in the UK's blood transfusion safety governance strategy. Understanding the content and background of the Standards will be beneficial for contemplating and exploring the future direction of China's blood transfusion safety governance strategy.

As the second part of this series, this article summarizes and synthesizes the key aspects of UK Serious Hazards of Transfusion (SHOT), SHOT’s continuous promotion of learning from excellent daily transfusion events over the past six years. This summary is based on an introduction to the holistic approach to improving patient safety—proactively learning from both failures and successes. The covered topics include an overview, definitions, case studies, implementation methods, safety culture, psychological safety in the workplace, civility in work, the use of neutral language, leading and lagging indicators, and compassionate governance. It is hoped that this article will assist domestic colleagues in understanding and studying the strategic significance of the transformation of transfusion safety governance in the UK, and inspire reflection on the strategic development direction of transfusion safety governance in China.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Whole blood, containing all blood components in physiological proportions, is a preferred resuscitative fluid for patients with severe hemorrhage. The preparation, supply, and clinical use of whole blood are more convenient, safe, and effective, offering the advantages of reduced blood utilization and associated costs. In recent years, an increasing number of countries and regions have initiated whole blood transfusion programs. The newly issued "Medical Treatment Specifications for Trauma Patients in Emergencies (2025 Edition)" by China's National Health Commission designates whole blood as the preferred choice for early trauma transfusion. Establishing a priority supply mechanism for whole blood has become a critical task for blood services in China. This paper introduces the recommendations of the European Blood Alliance practical guidance on implementation of a whole blood programme within a blood service, hoping to provide insights and assistance in establishing a priority supply mechanism for whole blood in China.

Objective To evaluate the short-term effects of comprehensive health management interventions for stroke high-risk population screening on the prevention and treatment of ischemic stroke, and to provide reference and basis for improving and exploring health management and prevention strategies for stroke high-risk population. Methods From 2018 to 2022, 13 community health service centers in Jiading District, Shanghai were selected in the present study. Based on information push platform, stroke risk assessment and health intervention follow-up were conducted for community residents through convenience sampling. The residents were divided into a full course intervention group (intervention group) and a routine intervention group (control group) according to different health intervention measures and forms. The incidence of ischemic stroke in the two groups of survey subjects was tracked within 36 months. Results A total of 52144 subjects were included in the study. The total number of patients in the full course intervention group was 14227, with an incidence density of 577.32/100 000 (556.49/100 000-598.12/100 000), which was lower than that of the conventional intervention group (37 917), with an incidence density of 1 485.47/100 000 (1 464.99/100 000-1 505.94/100 000) (χ²=2490.212, P<0.001). The relative risk of the full course intervention group was 0.39, and the relative risk of stroke risk factors in the full course intervention group from low to high was 0.33, 0.43, 0.45, and 0.49, respectively. The incidence density of males in the full course intervention group was 660.76 (627.46/100 000 - 694.05/100 000), with a relative risk of 0.43, and the incidence density of female patients was 509.71/100 000 (483.37/100 000 - 536.05/100 000), with a relative risk of 0.35. The overall incidence density of the population under 62 years old gourp, 62-75 years old group and over 75 years old group was 197.45/100 000 (173.09/100 000 -221.80/100 000), 608.36/100 000 (580.19/100 000-636.54/100 000), and 1 025.06/100 000 (958.51/100 000-1 091.61/100 000), with relative risks of 0.51, 0.44, and 0.38, respectively. Conclusion Comprehensive health management measures can effectively reduce the short-term risk of ischemic stroke, and should be further promoted and improved to enhance the effectiveness of stroke prevention and control.

Objective To investigate the exposure-response relationships and lag effects between air pollutants (PM_2.5, PM₁₀, O₃, and NO₂) and mortality in Jiading District, Shanghai, and to provide a scientific basis for the formulation of environmental health policies. Methods Using an individual-level time-stratified case-crossover design, conditional logistic regression models in conjunction with a distributed lag nonlinear model (DLNM) were employed to analyze the exposure-response relationship and temporal lag patterns of ambient air pollution on resident mortality in Jiading District (1994–2024). Results A total of 59 048 death cases were collected, including 18,701 deaths from cardiovascular diseases and 11 731 deaths from respiratory diseases. PM_2.5 and NO₂ had a significant impact on all-cause mortality, cardiovascular disease mortality, and respiratory disease mortality, with the most significant effects observed within a lag of 0–3 days. PM₁₀ also had some impact on these three types of mortality, but its effect was generally weaker than that of PM_2.5 and NO₂. The exposure-response curves showed that the risk of death increased rapidly with increasing concentrations of PM_2.5 and PM₁₀, while the effect of NO₂ plateaued at higher levels. No significant differences were found across age or gender subgroups. Conclusion Short-term exposure to PM_2.5, PM₁₀, and NO₂ significantly increases all-cause mortality risk in Jiading District, with effects persisting up to 7 days, highlighting the need for enhanced air pollution control measures, particularly targeting fine particulate matter.

This article reviews the history and current status of the development of quality management good practice for blood establishments worldwide, covering its standardization, systematization, formalization, and global harmonization and collaboration. It introduces three international harmonization guidelines for quality management in blood establishments, namely, the WHO Good practices for blood establishments, the EU Good practice guidelines for blood establishments, and the PIC/S Good practices guide for blood establishments and hospital blood banks, with the aim of contributing to the reflection and exploration of directions for revising quality management standards for blood establishments in China.

Objective: To establish a prediction model for high-risk cardiovascular disease (CVD) among residents aged 35 to 75 years, so as to provide the basis for improving CVD prevention and control measures. Methods: Permanent residents aged 35 to 75 years were selected from Dongcheng District, Beijing Municipality using the stratified random sampling method from 2018 to 2023. Demographic information, lifestyle, waist circumference and blood biochemical indicators were collected through questionnaire surveys, physical examinations and laboratory tests. Influencing factors for high-risk CVD among residents aged 35 to 75 years were identified using a multivariable logistic regression model, and a prediction model for high-risk CVD was established. The predictive effect was evaluated using the receiver operating characteristic (ROC) curve. Results: A total of 6 968 individuals were surveyed, including 2 821 males (40.49%) and 4 147 females (59.51%), and had a mean age of (59.92±9.33) years. There were 1 155 high-risk CVD population, with a detection rate of 16.58%. Multivariable logistic regression analysis showed that gender, age, smoking, central obesity, systolic blood pressure, fasting blood glucose, triglyceride and low-density lipoprotein cholesterol were influencing factors for high-risk CVD among residents aged 35 to 75 years (all P<0.05). The area under the ROC curve of the established prediction model was 0.849 (95%CI: 0.834-0.863), with a sensitivity of 0.693 and a specificity of 0.863, indicating good discrimination. Conclusion The model constructed by eight factors including demographic characteristics, lifestyle and blood biochemical indicators has good predictive value for high-risk CVD among residents aged 35 to 75 years.