Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Septic shock is the primary cause of mortality in sepsis, with its core pathophysiological mechanism being severe ischemia and hypoxia in critical units—composed of microcirculation and the mitochondria of functional cells—resulting from disruptions in blood flow and oxygen flow following a dysregulated host response. Due to the systemically convergent yet clinically heterogeneous nature of the host response, current understanding and management strategies for hemodynamics remain inconsistent, often leading to inadequate resuscitation or overtreatment. To improve the quality of care, based on a systematic review of the "blood flow-oxygen flow" theory, an expert panel emphasizes reevaluating septic shock from an integrated perspective of blood flow and oxygen flow, and has formulated the Expert Consensus on Blood Flow and Oxygen Delivery Phenotyping and Clinical Management of Septic Shock (2025). The consensus proposes that clinical typing of blood flow-oxygen flow should comprehensively consider cardiac function, vascular tone, oxygen flow utilization status in critical units, and disease trajectory, while optimizing subtype identification by integrating host response phenotypes and artificial intelligence technologies. It advocates establishing a continuous assessment system through multi-site oxygen flow monitoring for organ perfusion, peripheral perfusion monitoring, and critical care ultrasound. Under the framework of the "critical care triangle", the consensus promotes the implementation of individualized, bundled management strategies, providing guidance for multiple management points to restore blood flow-oxygen flow matching, reduce the risk of organ failure, and decrease patient mortality.

With the rapid advancement of hemodynamic indices and monitoring technologies, their classification methods and application processes have become increasingly complex. Currently, no unified standard hasbeen established, making it difficult to fully meet the clinical requirements for hemodynamic management. To assist in hemodynamic monitoring assessment and therapeutic decision-making in critically ill patients, the Critical Hemodynamic Therapy Collaborative Group, in conjunction with the Critical Ultrasound Study Group, has jointly developed the Standard for the Application of Hemodynamic Monitoring Techniques in Critical Care. The first part of this standard systematically categorizes hemodynamic indicators into flow indicators, pressure and its derivative indicators, and tissue perfusion indicators, while elaborating on the clinical application of each. The second part establishes a standardized clinical implementation pathway for hemodynamic monitoring. It proposes a tiered monitoring strategy-comprising basic, advanced, indication-specific, and special scenario monitoring-tailored to different clinical settings. It emphasizes the central role of critical care ultrasound across all levels of monitoring and establishes hemodynamic assessment standards for organs such as the brain, kidneys, and gastrointestinal tract. This standard aims to provide a unified framework for clinical practice, teaching, training, and research in critical care medicine, thereby promoting standardized development within the discipline.

Objective:To study the risk factors and dosiomics-based prediction model of bone marrow suppression in patients with esophageal cancer during radiotherapy.Methods:Clinic data and radiotherapy planning documents of 107 patients with oesophageal cancer who underwent radiotherapy at the First Affiliated Hospital of Nanjing Medical University from January 2021 to May 2024 were retrospectively analyzed. Blood test results before and during radiotherapy were collected, and patients were classified into myelosuppressive groups (≤grade 1 and ≥grade 2). Clinical features, traditional dosimetric features and dosiomics features were collected, respectively. According to the stratified randomization grouping method, all patients were divided into the training and test sets in a 7 vs. 3 ratio. The region of interest was obtained by automatically outlining the thoracic skeleton (including the sternum, thoracic vertebrae and ribs) by AccuContour software. Dosiomics features were extracted from the dose distribution of the thoracic skeleton, and these features were screened using the independent samples t-test, the muse selector and the least absolute shrinkage operator. Subsequently, the dosiomic scores were calculated. Statistically significant clinical characteristics were screened using univariate and multivariate logistic regression analyses. Support vector machine method was used to construct a clinical model and a clinical combined with dosiomic model. Subsequently, nomogram was drawn for clinical prediction. The clinical efficacy and clinical benefit of predictive model were assessed by plotting the receiver operating characteristic (ROC) curve and evaluating its performance through the area under the ROC curve (AUC), the calibration curve and decision curve analysis (DCA). Results:Thirteen dosiomic features associated with bone marrow suppression were screened. Based on both univariate and multivariate logistic regression analyses, simultaneous chemotherapy, V 35 Gy and the average dose to bone were identified as statistically significant clinical predictors (all P<0.05). The AUC values of the combined model in the training and test sets were 0.800 and 0.776, higher than 0.709 and 0.650 of the clinical model. The calibration curves showed good agreement between the predicted and actual probabilities of the combined model. The DCA results showed that the net clinical benefit of the combined model was higher than that of the clinical model. Conclusions:The combined dosiomics-based model is effective in improving the predictive performance of bone marrow suppression occurring after radiotherapy for esophageal cancer.

Objective:To investigate the clinical features and prognostic factors of newly-treated elderly acute myeloid leukemia (AML) patients with intermediate-risk karyotype.Methods:A retrospective case series study was conducted. A total of 87 newly-treated elderly AML patients with intermediate-risk karyotype in the First Affiliated Hospital of University of Science and Technology of China (Anhui Provincial Hospital) from January 2013 to December 2023 were selected. The clinical characteristics were summarized. The Kaplan-Meier method was used for survival analysis and Cox proportional hazards model was used to make univariate and multivariate analyses of prognostic factors.Results:The median age [ M ( Q1, Q3)] of 87 patients was 69 (60, 87) years. The patients with normal karyotype and abnormal karyotype accounted for 77.1% (67/87), 22.9% (20/87), respectively. A total of 74 patients (85.1%) had 1 or more gene mutations, of which FLT3-ITD, NPM1 mutation, CEBPA mutation and WT1 high expression accounted for 29.9% (26/87), 26.4% (23/87), 19.5% (17/87), and 65.5% (57/87), respectively; additionally, 44.7% (39/87) of patients had 2 or more gene mutations. The objective response rate of patients after induction therapy was 47.7% (41/87), while the relapse rate was 73.2% (30/41). The median progression-free survival (PFS) time was 7.8 months, and the median overall survival (OS) time was 12.1 months. Univariate analysis result revealed that age, FLT3-ITD, hypomethylating agents, and minimal residual disease complete remission (MDR-CR) were factors influencing the OS of newly-treated elderly AML patients with intermediate-risk karyotype (all P < 0.05). Multivariate analysis indicated that MDR-CR was an independent risk factor for OS (yes vs. no: HR = 0.27, 95% CI: 0.14-0.51, P < 0.001). Conclusions:Newly-treated elderly AML patients with intermediate-risk karyotype have a high relapse rate and poor prognosis, and MDR-CR is identified as an independent influencing factor for the prognosis of these patients.

Medication literacy directly impacts the safety of drug therapy and clinical outcomes.Patients with low medication literacy demonstrate poorer medication adherence,higher medication risks,and inferior disease control outcomes.Chronic disease patients face significant medication safety hazards due to multimorbidity and polypharmacy.Accurately assessing medication literacy can quantify individual medication capabilities and promote safe medication management.This paper reviews the structure,methods,applicable population,current applications,advantages,and limitations of medication literacy assessment tools for chronic disease patients,both domestically and internationally.The aim is to provide references for developing and applying medication literacy assessment tools for patients in China,offering a basis for scientifically evaluating medication literacy levels and formulating medication safety intervention strategies.

Objective:To investigate the awareness of medical staff on pharmacovigilance and the current situation of the construction of pharmacovigilance system in medical institutions.Methods:A self-designed questionnaire was sent to medical institutions in China through Professional Committee on Pharmacovigilance Research, China Society for Drug Regulation in the form of Wechat, and medical staff participated voluntarily. The contents of the questionnaire included 23 questions in 4 dimensions, including the basic information of the respondents, their understanding of the concept and regulations of pharmacovigilance, the management of pharmacovigilance, and the reporting and feedback of adverse drug reactions(ADRs)/events in their medical institutions. The survey time was from August 18, 2023 to October 18, 2023. The data from the questionnaire were analyzed descriptively.Results:The collected questionnaires were from medical institutions in 31 provinces, autonomous regions, and municipalities directly under the central government, with a total of over 100 questionnaires collected in each region. A total of 10 991 medical staff participated in the survey, including 5 504 pharmacists, 2 120 doctors, and 3 367 nurses. Among them, 10 131 (92.18%) respondents had heard of pharmacovigilance, 4 511 (41.04%) had participated in pharmacovigilance-related works, 9 368 respondents (86.41%) answered that the ADRs monitoring and management system had been established in medical institutions where they worked, 8 186 respondents (75.51%) answered that leading group for pharmacovigilance (including ADRs monitoring) had been set up in the medical institutions where they worked, 8 605 respondents (79.37%) answered that the pharmacovigilance works was managed by special personnel in the institutions where they worked, 7 859 (72.49%) answered that there were liaison officers in the clinical departments where they worked, 6 043 (55.74%) answered that the individuals would be rewarded for reporting ADRs, 4 809 (44.36%) answered that pharmacovigilance had been included in the daily works and assessment indicators of the departments, and 5 351 (49.36%) answered that reports of ADRs were reviewed by special personnel. Active reporting by medical staff was the main collection channel of ADRs, 3 391 (31.28%) answered they had actively captured ADRs from the hospital information system, and 7 728 (71.28%) answered they had reported ADRs through the hospital information system, 10 061 (92.81%) answered that the monitoring results of ADRs would be regularly fed back in the hospitals where they worked, and 6 239 (57.55%) answered that regular training on pharmacovigilance for all medical staff would be provided in the institutions where they worked.Conclusions:Medical staff have generally heard of pharmacovigilance and are aware of the national pharmacovigilance system, but they still have insufficient understanding of the concept and regulations of pharmacovigilance. The degree of participating in pharmacovigilance works of medical staff in different regions are different. The monitoring and management of ADRs could be paid attention to in the most medical institutions, but the degree of improvement of pharmacovigilance system in different levels of medical institutions is different.

Medication literacy directly impacts the safety of drug therapy and clinical outcomes.Patients with low medication literacy demonstrate poorer medication adherence,higher medication risks,and inferior disease control outcomes.Chronic disease patients face significant medication safety hazards due to multimorbidity and polypharmacy.Accurately assessing medication literacy can quantify individual medication capabilities and promote safe medication management.This paper reviews the structure,methods,applicable population,current applications,advantages,and limitations of medication literacy assessment tools for chronic disease patients,both domestically and internationally.The aim is to provide references for developing and applying medication literacy assessment tools for patients in China,offering a basis for scientifically evaluating medication literacy levels and formulating medication safety intervention strategies.

Objective:To investigate the awareness of medical staff on pharmacovigilance and the current situation of the construction of pharmacovigilance system in medical institutions.Methods:A self-designed questionnaire was sent to medical institutions in China through Professional Committee on Pharmacovigilance Research, China Society for Drug Regulation in the form of Wechat, and medical staff participated voluntarily. The contents of the questionnaire included 23 questions in 4 dimensions, including the basic information of the respondents, their understanding of the concept and regulations of pharmacovigilance, the management of pharmacovigilance, and the reporting and feedback of adverse drug reactions(ADRs)/events in their medical institutions. The survey time was from August 18, 2023 to October 18, 2023. The data from the questionnaire were analyzed descriptively.Results:The collected questionnaires were from medical institutions in 31 provinces, autonomous regions, and municipalities directly under the central government, with a total of over 100 questionnaires collected in each region. A total of 10 991 medical staff participated in the survey, including 5 504 pharmacists, 2 120 doctors, and 3 367 nurses. Among them, 10 131 (92.18%) respondents had heard of pharmacovigilance, 4 511 (41.04%) had participated in pharmacovigilance-related works, 9 368 respondents (86.41%) answered that the ADRs monitoring and management system had been established in medical institutions where they worked, 8 186 respondents (75.51%) answered that leading group for pharmacovigilance (including ADRs monitoring) had been set up in the medical institutions where they worked, 8 605 respondents (79.37%) answered that the pharmacovigilance works was managed by special personnel in the institutions where they worked, 7 859 (72.49%) answered that there were liaison officers in the clinical departments where they worked, 6 043 (55.74%) answered that the individuals would be rewarded for reporting ADRs, 4 809 (44.36%) answered that pharmacovigilance had been included in the daily works and assessment indicators of the departments, and 5 351 (49.36%) answered that reports of ADRs were reviewed by special personnel. Active reporting by medical staff was the main collection channel of ADRs, 3 391 (31.28%) answered they had actively captured ADRs from the hospital information system, and 7 728 (71.28%) answered they had reported ADRs through the hospital information system, 10 061 (92.81%) answered that the monitoring results of ADRs would be regularly fed back in the hospitals where they worked, and 6 239 (57.55%) answered that regular training on pharmacovigilance for all medical staff would be provided in the institutions where they worked.Conclusions:Medical staff have generally heard of pharmacovigilance and are aware of the national pharmacovigilance system, but they still have insufficient understanding of the concept and regulations of pharmacovigilance. The degree of participating in pharmacovigilance works of medical staff in different regions are different. The monitoring and management of ADRs could be paid attention to in the most medical institutions, but the degree of improvement of pharmacovigilance system in different levels of medical institutions is different.

Objective:To study the risk factors and dosiomics-based prediction model of bone marrow suppression in patients with esophageal cancer during radiotherapy.Methods:Clinic data and radiotherapy planning documents of 107 patients with oesophageal cancer who underwent radiotherapy at the First Affiliated Hospital of Nanjing Medical University from January 2021 to May 2024 were retrospectively analyzed. Blood test results before and during radiotherapy were collected, and patients were classified into myelosuppressive groups (≤grade 1 and ≥grade 2). Clinical features, traditional dosimetric features and dosiomics features were collected, respectively. According to the stratified randomization grouping method, all patients were divided into the training and test sets in a 7 vs. 3 ratio. The region of interest was obtained by automatically outlining the thoracic skeleton (including the sternum, thoracic vertebrae and ribs) by AccuContour software. Dosiomics features were extracted from the dose distribution of the thoracic skeleton, and these features were screened using the independent samples t-test, the muse selector and the least absolute shrinkage operator. Subsequently, the dosiomic scores were calculated. Statistically significant clinical characteristics were screened using univariate and multivariate logistic regression analyses. Support vector machine method was used to construct a clinical model and a clinical combined with dosiomic model. Subsequently, nomogram was drawn for clinical prediction. The clinical efficacy and clinical benefit of predictive model were assessed by plotting the receiver operating characteristic (ROC) curve and evaluating its performance through the area under the ROC curve (AUC), the calibration curve and decision curve analysis (DCA). Results:Thirteen dosiomic features associated with bone marrow suppression were screened. Based on both univariate and multivariate logistic regression analyses, simultaneous chemotherapy, V 35 Gy and the average dose to bone were identified as statistically significant clinical predictors (all P<0.05). The AUC values of the combined model in the training and test sets were 0.800 and 0.776, higher than 0.709 and 0.650 of the clinical model. The calibration curves showed good agreement between the predicted and actual probabilities of the combined model. The DCA results showed that the net clinical benefit of the combined model was higher than that of the clinical model. Conclusions:The combined dosiomics-based model is effective in improving the predictive performance of bone marrow suppression occurring after radiotherapy for esophageal cancer.

Objective:To explore the feasibility of predicting complexity of intensity modulated radiotherapy(IMRT)plan through adopted machine learning method to extract planomics features of radiotherapy,so as to provide a new method for comprehensive evaluation of the complexity of IMRT plan.Methods:The medical case data of 3203 patients with pelvic tumor,or abdominal tumor or head and neck tumor,who admitted to The First Affiliated Hospital with Nanjing Medical University from December 2022 to November 2023,were selected.All patients adopted Monaco system to conduct design for plan,and underwent treatment on Precise and Axesse accelerators.The evaluation indicator of complexity of 10 plans was calculated by using Python software,and the planomics features in the files of radiotherapy plans were extracted through format conversion and pyradiomics tool of imaging omics.The planomics features of radiotherapy were selected through data cleaning,filtering method and embedding method of machine learning.The corresponding predictive model of the evaluation indicator of complexity of 10 common plans was respectively constructed through used Gradient Boosting Decision Tree algorithm.The goodness of fit(R2)was adopted to evaluate the prediction performance of the model,and the 5-fold cross-validation method was adopted to detect the generalization ability of the model.Results:There were statistically significant differences between Precise accelerator and Axesse accelerator in average leaf to area(LA),plan irregularity(PI)of beam shape and standard circle,modulation complexity score(MCS)of the variability between shape and area of subfield,and the advantage value of leaf travel(LT)(t=63.894,-63.678,72.582,-48.858,P＜0.01),respectively.A total of 107 planomics features were extracted through pyradiomics tool,and 38 features were remained after filtering method conducted screening,and 4 to 11 features were remained after embedding method conducted screening.The goodness of fits of mean field area(MFA),LA and leaf gap average(LGA)value were better in the validation set,with R2＞0.970,however the goodness of fits of the proportion of small aperture score 20 mm(SAS20)was poor in validation set,with R2=0.917.The 5-fold cross-validation results showed that the average value of prediction accuracy of all indicators of complexity was＞90％.Conclusions:The extracted planomics features of radiotherapy based on radiomics method can accurately predict the complexity of IMRT plan,which are expected to play a greater role in improving the ensure efficiency of individual quality of patient,and screening radiotherapy plan with higher-quality.