Objective:To examine the prevalence of malnutrition and evaluate the impact of nutritional support on clinical outcomes in elderly patients diagnosed with gastric and colorectal cancer.Methods:A retrospective cohort study was conducted, analyzing elderly patients with gastrointestinal tumors who underwent surgical treatment in the general surgery department from January 2019 to June 2020.The Global Leadership Initiative on Malnutrition(GLIM)criteria were utilized to diagnose malnutrition, and the effects of malnutrition and nutritional support on clinical prognosis were investigated.Results:A total of 426 elderly hospitalized patients with gastric and colorectal tumors who underwent surgical treatment were included in this study.This cohort comprised 199 cases of gastric cancer and 227 cases of colorectal cancer, with ages ranging from 65 to 91 years(mean age: 72.05±5.99).According to the GLIM criteria, 43.7%(186/426)of the patients were diagnosed with malnutrition, of which 25.6%(109/426)were moderately malnourished and 18.1%(77/426)were severely malnourished.Among the gastric cancer patients, 73.4%(146/199)were identified as having nutritional risk, with 48.7%(97/199)being malnourished and 22.6%(45/199)experiencing severe malnutrition.In the colorectal cancer group, 63.9%(145/227)were at nutritional risk, 39.2%(89/227)were malnourished, and 14.1%(32/227)had severe malnutrition.Additionally, 60.3%(257/426)of the patients received nutritional support therapy: 25.4%(108/426)received parenteral nutrition(PN), 11.3%(48/426)received enteral nutrition(EN), 23.7%(101/426)received a combination of EN and PN, while 39.7%(169/426)did not receive any nutritional support.Regardless of the presence or degree of malnutrition, patients who received nutritional support had significantly shorter total hospital stays compared to those who did not receive nutritional support, and this difference was statistically significant( t=5.58, 3.69, 2.21, 3.03, all P<0.05). Conclusions:Providing nutritional support to malnourished patients can reduce the length of hospital stay and improve clinical outcomes.

Objective:To investigate the correlation between occupational ionizing radiation exposure and abnormal metabolic indicators, providing a basis for assessing the health risks of occupational ionizing radiation workers and establishing a risk prediction model for chronic metabolic diseases.Methods:In January 2023, 7708 individuals were randomly selected from the occupational health examination data in Zhejiang Province. After excluding 16 individuals due to record errors, 2698 on-the-job workers exposed to ionizing radiation from 2020 to 2021 were selected as the exposure group, 2027 pre-employment workers exposed to ionizing radiation from 2016 to 2022 were selected as the pre-employment control group, and 2967 non-ionizing radiation workers from 2016 to 2022 were selected as the control group. Demographic data, blood routine, urine routine, biochemical indicators, and peripheral blood lymphocyte micronucleus rate of each group were collected. One-way ANOVA and rank sum test were used for comparison of indicators. The exposure group was divided into different groups based on age, exposure duration, and body mass index (BMI), and the correlation between indicators and occupational ionizing radiation was analyzed. Lasso variable selection was conducted by constructing a penalty coefficient (λ), and a complete regression model was established.Results:There were statistically significant differences in indicators such as blood pressure, heart rate, and average hemoglobin concentration between the exposure group and the control group, as well as the pre-employment control group ( P<0.05). Through Lasso variable selection, 19 indicators including exposure length, systolic blood pressure (SBP), diastolic blood pressure (DBP), body weight, body mass index (BMI), urine pH value, red blood cell count, microscopic white blood cells, casts, absolute value of monocytes, mean corpuscular volume of red blood cells, mean hemoglobin concentration, alkaline phosphatase, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, and low-density lipoprotein cholesterol (LDL-C). There were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers of different ages in the exposure group ( P<0.05) ; there were statistically significant differences in SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers with different exposure durations ( P<0.05) ; there were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, red blood cells, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, absolute value of monocytes, mean corpuscular volume of red blood cells, and mean hemoglobin concentration among workers with different BMIs ( P<0.05) . Conclusion:Occupational ionizing radiation is associated with abnormal metabolic indicators such as blood pressure, heart rate, total bile acid, α-L-fucosidase, urea, and creatinine in the human body. More attention should be paid to the risk of chronic metabolic diseases among workers exposed to ionizing radiation.

To evaluate long-term survival and clinical outcomes of patients with knee osteo-arthritis undergoing total knee arthroplasty (TKA) through long-term follow-up.

To analyze the occurrence of early complications after total hip arthroplasty (THA) in patients with systemic lupus erythematosus (SLE).

In recent years, the rapid development of artificial intelligence (AI) has revolutionized the whole-course nutritional management of elderly patients. AI technologies, including machine learning and natural language processing, are capable of efficiently processing vast amounts of multidimensional information such as clinical data, laboratory test results, and imaging findings. For instance, machine learning algorithms can efficiently identify complex nutritional metabolism patterns and accurately predict malnutrition and its trends in elderly patients. Following the standard pathway of "screening, assessment, diagnosis, treatment, and monitoring", AI technology empowers the whole-course nutritional management for elderly patients, forming a refined, data-driven management model, and shows great potential in improving the nutritional status of elderly patients, enhancing treatment outcomes, and promoting elderly health.

Objective:To evaluate the effectiveness of the Total Nutritional Therapy (TNT) course initiated by the Chinese Society for Parenteral and Enteral Nutrition (CSPEN) over the 20 years since its implementation in China.Methods:Participants who attended the CSPEN-organized TNT course between 2005 and 2024 were randomly selected as survey subjects. A four-level questionnaire (reaction, learning, behavior, and results) was developed via expert consensus, based on the Kirkpatrick model. An electronic link to the survey, created via Wenjuanxing, was distributed to invite participants to complete the questionnaire.Results:A total of 1,548 healthcare professionals from various specialties who had received TNT course participated in the online survey. Over 93% of participants reported improvements in theoretical knowledge and 94% in enhanced clinical diagnosis and treatment capabilities. Additionally, 65.4% of participants reported a "significant" or "noticeable" increase in the frequency of nutritional screening and assessments, with the frequency of nutritional support therapy utilization increased by 91.2%. Furthermore, 52.6% of respondents perceived a "significant" or "noticeable" career advancement, particularly in professional title promotion and international academic exchanges. The TNT course also positively impacted discipline development and management: 63.6% of the trainees' hospitals established clinical nutrition departments, 58.98% opened nutrition outpatient clinics, and 56.9% formed nutrition support teams. The adoption rate of standardized procedures, such as nutritional screening, exceeded 92.5% in relevant departments.Conclusions:Over the past 20 years, the CSPEN-led TNT course has successfully established a virtuous cycle of "knowledge dissemination–practice transformation–system innovation" in China. It has played a positive role in enhancing the professional competencies of healthcare workers and promoting the development of clinical nutrition as a discipline.

Objective:To investigate the relationship between dynamic alterations in serum albumin (ALB) concentrations and clinical outcomes in hospitalized surgical patients, thus providing a basis for optimizing clinical management strategies.Methods:This study utilized data from a prospective observational cohort study on nutritional status among 7 122 elderly hospitalized patients across 34 tertiary hospitals in 18 Chinese cities. A total of 1 714 surgical patients hospitalized for 7-30 days with complete data were included. Standardized protocols were used to collect demographic data, clinical outcomes, and a range of laboratory results, including nutritional and hematological parameters. Heterogeneous effects of ALB on clinical outcomes were explored. Receiver operating characteristic (ROC) curves were used to determine cutoff values for infection-related complications. Correlation analyses and multiple linear regression models were used to identify independent predictors of the absolute change in ALB (?ALB).Results:Among the surgical patients, 69.7% (1 195/1 714) experienced a decline in ALB levels during their hospital stay, which was significantly associated with the occurrence of both infection- and non-infection-related complications. Simultaneously, a marked decrease in ALB was also significantly correlated with changes in nutritional and inflammatory status during hospitalization, worsening of gastrointestinal symptoms at discharge, and functional activity abnormalities (all P<0.05). ?ALB exhibited a close association with outcome variables such as infection-related complications. Based on the incidence of infection-related complications, a cutoff value for ALB was calculated, dividing patients into a high-risk group ( n=179) and a low-risk group ( n=1 535), and a statistically significant difference in the incidence of infection-related complications was found between these two groups ( P<0.05). Correlation analysis and multiple linear regression modeling revealed that female gender, a higher baseline ALB level, a poorer baseline inflammatory status, an exacerbation of inflammatory status, larger alterations in platelet-to-lymphocyte ratio, and the presence of infection-related complications were predictive factors for a decline in ALB levels among surgical patients during their hospital stay. Conclusions:?ALB serves as a critical indicator of the inflammatory-nutritional interplay, with its magnitude of decline effectively predicting clinical outcomes and nutritional status changes and guiding multidisciplinary interventions in surgical patients.

The high prevalence of frailty in older adults and its close link to adverse outcomes make it a critical public health challenge in the aging global population. Frailty, characterized by multisystem functional decline, significantly increases the risk of falls, disability, and even death, yet its underlying mechanisms remain poorly understood. While the role of gut microbiota as the "second genome" in disease regulation has been widely recognized, its specific mechanisms in the development of frailty syndrome remain to be systematically investigated. This review synthesizes findings from the last decade of international literature to analyze the mechanisms by which gut microbiota dysbiosis contributes to frailty syndrome. We focus on pathways including metabolic disorders, chronic inflammation, oxidative stress, and the oral-gut microbiota axis, aiming to provide insights for clinical diagnosis and treatment.

Micronutrients (MNs), including vitamins and trace elements, are essential for maintaining normal human metabolism and promoting postoperative recovery. Surgical procedures, especially those involving the digestive tract, may alter the structure and function of the gastrointestinal tract, thereby affecting the digestion and absorption of MNs and leading to deficiencies in various MNs. Perioperative MN intervention is an important strategy for preventing and treating postoperative malnutrition in surgical patients. This article reviews recent domestic and international research, summarizing and analyzing the current status of perioperative MN deficiencies in surgical patients, specific deficiency manifestations after different surgeries, impact of MN supplementation on postoperative recovery, and nutritional management measures. The aim is to provide more precise and scientific nutritional intervention strategies for clinical practice, promoting comprehensive recovery of patients.

Metabolic and bariatric surgery (MBS) is an effective treatment for obesity as it can dramatically reduce body weight and improve obesity-related comorbidities. However, postoperative changes from MBS can impair gastrointestinal structure and function, leading to micronutrient (MN) deficiencies and potentially severe organ dysfunction. MNs, including vitamins and trace elements, are crucial for human metabolism and can influence disease progression and outcomes. By reviewing the domestic and international literature in the past 5 years, we summarized and analyzed MN changles and nutritional management after various MBS procedures, aiming to further inform clinical practice.