Objective:To explore the current status of quality of life of rheumatoid arthritis (RA) patients and its influencing factors based on the health ecology model (HEM) , and to provide a scientific basis for the development of health education programs for RA patients.Methods:From November 2023 to April 2024, 230 RA patients in the Department of Rheumatology and Immunology, General Hospital of Ningxia Medical University, were selected for the study using convenience sampling method. Patients were surveyed using the General Information Questionnaire, Quality of Life Instruments for Chronic Diseases in RA (QLICD-RA) , Health Literacy Management Scale, Social Support Rate Scale, Brief Illness Perception Questionnaire, 8-item Morisky Medication Adherence Scale, Pain Catastrophizing Scale, Chronic Disease Self-Management Study Measures, Fear of Progression Questionnaire-Short Form, Tampa Scale for Kinesiophobia and Visual Analogue Scale. Pearson and Spearman correlation was used to analyze the correlation between quality of life and health literacy, social support, disease perception, self-management behaviors, fear of disease progression, fear of exercise, medication adherence, pain catastrophizing, and pain in RA patients. Multiple linear regression was used to analyze the factors influencing the quality of life of RA patients.Results:A total of 230 questionnaires were distributed and 228 valid questionnaires were recovered, with a valid recovery rate of 99.13% (228/230) . The total QLICD-RA score of 228 RA patients was (137.53±27.57) . Duration of disease, disease perception, pain, pain catastrophizing, self-management behavior, joint deformity, morning stiffness duration, gastrointestinal response, sleep, social support, and main economic sources were the factors influencing the quality of life of RA patients ( P<0.05) , explaining 83.6% of the total variance. Conclusions:The quality of life of RA patients is moderate, and its influencing factors are distributed at all levels of HEM. Healthcare professionals can optimize the health education program for the main influencing factors of each layer, focusing on guiding patients to correctly understand the disease, stimulating the subjective initiative of patients, enhancing the ability of patients to actively manage the disease, and improving the quality of life of patients.

Objective:To analyze the clinical characteristics of immune checkpoint inhibitor (ICI)-induced type 1 diabetes (T1D).Methods:This was a retrospective case series study of clinical data from 24 patients with ICI-T1D admitted to People′s Hospital of Henan Provincial between January 2018 and December 2024. The data collected included demographic characteristics, ICI usage, clinical manifestations, laboratory test results, and clinical outcome. Patients were categorized into mild and severe groups based on disease severity. Clinical characteristics between the two groups were compared using the Mann-Whitney U test. Results:Of the 24 patients, 21 (87.5%) were male and 3 (12.5%) were female, with an average age of (62.0±10.6) years. Patients in the severe disease group were significantly older than those in the mild disease group [(68.0±9.5) years vs. (58.4±9.8) years, P<0.05]. Compared to patients with mild disease, those with severe disease had significantly higher rates of impaired consciousness (9/9 vs.2/15), shorter ICI treatment cycles [3 (2, 6) vs. 6 (5, 8)], shorter time from ICI initiation to diabetes diagnosis [68 (31, 168) d vs. 162 (135, 235) d], and shorter time from the onset of diabetes symptoms to medical consultation [4 (2, 5) d vs. 8 (4, 26) d] (all P<0.05). The severe disease group also showed significantly higher blood glucose levels [43.0 (39.1, 57.3) mmol/L vs. 24.6 (19.6, 29.6) mmol/L] and a lower glycated hemoglobin level [6.8% (6.3%, 7.6%) vs. 7.9% (7.6%, 8.6%)], along with a higher incidence of fulminant T1D (8/9 vs. 2/15, all P<0.05). All patients received insulin injection therapy. After discharge, fasting C-peptide levels in 3 patients with mild disease showed a transient increase to 0.26, 0.43, 0.49 nmol/L but declined again after six months. Conclusions:ICI-T1D is characterized by acute onset and rapid progression. Older patients are more likely to develop severe disease. All patients require insulin therapy.

Cognitive frailty, as one of the independent dimensions of frailty syndrome, has received increasing attention from researchers in recent years. Cognitive frailty not only reduces the quality of life for elderly people, but also increases the risk of adverse outcomes such as falls, disabilities, hospitalization, dementia, and death. This article introduces the concept, assessment methods, influencing factors, and intervention measures of cognitive frailty, emphasizing the important role of general practitioners in screening and management of cognitive frailty.

Objective:To investigate the correlation between frailty and immune markers in elderly patients diagnosed with heart failure with preserved ejection fraction(HFpEF).Methods:A total of 416 elderly patients with HFpEF, who were hospitalized in the Department of Geriatrics at Henan Provincial People's Hospital from March 2021 to December 2023, were selected as research subjects.The Fried frailty phenotype was employed to assess frailty.Fasting venous blood samples were collected to measure levels of CD4+ T lymphocytes, CD8+ T lymphocytes, the CD4+ /CD8+ ratio, and immunoglobulins A, M, and G. Spearman correlation analysis and multiple linear regression analysis were conducted to evaluate the relationship between frailty scores and immune markers.Results:Spearman correlation analysis revealed a significant association between frailty score and the CD4+ /CD8+ ratio( r=-0.659, P<0.001), immunoglobulin A( r=-0.454, P<0.001), immunoglobulin M( r=-0.522, P<0.001), and immunoglobulin G( r=-0.802, P<0.001).Furthermore, multiple linear regression analysis indicated that, after adjusting for confounding factors, frailty score served as a significant negative predictor of the CD4+ /CD8+ ratio( β=-0.562, P<0.001), immunoglobulin A( β=-0.366, P<0.001), immunoglobulin M( β=-0.445, P<0.001), and immunoglobulin G( β=-0.772, P<0.001).In comparison to the non-frail group, the frail group exhibited significantly lower values for the CD4+ /CD8+ ratio( β=-0.666, P<0.001)and levels of immunoglobulin A( β=-0.514, P<0.001), immunoglobulin M( β=-0.526, P<0.001), and immunoglobulin G( β=-0.814, P<0.001). Conclusions:In hospitalized elderly patients with heart failure with HFpEF, frailty serves as an independent risk factor for the reduction of the CD4+ /CD8+ ratio, as well as levels of immunoglobulin A, immunoglobulin M, and immunoglobulin G. Furthermore, the frailty score demonstrates a significant negative predictive value for these immunological markers.Therefore, it is essential to enhance our understanding of frailty and to prioritize its prevention and treatment, as this may help mitigate immune dysfunction and promote recovery in elderly patients.

Objective:To explore the current status of quality of life of rheumatoid arthritis (RA) patients and its influencing factors based on the health ecology model (HEM) , and to provide a scientific basis for the development of health education programs for RA patients.Methods:From November 2023 to April 2024, 230 RA patients in the Department of Rheumatology and Immunology, General Hospital of Ningxia Medical University, were selected for the study using convenience sampling method. Patients were surveyed using the General Information Questionnaire, Quality of Life Instruments for Chronic Diseases in RA (QLICD-RA) , Health Literacy Management Scale, Social Support Rate Scale, Brief Illness Perception Questionnaire, 8-item Morisky Medication Adherence Scale, Pain Catastrophizing Scale, Chronic Disease Self-Management Study Measures, Fear of Progression Questionnaire-Short Form, Tampa Scale for Kinesiophobia and Visual Analogue Scale. Pearson and Spearman correlation was used to analyze the correlation between quality of life and health literacy, social support, disease perception, self-management behaviors, fear of disease progression, fear of exercise, medication adherence, pain catastrophizing, and pain in RA patients. Multiple linear regression was used to analyze the factors influencing the quality of life of RA patients.Results:A total of 230 questionnaires were distributed and 228 valid questionnaires were recovered, with a valid recovery rate of 99.13% (228/230) . The total QLICD-RA score of 228 RA patients was (137.53±27.57) . Duration of disease, disease perception, pain, pain catastrophizing, self-management behavior, joint deformity, morning stiffness duration, gastrointestinal response, sleep, social support, and main economic sources were the factors influencing the quality of life of RA patients ( P<0.05) , explaining 83.6% of the total variance. Conclusions:The quality of life of RA patients is moderate, and its influencing factors are distributed at all levels of HEM. Healthcare professionals can optimize the health education program for the main influencing factors of each layer, focusing on guiding patients to correctly understand the disease, stimulating the subjective initiative of patients, enhancing the ability of patients to actively manage the disease, and improving the quality of life of patients.

Cognitive frailty, as one of the independent dimensions of frailty syndrome, has received increasing attention from researchers in recent years. Cognitive frailty not only reduces the quality of life for elderly people, but also increases the risk of adverse outcomes such as falls, disabilities, hospitalization, dementia, and death. This article introduces the concept, assessment methods, influencing factors, and intervention measures of cognitive frailty, emphasizing the important role of general practitioners in screening and management of cognitive frailty.

Objective:To investigate the correlation between frailty and immune markers in elderly patients diagnosed with heart failure with preserved ejection fraction(HFpEF).Methods:A total of 416 elderly patients with HFpEF, who were hospitalized in the Department of Geriatrics at Henan Provincial People's Hospital from March 2021 to December 2023, were selected as research subjects.The Fried frailty phenotype was employed to assess frailty.Fasting venous blood samples were collected to measure levels of CD4+ T lymphocytes, CD8+ T lymphocytes, the CD4+ /CD8+ ratio, and immunoglobulins A, M, and G. Spearman correlation analysis and multiple linear regression analysis were conducted to evaluate the relationship between frailty scores and immune markers.Results:Spearman correlation analysis revealed a significant association between frailty score and the CD4+ /CD8+ ratio( r=-0.659, P<0.001), immunoglobulin A( r=-0.454, P<0.001), immunoglobulin M( r=-0.522, P<0.001), and immunoglobulin G( r=-0.802, P<0.001).Furthermore, multiple linear regression analysis indicated that, after adjusting for confounding factors, frailty score served as a significant negative predictor of the CD4+ /CD8+ ratio( β=-0.562, P<0.001), immunoglobulin A( β=-0.366, P<0.001), immunoglobulin M( β=-0.445, P<0.001), and immunoglobulin G( β=-0.772, P<0.001).In comparison to the non-frail group, the frail group exhibited significantly lower values for the CD4+ /CD8+ ratio( β=-0.666, P<0.001)and levels of immunoglobulin A( β=-0.514, P<0.001), immunoglobulin M( β=-0.526, P<0.001), and immunoglobulin G( β=-0.814, P<0.001). Conclusions:In hospitalized elderly patients with heart failure with HFpEF, frailty serves as an independent risk factor for the reduction of the CD4+ /CD8+ ratio, as well as levels of immunoglobulin A, immunoglobulin M, and immunoglobulin G. Furthermore, the frailty score demonstrates a significant negative predictive value for these immunological markers.Therefore, it is essential to enhance our understanding of frailty and to prioritize its prevention and treatment, as this may help mitigate immune dysfunction and promote recovery in elderly patients.

Objective:To analyze the clinical characteristics of immune checkpoint inhibitor (ICI)-induced type 1 diabetes (T1D).Methods:This was a retrospective case series study of clinical data from 24 patients with ICI-T1D admitted to People′s Hospital of Henan Provincial between January 2018 and December 2024. The data collected included demographic characteristics, ICI usage, clinical manifestations, laboratory test results, and clinical outcome. Patients were categorized into mild and severe groups based on disease severity. Clinical characteristics between the two groups were compared using the Mann-Whitney U test. Results:Of the 24 patients, 21 (87.5%) were male and 3 (12.5%) were female, with an average age of (62.0±10.6) years. Patients in the severe disease group were significantly older than those in the mild disease group [(68.0±9.5) years vs. (58.4±9.8) years, P<0.05]. Compared to patients with mild disease, those with severe disease had significantly higher rates of impaired consciousness (9/9 vs.2/15), shorter ICI treatment cycles [3 (2, 6) vs. 6 (5, 8)], shorter time from ICI initiation to diabetes diagnosis [68 (31, 168) d vs. 162 (135, 235) d], and shorter time from the onset of diabetes symptoms to medical consultation [4 (2, 5) d vs. 8 (4, 26) d] (all P<0.05). The severe disease group also showed significantly higher blood glucose levels [43.0 (39.1, 57.3) mmol/L vs. 24.6 (19.6, 29.6) mmol/L] and a lower glycated hemoglobin level [6.8% (6.3%, 7.6%) vs. 7.9% (7.6%, 8.6%)], along with a higher incidence of fulminant T1D (8/9 vs. 2/15, all P<0.05). All patients received insulin injection therapy. After discharge, fasting C-peptide levels in 3 patients with mild disease showed a transient increase to 0.26, 0.43, 0.49 nmol/L but declined again after six months. Conclusions:ICI-T1D is characterized by acute onset and rapid progression. Older patients are more likely to develop severe disease. All patients require insulin therapy.

Objective To compare the consistency between the estimated values of nine common resting energy expenditure estimation equations and the measured values among the elderly population in pension institutions. Methods A total of 181 elderly individuals from Henan Guangda Ouan Leling Nursing Center were recruited as study objects through cluster sampling. The differences between the estimated values of nine common equations and the measured values obtained by indirect calorimetry were compared, and subgroup analyses were conducted to compare their consistency across different subgroups. Results Among the nine equations, the Cunningham equation and the Owen equation showed relatively small deviations from the measured values, with no significant differences (deviation rates of -1.9% and -2.0%, root mean square errors of 222.7 kcal/d and 239.4 kcal/d, and coincidence rates of 48.4% and 47.5%, respectively). In subgroups stratified by gender and body mass index (BMI), the Cunningham equation showed no significant difference compared with the measured values. The Owen equation showed no significant difference compared with the measured values only in some subgroups [males with BMI of 20~ < 27 kg/m² and ≥27 kg/m², and females with BMI < 20 kg/m²]. Conclusion The Cunningham equation, which utilizes body composition data, can assess the resting energy expenditure of the elderly in pension institutions with relatively high accuracy and speed, demonstrating strong applicability in this population.

OBJECTIVE To study the effects of Zigui yichong formula on premature ovarian insufficiency （POI） in mice through glycolysis metabolic pathway. METHODS Eighty SPF C57BL/6N female mice were divided into normal group， model group， Zigui yichong formula group （14.175 g/kg）， Zigui yichong formula+2-deoxy-D-arabino-hexose （2-DG） group （Zigui yichong formula 14.175 g/kg + glycolysis inhibitor 2-DG 100 mg/kg）， with 20 mice in each group. Except for the normal group， POI model mice were induced by intraperitoneal administration of cyclophosphamide in the other groups. After the model was successfully established， each group was given corresponding drugs. HE staining was employed to observe the pathomorphological changes in ovarian tissue and to count follicles at all developmental stages； radioimmunoassay was conducted to measure the serum levels of estradiol （E2）， anti-Müllerian hormone （AMH）， and follicle-stimulating hormone （FSH）； TUNEL assay was employed to detect apoptosis in ovarian granulosa cells of mice； the activities of hexokinase （HK）， pyruvate kinase （PK） and lactate dehydrogenase （LDH） were detected by colorimetry； Western blot and real-time fluorescence quantitative PCR were employed to analyze the protein and mRNA expressions of B-cell lymphoma-2 （Bcl-2）， Bcl-2 associated X protein （Bax）， caspase-3， HK2， pyruvate kinase M2 （PKM2）， and lactate dehydrogenase A （LDHA）. RESULTS Compared with model group， the number of primordial follicles， growing follicles， antral follicles and granulosa cells were increased significantly（P＜0.05）， and granulosa cells arranged neatly， but the number of atretic follicles and granulosa cells apoptosis were decreased significantly in Zigui yichong formula group （P＜0.05）； the serum levels of E2 and AMH， the activities of HK， PK and LDH， protein and mRNA expressions of Bcl-2， HK2， PKM2 and LDHA were increased significantly （P＜0.05）； the serum levels of FSH， the protein and mRNA expressions of Bax and caspase-3， Bax/Bcl-2 ratio were decreased significantly （P＜0.05）. 2-DG could reverse the improvement effects of Zigui yichong formula on the above indexes of POI model mice. CONCLUSIONS Zigui yichong formula may inhibit the apoptosis of ovarian granulosa cells， reduce follicle atresia and improve ovarian reserve function by promoting glycolysis levels in POI model mice.