Objective To screen the risk factors for hypoglycemia in adult intensive care unit(ICU)patients,construct a risk prediction model,and validate its predictive effect.Methods A retrospective study was conducted on adult critically ill patients admitted to the general ICU of Hospital of Chengdu University of Traditional Chinese Medicine from December 2023 to September 2024.Patients admitted from December 2023 to June 2024 served as the modeling group,and those from July to September 2024 as the validation group.A total of 928 patients were included,with 650 in the modeling group and 278 in the validation group.After literature review and expert consultation,27 potential risk factors for hypoglycemia in ICU patients were initially screened,and data were collected including general information[gender,age,acute physiology and chronic health evaluation Ⅱ(APACHEⅡ)score,sequential organ failure assessment(SOFA)score,nutrition risk in critically ill(NUTRIC)score,mechanical ventilation status,hemodialysis status,enteral nutrition status],disease data(sepsis,liver disease history,kidney disease history,diabetes history,hypoglycemia history),blood glucose-related indicators[mean blood glucose,blood glucose coefficient of variation,insulin dosage,intravenous insulin titration use,inotropic drug use,insulin secretagogues(Sulfonylureas and Glinides),and combined use of hypoglycemic drugs(two or more)],and laboratory indicators[serum creatinine(SCr),blood urea nitrogen(BUN),serum albumin(Alb),alanine aminotransferase(ALT),aspartate aminotransferase(AST),total bilirubin(TBil),glomerular filtration rate(GFR)].The patients were divided into a hypoglycemia group and a non-hypoglycemia group based on the occurrence of hypoglycemia.Univariate analysis and binary Logistic regression analysis were used to identify influencing factors of hypoglycemia in adult ICU patients,and a nomogram prediction model was constructed.The area under the receiver operator characteristic curve(AUC)and calibration curves were employed to evaluate the discrimination and calibration of the model.Results The modeling cohort included 552 non-hypoglycemic patients and 98 hypoglycemic patients,with an ICU hypoglycemia incidence rate of 15.1％.Compared with the hypoglycemia group,the non-hypoglycemia group showed significantly lower proportions of patients with renal disease history,diabetes history,hypoglycemia history,undergoing hemodialysis,using intravenous insulin titration,and combined use of hypoglycemic drugs,as well as lower blood glucose coefficient of variation,lower APACHEⅡ scores,and significantly elevated GFR(all P<0.05).Binary Logistic regression analysis was performed using the 9 variables with statistically significant differences in univariate analysis as independent variables and hypoglycemia occurrence as the dependent variable.The results indicated that a history of diabetes,a history of hypoglycemia,APACHEⅡ score,GFR,blood glucose coefficient of variation,and combined use of hypoglycemic drugs were independent risk factors for hypoglycemia in ICU patients[odds ratios(OR)were 1.761,2.095,1.048,0.990,1.029,and 1.975,respectively,and 95％confidence intervals(95％CI)were 1.052-2.949,1.220-3.600,1.022-1.074,0.982-0.997,1.013-1.046,and 1.145-3.408,respectively.The corresponding Pvalues were 0.031,0.007,0.000,0.009,<0.001,0.014].A nomogram prediction model for hypoglycemia in ICU patients was constructed using six independent predictors selected through binary logistic regression analysis.The ROC curve AUC for the modeling group was 0.884(95％CI 0.826-0.941,P=0.250),with a maximum Youden index of 0.713,sensitivity of 92.1％,and specificity of 79.2％.The validation cohort included 38 patients with hypoglycemia and 240 patients without hypoglycemia.Compared with the hypoglycemia group,the non-hypoglycemia group showed significantly lower proportions of patients with a history of diabetes,a history of hypoglycemia,and combined use of hypoglycemic drugs,as well as lower APACHEⅡ scores and lower blood glucose coefficient of variation,with significantly increased GFR(all P<0.05).The ROC curve AUC for the validation cohort was 0.803(95％CI was 0.757-0.849,P=0.138),indicating high discriminatory ability.The predicted probability at the diagnostic cutoff point was P=0.138.The model's diagnostic threshold for predicted probability was P=0.138,while the optimal cut-off value based on the Youden index was 0.513,yielding a sensitivity of 76.5％and specificity of 74.8％,indicating predictive value for hypoglycemia in adult ICU patients.The mean absolute error(MAE)results for the modeling group and validation group were<0.05.The calibration curves of both the modeling and validation groups showed close alignment with the ideal curve,indicating excellent calibration performance of the model.Conclusion The constructed hypoglycemia risk prediction model for adult ICU patients has good predictive performance,which can quickly identify high-risk populations of hypoglycemia in ICU and provide reference for clinical preventive nursing.

Depressive disorder is widely stigmatized worldwide. Stigma associated with depressive disorder has become an essential obstacle in the rehabilitation of patients. This paper summarizes the generation, measurement tools, influencing factors, and intervention measures of depressive disorder-related stigma, aiming to provide a reference for conducting research on depressive disorder-related stigma and formulating intervention measures for depressive disorder-related stigma.

OBJECTIVE To explore the current status,etiological characteristics and risk factors for nosocomial in-fections in the patients who are treated with extracorporeal membrane oxygenation(ECMO)so as to provide bases for treatment and prevention of nosocomial infections in the ICU patients treated with ECMO.METHODS The clinical data were retrospectively collected from the patients who were treated with ECMO in the ICU of Xinyang Central Hospital from Jan.2021 to Dec.2023.The patients were divided into the infection group and the non-infec-tion group according the status of nosocomial infection during the ECMO treatment period.The constituent ratios of pathogens isolated from the patients with infections were recorded,and multivariate logistic regression analysis was performed for independent risk factors for the ECMO-related nosocomial infections.RESULTS Of 86 patients who were finally enrolled in the study,33(38.37％)had nosocomial infections.Totally 54 strains of pathogens were isolated from the patients with the infections,43(79.63％)of which were gram-negative bacteria,7(12.97％)were gram-positive bacteria,and 4(7.41％)were fungi.There were 36(66.67％)strains of multi-drug-resistant organisms(MDROs)among the 54 strains of pathogens,and 27(81.82％)patients were detected with MDROs.Among the ECMO patients with postoperative nosocomial infections,21(63.64％)cases had pul-monary infections,8(24.24％)cases had bloodstream infection,and 4(12.12％)had urinary system infections.Multivariate logistic analysis showed that the high blood glucose level at the beginning of treatment with ECMO,long duration of ECMO treatment and long time of central venous catheter indwelling were the independent risk factors for the nosocomial infections in the patients treated with ECMO(P＜0.05).CONCLUSION The isolation rate of gram-negative bacteria is relatively high among the pathogens isolated from the ECMO patients with post-operative nosocomial infections,and the drug resistance rates are high.The high blood glucose level,long duration of ECMO supporting treatment and long time of central venous catheter indwelling are the independent risk factors for the nosocomial infections in the patients treated with ECMO.

OBJECTIVE To explore the current status,etiological characteristics and risk factors for nosocomial in-fections in the patients who are treated with extracorporeal membrane oxygenation(ECMO)so as to provide bases for treatment and prevention of nosocomial infections in the ICU patients treated with ECMO.METHODS The clinical data were retrospectively collected from the patients who were treated with ECMO in the ICU of Xinyang Central Hospital from Jan.2021 to Dec.2023.The patients were divided into the infection group and the non-infec-tion group according the status of nosocomial infection during the ECMO treatment period.The constituent ratios of pathogens isolated from the patients with infections were recorded,and multivariate logistic regression analysis was performed for independent risk factors for the ECMO-related nosocomial infections.RESULTS Of 86 patients who were finally enrolled in the study,33(38.37％)had nosocomial infections.Totally 54 strains of pathogens were isolated from the patients with the infections,43(79.63％)of which were gram-negative bacteria,7(12.97％)were gram-positive bacteria,and 4(7.41％)were fungi.There were 36(66.67％)strains of multi-drug-resistant organisms(MDROs)among the 54 strains of pathogens,and 27(81.82％)patients were detected with MDROs.Among the ECMO patients with postoperative nosocomial infections,21(63.64％)cases had pul-monary infections,8(24.24％)cases had bloodstream infection,and 4(12.12％)had urinary system infections.Multivariate logistic analysis showed that the high blood glucose level at the beginning of treatment with ECMO,long duration of ECMO treatment and long time of central venous catheter indwelling were the independent risk factors for the nosocomial infections in the patients treated with ECMO(P＜0.05).CONCLUSION The isolation rate of gram-negative bacteria is relatively high among the pathogens isolated from the ECMO patients with post-operative nosocomial infections,and the drug resistance rates are high.The high blood glucose level,long duration of ECMO supporting treatment and long time of central venous catheter indwelling are the independent risk factors for the nosocomial infections in the patients treated with ECMO.

Depressive disorder is widely stigmatized worldwide. Stigma associated with depressive disorder has become an essential obstacle in the rehabilitation of patients. This paper summarizes the generation, measurement tools, influencing factors, and intervention measures of depressive disorder-related stigma, aiming to provide a reference for conducting research on depressive disorder-related stigma and formulating intervention measures for depressive disorder-related stigma.

Objective To screen the risk factors for hypoglycemia in adult intensive care unit(ICU)patients,construct a risk prediction model,and validate its predictive effect.Methods A retrospective study was conducted on adult critically ill patients admitted to the general ICU of Hospital of Chengdu University of Traditional Chinese Medicine from December 2023 to September 2024.Patients admitted from December 2023 to June 2024 served as the modeling group,and those from July to September 2024 as the validation group.A total of 928 patients were included,with 650 in the modeling group and 278 in the validation group.After literature review and expert consultation,27 potential risk factors for hypoglycemia in ICU patients were initially screened,and data were collected including general information[gender,age,acute physiology and chronic health evaluation Ⅱ(APACHEⅡ)score,sequential organ failure assessment(SOFA)score,nutrition risk in critically ill(NUTRIC)score,mechanical ventilation status,hemodialysis status,enteral nutrition status],disease data(sepsis,liver disease history,kidney disease history,diabetes history,hypoglycemia history),blood glucose-related indicators[mean blood glucose,blood glucose coefficient of variation,insulin dosage,intravenous insulin titration use,inotropic drug use,insulin secretagogues(Sulfonylureas and Glinides),and combined use of hypoglycemic drugs(two or more)],and laboratory indicators[serum creatinine(SCr),blood urea nitrogen(BUN),serum albumin(Alb),alanine aminotransferase(ALT),aspartate aminotransferase(AST),total bilirubin(TBil),glomerular filtration rate(GFR)].The patients were divided into a hypoglycemia group and a non-hypoglycemia group based on the occurrence of hypoglycemia.Univariate analysis and binary Logistic regression analysis were used to identify influencing factors of hypoglycemia in adult ICU patients,and a nomogram prediction model was constructed.The area under the receiver operator characteristic curve(AUC)and calibration curves were employed to evaluate the discrimination and calibration of the model.Results The modeling cohort included 552 non-hypoglycemic patients and 98 hypoglycemic patients,with an ICU hypoglycemia incidence rate of 15.1％.Compared with the hypoglycemia group,the non-hypoglycemia group showed significantly lower proportions of patients with renal disease history,diabetes history,hypoglycemia history,undergoing hemodialysis,using intravenous insulin titration,and combined use of hypoglycemic drugs,as well as lower blood glucose coefficient of variation,lower APACHEⅡ scores,and significantly elevated GFR(all P<0.05).Binary Logistic regression analysis was performed using the 9 variables with statistically significant differences in univariate analysis as independent variables and hypoglycemia occurrence as the dependent variable.The results indicated that a history of diabetes,a history of hypoglycemia,APACHEⅡ score,GFR,blood glucose coefficient of variation,and combined use of hypoglycemic drugs were independent risk factors for hypoglycemia in ICU patients[odds ratios(OR)were 1.761,2.095,1.048,0.990,1.029,and 1.975,respectively,and 95％confidence intervals(95％CI)were 1.052-2.949,1.220-3.600,1.022-1.074,0.982-0.997,1.013-1.046,and 1.145-3.408,respectively.The corresponding Pvalues were 0.031,0.007,0.000,0.009,<0.001,0.014].A nomogram prediction model for hypoglycemia in ICU patients was constructed using six independent predictors selected through binary logistic regression analysis.The ROC curve AUC for the modeling group was 0.884(95％CI 0.826-0.941,P=0.250),with a maximum Youden index of 0.713,sensitivity of 92.1％,and specificity of 79.2％.The validation cohort included 38 patients with hypoglycemia and 240 patients without hypoglycemia.Compared with the hypoglycemia group,the non-hypoglycemia group showed significantly lower proportions of patients with a history of diabetes,a history of hypoglycemia,and combined use of hypoglycemic drugs,as well as lower APACHEⅡ scores and lower blood glucose coefficient of variation,with significantly increased GFR(all P<0.05).The ROC curve AUC for the validation cohort was 0.803(95％CI was 0.757-0.849,P=0.138),indicating high discriminatory ability.The predicted probability at the diagnostic cutoff point was P=0.138.The model's diagnostic threshold for predicted probability was P=0.138,while the optimal cut-off value based on the Youden index was 0.513,yielding a sensitivity of 76.5％and specificity of 74.8％,indicating predictive value for hypoglycemia in adult ICU patients.The mean absolute error(MAE)results for the modeling group and validation group were<0.05.The calibration curves of both the modeling and validation groups showed close alignment with the ideal curve,indicating excellent calibration performance of the model.Conclusion The constructed hypoglycemia risk prediction model for adult ICU patients has good predictive performance,which can quickly identify high-risk populations of hypoglycemia in ICU and provide reference for clinical preventive nursing.

Objective:To explore the correlation between periodontitis (PD) and chronic kidney disease (CKD) in adults, as well as the potential mechanisms involved.Methods:Data on PD and CKD from the National Health and Nutrition Examination Survey (NHANES) database between 1999 and 2014 were downloaded. Weighted univariate and multivariate logistic regression analyses were conducted to investigate the risk factors associated with PD and CKD, considering demographic and clinical indicators. Using publicly available genome-wide association study (GWAS) summary datasets for CKD and PD as outcome variables, as well as 731 immune cell phenotypes and 91 inflammatory proteins as exposure factors from the OPEN GWAS database, a two-sample Mendelian randomization (TSMR) analysis was performed using the inverse-variance weighted (IVW) method.Results:Seven demographic indicators including gender, age, race, education level, marital status, income, and health are related to the incidence of CKD and PD. Among them, the elderly (≥60 years old), poverty (poverty-income ratio <1.3), divorce or widowhood, and male ratio in the comorbidity group of CKD and PD [67.12% (833/1 241), 36.83% (457/1 241), 34.41% (427/1 241), and 57.78% (717/1 241) respectively] were significantly higher than those in the control group [23.71% (4 179/17 623), 29.17% (5 141/17 623), 18.16% (3 200/17 623), and 48.73% (8 587/17 623) respectively] (all P<0.001). Those with high educational level (university and above) and self-rated excellent health accounted for a relatively small proportion in the comorbidity group [14.10% (175/1 241) and 8.22% (102/1 241) respectively]. The prevalence of PD increased among individuals with abnormal renal function indices, including glomerular filtration rate, urine protein/creatinine ratio, serum creatinine, serum uric acid, and blood urea nitrogen. Univariate logistic regression analysis showed a positive correlation between the incidence of PD and CKD ( OR=2.14, 95 %CI: 1.90-2.42, P<0.001). Multivariate logistic regression analysis also indicated that PD and CKD were potential risk factors for each other (PD for CKD: OR=1.22, 95 %CI: 1.07-1.40, P=0.004; CKD for PD: OR=1.19, 95 %CI: 1.04-1.37, P=0.012). Furthermore, after adjusting the model based on demographic indicators, there was still a significant correlation between PD and CKD ( P=0.010). Mechanistically, the results of the TSMR analysis support the existence of a common risk factor mediated by immune cells between CKD and PD, namely the expression of CD64 on multiple innate immune cells mediates the occurrence of CKD and PD. The absolute count of CD64 + monocytes is associated with an increased risk for both CKD ( HR=1.11) and PD ( HR=1.07), while same tendency showed in the absolute count of CD64 + neutrophils for CKD ( HR=1.22) and PD ( HR=1.23). Conclusions:There is a positive correlation between CKD and PD, particularly moderate to severe PD, and the shared pathogenesis involves CD64 + monocytes in the circulatory system. Targeted interventions focusing on CD64 molecules or monocyte subsets may be beneficial.

Objective: To observe the clinical efficacy of herbal cake-partitioned moxibustion for ulcerative colitis (UC) and elucidate its mechanism by targeting the vitamin D receptor (VDR) signaling pathway. Methods: A total of 63 patients with UC were randomly divided into an observation group (30 cases, treated with herbal cake-partitioned moxibustion) and a control group (33 cases, treated with sham herbal cake-partitioned moxibustion). Moxibustion treatment was performed at Qihai (CV6) and bilateral Tianshu (ST25) and Shangjuxu (ST37), 3 times per week for 12 weeks. The total effective rate, visual analog scale (VAS) score for abdominal bloating and pain, and hospital anxiety and depression scale (HADS) score were compared between the two groups. Enzyme-linked immunosorbent assay was used to detect the concentrations of serum C-reactive protein (CRP), 25-hydroxyvitamin D [25(OH)D], and interleukin-12 (IL-12)/interleukin-23 (IL-23) p40. Immunohistochemistry was used to observe the expression levels of VDR and regenerating gene Ⅳ (Reg Ⅳ) proteins in colonic mucosa. The expression levels of VDR, cytochrome p45027B1 (CYP27B1), and Reg Ⅳ mRNAs were detected by real-time fluorescence quantitive polymerase chain reaction. Results: After treatment, the total effective rate in the observation group was 86.7％, which was significantly higher than 51.5％ in the control group (P<0.05). After treatment, the VAS scores for abdominal bloating and pain in the observation group were significantly decreased (P<0.01), as well as the HADS-depression subscale (HADS-D) and HADS-anxiety subscale (HADS) scores (P<0.05), while only the VAS score for abdominal pain in the control group was reduced (P<0.05), and the improvements of the scores in the observation group were more significant than those in the control group (P<0.05). After treatment, the serum CRP concentrations in both groups and the IL-12/IL-23 p40 concentration in the observation group were significantly decreased (P<0.05), and the concentrations in the observation group were lower than those in the control group (P<0.05). The expression levels of VDR protein and mRNA in the colon in both groups were all increased (P<0.01), and the expression levels of Reg Ⅳ protein and mRNA and CYP27B1 mRNA were all decreased in the two groups (P<0.05 or P<0.01); the improvements in the observation group were more notable than those in the control group (P<0.05 or P<0.01). Conclusion: Herbal cake-partitioned moxibustion can effectively alleviate abdominal pain and diarrhea in patients with UC, improve depression and anxiety disorders, and regulate the expression of related proteins in the VDR signaling pathway. The mechanism may be related to inhibiting intestinal inflammation by reducing the release of the proinflammatory cytokine IL-12/IL-23 p40.

Objective:To explore the influencing factors by investigating the spiritual health status of patients with lung cancer during perioperative period.Methods:A total of 208 perioperative patients who underwent radical resection of lung cancer in Cancer Hospital Chinese Academy of Medical Sciences from September 2020 to September 2021 were selected as research objects by the convenient sampling method. The General Data Questionnaire, Chinese version of Functional Assessment of Chronic illness Therapy-Spiritual (FACIT-SP-12) and Family APGAR Index (APGAR) were used to investigate the patients. Pearson correlation analysis was used to explore the correlation between spiritual health and family caring. Pearson correlation analysis was used to explore the correlation between spiritual health and family caring. Multiple linear regression analysis was used to investigate the influencing factors of spiritual health in patients with lung cancer during perioperative period. A total of 208 questionnaires were sent out and 200 were effectively received, with the effective recovery of 96.15%.Results:The total score of FACIT-SP-12 of 200 patients with perioperative lung cancer was (35.59±8.16) , indicating a moderate spiritual health level. The main factors affecting spiritual health of perioperative lung cancer patients were the degree of family care, marital status and payment of medical expenses ( P<0.05) . Conclusions:The spiritual health of perioperative lung cancer patients is in the middle level, and the spiritual health of patients with different family caring degrees, marital status and medical payment method is different. Clinical medical workers can carry out targeted nursing intervention according to individual conditions of patients to improve their quality of life.

Objective: The status of masked obesity in female college students and the related factors were investigated to provide a theoretical reference for instructing the physical health education of female college students and improving their physical exercises. Methods: Body composition tests were performed on 2 975 female college students, selected from 3 colleges in North China by using cluster sampling method during October to December in 2018, and their basic information and lifestyle were investigated using questionnaires. Results: The incidence of masked obesity among female college students was 33.18%, of which 2.53% came from low-weight people. The difference in the incidence of masked obesity among female college students with different take-out frequencies was statistically significant (χ2=21.98, P<0.01). Compared with those who never take takeaway, people who take takeaway every day have an increased risk of masked obesity (OR=1.49, 95%CI=0.76-2.91). The difference in the incidence of masked obesity with the frequency of eating midnight snack was statistically significant (χ2=20.80, P<0.05). The difference in the incidence of masked obesity among female college students with different exercise time was statistically significant (χ2=18.49, P<0.01). Compared with exercise time above 60 min/d, female college students who are not exercising have an increased risk of masked obesity (OR=3.20, 95%CI=1.63-6.30). The difference in the incidence of masked obesity among female college students with different weight satisfaction was statistically significant (χ2=217.54, P<0.01). Compared with female college students who were satisfied with weight, female college students who were not satisfied with weight had an increased risk of masked obesity (OR=3.47, 95%CI=1.91-6.31). The difference in the incidence of masked obesity in different weightdown plans is statistically significant (χ2=186.40, P<0.01). Those who want to lose weight have a higher risk of developing masked obesity than those who want to gain weight (OR=18.11, 95%CI=5.54-50.13). Conclusion Female college students who drink a small amount of water, eat takeaways often, eat midnight snacks, do not exercise, and are not satisfied with their weight are more likely to develop masked obesity.