OBJECTIVE To explore the influencing factors for secondary heart failure in the children with severe pneumonia and establish the nomogram prediction model.METHODS A total of 767 children with severe pneumo-nia who were treated in Children's Hospital of Nanjing Medical University from Mar.2018 to Mar.2024 were en-rolled in the study and were divided into the modeling group with 537 cases and the validation group with 230 ca-ses in a 7∶3 ratio.Meanwhile,127 children with severe pneumonia who were treated from Apr.2024 to Dec.2024 were chosen as the external validation group.The children of the modeling group were divided into the heart failure group with 56 cases and the non-heart failure group with 481 cases according to the status of secondary heart fail-ure.The clinical data were collected from the children.Multivariate logistic regression analysis was performed for the influencing factors for the secondary heart failure in the children with severe pneumonia,the prediction model for secondary heart failure in the severe pneumonia children was established with the use of R software.The effica-cy of the model in prediction of secondary heart failure in the children with severe pneumonia was analyzed by means of receiver operating characteristic(ROC)curves and Hosmer-Lemeshow(H-L)fitting test.RESULTS The critically ill case score(OR=8.847,95％CI:3.806 to 20.566),persistent pulmonary arterial hypertension(OR=5.557,95％CI:2.450 to 12.604),respiratory failure(OR=2.646,95％CI:1.066 to 6.567),coagulation dysfunction(OR=13.444,95％CI:5.790 to 31.219)and procalcitonin(PCT)(OR=8.103,95％CI:3.466 to 18.943)were the influencing factors for the secondary heart failure in the children with severe pneumonia(P＜0.05).The area under the ROC curve of the validation group was 0.962,the external validation group 0.973;the H-L test showed that the prediction model had high consistency and discrimination for the secondary heart fail-ure in the children with severe pneumonia.CONCLUSIONS The critically ill case score,persistent pulmonary arte-rial hypertension,respiratory failure,coagulation dysfunction and PCT level are the influencing factors for the sec-ondary heart failure in the children with severe pneumonia.The prediction model that is established based on the influencing factors shows high efficiency.

OBJECTIVE To analyze the risk factors for severe adenovirus pneumonia(AP)in children and construct a nomogram.METHODS A total of 108 children with AP admitted to the Department of Infectious Diseases at Children's Hospital of Nanjing Medical University from Nov.2023 to Apr.2024 were selected and divided into a severe group(n=38)and a non-severe group(n=70)based on disease severity.Logistic regression analysis was used to identify the risk factors for severe AP in children.A nomogram was developed by R software,and its per-formance was evaluated by the receiver operating characteristic(ROC)curve,calibration curve and Hosmer-Lemeshow goodness-of-fit test.RESULTS Anemia(OR=4.370,95％CI:1.370-13.941,P=0.013),congenital heart disease(OR=4.036,95％CI:1.277-12.754,P=0.017),multiple infection(OR=4.984,95％CI:1.546-16.069,P=0.007)and pulmonary consolidation(OR=17.492,95％CI:5.288-57.864,P＜0.001)were identified as risk factors for severe AP in children.The area under the ROC curve of the nomogram for pre-dicting severe AP in children was 0.896(95％CI:0.838-0.954).The slope of calibration curve was close to 1,and the Hosmer-Lemeshow goodness-of-fit test yielded x2=7.754,P=0.355.CONCLUSIONS Anemia,congenital heart dis-ease,multiple infection and pulmonary consolidation are risk factors for severe AP in children.The constructed nomogram enables individualized prediction of severe AP risk in children,thereby guiding personalized interventions.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

OBJECTIVE To analyze the risk factors for severe adenovirus pneumonia(AP)in children and construct a nomogram.METHODS A total of 108 children with AP admitted to the Department of Infectious Diseases at Children's Hospital of Nanjing Medical University from Nov.2023 to Apr.2024 were selected and divided into a severe group(n=38)and a non-severe group(n=70)based on disease severity.Logistic regression analysis was used to identify the risk factors for severe AP in children.A nomogram was developed by R software,and its per-formance was evaluated by the receiver operating characteristic(ROC)curve,calibration curve and Hosmer-Lemeshow goodness-of-fit test.RESULTS Anemia(OR=4.370,95％CI:1.370-13.941,P=0.013),congenital heart disease(OR=4.036,95％CI:1.277-12.754,P=0.017),multiple infection(OR=4.984,95％CI:1.546-16.069,P=0.007)and pulmonary consolidation(OR=17.492,95％CI:5.288-57.864,P＜0.001)were identified as risk factors for severe AP in children.The area under the ROC curve of the nomogram for pre-dicting severe AP in children was 0.896(95％CI:0.838-0.954).The slope of calibration curve was close to 1,and the Hosmer-Lemeshow goodness-of-fit test yielded x2=7.754,P=0.355.CONCLUSIONS Anemia,congenital heart dis-ease,multiple infection and pulmonary consolidation are risk factors for severe AP in children.The constructed nomogram enables individualized prediction of severe AP risk in children,thereby guiding personalized interventions.

OBJECTIVE To construct a nomogram diagnosis model for Epstein-Barr virus(EBV)co-infection in children with Mycoplasma pneumoniae pneumonia(MPP).METHODS Clinical data of 427 children with MPP ad-mitted to the Children's Hospital of Nanjing Medical University from Jul.2020 to Jul.2024 were retrospectively analyzed.The children were divided into a modeling group(n=299)and a validation group(n=128).The model-ing group was further categorized into an MPP group(n=235)and an MPP co-infection group(n=64)based on EBV infection status.Multivariate logistic regression was used to identify risk factors for EBV co-infection in chil-dren with MPP,and a nomogram diagnosis model was constructed.The diagnostic value and clinical application value of the model were evaluated by receiver operating characteristic(ROC)curves,calibration curves and deci-sion curve analysis(DCA).RESULTS The white blood cell count(WBC)in the MPP co-infection group was(12.37±2.32)× 109/L,significantly higher than that in the MPP group(P＜0.05).Platelet count(PLT)and hemoglobin(Hb)levels were(197.95±32.85)× 109/L and(102.58±13.74)g/L,respectively,lower than those in the MPP group(P＜0.05).Additionally,the MPP co-infection group exhibited higher proportions of fe-ver duration ≥10 days,dyspnea and pleural effusion compared to the MPP group(P＜0.05).Multivariate logistic regression analysis revealed that WBC(OR=1.514),PLT(OR=0.970),Hb(OR=0.959),fever duration(OR=4.790),dyspnea(OR=3.777)and pleural effusion(OR=4.795)were significantly associated with EBV infection in children with MPP(P＜0.05).The nomogram demonstrated that when the total model score reached 219 points,the probability of EBV infection in children with MMP was 0.9.The areas under the ROC curve for the modeling group and validation group were 0.882(95％CI:0.836-0.927)and 0.943(95％CI:0.902-0.984),respectively,with sensitivities of 76.56％and 91.30％,respectively,and specificities of 82.55％and 85.71％,respectively.The Hosmer-Lemeshow goodness-of-fit test showed x2=4.124,P=0.846 for the modeling group and x2=4.203,P=0.838 for the validation group.DCA curve indicated high clinical applica-tion value of the model.CONCLUSIONS WBC,PLT,Hb levels,fever duration,dyspnea and pleural effusion have diagnostic values for EBV co-infection in children with MPP.The nomogram model constructed based on these six factors demonstrates excellent diagnostic performance.

OBJECTIVE To construct a nomogram diagnosis model for Epstein-Barr virus(EBV)co-infection in children with Mycoplasma pneumoniae pneumonia(MPP).METHODS Clinical data of 427 children with MPP ad-mitted to the Children's Hospital of Nanjing Medical University from Jul.2020 to Jul.2024 were retrospectively analyzed.The children were divided into a modeling group(n=299)and a validation group(n=128).The model-ing group was further categorized into an MPP group(n=235)and an MPP co-infection group(n=64)based on EBV infection status.Multivariate logistic regression was used to identify risk factors for EBV co-infection in chil-dren with MPP,and a nomogram diagnosis model was constructed.The diagnostic value and clinical application value of the model were evaluated by receiver operating characteristic(ROC)curves,calibration curves and deci-sion curve analysis(DCA).RESULTS The white blood cell count(WBC)in the MPP co-infection group was(12.37±2.32)× 109/L,significantly higher than that in the MPP group(P＜0.05).Platelet count(PLT)and hemoglobin(Hb)levels were(197.95±32.85)× 109/L and(102.58±13.74)g/L,respectively,lower than those in the MPP group(P＜0.05).Additionally,the MPP co-infection group exhibited higher proportions of fe-ver duration ≥10 days,dyspnea and pleural effusion compared to the MPP group(P＜0.05).Multivariate logistic regression analysis revealed that WBC(OR=1.514),PLT(OR=0.970),Hb(OR=0.959),fever duration(OR=4.790),dyspnea(OR=3.777)and pleural effusion(OR=4.795)were significantly associated with EBV infection in children with MPP(P＜0.05).The nomogram demonstrated that when the total model score reached 219 points,the probability of EBV infection in children with MMP was 0.9.The areas under the ROC curve for the modeling group and validation group were 0.882(95％CI:0.836-0.927)and 0.943(95％CI:0.902-0.984),respectively,with sensitivities of 76.56％and 91.30％,respectively,and specificities of 82.55％and 85.71％,respectively.The Hosmer-Lemeshow goodness-of-fit test showed x2=4.124,P=0.846 for the modeling group and x2=4.203,P=0.838 for the validation group.DCA curve indicated high clinical applica-tion value of the model.CONCLUSIONS WBC,PLT,Hb levels,fever duration,dyspnea and pleural effusion have diagnostic values for EBV co-infection in children with MPP.The nomogram model constructed based on these six factors demonstrates excellent diagnostic performance.

OBJECTIVE To explore the influencing factors for secondary heart failure in the children with severe pneumonia and establish the nomogram prediction model.METHODS A total of 767 children with severe pneumo-nia who were treated in Children's Hospital of Nanjing Medical University from Mar.2018 to Mar.2024 were en-rolled in the study and were divided into the modeling group with 537 cases and the validation group with 230 ca-ses in a 7∶3 ratio.Meanwhile,127 children with severe pneumonia who were treated from Apr.2024 to Dec.2024 were chosen as the external validation group.The children of the modeling group were divided into the heart failure group with 56 cases and the non-heart failure group with 481 cases according to the status of secondary heart fail-ure.The clinical data were collected from the children.Multivariate logistic regression analysis was performed for the influencing factors for the secondary heart failure in the children with severe pneumonia,the prediction model for secondary heart failure in the severe pneumonia children was established with the use of R software.The effica-cy of the model in prediction of secondary heart failure in the children with severe pneumonia was analyzed by means of receiver operating characteristic(ROC)curves and Hosmer-Lemeshow(H-L)fitting test.RESULTS The critically ill case score(OR=8.847,95％CI:3.806 to 20.566),persistent pulmonary arterial hypertension(OR=5.557,95％CI:2.450 to 12.604),respiratory failure(OR=2.646,95％CI:1.066 to 6.567),coagulation dysfunction(OR=13.444,95％CI:5.790 to 31.219)and procalcitonin(PCT)(OR=8.103,95％CI:3.466 to 18.943)were the influencing factors for the secondary heart failure in the children with severe pneumonia(P＜0.05).The area under the ROC curve of the validation group was 0.962,the external validation group 0.973;the H-L test showed that the prediction model had high consistency and discrimination for the secondary heart fail-ure in the children with severe pneumonia.CONCLUSIONS The critically ill case score,persistent pulmonary arte-rial hypertension,respiratory failure,coagulation dysfunction and PCT level are the influencing factors for the sec-ondary heart failure in the children with severe pneumonia.The prediction model that is established based on the influencing factors shows high efficiency.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To analyze the clinical characteristics of patients with novel coronavirus pneumonia (COVID-19) and the factors influencing mild cases developing into severe cases, so as to provide a basis for clinical screening, prevention and treatment of potential severe cases.Methods:Retrospective analysis was performed on the clinical characteristics of 168 cases who were admitted to two tertiary general hospitals in Anhui province and diagnosed with COVID-19 from January 20 to March 4, 2020. According to the classification criteria in the COVID-19 diagnosis and treatment program (trial version 6) issued by the National Health Commission, the mild and common cases were classified as the mild group ( n=137), and the severe and critical cases were classified as the severe group ( n=31). The general data, epidemiological history, clinical manifestations, laboratory examination and imaging indexes of the two groups were compared. Univariate analysis was performed. Then multivariate Logistic regression analysis was conducted on the factors with statistically significant differences in univariate analysis to obtain independent influencing factors of the occurrence of severe COVID-19. Results:Among the 168 COVID-19 patients, 95 were male and 73 were female, with an average age of 42.6±15.8 years old. The mean age of the mild group was younger than that of the severe group (40.5±15.5 vs 51.6 ±14.1, P<0.01). The proportion of patients combined with hypertension (29.0% vs 10.9%), diabetes (25.8% vs 2.2%, P=0.005) and two or more underlying diseases (29.0% vs 4.4%, P=0.006) in the severe group were significantly higher than those in the mild group. In the severe group, the proportion of patients receiving initial treatment in Medical institutions below secondary hospitals was significantly higher than that in the mild group ( P<0.01), and the time between symptom onset and diagnosis was longer [(8.00±3.27) d vs (6.49±3.90) d, P=0.048]. There was no significant difference in the initial symptoms between the mild group and the severe group. However, the body temperature was higher in the severe group [(38.80±0.67)℃ vs (37.9±0.60)℃, P<0.01]. At the time of admission, the lymphocyte percentage of the severe group was significantly lower than that of the mild group [(18.20±9.13)% vs (24.43±10.43)%, P<0.01], while C-reactive protein, interleukin-6 (IL-6), D-dimer, LDH, aspartate and aminotransferase were significantly higher than that of the mild group ( P<0.01). CT imaging showed that 11 (8%) patients in the mild group had lesions confined to a single lobe of the lung, while all patients in the severe group had multi-lobe lesions ( P<0.01). All the 168 COVID-19 patients in this study were cured, and the length of hospital stay in the severe group was significantly longer than that in the mild group [(24.71±7.72) d vs (20.28±7.67) d, P=0.021]. According to multivariate binary Logistic regression analysis, age ( P=0.042), diabetes ( P=0.021), body temperature at admission ( P=0.001), and IL-6 measured at admission ( P=0.008) were independent factors affecting COVID-19 to severe progress. Conclusions:Strengthening the professional knowledge training of primary hospitals is helpful for early diagnosis of COVID-19. Patients with older age, combined with diabetes, high initial fever and significantly increased IL-6 level are more possibly to develop into severe disease. Early identification and prevention should be carried out.