Objective: To analyze the consumption frequency of major foods among Chinese children aged 6-17 years old, and to provide a basis for optimizing the dietary structure of children in China. Methods: Using data from the China Nutrition and Health System Survey and Application Program for Children 0-18 years old, 56 734 children aged 6-17 years old from North, Norththeast East, Central, South, Southwest and Northwest seven regions in China were selected for the study using stratified cluster random sampling from 2019 to 2021. A food frequency questionnaire was used to investigate the intake frequency of eight food groups in a month, including fresh vegetables, fresh fruits, livestock and poultry meats, aquatic products, eggs, dairy products, legumes, and cereals and potatoes. The foods were grouped according to whether they met the recommended intake criteria outlined in the Dietary Guidelines for Chinese Residents 2022. The〖KG*2〗χ2 test was used to compare the differences in the proportion of childrens intake frequency of each food group meeting the standard in different regions and age groups. Results: The proportions of Chinese children aged 6-17 years who consumed fresh vegetables and cereals and potatoes ≥3 times/d were 12.1% and 67.2%, respectively. The proportions of children who consumed fresh fruits, livestock and poultry meats, eggs and dairy products ≥1 time/d were 50.8%, 58.8%, 36.0% and 54.3%, respectively. The proportion of legumes consumed ≥4 times/week was 37.4%, and the proportion of aquatic products consumed ≥2 times/week was 39.7%. Fresh vegetables (5.5%), fresh fruits (33.1%), and dairy products (36.4%) had the lowest frequency of meeting the recommended standards in South China, and aquatic products (27.4%) and eggs (21.1%) had the lowest frequency of meeting the recommended standards in Northwest (P<0.008 3). Conclusion The overall intake frequency of fresh vegetables, fresh fruits, legumes, and dairy products are insufficient among Chinese children, with significant regional variations.

PURPOSE: To evaluate the relationship between the timing of thoracic endovascular aortic repair (TEVAR) for blunt thoracic aortic injury (BTAI) and prognosis. METHODS: This is a single-center retrospective cohort study. Patients who received TEVAR for BTAI at our institution from October 2016 to September 2023 were divided into 2 categories depending on the injury severity score (ISS) (≤ 25 vs. > 25) and when the TEVAR was performed for BTAI (within 24 h vs. after 24 h), respectively. The analysis included all patients who received TEVAR treatment after being diagnosed with BTAI through whole-body CT angiography. Patients treated with open repair and non-operative management were excluded. After propensity-score matching for various factors, outcomes during hospitalization and follow-up were compared. These factors included demographics, comorbidities, concomitant injuries, cause and location of aortic injury, Glasgow coma scale score, society for vascular surgery grading, hemoglobin concentration, creatinine concentration, shock, systolic blood pressure, and heart rate at admission. The comparison was conducted using SPSS 26 software. Continuous variables were presented as either the mean ± standard deviation or median (Q₁, Q₃), and were compared using either the t-test or the Mann-Whitney U test. Categorical variables were expressed as n (%), and comparisons were made between the 2 groups using the χ² test or Fisher's exact test. Statistical significance was defined as a 2-sided p < 0.05. RESULTS: In total, 110 patients were involved in the study, with 65 (59.1%) patients having ISS scores > 25 and 32 (29.1%) receiving immediate TEVAR. The perioperative overall mortality rate in the group with ISS > 25 was significantly higher than that in the group with ISS ≤ 25 (11 (16.9%) vs. 2 (4.4%), p < 0.001). Upon admission, the elective group exhibited a notably higher Glasgow coma scale score (median (Q₁, Q₃)) compared to the immediate group (15 (12, 15) vs. 13.5 (9, 15), p = 0.039), while the creatinine concentration (median (Q₁, Q₃)) at admission was significantly higher in the immediate group (90.5 (63.8, 144.0) vs. 71.5 (58.3, 80.8), p = 0.012). The final sample included 52 matched patients. Complications occurred significantly less frequently in the elective group compared to the immediate group (16 (50.0%) vs. 3 (10.0%), p < 0.001). Single-factor analysis of variance showed that complications in hospitalized patients were significantly associated with immediate TEVAR as the sole independent risk factor (odds ratio: 9.000, 95% confidence interval: 2.266-35.752, p = 0.002). CONCLUSION In this propensity-score matched analysis of patients undergoing TEVAR for BTAI, elective TEVAR was significantly associated with a lower risk of complication rates. In this study using propensity-score matching, patients who underwent elective TEVAR for BTAI had lower complication rates than immediate TEVAR.
Humans ; Retrospective Studies ; Male ; Aorta, Thoracic/surgery* ; Female ; Endovascular Procedures/methods* ; Wounds, Nonpenetrating/mortality* ; Middle Aged ; Adult ; Aged ; Injury Severity Score ; Elective Surgical Procedures ; Time Factors ; Treatment Outcome ; Endovascular Aneurysm Repair

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.