Alzheimer's disease (AD) remains a formidable challenge in modern healthcare, necessitating innovative approaches for its early detection and intervention. This study aimed to enhance the identification of individuals with mild cognitive impairment (MCI) at risk of developing AD. Leveraging advances in computational power and the extensive availability of healthcare data, we explored the potential of deep learning models for early prediction using medical claims data. We employed a bidirectional gated recurrent unit (BiGRU) deep learning model for predictive modeling of MCI progression across various prediction intervals, extending up to five years post-initial MCI diagnosis. The performance of the BiGRU model was rigorously compared with several machine-learning model baselines to evaluate its efficacy. Using a robust cross-validation methodology, the BiGRU emerged as the top-performing model, achieving an Area Under the Receiver Operating Characteristic Curve (AUC-ROC) of 0.833 (95% CI: 0.822, 0.843), an Area Under the Precision-Recall Curve (AUC-PR) of 0.856 (95% CI: 0.845, 0.867), and an F1-Score of 0.71 (95% CI: 0.694, 0.724) for a five-year prediction interval. The results indicate that BiGRU, utilizing longitudinal claims data, reliably predicts MCI-to-AD progression over a lengthy interval following the initial MCI diagnosis, offering clinicians a valuable tool for targeted risk identification and stratification.

Objective:To summarize the clinical features of primary segmental volvulus (PSV) in neonates.Methods:A retrospective analysis was conducted on the clinical data of neonates with PSV who were admitted to the Department of Neonatal Surgery, Children's Hospital Affiliated to Capital Institute of Pediatrics from May 2014 to May 2023. The clinical manifestations, auxiliary examinations, treatment and prognosis of the neonates were summarized, and descriptive statistical analysis was performed on the collected data.Results:A total of 10 neonates with PSV were included, with a mean gestational age of (34.1±3.0) weeks and birth weight of (2 291±646) g. Eight cases had an onset age of 3 d or less, and 2 cases had an onset age of more than 3 d. Abdominal distension was observed as the main manifestation in all cases, while bilious vomiting occurred in seven cases and hematochezia in five cases. Imaging examinations mainly revealed low intestinal obstruction without specific manifestations. Laboratory tests showed metabolic acidosis and varing degrees of anaemia. Nine cases underwent diagnostic abdominal puncture, of which five had bloody ascites, two had clear ascites, one had bloody mixed with fecal-like ascites, and one had chylous ascites. All the cases underwent emergency exploratory laparotomy and segmental small bowel resections with either primary intestinal anastomosis or enterostomy. All cases were successfully cured and had been followed up to the age of 4 months to 9 years with good growth and development as normal children of the same age.Conclusions:Neonatal PSV is an independent abdominal emergency characterized by non-specific clinical manifestations and difficult preoperative diagnosis, but the overall prognosis is favorable after active surgical treatment.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.

Objective:To analyze the researches on nutrition for premature infants and steer future research directions.Methods:The Web of Science core collection was employed as the primary source to conduct a comprehensive search and retrieve relevant literature on nutrition for premature infants published up from 1975 to December 2023. A visualized analysis was conducted using CiteSpace.Results:After screening, a total of 2 661 publications were included. A rising trend was seen in the amount of publications. Countries with the most publications were the United States, the United Kingdom, and Italy, with the leading institutions of Baylor College of Medicine and the University of Copenhagen. Shanghai Jiao Tong University was the institution that published the most in China. Key topics that were studied frequently encompassed parenteral nutrition, breast milk utilization and necrotizing enterocolitis. Cluster analysis of keywords identified 18 representative cluster labels, revealing the research focuses on parenteral nutrition, enteral nutrition, necrotizing enterocolitis and feeding intolerance in premature infants.Conclusion:The researches on nutrition for premature infants are on the rise, and the nutritional support regimen, how to reduce complications, and nutritional care are the hot topics of future researches on nutrition for premature infants.

Humans ; HIV-1 ; Leukocytes, Mononuclear ; Lymphoma, Non-Hodgkin ; DNA ; HIV Infections

Objective:To construct a Question Prompt List of information needs for patients with interstitial lung disease, providing a tool for patients with interstitial lung disease to actively obtain disease-related information.Methods:A literature study was conducted based on the three core needs (ERG) theory framework of existence,relatedness and growth. A purposive sampling method was used to select 15 patients with interstitial lung disease from Drum Tower Hospital, Medical School of Nanjing University from December 2021 to January 2022 for descriptive research. Based on literature research and qualitative research, the initial items of the Question Prompt List were determined through expert inquiry, and the items were extracted, discussed, and adjusted, and finalized the list of information needs and prompts for patients with interstitial lung disease.Results:The 19 experts participated in the consultation, with a positive coefficient of 100.0% and 94.7% for two rounds of consultation, an authoritative coefficient of 0.91 and 0.92, and the Kendall coordination coefficient of 0.31 and 0.23, respectively. Finally, a list of interstitial lung disease patients′ question prompts containing 4 primary indicators and 34 secondary indicators was formed.Conclusions:Based on the ERG theory, the research method for the Question Prompt List of information needs for patients with interstitial lung disease is scientific and reliable, and can be used in clinical practice to help patients inquire and obtain the necessary information.

"Flipped Classroom" is a new kind of "student-centered" teaching model, which can give full play to the advantages of both sides of teaching and learning. According to this teaching model, we redesigned the teaching process, in which the students studied by themselves and built their own knowledge system. Moreover, each of them took part in three stages of experimental design including digital signal collection, analysis and processing in groups. Results have shown that this model can fully stimulate students' learning interest, not only helps students to deepen understanding of digital signal processing theory knowledge, but also strengthen the ability of autonomous learning and team collaboration. The teaching model maybe have certain reference function in comprehensive experiment teaching of Digital Signal Processing course for biomedical engineering specialty.

Based on the summary and reflection of the existing course construction content, this paper redesigns the course teaching to Brain Functional Imaging and forms a new curriculum construction scheme, including improving the professional teachers' ability of the teaching team by means of "internal training" + "external introduction", building an online and offline integrated teaching mode by combining online teaching resources such as course website with offline teaching (such as literature guidance, classroom discussion, comprehensive experimental design, etc.), and designing comprehensive experiments related to Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which is driven by scientific research projects, based on the scientific research experimental platform of the teaching and research department. This construction scheme is of great significance for improving the teaching quality of the course, stimulating the learning interest of graduate students, and cultivating the comprehensive application and practical innovation ability of graduate students' brain imaging technology. And it also provides the reference for the further construction of the course and teaching reform in the future.

Objective:To explore the factors that affect the participation of elderly care nurses in home-based elderly care services, in order to provide reference for the targeted improvement of human problems in home-based elderly care services.Methods:The phenomenological research method of qualitative research was used to conduct semi-structured in-depth interviews, on-site recordings and transcripts with 14 nurses in the geriatrics department of Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical College from September to October, 2021. The collected data were analyzed and the theme was refined by using the 7-step analysis method of Colaizzi phenomenology.Results:Through sorting and analysis, four themes and six sub themes were extracted as follows: language behavior factors including environmental discomfort and differences in living habits, freedom was limited; psychological and emotional factors including high psychological pressure and loneliness, not respected; career development factors; social security factors including the definition of work scope is unclear, the division of responsibility for the accident was unclear and the protection of relevant rights and interests was insufficient.Conclusions:The intention of elderly care nurses to participate in home-based elderly care services is affected by many factors. These factors need to be accurately identified and targeted support measures should be taken to improve their enthusiasm to participate in home-based elderly care services and improve the human problems in home-based elderly care services.