Objective: To investigate the current status of benefit finding among young and middle-aged patients with type 2 diabetes mellitus (T2DM) and analyze its influencing factors, so as to provide a reference for improving the level of benefit finding in this population. Methods: From November 2022 to May 2023, young and middle-aged patients with T2DM aged 18-59 years hospitalized in the endocrinology departments of 2 tertiary hospitals in Hengyang City, Hunan Province were selected as survey subjects by a convenience sampling method. Basic demographic information was collected using a general questionnaire survey. Benefit finding, resourcefulness, and stigma were evaluated using the Benefit Finding Scale, the Chinese Version of the Resourcefulness Scale, and the Type 2 Diabetes Stigma Assessment Scale, respectively. A multiple linear regression model was used to analyze the influencing factors of benefit finding among young and middle-aged patients with T2DM. Results: A total of 305 young and middle-aged patients with T2DM were investigated, including 222 males (72.79%) and 83 females (27.21%). There were 231 cases aged 45-59 years, accounting for 75.74%. The scores for benefit finding, resourcefulness, and stigma were (42.86±6.06), (75.12±11.30), and (41.20±10.10), respectively. Multiple linear regression analysis showed that young and middle-aged patients with T2DM who were male (β′=0.088), aged 18-<45 years (β′=0.083), absence of diabetes complications (β′=0.124), and had higher resourcefulness scores (β′=0.679) had higher levels of benefit finding, while patients with higher stigma scores (β′=-0.097) had lower levels of benefit finding. Conclusion The level of benefit finding among young and middle-aged patients with T2DM was moderate, and was related to gender, age, diabetes complications, resourcefulness, and stigma.

Objective:To assess the status of undernutrition and appropriate catch-up growth in extremely preterm infants within 24 months of corrected age (CA).Methods:A retrospective cohort study was conducted. A total of 422 extremely preterm infants born at Shenzhen Maternity and Child Healthcare Hospital, Women and Children's Medical Center, Southern Medical University from January 2017 to December 2022 and followed up until 24 months of CA were enrolled. The extremely preterm infants were grouped by gestational age at birth (<25, 25-26, 27 weeks), birth weight (<500, 500-749, 750-999,≥1 000 g), weight for gestational age (large for gestational age (LGA), appropriate for gestational age (AGA), small for gestational age (SGA)) and sex. Weight data within 24 months of CA were collected every 3 months. Nutritional insufficiency, growth rate, and achievement of adequate catch-up growth were analyzed during the period from 0 to 24 months of CA. Z-score method was used to analyze data. Fenton 2013 preterm growth charts (Fenton 2013) were used before 40 weeks of corrected gestational age, and World Health Organization child growth standards (2009) fitted Z-scores were applied from 40 weeks of CA. Changes in weight Z-scores of extremely preterm infants from 0 to 24 months of CA were observed and compared, the occurrence of moderate to severe malnutrition and growth retardation was determined, nutritional insufficiency was assessed, and growth rate as well as the achievement of appropriate catch-up growth were analyzed. The Lambda-mu-sigma method combined with the Z-score fitting model was used to fit and analyze the distribution characteristics of weight percentiles in extremely preterm infants. The Chi-square test was used to compare differences among groups.Results:A total of 422 extremely preterm infants were included, with a gestational age at birth of 26.3(25.4, 27.2) weeks and a birth weight of (880±177) g. Among them, 238 were males and 184 were females; 36 cases (8.5%) were LGA, and 16 cases (3.8%) were SGA. During follow-up within 24 month of CA, 89 cases (21.1%) developed moderate to severe malnutrition. When compared separately among different birth weight and gestational age at birth groups, there had both statistically differences in the incidence of moderate to severe malnutrition ( χ2=42.94 and 9.17, both P<0.05). The incidence was the highest in the birth weight of CA<500 g group and the <25 weeks gestational age at birth group, while it was the lowest in the birth weight of CA≥1 000 g group and the 27 weeks gestational age at birth group in their respective groups. Growth retardation occurred in 5.2% (22/422). However, there had statistically differences in the incidence of growth retardation among different birth weight and gestational age at birth groups, in each grouped time interval ( χ2=21.61 and 4.30, both P<0.05). The proportions of rapid growth were relatively high in the 0-3 months and 3-6 months of CA groups, which were 96 cases (27.4%) and 98 cases (26.6%), respectively. Overall, appropriate catch-up growth was achieved in 341 cases (80.8%) from 0 to 24 months of CA. There had statistically differences in the completion rate of appropriate catch-up growth among different birth weight and gestational age at birth groups ( χ2=23.65 and 7.08, both P<0.05). The completion rate was the highest in the birth weight of CA<500 g group and the <25 weeks of gestational age at birth group, while it was the lowest in the birth weight of CA≥1 000 g group and the 27 weeks of gestational age at birth group. Conclusions:The lower the birth weight and gestational age of extremely preterm infants, the higher the incidence of moderate to severe malnutrition and the lower the achievement rate of adequate catch-up growth within 24 months of CA. The period of 0-6 months of CA is the critical window for catch-up in extremely preterm infants.

Objective:To assess the status of undernutrition and appropriate catch-up growth in extremely preterm infants within 24 months of corrected age (CA).Methods:A retrospective cohort study was conducted. A total of 422 extremely preterm infants born at Shenzhen Maternity and Child Healthcare Hospital, Women and Children's Medical Center, Southern Medical University from January 2017 to December 2022 and followed up until 24 months of CA were enrolled. The extremely preterm infants were grouped by gestational age at birth (<25, 25-26, 27 weeks), birth weight (<500, 500-749, 750-999,≥1 000 g), weight for gestational age (large for gestational age (LGA), appropriate for gestational age (AGA), small for gestational age (SGA)) and sex. Weight data within 24 months of CA were collected every 3 months. Nutritional insufficiency, growth rate, and achievement of adequate catch-up growth were analyzed during the period from 0 to 24 months of CA. Z-score method was used to analyze data. Fenton 2013 preterm growth charts (Fenton 2013) were used before 40 weeks of corrected gestational age, and World Health Organization child growth standards (2009) fitted Z-scores were applied from 40 weeks of CA. Changes in weight Z-scores of extremely preterm infants from 0 to 24 months of CA were observed and compared, the occurrence of moderate to severe malnutrition and growth retardation was determined, nutritional insufficiency was assessed, and growth rate as well as the achievement of appropriate catch-up growth were analyzed. The Lambda-mu-sigma method combined with the Z-score fitting model was used to fit and analyze the distribution characteristics of weight percentiles in extremely preterm infants. The Chi-square test was used to compare differences among groups.Results:A total of 422 extremely preterm infants were included, with a gestational age at birth of 26.3(25.4, 27.2) weeks and a birth weight of (880±177) g. Among them, 238 were males and 184 were females; 36 cases (8.5%) were LGA, and 16 cases (3.8%) were SGA. During follow-up within 24 month of CA, 89 cases (21.1%) developed moderate to severe malnutrition. When compared separately among different birth weight and gestational age at birth groups, there had both statistically differences in the incidence of moderate to severe malnutrition ( χ2=42.94 and 9.17, both P<0.05). The incidence was the highest in the birth weight of CA<500 g group and the <25 weeks gestational age at birth group, while it was the lowest in the birth weight of CA≥1 000 g group and the 27 weeks gestational age at birth group in their respective groups. Growth retardation occurred in 5.2% (22/422). However, there had statistically differences in the incidence of growth retardation among different birth weight and gestational age at birth groups, in each grouped time interval ( χ2=21.61 and 4.30, both P<0.05). The proportions of rapid growth were relatively high in the 0-3 months and 3-6 months of CA groups, which were 96 cases (27.4%) and 98 cases (26.6%), respectively. Overall, appropriate catch-up growth was achieved in 341 cases (80.8%) from 0 to 24 months of CA. There had statistically differences in the completion rate of appropriate catch-up growth among different birth weight and gestational age at birth groups ( χ2=23.65 and 7.08, both P<0.05). The completion rate was the highest in the birth weight of CA<500 g group and the <25 weeks of gestational age at birth group, while it was the lowest in the birth weight of CA≥1 000 g group and the 27 weeks of gestational age at birth group. Conclusions:The lower the birth weight and gestational age of extremely preterm infants, the higher the incidence of moderate to severe malnutrition and the lower the achievement rate of adequate catch-up growth within 24 months of CA. The period of 0-6 months of CA is the critical window for catch-up in extremely preterm infants.

Clinical prediction models are statistical tools that incorporate multiple variables to predict the likelihood of specific outcomes, by which the accuracy and efficiency of medical decision-making can be facilitated and patient health outcomes can be improved. However, many current studies face problems, such as model construction and reporting irregularities, as well as questionable reliability, which limit their clinical application of clinical prediction model. Therefore, this study systematically reviews relevant literatures, including publications from journals like BMJ, and outline the steps involved in constructing clinical prediction models based on practical research experience. It also provides an in-depth comparison of commonly used methods during the construction process and proposes a comprehensive guiding framework to help researchers in the field to better understand and master the core concepts and practical skills of clinical prediction models for the purpose of improving their professional capabilities in the development, validation, and application of clinical prediction models.

Objective:To systematically evaluate the application of artificial intelligence (AI) in cervical cytopathology diagnosis.Methods:A systematic search was conducted using the keywords ′′cervical cancer′′ ′′cytology′′ ′′artificial intelligence′′ ′′sensitivity′′ and ′′specificity′′ (in both English and Chinese) across databases including PubMed, Web of Science, Embase, Cochrane Library, IEEE Xplore, CNKI, Wanfang, VIP Chinese Science and Technology Journals, and SinoMed. The search covered literature from inception until January 1, 2024, on the application of AI in cervical cytopathological diagnosis. Data were extracted using a predefined data extraction form to compile the contingency table data, from which sensitivity, specificity and area under the curve (AUC) were calculated.Results:A total of 1 616 articles were initially retrieved, and 27 articles were finally included in this study according to the inclusion and exclusion criteria. Five researches were conducted on the diagnosis of cytopathology slides, with pooled AUC, sensitivity and specificity of 0.92 (95% CI: 0.89-0.94), 0.91 (95% CI: 0.77-0.97) and 0.84 (95% CI: 0.77-0.90), respectively. About 22 researches were conducted on the diagnosis of cytopathology images (individual cells or cell clusters), with pooled AUC, sensitivity and specificity of 1.00 (95% CI: 0.99-1.00), 0.98 (95% CI: 0.97-0.99) and 0.98 (95% CI: 0.97-0.99), respectively. Conclusion:The application of AI in the field of cervical cytopathology shows certain diagnostic performance and potential clinical application value.

Objective:To explore the genotype and the clinical phenotype of SCN2A-related developmental delay in children. Methods:A case series study was adopted. Collect clinical data from 10 cases of children with SCN2A gene variants diagnosed with global developmental delay/intellectual disability who were admitted to the Children′s Hospital between July 2019 and March 2023. Summarize the clinical phenotype and genotype based on clinical data such as general information, clinical manifestations, imaging examinations, laboratory tests, genetic testing results, and comprehensive pediatric neuropsychological development assessment. Results:A total of 10 patients were recruited, including 7 males and 3 females, with an age range of 27 days to 5 years and 9 months. 9 patients underwent children′s neuropsychological and behavioral assessments, and the results were consistent with global developmental delay, including 2 mild cases, 4 moderate cases, and 3 severe cases. 3 cases had autism spectrum disorder, and 2 cases had epilepsy. 6 patients underwent complete head MRI examination, and 4 of them showed abnormalities, including delayed myelination, widening of the local extra brain space in the frontal lobe, and abnormal frontal lobe morphology. All 10 cases had point variants. Among them, 9 cases are de novo and 1 case is maternal inheritance. Out of 10 cases, there were 5 cases with copy number variations, but all of them were of unknown significance. Among the 10 variants, 8 have been reported and 2 have not been reported, namely c.4145A>T(p.N1382I) and c.4937T>A(p.I1646N). In this study, 4 out of 10 patients with SCN2A variants had variation sites located in the S4 segment of domain which constitute Nav1.2, the sodium ion channel encoded by SCN2A. The developmental quotient level was lower when the variation sites were located in the S4 segment of domain, and the difference was statistically significant ( t=-3.101, P=0.017), indicating that the severity of developmental delay may be related to the localization of amino acids corresponding to variant sites within the protein domain. Conclusion:SCN2A mutations are strongly associated with diverse neurodevelopmental disorders. In this study, the phenotypic spectrum of SCN2A variants encompassed epilepsy, global developmental delay, and autism spectrum disorder. Affected individuals exhibited early-onset developmental delays, predominantly moderate to severe in severity. Voltage-sensing domain dysfunction in sodium channels may constitute a critical pathomechanism underlying neurodevelopmental impairments. Further electrophysiological characterization and molecular mechanistic studies are warranted todelineate the genotype-phenotype correlations between specific variant loci and clinical severity.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective:To explore the genetic diversity of Mycobacterium tuberculosis (MTB) in different types of tuberculosis and its association with clinical features, providing evidence for precise diagnosis and treatment of tuberculosis. Methods:This cross-sectional study included 103 cases of tuberculosis (38 with simple pulmonary tuberculosis, 43 with tuberculous pleurisy, and 22 with pulmonary combined with extrapulmonary tuberculosis) from Shenzhen Third People′s Hospital from 2015 to 2018. Paired bacterial strains from lung and pleural effusion/extrapulmonary sites were collected. Whole-genome sequencing (WGS) was used for drug resistance prediction, and genetic diversity (π value) was calculated as well as differential genes screening. Statistical analysis included paired t-tests and χ2 tests to compare clinical, bacteriological and genetic diversity features among groups.Results:The simple pulmonary tuberculosis group exhibited significantly higher rates of retreatment (71.7%, 27/38), cavitation (70.4%, 19/27), and multidrug-resistant or rifampicin-resistant (MDR/RR) (60.5%, 23/38) compared to the tuberculous pleurisy group (retreatment 11.9%, 5/42; cavitation 11.9%, 5/42; MDR/RR 16.3%, 7/43) and extrapulmonary tuberculosis group (retreatment 9.1%, 2/22; cavitation 18.2%, 4/22; MDR/RR 13.6%, 3/22) ( P<0.05). The overall π values of the MTB strain genomes in lung [(5.94±3.93)×10 ?5], pleural effusion[(6.22±3.51)×10 ?5], and extrapulmonary tissues [(5.83±3.54)×10 ?5] showed no significant differences ( H=0.10, P=0.94). Differential gene diversity analysis revealed that π value alternating genes related to respiration and intermediate metabolism were prominently high [tuberculous pleurisy 32.4% (11/34) and extrapulmonary tuberculosis groups 31.4% (32/102)], while cell wall-associated genes dominated in the simple pulmonary tuberculosis group (42.9%, 6/14). Drug resistance profiles and mutation spectra were identical across isolates from different sites within the same patient. Conclusion:WGS revealed the MTB diversity among different types of tuberculosis. Difference between pulmonary and extrapulmonary environments may impel the adaptive alternations of the bacterial strains to maintain survival with higher overall genome stability. Drug resistance testing of lung-derived isolates may provide references on extrapulmonary tuberculosis treatment.

Objective:To explore the association of 21-gene recurrence score (RS) and clinicopathologic characteristics of hormone receptor (HR) positive T1-3N1M0 breast cancer and its value in prognosis evaluation.Methods:The clinicopathological data of 287 patients with T1-3N1M0 breast cancer were collected, the 21-gene assay was completed, and follow-up was conducted. According to the 21-gene RS, the patients were divided into the RS<26 and RS≥26 groups. The relationship between the 21-gene RS and clinicopathological characteristics, treatment, recurrence, and metastasis was analyzed. Univariate and multivariate statistical analyses were used to analyze the risk factors for disease free survival (DFS).Results:The median RS of the 287 patients was 16. There were 240 cases with RS <26 and 47 cases with RS≥26. Tumor size, grade, estrogen receptor (ER), progesterone receptor (PR), and Ki-67 index were significantly different between the two cohorts ( P<0.05 for all). After a median follow-up of 74 months, the recurrence rate in the RS<26 group (8.3%) was significantly lower than that in the RS≥26 group (23.4%), the locoregional recurrence (LRR) rates in the RS<26 and RS≥26 groups were 2.1% and 0%,and the distant metastasis (DM) rates were 6.3% and 23.4%, respectively. The 5-year relapse free survival (RFS) rates of patients with RS<26 and RS≥26 were 93.8% (95% CI: 90.7%-96.9%) and 87.2% (95% CI: 78.2%-97.3%), and the 5-year DFS rates were 92.1% (95% CI: 88.7%-95.6%) and 85.1% (95% CI: 75.5%-95.9%), respectively, with significant differences between the two cohorts ( P=0.007 and P=0.006, respectively). Univariate analysis showed age, tumor size, grade, PR status, Ki-67 index and RS were prognostic factors for DFS ( P<0.05 for all). Multivariate analysis showed that age and tumor size were independent significant predictors for DFS ( P<0.05). Conclusions:The 21-gene RS of T1-3N1M0 breast cancer is related to tumor size, grade, ER, PR, and Ki-67 index. RS is an important factor affecting DM and DFS.

Objective To analyze the economic cost of self-monitoring of gestational diabetes mellitus, and provide a basis for measuring the economic burden of gestational diabetes mellitus, and to provide a reference for the formulation of intervention development and the adjustment of resource allocation. Methods The individual economic cost of self-monitoring for gestational diabetes mellitus was measured based on a decision tree model, and the total economic cost of self-monitoring for gestational diabetes mellitus in Beijing was estimated. The uncertainty of the model parameters was analyzed using one-way sensitivity analysis. Results The average individual economic cost of gestational diabetes self-monitoring was 1184 RMB, and the individual cost incurred by choosing different types of blood glucose meters ranged from 403 to 18 000 RMB. The average individual economic cost of finger-stick blood glucose monitoring was 606 RMB and the average individual economic cost of continuous glucose monitoring was 2 374 RMB. The total economic cost of gestational diabetes self-monitoring in Beijing was 23.818 0 million RMB, and the total economic cost incurred by choosing different types of blood glucose meters ranged from 0.292 5 to 9.027 9 million RMB. The proportion of the finger-stick blood glucose monitoring had the greatest impact on the robustness of the results. Conclusion Finger-stick blood glucose monitoring is still the dominant self-monitoring method and is less costly than continuous glucose monitoring. Self-monitoring of pregnant women with gestational diabetes mellitus incurs certain economic cost and causes an economic burden on society.