Objective:Bibliometric analysis was performed to map scientific knowledge landscape, so that to explore the research status and future trends in the field of carbapenem-resistant Gram-negative bacteria (CRGNB) over the past decade.Methods:Literature on CRGNB published between January 1st, 2015 and December 31st, 2024 was retrieved from the China National Knowledge Internet (CNKI) database and Web of Science Core Collection (WoSCC). VOSviewer and CiteSpace were used for bibliometric analysis.Results:A total of 3 340 Chinese and 10 761 English publications were included in this study. The annual Chinese publications remained stable, while English publications exhibited a linear growth. It was anticipated that the English publications would decline in the forthcoming years, although remaining high. China contributed the highest number of publications, and Zhejiang University was the institution with the largest number of publications. Bonomo RA, Chen L, etc. were high-impact authors in the field of CRGNB and had formed a stable cooperative group. Antimicrobial Agents and Chemotherapy was the journal with the largest number of publications. High-frequency keywords in the domain of CRGNB were comprehensively categorized into four distinct clusters, including carbapenem resistance mechanisms and gene transmission, antimicrobial drugs and combination therapy, management of critically ill patients, and infections and colonization. It was imperative to acknowledge the significance of all of these research areas. Burst word analysis suggested that carbapenem-resistant Enterobacterales virulence genes as well as new isoforms of Klebsiella pneumoniae carbapenemase (KPC) had become a research hotspot. Conclusions:The issue of carbapenem resistance remains a significant concern. Current research focus on the resistance mechanisms and antimicrobial agents, highlighting its significant academic advancement and practical applications. Fostering international collaboration through academic exchanges between research teams worldwide is imperative to establish robust cooperative relationships, facilitate multidisciplinary cooperation, and promote high-quality research.

Objective:Bibliometric analysis was performed to map scientific knowledge landscape, so that to explore the research status and future trends in the field of carbapenem-resistant Gram-negative bacteria (CRGNB) over the past decade.Methods:Literature on CRGNB published between January 1st, 2015 and December 31st, 2024 was retrieved from the China National Knowledge Internet (CNKI) database and Web of Science Core Collection (WoSCC). VOSviewer and CiteSpace were used for bibliometric analysis.Results:A total of 3 340 Chinese and 10 761 English publications were included in this study. The annual Chinese publications remained stable, while English publications exhibited a linear growth. It was anticipated that the English publications would decline in the forthcoming years, although remaining high. China contributed the highest number of publications, and Zhejiang University was the institution with the largest number of publications. Bonomo RA, Chen L, etc. were high-impact authors in the field of CRGNB and had formed a stable cooperative group. Antimicrobial Agents and Chemotherapy was the journal with the largest number of publications. High-frequency keywords in the domain of CRGNB were comprehensively categorized into four distinct clusters, including carbapenem resistance mechanisms and gene transmission, antimicrobial drugs and combination therapy, management of critically ill patients, and infections and colonization. It was imperative to acknowledge the significance of all of these research areas. Burst word analysis suggested that carbapenem-resistant Enterobacterales virulence genes as well as new isoforms of Klebsiella pneumoniae carbapenemase (KPC) had become a research hotspot. Conclusions:The issue of carbapenem resistance remains a significant concern. Current research focus on the resistance mechanisms and antimicrobial agents, highlighting its significant academic advancement and practical applications. Fostering international collaboration through academic exchanges between research teams worldwide is imperative to establish robust cooperative relationships, facilitate multidisciplinary cooperation, and promote high-quality research.

Objective:To identify the risk factors and to construct a predictive model for early postnatal mortality (with the first 7 days of life) in extremely preterm infants.Methods:This retrospective study involved 244 extremely preterm infants with a gestational age of 22 to 27 weeks and 6 days, born at the Affiliated Hospital of Jining Medical College from January 2017 to December 2022. They were divided into an early survival group ( n=140) and an early mortality group ( n=84), based on survival for ≥7 days after birth. LASSO and logistic regression were used to select risk factors for early mortality. A nomogram predictive model was constructed using the R software program. The goodness-of-fit tests, area under the curve (AUC), calibration curves, and decision curves were used to evaluate its performance and clinical usefulness. Results:LASSO regression and multivariate logistic regression analyses showed that breech delivery ( OR=3.055, 95% CI: 1.125-8.296), intubation in the delivery room ( OR=4.320, 95% CI: 1.328-14.053), diagnosis of grade Ⅲ-Ⅳ neonatal respiratory distress syndrome within 6 h after birth ( OR=11.552, 95% CI: 3.056-43.677), and use of adrenaline in the delivery room ( OR=10.706, 95% CI: 1.454-78.816) were risk factors for early mortality in extremely preterm infants. Conversely, large gestation age ( OR=0.234, 95% CI: 0.125-0.436), antenatal administration of corticosteroids to promote fetal lung maturity ( OR=0.046, 95% CI: 0.014-0.145), and the use of pulmonary surfactant within 6 h after birth ( OR=0.021, 95% CI: 0.004-0.122) were protective factors against mortality. The goodness of fit test of the early death risk nomogram prediction model for extremely preterm infants indicates a good fit ( P=0.702). The AUC of the model was 0.963 (95% CI: 0.943-0.983), with a sensitivity of 0.904 (95% CI: 0.806-0.949), specificity of 0.892 (95% CI: 0.829-0.938), and accuracy of 0.880. Decision curve analysis indicated that a threshold probability>2% would yield a net benefit. Conclusions:Breech delivery, intubation in the delivery room, use of adrenaline in the delivery room, and the diagnosis of grade Ⅲ-Ⅳ neonatal respiratory distress syndrome within 6 h post-birth are independent risk factors for early mortality in extremely preterm infants. Large gestational age, antenatal administration of corticosteroids to promote fetal lung maturity and use of pulmonary surfactant within 6 h after birth are protective factors. The constructed prediction model based on the aforementioned factors can quantitatively, conveniently, and intuitively assess the risk of early mortality in extremely preterm infants.