Objective To explore the potential contributors and obstacles of evidence translation for airway hu-midification management in hospitalized patients with laryngectomy tracheostomy and non-mechanical ventilation,so as to provide references for clinical evidence-based practice.Methods An interview outline and questionnaire were developed according to the consolidated framework for implementation research(CFIR).Using purposive sampling,12 healthcare professionals from Department of Otorhinolaryngology,Head and Neck Surgery of a tertiary hospital in Shanxi Province were recruited for semi-structured interviews,and thematic analysis was applied to extract main themes.The interview themes were transformed into survey items,and a survey was conducted among 42 healthcare professionals in the same department.Results Totally 16 contributors and 20 obstacles were identified across 4 domains:the credibility of the evidence and research team,the external support environment for evidence-based practice,the internal conditions for evidence-based practice,and the role recognition of implementers.Contributors include efficient internal collaboration and communication,and rigorous processes for evidence acquisition.Obstacles include insufficient educational resources,low patient knowledge acceptance capacity,lack of professional value a-mong healthcare staff.Conclusion Evidence translation of the humidification management for patients with non-mechanical ventilation after laryngectomy and tracheostomy was influenced by various factors.Future efforts should focus on constructing targeted airway humidification education content and an evaluation index system,and enhanc-ing the professional value and practical leadership of nursing staff.

Objective:To evaluate the image quality and radiation dose in contrast-enhanced thoracic-abdominal-pelvic CT using automatic tube voltage modulation (ATVM) coupled with artificial intelligence iterative reconstruction (AIIR) versus routine tube voltage combined with Karl-3D iterative reconstruction (Karl-3D IR), and to determine the optimal noise level for AIIR in contrast-enhanced thoracic-abdominal-pelvic CT.Methods:A total of 100 patients who underwent contrast-enhanced thoracic-abdominal-pelvic CT examination in the Affiliated Hospital of Hebei University from April to October, 2023 were randomly divided into group A and group B using a random number table, with 50 patients in each group. Group A was scanned using ATVM, and images were reconstructed using AIIR with 1-5 noise levels. Group B was scanned using tube voltage 120 kVp and images were reconstructed with Karl-3D IR and noise level 5. The single-to-noise ratio (SNR), contrast-to-noise ratio (CNR), effective dose (E), and size-specific dose estimate (SSDE) were recorded or calculated for all patients or images. Subjective evaluations of all images were performed. The quality of the reconstructed images using AIIR with 1-5 noise levels were compared and the optimal noise level of AIIR for image reconstruction was determined. Image quality and radiation dose were statistically analyzed for Group A (image reconstruction with optimal AIIR noise level) and Group B.Results:The mean SNR and mean CNR of the reconstructed images using AIIR with noise levels 1, 2, and 3 in group A were higher than those using AIIR with noise levels 4 and 5. The images reconstructed using AIIR with noise levels 3 and 4 scored higher in subjective assessment than those reconstructed using AIIR with noise levels 1, 2, and 5. Therefore, noise level 3 was optimal for AIIR in reconstruction of contrast-enhanced thoracic-abdominal-pelvic CT images. The mean SNR, mean CNR, and subjective evaluation score of group A using AIIR with noise level 3 were higher than those of group B using Karl-3D IR with noise level 5 ( P<0.001). The mean SSDE and the mean E of group A were reduced by 46% and 41%, respectively, compared with those of group B. Conclusions:ATVM technology combined with the AIIR algorithm can improve image quality and reduced patient radiation dose in contrast-enhanced thoracic-abdominal-pelvic CT. Noise level 3 is optimal for AIIR in the reconstruction of arterial-phase and venous-phase contrast-enhanced thoracic-abdominal-pelvic CT images.

Objective:To comprehensively identify, describe and evaluate the research evidence on the application of ERAS in perioperative head and neck cancer by using the method of evidence mapping, so as to understand the research status and provide reference for clinical practice and future research in this field.Methods:Adopting an evidence-integrated research approach, PubMed, Embase, CINAHL, Web of Science, Cochrane Library, CNKI, Wanfang, VIP and Chinese Biomedical Literature Database were searched by computer. In addition, relevant references and grey literature databases such as OpenGrey were manually searched until August 25, 2024, to screen and summarize the included literature, and different quality evaluation tools were used to evaluate the quality of the included studies. The present research situation was presented with text and graphs.Results:A total of 105 articles were included, including 101 original studies and 4 systematic reviews/Meta-analyses. The number of published literature showed an increasing trend over time, but it fluctuated in a zigzag pattern. The most published studies were in China, and the study population was mainly patients with laryngeal and oral cancer, with a sample size of 51-100 cases. The results of methodology quality evaluation showed that the quality of most studies was relatively low. The intervention measures mainly involved 9 subjects, such as pre-rehabilitation, nutritional support, prevention of nausea and vomiting, and the outcome indicators involved 2 aspects related to patients and hospital. More attention was paid to outcome indicators such as complication rate and length of stay, while less attention was paid to outcome indicators such as condition of sputum and survival time. Most outcome effects were shown to be "beneficial", but some outcome effects were still controversial.Conclusions:ERAS has generally shown positive effects in perioperative application of head and neck cancer, but the quality of most studies is low. More high-quality clinical studies are needed in the future to provide more sufficient evidence for the application of ERAS in this field.

Objective:To comprehensively identify, describe and evaluate the research evidence on the application of ERAS in perioperative head and neck cancer by using the method of evidence mapping, so as to understand the research status and provide reference for clinical practice and future research in this field.Methods:Adopting an evidence-integrated research approach, PubMed, Embase, CINAHL, Web of Science, Cochrane Library, CNKI, Wanfang, VIP and Chinese Biomedical Literature Database were searched by computer. In addition, relevant references and grey literature databases such as OpenGrey were manually searched until August 25, 2024, to screen and summarize the included literature, and different quality evaluation tools were used to evaluate the quality of the included studies. The present research situation was presented with text and graphs.Results:A total of 105 articles were included, including 101 original studies and 4 systematic reviews/Meta-analyses. The number of published literature showed an increasing trend over time, but it fluctuated in a zigzag pattern. The most published studies were in China, and the study population was mainly patients with laryngeal and oral cancer, with a sample size of 51-100 cases. The results of methodology quality evaluation showed that the quality of most studies was relatively low. The intervention measures mainly involved 9 subjects, such as pre-rehabilitation, nutritional support, prevention of nausea and vomiting, and the outcome indicators involved 2 aspects related to patients and hospital. More attention was paid to outcome indicators such as complication rate and length of stay, while less attention was paid to outcome indicators such as condition of sputum and survival time. Most outcome effects were shown to be "beneficial", but some outcome effects were still controversial.Conclusions:ERAS has generally shown positive effects in perioperative application of head and neck cancer, but the quality of most studies is low. More high-quality clinical studies are needed in the future to provide more sufficient evidence for the application of ERAS in this field.

Objective To explore the potential contributors and obstacles of evidence translation for airway hu-midification management in hospitalized patients with laryngectomy tracheostomy and non-mechanical ventilation,so as to provide references for clinical evidence-based practice.Methods An interview outline and questionnaire were developed according to the consolidated framework for implementation research(CFIR).Using purposive sampling,12 healthcare professionals from Department of Otorhinolaryngology,Head and Neck Surgery of a tertiary hospital in Shanxi Province were recruited for semi-structured interviews,and thematic analysis was applied to extract main themes.The interview themes were transformed into survey items,and a survey was conducted among 42 healthcare professionals in the same department.Results Totally 16 contributors and 20 obstacles were identified across 4 domains:the credibility of the evidence and research team,the external support environment for evidence-based practice,the internal conditions for evidence-based practice,and the role recognition of implementers.Contributors include efficient internal collaboration and communication,and rigorous processes for evidence acquisition.Obstacles include insufficient educational resources,low patient knowledge acceptance capacity,lack of professional value a-mong healthcare staff.Conclusion Evidence translation of the humidification management for patients with non-mechanical ventilation after laryngectomy and tracheostomy was influenced by various factors.Future efforts should focus on constructing targeted airway humidification education content and an evaluation index system,and enhanc-ing the professional value and practical leadership of nursing staff.

Objective:To evaluate the image quality and radiation dose in contrast-enhanced thoracic-abdominal-pelvic CT using automatic tube voltage modulation (ATVM) coupled with artificial intelligence iterative reconstruction (AIIR) versus routine tube voltage combined with Karl-3D iterative reconstruction (Karl-3D IR), and to determine the optimal noise level for AIIR in contrast-enhanced thoracic-abdominal-pelvic CT.Methods:A total of 100 patients who underwent contrast-enhanced thoracic-abdominal-pelvic CT examination in the Affiliated Hospital of Hebei University from April to October, 2023 were randomly divided into group A and group B using a random number table, with 50 patients in each group. Group A was scanned using ATVM, and images were reconstructed using AIIR with 1-5 noise levels. Group B was scanned using tube voltage 120 kVp and images were reconstructed with Karl-3D IR and noise level 5. The single-to-noise ratio (SNR), contrast-to-noise ratio (CNR), effective dose (E), and size-specific dose estimate (SSDE) were recorded or calculated for all patients or images. Subjective evaluations of all images were performed. The quality of the reconstructed images using AIIR with 1-5 noise levels were compared and the optimal noise level of AIIR for image reconstruction was determined. Image quality and radiation dose were statistically analyzed for Group A (image reconstruction with optimal AIIR noise level) and Group B.Results:The mean SNR and mean CNR of the reconstructed images using AIIR with noise levels 1, 2, and 3 in group A were higher than those using AIIR with noise levels 4 and 5. The images reconstructed using AIIR with noise levels 3 and 4 scored higher in subjective assessment than those reconstructed using AIIR with noise levels 1, 2, and 5. Therefore, noise level 3 was optimal for AIIR in reconstruction of contrast-enhanced thoracic-abdominal-pelvic CT images. The mean SNR, mean CNR, and subjective evaluation score of group A using AIIR with noise level 3 were higher than those of group B using Karl-3D IR with noise level 5 ( P<0.001). The mean SSDE and the mean E of group A were reduced by 46% and 41%, respectively, compared with those of group B. Conclusions:ATVM technology combined with the AIIR algorithm can improve image quality and reduced patient radiation dose in contrast-enhanced thoracic-abdominal-pelvic CT. Noise level 3 is optimal for AIIR in the reconstruction of arterial-phase and venous-phase contrast-enhanced thoracic-abdominal-pelvic CT images.

Objective To explore the influencing factors of dwarfism in children and construct a nomogram model. Methods From June 2020 to December 2022, 1, 500 children were selected as the research objects, and 1, 422 cases were effectively investigated. According to incidence of dwarfism, the children were divided into normal group (n=1, 351) and dwarfism group (n=71). Univariate and multivariate Logistic regression analyses were used to explore the influencing factors of dwarfism in children; the R software was used to construct a nomogram model for prediction of the occurrence of dwarfism in children, and the receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the discrimination and consistency of the nomogram model. Results Among the 1 422 children, 71 cases had dwarfism, with an incidence rate of 4.99%. Multivariate Logistic regression analysis showed that birth weight, family history of dwarfism, milk intake and physical exercise were the influencing factors for the occurrence of dwarfism in children (P < 0.05). The area under the curve of the ROC curve predicted by the nomogram model for the occurrence of dwarfism in children was 0.897 (95%CI, 0.856 to 0.938), with good discrimination; the calibration curve slope of the nomogram model for predicting the occurrence of dwarfism in children approached 1, and the Hosmer-Lemeshow goodness of fit test showed that the was 5.020 and P was 0.740, indicating good consistency. Conclusion The nomogram model for predicting the occurrence of dwarfism in children based on four influencing factors of birth weight, family history of dwarfism, milk intake and physical exercise has good discrimination and consistency, which can provide reference for the development of personalized intervention measures in clinical practice.

Objective To investigate the influencing factors of facial pressure injury related to ventilation in prone positioning in children with severe pneumonia and to construct a nomogram prediction model. Methods A total of 158 children with severe pneumonia who underwent prone positioning ventilation were selected as research subjects. Clinical data were collected, and the children were divided into injury group (31 cases) and non-injury group (127 cases) based on whether facial pressure injury occurred. Univariate and multivariate Logistic regression analysis were used to explore the influencing factors of facial pressure injury related to prone positioning ventilation in children with severe pneumonia; the receiver operating characteristic (ROC) curve, consistency index, and Hosmer-Lemeshow goodness-of-fit test were used to evaluate the predictive efficiency of the nomogram model for facial pressure injury related to prone positioning ventilation in children with severe pneumonia. Results Univariate analysis showed that the proportion of children aged < 3 years, the proportion of those with complications, ventilation time in prone positioning, the proportions of children with sedative drugs and poor nutritional status, no decompression dressings, and the proportions of children without prone positioning ventilation training for medical staff in the injury group were higher or longer than that in the non-injury group (P < 0.05). Multivariate Logistic regression analysis showed that age < 3 years, presence of complications, longer prone positioning ventilation time, no decompression dressings, and lack of prone positioning ventilation training for medical staff were independent risk factors for facial pressure injury related to prone positioning ventilation in children with severe pneumonia (P < 0.05), and a nomogram prediction model was constructed based on these factors. The consistency index of the nomogram model was 0.940, and the area under the ROC curve was 0.978 (95%CI, 0.958 to 0.999). The calibration curve of predicting facial pressure injury related to prone positioning ventilation in children with severe pneumonia approached the ideal curve, and the Hosmer-Lemeshow goodness-of-fit test showed good fitting (χ²=12.416, P < 0.05). Conclusion The nomogram prediction model constructed based on 5 independent risk factors in this study has high risk identification ability and can early identify high-risk children with facial pressure injury related to prone positioning ventilation in severe pneumonia.

Objective:To review and summarize the best evidence of prevention and control measures of carbapenem-resistant Enterobacteriaceae (CRE) hospital infection, and provide evidence-based reference for health care workers to prevent and control CRE infection. Methods:A literature search strategy was developed to systematically search BMJ Best Clinical Practice, UpToDate, the World Health Organization, the Centers for Disease Control and Prevention website, the European Centers for Disease Control and Prevention website, the International Guidelines Collaboration website, the National Practice Technical Guidelines Library of the United States, the National Institute of Health and Clinical Optimization in the United Kingdom, the Ontario Medical Association of Canada, Maimai Tong, Cochrane Library, Australian Joanna Briggs Institute Evidence-Based Health Care Center database, PubMed, Web of Science, China National Knowledge Network, Wanfang database, VIP database, Chinese Biomedical Literature database of evidence related to the prevention and control of CRE hospital infection. The search period was from January 1, 2018 to October 1, 2023. The literature quality was evaluated independently by two research members, and evidence extraction and synthesis were carried out for the included literature.Results:A total of 10 articles were included, including 6 guidelines, 3 expert consensus articles, and 1 systematic review. 29 best evidences were formed from 6 aspects: preventive monitoring, active screening, contact isolation, environmental cleaning and disinfection, bacterial colonization, and hand hygiene measures.Conclusions:This study summarized the best evidence on the prevention and control measures of CRE infection in hospitals. Clinical staff and management departments should take active and effective prevention and control measures based on the local CRE epidemiological situation and resource requirements to reduce the risk of CRE infection.

Objective:To summarize emergency rescue capacity evaluation tools for community nurses.Methods:China National Knowledge Infrastructure, Wanfang Data, VIP, China Biology Medicine disc, PubMed, Embase, CINAHL, Web of Science core collection, and other databases were searched by computer, and the search period was from the establishment of the databases to April 23, 2023. The relevant contents of emergency rescue capacity evaluation tools for community nurses were extracted and analyzed.Results:A total of 16 articles were included, involving seven kinds of emergency rescue capacity assessment tools for community nurses. The evaluation methods of the tools were all self-evaluation. The evaluation mainly involved the ability of nurses in four stages of emergency rescue prevention, preparation, response, and recovery.Conclusions:There are limitations in the evaluation content, method, and application effect of the emergency rescue capacity evaluation tools for community nurses. In the future, it is still necessary to develop or introduce foreign emergency rescue capacity evaluation tools with comprehensive evaluation content and good reliability and validity.