Yuping Li, Xianru Gao, Haiqing Diao, Tian Shi, Jingyue Zhang, Yuting Liu, Qingping Zeng, JiaLi Ding, Juan Chen, Kai Yang, Qiang Ma, Xiaoguang Liu, Hailong Yu, Guangyu Lu
{"title":"神经重症监护病房耐碳青霉烯类鲍曼不动杆菌感染风险预测提名图的开发与应用:一项混合方法研究。","authors":"Yuping Li, Xianru Gao, Haiqing Diao, Tian Shi, Jingyue Zhang, Yuting Liu, Qingping Zeng, JiaLi Ding, Juan Chen, Kai Yang, Qiang Ma, Xiaoguang Liu, Hailong Yu, Guangyu Lu","doi":"10.1186/s13756-024-01420-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to develop and apply a nomogram with good accuracy to predict the risk of CRAB infections in neuro-critically ill patients. In addition, the difficulties and expectations of application such a tool in clinical practice was investigated.</p><p><strong>Methods: </strong>A mixed methods sequential explanatory study design was utilized. We first conducted a retrospective study to identify the risk factors for the development of CRAB infections in neuro-critically ill patients; and further develop and validate a nomogram predictive model. Then, based on the developed predictive tool, medical staff in the neuro-ICU were received an in-depth interview to investigate their opinions and barriers in using the prediction tool during clinical practice. The model development and validation is carried out by R. The transcripts of the interviews were analyzed by Maxqda.</p><p><strong>Results: </strong>In our cohort, the occurrence of CRAB infections was 8.63% (47/544). Multivariate regression analysis showed that the length of neuro-ICU stay, male, diabetes, low red blood cell (RBC) count, high levels of procalcitonin (PCT), and number of antibiotics ≥ 2 were independent risk factors for CRAB infections in neuro-ICU patients. Our nomogram model demonstrated a good calibration and discrimination in both training and validation sets, with AUC values of 0.816 and 0.875. Additionally, the model demonstrated good clinical utility. The significant barriers identified in the interview include \"skepticism about the accuracy of the model\", \"delay in early prediction by the indicator of length of neuro-ICU stay\", and \"lack of a proper protocol for clinical application\".</p><p><strong>Conclusions: </strong>We established and validated a nomogram incorporating six easily accessed indicators during clinical practice (the length of neuro-ICU stay, male, diabetes, RBC, PCT level, and the number of antibiotics used) to predict the risk of CRAB infections in neuro-ICU patients. Medical staff are generally interested in using the tool to predict the risk of CRAB, however delivering clinical prediction tools in routine clinical practice remains challenging.</p>","PeriodicalId":7950,"journal":{"name":"Antimicrobial Resistance and Infection Control","volume":"13 1","pages":"62"},"PeriodicalIF":4.8000,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11170918/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development and application of a risk nomogram for the prediction of risk of carbapenem-resistant Acinetobacter baumannii infections in neuro-intensive care unit: a mixed method study.\",\"authors\":\"Yuping Li, Xianru Gao, Haiqing Diao, Tian Shi, Jingyue Zhang, Yuting Liu, Qingping Zeng, JiaLi Ding, Juan Chen, Kai Yang, Qiang Ma, Xiaoguang Liu, Hailong Yu, Guangyu Lu\",\"doi\":\"10.1186/s13756-024-01420-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>This study aimed to develop and apply a nomogram with good accuracy to predict the risk of CRAB infections in neuro-critically ill patients. In addition, the difficulties and expectations of application such a tool in clinical practice was investigated.</p><p><strong>Methods: </strong>A mixed methods sequential explanatory study design was utilized. We first conducted a retrospective study to identify the risk factors for the development of CRAB infections in neuro-critically ill patients; and further develop and validate a nomogram predictive model. Then, based on the developed predictive tool, medical staff in the neuro-ICU were received an in-depth interview to investigate their opinions and barriers in using the prediction tool during clinical practice. The model development and validation is carried out by R. The transcripts of the interviews were analyzed by Maxqda.</p><p><strong>Results: </strong>In our cohort, the occurrence of CRAB infections was 8.63% (47/544). Multivariate regression analysis showed that the length of neuro-ICU stay, male, diabetes, low red blood cell (RBC) count, high levels of procalcitonin (PCT), and number of antibiotics ≥ 2 were independent risk factors for CRAB infections in neuro-ICU patients. Our nomogram model demonstrated a good calibration and discrimination in both training and validation sets, with AUC values of 0.816 and 0.875. Additionally, the model demonstrated good clinical utility. The significant barriers identified in the interview include \\\"skepticism about the accuracy of the model\\\", \\\"delay in early prediction by the indicator of length of neuro-ICU stay\\\", and \\\"lack of a proper protocol for clinical application\\\".</p><p><strong>Conclusions: </strong>We established and validated a nomogram incorporating six easily accessed indicators during clinical practice (the length of neuro-ICU stay, male, diabetes, RBC, PCT level, and the number of antibiotics used) to predict the risk of CRAB infections in neuro-ICU patients. Medical staff are generally interested in using the tool to predict the risk of CRAB, however delivering clinical prediction tools in routine clinical practice remains challenging.</p>\",\"PeriodicalId\":7950,\"journal\":{\"name\":\"Antimicrobial Resistance and Infection Control\",\"volume\":\"13 1\",\"pages\":\"62\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11170918/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Antimicrobial Resistance and Infection Control\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s13756-024-01420-6\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Antimicrobial Resistance and Infection Control","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13756-024-01420-6","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
Development and application of a risk nomogram for the prediction of risk of carbapenem-resistant Acinetobacter baumannii infections in neuro-intensive care unit: a mixed method study.
Objective: This study aimed to develop and apply a nomogram with good accuracy to predict the risk of CRAB infections in neuro-critically ill patients. In addition, the difficulties and expectations of application such a tool in clinical practice was investigated.
Methods: A mixed methods sequential explanatory study design was utilized. We first conducted a retrospective study to identify the risk factors for the development of CRAB infections in neuro-critically ill patients; and further develop and validate a nomogram predictive model. Then, based on the developed predictive tool, medical staff in the neuro-ICU were received an in-depth interview to investigate their opinions and barriers in using the prediction tool during clinical practice. The model development and validation is carried out by R. The transcripts of the interviews were analyzed by Maxqda.
Results: In our cohort, the occurrence of CRAB infections was 8.63% (47/544). Multivariate regression analysis showed that the length of neuro-ICU stay, male, diabetes, low red blood cell (RBC) count, high levels of procalcitonin (PCT), and number of antibiotics ≥ 2 were independent risk factors for CRAB infections in neuro-ICU patients. Our nomogram model demonstrated a good calibration and discrimination in both training and validation sets, with AUC values of 0.816 and 0.875. Additionally, the model demonstrated good clinical utility. The significant barriers identified in the interview include "skepticism about the accuracy of the model", "delay in early prediction by the indicator of length of neuro-ICU stay", and "lack of a proper protocol for clinical application".
Conclusions: We established and validated a nomogram incorporating six easily accessed indicators during clinical practice (the length of neuro-ICU stay, male, diabetes, RBC, PCT level, and the number of antibiotics used) to predict the risk of CRAB infections in neuro-ICU patients. Medical staff are generally interested in using the tool to predict the risk of CRAB, however delivering clinical prediction tools in routine clinical practice remains challenging.
期刊介绍:
Antimicrobial Resistance and Infection Control is a global forum for all those working on the prevention, diagnostic and treatment of health-care associated infections and antimicrobial resistance development in all health-care settings. The journal covers a broad spectrum of preeminent practices and best available data to the top interventional and translational research, and innovative developments in the field of infection control.