Construction and validation of a predictive risk model for nosocomial infections with MDRO in NICUs: a multicenter observational study
ObjectivesThis study aimed to construct and validate a predictive risk model (PRM) for nosocomial infections with multi-drug resistant organism (MDRO) in neonatal intensive care units (NICUs), in order to provide a scientific and reliable prediction tool, and to provide reference for clinical preven...
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| Format: | Article |
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Frontiers Media S.A.
2023-06-01
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| Series: | Frontiers in Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2023.1193935/full |
| _version_ | 1797795000205967360 |
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| author | Jinyan Zhou Feixiang Luo Jianfeng Liang Xiaoying Cheng Xiaofei Chen Linyu Li Shuohui Chen |
| author_facet | Jinyan Zhou Feixiang Luo Jianfeng Liang Xiaoying Cheng Xiaofei Chen Linyu Li Shuohui Chen |
| author_sort | Jinyan Zhou |
| collection | DOAJ |
| description | ObjectivesThis study aimed to construct and validate a predictive risk model (PRM) for nosocomial infections with multi-drug resistant organism (MDRO) in neonatal intensive care units (NICUs), in order to provide a scientific and reliable prediction tool, and to provide reference for clinical prevention and control of MDRO infections in NICUs.MethodsThis multicenter observational study was conducted at NICUs of two tertiary children’s hospitals in Hangzhou, Zhejiang Province. Using cluster sampling, eligible neonates admitted to NICUs of research hospitals from January 2018 to December 2020 (modeling group) or from July 2021 to June 2022 (validation group) were included in this study. Univariate analysis and binary logistic regression analysis were used to construct the PRM. H-L tests, calibration curves, ROC curves and decision curve analysis were used to validate the PRM.ResultsFour hundred and thirty-five and one hundred fourteen neonates were enrolled in the modeling group and validation group, including 89 and 17 neonates infected with MDRO, respectively. Four independent risk factors were obtained and the PRM was constructed, namely: P = 1/ (1+ e−X), X = −4.126 + 1.089× (low birth weight) +1.435× (maternal age ≥ 35 years) +1.498× (use of antibiotics >7 days) + 0.790× (MDRO colonization). A nomogram was drawn to visualize the PRM. Through internal and external validation, the PRM had good fitting degree, calibration, discrimination and certain clinical validity. The prediction accuracy of the PRM was 77.19%.ConclusionPrevention and control strategies for each independent risk factor can be developed in NICUs. Moreover, clinical staff can use the PRM to early identification of neonates at high risk, and do targeted prevention to reduce MDRO infections in NICUs. |
| first_indexed | 2024-03-13T03:11:15Z |
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| institution | Directory Open Access Journal |
| issn | 2296-858X |
| language | English |
| last_indexed | 2024-03-13T03:11:15Z |
| publishDate | 2023-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Medicine |
| spelling | doaj.art-c9490386393144b1b80e0e5afe0311aa2023-06-26T12:13:36ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2023-06-011010.3389/fmed.2023.11939351193935Construction and validation of a predictive risk model for nosocomial infections with MDRO in NICUs: a multicenter observational studyJinyan Zhou0Feixiang Luo1Jianfeng Liang2Xiaoying Cheng3Xiaofei Chen4Linyu Li5Shuohui Chen6Administration Department of Nosocomial Infection, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, ChinaNeonatal Intensive Care Unit, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, ChinaStatistics Office, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, ChinaQuality Improvement Office, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, ChinaGastroenterology Department, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, ChinaHangzhou Children's Hospital, Hangzhou, Zhejiang, ChinaAdministration Department of Nosocomial Infection, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, ChinaObjectivesThis study aimed to construct and validate a predictive risk model (PRM) for nosocomial infections with multi-drug resistant organism (MDRO) in neonatal intensive care units (NICUs), in order to provide a scientific and reliable prediction tool, and to provide reference for clinical prevention and control of MDRO infections in NICUs.MethodsThis multicenter observational study was conducted at NICUs of two tertiary children’s hospitals in Hangzhou, Zhejiang Province. Using cluster sampling, eligible neonates admitted to NICUs of research hospitals from January 2018 to December 2020 (modeling group) or from July 2021 to June 2022 (validation group) were included in this study. Univariate analysis and binary logistic regression analysis were used to construct the PRM. H-L tests, calibration curves, ROC curves and decision curve analysis were used to validate the PRM.ResultsFour hundred and thirty-five and one hundred fourteen neonates were enrolled in the modeling group and validation group, including 89 and 17 neonates infected with MDRO, respectively. Four independent risk factors were obtained and the PRM was constructed, namely: P = 1/ (1+ e−X), X = −4.126 + 1.089× (low birth weight) +1.435× (maternal age ≥ 35 years) +1.498× (use of antibiotics >7 days) + 0.790× (MDRO colonization). A nomogram was drawn to visualize the PRM. Through internal and external validation, the PRM had good fitting degree, calibration, discrimination and certain clinical validity. The prediction accuracy of the PRM was 77.19%.ConclusionPrevention and control strategies for each independent risk factor can be developed in NICUs. Moreover, clinical staff can use the PRM to early identification of neonates at high risk, and do targeted prevention to reduce MDRO infections in NICUs.https://www.frontiersin.org/articles/10.3389/fmed.2023.1193935/fullneonatal intensive care unitmulti-drug resistant organismnosocomial infectionrisk factorpredictive risk model |
| spellingShingle | Jinyan Zhou Feixiang Luo Jianfeng Liang Xiaoying Cheng Xiaofei Chen Linyu Li Shuohui Chen Construction and validation of a predictive risk model for nosocomial infections with MDRO in NICUs: a multicenter observational study Frontiers in Medicine neonatal intensive care unit multi-drug resistant organism nosocomial infection risk factor predictive risk model |
| title | Construction and validation of a predictive risk model for nosocomial infections with MDRO in NICUs: a multicenter observational study |
| title_full | Construction and validation of a predictive risk model for nosocomial infections with MDRO in NICUs: a multicenter observational study |
| title_fullStr | Construction and validation of a predictive risk model for nosocomial infections with MDRO in NICUs: a multicenter observational study |
| title_full_unstemmed | Construction and validation of a predictive risk model for nosocomial infections with MDRO in NICUs: a multicenter observational study |
| title_short | Construction and validation of a predictive risk model for nosocomial infections with MDRO in NICUs: a multicenter observational study |
| title_sort | construction and validation of a predictive risk model for nosocomial infections with mdro in nicus a multicenter observational study |
| topic | neonatal intensive care unit multi-drug resistant organism nosocomial infection risk factor predictive risk model |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2023.1193935/full |
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