Development and validation of the prediction score for augmented renal clearance in critically Ill Japanese adults
Abstract Background Augmented renal clearance (ARC) decreases the therapeutic concentration of drugs excreted by the kidneys in critically ill patients. Several ARC prediction models have been developed and validated; however, their usefulness in Japan has not been comprehensively investigated. Thus...
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BMC
2024-11-01
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| Series: | Journal of Pharmaceutical Health Care and Sciences |
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| Online Access: | https://doi.org/10.1186/s40780-024-00394-2 |
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| author | Ryusei Mikami Shungo Imai Mineji Hayakawa Hitoshi Kashiwagi Yuki Sato Shunsuke Nashimoto Mitsuru Sugawara Yoh Takekuma |
| author_facet | Ryusei Mikami Shungo Imai Mineji Hayakawa Hitoshi Kashiwagi Yuki Sato Shunsuke Nashimoto Mitsuru Sugawara Yoh Takekuma |
| author_sort | Ryusei Mikami |
| collection | DOAJ |
| description | Abstract Background Augmented renal clearance (ARC) decreases the therapeutic concentration of drugs excreted by the kidneys in critically ill patients. Several ARC prediction models have been developed and validated; however, their usefulness in Japan has not been comprehensively investigated. Thus, we developed a unique ARC prediction model for a Japanese mixed intensive care unit (ICU) population and compared it with existing models. Methods This retrospective study enrolled a mixed ICU population in Japan from January 2019 and June 2022. The primary outcome was the development and validation of a model to predict ARC onset based on baseline information at ICU admission. Patients admitted until May 2021 were included in the training set, and external validation was performed on patients admitted thereafter. A multivariate logistic regression model was used to develop an integer-based predictive scoring system for ARC. The new model (the JPNARC score) was externally validated along with the ARC and Augmented Renal Clearance in Trauma Intensive Care (ARCTIC) scores. Results A total of 2,592 critically ill patients were enrolled initially, with 651 patients finally included after excluding 1,941 patients. The training and validation datasets comprised 456 and 195 patients, respectively. Multivariate analysis was performed to develop the JPNARC score, which incorporated age, sex, serum creatinine, and diagnosis upon ICU admission (trauma or central nervous system disease). The JPNARC score had a larger area under the receiver operating characteristic curve than the ARC and ARCTIC scores in the validation dataset (0.832, 0.633, and 0.740, respectively). Conclusions An integer-based scoring system was developed to predict ARC onset in a critically ill Japanese population and showed high predictive performance. New models designed to predict the often-unrecognized ARC phenomenon may aid in the decision-making process for upward drug dosage modifications, especially in resource- and labor-limited settings. |
| format | Article |
| id | doaj-art-60f6328c5d344d40bfcd78d655612c70 |
| institution | OA Journals |
| issn | 2055-0294 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Pharmaceutical Health Care and Sciences |
| spelling | doaj-art-60f6328c5d344d40bfcd78d655612c702025-08-20T02:13:26ZengBMCJournal of Pharmaceutical Health Care and Sciences2055-02942024-11-011011910.1186/s40780-024-00394-2Development and validation of the prediction score for augmented renal clearance in critically Ill Japanese adultsRyusei Mikami0Shungo Imai1Mineji Hayakawa2Hitoshi Kashiwagi3Yuki Sato4Shunsuke Nashimoto5Mitsuru Sugawara6Yoh Takekuma7Graduate School of Life Science, Hokkaido UniversityFaculty of Pharmacy, Keio UniversityDepartment of Emergency Medicine, Hokkaido University HospitalFaculty of Pharmaceutical Sciences, Hokkaido UniversityFaculty of Pharmaceutical Sciences, Hokkaido UniversityFaculty of Pharmaceutical Sciences, Hokkaido UniversityDepartment of Pharmacy, Hokkaido University HospitalDepartment of Pharmacy, Hokkaido University HospitalAbstract Background Augmented renal clearance (ARC) decreases the therapeutic concentration of drugs excreted by the kidneys in critically ill patients. Several ARC prediction models have been developed and validated; however, their usefulness in Japan has not been comprehensively investigated. Thus, we developed a unique ARC prediction model for a Japanese mixed intensive care unit (ICU) population and compared it with existing models. Methods This retrospective study enrolled a mixed ICU population in Japan from January 2019 and June 2022. The primary outcome was the development and validation of a model to predict ARC onset based on baseline information at ICU admission. Patients admitted until May 2021 were included in the training set, and external validation was performed on patients admitted thereafter. A multivariate logistic regression model was used to develop an integer-based predictive scoring system for ARC. The new model (the JPNARC score) was externally validated along with the ARC and Augmented Renal Clearance in Trauma Intensive Care (ARCTIC) scores. Results A total of 2,592 critically ill patients were enrolled initially, with 651 patients finally included after excluding 1,941 patients. The training and validation datasets comprised 456 and 195 patients, respectively. Multivariate analysis was performed to develop the JPNARC score, which incorporated age, sex, serum creatinine, and diagnosis upon ICU admission (trauma or central nervous system disease). The JPNARC score had a larger area under the receiver operating characteristic curve than the ARC and ARCTIC scores in the validation dataset (0.832, 0.633, and 0.740, respectively). Conclusions An integer-based scoring system was developed to predict ARC onset in a critically ill Japanese population and showed high predictive performance. New models designed to predict the often-unrecognized ARC phenomenon may aid in the decision-making process for upward drug dosage modifications, especially in resource- and labor-limited settings.https://doi.org/10.1186/s40780-024-00394-2Augmented renal clearancePrediction scoreIntensive care unitJapan |
| spellingShingle | Ryusei Mikami Shungo Imai Mineji Hayakawa Hitoshi Kashiwagi Yuki Sato Shunsuke Nashimoto Mitsuru Sugawara Yoh Takekuma Development and validation of the prediction score for augmented renal clearance in critically Ill Japanese adults Journal of Pharmaceutical Health Care and Sciences Augmented renal clearance Prediction score Intensive care unit Japan |
| title | Development and validation of the prediction score for augmented renal clearance in critically Ill Japanese adults |
| title_full | Development and validation of the prediction score for augmented renal clearance in critically Ill Japanese adults |
| title_fullStr | Development and validation of the prediction score for augmented renal clearance in critically Ill Japanese adults |
| title_full_unstemmed | Development and validation of the prediction score for augmented renal clearance in critically Ill Japanese adults |
| title_short | Development and validation of the prediction score for augmented renal clearance in critically Ill Japanese adults |
| title_sort | development and validation of the prediction score for augmented renal clearance in critically ill japanese adults |
| topic | Augmented renal clearance Prediction score Intensive care unit Japan |
| url | https://doi.org/10.1186/s40780-024-00394-2 |
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