{"title":"印度尼西亚巴东重症监护病房患者急性肾损伤预测评分的发展。","authors":"Liliriawati Ananta Kahar","doi":"10.5644/ama2006-124.454","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This study aims to develop and create a specialized acute kidney injury (AKI) predictor score for the intensive care unit (ICU) patients in Padang, Indonesia.</p><p><strong>Patients and methods: </strong>This study was a prospective observational study on 352 ICU patients at three specialized hospitals in Padang City; Dr. M. Djamil General Hospital, Dr. Rasidin General Hospital, and Siti Rahmah Islamic Hospital. Data regarding demographics, clinical characteristics, laboratory results, and outcomes related to AKI were gathered. The factors that predict AKI were identified using multivariate logistic regression analysis to determine independent factors. The predictor scores were created using regression coefficients and then internally confirmed.</p><p><strong>Results: </strong>Out of a total of 352 patients, 128 individuals (36.4%) suffered from AKI. Factors that independently predict the occurrence of AKI include age over 60 years old, having a history of chronic kidney disease, having sepsis, need for vasopressors, and having creatinine level 1.3 mg/dL (IQR 1.0-1.8) upon admission to ICU. An area under the curve (AUC) of 0.85 (95% CI 0.80-0.90) indicated the strong performance of the constructed predictor score.</p><p><strong>Conclusion: </strong>The constructed AKI predictor score a scale factor of 10, resulting in a range of 0-10 for the AKI predictor score. It demonstrates a good level of accuracy in predicting AKI in ICU patients in Padang. This score can be used by healthcare professionals to quickly identify and categorize individuals based on their risk level, facilitating timely intervention and personalized treatment.</p>","PeriodicalId":38313,"journal":{"name":"Acta medica academica","volume":"53 2","pages":"136-145"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11626242/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development of Acute Kidney Injury Predictor Score in Intensive Care Unit Patients in Padang, Indonesia.\",\"authors\":\"Liliriawati Ananta Kahar\",\"doi\":\"10.5644/ama2006-124.454\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>This study aims to develop and create a specialized acute kidney injury (AKI) predictor score for the intensive care unit (ICU) patients in Padang, Indonesia.</p><p><strong>Patients and methods: </strong>This study was a prospective observational study on 352 ICU patients at three specialized hospitals in Padang City; Dr. M. Djamil General Hospital, Dr. Rasidin General Hospital, and Siti Rahmah Islamic Hospital. Data regarding demographics, clinical characteristics, laboratory results, and outcomes related to AKI were gathered. The factors that predict AKI were identified using multivariate logistic regression analysis to determine independent factors. The predictor scores were created using regression coefficients and then internally confirmed.</p><p><strong>Results: </strong>Out of a total of 352 patients, 128 individuals (36.4%) suffered from AKI. Factors that independently predict the occurrence of AKI include age over 60 years old, having a history of chronic kidney disease, having sepsis, need for vasopressors, and having creatinine level 1.3 mg/dL (IQR 1.0-1.8) upon admission to ICU. An area under the curve (AUC) of 0.85 (95% CI 0.80-0.90) indicated the strong performance of the constructed predictor score.</p><p><strong>Conclusion: </strong>The constructed AKI predictor score a scale factor of 10, resulting in a range of 0-10 for the AKI predictor score. It demonstrates a good level of accuracy in predicting AKI in ICU patients in Padang. This score can be used by healthcare professionals to quickly identify and categorize individuals based on their risk level, facilitating timely intervention and personalized treatment.</p>\",\"PeriodicalId\":38313,\"journal\":{\"name\":\"Acta medica academica\",\"volume\":\"53 2\",\"pages\":\"136-145\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11626242/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta medica academica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5644/ama2006-124.454\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta medica academica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5644/ama2006-124.454","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
摘要
目的:本研究旨在为印度尼西亚巴东的重症监护病房(ICU)患者开发和创建专门的急性肾损伤(AKI)预测评分。患者与方法:本研究对巴东市3家专科医院352例ICU患者进行前瞻性观察研究;M. Djamil医生总医院、Rasidin医生总医院和Siti Rahmah伊斯兰医院。收集了与AKI相关的人口统计学、临床特征、实验室结果和结局的数据。预测AKI的因素采用多变量logistic回归分析确定独立因素。预测分数是使用回归系数创建的,然后内部确认。结果:352例患者中,128例(36.4%)患有AKI。独立预测AKI发生的因素包括:年龄超过60岁、有慢性肾脏疾病史、有败血症、需要升压药物、入ICU时肌酐水平为1.3 mg/dL (IQR 1.0-1.8)。曲线下面积(AUC)为0.85 (95% CI 0.80-0.90)表明构建的预测评分表现良好。结论:构建的AKI预测评分量表因子为10,AKI预测评分范围为0-10。它显示了预测巴东ICU患者AKI的良好准确性。医疗保健专业人员可以使用该评分根据个人的风险水平快速识别和分类,促进及时干预和个性化治疗。
Development of Acute Kidney Injury Predictor Score in Intensive Care Unit Patients in Padang, Indonesia.
Objective: This study aims to develop and create a specialized acute kidney injury (AKI) predictor score for the intensive care unit (ICU) patients in Padang, Indonesia.
Patients and methods: This study was a prospective observational study on 352 ICU patients at three specialized hospitals in Padang City; Dr. M. Djamil General Hospital, Dr. Rasidin General Hospital, and Siti Rahmah Islamic Hospital. Data regarding demographics, clinical characteristics, laboratory results, and outcomes related to AKI were gathered. The factors that predict AKI were identified using multivariate logistic regression analysis to determine independent factors. The predictor scores were created using regression coefficients and then internally confirmed.
Results: Out of a total of 352 patients, 128 individuals (36.4%) suffered from AKI. Factors that independently predict the occurrence of AKI include age over 60 years old, having a history of chronic kidney disease, having sepsis, need for vasopressors, and having creatinine level 1.3 mg/dL (IQR 1.0-1.8) upon admission to ICU. An area under the curve (AUC) of 0.85 (95% CI 0.80-0.90) indicated the strong performance of the constructed predictor score.
Conclusion: The constructed AKI predictor score a scale factor of 10, resulting in a range of 0-10 for the AKI predictor score. It demonstrates a good level of accuracy in predicting AKI in ICU patients in Padang. This score can be used by healthcare professionals to quickly identify and categorize individuals based on their risk level, facilitating timely intervention and personalized treatment.