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Can we reduce CT scan and hospital costs in children with blunt trauma using four parameters? ANNALS OF PEDIATRIC SURGERY 2022. [DOI: 10.1186/s43159-021-00142-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Blunt trauma is one of the most common causes of admission to the emergency service in childhood. Children with trauma are generally evaluated in emergency services where pediatric and adult patients are together, and difficulties are experienced in managing children exposed to trauma. CT is preferred for quick detection and grading of toracoabdominal, skeleton, and neurological injury in high energy trauma. The present study aims to determine the severity of trauma and whether CT exposure can be reduced and patient cost using four parameters.
This study was conducted with 586 pediatric patients exposed to blunt abdominal trauma. The clinical prediction rule consisted of four parameters, including abdominal pain, physical examination findings, aspartate aminotransferase (AST), and chest x-ray (CXR, which was used to predict intraabdominal injury in patients with blunt trauma. Patients with no parameters of the clinical decision rule were considered very low risk, and those with one or more parameters were considered at risk. The hospital cost of the patients with and without clinical decision rule was calculated and compared.
Results
In our study, according to the four-variable clinical prediction rule, 88.1% of the patients had a very low risk of intraabdominal injury and 11.9% of them were at risk. The sensitivity was 97.3%, specificity 98.2%, and accuracy was 97.4% in very low-risk patients with four variables clinical prediction rule. In the very low-risk patients, the abnormal CT rate was 0.3% and conservative treatment was performed. With the use of four variables, 0.17% of solid organ injuries may be overlooked. In the risk of patients, 2.9% of these patients were abnormal CT findings, while tube thoracostomy was performed in four patients with pneumothorax, conservative treatment was performed in other patients.
It was determined that routine computed tomography scan increased the patient cost by 5.5 times.
Conclusion
Patients exposed to blunt trauma with a very low risk of intra-abdominal injury can be identified with a four-variable clinical prediction rule. According to the four-variable clinical prediction rule, very low-risk patients do not require immediate CT. The hospital costs can be reduced by reducing the CT scan. However, it should be kept in mind that a small proportion of intra-abdominal injuries may be overlooked.
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Wang L, Huang X, Zhou J, Wang Y, Zhong W, Yu Q, Wang W, Ye Z, Lin Q, Hong X, Zeng P, Zhang M. Predicting the occurrence of multidrug-resistant organism colonization or infection in ICU patients: development and validation of a novel multivariate prediction model. Antimicrob Resist Infect Control 2020; 9:66. [PMID: 32430043 PMCID: PMC7236142 DOI: 10.1186/s13756-020-00726-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 05/05/2020] [Indexed: 11/11/2022] Open
Abstract
Background Multidrug-resistant organisms (MDROs) have emerged as an important cause of poor prognoses of patients in the intensive care unit (ICU). This study aimed to establish an easy-to-use nomogram for predicting the occurrence of MDRO colonization or infection in ICU patients. Methods In this study, we developed a nomogram based on predictors in patients admitted to the ICU in the First Affiliated Hospital of Xiamen University from 2016 to 2018 using univariate and multivariate logistic regression analysis. We externally validated this nomogram in patients from another hospital over a similar period, and assessed its performance by calculating the area under the receiver operating characteristic (ROC) curve (AUC) and performing a decision curve analysis. Results 331 patients in the primary cohort and 181 patients in the validation cohort were included in the statistical analysis. Independent factors derived from the primary cohort to predict MDRO colonization or infection were male sex, higher C-reactive protein (CRP) levels and higher Pitt bacteremia scores (Pitt scores), which were all assembled in the nomogram. The nomogram yielded good discrimination with an AUC of 0.77 (95% CI 0.70–0.84), and the range of threshold probabilities of decision curves was approximately 30–95%. Conclusion This easy-to-use nomogram is potentially useful for predicting the occurrence of MDRO colonization or infection in ICU patients.
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Affiliation(s)
- Li Wang
- Intensive Care Unit, Xiamen Hospital of Traditional Chinese Medicine, 1739 Xian Yue Road, Xiamen, 361009, Fujian Province, China
| | - Xiaolong Huang
- Intensive Care Unit, First Affiliated Hospital of Xiamen University, 55 Zhen Hai Road, Xiamen, 361000, Fujian Province, China
| | - Jiating Zhou
- Intensive Care Unit, First Affiliated Hospital of Xiamen University, 55 Zhen Hai Road, Xiamen, 361000, Fujian Province, China
| | - Yajing Wang
- Intensive Care Unit, Xiamen Hospital of Traditional Chinese Medicine, 1739 Xian Yue Road, Xiamen, 361009, Fujian Province, China
| | - Weizhang Zhong
- Intensive Care Unit, Xiamen Hospital of Traditional Chinese Medicine, 1739 Xian Yue Road, Xiamen, 361009, Fujian Province, China
| | - Qing Yu
- Intensive Care Unit, Xiamen Hospital of Traditional Chinese Medicine, 1739 Xian Yue Road, Xiamen, 361009, Fujian Province, China
| | - Weiping Wang
- Intensive Care Unit, Xiamen Hospital of Traditional Chinese Medicine, 1739 Xian Yue Road, Xiamen, 361009, Fujian Province, China
| | - Zhiqiao Ye
- Intensive Care Unit, Xiamen Hospital of Traditional Chinese Medicine, 1739 Xian Yue Road, Xiamen, 361009, Fujian Province, China
| | - Qiaoyan Lin
- Intensive Care Unit, Xiamen Hospital of Traditional Chinese Medicine, 1739 Xian Yue Road, Xiamen, 361009, Fujian Province, China
| | - Xing Hong
- Intensive Care Unit, Xiamen Hospital of Traditional Chinese Medicine, 1739 Xian Yue Road, Xiamen, 361009, Fujian Province, China
| | - Ping Zeng
- Intensive Care Unit, Xiamen Hospital of Traditional Chinese Medicine, 1739 Xian Yue Road, Xiamen, 361009, Fujian Province, China
| | - Minwei Zhang
- Intensive Care Unit, First Affiliated Hospital of Xiamen University, 55 Zhen Hai Road, Xiamen, 361000, Fujian Province, China.
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