Physician practice and PECARN rule outperform CATCH and CHALICE rules based on the detection of traumatic brain injury as defined by PECARN

Babl, Franz E; Bressan, Silvia

doi:10.1136/ebmed-2014-110090

Cited by 10 publications

(9 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, according to the literature, there are studies showing that physician practice and the PECARN rules outperform the CATCH and CHALICE rules based on the detection of TBI (15). Therefore, the focus was on the PECARN rules in the current study.…”

Section: Discussionmentioning

confidence: 99%

“…There are other prediction methods for CT use in pediatric TBI, such as the Canadian Assessment of Tomography for Childhood Head injury (CATCH) and the Children's Head Injury Algorithm for the Prediction of Important Clinical Events (CHALICE). However, according to the literature, there are studies showing that physician practice and the PECARN rules outperform the CATCH and CHALICE rules based on the detection of TBI (15). Therefore, the focus was on the PECARN rules in the current study.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Pediatric Emergency Care Applied Research Network head injuryprediction rules: on the basis of cost and effectiveness

Gökharman¹,

Aydın²,

Fatihoğlu³

et al. 2017

Turk J Med Sci

View full text Add to dashboard Cite

Background/aim: Head injuries are commonly seen in the pediatric population. Noncontrast enhanced cranial CT is the method of choice to detect possible traumatic brain injury (TBI). Concerns about ionizing radiation exposure make the evaluation more challenging. The aim of this study was to evaluate the effectiveness of the Pediatric Emergency Care Applied Research Network (PECARN) rules in predicting clinically important TBI and to determine the amount of medical resource waste and unnecessary radiation exposure. Materials and methods:This retrospective study included 1041 pediatric patients presented to the emergency department. The patients were divided into subgroups of "appropriate for cranial CT", "not appropriate for cranial CT" and "cranial CT/observation of patient; both are appropriate". To determine the effectiveness of the PECARN rules, data were analyzed according to the presence of pathological findings Results: "Appropriate for cranial CT" results can predict pathology presence 118,056-fold compared to the "not appropriate for cranial CT" results. With "cranial CT/observation of patient; both are appropriate" results, pathology presence was predicted 11,457-fold compared to "not appropriate for cranial CT" results. Conclusion:PECARN rules can predict pathology presence successfully in pediatric TBI. Using PECARN can decrease resource waste and exposure to ionizing radiation.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Pediatric Emergency Care Applied Research Network head injuryprediction rules: on the basis of cost and effectiveness

Gökharman¹,

Aydın²,

Fatihoğlu³

et al. 2017

Turk J Med Sci

View full text Add to dashboard Cite

show abstract

“…This makes the direct comparison of the three tools difficult [72]. The CHALICE rule applies to a broad population of head injuries of any severity, the PECARN rule was developed for minor head injuries only and the CATCH rule focused on a group of patients with specific signs or symptoms [59]. The PECARN rule is the most validated [37], and has the best sensitivity while the CHALICE rule has the best specificity [66, 91, 92].…”

Section: Discussionmentioning

confidence: 99%

Grading and assessment of clinical predictive tools for paediatric head injury: a new evidence-based approach

Khalifa

Gallego

2019

BMC Emerg Med

View full text Add to dashboard Cite

Background Many clinical predictive tools have been developed to diagnose traumatic brain injury among children and guide the use of computed tomography in the emergency department. It is not always feasible to compare tools due to the diversity of their development methodologies, clinical variables, target populations, and predictive performances. The objectives of this study are to grade and assess paediatric head injury predictive tools, using a new evidence-based approach, and to provide emergency clinicians with standardised objective information on predictive tools to support their search for and selection of effective tools. Methods Paediatric head injury predictive tools were identified through a focused review of literature. Based on the critical appraisal of published evidence about predictive performance, usability, potential effect, and post-implementation impact, tools were evaluated using a new framework for grading and assessment of predictive tools (GRASP). A comprehensive analysis was conducted to explain why certain tools were more successful. Results Fourteen tools were identified and evaluated. The highest-grade tool is PECARN; the only tool evaluated in post-implementation impact studies. PECARN and CHALICE were evaluated for their potential effect on healthcare, while the remaining 12 tools were only evaluated for predictive performance. Three tools; CATCH, NEXUS II, and Palchak, were externally validated. Three tools; Haydel, Atabaki, and Buchanich, were only internally validated. The remaining six tools; Da Dalt, Greenes, Klemetti, Quayle, Dietrich, and Güzel did not show sufficient internal validity for use in clinical practice. Conclusions The GRASP framework provides clinicians with a high-level, evidence-based, comprehensive, yet simple and feasible approach to grade, compare, and select effective predictive tools. Comparing the three main tools which were assigned the highest grades; PECARN, CHALICE and CATCH, to the remaining 11, we find that the quality of tools’ development studies, the experience and credibility of their authors, and the support by well-funded research programs were correlated with the tools’ evidence-based assigned grades, and were more influential, than the sole high predictive performance, on the wide acceptance and successful implementation of the tools. Tools’ simplicity and feasibility, in terms of resources needed, technical requirements, and training, are also crucial factors for their success. Electronic supplementary material The online version of this article (10.1186/s12873-019-0249-y) contains supplementary material, which is available to authorized users.

show abstract

“…For patients belonging to the low-risk category, the PECARN rule does not recommend a head CT. Kuppermann et al were successful in proving the internal validity of the PECARN decision tool. Various pediatric EDs have independently or compared with other CDSTs [8][9][10] have conducted studies to rule out the validation of PECARN head injury guidelines in the past, and researchers showed that application of the PECARN rule could reduce up to 58.3% of unnecessary CT scans 1 . The present study is a meta-analysis of the studies from 2009 to 2020 for the PECARN decision rule's accuracy in children with a very low risk of blunt head trauma.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of Pecarn Decision Rule in Minor Blunt Head Trauma in Pediatric Emergency Department: A Meta-Analysis

Yang

Zhao

Sun

et al. 2021

Preprint

View full text Add to dashboard Cite

Background: Pediatric Emergency Care Applied Research Network (PECARN) is a useful Clinical Decision Support Tool (CDST) to identify traumatic brain injuries and reduce the use of head CT scans among pediatric patients. The present Meta-analysis aims to evaluate the diagnostic accuracy of the PECARN rule from 2009 to 2020 in children with a very low risk of blunt head trauma. Methods: A detailed search was conducted from the databases of Medline (via PubMed), Cinahl (via Ebsco), Scopus, Web of Sciences, from 2009 till the end of December 2020 using the keywords like decrease use of CT scan, blunt head trauma (BHT) combined with accuracy, Pediatric Emergency Care Applied Research Network (PECARN) OR Clinical Decision Support Tool (CDST). Studies showing the diagnostic accuracy of the PECARN rule in children younger than 18 years of age with minor BHT were included. Results: 13 studies were included in the present analysis. Pooled sensitivity of 0.08, (95% confidence interval of 0.074 - 0.087), pooled specificity of 0.20 ( 95% CI of 0.196 - 0.213) and diagnostic odds ratio of 0.004 (95% CI of 0.000-0.1666) was in <2 years of age. The overall sensitivity of 0.07, specificity of 0.66, and diagnostic odds ratio of 0.54 (95% CI of 0.10 -2.78) was seen in ≥2 years of age. Overall sensitivity of 0.13 (95% CI 0.12-0.14), specificity of 0.81 (95% CI 0.80-0.82) and diagnostic odds ratio of 0.79 (95% CI of 0.08 -7.71) was in 0-18 years of age. Conclusion: The present analysis indicates the PECARN decision tool as an accurate CDST in low-risk minor blunt head trauma cases in children below two years of age and can become a useful tool in reducing Head CT’s scan overuse in pediatric emergency departments.

show abstract

Physician practice and PECARN rule outperform CATCH and CHALICE rules based on the detection of traumatic brain injury as defined by PECARN

Cited by 10 publications

References 8 publications

Pediatric Emergency Care Applied Research Network head injuryprediction rules: on the basis of cost and effectiveness

Pediatric Emergency Care Applied Research Network head injuryprediction rules: on the basis of cost and effectiveness

Grading and assessment of clinical predictive tools for paediatric head injury: a new evidence-based approach

Accuracy of Pecarn Decision Rule in Minor Blunt Head Trauma in Pediatric Emergency Department: A Meta-Analysis

Contact Info

Product

Resources

About