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Clinical Decision Rule

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41. Clinical Decision Rule to Identify Orbital Wall Fracture Among Children: Retrospective Derivation and Validation Study. (PubMed)

Clinical Decision Rule to Identify Orbital Wall Fracture Among Children: Retrospective Derivation and Validation Study. Head and face injuries are leading causes of emergency department visits in children. There is yet no clinical decision rule on face CT such as pediatric head CT rules. The goal was to develop and validate a clinical decision rule for identifying orbital wall fractures in children with periorbital trauma in the emergency department.This was a retrospective derivation (...) and validation study. Children younger than 18 years who underwent orbit CT after periorbital trauma were included between January 2011 and December 2013 in 3 emergency centers. Among 16 candidate clinical variables, 13 clinical signs and symptoms were selected as clinical predictors. For the fracture model, these clinical predictors were analyzed by 3-fold cross-validation. Diagnostic performance was assessed using the area under the receiver operating characteristic (AUROC) curve in both cohorts.Four

2017 Pediatric Emergency Care

42. 3 Derivation and internal validation of a clinical decision rule to guide whole body computed tomography scanning in trauma. (PubMed)

3 Derivation and internal validation of a clinical decision rule to guide whole body computed tomography scanning in trauma.

2017 Emergency Medicine Journal

43. External Validation of Six Pediatric Fever and Neutropenia Clinical Decision Rules. (PubMed)

External Validation of Six Pediatric Fever and Neutropenia Clinical Decision Rules. Fever and neutropenia (FN) clinical decision rules (CDRs) are recommended to help distinguish children with cancer at high and low risk of severe infection. The aim of this study was to validate existing pediatric FN CDRs designed to stratify children with cancer at high or low risk of serious infection or medical complication.Pediatric CDRs suitable for validation were identified from a literature search (...) or failure to identify a clinically meaningful number of low-risk patients. The 24-hour rule arguably exhibits the best balance between sensitivity and specificity in our population.

2017 Pediatric Infectious Dsease Journal

44. Diagnostic Accuracy of Clinical Decision Rules to Exclude Fractures in Acute Ankle Injuries: Systematic Review and Meta-analysis. (PubMed)

Diagnostic Accuracy of Clinical Decision Rules to Exclude Fractures in Acute Ankle Injuries: Systematic Review and Meta-analysis. Ankle decision rules are developed to expedite patient care and reduce the number of radiographs of the ankle and foot. Currently, only three systematic reviews have been conducted on the accuracy of the Ottawa Ankle and Foot Rules (OAFR) in adults and children. However, no systematic review has been performed to determine the most accurate ankle decision rule.The (...) purpose of this study is to examine which clinical decision rules are the most accurate for excluding ankle fracture after acute ankle trauma.A systematic search was conducted in the databases PubMed, CINAHL, PEDro, ScienceDirect, and EMBASE. The sensitivity, specificity, likelihood ratios, and diagnostic odds ratio of the included studies were calculated. A meta-analysis was conducted if the accuracy of a decision rule was available from at least three different experimental studies.Eighteen studies

2017 The Journal of emergency medicine

45. Developing a decision rule to optimise clinical pharmacist resources for medication reconciliation in the emergency department. (PubMed)

Developing a decision rule to optimise clinical pharmacist resources for medication reconciliation in the emergency department. The process of obtaining a complete medication history for patients admitted to the hospital from the ED at hospital admission, without discrepancies, is error prone and time consuming.The goal of this study was the development of a clinical decision rule (CDR) with a high positive predictive value in detecting ED patients admitted to hospital at risk of at least one (...) ) cardiovascular drugs, (12) drugs acting on musculoskeletal system and (13) drugs acting on the nervous system; all recorded by the ED physician on admission. The final CDR resulted in an alert rate of 29% with a positive predictive value of 74%.The final CDR allows identification of the majority of patients with a potential discrepancy within a feasible workload for the pharmacy staff. Our CDR is a first step towards a rule that could be incorporated into electronic medical records or a scoring system.©

2017 Emergency Medicine Journal

46. MICE or NICE? An economic evaluation of clinical decision rules in the diagnosis of heart failure in primary care. (PubMed)

MICE or NICE? An economic evaluation of clinical decision rules in the diagnosis of heart failure in primary care. Detection and treatment of heart failure (HF) can improve quality of life and reduce premature mortality. However, symptoms such as breathlessness are common in primary care, have a variety of causes and not all patients require cardiac imaging. In systems where healthcare resources are limited, ensuring those patients who are likely to have HF undergo appropriate and timely (...) investigation is vital.A decision tree was developed to assess the cost-effectiveness of using the MICE (Male, Infarction, Crepitations, Edema) decision rule compared to other diagnostic strategies to identify HF patients presenting to primary care.Data from REFER (REFer for EchocaRdiogram), a HF diagnostic accuracy study, was used to determine which patients received the correct diagnosis decision. The model adopted a UK National Health Service (NHS) perspective.The current recommended National Institute

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2017 International journal of cardiology

47. Use of Traumatic Brain Injury Prediction Rules With Clinical Decision Support. (PubMed)

Use of Traumatic Brain Injury Prediction Rules With Clinical Decision Support. We determined whether implementing the Pediatric Emergency Care Applied Research Network (PECARN) traumatic brain injury (TBI) prediction rules and providing risks of clinically important TBIs (ciTBIs) with computerized clinical decision support (CDS) reduces computed tomography (CT) use for children with minor head trauma.Nonrandomized trial with concurrent controls at 5 pediatric emergency departments (PEDs) and 8 (...) general EDs (GEDs) between November 2011 and June 2014. Patients were <18 years old with minor blunt head trauma. Intervention sites received CDS with CT recommendations and risks of ciTBI, both for patients at very low risk of ciTBI (no Pediatric Emergency Care Applied Research Network rule factors) and those not at very low risk. The primary outcome was the rate of CT, analyzed by site, controlling for time trend.We analyzed 16 635 intervention and 2394 control patients. Adjusted for time trends, CT

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2017 Pediatrics

48. Screening Consolidated Clinical Document Architecture (CCDA) Documents for Sensitive Data Using a Rule-Based Decision Support System (PubMed)

Screening Consolidated Clinical Document Architecture (CCDA) Documents for Sensitive Data Using a Rule-Based Decision Support System The Centers for Medicare & Medicaid Services' Stage 2 final rule requires that eligible hospitals provide a visit summary electronically at transitions of care in order to qualify for "meaningful use" incentive payments. However, Massachusetts state law and Federal law prohibit the transmission of documents containing "sensitive" data unless there is a new patient (...) consent for each transmission.To describe the implementation and evaluation of a rule-based decision support system used to screen transition of care documents for sensitive data.We implemented a rule-based document screening system to identify transition of care documents that might contain sensitive data. The transmission of detected documents is withheld until a new patient consent is obtained. The documents that were flagged as containing sensitive data were reviewed in two different time periods

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2017 Applied clinical informatics

49. Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems (PubMed)

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach (...) to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical

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2017 AMIA Annual Symposium Proceedings

50. External validation of clinical decision rules for children with wrist trauma (PubMed)

External validation of clinical decision rules for children with wrist trauma Clinical decision rules help to avoid potentially unnecessary radiographs of the wrist, reduce waiting times and save costs.The primary aim of this study was to provide an overview of all existing non-validated clinical decision rules for wrist trauma in children and to externally validate these rules in a different cohort of patients. Secondarily, we aimed to compare the performance of these rules with the validated (...) Amsterdam Pediatric Wrist Rules.We included all studies that proposed a clinical prediction or decision rule in children presenting at the emergency department with acute wrist trauma. We performed external validation within a cohort of 379 children. We also calculated the sensitivity, specificity, negative predictive value and positive predictive value of each decision rule.We included three clinical decision rules. The sensitivity and specificity of all clinical decision rules after external

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2017 Pediatric Radiology

51. Change-Point Detection Method for Clinical Decision Support System Rule Monitoring (PubMed)

Change-Point Detection Method for Clinical Decision Support System Rule Monitoring A clinical decision support system (CDSS) and its components can malfunction due to various reasons. Monitoring the system and detecting its malfunctions can help one to avoid any potential mistakes and associated costs. In this paper, we investigate the problem of detecting changes in the CDSS operation, in particular its monitoring and alerting subsystem, by monitoring its rule firing counts. The detection

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2017 Artificial intelligence in medicine : 16th Conference on Artificial Intelligence in Medicine, Aime 2017, Vienna, Austria, June 21-24, 2017, Proceedings. Conference on Artificial Intelligence in Medicine (2005-) (16th : 2017 : Vienna, Au.

52. GLASS Clinical Decision Rule Applied to Thoracolumbar Spinal Fractures in Patients Involved in Motor Vehicle Crashes (PubMed)

GLASS Clinical Decision Rule Applied to Thoracolumbar Spinal Fractures in Patients Involved in Motor Vehicle Crashes There are established and validated clinical decision tools for cervical spine clearance. Almost all the rules include spinal tenderness on exam as an indication for imaging. Our goal was to apply GLASS, a previously derived clinical decision tool for cervical spine clearance, to thoracolumbar injuries. GLass intact Assures Safe Spine (GLASS) is a simple, objective method (...) thoracolumbar spine clearance tool. Prospective evaluation would be required to further evaluate the validity of this clinical decision rule.

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2017 Western Journal of Emergency Medicine

53. Proposed Clinical Decision Rules to Diagnose Acute Rhinosinusitis Among Adults in Primary Care (PubMed)

Proposed Clinical Decision Rules to Diagnose Acute Rhinosinusitis Among Adults in Primary Care To reduce inappropriate antibiotic prescribing, we sought to develop a clinical decision rule for the diagnosis of acute rhinosinusitis and acute bacterial rhinosinusitis.Multivariate analysis and classification and regression tree (CART) analysis were used to develop clinical decision rules for the diagnosis of acute rhinosinusitis, defined using 3 different reference standards (purulent antral (...) puncture fluid or abnormal finding on a computed tomographic (CT) scan; for acute bacterial rhinosinusitis, we used a positive bacterial culture of antral fluid). Signs, symptoms, C-reactive protein (CRP), and reference standard tests were prospectively recorded in 175 Danish patients aged 18 to 65 years seeking care for suspected acute rhinosinusitis. For each reference standard, we developed 2 clinical decision rules: a point score based on a logistic regression model and an algorithm based on a CART

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2017 Annals of family medicine

54. Systematic review: Clinical decision rules for the assessment of mild head injury, used in combination with clinical judgment, can inform the use of head imaging

Systematic review: Clinical decision rules for the assessment of mild head injury, used in combination with clinical judgment, can inform the use of head imaging Clinical decision rules for the assessment of mild head injury, used in combination with clinical judgment, can inform the use of head imaging | BMJ Evidence-Based Medicine We use cookies to improve our service and to tailor our content and advertising to you. You can manage your cookie settings via your browser at any time. To learn (...) more about how we use cookies, please see our . Log in using your username and password For personal accounts OR managers of institutional accounts Username * Password * your user name or password? Search for this keyword Search for this keyword Main menu Log in using your username and password For personal accounts OR managers of institutional accounts Username * Password * your user name or password? You are here Clinical decision rules for the assessment of mild head injury, used in combination

2012 Evidence-Based Medicine (Requires free registration)

55. Can a Septic Hip Decision Rule Aid in the Evaluation of Suspected Pediatric Musculoskeletal Infections? (PubMed)

Can a Septic Hip Decision Rule Aid in the Evaluation of Suspected Pediatric Musculoskeletal Infections? Musculoskeletal (MSK) infections can be difficult to diagnose in acute care settings. The utility of clinical decision tools for pediatric MSK infections in an emergency department has not been well studied.Our aim was to evaluate the performance of a septic hip clinical decision rule (CDR) in the evaluation of pediatric musculoskeletal infections.We performed a retrospective study (...) of children evaluated for an MSK infection in our emergency department from 2014 to 2016. Data collection included demographics, discharge diagnoses, and clinical/laboratory predictors from the CDR. A χ2 analysis and Wilcoxon rank-sum tests compared patients with and without MSK infections. Logistic regression analysis examined the predictors for MSK infections. A receiver operating characteristic (ROC) curve was calculated to evaluate the performance of the predictors.Of 996 evaluations included

2019 Journal of Emergency Medicine

56. Accuracy of PECARN, CATCH, and CHALICE head injury decision rules in children: a prospective cohort study. (PubMed)

Accuracy of PECARN, CATCH, and CHALICE head injury decision rules in children: a prospective cohort study. Clinical decision rules can help to determine the need for CT imaging in children with head injuries. We aimed to validate three clinical decision rules (PECARN, CATCH, and CHALICE) in a large sample of children.In this prospective observational study, we included children and adolescents (aged <18 years) with head injuries of any severity who presented to the emergency departments of ten (...) in children 2 years and older (99·0%, 94·4-100·0; 97/98), followed by CATCH (high-risk predictors only; 95·2%; 76·2-99·9; 20/21; medium-risk and high-risk predictors 88·7%; 82·2-93·4; 125/141) and CHALICE (92·3%, 89·2-94·7; 370/401). In the comparison cohort of 18 913 patients with mild injuries, sensitivities for clinically important TBI were similar. Negative predictive values in both analyses were higher than 99% for all rules.The sensitivities of three clinical decision rules for head injuries

2017 Lancet

57. Comparison of Machine Learning Optimal Classification Trees With the Pediatric Emergency Care Applied Research Network Head Trauma Decision Rules. (PubMed)

Comparison of Machine Learning Optimal Classification Trees With the Pediatric Emergency Care Applied Research Network Head Trauma Decision Rules. Computed tomographic (CT) scanning is the standard for the rapid diagnosis of intracranial injury, but it is costly and exposes patients to ionizing radiation. The Pediatric Emergency Care Applied Research Network (PECARN) rules for identifying children with minor head trauma who are at very low risk of clinically important traumatic brain injury (...) (ciTBI) are widely used to triage CT imaging.To examine whether optimal classification trees (OCTs), which are novel machine-learning classifiers, improve on PECARN rules' predictive accuracy.A secondary analysis of prospective, publicly available data on emergency department visits for head trauma used by the PECARN group to develop their tool was conducted to derive OCT-based prediction rules for ciTBI in a development cohort and compare their predictive performance vs the PECARN rules

2019 JAMA pediatrics

58. Application of decision rules on diagnosis and prognosis of renal colic: a systematic review and meta-analysis. (PubMed)

Application of decision rules on diagnosis and prognosis of renal colic: a systematic review and meta-analysis. Renal colic is a prevalent emergency department presentation resulting from urolithiasis. Clinical decision rules for the diagnosis of urolithiasis were developed to help clinicians with better judgment. In this systematic review, we assessed the performance of prediction rules on urolithiasis diagnosis and prognosis. MEDLINE, Embase, Web of Science, and Scopus were searched (...) for studies on the performance of a clinical decision tool for diagnosis or prognosis of urolithiasis. Performance and accuracy of the rules were the key outcomes of interest. Databases were searched from inception to March 2019. Of the 4980 articles reviewed, 28 studies were included in the present analysis. Twenty-one studies were on urolithiasis diagnosis (including eight studies on STONE rule), and 10 studies reported urolithiasis outcomes. Studies were at low to moderate risk of bias. The pooling

2019 European Journal of Emergency Medicine

59. Do Clinical Prediction Rules for Acute Pulmonary Embolism Have Sufficient Sensitivity to Identify Patients at Very Low Risk of Death?

- pulmonaryembolismall-cause mortality:abivariatemeta- analysis.Chest.2015;147:1043- 1062. 1. Whiting PF, Rutjes AWS, Westwood ME, et al; QUADAS-2 Group. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155:529-536. 2. McGinn TG, Guyatt GH, Wyer PC, et al; Evidence-Based Medicine Working Group. Users’ guides to the medical literature: XXII: how to use articles about clinical decision rules. JAMA. 2000;284: 79-84. 3. Silverstein MD, Heit JA, Mohr DN, et al (...) Do Clinical Prediction Rules for Acute Pulmonary Embolism Have Sufficient Sensitivity to Identify Patients at Very Low Risk of Death? Systematic Review Snapshot TAKE-HOME MESSAGE Five pulmonary embolism clinical prediction rules to predict early all-cause mortality have sensitivities greater than 88%, but only 3 are supported by a high level of evidence. The simpli?ed Pulmonary Embolism Severity Index appears to have the greatest potential, given its relatively higher sensitivity and ease

2016 Annals of Emergency Medicine Systematic Review Snapshots

60. A simple clinical decision rule to rule out appendicitis in patients with nondiagnostic ultrasound results (PubMed)

A simple clinical decision rule to rule out appendicitis in patients with nondiagnostic ultrasound results The objective was to identify a set of clinical features that can rule out appendicitis in patients with suspected acute appendicitis and nondiagnostic ultrasound (US) results, allowing safe discharge and next-day reevaluation without initial computed tomography (CT) or magnetic resonance imaging (MRI).Data on clinical and US evaluation, including a number of prespecified variables (...) potentially associated with acute appendicitis, were prospectively collected in two diagnostic accuracy studies of imaging. These studies included patients with suspected appendicitis seen in the emergency department (ED). For development and validation of the clinical decision rule (CDR), only patients with inconclusive or negative US results were included. There were 199 (of 422) patients in the development cohorts and 120 (of 211) patients in the validation cohort. Logistic regression analysis was used

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2014 EvidenceUpdates

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