1580: A CLINICAL DECISION TOOL TO PREDICT THE NEED FOR CERVICAL IMAGING IN CHILDREN LESS THAN 8 YEARS

Aims/Objectives/BackgroundObjectivesTo assess if application of a nurse-led paediatric head injury clinical decision tool would be safe compared to current practice.Background>700,000 children attend UK hospitals’ each year with a head injury. Research indicates <1% undergo neurosurgical intervention. No published evidence for nurse-led discharge of paediatric head injuries exists.Methods/DesignMethods – All paediatric (<17 years) patients with head injuries presenting to our Emergency department (ED) 1st May to 31st October 2018 were prospectively screened by a nurse using a mandated electronic ‘Head Injury Discharge At Triage’ questionnaire (HIDATq). We determined which patients underwent computed tomography (CT) brain and whether there was a clinically important intracranial injury or re-presentation to ED. The negative predictive value of the screening tool was assessed. We determined what proportion of patients could have been sent home from triage using HIDATq.Results/ConclusionsResults - Of 1739 patients screened; 61 had CTs performed due to head injury (6 abnormal) with a CT rate of 3.5% and 2% re-presentations. Of the entire cohort, 1052 screened negative. 1 CT occurred in this group showing no abnormalities. Of those screened negative: 349/1052 (33%) had ‘no other injuries’ and 543/1052 (52%) had ‘abrasions or lacerations’. HIDATq’s negative predictive value for CT was 99.9% (95% Confidence interval (CI) 99.4–99.9%) and 100% (CI 99.0–100%) for intracranial injury. The positive predictive value of the tool was low. Five patients screened negative and re-presented within 72hrs but did not require CT imaging.Conclusion - A negative HIDATq appears safe in our ED. Potentially 20% (349/1739) of all patients with head injuries presenting to our department could be discharged by nurses at triage with adequate safety netting advice. This increases to 50% (543/1739) if patients with lacerations or abrasions were treated and discharged at triage. A large multi-centre study is required to validate the tool.

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Feasibility of a structured 3-minute walk test as a clinical decision tool for patients presenting to the emergency department with acute dyspnoea

Emergency Medicine Journal ◽

10.1136/emj.2008.059774 ◽

2009 ◽

Vol 26 (4) ◽

pp. 278-282 ◽

Cited By ~ 14

Author(s):

A M Pan ◽

I G Stiell ◽

C M Clement ◽

J Acheson ◽

S D Aaron

Keyword(s):

Emergency Department ◽

Clinical Decision ◽

Walk Test ◽

Decision Tool ◽

Acute Dyspnoea ◽

Minute Walk

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Development and Validation of a Simulation Model–Based Clinical Decision Tool: Identifying Patients Where 21-Gene Recurrence Score Testing May Change Decisions

Journal of Clinical Oncology ◽

10.1200/jco.21.00651 ◽

2021 ◽

pp. JCO.21.00651

Author(s):

Jinani Jayasekera ◽

Joseph A. Sparano ◽

Suzanne O'Neill ◽

Young Chandler ◽

Claudine Isaacs ◽

...

Keyword(s):

Breast Cancer ◽

Simulation Model ◽

Endocrine Therapy ◽

External Validation ◽

Recurrence Score ◽

Clinical Decision ◽

Recurrence Risk ◽

Distant Recurrence ◽

Decision Tool ◽

Life Years

PURPOSE There is a need for industry-independent decision tools that integrate clinicopathologic features, comorbidities, and genomic information for women with node-negative, invasive, hormone receptor–positive, human epidermal growth factor receptor-2–negative (early-stage) breast cancer. METHODS We adapted an extant Cancer Intervention and Surveillance Modeling Network simulation model to estimate the 10-year risk of distant recurrence, breast cancer–specific mortality, other-cause mortality, and life-years gained with chemoendocrine versus endocrine therapy. We simulated outcomes for 1,512 unique patient subgroups based on all possible combinations of age, tumor size, grade, and comorbidity level; simulations were performed with and without 21-gene recurrence scores (RSs). Model inputs were derived from clinical trials, large US cohort studies, registry, and claims data. External validation was performed by comparing results to observed rates in two independent sources. We highlight results for one scenario where treatment choice may be uncertain. RESULTS Chemoendocrine versus endocrine therapy in a 65-69-year-old woman with a small (≤ 2 cm), intermediate-grade tumor, and mild comorbidities provides a 1.3% absolute reduction in 10-year distant recurrence risk, with 0.23 life-years gained. With these tumor features, a woman like this will have a 28% probability of having an RS 16-20, 18% RS 21-25, and 11% RS 26+. If testing is done, and her RS is 16-20, chemoendocrine therapy reduces 10-year distant recurrence risk to 1%, with 0.20 life-years gained, a similar result as without testing. The absolute benefits would increase to 4.8%-5.5% if the RS was 26+. The model closely reproduced observed rates in both independent data sets. CONCLUSION Our validated clinical decision tool is flexible, readily adaptable to include new therapies, and can support discussions about genomic testing and early breast cancer treatment.

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A simulation model-based clinical decision tool to guide personalized treatment based on individual characteristics: Does 21-gene recurrence score assay testing change decisions?

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e12507 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e12507-e12507

Author(s):

Jinani Jayasekera ◽

Joseph A. Sparano ◽

Young Chandler ◽

Claudine Isaacs ◽

Allison W. Kurian ◽

...

Keyword(s):

Breast Cancer ◽

Simulation Model ◽

Early Stage ◽

Clinical Decision ◽

Distant Recurrence ◽

Decision Tool ◽

Decision Tools ◽

Model Based ◽

Life Years ◽

Size Grade

e12507 Background: There is a need for web-based decision tools that integrate clinicopathologic features and genomic information to guide breast cancer therapy for women with node-negative, hormone receptor positive, HER2 negative (“early-stage”) breast cancer. We developed a novel simulation model-based clinical decision tool that provides prognostic estimates of treatment outcomes based on age, tumor size, grade, and comorbidities with and without 21-gene recurrence scores (RS). Methods: We adapted an extant breast cancer simulation model developed within the NCI-funded Cancer Intervention and Surveillance Modeling Network (CISNET) to derive estimates for the 10-year risks of distant recurrence, breast cancer-specific mortality, other cause mortality and life-years gained with endocrine vs. chemo-endocrine therapy for individual women based on their age, tumor size, grade, and comorbidity-level with and without RS test results. The model used an empiric Bayesian analytical approach to combine information from clinical trials, registry and claims data to provide individual estimates. External validation of the model was performed by comparing model-based breast cancer mortality rates and observed rates in the Surveillance Epidemiology and End Results (SEER) registry. Results: Several exemplar profiles were selected to illustrate the clinical utility of the decision tool. For example, the absolute chemotherapy benefit for 10-year distant recurrence risk and life-years gained, without RS testing, and the outcomes if a woman got tested and had a RS 16-20 are provided below for a 40-44-year-old woman and a 65–69-year-old woman diagnosed with a small (≤2cm), intermediate grade tumor and mild comorbidities. Conclusions: Simulation modeling is useful for creating clinical decision tools to support shared decision making for early-stage breast cancer treatment.[Table: see text]

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The Nijmegen Decision Tool for Chronic Low Back Pain. Development of a Clinical Decision Tool for Secondary or Tertiary Spine Care Specialists

PLoS ONE ◽

10.1371/journal.pone.0104226 ◽

2014 ◽

Vol 9 (8) ◽

pp. e104226 ◽

Cited By ~ 26

Author(s):

Miranda L. van Hooff ◽

Jan van Loon ◽

Jacques van Limbeek ◽

Marinus de Kleuver

Keyword(s):

Low Back Pain ◽

Back Pain ◽

Chronic Low Back Pain ◽

Clinical Decision ◽

Low Back ◽

Decision Tool ◽

Spine Care

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P121: Derivation of a clinical decision tool for predicting adverse outcomes among emergency department patients with lower gastrointestinal bleeding

CJEM ◽

10.1017/cem.2018.319 ◽

2018 ◽

Vol 20 (S1) ◽

pp. S99-S100

Author(s):

R. Ramaekers ◽

C. Leafloor ◽

J. J. Perry ◽

V. Thiruganasambandamoorthy

Keyword(s):

Emergency Department ◽

Adverse Events ◽

Gastrointestinal Bleeding ◽

Likelihood Ratio ◽

Negative Likelihood Ratio ◽

Clinical Decision ◽

Lower Gastrointestinal Bleeding ◽

Bloody Stool ◽

Decision Tool ◽

Serious Adverse Events

Introduction: Lower gastrointestinal bleeding (LGIB) can result in serious adverse events, including recurrent bleeding, need for intervention and death. Endoscopy is important in the management of LGIB, however gastroenterologists have limited resources to safe endoscopy. Risk stratification of LGIB patients can aid physicians in disposition decisions. Objective: to develop a clinical decision tool to accurately identify LGIB patients presenting to the emergency department (ED) who are at risk for 30-day serious adverse events. Methods: We conducted a health records review and included 372 adult ED patients who presented with an acute LGIB. The outcome was a 30-day composite outcome consisting of all-cause death, recurrent LGIB, need for intervention to control the bleed and ICU admission. A second researcher confirmed data-collection of 10% of the data and we calculated a -value for inter-rater reliability. We analyzed the data using stepwise backwards selection and SELECTION=SCORE option and calculated the diagnostic accuracy of the final model. Results: Age 75 years, hemoglobin 100 g/L, INR 2.0, a bloody stool in the ED and a past medical history of colorectal polyps were significant predictors in the multivariable regression analysis. The AUC was 0.83 (95% CI 0.77-0.89), sensitivity 0.96 (0.90-1.00), specificity 0.53 (0.48-0.59), and negative likelihood ratio 0.08 (0.02-0.30) for a cut-off score of 1. Conclusion: This model showed good ability to identify LGIB patients at low risk for adverse events as evidenced by the high AUC, sensitivity and negative likelihood ratio. Future, large prospective studies should be done to confirm the data, after which it should be validated and implemented.

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