Accuracy of the Wells Clinical Prediction Rule for Pulmonary Embolism in Older Ambulatory Adults

2014 ◽  
Vol 62 (11) ◽  
pp. 2136-2141 ◽  
Author(s):  
Henrike J. Schouten ◽  
Geert-Jan Geersing ◽  
Ruud Oudega ◽  
Johannes J.M. van Delden ◽  
Karel G.M. Moons ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Prediction Rule ◽  
Clinical Prediction Rule ◽  
Clinical Prediction

Derivation of a Simple Clinical Model to Categorize Patients Probability of Pulmonary Embolism: Increasing the Models Utility with the SimpliRED D-dimer

2000 ◽  
Vol 83 (03) ◽  
pp. 416-420 ◽  
Author(s):  
David Anderson ◽  
Marc Rodger ◽  
Jeffrey Ginsberg ◽  
Clive Kearon ◽  
Michael Gent ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Scoring System ◽  
Clinical Symptoms ◽  
Prediction Rule ◽  
Scoring Systems ◽  
Clinical Prediction Rule ◽  
Clinical Prediction ◽  
Clinical Model ◽  
Validation Set ◽  
D Dimer

SummaryWe have previously demonstrated that a clinical model can be safely used in a management strategy in patients with suspected pulmonary embolism (PE). We sought to simplify the clinical model and determine a scoring system, that when combined with D-dimer results, would safely exclude PE without the need for other tests, in a large proportion of patients. We used a randomly selected sample of 80% of the patients that participated in a prospective cohort study of patients with suspected PE to perform a logistic regression analysis on 40 clinical variables to create a simple clinical prediction rule. Cut points on the new rule were determined to create two scoring systems. In the first scoring system patients were classified as having low, moderate and high probability of PE with the proportions being similar to those determined in our original study. The second system was designed to create two categories, PE likely and unlikely. The goal in the latter was that PE unlikely patients with a negative D-dimer result would have PE in less than 2% of cases. The proportion of patients with PE in each category was determined overall and according to a positive or negative SimpliRED D-dimer result. After these determinations we applied the models to the remaining 20% of patients as a validation of the results. The following seven variables and assigned scores (in brackets) were included in the clinical prediction rule: Clinical symptoms of DVT (3.0), no alternative diagnosis (3.0), heart rate >100 (1.5), immobilization or surgery in the previous four weeks (1.5), previous DVT/PE (1.5), hemoptysis (1.0) and malignancy (1.0). Patients were considered low probability if the score was <2.0, moderate of the score was 2.0 to 6.0 and high if the score was over 6.0. Pulmonary embolism unlikely was assigned to patients with scores <4.0 and PE likely if the score was >4.0. 7.8% of patients with scores of less than or equal to 4 had PE but if the D-dimer was negative in these patients the rate of PE was only 2.2% (95% CI = 1.0% to 4.0%) in the derivation set and 1.7% in the validation set.Importantly this combination occurred in 46% of our study patients. A score of <2.0 and a negative D-dimer results in a PE rate of 1.5% (95% CI = 0.4% to 3.7%) in the derivation set and 2.7% (95% CI = 0.3% to 9.0%) in the validation set and only occurred in 29% of patients. The combination of a score <4.0 by our simple clinical prediction rule and a negative SimpliRED D-Dimer result may safely exclude PE in a large proportion of patients with suspected PE.

scholarly journals A data-driven clinical prediction rule for pulmonary embolism

2013 ◽  
Vol 34 (suppl 1) ◽  
pp. P243-P243
Author(s):  
L. G. Falsetti ◽  
E. Merelli ◽  
M. Rucco ◽  
C. Nitti ◽  
T. Gentili ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Prediction Rule ◽  
Clinical Prediction Rule ◽  
Data Driven ◽  
Clinical Prediction

scholarly journals Development and validation of a clinical prediction rule for development of diabetic foot ulceration: an analysis of data from five cohort studies

2021 ◽  
Vol 9 (1) ◽  
pp. e002150
Author(s):  
Francesca M Chappell ◽  
Fay Crawford ◽  
Margaret Horne ◽  
Graham P Leese ◽  
Angela Martin ◽  
...  
Keyword(s):  
Cohort Studies ◽  
Secondary Care ◽  
Prediction Rule ◽  
Clinical Prediction Rule ◽  
Initial Assessment ◽  
Validation Dataset ◽  
Benefit Analysis ◽  
Clinical Prediction ◽  
Net Benefit ◽  
Foot Ulceration

IntroductionThe aim of the study was to develop and validate a clinical prediction rule (CPR) for foot ulceration in people with diabetes.Research design and methodsDevelopment of a CPR using individual participant data from four international cohort studies identified by systematic review, with validation in a fifth study. Development cohorts were from primary and secondary care foot clinics in Europe and the USA (n=8255, adults over 18 years old, with diabetes, ulcer free at recruitment). Using data from monofilament testing, presence/absence of pulses, and participant history of previous ulcer and/or amputation, we developed a simple CPR to predict who will develop a foot ulcer within 2 years of initial assessment and validated it in a fifth study (n=3324). The CPR’s performance was assessed with C-statistics, calibration slopes, calibration-in-the-large, and a net benefit analysis.ResultsCPR scores of 0, 1, 2, 3, and 4 had a risk of ulcer within 2 years of 2.4% (95% CI 1.5% to 3.9%), 6.0% (95% CI 3.5% to 9.5%), 14.0% (95% CI 8.5% to 21.3%), 29.2% (95% CI 19.2% to 41.0%), and 51.1% (95% CI 37.9% to 64.1%), respectively. In the validation dataset, calibration-in-the-large was −0.374 (95% CI −0.561 to −0.187) and calibration slope 1.139 (95% CI 0.994 to 1.283). The C-statistic was 0.829 (95% CI 0.790 to 0.868). The net benefit analysis suggested that people with a CPR score of 1 or more (risk of ulceration 6.0% or more) should be referred for treatment.ConclusionThe clinical prediction rule is simple, using routinely obtained data, and could help prevent foot ulcers by redirecting care to patients with scores of 1 or above. It has been validated in a community setting, and requires further validation in secondary care settings.

scholarly journals Developing a clinical prediction rule for repeated consultations with functional somatic symptoms in primary care: a cohort study

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e040730
Author(s):  
Gea A Holtman ◽  
Huibert Burger ◽  
Robert A Verheij ◽  
Hans Wouters ◽  
Marjolein Y Berger ◽  
...  
Keyword(s):  
Primary Care ◽  
Cohort Study ◽  
Somatic Symptoms ◽  
Prediction Rule ◽  
Clinical Prediction Rule ◽  
Model Discrimination ◽  
Clinical Prediction ◽  
Internal Validation ◽  
Predictive Values ◽  
Healthy Activity

ObjectivesPatients who present in primary care with chronic functional somatic symptoms (FSS) have reduced quality of life and increased health care costs. Recognising these early is a challenge. The aim is to develop and internally validate a clinical prediction rule for repeated consultations with FSS.Design and settingRecords from the longitudinal population-based (‘Lifelines’) cohort study were linked to electronic health records from general practitioners (GPs).ParticipantsWe included patients consulting a GP with FSS within 1 year after baseline assessment in the Lifelines cohort.Outcome measuresThe outcome is repeated consultations with FSS, defined as ≥3 extra consultations for FSS within 1 year after the first consultation. Multivariable logistic regression, with bootstrapping for internal validation, was used to develop a risk prediction model from 14 literature-based predictors. Model discrimination, calibration and diagnostic accuracy were assessed.Results18 810 participants were identified by database linkage, of whom 2650 consulted a GP with FSS and 297 (11%) had ≥3 extra consultations. In the final multivariable model, older age, female sex, lack of healthy activity, presence of generalised anxiety disorder and higher number of GP consultations in the last year predicted repeated consultations. Discrimination after internal validation was 0.64 with a calibration slope of 0.95. The positive predictive value of patients with high scores on the model was 0.37 (0.29–0.47).ConclusionsSeveral theoretically suggested predisposing and precipitating predictors, including neuroticism and stressful life events, surprisingly failed to contribute to our final model. Moreover, this model mostly included general predictors of increased risk of repeated consultations among patients with FSS. The model discrimination and positive predictive values were insufficient and preclude clinical implementation.

scholarly journals Prognostic value of the ABCD2 clinical prediction rule: a systematic review and meta-analysis

2011 ◽  
Vol 28 (4) ◽  
pp. 366-376 ◽  
Author(s):  
R. Galvin ◽  
C. Geraghty ◽  
N. Motterlini ◽  
B. D. Dimitrov ◽  
T. Fahey
Keyword(s):  
Systematic Review ◽  
Prognostic Value ◽  
Meta Analysis ◽  
Prediction Rule ◽  
Clinical Prediction Rule ◽  
Clinical Prediction
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