The Use of a Clinical Prediction Model and D-Dimer (DD) Testing in the Diagnosis of Deep Vein Thrombosis (DVT): A Systematic Review.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 1052-1052
Author(s):  
Carolyn J. Owen ◽  
Steve Doucette ◽  
Philip S. Wells
Keyword(s):  
High Risk ◽  
High Probability ◽  
Prediction Rule ◽  
Clinical Prediction Rule ◽  
Clinical Prediction ◽  
Clinical Prediction Model ◽  
Prediction Rules ◽  
Clinical Probability ◽  
Probability Estimates ◽  
Low Probability

Abstract Background: The diagnosis of DVT can be made by determining pretest probability of disease and using this information in combination with DD testing and ultrasound imaging. A number of studies have evaluated the use of clinical probability but this literature has not been summarized. Purpose: To systematically review trials that evaluated DVT prevalence using clinical prediction rules either with or without DD for the diagnosis of DVT. Data Sources: English and French language studies were identified from a MEDLINE search from 1990 to March 2004 and were supplemented by a review of all relevant bibliographies. Study Selection: Prospective management studies of symptomatic outpatients with suspected DVT in which patients were followed for a minimum of 3 months were selected. Clinical prediction rules had to be employed prior to DD and diagnostic tests. Studies were excluded if patients with a history of prior DVT were enrolled or if insufficient information was presented to calculate the prevalence of DVT for each of the 3 clinical probability estimates (low, moderate and high risk). Data Extraction: Two reviewers assessed each study for inclusion/exclusion criteria and collected data on prevalence and on sensitivity, specificity and likelihood ratios of DD in each of the 3 clinical probability estimates (low, moderate and high risk). Data Synthesis: 14 management studies involving a clinical prediction model in the diagnosis of DVT in over 8000 patients were included, of which 11 utilized DD in the diagnostic algorithm. All studies employed the same clinical prediction rule. The inverse variance weighted average prevalence of DVT in the low, moderate and high probability subgroups were 4.9% (95% CI= 4.2% to 5.7%), 17.4% (95% CI= 16.2% to 18.8%), and 53.6% (95% CI= 51.1% to 56.2%), respectively. The overall weighted prevalence was 18.3% (95% CI= 17.4% to 19.2%). The sensitivity of DD for the diagnosis of DVT in the low, moderate and high probability subgroups were 90.4% (95% CI= 84.7% to 94.2%), 92.0 % (95% CI= 89.1% to 94.2%), 93.6% (95% CI= 91.2% to 94.3%); and the specificities were 69.9% (95% CI= 68.0% to 71.8%), 52.4% (95% CI= 49.8% to 55.0%), and 43.2% (95% CI= 38.8% to 47.6%), respectively. The Mantel-Haenszel pooled estimates for diagnostic odds ratios (DOR) were 17.4 (95%CI=10.4–29.1), 10.2 (95% CI=7.1–14.6), and 10.1 (95% CI=6.9–14.9) in low, moderate and high groups respectively. Conclusion: Accurate estimates of the prevalence of DVT can be achieved using the same clinical prediction rule. Using this rule, it is unlikely that low probability patients have a DVT probability of more than 5%. Specificity of the DD seems to have clinically relevant differences depending on pretest probability but the DORs (which incorporate sensitivity and specificity) are similar. The data suggest that DVT can be excluded if patients are low probability even when DDs of lower sensitivity are employed and that DD testing has lower utility in high probability patients since false positives are common.

Accuracy and usefulness of a clinical prediction rule and D-dimer testing in excluding deep vein thrombosis (DVT) in cancer patients

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 19522-19522
Author(s):  
M. Carrier ◽  
A. Lee ◽  
S. Bates ◽  
P. S. Wells
Keyword(s):  
Cancer Patients ◽  
Diagnostic Testing ◽  
Prediction Rule ◽  
Clinical Prediction Rule ◽  
Clinical Prediction ◽  
Probability Score ◽  
Vein Thrombosis ◽  
Clinical Probability ◽  
Low Probability ◽  
D Dimer

19522 Background: Cancer patients frequently present with thrombotic complications and rapid, accurate diagnostic testing would reduce morbidity and mortality. Although the combination of a low clinical probability using clinical prediction rules (e.g. Well’s Score) and a negative D-dimer result have proven to be safe and reliable in ruling out DVT in the general population, the accuracy of such a strategy is less certain in cancer patients. Because cancer patients often have alternative reasons for leg swelling and pain, and because malignancy and chemotherapy can render the D-dimer test positive in the absence of DVT, we hypothesize that the Well’s Score and D-dimer testing are potentially less accurate and less useful in excluding DVT in patients with active cancer. Methods: We performed a retrospective analysis of 2 prospective studies to compare the diagnostic test characteristics of the Well’s Score and D-dimer testing between patients with and without cancer presenting with suspected DVT. Results: A total of 1630 patients were studied; 107 had cancer. DVT was confirmed in 39.3% of patients with and 13.7% of patients without cancer. In both patient groups, the proportions of patients with DVT were significantly different among the high-, moderate- and low-probability groups according to the Well’s score (P<0.001). However, significantly fewer cancer patients (19.6%) had a low-probability score compared to patients without cancer (47.5%) (P<0.001). Similarly, 36.4% of cancer vs. 60.4% of noncancer patients had a negative D-dimer result (P<0.001). In cancer patients, a low probability score alone had a sensitivity of 95.2% (95%CI 82.6%-99.2%) and a specificity of 29.2% (95% CI 18.9%-42.0%). In combination with D-dimer testing, the sensitivity improved to 100% (95%CI 31.0%-100%) but the specificity was reduced to 26.4% (95%CI 13.5%-44.7%). In contrast, the specificity in patients without cancer was preserved at 53.9% (95%CI 50.4%-57.3%). Conclusion: DVT can be ruled out in cancer patients with a low clinical probability of DVT and a negative D-dimer result. However, the low specificity of these tests excludes very few patients and thereby limits their clinical usefulness. No significant financial relationships to disclose.

Predicting Venous Thromboembolism Recurrence Risk in Patients with Cancer: A Validation Study

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 394-394
Author(s):  
Martha L Louzada ◽  
Gauruv Bose ◽  
Andrew Cheung ◽  
Benjamin H Chin-Yee ◽  
Simon Wells ◽  
...  
Keyword(s):  
High Risk ◽  
Low Molecular Weight Heparin ◽  
Treatment Strategies ◽  
Prediction Rule ◽  
Clinical Prediction Rule ◽  
Recurrence Risk ◽  
Low Molecular Weight ◽  
Clinical Prediction ◽  
Unusual Site ◽  
Patients With Cancer

Abstract Abstract 394 Background: Long-term low molecular weight heparin (LMWH) is the current standard for treatment of venous thromboembolism (VTE) in cancer patients. Whether treatment strategies should vary according to individual risk of VTE recurrence remains unknown. We have derived a clinical prediction rule that stratifies VTE recurrence risk in patients with cancer-associated VTE. The derivation model includes 4 independent predictors (sex, primary tumor site, stage and prior VTE). The score sum ranges between −3 and +3 points. Patients with a score ≤ 0 had low risk (≤4.5%) for recurrence and patients with a score above 1 had a high risk (≥ 19%) for VTE recurrence. Subsequently, we applied and validated the rule in an independent set of 819 patients from 2 randomized controlled trials comparing LMWH to warfarin for VTE treatment in cancer patients. In the current study we aim to externally validate our clinical prediction rule with an independent population of patients with cancer-associated VTE followed at the Thrombosis clinics of two tertiary Canadian centres. Methods: We conducted a retrospective cohort study of patients with cancer and VTE diagnosed and/or followed at the Thrombosis Clinic of the Victoria Hospital (London, Canada) from January 2006 to December 2010; and the Thrombosis Unit of the Ottawa Hospital (Ottawa, Canada) from January 2009 to December 2011. We included data from adult patients with active malignancy and objectively diagnosed acute pulmonary embolism (PE) or deep venous thrombosis (DVT) of the lower extremity (above knee), upper extremity and neck veins, or unusual site thrombosis. The primary outcome measure was VTE recurrence during the first six months of anticoagulation. Results: 353 patients fulfilled our inclusion criteria and were included in the study. There were 149 males, and the overall population had a median age of 64 years (range: 18 – 95). One hundred and twenty-three patients had lower extremity DVT, 93 had PE and 57 had both. The remaining 80 patients had either upper extremity/neck DVT (n = 55) or unusual site thrombosis (n = 25). 77 patients had a prior history of VTE. The most common primary tumour site was gastrointestinal, followed by the lung. Of the 304 patients with solid tumours, 230 (75.7%%) had TNM greater than I. Two hundred and ninety-three (83.0%) patients were treated with longterm low molecular weight heparin (LMWH) only and 60 (17.0%) with warfarin (VKA). VTE recurrence occurred in 44 of 353 patients (12.4%). When we evaluated VTE recurrence risk per site, there was no significant difference: London 13 of 90 and Ottawa 31 of 263 [RR=1.23 (95%CI= 0.671 – 2.237; p=0. 507)]. In addition, there was no significant benefit with the use of LMWH (37 of 293) over VKA (7 of 60) in the risk of recurrence [RR=0.92 (95%CI= 0.433 – 1.973; p= 0.8379)]. When we applied our clinical prediction rule (Table 1) in the entire study population, recurrent VTE occurred in 12 of 204 (5.8%) patients stratified as low risk probability and in 32 of 149 (21.4%) patients stratified as high risk probability (Table 2). Conclusions: Our prediction rule has been adequately validated to now be used in prospective trials of treatment. Future trials evaluating novel treatment strategies for high risk patients are warranted. Disclosures: No relevant conflicts of interest to declare.

Diagnosis: clinical prediction rules and laboratory tests

ESC CardioMed ◽  
2018 ◽  
pp. 2758-2761
Author(s):  
Piotr Pruszczyk
Keyword(s):  
Pulmonary Embolism ◽  
High Probability ◽  
Clinical Manifestations ◽  
High Sensitivity ◽  
Clinical Prediction ◽  
Clinical Prediction Rules ◽  
Prediction Rules ◽  
Vein Thrombosis ◽  
Clinical Probability ◽  
D Dimer

Clinical manifestations of venous thromboembolism (VTE) usually are non-specific. In order to facilitate proper diagnosis, clinical prediction rules were derived. The best studied models are the Wells criteria for deep vein thrombosis and pulmonary embolism and the Geneva score for pulmonary embolism. They classify patients into different categories of clinical pretest VTE probability. Pulmonary embolism prevalence is approximately 10% in low-, 30% in moderate-, and up to 65% in high-probability categories. Plasma D-dimer levels are elevated in not only VTE but also in other conditions. A D-dimer assay should be used in combination with pretest VTE clinical probability. A normal high-sensitivity D-dimer level excludes pulmonary embolism in patients with low/intermediate or non-high VTE probability, while in the high probability category does not allow VTE to be safely excluded. Age-adjusted D-dimer thresholds (age × 10 μ‎g/L above 50 years) can limit the need for imaging methods without increasing the rate of missed diagnoses in non-high clinical probability patients.

scholarly journals Identification of Cardiometabolic Risk Among Collegiate Football Players

2010 ◽  
Vol 45 (1) ◽  
pp. 67-74 ◽  
Author(s):  
Gary B. Wilkerson ◽  
J. Todd Bullard ◽  
David W. Bartal
Keyword(s):  
Metabolic Syndrome ◽  
High Risk ◽  
Cardiometabolic Risk ◽  
Prediction Rule ◽  
Clinical Prediction Rule ◽  
Quadriceps Strength ◽  
Football Players ◽  
Clinical Prediction ◽  
Collegiate Football

Abstract Context: Excessive fat mass clearly has adverse effects on metabolic processes that can ultimately lead to the development of chronic disease. Early identification of high-risk status may facilitate referral for definitive diagnostic tests and implementation of interventions to reduce cardiometabolic risk. Objective: To document the prevalence of metabolic syndrome among collegiate football players and to develop a clinical prediction rule that does not require blood analysis to identify players who may possess a high level of cardiometabolic risk. Design: Cross-sectional cohort study. Setting: University athletic training research laboratory. Patients or Other Participants: Sixty-two National Collegiate Athletic Association Division I Football Championship Subdivision football players (age  =  19.9 ± 1.2 years, height  =  182.6 ± 6.1 cm, mass  =  97.4 ± 18.3 kg). Main Outcome Measure(s): Anthropometric characteristics associated with body fat, isokinetic quadriceps strength, and biometric indicators associated with metabolic syndrome were measured. Participants were classified as high risk or low risk for future development of type 2 diabetes and cardiovascular disease. Results: The prevalence of metabolic syndrome in the cohort was 19% (12 of 62), and 79% (49 of 62) of the players exceeded the threshold for 1 or more of its 5 components. A 4-factor clinical prediction rule that classified individuals on the basis of waist circumference, blood pressure, quadriceps strength, and ethnic category had 92% sensitivity (95% confidence interval  =  65%, 99%) and 76% specificity (95% confidence interval  =  63%, 86%) for discrimination of high-risk or low-risk status. Conclusions: The risk for developing type 2 diabetes and cardiovascular disease appears to be exceptionally high among collegiate football players. A lack of race-specific criteria for the diagnosis of metabolic syndrome almost certainly contributes to an underestimation of the true level of cardiometabolic risk for African American collegiate football players.

scholarly journals La bola de cristal. Lectura crítica de reglas de predicción clínica.

2019 ◽  
Vol 11 (4) ◽  
pp. 2
Author(s):  
Manuel Molina
Keyword(s):  
Critical Appraisal ◽  
Internal Validity ◽  
Prediction Rule ◽  
Clinical Prediction Rule ◽  
Clinical History ◽  
Specific Response ◽  
Clinical Prediction ◽  
Clinical Environment ◽  
Crystal Ball ◽  
Prediction Rules

Una regla de predicción clínica es una herramienta compuesta por un conjunto de variables de la historia clínica, exploración física y pruebas complementarias básicas, que nos proporciona una estimación de la probabilidad de un evento, nos sugiere un diagnóstico o nos predice una respuesta concreta a un tratamiento. Para conocer el valor de sus conclusiones será importante estudiar su validez interna, la importancia clínica de sus conclusiones y si son aplicables y de utilidad en nuestro entorno clínico. ABSTRACT The crystal ball. Critical appraisal of clinical prediction rules. A clinical prediction rule is a tool composed of a set of variables from clinical history, physical examination and basic complementary tests, which provides us with an estimate of the probability of an event, suggests a diagnosis or predicts a specific response to a treatment. In order to know the value of its conclusions, it will be important to study its internal validity, the clinical relevance of its conclusions and if they are applicable and useful in our clinical environment.

scholarly journals Failure to Validate a Multivariable Clinical Prediction Model to Identify Pediatric Intensive Care Unit Patients at High Risk for Candidemia

2015 ◽  
Vol 5 (4) ◽  
pp. 458-461 ◽  
Author(s):  
Brian T. Fisher ◽  
Rachael K. Ross ◽  
Emmanuel Roilides ◽  
Debra L. Palazzi ◽  
Mark J. Abzug ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Pediatric Intensive Care Unit ◽  
Case Control Study ◽  
Prediction Rule ◽  
Pediatric Intensive Care ◽  
Clinical Prediction Rule ◽  
Clinical Prediction ◽  
Clinical Prediction Model ◽  
Control Study

Abstract We attempted to validate a previously derived clinical prediction rule for candidemia in the pediatric intensive care unit. This multicenter case control study did not identify significant association of candidemia with most of the previously identified predictors. Additional study in larger cohorts with other predictor variables is needed.

Development of A Clinical Prediction Rule for Risk Stratification of Recurrent Venous Thromboembolism In Patients with Cancer-Associated Venous Thromboembolism

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 475-475 ◽  
Author(s):  
Martha L Louzada ◽  
Alejandro Lazo-Langner ◽  
Vi Dao ◽  
Jerry Zhang ◽  
Michael J. Kovacs ◽  
...  
Keyword(s):  
Venous Thromboembolism ◽  
High Risk ◽  
Prediction Rule ◽  
Clinical Prediction Rule ◽  
Low Risk ◽  
Clinical Prediction ◽  
Potential Predictor ◽  
Patients With Cancer ◽  
History Of ◽  
Recurrent Vte

Abstract Abstract 475 Background: Current guidelines suggest that all cancer patients with venous thromboembolism be treated with long-term low molecular weight heparin (LMWH). However, whether treatment strategies should vary according to patient and malignancy characteristics, in particular whether patients with low risk of VTE recurrence can be identified, remains unknown. Methods: We performed a single centre retrospective cohort study conducted at the Thrombosis Unit of the Ottawa Hospital. The charts of patients with cancer and VTE followed from 2002 to 2004 and from 2007 to 2008 were reviewed to assess the feasibility of derivation of a clinical prediction rule that stratifies VTE recurrence risk in patients with cancer—associated venous thrombosis through identification and evaluation of characteristics of malignancy and other clinical characteristics. We analysed only the patients who had a recurrent VTE within the first 6 months of anticoagulation. A univariate analysis determined the strength of association between each potential predictor and VTE recurrence. All potential predictor variables (p<0.25) were evaluated in a logistic regression model. Result: Of 543 patients 55 (10.1%) presented with a VTE recurrence during the first 6 months of anticoagulation. At VTE recurrence 19 (9.5%) patients were using VKA and 36 (10.5%) patients were using LMWH. The relative risk for VTE recurrence was not significantly different between patients who used VKA or LMWH [RR= 1. 13 (95%CI, 0.743 – 1.711; p= 0.565)]. A multivariate analysis suggested that gender, primary tumour site, tumour stage and history of prior VTE were significant variables to include in the clinical prediction rule. The final model included female gender, lung cancer and prior history of VTE as increasing risk and breast cancer and stage I disease as lowering risk. Patients with a score equal or less than 0 have low risk (4.5%) for VTE recurrence and this represented 48% of our patients. Patients with a score equal or above 1 have high risk (> 19%) for VTE recurrence (Tables 1 and 2). Conclusion: We were able to derive a simple and easy scoring system that stratifies patients with cancer-associated thrombosis into low or high risk of recurrent VTE. Future prospective validation of the model is warranted and may be very relevant to better tailor anticoagulation treatment in this heterogeneous population. Disclosure: No relevant conflicts of interest to declare.

Sign in / Sign up

Export Citation Format

Share Document