Meta-Analysis: The Value of Clinical Assessment in the Diagnosis of Deep Venous Thrombosis

19 July 2005 | Volume 143 Issue 2 | Pages 129-139

Background: Clinical assessment of suspected deep venous thrombosis (DVT) should be based on systematically evaluated evidence.

Purpose: To determine whether clinical findings, risk scores, and physicians' empirical judgments affect the likelihood of detecting DVT on definitive testing.

Data Sources: MEDLINE, EMBASE, CINAHL, Web of Science, Cochrane Database of Systematic Reviews, Cochrane Controlled Trials Register, Database of Reviews of Effectiveness, ACP Journal Club, and citation lists (1966 to January 2005).

Study Selection: Cohort studies published in English, French, Spanish, or Italian that compared clinical assessment with a reference standard.

Data Extraction: The authors extracted standardized data, including setting, exclusions, population characteristics, reference standard, and results, and assessed quality against validated criteria.

Data Synthesis: The authors combined data by using random-effects meta-analysis and, if appropriate, used meta-regression to identify covariates that predicted diagnostic accuracy. Only malignancy (likelihood ratio [LR], 2.71), previous DVT (LR, 2.25), recent immobilization (LR, 1.98), difference in calf diameter (LR, 1.80), and recent surgery (LR, 1.76) were useful for ruling in DVT, while only absence of calf swelling (LR, 0.67) or difference in calf diameter (LR, 0.57) was useful for ruling out DVT. The Wells clinical score was more valuable than the individual characteristics; it stratified patients into groups with high (LR, 5.2), intermediate, and low (LR, 0.25) probability of DVT. The Wells score seemed able to stratify patients by risk only for proximal DVT, and it performed better in cohorts that were younger or excluded patients with previous thromboembolism.

Limitations: Pooled estimates were subject to substantial heterogeneity. This may limit extrapolation between observers and settings. Only published studies were included, so findings may be subject to publication bias.

Conclusion: Individual clinical features are of limited value in diagnosing DVT. Overall assessment of clinical probability by using the Wells score is more useful.

Editors' Notes Context Which clinical findings most affect the probability of deep venous thrombosis (DVT)? Contribution This systematic review of 54 cohort studies found that previous DVT and malignant disease modestly increased the probability of DVT (positive likelihood ratios, 2.25 and 2.71), followed by recent immobilization, difference in calf diameter, and recent surgery (positive likelihood ratios, 1.75 to 1.98). Wells scores, based on 9 items, stratified patients' probability of proximal DVT much better than did individual findings, particularly in younger patients and in patients without previous DVT. Implications Estimating the probability of DVT is best accomplished by assessing and scoring multiple findings. –The Editors

 

Author and Article Information

From University of Sheffield, Sheffield, and University of Leicester, Leicester, United Kingdom.

Disclaimer: The views and opinions expressed herein are those of the authors and do not necessarily reflect those of the United Kingdom Department of Health.

Acknowledgments: The authors thank Vanja Dukic for her assistance with the meta-regression analysis and Angie Ryan for her help with the literature searches.

Grant Support: The United Kingdom Health Technology Assessment R&D Programme funded this project (reference no. 02/03/01).

Potential Financial Conflicts of Interest: None disclosed.

Requests for Single Reprints: Steve Goodacre, MB, ChB, FFAEM, MSc, PhD, Medical Care Research Unit, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, United Kingdom; e-mail, s.goodacre{at}sheffield.ac.uk.

Current Author Addresses: Dr. Goodacre and Ms. Sampson: Medical Care Research Unit, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, United Kingdom.

Dr. Sutton: Department of Health Sciences, University of Leicester, 22-28 Princess Road West, Leicester, LE1 6TP, United Kingdom.