Geert-Jan Geersing

Clinical decision rules for excluding pulmonary embolism: a meta-analysis.

BACKGROUND Clinical probability assessment is combined with d-dimer testing to exclude pulmonary embolism (PE). PURPOSE To compare the test characteristics of gestalt (a physicians unstructured estimate) and clinical decision rules for evaluating adults with suspected PE and assess the failure rate of gestalt and rules when used in combination with d-dimer testing. DATA SOURCES Articles in MEDLINE and EMBASE in English, French, German, Italian, Spanish, or Dutch that were published between 1966 and June 2011. STUDY SELECTION 3 reviewers, working in pairs, selected prospective studies in consecutive patients suspected of having PE. Studies had to estimate the probability of PE by using gestalt or a decision rule and verify the diagnosis by using an appropriate reference standard. DATA EXTRACTION Data on study characteristics, test performance, and prevalence were extracted. Reviewers constructed 2 × 2 tables and assessed the methodological quality of the studies. DATA SYNTHESIS 52 studies, comprising 55 268 patients, were selected. Meta-analysis was performed on studies that used gestalt (15 studies; sensitivity, 0.85; specificity, 0.51), the Wells rule with a cutoff value less than 2 (19 studies; sensitivity, 0.84; specificity, 0.58) or 4 or less (11 studies; sensitivity, 0.60; specificity, 0.80), the Geneva rule (5 studies; sensitivity, 0.84; specificity, 0.50), and the revised Geneva rule (4 studies; sensitivity, 0.91; specificity, 0.37). An increased prevalence of PE was associated with higher sensitivity and lower specificity. Combining a decision rule or gestalt with d-dimer testing seemed safe for all strategies, except when the less-sensitive Wells rule (cutoff value ≤4) was combined with less-sensitive qualitative d-dimer testing. LIMITATIONS Studies had substantial heterogeneity due to prevalence of PE and differences in threshold. Many studies (63%) had potential bias due to differential disease verification. CONCLUSION Clinical decision rules and gestalt can safely exclude PE when combined with sensitive d-dimer testing. The authors recommend standardized rules because gestalt has lower specificity, but the choice of a particular rule and d-dimer test depend on both prevalence and setting.

Diagnostic accuracy of conventional or age adjusted D-dimer cut-off values in older patients with suspected venous thromboembolism: systematic review and meta-analysis

Objective To review the diagnostic accuracy of D-dimer testing in older patients (>50 years) with suspected venous thromboembolism, using conventional or age adjusted D-dimer cut-off values. Design Systematic review and bivariate random effects meta-analysis. Data sources We searched Medline and Embase for studies published before 21 June 2012 and we contacted the authors of primary studies. Study selection Primary studies that enrolled older patients with suspected venous thromboembolism in whom D-dimer testing, using both conventional (500 µg/L) and age adjusted (age×10 µg/L) cut-off values, and reference testing were performed. For patients with a non-high clinical probability, 2×2 tables were reconstructed and stratified by age category and applied D-dimer cut-off level. Results 13 cohorts including 12 497 patients with a non-high clinical probability were included in the meta-analysis. The specificity of the conventional cut-off value decreased with increasing age, from 57.6% (95% confidence interval 51.4% to 63.6%) in patients aged 51-60 years to 39.4% (33.5% to 45.6%) in those aged 61-70, 24.5% (20.0% to 29.7% in those aged 71-80, and 14.7% (11.3% to 18.6%) in those aged >80. Age adjusted cut-off values revealed higher specificities over all age categories: 62.3% (56.2% to 68.0%), 49.5% (43.2% to 55.8%), 44.2% (38.0% to 50.5%), and 35.2% (29.4% to 41.5%), respectively. Sensitivities of the age adjusted cut-off remained above 97% in all age categories. Conclusions The application of age adjusted cut-off values for D-dimer tests substantially increases specificity without modifying sensitivity, thereby improving the clinical utility of D-dimer testing in patients aged 50 or more with a non-high clinical probability.

Excluding venous thromboembolism using point of care D-dimer tests in outpatients: a diagnostic meta-analysis

Objective To review the evidence on the diagnostic accuracy of the currently available point of care D-dimer tests for excluding venous thromboembolism. Design Systematic review of research on the accuracy of point of care D-dimer tests, using bivariate regression to examine sources of variation and to estimate sensitivity and specificity. Data sources Studies on the diagnostic accuracy of point of care D-dimer tests published between January 1995 and September 2008 and available in either Medline or Embase. Review methods The analysis included studies that compared point of care D-dimer tests with predefined reference criteria for venous thromboembolism, enrolled consecutive outpatients, and allowed for construction of a 2×2 table. Results 23 studies (total number of patients 13 959, range in mean age 38-65 years, range of venous thromboembolism prevalence 4-51%) were included in the meta-analysis. The studies reported two qualitative point of care D-dimer tests (SimpliRED D-dimer (n=12) and Clearview Simplify D-dimer (n=7)) and two quantitative point of care D-dimer tests (Cardiac D-dimer (n=4) and Triage D-dimer (n=2)). Overall sensitivity ranged from 0.85 (95% confidence interval 0.78 to 0.90) to 0.96 (0.91 to 0.98) and overall specificity from 0.48 (0.33 to 0.62) to 0.74 (0.69 to 0.78). The two quantitative tests Cardiac D-dimer and Triage D-dimer scored most favourably. Conclusions In outpatients suspected of venous thromboembolism, point of care D-dimer tests can contribute important information and guide patient management, notably in low risk patients (that is, those patients with a low score on a clinical decision rule).

Safe exclusion of pulmonary embolism using the Wells rule and qualitative D-dimer testing in primary care: prospective cohort study

Objective To validate the use of the Wells clinical decision rule combined with a point of care D-dimer test to safely exclude pulmonary embolism in primary care. Design Prospective cohort study. Setting Primary care across three different regions of the Netherlands (Amsterdam, Maastricht, and Utrecht). Participants 598 adults with suspected pulmonary embolism in primary care. Interventions Doctors scored patients according to the seven variables of the Wells rule and carried out a qualitative point of care D-dimer test. All patients were referred to secondary care and diagnosed according to local protocols. Pulmonary embolism was confirmed or refuted on the basis of a composite reference standard, including spiral computed tomography and three months’ follow-up. Main outcome measures Diagnostic accuracy (sensitivity and specificity), proportion of patients at low risk (efficiency), number of missed patients with pulmonary embolism in low risk category (false negative rate), and the presence of symptomatic venous thromboembolism, based on the composite reference standard, including events during the follow-up period of three months. Results Pulmonary embolism was present in 73 patients (prevalence 12.2%). On the basis of a threshold Wells score of ≤4 and a negative qualitative D-dimer test result, 272 of 598 patients were classified as low risk (efficiency 45.5%). Four cases of pulmonary embolism were observed in these 272 patients (false negative rate 1.5%, 95% confidence interval 0.4% to 3.7%). The sensitivity and specificity of this combined diagnostic approach was 94.5% (86.6% to 98.5%) and 51.0% (46.7% to 55.4%), respectively. Conclusion A Wells score of ≤4 combined with a negative qualitative D-dimer test result can safely and efficiently exclude pulmonary embolism in primary care.

Exclusion of deep vein thrombosis using the Wells rule in clinically important subgroups: individual patient data meta-analysis

Objective To assess the accuracy of the Wells rule for excluding deep vein thrombosis and whether this accuracy applies to different subgroups of patients. Design Meta-analysis of individual patient data. Data sources Authors of 13 studies (n=10 002) provided their datasets, and these individual patient data were merged into one dataset. Eligibility criteria Studies were eligible if they enrolled consecutive outpatients with suspected deep vein thrombosis, scored all variables of the Wells rule, and performed an appropriate reference standard. Main outcome measures Multilevel logistic regression models, including an interaction term for each subgroup, were used to estimate differences in predicted probabilities of deep vein thrombosis by the Wells rule. In addition, D-dimer testing was added to assess differences in the ability to exclude deep vein thrombosis using an unlikely score on the Wells rule combined with a negative D-dimer test result. Results Overall, increasing scores on the Wells rule were associated with an increasing probability of having deep vein thrombosis. Estimated probabilities were almost twofold higher in patients with cancer, in patients with suspected recurrent events, and (to a lesser extent) in males. An unlikely score on the Wells rule (≤1) combined with a negative D-dimer test result was associated with an extremely low probability of deep vein thrombosis (1.2%, 95% confidence interval 0.7% to 1.8%). This combination occurred in 29% (95% confidence interval 20% to 40%) of patients. These findings were consistent in subgroups defined by type of D-dimer assay (quantitative or qualitative), sex, and care setting (primary or hospital care). For patients with cancer, the combination of an unlikely score on the Wells rule and a negative D-dimer test result occurred in only 9% of patients and was associated with a 2.2% probability of deep vein thrombosis being present. In patients with suspected recurrent events, only the modified Wells rule (adding one point for the previous event) is safe. Conclusion Combined with a negative D-dimer test result (both quantitative and qualitative), deep vein thrombosis can be excluded in patients with an unlikely score on the Wells rule. This finding is true for both sexes, as well as for patients presenting in primary and hospital care. In patients with cancer, the combination is neither safe nor efficient. For patients with suspected recurrent disease, one extra point should be added to the rule to enable a safe exclusion.

Search filters for finding prognostic and diagnostic prediction studies in Medline to enhance systematic reviews.

Background The interest in prognostic reviews is increasing, but to properly review existing evidence an accurate search filer for finding prediction research is needed. The aim of this paper was to validate and update two previously introduced search filters for finding prediction research in Medline: the Ingui filter and the Haynes Broad filter. Methodology/Principal Findings Based on a hand search of 6 general journals in 2008 we constructed two sets of papers. Set 1 consisted of prediction research papers (n = 71), and set 2 consisted of the remaining papers (n = 1133). Both search filters were validated in two ways, using diagnostic accuracy measures as performance measures. First, we compared studies in set 1 (reference) with studies retrieved by the search strategies as applied in Medline. Second, we compared studies from 4 published systematic reviews (reference) with studies retrieved by the search filter as applied in Medline. Next – using word frequency methods – we constructed an additional search string for finding prediction research. Both search filters were good in identifying clinical prediction models: sensitivity ranged from 0.94 to 1.0 using our hand search as reference, and 0.78 to 0.89 using the systematic reviews as reference. This latter performance measure even increased to around 0.95 (range 0.90 to 0.97) when either search filter was combined with the additional string that we developed. Retrieval rate of explorative prediction research was poor, both using our hand search or our systematic review as reference, and even combined with our additional search string: sensitivity ranged from 0.44 to 0.85. Conclusions/Significance Explorative prediction research is difficult to find in Medline, using any of the currently available search filters. Yet, application of either the Ingui filter or the Haynes broad filter results in a very low number missed clinical prediction model studies.

Categorization of patients as having provoked or unprovoked venous thromboembolism: guidance from the SSC of ISTH.

C. KEARON,* W. AGENO,† S . C . CANNEGIETER ,‡ B . COSMI ,§ G. J . GEERS ING ¶ and P . A . KYRLE ,** FOR THE SUBCOMMITTEES ON CONTROL OF ANT ICOAGULAT ION, AND PREDICT IVE AND DIAGNOST IC VAR IABLES IN THROMBOT IC D ISEASE *McMaster University, Hamilton, ON, Canada; †University of Insubria, Varese, Italy; ‡Leiden University, Leiden, the Netherlands; §University of Bologna, Bologna, Italy; ¶Utrecht University, Utrecht, the Netherlands; and **Medical University of Vienna, Vienna, Austria

Validation of two age dependent D-dimer cut-off values for exclusion of deep vein thrombosis in suspected elderly patients in primary care: retrospective, cross sectional, diagnostic analysis

Objective To determine whether the use of age adapted D-dimer cut-off values can be translated to primary care patients who are suspected of deep vein thrombosis. Design Retrospective, cross sectional diagnostic study. Setting 110 primary care doctors affiliated with three hospitals in the Netherlands. Participants 1374 consecutive patients (936 (68.1%) aged >50 years) with clinically suspected deep vein thrombosis. Main outcome measures Proportion of patients with D-dimer values below two proposed age adapted cut-off levels (age in years×10 μg/L in patients aged >50 years, or 750 μg/L in patients aged ≥60 years), in whom deep vein thrombosis could be excluded; and the number of false negative results. Results Using the Wells score, 647 patients had an unlikely clinical probability of deep vein thrombosis. In these patients (at all ages), deep vein thrombosis could be excluded in 309 (47.8%) using the age dependent cut-off value compared with 272 (42.0%) using the conventional cut-off value of 500 μg/L (increase 5.7%, 95% confidence interval 4.1% to 7.8%). This exclusion rate resulted in 0.5% and 0.3% false negative cases, respectively (increase 0.2%, 0.004% to 8.6%).The increase in exclusion rate by using the age dependent cut-off value was highest in the oldest patients. In patients older than 80 years, deep vein thrombosis could be safely excluded in 22 (35.5%) patients using the age dependent cut-off value compared with 13 (21.0%) using the conventional cut-off value (increase 14.5%, 6.8% to 25.8%). Compared with the age dependent cut-off value, the cut-off value of 750 μg/L had a similar exclusion rate (307 (47.4%) patients) and false negative rate (0.3%). Conclusions Combined with a low clinical probability of deep vein thrombosis, use of the age dependent D-dimer cut-off value for patients older than 50 years or the cut-off value of 750 μg/L for patients aged 60 years and older resulted in a considerable increase in the proportion of patients in primary care in whom deep vein thrombosis could be safely excluded, compared with the conventional cut-off value of 500 μg/L.

Diagnostic and prognostic prediction models.

Risk prediction models can be used to estimate the probability of either having (diagnostic model) or developing a particular disease or outcome (prognostic model). In clinical practice, these models are used to inform patients and guide therapeutic management. Examples from the field of venous thrombo‐embolism (VTE) include the Wells rule for patients suspected of deep venous thrombosis and pulmonary embolism, and more recently prediction rules to estimate the risk of recurrence after a first episode of unprovoked VTE. In this paper, the three phases that are recommended before a prediction model may be used in daily practice are described: development, validation, and impact assessment. In the development phase, the focus is on model development commonly using a multivariable logistic (diagnostic) or survival (prognostic) regression analysis. The performance of the developed model is expressed by discrimination, calibration and (re‐) classification. In the validation phase, the developed model is tested in a new set of patients using these same performance measures. This is important, as model performance is commonly poorer in a new set of patients, e.g. due to case‐mix or domain differences. Finally, in the impact phase the ability of a prediction model to actually guide patient management is evaluated. Whereas in the development and validation phase single cohort designs are preferred, this last phase asks for comparative designs, ideally randomized designs; therapeutic management and outcomes after using the prediction model is compared to a control group not using the model (e.g. usual care).

Diagnostic prediction models for suspected pulmonary embolism: systematic review and independent external validation in primary care.

Objective To validate all diagnostic prediction models for ruling out pulmonary embolism that are easily applicable in primary care. Design Systematic review followed by independent external validation study to assess transportability of retrieved models to primary care medicine. Setting 300 general practices in the Netherlands. Participants Individual patient dataset of 598 patients with suspected acute pulmonary embolism in primary care. Main outcome measures Discriminative ability of all models retrieved by systematic literature search, assessed by calculation and comparison of C statistics. After stratification into groups with high and low probability of pulmonary embolism according to pre-specified model cut-offs combined with qualitative D-dimer test, sensitivity, specificity, efficiency (overall proportion of patients with low probability of pulmonary embolism), and failure rate (proportion of pulmonary embolism cases in group of patients with low probability) were calculated for all models. Results Ten published prediction models for the diagnosis of pulmonary embolism were found. Five of these models could be validated in the primary care dataset: the original Wells, modified Wells, simplified Wells, revised Geneva, and simplified revised Geneva models. Discriminative ability was comparable for all models (range of C statistic 0.75-0.80). Sensitivity ranged from 88% (simplified revised Geneva) to 96% (simplified Wells) and specificity from 48% (revised Geneva) to 53% (simplified revised Geneva). Efficiency of all models was between 43% and 48%. Differences were observed between failure rates, especially between the simplified Wells and the simplified revised Geneva models (failure rates 1.2% (95% confidence interval 0.2% to 3.3%) and 3.1% (1.4% to 5.9%), respectively; absolute difference −1.98% (−3.33% to −0.74%)). Irrespective of the diagnostic prediction model used, three patients were incorrectly classified as having low probability of pulmonary embolism; pulmonary embolism was diagnosed only after referral to secondary care. Conclusions Five diagnostic pulmonary embolism prediction models that are easily applicable in primary care were validated in this setting. Whereas efficiency was comparable for all rules, the Wells rules gave the best performance in terms of lower failure rates.