Excluding deep vein thrombosis safely in primary care.

Our validated primary care rule safely excludes deep vein thrombosis in one-quarter of patients suspected of having the disease. We recommend the use of this rule by family practitioners.

Common alternative diagnoses in general practice when deep venous thrombosis is excluded.

BACKGROUND: In patients initially suspected of deep venous thrombosis (DVT) the diagnosis can be confirmed in approximately 10 to 30% of cases. For the majority of patients this means that eventually an alternative diagnosis is assigned. OBJECTIVE: To assess the frequency distribution of alternative diagnoses and subsequent management of patients in primary care after initial exclusion of DVT. In addition, assess the value of ultrasound examination for the allocation of alternative diagnoses. METHODS: Data were recorded by general practitioners alongside a diagnostic study in primary care in the Netherlands (AMUSE). Additional data were retrieved from a three-month follow-up questionnaire. A descriptive analysis was performed using these combined data. RESULTS: The most prevalent diagnoses were muscle rupture (18.5%), chronic venous insufficiency (CVI) (14.6%), erysipelas/cellulitis (12.6%) and superficial venous thrombosis (SVT) (10.9%). Alternative diagnoses were based mainly on physical examination; ultrasound examination (US) did not improve the diagnostic yield for the allocation of alternative diagnoses. In about 30% of all cases, a wait and see approach was used (27 to 41%). During the three-month follow-up nine patients were diagnosed with venous thromboembolic disease, three of which occurred in patients with the working diagnosis of SVT (p=0.026). CONCLUSIONS: We found that after exclusion of DVT in general practice a wait and see policy in the primary care setting is uneventful for almost one third of patients, but with the alternative diagnosis of SVT, patients may require closer surveillance since we found a significant association with thrombosis in these patients.

Cost-effectiveness of ruling out deep venous thrombosis in primary care versus care as usual.

BACKGROUND: Referral for ultrasound testing in all patients suspected of DVT is inefficient, because 80-90% have no DVT. OBJECTIVE: To assess the incremental cost-effectiveness of a diagnostic strategy to select patients at first presentation in primary care based on a point of care D-dimer test combined with a clinical decision rule (AMUSE strategy), compared with hospital-based strategies. PATIENTS/METHODS: A Markov-type cost-effectiveness model with a societal perspective and a 5-year time horizon was used to compare the AMUSE strategy with hospital-based strategies. Data were derived from the AMUSE study (2005-2007), the literature, and a direct survey of costs (2005-2007). RESULTS OF BASE-CASE ANALYSIS: Adherence to the AMUSE strategy on average results in savings of euro138 ($185) per patient at the expense of a very small health loss (0.002 QALYs) compared with the best hospital strategy. The iCER is euro55 753($74 848). The cost-effectiveness acceptability curves show that the AMUSE strategy has the highest probability of being cost-effective. RESULTS OF SENSITIVITY ANALYSIS: Results are sensitive to decreases in sensitivity of the diagnostic strategy, but are not sensitive to increase in age (range 30-80), the costs for health states, and events. CONCLUSION: A diagnostic management strategy based on a clinical decision rule and a point of care D-dimer assay to exclude DVT in primary care is not only safe, but also cost-effective as compared with hospital-based strategies.

A new diagnostic rule for deep vein thrombosis: safety and efficiency in clinically relevant subgroups.

BACKGROUND: Recently, a new, simple diagnostic rule was introduced to enable GPs to safely refrain from referring a considerable proportion of the patients suspected of having deep vein thrombosis (DVT). The rule (which includes seven patient history and physical examination items plus the result of a D-dimer test) discriminates 'very low' risk patients (not to be referred) from patients with an increased risk of DVT (to be referred). However, the rule's 'efficiency' (proportion of patients designated by the rule as very low risk) and safety (DVT prevalence among these very low risk patients) may change according to patient characteristics. OBJECTIVE: To test the rule's safety and efficiency in clinically relevant subgroups; i.e. across three age groups, in men and women, and in patients with and without a history of DVT, separately. METHODS: We retrospectively analysed data of 2086 primary care patients suspected of DVT, in whom all rule items and the result of the reference ('gold') standard (compression ultrasonography) were collected. RESULTS: The rule's efficiency decreased with age from 38.1% in the relatively young (<50 years) compared to 9.8% in patients aged > or =70 years. The percentage of DVT among the very low risk patients was <1.5% in all subgroups. The low efficiency in the elderly could be improved without compromising the safety by increasing the D-dimer threshold. CONCLUSION: The rule can safely exclude DVT in primary care patients suspected of DVT, irrespective of age, gender and history of DVT.

Validation, updating and impact of clinical prediction rules: a review.

OBJECTIVE: To provide an overview of the research steps that need to follow the development of diagnostic or prognostic prediction rules. These steps include validity assessment, updating (if necessary), and impact assessment of clinical prediction rules. STUDY DESIGN AND SETTING: Narrative review covering methodological and empirical prediction studies from primary and secondary care. RESULTS: In general, three types of validation of previously developed prediction rules can be distinguished: temporal, geographical, and domain validations. In case of poor validation, the validation data can be used to update or adjust the previously developed prediction rule to the new circumstances. These update methods differ in extensiveness, with the easiest method a change in model intercept to the outcome occurrence at hand. Prediction rules -- with or without updating -- showing good performance in (various) validation studies may subsequently be subjected to an impact study, to demonstrate whether they change physicians' decisions, improve clinically relevant process parameters, patient outcome, or reduce costs. Finally, whether a prediction rule is implemented successfully in clinical practice depends on several potential barriers to the use of the rule. CONCLUSION: The development of a diagnostic or prognostic prediction rule is just a first step. We reviewed important aspects of the subsequent steps in prediction research.