Estimation Of Pretest Probability Research Articles

Arming the Bayesian physician to rule out pulmonary embolism: using evidence-based diagnostics to combat overtesting.

Arming the Bayesian physician to rule out pulmonary embolism: using evidence-based diagnostics to combat overtesting.

Accuracy of Point-of-Care Multiorgan Ultrasonography for the Diagnosis of Pulmonary Embolism

Presenting signs and symptoms of pulmonary embolism (PE) are nonspecific, favoring a large use of second-line diagnostic tests such as multidetector CT pulmonary angiography (MCTPA), thus exposing patients to high-dose radiation and to potential serious complications. We investigated the diagnostic performance of multiorgan ultrasonography (lung, heart, and leg vein ultrasonography) and whether multiorgan ultrasonography combined to Wells score and D-dimer could safely reduce MCTPA tests. Consecutive adult patients suspected of PE and with a Wells score > 4 or a positive D-dimer result were prospectively enrolled in three EDs. Final diagnosis was obtained with MCTPA. Multiorgan ultrasonography was performed before MCTPA and considered diagnostic for PE if one or more subpleural infarcts, right ventricular dilatation, or DVT was detected. If multiorgan ultrasonography was negative for PE, an alternative ultrasonography diagnosis was sought. Accuracies of each single-organ and multiorgan ultrasonography were calculated. PE was diagnosed in 110 of 357 enrolled patients (30.8%). Multiorgan ultrasonography yielded a sensitivity of 90% and a specificity of 86.2%, lung ultrasonography 60.9% and 95.9%, heart ultrasonography 32.7% and 90.9%, and vein ultrasonography 52.7% and 97.6%, respectively. Among the 132 patients (37%) with multiorgan ultrasonography negative for PE plus an alternative ultrasonographic diagnosis or plus a negative D-dimer result, no patients received PE as a final diagnosis. Multiorgan ultrasonography is more sensitive than single-organ ultrasonography, increases the accuracy of clinical pretest probability estimation in patients with suspected PE, and may safely reduce the MCTPA burden. ClinicalTrials.gov; No.: NCT01635257; URL: www.clinicaltrials.gov.

Multicenter, Randomized Trial of Quantitative Pretest Probability to Reduce Unnecessary Medical Radiation Exposure in Emergency Department Patients With Chest Pain and Dyspnea

Use of pretest probability can reduce unnecessary testing. We hypothesize that quantitative pretest probability, linked to evidence-based management strategies, can reduce unnecessary radiation exposure and cost in low-risk patients with symptoms suggestive of acute coronary syndrome and pulmonary embolism. This was a prospective, 4-center, randomized controlled trial of decision support effectiveness. Subjects were adults with chest pain and dyspnea, nondiagnostic ECGs, and no obvious diagnosis. The clinician provided data needed to compute pretest probabilities from a Web-based system. Clinicians randomized to the intervention group received the pretest probability estimates for both acute coronary syndrome and pulmonary embolism and suggested clinical actions designed to lower radiation exposure and cost. The control group received nothing. Patients were followed for 90 days. The primary outcome and sample size of 550 was predicated on a significant reduction in the proportion of healthy patients exposed to >5 mSv chest radiation. A total of 550 patients were randomized, and 541 had complete data. The proportion with >5 mSv to the chest and no significant cardiopulmonary diagnosis within 90 days was reduced from 33% to 25% (P=0.038). The intervention group had significantly lower median chest radiation exposure (0.06 versus 0.34 mSv; P=0.037, Mann-Whitney U test) and lower median costs ($934 versus $1275; P=0.018) for medical care. Adverse events occurred in 16% of controls and 11% in the intervention group (P=0.06). Provision of pretest probability and prescriptive advice reduced radiation exposure and cost of care in low-risk ambulatory patients with symptoms of acute coronary syndrome and pulmonary embolism. URL: http://www.clinicaltrials.gov. Unique identifier: NCT01059500.

Outcomes and Radiation Exposure of Emergency Department Patients With Chest Pain and Shortness of Breath and Ultralow Pretest Probability: A Multicenter Study

Excessive radiation exposure remains a concern for patients with symptoms suggesting acute coronary syndrome and pulmonary embolism but must be judged in the perspective of pretest probability and outcomes. We quantify and qualify the pretest probability, outcomes, and radiation exposure of adults with both chest pain and dyspnea. This was a prospective, 4-center, outcomes study. Patients were adults with dyspnea and chest pain, nondiagnostic ECGs, and no obvious diagnosis. Pretest probability for both acute coronary syndrome and pulmonary embolism was assessed with a validated method; ultralow risk was defined as pretest probability less than 2.5% for both acute coronary syndrome and pulmonary embolism. Patients were followed for diagnosis and total medical radiation exposure for 90 days. Eight hundred forty patients had complete data; 23 (3%) had acute coronary syndrome and 15 (2%) had pulmonary embolism. The cohort received an average of 4.9 mSv radiation to the chest, 48% from computed tomography pulmonary angiography. The pretest probability estimates for acute coronary syndrome and pulmonary embolism were less than 2.5% in 227 patients (27%), of whom 0 of 277 (0%; 95% confidence interval 0% to 1.7%) had acute coronary syndrome or pulmonary embolism and 7 of 227 (3%) had any significant cardiopulmonary diagnosis. The estimated chest radiation exposure per patient in this ultralow-risk group was 3.5 mSv, including 26 (3%) with greater than 5 mSv radiation to the chest and no significant cardiopulmonary diagnosis. One quarter of patients with chest pain and dyspnea had ultralow risk and no acute coronary syndrome or pulmonary embolism but were exposed to an average of 3.5 mSv radiation to the chest. These data can be used in a clinical guideline to reduce radiation exposure.

Clinician Gestalt Estimate of Pretest Probability for Acute Coronary Syndrome and Pulmonary Embolism in Patients With Chest Pain and Dyspnea

Pretest probability helps guide diagnostic testing for patients with suspected acute coronary syndrome and pulmonary embolism. Pretest probability derived from the clinician's unstructured gestalt estimate is easier and more readily available than methods that require computation. We compare the diagnostic accuracy of physician gestalt estimate for the pretest probability of acute coronary syndrome and pulmonary embolism with a validated, computerized method. This was a secondary analysis of a prospectively collected, multicenter study. Patients (N=840) had chest pain, dyspnea, nondiagnostic ECGs, and no obvious diagnosis. Clinician gestalt pretest probability for both acute coronary syndrome and pulmonary embolism was assessed by visual analog scale and from the method of attribute matching using a Web-based computer program. Patients were followed for outcomes at 90 days. Clinicians had significantly higher estimates than attribute matching for both acute coronary syndrome (17% versus 4%; P<.001, paired t test) and pulmonary embolism (12% versus 6%; P<.001). The 2 methods had poor correlation for both acute coronary syndrome (r(2)=0.15) and pulmonary embolism (r(2)=0.06). Areas under the receiver operating characteristic curve were lower for clinician estimate compared with the computerized method for acute coronary syndrome: 0.64 (95% confidence interval [CI] 0.51 to 0.77) for clinician gestalt versus 0.78 (95% CI 0.71 to 0.85) for attribute matching. For pulmonary embolism, these values were 0.81 (95% CI 0.79 to 0.92) for clinician gestalt and 0.84 (95% CI 0.76 to 0.93) for attribute matching. Compared with a validated machine-based method, clinicians consistently overestimated pretest probability but on receiver operating curve analysis were as accurate for pulmonary embolism but not acute coronary syndrome.

The End of X‐rays for Suspected Small Bowel Obstruction? Using Evidence‐based Diagnostics to Inform Best Practices in Emergency Medicine

The End of X‐rays for Suspected Small Bowel Obstruction? Using Evidence‐based Diagnostics to Inform Best Practices in Emergency Medicine

Comparison of empirical estimate of clinical pretest probability with the Wells score for diagnosis of deep vein thrombosis

Wells score has been validated for estimation of pretest probability in patients with suspected deep vein thrombosis (DVT). In clinical practice, many clinicians prefer to use empirical estimation rather than Wells score. However, which method is better to increase the accuracy of clinical evaluation is not well understood. Our present study compared empirical estimation of pretest probability with the Wells score to investigate the efficiency of empirical estimation in the diagnostic process of DVT. Five hundred and fifty-five patients were enrolled in this study. One hundred and fifty patients were assigned to examine the interobserver agreement for Wells score between emergency and vascular clinicians. The other 405 patients were assigned to evaluate the pretest probability of DVT on the basis of the empirical estimation and Wells score, respectively, and plasma D-dimer levels were then determined in the low-risk patients. All patients underwent venous duplex scans and had a 45-day follow up. Weighted Cohen's κ value for interobserver agreement between emergency and vascular clinicians of the Wells score was 0.836. Compared with Wells score evaluation, empirical assessment increased the sensitivity, specificity, Youden's index, positive likelihood ratio, and positive and negative predictive values, but decreased negative likelihood ratio. In addition, the appropriate D-dimer cutoff value based on Wells score was 175 μg/l and 108 patients were excluded. Empirical assessment increased the appropriate D-dimer cutoff point to 225 μg/l and 162 patients were ruled out. Our findings indicated that empirical estimation not only improves D-dimer assay efficiency for exclusion of DVT but also increases clinical judgement accuracy in the diagnosis of DVT.

Information Theoretic Quantification of Diagnostic Uncertainty

Diagnostic test interpretation remains a challenge in clinical practice. Most physicians receive training in the use of Bayes’ rule, which specifies how the sensitivity and specificity of a test for a given disease combine with the pre-test probability to quantify the change in disease probability incurred by a new test result. However, multiple studies demonstrate physicians’ deficiencies in probabilistic reasoning, especially with unexpected test results. Information theory, a branch of probability theory dealing explicitly with the quantification of uncertainty, has been proposed as an alternative framework for diagnostic test interpretation, but is even less familiar to physicians. We have previously addressed one key challenge in the practical application of Bayes theorem: the handling of uncertainty in the critical first step of estimating the pre-test probability of disease. This essay aims to present the essential concepts of information theory to physicians in an accessible manner, and to extend previous work regarding uncertainty in pre-test probability estimation by placing this type of uncertainty within a principled information theoretic framework. We address several obstacles hindering physicians’ application of information theoretic concepts to diagnostic test interpretation. These include issues of terminology (mathematical meanings of certain information theoretic terms differ from clinical or common parlance) as well as the underlying mathematical assumptions. Finally, we illustrate how, in information theoretic terms, one can understand the effect on diagnostic uncertainty of considering ranges instead of simple point estimates of pre-test probability.

Propagation of Uncertainty in Bayesian Diagnostic Test Interpretation

Bayesian interpretation of diagnostic test results usually involves point estimates of the pretest probability and the likelihood ratio corresponding to the test result; however, it may be more appropriate in clinical situations to consider instead a range of possible values to express uncertainty in the estimates of these parameters. We thus sought to demonstrate how uncertainty in sensitivity, specificity, and disease pretest probability can be accommodated in Bayesian interpretation of diagnostic testing. We investigated three questions: How does uncertainty in the likelihood ratio propagate to the posttest probability range, assuming a point estimate of pretest probability? How does uncertainty in the sensitivity and specificity of a test affect uncertainty in the likelihood ratio? How does uncertainty propagate when present in both the pretest probability and the likelihood ratio? Propagation of likelihood ratio uncertainty depends on the pretest probability and is more prominent for unexpected test results. Uncertainty in sensitivity and specificity propagates into the calculation of likelihood ratio prominently as these parameters approach 100%; even modest errors of ± 10% caused dramatic propagation. Combining errors of ± 20% in the pretest probability and in the likelihood ratio exhibited modest propagation to posttest probability, suggesting a realistic target range for clinical estimations. The results provide a framework for incorporating ranges of uncertainty into Bayesian reasoning. Although point estimates simplify the implementation of Bayesian reasoning, it is important to recognize the implications of error propagation when ranges are considered in this multistep process.

211 Head CT Utilization for Minor Head Injury: What Motivates Patients to Present to the Emergency Department for Evaluation, and Why Do Emergency Physicians Choose to Evaluate Them With CT?

211 Head CT Utilization for Minor Head Injury: What Motivates Patients to Present to the Emergency Department for Evaluation, and Why Do Emergency Physicians Choose to Evaluate Them With CT?

The clinical diagnostic reasoning process determining the use of endoscopy in diagnosing peptic ulcer disease.

To evaluate the clinical diagnostic reasoning process as a tool to decrease the number of unnecessary endoscopies for diagnosing peptic ulcer disease. tudy Cross-sectional KAP study. Shifa College of Medicine, Islamabad, from April to August 2010. Two hundred doctors were assessed with three common clinical scenarios of low, intermediate and high pre-test probability for peptic ulcer disease using a questionnaire. The differences between the reference estimates and the respondents' estimates of pre-test and post test probability were used for assessing the ability of estimating the pretest probability and the post test probability of the disease. Doctors were also enquired about the cost-effectiveness and safety of endoscopy. Consecutive sampling technique was used and the data was analyzed using SPSS version 16. In the low pre-test probability settings, overestimation of the disease probability suggested the doctors' inability to rule out the disease. The post test probabilities were similarly overestimated. In intermediate pre-test probability settings, both over and under estimation of probabilities were noticed. In high pre-test probability setting, there was no significant difference in the reference and the responders' intuitive estimates of post test probability. Doctors were more likely to consider ordering the test as the disease probability increased. Most respondents were of the opinion that endoscopy is not a cost-effective procedure and may be associated with a potential harm. Improvement is needed in doctors' diagnostic ability by more emphasis on clinical decision-making and application of bayesian probabilistic thinking to real clinical situations.

Bedside teaching of clinical reasoning and evidence-based physical examination

Context and setting Medical school physical examination (PE) education focuses on the acquisition of skills in three domains: psychomotor (motor skills); affective (interaction with examinees), and cognitive (interpretation). To reinforce learning in the cognitive domain, we currently offer an advanced physical diagnosis elective to senior medical students to teach the principles of evidence-based physical examination (EBPE). Why the idea was necessary Recent studies have emphasised a ‘synthetic’ domain: practising doctors must not only recognise findings and understand their evidence-based utility, but must also make optimal management decisions based on these findings. ‘Synthesis’ is rarely taught; rather, students are expected to become adept simply with experience. Consequently, as they make the transition to internship, students may be ill-prepared to apply EBPE in practice. What was done The existing elective includes an introduction to the principles of EBPE. We developed a 3-hour structured bedside rounding session to reinforce key EBPE skills, including: estimation of pre-test probability; recognition of PE findings; evidence-based estimation of post-test probability of the disease, and decision making based on this assessment. For example, in a patient with dyspnoea, elevated neck veins, S3 heart sound and abdominojugular reflux, students decide whether to prescribe diuretics or to order an echocardiogram. Each session is structured as follows: faculty staff preselect two to four patients to examine at the bedside; small groups of three or four students examine the patients and are given feedback by the faculty staff about their examination technique and findings; the students commit to a next step in management, and the faculty staff provide feedback on the students’ decision making. Students answered preand post-elective questionnaires that measured their confidence in their ability to perform EBPE, the perceived utility of PE, and the usefulness of elective activities. Clinical vignettes presenting practice choices were used to assess clinical reasoning. Evaluation of results and impact Three 2-week electives were offered between November 2009 and March 2010. Twenty-one students participated. On a Likert scale of 1–5 (1 = not at all confident, 5 = very confident), students showed increased confidence in: (i) their PE skills in general (mean ± standard deviation [SD] score: retrospective pre-elective 3.38 ± 0.50, post-elective 4.19 ± 0.40; p < 0.05); (ii) understanding the significance of findings (mean ± SD: retrospective pre-elective 2.86 ± 0.57, post-elective 4.23 ± 0.44; p < 0.05), and (iii) making management decisions based on findings (mean ± SD: retrospective pre-elective 2.90 ± 0.87, post-elective 4.57 ± 0.60; p < 0.05). Most students requested that more bedside rounds be included in the elective. Vignettes designed to assess clinical reasoning won high pre-elective scores that did not change appreciably in post-elective testing. Our pilot of structured bedside rounds to teach senior medical students to recognise findings, understand their evidence-based utility and use assessments to make optimal management decisions was well received and valued by students. Students reported increased confidence in making management decisions based on PE findings at the end of the elective. However, improvement in clinical reasoning could not be detected using our assessments, indicating that better calibrated instruments to measure the synthetic domain must be developed.

Prognostic value of demographic factors, pre-test probability scoring, exercise test diagnosis, and inability to exercise in patients with recent onset suspected cardiac chest pain

To assess the prognostic value of an inconclusive exercise test or inability to exercise in patients with recent onset suspected cardiac chest pain and to determine the independent predictors of events in these patients. This was an observational follow-up study of patients presenting to a rapid access chest pain clinic with a history of recent-onset suspected cardiac chest pain as referred by the family practitioner. The main outcome measure was a composite endpoint of death and acute coronary syndrome hospital admission. The study cohort consisted of 1851 patients in whom a total of 147 events were recorded during a mean follow-up period of 4.1 ± 1.1 years. Those with events were significantly older (65.1 ± 12.5 years versus 56.4 ± 13.2 years, p < 0.001), had higher mean pre-test probability of coronary artery disease (CAD), and had higher prevalence of diabetes (18.4% vs. 13.6%, p < 0.001), hypertension (55.8% vs. 38.7%, p < 0.001), and smoking (36.7% vs. 25.4%, p = 0.03) than those without events. These patients were also more likely to have a positive exercise electrocardiogram (ECG) (15.6% vs. 8.6%, p < 0.001) or not have a diagnostic exercise test because of an inconclusive result or inability to exercise (60.5% vs. 28.6%, p < 0.001). Cox multivariate regression analysis showed that age (hazard ratio, HR 1.03, p < 0.001), pre-test probability of CAD (HR 1.08, p = 0.04), positive exercise ECG (HR 2.94, p < 0.001), and an inconclusive test or inability to exercise (HR 3.45, p < 0.001) were independent predictors of events. In patients with recent onset suspected cardiac chest pain, not having a diagnostic exercise ECG because of an inconclusive test or inability to exercise is an independent predictor of events and has similar prognostic implications to a positive exercise ECG. In addition, pre-test probability estimation at baseline is a robust indicator of clinical outcome. Future models of care need to incorporate early and increased access to non-exercise cardiac imaging techniques in order to meet the needs of this high-risk subgroup of patients.

A Clinical Scoring System for Selection of Patients for PTEN Mutation Testing Is Proposed on the Basis of a Prospective Study of 3042 Probands

Cowden syndrome (CS) and Bannayan-Riley-Ruvalcaba syndrome are allelic, defined by germline PTEN mutations, and collectively referred to as PTEN hamartoma tumor syndrome. To date, there are no existing criteria based on large prospective patient cohorts to select patients for PTEN mutation testing. To address these issues, we conducted a multicenter prospective study in which 3042 probands satisfying relaxed CS clinical criteria were accrued. PTEN mutation scanning, including promoter and large deletion analysis, was performed for all subjects. Pathogenic mutations were identified in 290 individuals (9.5%). To evaluate clinical phenotype and PTEN genotype against protein expression, we performed immunoblotting (PTEN, P-AKT1, P-MAPK1/2) for a patient subset (n = 423). In order to obtain an individualized estimation of pretest probability of germline PTEN mutation, we developed an optimized clinical practice model to identify adult and pediatric patients. For adults, a semiquantitative score-the Cleveland Clinic (CC) score-resulted in a well-calibrated estimation of pretest probability of PTEN status. Overall, decreased PTEN protein expression correlated with PTEN mutation status; decreasing PTEN protein expression correlated with increasing CC score (p < 0.001), but not with the National Comprehensive Cancer Network (NCCN) criteria (p = 0.11). For pediatric patients, we identified highly sensitive criteria to guide PTEN mutation testing, with phenotypic features distinct from the adult setting. Our model improved sensitivity and positive predictive value for germline PTEN mutation relative to the NCCN 2010 criteria in both cohorts. We present the first evidence-based clinical practice model to select patients for genetics referral and PTEN mutation testing, further supported biologically by protein correlation.

Pretest probability estimation in the evaluation of patients with possible deep vein thrombosis

Introduction An estimation of pretest probability is integral to the proper interpretation of a negative compression ultrasound in the diagnostic assessment of lower-extremity deep vein thrombosis. We sought to determine the rate, method, and predictors of pretest probability estimation in such patients. Methods This cross-sectional study of outpatients was conducted in a suburban community hospital in 2006. Estimation of pretest probability was done by enzyme-linked immunosorbent assay d-dimer, Wells criteria, and unstructured clinical impression. Using logistic regression analysis, we measured predictors of documented risk assessment. A cohort analysis was undertaken to compare 3-month thromboembolic outcomes between risk groups. Results Among 524 cases, 289 (55.2%) underwent pretest probability estimation using the following methods: enzyme-linked immunosorbent assay d-dimer (228; 43.5%), clinical impression (106; 20.2%), and Wells criteria (24; 4.6%), with 69 (13.2%) patients undergoing a combination of at least two methods. Patient factors were not predictive of pretest probability estimation, but the specialty of the clinician was predictive; emergency physicians ( P < .0001) and specialty clinicians ( P = .001) were less likely than primary care clinicians to perform risk assessment. Thromboembolic events within 3 months were experienced by 0 of 52 patients in the explicitly low-risk group, 4 (1.8%) of 219 in the explicitly moderate- to high-risk group, and 1 (0.4%) of 226 in the group that did not undergo explicit risk assessment. Conclusions Negative ultrasounds in the workup of deep vein thrombosis are commonly interpreted in isolation apart from pretest probability estimations. Risk assessments varied by physician specialties. Opportunities exist for improvement in the diagnostic evaluation of these patients.

Pretest expectations strongly influence interpretation of abnormal laboratory results and further management

BackgroundAbnormal results of diagnostic laboratory tests can be difficult to interpret when disease probability is very low. Although most physicians generally do not use Bayesian calculations to interpret abnormal results, their estimates of pretest disease probability and reasons for ordering diagnostic tests may - in a more implicit manner - influence test interpretation and further management. A better understanding of this influence may help to improve test interpretation and management. Therefore, the objective of this study was to examine the influence of physicians' pretest disease probability estimates, and their reasons for ordering diagnostic tests, on test result interpretation, posttest probability estimates and further management.MethodsProspective study among 87 primary care physicians in the Netherlands who each ordered laboratory tests for 25 patients. They recorded their reasons for ordering the tests (to exclude or confirm disease or to reassure patients) and their pretest disease probability estimates. Upon receiving the results they recorded how they interpreted the tests, their posttest probability estimates and further management. Logistic regression was used to analyse whether the pretest probability and the reasons for ordering tests influenced the interpretation, the posttest probability estimates and the decisions on further management.ResultsThe physicians ordered tests for diagnostic purposes for 1253 patients; 742 patients had an abnormal result (64%). Physicians' pretest probability estimates and their reasons for ordering diagnostic tests influenced test interpretation, posttest probability estimates and further management. Abnormal results of tests ordered for reasons of reassurance were significantly more likely to be interpreted as normal (65.8%) compared to tests ordered to confirm a diagnosis or exclude a disease (27.7% and 50.9%, respectively). The odds for abnormal results to be interpreted as normal were much lower when the physician estimated a high pretest disease probability, compared to a low pretest probability estimate (OR = 0.18, 95% CI = 0.07-0.52, p < 0.001).ConclusionsInterpretation and management of abnormal test results were strongly influenced by physicians' estimation of pretest disease probability and by the reason for ordering the test. By relating abnormal laboratory results to their pretest expectations, physicians may seek a balance between over- and under-reacting to laboratory test results.

Accuracy of Very Low Pretest Probability Estimates for Pulmonary Embolism Using the Method of Attribute Matching Compared with the Wells Score

Attribute matching matches an explicit clinical profile of a patient to a reference database to estimate the numeric value for the pretest probability of an acute disease. The authors tested the accuracy of this method for forecasting a very low probability of venous thromboembolism (VTE) in symptomatic emergency department (ED) patients. The authors performed a secondary analysis of five data sets from 15 hospitals in three countries. All patients had data collected at the time of clinical evaluation for suspected pulmonary embolism (PE). The criterion standard to exclude VTE required no evidence of PE or deep venous thrombosis (DVT) within 45 days of enrollment. To estimate pretest probabilities, a computer program selected, from a large reference database of patients previously evaluated for PE, patients who matched 10 predictor variables recorded for each current test patient. The authors compared the outcome frequency of having VTE [VTE(+)] in patients with a pretest probability estimate of <2.5% by attribute matching, compared with a value of 0 from the Wells score. The five data sets included 10,734 patients, and 747 (7.0%, 95% confidence interval [CI] = 6.5% to 7.5%) were VTE(+) within 45 days. The pretest probability estimate for PE was <2.5% in 2,975 of 10,734 (27.7%) patients, and within this subset, the observed frequency of VTE(+) was 48 of 2,975 (1.6%, 95% CI = 1.2% to 2.1%). The lowest possible Wells score (0) was observed in 3,412 (31.7%) patients, and within this subset, the observed frequency of VTE(+) was 79 of 3,412 (2.3%, 95% CI = 1.8% to 2.9%) patients. Attribute matching categorizes over one-quarter of patients tested for PE as having a pretest probability of <2.5%, and the observed rate of VTE within 45 days in this subset was <2.5%.

Performance of two relatively new quantitative D-dimer assays (Innovance D-dimer and AxSYM D-dimer) for the exclusion of deep vein thrombosis

Introduction D-dimer assays are now widely used as the first-line test in the diagnostic algorithm of suspected deep vein thrombosis (DVT). The aim of this study was to evaluate the performance of two relatively new quantitative D-Dimer assays (Innovance™ and AxSYM®) by comparison with a clinical gold standard. Patients and methods 311 samples from outpatients with clinical suspicion of DVT, included in a prospective management study, was analysed (prevalence of DVT 23%). The diagnostic workup included estimation of pre-test probability, D-dimer determination, objective imaging as well as 3 month clinical follow up of negative patients. Results No significant differences were seen in sensitivity and negative predictive values between Innovance, AxSYM and the reference assays. The area under the ROC curve was slightly lower for the AxSYM assay and the correlation to the reference assays was only moderate (r < 0.8) whereas the agreement with the Vidas assay was near excellent (κ = 0.8). The Innovance assay reached the highest AUC, showed a strong correlation with the reference assays (r ≥ 0.9) and a good agreement with the Vidas assay (κ = 0.76). In combination with a low pre-test probability score the Innovance assay reached a NPV of 100% (95% CI, 92-100) and the AxSYM assay 98% (95% CI, 87-100). Conclusion The Innovance and AxSYM assays show an overall good and comparable performance for the exclusion of DVT when compared to the established assays. Our results for the AxSYM assay indicate that the optimal cut-off value needs to be further evaluated.

Randomized Trial of Computerized Quantitative Pretest Probability in Low-Risk Chest Pain Patients: Effect on Safety and Resource Use

We hypothesize that the presentation of a quantitative pretest probability of acute coronary syndrome would safely reduce unnecessary resource use in low-risk emergency department (ED) chest pain patients. Randomized controlled trial of adult patients with chest pain paired with their clinicians. Patients had neither obvious evidence of acute coronary syndrome nor obvious other reason for admission. Clinicans provided their unstructured point estimate for pretest probability before randomization. Clinicans and patients in the intervention group received a printout of pretest probability of acute coronary syndrome result displayed numerically and graphically. Controls received no printout. Patients were followed for 45 days for predefined criteria of acute coronary syndrome and efficacy endpoints. Endpoints were compared between groups, with 95% confidence intervals (CIs) for differences. Four hundred were enrolled, and 31 were excluded for cocaine use or elopement from care. The mean pretest probability estimates of acute coronary syndrome were 4 (SD 5%) from clinicians and 4 (SD 6%) from the computer. Safety and efficacy endpoints for controls (n=185) versus intervention patients (n=184) were as follows: (1) delayed or missed diagnosis of acute coronary syndrome: 1 of 185 versus 0 of 184 (95% CI for difference -2.8% to 15.0%); (2) hospital admission with no significant cardiovascular diagnosis, 11% versus 5% (-0.2% to 11%); (3) thoracic imaging imparting greater than 5 mSv radiation with a negative result, 20% versus 9% (95% CI for difference = 3.8% to 18.0%); (4) median length of stay, 11.4 hours versus 9.2 hours (95% CI for difference = -2.9 to 7.6 hours); (5) reported feeling "very satisfied" with clinician explanation of problem on follow-up survey, 38% versus 49% (95% CI for difference = 0.9% to 21.0%); (6) readmitted within 7 days, 11% versus 4% (95% CI for difference = 2.5% to 13.2%). Presentation of a quantitative estimate of the pretest probability of acute coronary syndrome to clinicians and low-risk ED chest pain patients was associated with reduced resource use, without evidence of increased rate of premature discharge of patients with acute coronary syndrome.

Incorporating Uncertainty Into Medical Decision Making: An Approach to Unexpected Test Results

The utility of diagnostic tests derives from the ability to translate the population concepts of sensitivity and specificity into information that will be useful for the individual patient: the predictive value of the result. As the array of available diagnostic testing broadens, there is a temptation to de-emphasize history and physical findings and defer to the objective rigor of technology. However, diagnostic test interpretation is not always straightforward. One significant barrier to routine use of probability-based test interpretation is the uncertainty inherent in pretest probability estimation, the critical first step of Bayesian reasoning. The context in which this uncertainty presents the greatest challenge is when test results oppose clinical judgment. It is this situation when decision support would be most helpful. The authors propose a simple graphical approach that incorporates uncertainty in pretest probability and has specific application to the interpretation of unexpected results. This method quantitatively demonstrates how uncertainty in disease probability may be amplified when test results are unexpected (opposing clinical judgment), even for tests with high sensitivity and specificity. The authors provide a simple nomogram for determining whether an unexpected test result suggests that one should "switch diagnostic sides.'' This graphical framework overcomes the limitation of pretest probability uncertainty in Bayesian analysis and guides decision making when it is most challenging: interpretation of unexpected test results.