Retrospective validation of the pulmonary embolism rule-out criteria rule in 'PE unlikely' patients with suspected pulmonary embolism

Pulmonary Embolism Rule-out Criteria: Diagnostic Accuracy and Impact of COVID-19

BACKGROUND

The Pulmonary Embolism Rule-Out Criteria (PERC), developed to minimize unnecessary testing in low-risk pulmonary embolism (PE) cases, lacks clear validation in the context of COVID-19.

OBJECTIVES

To assess the validity of the PERC in emergency department patients having undergone computed tomography pulmonary angiography (CTPA) during the COVID-19 pandemic.

METHODS

We conducted a retrospective analysis of emergency department patients who underwent CTPA for suspected PE. COVID-19 status was based on the results of a reverse transcription-polymerase chain reaction (RT-PCR) test performed in the emergency department, or within 30 days prior to visiting the emergency department. We collected data on demographics, symptoms, d-dimer levels, and medical history relevant to thrombosis and conducted the PERC test using the criteria including age, oxygen saturation, heart rate, and the absence of hemoptysis or recent trauma. We categorized outcomes based on the concordance between the PERC results and CTPA findings, with specific definitions for true positive and negative, as well as false positive and negative results. We also evaluated the impact of COVID-19 status on the diagnostic performance of the PERC by analyzing the prevalence of PE in patients testing positive and negative for COVID-19.

RESULTS

Among the 2.430 participants, 45.1% tested negative for COVID-19, 43.4% tested positive, and 11.5% were untested. The PERC identified 91.2% of the cases as positive, 6.9% of which were confirmed to have PE. Overall, 84.9% of cases (n = 2.062) showed a discordant result between the PERC and CTPA findings. The lack of significant correspondence between the PERC positivity and actual PE presence (p = 0.001; p < 0.01) indicated low diagnostic concordance. In patients with a positive COVID-19 test result, the PERC demonstrated a sensitivity of 95.3% (95% CI: 86.91-99.02), a specificity of 9.1% (95% CI: 7.46-11.15), a positive predictive value of 6.3% (95% CI: 6.01-6.70), a negative predictive value of 96.8% (95% CI: 90.81-98.94), and an accuracy of 14.4% (95% CI: 12.34-16.67). In patients who tested negative for COVID-19, the sensitivity was 95.4% (95% CI: 88.64-98.73), the specificity was 7.8% (95% CI: 6.25-9.66), the positive predictive value was 8.1% (95% CI: 7.83-8.57), the negative predictive value was 95.1% (95% CI: 88.11-98.14), and the accuracy was 14.7% (95% CI: 12.73-17.02).

CONCLUSION

The study demonstrates that the sensitivity and negative predictive value of the PERC are comparable in COVID-19 positive and negative patients. Furthermore, the incidence of PE among patients presenting to the emergency department did not significantly differ based on COVID-19 status. While this study highlights the relevance of the PERC in clinical decision-making, caution is advised as the PERC may not always provide reliable results when used as the sole diagnostic test.

Intermediate-Risk and High-Risk Pulmonary Embolism: Recognition and Management: Cardiology Clinics: Cardiac Emergencies

Pulmonary embolism (PE) is the third most common cause of cardiovascular death. Every specialty of medical practitioner will encounter PE in their patients, and should be prepared to employ contemporary strategies for diagnosis and initial risk-stratification. Treatment of PE is based on risk-stratification, with anticoagulation for all patients, and advanced modalities including systemic thrombolysis, catheter-directed therapies, and mechanical circulatory supports utilized in a manner paralleling PE severity and clinical context.

Safety of the pulmonary embolism rule-out criteria rule: Findings from the Registro Informatizado de la Enfermedad TromboEmbolica venosa (RIETE) registry

BACKGROUND

The diagnostic strategy for pulmonary embolism (PE) includes a D-dimer test when PE probability is low or intermediate, but false-positive D-dimer results are frequent and can result in an unnecessary computed tomography pulmonary angiogram. The PE rule-out criteria (PERC) rule excludes PE without D-dimer testing when pretest probability is <15%. The aim of this study was to assess the safety of the PERC rule strategy in patients included in the Registro Informatizado de la Enfermedad TromboEmbolica venosa (RIETE) registry.

METHODS

This retrospective cohort study used data from the RIETE registry, an ongoing, international prospective registry of patients with objectively confirmed venous thromboembolism. The primary outcome was the failure rate of the PERC strategy, represented by the proportion of PERC-negative (PERC-N) patients with a PE included in the registry. Secondary outcomes were a comparison of the clinical characteristics, treatment strategy, and outcome of PERC-N versus PERC-positive (PERC-P) patients at 3 months.

RESULTS

From 2001 to 2021, a total of 49,793 patients with acute PE were enrolled in the RIETE registry. We included 48,903 in the final analysis after exclusion of 890 patients with an undetermined PERC status. Only 346 patients were PERC-N with a failure rate of 0.7% (95% confidence interval 0.6%-0.8%). PERC-N patients presented more frequently with chest pain but less often with dyspnea, syncope, or hypotension. They also had subsegmental or segmental PE more frequently, were more often treated with direct oral anticoagulants, and received mechanical or pharmacological thrombolysis less often. In addition, PERC-N patients had a lower incidence of recurrent deep vein thrombosis, major bleeding, and death attributed to PE during the 3-month follow-up.

CONCLUSIONS

A low failure rate of the PERC rule was observed in the RIETE registry, thus supporting its use to safely identify patients with an unlikely probability of PE.

Adherence to Best Practice Advice for Diagnosis of Pulmonary Embolism

PURPOSE

This study evaluated clinician adherence to the American College of Physicians Best Practice Advice for diagnosis of pulmonary embolism.

DESIGN

A prospective, single-center, descriptive design was utilized.

METHODS

A heterogeneous sample of 111 hemodynamically stable adult inpatients with a computed tomography pulmonary angiogram ordered was consented. Electronic medical records were reviewed for demographic and clinical variables to determine adherence. The 6 individual best practice statements and the overall adherence were evaluated by taking the sum of "yes" answers divided by the sample size.

RESULTS

Overall adherence was 0%. Partial adherence was observed with clinician-recorded clinical decisions rules and obtaining d-dimer (3.6% [4/111] and 10.2% [9/88], respectively) of low/intermediate probability scorers. Age adjustment of d-dimer was not recorded. Computed tomography pulmonary angiogram was the first diagnostic test in 89.7% (79/88) in low/intermediate probability patients.

CONCLUSION

In hemodynamically stable, hospitalized adults, adherence to best practice guidelines for diagnosis of pulmonary embolism was minimal. Clinical utility of the guidelines in hospitalized adults needs further evaluation. Systems problems (eg, lack of standardized orders, age-adjusted d-dimer values, information technology support) likely contributed to poor guideline adherence.

Previously undiagnosed scoliosis presenting as pleuritic chest pain in the emergency department - a case series and a validating retrospective audit

Background

Chest pain is one of the commonest presenting complaints in urgent/emergency care, with a lifelong prevalence of up to 25% in the adult population. Pleuritic chest pain is a subset of high investigation burden because of a diverse range of possible causes varying from simple musculoskeletal conditions to pulmonary embolism.

Case series

Among otherwise fit and healthy adult patients presenting in our emergency department with sudden onset of unilateral pleuritic chest pain, within 1 month we identified a cohort of five patients with pin-point tenderness in one specific costo-sternal joint often with referred pain to the back. All cases had apparent and, previously undiagnosed mild/moderate scoliosis.

Methods

To confirm and validate the observed association between scoliosis and pleuritic chest pain, a retrospective audit was designed and performed using the hospital’s electronic medical record system to reassess all consecutive adult chest pain patients.

Results

The Odds Ratio for having chest pain with scoliosis was 30.8 [95%CI 1.71–553.37], twenty times higher than suggested by prevalence data.

Discussion

In scoliosis the pathologic lateral curvature of the spine adversely affects the functional anatomy of both the spine and ribcage. In our hypothesis the chest wall asymmetry enables minor slip/subluxation of a rib either in the costo-sternal and/or costovertebral junction exerting direct pressure on the intercostal nerve causing pleuritic pain.

Conclusion

Thorough physical examination of the anterior and posterior chest wall is key to identify underlying scoliosis in otherwise fit patients presenting with sudden onset of pleuritic pain. Incorporating assessment for scoliosis in the low-risk chest pain protocols/tools may help reducing the length of stay in the emergency department and, facilitate speedy but safe discharge with increased patient satisfaction.

Systematic review and meta-analysis of test accuracy for the diagnosis of suspected pulmonary embolism

Pulmonary embolism (PE) is a common, potentially life-threatening yet treatable condition. Prompt diagnosis and expeditious therapeutic intervention is of paramount importance for optimal patient management. Our objective was to systematically review the accuracy of D-dimer assay, compression ultrasonography (CUS), computed tomography pulmonary angiography (CTPA), and ventilation-perfusion (V/Q) scanning for the diagnosis of suspected first and recurrent PE. We searched Cochrane Central, MEDLINE, and EMBASE for eligible studies, reference lists of relevant reviews, registered trials, and relevant conference proceedings. 2 investigators screened and abstracted data. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 and certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation framework. We pooled estimates of sensitivity and specificity. The review included 61 studies. The pooled estimates for D-dimer sensitivity and specificity were 0.97 (95% confidence interval [CI], 0.96-0.98) and 0.41 (95% CI, 0.36-0.46) respectively, whereas CTPA sensitivity and specificity were 0.94 (95% CI, 0.89-0.97) and 0.98 (95% CI, 0.97-0.99), respectively, and CUS sensitivity and specificity were 0.49 (95% CI, 0.31-0.66) and 0.96 (95% CI, 0.95-0.98), respectively. Three variations of pooled estimates for sensitivity and specificity of V/Q scan were carried out, based on interpretation of test results. D-dimer had the highest sensitivity when compared with imaging. CTPA and V/Q scans (high probability scan as a positive and low/non-diagnostic/normal scan as negative) both had the highest specificity. This systematic review was registered on PROSPERO as CRD42018084669.

A retrospective application of the pulmonary embolism rule out criteria (PERC) of the American College of Physicians would reduce the number of CTPAS by 6% without a false negative in an Irish hospital

BACKGROUND

Internationally, the number of computerised tomographic pulmonary angiographies (CTPAs) being performed to rule out pulmonary embolism (PE) has caused some concern.

AIM

This study was performed to assess if the application of Pulmonary Embolism Rule-out Criteria (PERC) in an Irish Emergency Department (ED) would have helped to safely reduce the number of D-dimer assays and computed tomographic pulmonary angiographies (CTPAs) ordered.

METHODS

The PERC was retrospectively calculated in all patients who underwent CTPA for possible PE. It was then established if the application of the PERC as per the American College of Physicians' (ACP) guidelines would have safely ruled out the need for further imaging.

RESULTS

Of the 529 patients who underwent CTPA in the study, 63 patients (12%) had PE on CTPA. Had the PERC criteria been applied, no patient who had a PE would have been missed. In this study, PERC had 100% sensitivity and 14% specificity.

DISCUSSION/CONCLUSION

Application of the PERC rule, as per the ACP guidelines, would have reduced the number of CTPAs performed by 32 (6%) without missing any patient with a proven pulmonary embolus.

EANM guideline for ventilation/perfusion single-photon emission computed tomography (SPECT) for diagnosis of pulmonary embolism and beyond

These guidelines update the previous EANM 2009 guidelines on the diagnosis of pulmonary embolism (PE). Relevant new aspects are related to (a) quantification of PE and other ventilation/perfusion defects; (b) follow-up of patients with PE; (c) chronic PE; and (d) description of additional pulmonary physiological changes leading to diagnoses of left ventricular heart failure (HF), chronic obstructive pulmonary disease (COPD) and pneumonia. The diagnosis of PE should be reported when a mismatch of one segment or two subsegments is found. For ventilation, Technegas or krypton gas is preferred over diethylene triamine pentaacetic acid (DTPA) in patients with COPD. Tomographic imaging with V/PSPECT has higher sensitivity and specificity for PE compared with planar imaging. Absence of contraindications makes V/PSPECT an essential method for the diagnosis of PE. When V/PSPECT is combined with a low-dose CT, the specificity of the test can be further improved, especially in patients with other lung diseases. Pitfalls in V/PSPECT interpretation are discussed. In conclusion, V/PSPECT is strongly recommended as it accurately establishes the diagnosis of PE even in the presence of diseases like COPD, HF and pneumonia and has no contraindications.

Prevalence of pulmonary embolism in emergency department patients with isolated syncope: a prospective cohort study

BACKGROUNDS

Paramount to guide the diagnostic strategy, the prevalence of pulmonary embolism in patients with syncope and no other symptoms is uncertain. We aimed to assess the pulmonary embolism prevalence in patients that present to the emergency department (ED) with syncope and no chest pain nor dyspnea.

METHODS

Multicenter prospective cohort study in seven EDs in France. Adult patients who presented to the ED with syncope (transient loss of consciousness) were included. Patients with chest pain or dyspnea were excluded. Included patients underwent formal work-up for pulmonary embolism, including D-dimer testing and further imaging if positive. Cases of pulmonary embolism were adjudicated by two independent expert radiologists with the review of imaging studies. Secondary objectives included the pulmonary embolism prevalence in the subgroup of patients with cancer, in patients with negative Pulmonary Embolism Rule Out criteria (PERC) score, and according to the clinical probability assessed either by Wells or revised Geneva score.

RESULTS

We analyzed 411 patients, in whom 128 (31%) underwent a computed tomographic pulmonary angiogram and 9 (2%) a ventilation-perfusion scan. A pulmonary embolism was confirmed in nine patients (prevalence of 2.2%, 95% confidence interval, 1.1-4.3%), including one subsegmental pulmonary embolism. This prevalence was of 18% (3-52%) in patients with cancer and 0.7% (0.1-4%) in PERC negative patients.

CONCLUSION

In our sample of patients with isolated syncope, the prevalence of pulmonary embolism was 2.2%. This value is not sufficiently low to negate the requirement for a formal work up in the ED, even in the absence of chest pain or dyspnea. However, the large confidence interval precludes any strong conclusion.

Retrospective Analysis of the Computed Tomography Pulmonary Angiogram Utilization Patterns in the Emergency Department

OBJECTIVES

Guidelines and high-quality studies recommend using clinical decision-making (CDM) tools over clinical gestalt when evaluating a patient for pulmonary embolism. The purpose of this study is to investigate our computed tomography pulmonary angiogram (CTPA) utilization patterns and identify causal factors.

METHODS

A retrospective cohort study of CTPA studies ordered by emergency physicians in January, April, July, and October 2017 was undertaken. All necessary information to categorize patients by Wells' score, revised Geneva score, and pulmonary embolism rule-out criteria (PERC) was collected. In addition, various bloodwork, chest radiograph, and computed tomography results were collected. This data was analysed by the Pearson chi-square test or Fisher's exact test for categorical data and independent-samples t test for continuous variables.

RESULTS

A total of 510 CTPA studies were performed, with a mean age was 61.6 and a 50.6% female population. 136 studies (26.7%) failed to appropriately follow any CDM tool. CDM tool failure rate was dependent on whether the study was ordered from a community (14.9%) or tertiary hospital (University of Alberta Hospital, 27.9% and Royal Alexandra Hospital, 24.6%) (P = .038). Of these 136 studies, 31 were low/moderate risk and the d-dimer was negative. The remainder were either PERC-negative or low/moderate risk without d-dimer performed. The cumulative positive pulmonary embolism rate was 12.5%. With utilization of a CDM tool, the positive pulmonary embolism rate was 15.0%, compared to 5.9% when using gestalt (P = .026).

CONCLUSIONS

This study confirms a high rate of CDM tool use failure, and a higher positive CTPA rate for CDM tools compared to clinical gestalt.

Development and Performance of the Pulmonary Embolism Result Forecast Model (PERFORM) for Computed Tomography Clinical Decision Support

IMPORTANCE

Pulmonary embolism (PE) is a life-threatening clinical problem, and computed tomographic imaging is the standard for diagnosis. Clinical decision support rules based on PE risk-scoring models have been developed to compute pretest probability but are underused and tend to underperform in practice, leading to persistent overuse of CT imaging for PE.

OBJECTIVE

To develop a machine learning model to generate a patient-specific risk score for PE by analyzing longitudinal clinical data as clinical decision support for patients referred for CT imaging for PE.

DESIGN, SETTING, AND PARTICIPANTS

In this diagnostic study, the proposed workflow for the machine learning model, the Pulmonary Embolism Result Forecast Model (PERFORM), transforms raw electronic medical record (EMR) data into temporal feature vectors and develops a decision analytical model targeted toward adult patients referred for CT imaging for PE. The model was tested on holdout patient EMR data from 2 large, academic medical practices. A total of 3397 annotated CT imaging examinations for PE from 3214 unique patients seen at Stanford University hospitals and clinics were used for training and validation. The models were externally validated on 240 unique patients seen at Duke University Medical Center. The comparison with clinical scoring systems was done on randomly selected 100 outpatient samples from Stanford University hospitals and clinics and 101 outpatient samples from Duke University Medical Center.

MAIN OUTCOMES AND MEASURES

Prediction performance of diagnosing acute PE was evaluated using ElasticNet, artificial neural networks, and other machine learning approaches on holdout data sets from both institutions, and performance of models was measured by area under the receiver operating characteristic curve (AUROC).

RESULTS

Of the 3214 patients included in the study, 1704 (53.0%) were women from Stanford University hospitals and clinics; mean (SD) age was 60.53 (19.43) years. The 240 patients from Duke University Medical Center used for validation included 132 women (55.0%); mean (SD) age was 70.2 (14.2) years. In the samples for clinical scoring system comparisons, the 100 outpatients from Stanford University hospitals and clinics included 67 women (67.0%); mean (SD) age was 57.74 (19.87) years, and the 101 patients from Duke University Medical Center included 59 women (58.4%); mean (SD) age was 73.06 (15.3) years. The best-performing model achieved an AUROC performance of predicting a positive PE study of 0.90 (95% CI, 0.87-0.91) on intrainstitutional holdout data with an AUROC of 0.71 (95% CI, 0.69-0.72) on an external data set from Duke University Medical Center; superior AUROC performance and cross-institutional generalization of the model of 0.81 (95% CI, 0.77-0.87) and 0.81 (95% CI, 0.73-0.82), respectively, were noted on holdout outpatient populations from both intrainstitutional and extrainstitutional data.

CONCLUSIONS AND RELEVANCE

The machine learning model, PERFORM, may consider multitudes of applicable patient-specific risk factors and dependencies to arrive at a PE risk prediction that generalizes to new population distributions. This approach might be used as an automated clinical decision-support tool for patients referred for CT PE imaging to improve CT use.