Pulmonary Embolism Rule-out Criteria Research Articles

Development of a machine learning model using electrocardiogram signals to improve acute pulmonary embolism screening.

AimsClinical scoring systems for pulmonary embolism (PE) screening have low specificity and contribute to computed tomography pulmonary angiogram (CTPA) overuse. We assessed whether deep learning models using an existing and routinely collected data modality, electrocardiogram (ECG) waveforms, can increase specificity for PE detection.Methods and resultsWe create a retrospective cohort of 21 183 patients at moderate- to high suspicion of PE and associate 23 793 CTPAs (10.0% PE-positive) with 320 746 ECGs and encounter-level clinical data (demographics, comorbidities, vital signs, and labs). We develop three machine learning models to predict PE likelihood: an ECG model using only ECG waveform data, an EHR model using tabular clinical data, and a Fusion model integrating clinical data and an embedded representation of the ECG waveform. We find that a Fusion model [area under the receiver-operating characteristic curve (AUROC) 0.81 ± 0.01] outperforms both the ECG model (AUROC 0.59 ± 0.01) and EHR model (AUROC 0.65 ± 0.01). On a sample of 100 patients from the test set, the Fusion model also achieves greater specificity (0.18) and performance (AUROC 0.84 ± 0.01) than four commonly evaluated clinical scores: Wells’ Criteria, Revised Geneva Score, Pulmonary Embolism Rule-Out Criteria, and 4-Level Pulmonary Embolism Clinical Probability Score (AUROC 0.50–0.58, specificity 0.00–0.05). The model is superior to these scores on feature sensitivity analyses (AUROC 0.66–0.84) and achieves comparable performance across sex (AUROC 0.81) and racial/ethnic (AUROC 0.77–0.84) subgroups.ConclusionSynergistic deep learning of ECG waveforms with traditional clinical variables can increase the specificity of PE detection in patients at least at moderate suspicion for PE.

Machine learning with D-dimer in the risk stratification for pulmonary embolism: a derivation and internal validation study.

To develop a machine learning model to predict the diagnosis of pulmonary embolism (PE). We undertook a derivation and internal validation study to develop a risk prediction model for use in patients being investigated for possible PE. The machine learning technique, generalized logistic regression using elastic net, was chosen following an assessment of seven machine learning techniques and on the basis that it optimized the area under the receiver operator characteristic curve (AUC) and Brier score. Models were developed both with and without the addition of D-dimer. A total of 3347 patients were included in the study of whom, 219 (6.5%) had PE. Four clinical variables (O2 saturation, previous deep venous thrombosis or PE, immobilization or surgery, and alternative diagnosis equal or more likely than PE) plus D-dimer contributed to the machine learning models. The addition of D-dimer improved the AUC by 0.16 (95% confidence interval 0.13-0.19), from 0.73 to 0.89 (0.87-0.91) and decreased the Brier score by 14% (10-18%). More could be ruled out with a higher positive likelihood ratio than by the Wells score combined with D-dimer, revised Geneva score combined with D-dimer, or the Pulmonary Embolism Rule-out Criteria score. Machine learning with D-dimer maintained a low-false-negative rate at a true-negative rate of nearly 53%, which was better performance than any of the other alternatives. A machine learning model outperformed traditional risk scores for the risk stratification of PE in the emergency department. However, external validation is needed.

Acute Pulmonary Embolism–Its Diagnosis and Treatment From a Multidisciplinary Viewpoint.

Physicians from many different specialties see patients suffering from acute pulmonary embolism (PE), which has an incidence of 39-115 cases per 100 000 persons per year. Because PE can be life-threatening, a rapid, targeted response is essential. This review is based on pertinent publications retrieved by a selective literature search of international databases, with particular attention to current guidelines and expert opinions. Whenever PE is suspected, clinical assessment tools must be applied for risk stratification and diagnostic evaluation. The PERC (Pulmonary Embolism Rule-out Criteria) and the YEARS algorithm lead to more effective diagnosis. For hemodynamically unstable patients, bedside echocardiography is of high value and enables risk stratification. New oral anticoagulants have fewer hemorrhagic complications than vitamin K antagonists and are not inferior to them with respect to the risk of recurrent PE (hazard ratio 0.84-1.09). The duration of anticoagulation is set according to the risk of recurrence. Systemic thrombolysis is recommended for patients with a high-risk PE, in whom it significantly reduces mortality (odds ratio 0.53, number needed to treat 59). Surgical or interventional techniques can be considered if thrombolysis is contraindicated or unsuccessful. Newly introduced diagnostic aids and algorithms simplify the diagnosis and treatment of acute PE while continuing to assure a high degree of patient safety.

Combined Use of Wells Scores and D-dimer Levels for the Diagnosis of Deep Vein Thrombosis and Pulmonary Embolism in COVID-19: A Retrospective Cohort Study.

IntroductionDeep vein thrombosis (DVT) and pulmonary embolism (PE) are key complications of coronavirus disease 2019 (COVID-19). The study's primary outcome was assessing the utility of Wells DVT, Wells PE scores, and D-dimers in diagnosing DVT and PE. Secondary outcomes were the risk factors for the development of PE and DVT in COVID-19 patients.Materials and methodsWe compared COVID-19 patients with a positive and negative lower extremity (LE) duplex. A similar approach was made for patients who underwent imaging for PE.ResultsThe prevalence of PE was 23.8% (26 out of 109 patients), and the prevalence of DVT was 33% (35 out of 106). A D-dimer of 500 ng/mL had a sensitivity of 95.6% and 93.7% for the diagnosis of PE and DVT, respectively. A Wells DVT score of 3 points had a specificity of 92.9% and sensitivity of 8.8% for DVT diagnosis in COVID-19. A Wells PE score of 4 had a specificity of 100% and a sensitivity of 20% for the diagnosis of PE. The combined approach of using a Wells DVT score of 3 in suspected DVT and a Wells PE score of 4 in suspected PE and D-dimers of 500 ng/ml has a sensitivity of 94.2% and 96.1%, respectively.In the suspected DVT group, male gender (OR 3.88, 95% CI 1.55-9.7, P=0.004), lower body mass index (BMI) (OR 0.92, 95% CI 0.86-0.99, P=0.037), antiplatelet use (OR 0.19, 95% CI 0.04-0.88, P=0.035), systolic blood pressure ≤100 mmhg (OR 4.96, 95% CI 1.37-17.86, P=0.014), absolute lymphocytes ≤1 (OR 2.57, 95% CI 1.07-6.12, P=0.033), D-dimer ≥500 ng/ml (OR 6.42, 95% CI 1.40-29.38, P=0.016), blood urea nitrogen (BUN) ≥20 mg/dl (OR 2.33, 95% CI 1.00-5.41, P=0.048), and intubation (OR 3.32, 95% CI 1.26-8.78, P=0.015) were found to be statistically significant for DVT.In the suspected PE group, history of cancer (OR 10.69, 95% CI 1.06-107.74, P=0.044), total WBC count (OR 1.07, 95% CI 0.95-1.21, P=0.032), platelets ≥ 400,000 (OR 5.13, 95% CI 1.79-14.68, P=0.002), D-dimer levels ≥ 500 ng/ml (OR 25.47, 95% CI 3.27-197.97, P=0.002), Wells PE score (OR 2.46, 95% CI 1.50-4.06, P<0.001), pulmonary embolism rule-out criteria (PERC) score (OR 1.79, 95% CI 1.05-3.05, P=0.054), and Sequential Organ Failure Assessment (SOFA) score (OR 1.91, 95% CI 1.16-3.12, P=0.002) were statistically significant.ConclusionsThe combined approach of using a Wells DVT score of 3 in suspected DVT and Wells PE score of 4 in suspected PE and D-dimers of 500 ng/ml may be used to diagnose PE and DVT in COVID-19. Venous thromboembolism (VTE) occurrence in COVID-19 is associated with non-traditional risk factors such as intubation and higher severity of systemic inflammation, and these patients may benefit from more aggressive testing for VTE.

Venous thromboembolism management and the new NICE guidance: what the busy GP needs to know.

This article summarises the 2020 National Institute for Health and Care Excellence (NICE) venous thromboembolism (VTE) guidelines, which are also covered in Royal College of General Practitioners (RCGP) Essential Knowledge Updates (EKU) e-learning. This article focuses on rapid detection and treatment, changes in recommendations around anticoagulation, and implications for primary care practice.1 Individual signs and symptoms have a low positive predictive value (PPV) for VTE, making the clinical diagnosis difficult. For example, one primary care study found 77.8% of patients with a pulmonary embolism (PE) were breathless at time of assessment and 59.8% had chest pain, but only 29.5% were tachycardic and 28.0% had calf pain.2 The PPV of unilateral leg swelling ≥2 cm is just 27% for deep vein thrombosis (DVT).3 Reassuringly, the absence of any clinical signs suggestive of DVT in low-risk patients has a negative predictive value of 97%.3 To help exclude a PE on clinical grounds, the NICE now recommends using the PERC rule (Pulmonary Embolism Rule-Out Criteria) among selected low-risk patients.4 A patient must score zero to exclude a PE. One external validation study including over 8000 patients found that a PERC score of 0 had a false negative rate of just 1.0% (95% confidence interval [CI] = 0.6% to 1.6%) in low-risk patients.4 It is important to note that the PERC score was developed in emergency departments and is yet to be externally …

Electronic pulmonary embolism clinical decision support and effect on yield of computerized tomographic pulmonary angiography: ePE-A pragmatic prospective cohort study.

ObjectiveMultiple professional societies recommend pre‐test probability (PTP) assessment prior to imaging in the evaluation of patients with suspected pulmonary embolism (PE), however, PTP testing remains uncommon, with imaging occurring frequently and rates of confirmed PE remaining low. The goal of this study was to assess the impact of a clinical decision support tool embedded into the electronic health record to improve the diagnostic yield of computerized tomography pulmonary angiography (CTPA) in suspected patients with PE in the emergency department (ED).MethodsBetween July 24, 2014 and December 31, 2016, 4 hospitals from a healthcare system embedded an optional electronic clinical decision support system to assist in the diagnosis of pulmonary embolism (ePE). This system employs the Pulmonary Embolism Rule‐out Criteria (PERC) and revised Geneva Score (RGS) in series prior to CT imaging. We compared the diagnostic yield of CTPA) among patients for whom the physician opted to use ePE versus the diagnostic yield of CTPA when ePE was not used.ResultsDuring the 2.5‐year study period, 37,288 adult patients were eligible and included for study evaluation. Of eligible patients, 1949 of 37,288 (5.2%) were enrolled by activation of the tool. A total of 16,526 CTPAs were performed system‐wide. When ePE was not engaged, CTPA was positive for PE in 1556 of 15,546 scans for a positive yield of 10.0%. When ePE was used, CTPA identified PE in 211 of 980 scans (21.5% yield) (P < 0.001).ConclusionsePE significantly increased the diagnostic yield of CTPA without missing 30‐day clinically overt PE.

Pulmonary Embolism in Sickle Cell Disease: Retrospective Analysis of the Use and Yield of Radiographic Studies

▪Venous thromboembolism is a well-known complication of sickle cell disease1-3 and is associated with significant morbidity and mortality, particularly in the case of pulmonary embolisms. On the other hand, concerns have been raised regarding the overuse of imaging when evaluating for PE.4,5 Multiple algorithms have been developed, including the Geneva score,6 Wells' criteria,7 and Pulmonary Embolism Rule-Out Criteria (PERC),8 to better determine the pre-test probability of pulmonary embolism and help curtail the utilization of imaging. Patients with sickle cell disease, particularly when in vaso-occlusive crisis, may have a presentation that confounds the data incorporated into the algorithms, such as abnormal vital signs or d-dimer measurements, making the evaluation challenging. Furthermore, acute chest syndrome (ACS) is another notable acute clinical manifestation of sickle cell disease and can have symptoms and objective measures that are similar to PE with PE itself being a potential trigger for ACS. There is limited data on the extent to which SCD patients undergo scans to evaluate for PE and on the yield of these scans. While complications of SCD including ACS have been found to be more common in patients with hemoglobin SS than SC or sickle beta thalassemia,9 venous thromboembolism has been found to be more prevalent in SC and sickle beta thalassemia.2The sickle cell center at Grady Memorial Hospital, Atlanta, GA currently has more than 1,100 adult patients enrolled, accounting for the largest adult sickle cell population in North America. Through a retrospective chart review of these patients, we determined the prevalence of use of imaging to evaluate for pulmonary embolism and the yield from these radiographic studies, comparing this data across the hemoglobin genotypes. We also assessed for how often these these patients were ultimately diagnosed with ACS instead of or in addition to PE.In total, the charts of 1,143 patients were reviewed. 1,127 of these patients had clearly documented hemoglobin (Hgb) phenotypes; the 16 charts without known Hgb phenotype were excluded from further analysis. Of the 1,127 patients, 709 patients were Hgb SS, 311 SC, 87 sickle beta plus thalassemia (Sb+), 18 sickle beta zero thalassemia (Sb°), 1 SD, and 1 O-Arab. 231 (32.6%) of the Hgb SS patients had imaging while 69 (22.2%) of the SC patients (Table 1), 20 (23.0%) of the Sb+ patients, and 3 (16.7%) of the Sb° patients had imaging. SS patients had 21 (6.2%) studies positive for PE while SC patients had 17 (17.3%) (Table 1), Sb+ patients had 4 (13.3%), and Sb° patients had 2 (9.1%) such studies. Of the PEs diagnosed via CT scans, 13 out of the 17 positive studies for SS patients involved segmental vessels, which was the case with 11 out of 15 for SC patients. When imaged, either inpatient or outpatient, 81 (24.0%) of the cases involving SS patients resulted in a diagnosis of acute chest syndrome; this occurred in 15 (15.3%) of SC patient cases, 4 (13.3%) of Sb+ cases, and 1 (4.5%) of Sb° cases.In this study, we demonstrate that a significantly higher proportion of the Hgb SS patients underwent radiographic studies to evaluate for a pulmonary embolism compared to their SC counterparts despite having a significantly lower yield on these studies. However, the SS patients were more likely to be diagnosed with ACS, suggesting that this diagnosis may need to be more seriously considered before PE in this cohort. This data also suggests that though literature may have previously suggested that thromboembolic disease is more prevalent in SC than SS patients, there may be less awareness of such data among providers, who may be assuming that all sickle cell complications are most common in SS patients. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Development of a Machine Learning Model Using Electrocardiogram Signals to Improve Pulmonary Embolism Screening

Background: Clinical scoring systems for pulmonary embolism (PE) screening have low specificity and contribute to CT pulmonary angiogram (CTPA) overuse. We assessed whether deep learning models using an existing and routinely collected data modality, electrocardiogram (ECG) waveforms, can increase specificity for PE detection. Methods: We use clinical variables, annotated CTPAs, and ECG waveform and morphological parameter data from five hospitals to conduct a retrospective cohort study and develop three models to predict PE likelihood: an ECG model using only ECG waveform data, an EHR model using tabular clinical data, and a Fusion model integrating tabular clinical data and an embedded representation of the ECG waveform. We benchmark the best model against four clinical scores: Wells’ Criteria, Revised Geneva Score, Pulmonary Embolism Rule-Out Criteria, and 4-Level Pulmonary Embolism Clinical Probability Score. Finally, we investigate model robustness through feature sensitivity analyses and assess for demographic subgroup performance parity. Findings: We create a dataset linking 23,793 CTPAs (10·0% PE-positive) and 320,746 ECGs from 21,183 patients for model development and testing. We find that a Fusion model (area under receiver-operating characteristic [AUROC] 0·81 ± 0·01) outperforms both the ECG model (AUROC 0·59 ± 0·01) and EHR model (AUROC 0·65 ± 0·01). On a sample of 100 patients from the test set, the Fusion model has greater specificity (0·18) and performance (AUROC 0·84 ± 0.01) than the all four clinical criteria (AUROC 0·50-0·58, specificity 0·00-0·05). The model also retains superiority over clinical scores in feature sensitivity analyses (AUROC 0·66 to 0·84) and achieves comparable performance across different sex (AUROC 0·81) and racial (AUROC 0·77 to 0·84) subgroups. Interpretation: Integration of electrocardiogram waveforms with traditional clinical variables synergistically increases prediction performance and specificity for PE detection in those who are at least at moderate suspicion for PE. Funding: National Center for Advancing Translational Sciences, National Institutes of Health. Declaration of Interest: All authors declare no competing interests with this study. Ethical Approval: The study was approved by the Mount Sinai Institutional Review Board.

Clinician Gestalt in Managing Pediatric Pneumonia: Can We Predict the Future?

* Abbreviation: CAP — : community acquired pneumonia > It’s tough to make predictions, especially about the future. > > Yogi Berra In this issue of Pediatrics , Gao et al1 examine the value of clinical gestalt in predicting the progression to severe disease in children presenting to an urban pediatric emergency department with suspected community acquired pneumonia (CAP). CAP is one of the most common serious infections of childhood, accounting for ∼2 million annual ambulatory visits and 124 000 annual hospitalizations in the United States alone.2–5 Globally, childhood pneumonia accounts for significant morbidity and mortality, particularly in low- and middle-income countries.6 Complications of CAP include pleural effusions, empyema, sepsis, and others that may require additional procedures, ICU stays, and prolonged antibiotic courses. The management of CAP relies on appropriate diagnosis as well as thoughtful risk stratification to inform decisions, such as antimicrobial choice, patient disposition, and follow-up timing. Clinicians are often required to make these types of diagnoses and initial management decisions on the basis of brief encounters with patients. The impressions made on these visits often rely on a heuristic (ie, shortcut) approach to diagnosis and management. Much of medical decision-making relies on pattern recognition, which can include gestalt, gut feeling, or intuition.7 In this prospective cohort study, pediatric emergency medicine physicians were asked to estimate the probability that patients with suspected pneumonia (based on initial patient encounter and chest radiograph findings) will develop a complicated and/or severe pneumonia.1 The authors found that clinician gestalt was most sensitive (>90%) when the estimate for a complicated pneumonia was low and most specific (>90%) when the probability for complications to develop was judged to be … Address correspondence to Louis M. Bell, MD, Children’s Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104. E-mail: belll{at}chop.edu

Serial use of existing clinical decisions aids can reduce computed tomography pulmonary angiography for pulmonary embolism.

Pulmonary embolism (PE) remains a diagnostic challenge in emergency medicine. Clinical decision aids (CDAs) like the Pulmonary Embolism Rule-Out Criteria (PERC) are sensitive but poorly specific; serial CDA use may improve specificity. The goal of this before-and-after study was to determine if serial use of existing CDAs in a novel diagnostic algorithm safely decreases the use of CT pulmonary angiograms (CTPA). This was a retrospective before-and-after study conducted at an urban ED with 105,000 annual visits. Our algorithm uses PERC, Wells' score, and D-dimer in series, before moving to CTPA. The algorithm was introduced in January, 2017. Use of CDAs and D-dimer in the 24months pre- and 12months post-intervention were obtained by chart review. The algorithm's effect on CTPA ordering was assessed by comparing volume 5years pre- and 3years post-intervention, adjusted for ED volume. Mean CTPAs per 1000 adult ED visits was 11.1 in the 5 pre-intervention years and 9.9 in the 3 post-intervention years (p < 0.0001). Use of PERC, Wells' score and D-dimer increased from 1.1%, 1.1%, and 28% to 8.8% (p = 0.0002) 8.1% (p = 0.0005), and 35% (p = 0.0066), respectively. Pre-intervention, there were six potentially missed PEs compared to three in the post-intervention period. Introduction of our serial CDA diagnostic algorithm was associated with increased use of CDAs and D-dimer and reduced CTPA rate without an apparent increase in the number of missed PEs. Prospective validation is needed to confirm these results.

Consenso multidisciplinar para el manejo de la tromboembolia de pulmón

We have updated recommendations on 12 controversial topics that were published in the 2013 National Consensus on the diagnosis, risk stratification and treatment of patients with pulmonary embolism (PE). A comprehensive review of the literature was performed for each topic, and each recommendation was evaluated in two teleconferences. For diagnosis, we recommend against using the Pulmonary Embolism Rule Out Criteria (PERC) rule as the only test to rule out PE, and we recommend using a D-dimer cutoff adjusted to age to rule out PE. We suggest using computed tomography pulmonary angiogram as the imaging test of choice for the majority of patients with suspected PE. We recommend using direct oral anticoagulants (over vitamin K antagonists) for the vast majority of patients with acute PE, and we suggest using anticoagulation for patients with isolated subsegmental PE. We recommend against inserting an inferior cava filter for the majority of patients with PE, and we recommend using full-dose systemic thrombolytic therapy for PE patients requiring reperfusion. The decision to stop anticoagulants at 3 months or to treat indefinitely mainly depends on the presence (or absence) and type of risk factor for venous thromboembolism, and we recommend against thrombophilia testing to decide duration of anticoagulation. Finally, we suggest against extensive screening for occult cancer in patients with PE.

In-Silico Screening: Accurately Predicting Results of the Direct Antiglobulin Test using Commonly Available Lab Data

Abstract Introduction/Objective The Direct Antiglobulin Test (DAT) is a useful screening test to determine whether a patient’s red blood cells have been sensitized to immunoglobulin or complement. Like the majority of screening tests, the DAT compromises specificity for sensitivity in order to quickly assess for hemolysis and its dangerous sequelae. Because of the high sensitivity of the DAT, improper ordering of this test can confuse the clinical picture at best and result in misdiagnosis at worst. Pre-tests for ruling-out disease have proven effective in limiting test ordering, such as the Pulmonary Embolism Rule-out Criteria (“PERC rule”) for limiting the use of D-dimers. A similar pre-test could prove useful in DATs. We use “in silico testing” – testing via computer simulation – to predict the likelihood of any DAT being positive, given common patient attributes and laboratory values. Methods A three-layer deep-learning artificial neural network (ANN) was created using Python and the machine learning framework Keras. The ANN was compiled to maximize specificity while retaining 100% sensitivity. Input variables to the model were patient sex and age, along with most recent lab values for hemoglobin, hematocrit, white blood cell count, platelet count, total bilirubin, direct bilirubin, and haptoglobin, where available. The output of the ANN was a binary variable: “ruled-out” versus “further testing necessary”. The ANN was trained on all positive (n=30) and negative (n=63) DATs performed on November 2019 through March 2020, with a final total of ninety-three patients. A 10-fold cross-validation of the entire dataset was used to measure performance. Results The ANN was able to maximize specificity to 83% while retaining 100% sensitivity. A ROC curve of the model shows performance well above that of the no-discrimination line. Conclusion “In-silico testing” can accurately screen the likelihood of a positive result for a labor and time-intensive test, such as the DAT, before the actual test is performed. This has the potential to reduce unnecessary testing if validated in clinical practice. Analogous to their clinical counterpart “the PERC rule,” computer models that maximize specificity while retaining 100% sensitivity could achieve more effective test utilization and more informative results.

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.

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

Case Report: A Near Miss of Pulmonary Embolism in a Division 1 Collegiate Basketball Player.

IntroductionThe clinical presentation of pulmonary embolism (PE) is often associated with classic vital instability such as tachycardia, hypoxia, and tachypnea. This critical diagnosis is often less likely if a patient is negative by Pulmonary Embolism Rule-Out Criteria (PERC) standards with a low pre-test probability of disease. Caution must be used when evaluating elite athletes with the PERC rule due to low resting heart rate and certain risk factors, which are inherent to athletics.Case ReportWe report the case of a 20-year-old male Division 1 collegiate athlete with pleuritic chest pain diagnosed with PE despite being PERC negative. His presenting heart rate (HR) of 79 beats per minute was correctly determined to be tachycardic relative to his resting HR of 47–60 beats per minute. Despite his PERC negative status, PE was found after an elevated D-dimer and subsequent computed tomography angiography.ConclusionSpecial consideration should be used when evaluating elite athletes for PE, as their resting physiology may differ from the general population. Additionally, certain risk factors for thromboembolic disease are inherent in competitive athletics and should be considered during an initial risk assessment. The presented patient was successfully treated with oral anticoagulation for three months and was able to return to play.

Hot Off the Press: Tell Me How To Diagnose a Pulmonary Embolism.

Pulmonary embolism (PE) is common and life-threatening Emergency Department (ED) diagnosis. Multiple validated risk stratification tools exist to help evaluate for PE and reduce unnecessary imaging. Despite these tools, there is still significant over-investigation for PE and low value testing persists. This study asks ED providers what are the barriers and facilitators to uptake of validated risk stratification tools in evaluation of PE.

Patients with Mild COVID-19 Symptoms and Coincident Pulmonary Embolism: A Case Series.

IntroductionFrequent thrombotic complications have been reported in patients with severe coronavirus disease 2019 (COVID-19) infection. The risk in patients with mild disease is unknown.Case ReportWe report a case series of three individuals recently diagnosed with COVID-19, who presented to the emergency department with chest pain and were found to have pulmonary emboli. The patients had mild symptoms, no vital sign abnormalities, and were negative according to the pulmonary embolism rule-out criteria.ConclusionThis suggests that patients with active or suspected COVID-19 should be considered at elevated risk for pulmonary embolism when presenting with chest pain, even without common risk factors for pulmonary embolism.

MOdified DIagnostic strateGy to safely ruLe-out pulmonary embolism In the emergency depArtment: study protocol for the Non-Inferiority MODIGLIANI cluster cross-over randomized trial

IntroductionIn the work-up strategy for pulmonary embolism (PE) in the ED, the recently introduced YEARS rule allows the raising of the D-dimer threshold to 1000 ng/ml in patients with no signs of deep venous thrombosis and no hemoptysis and in whom PE is not the most likely diagnosis. However, this decision rule has never been prospectively compared to the usual strategy. Furthermore, it is unclear if the YEARS rule can be used on top of the Pulmonary Embolism Rule-out Criteria (PERC). We aim to assess the non-inferiority of YEARS compared to current guidelines to rule out PE among PERC-positive ED patients with suspicion of PE.Methods/designThe MODIGLIANI study is a multicenter, European, non-inferiority, cluster-randomized, two periods cross-over, controlled trial. Each center will be randomized for the sequence of two 4-month periods: intervention (MOdified Diagnostic Strategy: MODS) followed by control (usual care), or control followed by intervention with 1 month of “wash-out” between the two periods. In the control period, the threshold will be as usual (500 ng/ml for patients aged 50 years or younger and age × 10 for older patients). In the MODS period, the threshold of D-dimers to rule out PE will be raised to 1000 ng/ml if no item of the YEARS score is present or will remain unchanged otherwise. Patients will be included if they have a suspicion of PE, defined as chest pain, dyspnea, or syncope. Non-inclusion criteria comprise a high clinical probability of PE or PERC-negative patients with low clinical probability.Ethics and disseminationThe study has received the following approvals: Comité de protection des personnes Ile de France XI (France) and Comité de Ética de la Investigación con medicamentos del Hospital Clínic de Barcelona (Spain). Results will be made available to all included participants and other researchers.Trial registrationClinicalTrials.gov, NCT04032769. Registered on 24 July 2019.

Advances in the Diagnosis of Venous Thromboembolism: A Literature Review.

The incidence of venous thromboembolism (VTE), including lower extremity deep vein thrombosis (DVT) and pulmonary embolism (PE) is increasing. The increase in suspicion for VTE has lowered the threshold for performing imaging studies to confirm diagnosis of VTE. However, only 20% of suspected cases have a confirmed diagnosis of VTE. Development of pulmonary embolism rule-out criteria (PERC) and update in pre-test probability have changed the paradigm of ruling-out patient with low index of suspicion. The D-dimer test in conjunction to the pre-test probability has been utilized in VTE diagnosis. The age appropriate D-dimer cutoff and inclusion of YEARS algorithm (signs of the DVT, hemoptysis and whether PE is the likely diagnosis) for the D-dimer cutoff have been recent updates in the evaluation of suspected PE. Multi-detector computed tomography pulmonary angiography (CTPA) and compression ultrasound (CUS) are the preferred imaging modality to diagnose PE and DVT respectively. The VTE diagnostic algorithm do differ in pregnant individuals. The prerequisite of avoiding excessive radiation has recruited planar ventilation-perfusion (V/Q) scan as preferred in pregnant patients to evaluate for PE. The modification of CUS protocol with addition of the Valsalva maneuver should be performed while evaluating DVT in pregnant individual.

The use of clinical decision rules for pulmonary embolism in the emergency department: a retrospective study

BackgroundPulmonary embolism (PE) is a common and life-threatening medical condition with non-specific clinical presentation. Computed tomography pulmonary angiography (CT-PA) has been the diagnostic modality of choice, but its use is not without risks. Clinical decision rules have been established for the use of diagnostic modalities for patients with suspected PE. This study aims to assess the adherence of physicians to the diagnostic algorithms and rules.MethodsA retrospective observational study examining the utilization of CT-PA in the Emergency Department of King Fahd Hospital of Imam Abdulrahman Bin Faisal University for patients with suspected PE from May 2016 to December 2019. The electronic health records were used to collect the data, including background demographic data, clinical presentation, triage vital signs, D-dimer level (if ordered), risk factors for PE, and the CT-PA findings. The Wells score and pulmonary embolism rule-out (PERC) criteria were calculated retrospectively without knowledge of the results of D-dimer and the CT-PA.ResultsThe study involved a total of 353 patients (125 men and 228 women) with a mean age of 46.7 ± 18.4 years. Overall, 200 patients (56.7%) were classified into the “PE unlikely” group and 153 patients (43.3%) in the “PE likely” group as per Wells criteria. Out of all the CT-PA, 119 CT-PA (33.7%) were requested without D-dimer assay (n = 114) or with normal D-dimer level (n = 5) despite being in the “PE unlikely” group. Only 49 patients had negative PERC criteria, of which three patients had PE.ConclusionsThe study revealed that approximately one-third of all CT-PA requests were not adhering to the clinical decision rules with a significant underutilization of D-dimer assay in such patients. To reduce overutilization of imaging, planned interventions to promote the adherence to the current guidelines seem imperative.

Wells ve PERC skorlarının bir göğüs hastalıkları hastanesi acil servisinde pulmoner emboliyi dışlamada etkinliği

Aim: The Pulmonary Embolism Rule-out Criteria (PERC) rule is a diagnostic algorithm to exclude pulmonary embolism (PE). Even it is not widely used in routine practice, has better negative predictive value in low-risk populations among existed clinical assessment tests. We aimed to examine availability of PERC rules combined with Wells score in a pulmonary emergency ward.Material and Methods: A retrospective hospitalized database study was conducted with 163 patients. All patients who underwent radiological investigation due to suspicious for PE were included. We calculated prevalence of PE in group of PERC negative and PERC positive. All PERC parameters were evaluated solely for risk of PE.Results: PERC positivity was 82.4% in patients diagnosed with PE. There were no significant differences in terms of PERC positivity between PE+ and PE- groups (p=0.336). False positivity rate for moderate to high Wells score was 36.1%. Frequency of PERC negativity among PE negative patients was only %36.1 and %17.6 in PE positive group (p=0.75 and r=-0.025). The sensitivity of the PERC test was 82.3%, specificity 19.6%, PPV 63.1%, NPV 40%, false positivity rate 36.8% and false negativity rate 60%. Among patients with moderate to high wells, 61 patients were diagnosed PE and 14 of them were PERC negative.Conclusion: Our study suggests that PERC scoring system even combined with Wells score does not sufficient enough to prevent unnecessary irradiative imaging studies in a pulmonary emergency ward.