Comparing predictive performance of pulmonary embolism risk stratification tools for acute clinical deterioration.

Objectives: Existing pulmonary embolism (PE) risk scores were developed to predict death within weeks, but not more proximate adverse events. We determined the ability of 3 PE risk stratification tools (simplified pulmonary embolism severity index [sPESI], 2019 European Society of Cardiology guidelines [ESC], and PE short-term clinical outcomes risk estimation [PE-SCORE]) to predict 5-day clinical deterioration after emergency department (ED) diagnosis of PE. Methods: We analyzed data from six EDs on ED patients with confirmed PE. Clinical deterioration was defined as death, respiratory failure, cardiac arrest, new dysrhythmia, sustained hypotension requiring vasopressors or volume resuscitation, or escalated intervention within 5 days of PE diagnosis. We determined sensitivity and specificity of sPESI, ESC, and PE-SCORE for predicting clinical deterioration. Results: Of 1569 patients, 24.5% had clinical deterioration within 5 days. sPESI, ESC, and PE-SCORE classifications were low-risk in 558 (35.6%), 167 (10.6%), and 309 (19.6%), respectively. Sensitivities of sPESI, ESC, and PE-SCORE for clinical deterioration were 81.8 (78, 85.7), 98.7 (97.6, 99.8), and 96.1 (94.2, 98), respectively. Specificities of sPESI, ESC, and PE-SCORE for clinical deterioration were 41.2 (38.4, 44), 13.7 (11.7, 15.6), and 24.8 (22.4, 27.3). Areas under the curve were 61.5 (59.1, 63.9), 56.2 (55.1, 57.3), and 60.5 (58.9, 62.0). Negative predictive values were 87.5 (84.7, 90.2), 97 (94.4, 99.6), and 95.1 (92.7, 97.5). Conclusions: ESC and PE-SCORE were better than sPESI for detecting clinical deterioration within 5 days after PE diagnosis.

Quality of life 1 month after acute pulmonary embolism in emergency department patients.

OBJECTIVE: The Pulmonary Embolism Quality-of-Life (PEmb-QoL) questionnaire assesses quality of life (QoL) after pulmonary embolism (PE). We aimed to determine whether any clinical or pathophysiologic features of PE were associated with worse PEmb-QoL scores 1 month after PE. METHODS: In this prospective multicenter registry, we conducted PEmb-QoL questionnaires. We determined differences in QoL domain scores for four primary variables: clinical deterioration (death, cardiac arrest, respiratory failure, hypotension requiring fluid bolus, catecholamine support, or new dysrhythmia), right ventricular dysfunction (RVD), PE risk stratification, and subsequent rehospitalization. For overall QoL score, we fit a multivariable regression model that included these four primary variables as independent variables. RESULTS: Of 788 PE patients participating in QoL assessments, 156 (19.8%) had a clinical deterioration event, 236 (30.7%) had RVD of which 38 (16.1%) had escalated interventions. For those without and with clinical deterioration, social limitations had mean (±SD) scores of 2.07 (±1.27) and 2.36 (±1.47), respectively (p = 0.027). For intensity of complaints, mean (±SD) scores for patients without RVD (4.32 ± 2.69) were significantly higher than for those with RVD with or without reperfusion interventions (3.82 ± 1.81 and 3.83 ± 2.11, respectively; p = 0.043). There were no domain score differences between PE risk stratification groups. All domain scores were worse for patients with rehospitalization versus without. By multivariable analysis, worse total PEmb-QoL scores with effect sizes were subsequent rehospitalization 11.29 (6.68-15.89), chronic obstructive pulmonary disease (COPD) 8.17 (3.91-12.43), and longer index hospital length of stay 0.06 (0.03-0.08). CONCLUSIONS: Acute clinical deterioration, RVD, and PE severity were not predictors of QoL at 1 month post-PE. Independent predictors of worsened QoL were rehospitalization, COPD, and index hospital length of stay.

Electrocardiographic findings associated with early clinical deterioration in acute pulmonary embolism.

OBJECTIVES: We sought to determine associations of early electrocardiogram (ECG) patterns with clinical deterioration (CD) within 5 days and with RV abnormality (abnlRV) by echocardiography in pulmonary embolism (PE). METHODS: In this prospective, multicenter study of newly confirmed PE patients, early echocardiography and initial ECG were examined. Initial ECG patterns included lead-specific ST-segment elevation (STE) or depression (STD), T-wave inversion (TWI), supraventricular tachycardia (SVT), sinus tachycardia, and right bundle branch block as complete (cRBBB) or incomplete (iRBBB). We defined CD as respiratory failure, hypotension, dysrhythmia, cardiac arrest, escalated PE intervention, or death within 5 days. We calculated odds ratios (ORs) for CD and abnlRV with univariate and full multivariate models in the presence of other variables. RESULTS: Of 1676 patients, 1629 (97.2%) had both ECG and GDE; 415/1676 (24.7%) had CD, and 529/1629 (32.4%) had abnlRV. AbnlRV had an OR for CD of 4.25 (3.35, 5.38). By univariable analysis, the absence of abnormal ECG patterns had OR for CD and abnlRV of 0.34 (0.26, 0.44; p < 0.001) and 0.24 (0.18, 0.31; p < 0.001), respectively. By multivariable analyses, one ECG pattern had a significant OR for CD: SVT 2.87 (1.66, 5.00). Significant ORS for abnlRV were: TWI V2-4 4.0 (2.64, 6.12), iRBBB 2.63 (1.59, 4.38), STE aVR 2.42 (1.58, 3.74), S1-Q3-T3 2.42 (1.70, 3.47), and sinus tachycardia 1.68 (1.14, 2.49). CONCLUSIONS: SVT was an independent predictor of CD. TWI V2-4 , iRBBB, STE aVR, sinus tachycardia, and S1-Q3-T3 were independent predictors of abnlRV. Finding one or more of these ECG patterns may increase considerations for performance of echocardiography to look for RV abnormalities and, if present, inform concerns for early clinical deterioration.

Evaluation of Glial and Neuronal Blood Biomarkers Compared With Clinical Decision Rules in Assessing the Need for Computed Tomography in Patients With Mild Traumatic Brain Injury.

Importance: In 2018, the combination of glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase (UCH-L1) levels became the first US Food and Drug Administration-approved blood test to detect intracranial lesions after mild to moderate traumatic brain injury (MTBI). How this blood test compares with validated clinical decision rules remains unknown. Objectives: To compare the performance of GFAP and UCH-L1 levels vs 3 validated clinical decision rules for detecting traumatic intracranial lesions on computed tomography (CT) in patients with MTBI and to evaluate combining biomarkers with clinical decision rules. Design, Setting, and Participants: This prospective cohort study from a level I trauma center enrolled adults with suspected MTBI presenting within 4 hours of injury. The clinical decision rules included the Canadian CT Head Rule (CCHR), New Orleans Criteria (NOC), and National Emergency X-Radiography Utilization Study II (NEXUS II) criteria. Emergency physicians prospectively completed data forms for each clinical decision rule before the patients' CT scans. Blood samples for measuring GFAP and UCH-L1 levels were drawn, but laboratory personnel were blinded to clinical results. Of 2274 potential patients screened, 697 met eligibility criteria, 320 declined to participate, and 377 were enrolled. Data were collected from March 16, 2010, to March 5, 2014, and analyzed on August 11, 2021. Main Outcomes and Measures: The presence of acute traumatic intracranial lesions on head CT scan (positive CT finding). Results: Among enrolled patients, 349 (93%) had a CT scan performed and were included in the analysis. The mean (SD) age was 40 (16) years; 230 patients (66%) were men, 314 (90%) had a Glasgow Coma Scale score of 15, and 23 (7%) had positive CT findings. For the CCHR, sensitivity was 100% (95% CI, 82%-100%), specificity was 33% (95% CI, 28%-39%), and negative predictive value (NPV) was 100% (95% CI, 96%-100%). For the NOC, sensitivity was 100% (95% CI, 82%-100%), specificity was 16% (95% CI, 12%-20%), and NPV was 100% (95% CI, 91%-100%). For NEXUS II, sensitivity was 83% (95% CI, 60%-94%), specificity was 52% (95% CI, 47%-58%), and NPV was 98% (95% CI, 94%-99%). For GFAP and UCH-L1 levels combined with cutoffs at 67 and 189 pg/mL, respectively, sensitivity was 100% (95% CI, 82%-100%), specificity was 25% (95% CI, 20%-30%), and NPV was 100%; with cutoffs at 30 and 327 pg/mL, respectively, sensitivity was 91% (95% CI, 70%-98%), specificity was 20% (95% CI, 16%-24%), and NPV was 97%. The area under the receiver operating characteristic curve (AUROC) for GFAP alone was 0.83; for GFAP plus NEXUS II, 0.83; for GFAP plus NOC, 0.85; and for GFAP plus CCHR, 0.88. The AUROC for UCH-L1 alone was 0.72; for UCH-L1 plus NEXUS II, 0.77; for UCH-L1 plus NOC, 0.77; and for UCH-L1 plus CCHR, 0.79. The GFAP biomarker alone (without UCH-L1) contributed the most improvement to the clinical decision rules. Conclusions and Relevance: In this cohort study, the CCHR, the NOC, and GFAP plus UCH-L1 biomarkers had equally high sensitivities, and the CCHR had the highest specificity. However, using different cutoff values reduced both sensitivity and specificity of GFAP plus UCH-L1. Use of GFAP significantly improved the performance of the clinical decision rules, independently of UCH-L1. Together, the CCHR and GFAP had the highest diagnostic performance.

Can right ventricular assessments improve triaging of low risk pulmonary embolism?

OBJECTIVES: Identifying right ventricle (RV) abnormalities is important to stratifying pulmonary embolism (PE) severity. Disposition decisions are influenced by concerns about early deterioration. Triaging strategies, like the Simplified Pulmonary Embolism Severity Index (sPESI), do not include RV assessments as predictors or early deterioration as outcome(s). We aimed to (1) determine if RV assessment variables add prognostic accuracy for 5-day clinical deterioration in patients classified low risk by sPESI, and (2) determine the prognostic importance of RV assessments compared to other variables and to each other. METHODS: We identified low risk sPESI patients (sPESI = 0) from a prospective PE registry. From a large field of candidate variables, we developed, and compared prognostic accuracy of, full and reduced random forest models (with and without RV assessment variables, respectively) on a validation database. We reported variable importance plots from full random forest and provided odds ratios for statistical inference of importance from multivariable logistic regression. Outcomes were death, cardiac arrest, hypotension, dysrhythmia, or respiratory failure within 5 days of PE. RESULTS: Of 1736 patients, 610 (35.1%) were low risk by sPESI and 72 (11.8%) experienced early deterioration. Of the 610, RV abnormality was present in 157 (25.7%) by CT, 121 (19.8%) by echocardiography, 132 (21.6%) by natriuretic peptide, and 107 (17.5%) by troponin. For deterioration, the receiver operating characteristics for full and reduced random forest prognostic models were 0.80 (0.77-0.82) and 0.71 (0.68-0.73), respectively. RV assessments were the top four in the variable importance plot for the random forest model. Echocardiography and CT significantly increased predicted probability of 5-day clinical deterioration by the multivariable logistic regression. CONCLUSIONS: A PE triaging strategy with RV imaging assessments had superior prognostic performance at classifying low risk for 5-day clinical deterioration versus one without.

Development and validation of a prognostic tool: Pulmonary embolism short-term clinical outcomes risk estimation (PE-SCORE).

OBJECTIVE: Develop and validate a prognostic model for clinical deterioration or death within days of pulmonary embolism (PE) diagnosis using point-of-care criteria. METHODS: We used prospective registry data from six emergency departments. The primary composite outcome was death or deterioration (respiratory failure, cardiac arrest, new dysrhythmia, sustained hypotension, and rescue reperfusion intervention) within 5 days. Candidate predictors included laboratory and imaging right ventricle (RV) assessments. The prognostic model was developed from 935 PE patients. Univariable analysis of 138 candidate variables was followed by penalized and standard logistic regression on 26 retained variables, and then tested with a validation database (N = 801). RESULTS: Logistic regression yielded a nine-variable model, then simplified to a nine-point tool (PE-SCORE): one point each for abnormal RV by echocardiography, abnormal RV by computed tomography, systolic blood pressure < 100 mmHg, dysrhythmia, suspected/confirmed systemic infection, syncope, medico-social admission reason, abnormal heart rate, and two points for creatinine greater than 2.0 mg/dL. In the development database, 22.4% had the primary outcome. Prognostic accuracy of logistic regression model versus PE-SCORE model: 0.83 (0.80, 0.86) vs. 0.78 (0.75, 0.82) using area under the curve (AUC) and 0.61 (0.57, 0.64) vs. 0.50 (0.39, 0.60) using precision-recall curve (AUCpr). In the validation database, 26.6% had the primary outcome. PE-SCORE had AUC 0.77 (0.73, 0.81) and AUCpr 0.63 (0.43, 0.81). As points increased, outcome proportions increased: a score of zero had 2% outcome, whereas scores of six and above had ≥ 69.6% outcomes. In the validation dataset, PE-SCORE zero had 8% outcome [no deaths], whereas all patients with PE-SCORE of six and above had the primary outcome. CONCLUSIONS: PE-SCORE model identifies PE patients at low- and high-risk for deterioration and may help guide decisions about early outpatient management versus need for hospital-based monitoring.