Delayed Diagnosis in Pulmonary Embolism: Frequency, Patient Characteristics, and Outcome

Accuracy of transthoracic lung ultrasound for diagnosing pulmonary embolism: An updated systematic review and meta-analysis

BACKGROUND

Computed tomography pulmonary angiography (CTPA) simplifies the diagnosis of pulmonary embolism (PE) but is not suitable for all patients. Transthoracic lung ultrasound (LUS) is a potential alternative; this meta-analysis evaluates its accuracy for diagnosing PE.

METHODS

We systematically searched PubMed, Embase and Cochrane Library from the inception of each database up to April 2024 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies guidelines. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool, and a bivariate random effects model was used to pool sensitivity and specificity.

RESULTS

A total of 18 studies with 2158 patients were analyzed. Lung ultrasound showed a sensitivity of 0.80 (95 %, confidence interval (CI): 0.71-0.86; I2 = 85.2 %) and specificity of 0.87 (95 %, CI: 0.81-0.92; I2 = 87.3 %). The diagnostic score was 3.27 (95 %, CI: 2.75-3.78; I2 = 61.9 %), and the diagnostic odds ratio was 26 (95 %, CI: 16-44; I2 = 100.0 %). The pooled positive likelihood ratio was 6.2 (95 %, CI: 4.2-9.1; I2 = 79.2 %), and the negative likelihood ratio was 0.24 (95 %, CI: 0.16-0.34; I2 = 83.7 %). The summary area under the curve was 0.91 (95 %, CI: 0.88-0.93). Significant heterogeneity was observed, which may impact the generalisability of the results, and no publication bias was detected.

CONCLUSION

Transthoracic LUS shows potential as an alternative to CTPA for PE diagnosis, but further research is needed to improve its accuracy and establish standardised diagnostic criteria. The observed heterogeneity highlights the need for a cautious interpretation of the results.

Characterizing Acute Pulmonary Embolism Cases Diagnosed at an Emergency Department Revisit Using a Statewide Clinical Registry

STUDY OBJECTIVE

To assess the rate and characteristics of acute pulmonary embolism (PE) cases diagnosed in the emergency department (ED) following an ED discharge visit within 10 days.

METHODS

This is a retrospective analysis of 40 EDs in a statewide clinical registry from 2017 to 2022. We identified adult patients with acute PEs diagnosed in the ED. We assessed PE cases wherein a prior ED visit for the same patient resulting in discharge had taken place within 10 days without interval hospitalization. We then characterized the overall rate of revisit PE cases per overall acute PE cases and per 10,000 ED discharges. We also reported on subgroups of revisit cases where the preceding visit resulted in diagnosis of COVID-19, other cardiopulmonary conditions, and cardiopulmonary symptom codes (eg, chest pain, unspecified).

RESULTS

Of 24,525 acute PEs, 1,202 (4.9%, 95% confidence interval [CI] 4.6% to 5.2%) had an ED discharge within the preceding 10 days (2.0 per 10,000 ED discharges, 95% CI 1.9 to 2.1). Two hundred thirty-three (19.4%) were originally discharged with a COVID-19 diagnosis, 107 (8.9%) were originally discharged with another cardiopulmonary condition, and 201 (16.7%) were cases discharged with a nonspecific cardiopulmonary symptom code. Discharges with diagnoses of COVID-19, pneumonia, and pleural effusion had higher rates of revisits with acute PE.

CONCLUSION

In this retrospective analysis, about 1 in 20 acute PEs and 2 in 10,000 ED discharges were associated with an ED revisit for acute PE. Some cases may represent potential diagnostic opportunities, whereas others may be progression of disease, risk factors for PE, or unrelated.

Risk of Venous Thromboembolism in Patients With Stage III and IV Non-Small-Cell Lung Cancer: Nationwide Descriptive Cohort Study

BACKGROUND

Venous thromboembolism (VTE) is a common complication in patients starting cancer therapies for non-small-cell lung cancer (NSCLC). We examined the risk and timing of VTE in patients with stage IIIA, IIIB to C, and stage IV NSCLC according to received cancer treatments.

MATERIALS AND METHODS

A nationwide registry-based cohort study of patients recorded in the Danish Lung Cancer Registry (2010-2021) followed for 1 year after entry into the registry to assess the incidence of VTE. The Aalen-Johansen estimator was used to calculate the risk of VTE after treatment commencement with chemotherapy, radiotherapy, chemoradiation, immunotherapy, and targeted therapy.

RESULTS

Among the 3475 patients with stage IIIA, 4047 with stage IIIB to C, and 18,082 patients with stage IV cancer, the 1-year risk of VTE was highest in the first 6 months and varied markedly by cancer stage and cancer treatment. In stage IIIA, VTE risk was highest with chemotherapy (3.9%) and chemoradiation (4.1%). In stage IIIB to C, risks increased with chemotherapy (5.2%), immunotherapy (9.4%), and targeted therapy (6.0%). Stage IV NSCLC showed high risk with targeted therapy (12.5%) and immunotherapy (12.2%). The risk was consistently higher for pulmonary embolism than deep vein thrombosis.

CONCLUSION

VTE risks vary substantially according to cancer treatments and cancer stages. The highest risk was observed in the initial 6 months of therapy initiation. These insights emphasize the need for tailored risk assessment and vigilance in managing VTE complications in patients with NSCLC. Further research is needed to optimize individual thromboprophylaxis strategies for patients with unresectable and metastatic NSCLC.

Emergency Ultrasound Unveils Intermediate-High Risk Saddle Pulmonary Embolism with Extensive Bilateral Clot Burden, Masquerading as Micturition Syncope: A Case Report

BACKGROUND

Isolated syncope as the manifestation of pulmonary embolism (PE) is a rare and diagnostically challenging presentation that often leads to delayed or missed diagnosis, increasing morbidity and mortality. In spite of emphasizing cardiovascular etiologies of syncope, current guidelines offer essentially no guidance in establishing a diagnostic workup for PE in these patients. By performing bedside echocardiography, emergency physicians can accurately identify concerning features suggestive of PE in patients with syncope.

CASE REPORT

A 78-year-old man, receiving ertapenem via a peripherally inserted central catheter for treatment of extended spectrum β-lactamase urinary tract infection, presented to the emergency department for isolated syncope with collapse while urinating. Arriving asymptomatic with normal vital signs and a benign physical examination, a presumptive diagnosis of micturition syncope was made. However, subtle vital sign changes on reassessment prompted performance of a point-of-care echocardiogram, which revealed signs of right heart strain. A computed tomography angiogram confirmed a saddle PE with extensive bilateral clot burden. Catheter-directed thrombectomy was performed via interventional radiology, with successful removal of pulmonary emboli. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: Pulmonary embolism presenting as isolated syncope represents a daunting diagnostic dilemma, as emergency physicians may not consider it, or anchor on more benign etiologies of syncope. Although lacking sufficient sensitivity to rule out PE, point-of-care echocardiography to evaluate for signs of right heart strain can quickly and effectively point toward the diagnosis, while also assessing for other emergent cardiovascular causes of syncope. Given the lack of evidence-based guidance concerning PE presenting as syncope, bedside echocardiography should be highly considered as a part of the emergency physician's diagnostic workup, especially in patients with abnormal vital signs.

[Interventional therapy of pulmonary embolism - update]

Several catheter-based systems have been developed for interventional recanalization of pulmonary embolism. These include local ultrasound assisted thrombolysis (EKOS), in-toto-thrombectomy via retriever and aspiration system (FlowTriever) and the Indigo mechanical aspiration system. Safety and efficacy in the removal of thrombus have been demonstrated for all systems. Interventional recanalization strategies for high- and intermediate-high risk pulmonary embolism are potentially more effective in the removal of thrombus and restoration of right heart function than systemic thrombolysis with a lower risk of major bleeding complications. Preliminary data from registries and observational studies are very promising whereas the evidence for systemic thrombolysis treatment in high and intermediate-high risk pulmonary embolism is low. Randomized controlled clinical trials are currently performed comparing catheter based interventional therapies to systemic thrombolysis for the treatment of intermediate-high risk pulmonary embolisms. Primary outcome measurements include mortality, hemodynamic collapse, and major bleedings. Results are expected in 2025. The introduction of interventional therapies for pulmonary embolism was accompanied by an increased awareness of the complexity of pulmonary embolism management. The need for specialized interdisciplinary pulmonary embolism response teams (PERT-teams) and a well-structured approach including a PDCA cycle was recognized.

From pixels to prognosis: Imaging biomarkers for discrimination and outcome prediction of pulmonary embolism : Original Research Article

PURPOSE

Recent advancements in medical imaging have transformed diagnostic assessments, offering exciting possibilities for extracting biomarker-based information. This study aims to investigate the capabilities of a machine learning classifier that incorporates dual-energy computed tomography (DECT) radiomics. The primary focus is on discerning and predicting outcomes related to pulmonary embolism (PE).

METHODS

The study included 131 participants who underwent pulmonary artery DECT angiography between January 2015 and March 2022. Among them, 104 patients received the final diagnosis of PE and 27 patients served as a control group. A total of 107 radiomic features were extracted for every case based on DECT imaging. The dataset was divided into training and test sets for model development and validation. Stepwise feature reduction identified the most relevant features, which were used to train a gradient-boosted tree model. Receiver operating characteristics analysis and Cox regression tests assessed the association of texture features with overall survival.

RESULTS

The trained machine learning classifier achieved a classification accuracy of 0.94 for identifying patients with acute PE with an area under the receiver operating characteristic curve of 0.91. Radiomics features could be valuable for predicting outcomes in patients with PE, demonstrating strong prognostic capabilities in survival prediction (c-index, 0.991 [0.979-1.00], p = 0.0001) with a median follow-up of 130 days (IQR, 38-720). Notably, the inclusion of clinical or DECT parameters did not enhance predictive performance.

CONCLUSION

In conclusion, our study underscores the promising potential of leveraging radiomics on DECT imaging for the identification of patients with acute PE and predicting their outcomes. This approach has the potential to improve clinical decision-making and patient management, offering efficiencies in time and resources by utilizing existing DECT imaging without the need for an additional scoring system.

The potential of virtual triage AI to improve early detection, care acuity alignment, and emergent care referral of life-threatening conditions

Objective

To evaluate the extent to which patient-users reporting symptoms of five severe/acute conditions requiring emergency care to an AI-based virtual triage (VT) engine had no intention to get such care, and whose acuity perception was misaligned or decoupled from actual risk of life-threatening symptoms.

Methods

A dataset of 3,022,882 VT interviews conducted over 16 months was evaluated to quantify and describe patient-users reporting symptoms of five potentially life-threatening conditions whose pre-triage healthcare intention was other than seeking urgent care, including myocardial infarction, stroke, asthma exacerbation, pneumonia, and pulmonary embolism.

Results

Healthcare intent data was obtained for 12,101 VT patient-user interviews. Across all five conditions a weighted mean of 38.5% of individuals whose VT indicated a condition requiring emergency care had no pre-triage intent to consult a physician. Furthermore, 61.5% intending to possibly consult a physician had no intent to seek emergency medical care. After adjustment for 13% VT safety over-triage/referral to ED, a weighted mean of 33.5% of patient-users had no intent to seek professional care, and 53.5% had no intent to seek emergency care.

Conclusion

AI-based VT may offer a vehicle for early detection and care acuity alignment of severe evolving pathology by engaging patients who believe their symptoms are not serious, and for accelerating care referral and delivery for life-threatening conditions where patient misunderstanding of risk, or indecision, causes care delay. A next step will be clinical confirmation that when decoupling of patient care intent from emergent care need occurs, VT can influence patient behavior to accelerate care engagement and/or emergency care dispatch and treatment to improve clinical outcomes.

Imaging-based risk stratification of patients with pulmonary embolism based on dual-energy CT-derived radiomics

BACKGROUND

Technological progress in the acquisition of medical images and the extraction of underlying quantitative imaging data has introduced exciting prospects for the diagnostic assessment of a wide range of conditions. This study aims to investigate the diagnostic utility of a machine learning classifier based on dual-energy computed tomography (DECT) radiomics for classifying pulmonary embolism (PE) severity and assessing the risk for early death.

METHODS

Patients who underwent CT pulmonary angiogram (CTPA) between January 2015 and March 2022 were considered for inclusion in this study. Based on DECT imaging, 107 radiomic features were extracted for each patient using standardized image processing. After dividing the dataset into training and test sets, stepwise feature reduction based on reproducibility, variable importance and correlation analyses were performed to select the most relevant features; these were used to train and validate the gradient-boosted tree models.

RESULTS

The trained machine learning classifier achieved a classification accuracy of .90 for identifying high-risk PE patients with an area under the receiver operating characteristic curve of .59. This CT-based radiomics signature showed good diagnostic accuracy for risk stratification in individuals presenting with central PE, particularly within higher risk groups.

CONCLUSION

Models utilizing DECT-derived radiomics features can accurately stratify patients with pulmonary embolism into established clinical risk scores. This approach holds the potential to enhance patient management and optimize patient flow by assisting in the clinical decision-making process. It also offers the advantage of saving time and resources by leveraging existing imaging to eliminate the necessity for manual clinical scoring.

Radiologist Worklist Reprioritization Using Artificial Intelligence: Impact on Report Turnaround Times for CTPA Examinations Positive for Acute Pulmonary Embolism

BACKGROUND. In patients with acute pulmonary embolism (PE), timely intervention (e.g., initiation of anticoagulation) is critical for optimizing clinical outcomes. OBJECTIVE. The purpose of this study was to evaluate the effect of artificial intelligence (AI)-based radiologist worklist reprioritization on report turnaround times for pulmonary CTA (CTPA) examinations positive for acute PE. METHODS. This retrospective single-center study included patients who underwent CTPA before (October 1, 2018-March 31, 2019 [pre-AI period]) and after (October 1, 2019-March 31, 2020 [post-AI period]) implementation of an AI tool that reprioritized CTPA examinations to the top of radiologists' reading worklists if acute PE was detected. EMR and dictation system timestamps were used to determine the wait time (time from examination completion to report initiation), read time (time from report initiation to report availability), and report turnaround time (sum of wait and read times) for the examinations. Times for reports positive for PE, with final radiology reports as reference, were compared between periods. RESULTS. The study included 2501 examinations of 2197 patients (1307 women, 890 men; mean age, 57.4 ± 17.0 [SD] years), including 1335 examinations from the pre-AI period and 1166 from the post-AI period. The frequency of acute PE, based on radiology reports, was 15.1% (201/1335) during the pre-AI period and 12.3% (144/1166) during the post-AI period. During the post-AI period, the AI tool reprioritized 12.7% (148/1166) of examinations. For PE-positive examinations, the post-AI period, compared with the pre-AI period, had significantly shorter mean report turnaround time (47.6 vs 59.9 minutes; mean difference, 12.3 minutes [95% CI, 0.6-26.0 minutes]) and mean wait time (21.4 vs 33.4 minutes; mean difference, 12.0 minutes [95% CI, 0.9-25.3 minutes]) but no significant difference in mean read time (26.3 vs 26.5 minutes; mean difference, 0.2 minutes [95% CI, -2.8 to 3.2 minutes]). During regular operational hours, wait time was significantly shorter in the post-AI than in the pre-AI period for routine-priority examinations (15.3 vs 43.7 minutes; mean difference, 28.4 minutes [95% CI, 2.2-64.7 minutes]) but not for stat- or urgent-priority examinations. CONCLUSION. AI-driven worklist reprioritization yielded reductions in report turnaround time and wait time for PE-positive CTPA examinations. CLINICAL IMPACT. By assisting radiologists in providing rapid diagnoses, the AI tool has potential for enabling earlier interventions for acute PE.

Augmentation of the RSNA Pulmonary Embolism CT Dataset with Bounding Box Annotations and Anatomic Localization of Pulmonary Emboli

Supplemental material is available for this article. Keywords: CT, Pulmonary Arteries, Embolism/Thrombosis, Feature Detection © RSNA, 2023.

Gadolinium Enhances Dual-energy Computed Tomography Scan of Pulmonary Artery

OBJECTIVE

To evaluate the feasibility of using gadopentetate dimeglumine (Gd-DTPA) for dual-energy computed tomography pulmonary angiography (CTPA).

METHODS

Sixty-six patients were randomly divided into three groups and underwent CTPA. Group A had a turbo flash scan using an iohexol injection, Group B had a turbo flash scan using Gd-DTPA, and Group C had a dual-energy scan using Gd-DTPA. The original images of Group C were linearly blended with a blending factor of 0.5 or reconstructed at 40, 50, 60, 70, 80, 90, 100, and 110 keV, respectively. The groups were compared in terms of pulmonary artery CT value, image quality, and radiation dose.

RESULTS

The pulmonary artery CT values were significantly higher in Group C_40keV than in Groups B and C, but lower than in Group A. There was no significant difference in the image noise of Groups C_40keV, B, and C. Moreover, Group A had the largest beam hardening artifacts of the superior vena cava (SVC), followed by Groups B and C. Group C_40keV showed better vascular branching than the other three groups, among which Group B was superior to Group A. The subjective score of the image quality of Groups A, B, and C showed no significant difference, but the score was significantly higher in Group C_40keV than in Groups A and B. The radiation dose was significantly lower in Group B than in Groups A and C.

CONCLUSION

Gd-CTPA is recommended to patients who are unsuitable for receiving an iodine-based CTPA. Furthermore, a turbo flash scan could surpass a dual-energy scan without consideration for virtual monoenergetic imaging.

Clinical Characteristics, Risk Factors, and Outcomes of Acute Pulmonary Embolism in Asian Population

BACKGROUND

Acute pulmonary embolism (APE) is a common condition with increasing worldwide incidence. However, the clinical characteristics, risk factors, and clinical outcomes of APE in the Asian population especially in the Thai population are still limited. Therefore, the objective of this study was to identify the clinical characteristics, risk factors, and clinical outcomes of APE in the Asian population.

METHODS

A cross-sectional study was conducted on patients diagnosed with APE at Chiang Mai University Hospital, Thailand during 2011-2020.

RESULTS

During the study period, 696 patients confirmed the diagnosis of APE with a mean age of 57.7 ± 15.7 years and 41.1% males. APE was suspected in 468 of 696 patients (67.2%), while 228 patients (32.8%) had incidental PE. Active malignancy during treatment was found in 388 (55.7%). Dyspnea, cough, and chest pain were the most common presenting symptoms. Respiratory failure was found in 129 patients (18.6%). The thirty-day all-cause mortality rate was 19.1%. PE-related mortality was 5.6%. Most PE-related mortality was high-risk PE.

CONCLUSION

APE was not uncommon in the Asian population. Active cancer, especially lung cancer was the most common risk factors. High-risk and intermediate-high-risk PE were associated with high mortality. Risk stratification and prompt management are warranted to improve outcomes.

Tricuspid Annular Plane Systolic Excursion (TAPSE) Measurement by Emergency Medicine Residents in Patients Suspected of Pulmonary Emboli

OBJECTIVES

We aimed to evaluate the ability of emergency medicine (EM) residents to measure tricuspid annular plane systolic excursion (TAPSE) by M-Mode ultrasound.

METHODS

Four EM residents with prior focused cardiac ultrasound (FOCUS) experience participated in 10 hours of hands-on training and then performed TAPSE measurements in adult patients at high risk of having pulmonary emboli (PE) between December 2020 and April 2021. Patients underwent bedside echocardiography by cardiology residents, and a CT pulmonary angiogram (CTPA) was performed to confirm the diagnosis. The agreement between EM and cardiology residents was assessed by intraclass correlation coefficient (ICC).

RESULTS

Sixty-six patients were included (mean age = 58.7 ± 16.7 years), of which 28 patients (42.8%) had positive CTPA. The mean TAPSE, measured by EM residents was 16.36 ± 1.59 mm in the PE positive group and 21.68 ± 2.87 mm in the PE negative group (P-value = <.0001). The mean ± SD TAPSE, measured by cardiology residents, was 17.7 ± 1.98 mm in the PE group and 22.5 ± 3.6 mm in the PE negative group (P-value = <.0001). There was significant agreement between EM and cardiology residents in terms of measuring TAPSE (ICC = 0.91, 95% confidence interval [CI] = 0.80-0.95). The receiver operating characteristic (ROC) curves of TAPSE for diagnosing PE revealed that TAPSE, measured by EM residents, had a high level of accuracy (area under the ROC curve [AUC] = 0.93, 95% CI, 0.878-0.99).

CONCLUSIONS

EM residents can perform M-Mode TAPSE measurement in suspected PE cases after 10 hours of hands-on training. TAPSE measurement should be added to routine FOCUS protocols, especially when there is suspicion of PE.

Performance of Prehospital Use of Chest Pain Risk Stratification Tools: The RESCUE Study

BACKGROUND

Emergency medical services (EMS) assesses millions of patients with chest pain each year. However, tools validated to risk stratify patients for acute coronary syndrome (ACS) and pulmonary embolism (PE) have not been translated to the prehospital setting. The objective of this study is to assess the prehospital performance of risk stratification scores for 30-day major adverse cardiac events (MACE) and PE.

METHODS

A prospective observational cohort study of patients ≥21 years of age with acute chest pain who were transported by EMS in two North Carolina (NC) counties was conducted from 18 April 2018-2 January 2019. In this convenience sample, paramedics completed HEAR (history, electrocardiogram, age, risk factor), ED Assessment of Chest Pain Score (EDACS), Revised Geneva Score (RGS), and pulmonary embolism rule-out criteria (PERC) assessments on each patient. MACE (all-cause death, myocardial infarction, and revascularization) and PE at 30 days were determined by hospital records and NC Death Index. The positive (+LR) and negative likelihood ratios (-LR) of the risk scores for 30-day MACE and PE were calculated.

RESULTS

During the study period, 82.1% (687/837) patients had all four risk score assessments. The cohort was 51.1% (351/687) female, 49.5% (340/687) African American, and had a mean age of 55.0 years (SD 16.0). At 30 days, MACE occurred in 7.4% (51/687), PE occurred in 0.9% (6/687), and the combined outcome occurred in 8.2% (56/687). The HEAR score had a - LR of 0.46 (95% CI 0.27-0.78) and + LR of 1.48 (95% CI 1.26-1.74) for 30-day MACE. EDACS had a - LR of 0.61 (95% CI 0.46-0.81) and + LR of 2.53 (95% CI 1.86-3.46) for 30-day MACE. The PERC score had a - LR of 0 (95% CI 0.0-1.4) and a + LR of 1.38 (95% CI 1.32-1.45) for 30-day PE. The RGS score had a - LR of 0 (95% CI 0.0-0.65) and a + LR of 2.36 (95% CI 2.16-2.57) for 30-day PE. The combination of a low-risk HEAR score and negative PERC evaluation had a - LR of 0.25 (95% CI 0.08-0.76) and a + LR of 1.21 (95% CI 1.21-1.30) for 30-day MACE or PE.

CONCLUSION

The combination of a paramedic-obtained HEAR score and PERC evaluation performed best to exclude 30-day MACE and PE but was not sufficient for directing prehospital decision making.

Deep learning-based automated detection of pulmonary embolism on CT pulmonary angiograms: No significant effects on report communication times and patient turnaround in the emergency department nine months after technical implementation

OBJECTIVES

Rapid communication of CT exams positive for pulmonary embolism (PE) is crucial for timely initiation of anticoagulation and patient outcome. It is unknown if deep learning automated detection of PE on CT Pulmonary Angiograms (CTPA) in combination with worklist prioritization and an electronic notification system (ENS) can improve communication times and patient turnaround in the Emergency Department (ED).

METHODS

In 01/2019, an ENS allowing direct communication between radiology and ED was installed. Starting in 10/2019, CTPAs were processed by a deep learning (DL)-powered algorithm for detection of PE. CTPAs acquired between 04/2018 and 06/2020 (n = 1808) were analysed. To assess the impact of the ENS and the DL-algorithm, radiology report reading times (RRT), radiology report communication time (RCT), time to anticoagulation (TTA), and patient turnaround times (TAT) in the ED were compared for three consecutive time periods. Performance measures of the algorithm were calculated on a per exam level (sensitivity, specificity, PPV, NPV, F1-score), with written reports and exam review as ground truth.

RESULTS

Sensitivity of the algorithm was 79.6 % (95 %CI:70.8-87.2%), specificity 95.0 % (95 %CI:92.0-97.1%), PPV 82.2 % (95 %CI:73.9-88.3), and NPV 94.1 % (95 %CI:91.4-96 %). There was no statistically significant reduction of any of the observed times (RRT, RCT, TTA, TAT).

CONCLUSION

DL-assisted detection of PE in CTPAs and ENS-assisted communication of results to referring physicians technically work. However, the mere clinical introduction of these tools, even if they exhibit a good performance, is not sufficient to achieve significant effects on clinical performance measures.

Nontraumatic Headache in Adult Emergency Patients: Prevalence, Etiologies, and Radiological Findings

The aim of this study was to measure prevalence, to describe underlying etiologies, and to assess radiological findings, focusing on significant intracranial abnormality (sICA). This was a prospective study of unselected adult patients admitted to the emergency department (ED) in a tertiary care hospital where all presenters were systematically interviewed about their symptoms. We attributed nontraumatic headache with neuroimaging to four groups: Normal or no new finding, extracranial abnormality, insignificant intracranial abnormality, or significant intracranial abnormality. sICA was defined as “needing acute therapy”, “needing follow-up neuroimaging”, or “clinically important neurological disorder”. Among 11,269 screened ED presentations, the prevalence of nontraumatic headache was 10.1% (1132 patients). Neuroimaging (cCT and/or cMRI) was performed in 303 patients. Seventy (23.1% of scanned; 6.2% of all headache patients) patients had sICA. Etiologies were cerebrovascular disease (56%), intracranial bleeding (17%), tumors (14%), infection (9%), and others (6%). Short-term outcome was excellent, with 99.3% in-hospital survival in patients with and 99.4% in patients without neuroimaging, and 97.1% in sICA; 1-year survival in outpatients with neuroimaging was 99.2%, 99.0% in outpatients without, and 88.6% in patients with sICA. Factors associated with sICA were age, emergency severity index (ESI) of 1 or 2, Glasgow coma score (GCS) under 14, focal neurological signs, and a history of malignancy. Prevalence of headache and incidence of sICA were high, but survival after work-up for nontraumatic headache was excellent in the 94% patients without sICA. Due to the incidence of sICA, extensive indication for neuroimaging in headache patients is further warranted, particularly in patients with risk factors.