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

Mansella, Gregory; Keil, C.; Nickel, Christian H.; Eken, Ceylan; Wirth, Christian; Tzankov, Alexandar; Peterson, Caspar J.; Aujesky, Drahomir; Bingisser, Roland

doi:10.1159/000508396

Cited by 15 publications

(7 citation statements)

References 35 publications

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“…On the other hand, the high overall incidence of sICA in our patients showed that the selection of patients to undergo neuroimaging was adequate. In a comparably difficult situation, pulmonary embolism (PE) rule-out, the incidence of significant findings in CT pulmonary angiography in our ED was also over 15%, indicating a generally conservative indication of CT [49] in our ED. The comparison between such diverse entities is interesting from the point of view of the hit-to-miss ratio in potentially lethal situations.…”

Section: Discussionmentioning

confidence: 67%

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

Handschin

Oppliger

Psychogios

et al. 2020

JCM

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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.

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Section: Discussionmentioning

confidence: 67%

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

Handschin

Oppliger

Psychogios

et al. 2020

JCM

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“…The increasing availability of newer imaging modalities is likely to improve the diagnosis. Despite the advance in diagnostic methods, delays in APE diagnosis are still common [ 11 ] and affect the worse clinical outcomes [ 12 ]. A high index of clinical suspicion, appropriate diagnostic investigations and clinical severity assessment, and appropriate therapy are crucial for the management of APE.…”

Section: Introductionmentioning

confidence: 99%

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

Bumroongkit

Deesomchok

Liwsrisakun

et al. 2022

JCM

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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.

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“…Therefore, fast diagnosis and report communication is becoming a major challenge in the field of radiology [4]. CT pulmonary angiograms (CTPAs) with the clinical question of pulmonary embolism (PE) are positive in only around 10-20 % [4,5]. Rapid anticoagulation is critical in this potentially life-threatening condition [6,7].…”

Section: Introductionmentioning

confidence: 99%

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

Schmuelling

Franzeck

Nickel

et al. 2021

European Journal of Radiology

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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, F1score), 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.

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

Cited by 15 publications

References 35 publications

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

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

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

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

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