{"doi":"10.1016/j.afjem.2023.02.003","title":"Comparative study of National Emergency X-Radiography Utilization Study (NEXUS) chest algorithm and extended focused assessment with sonography for trauma (E-FAST) in the early detection of blunt chest injuries in polytrauma patients","abstract":"Introduction: [1] A reliable, economic, bedside, and rapidly accomplished screening test can be pivotal. [2]. Objective: The aim of this study was to compare the accuracy of extended- focused assessment with sonography for trauma (E-FAST) to that of the National Emergency X-Radiography Utilisation Study (NEXUS) chest algorithm in detecting blunt chest injuries. Methods: This descriptive cross-sectional study included 50 polytrauma patients with blunt chest trauma from the emergency centre of Suez Canal University Hospital. E-FAST and computed tomography (CT) were conducted, followed by reporting of NEXUS criteria for all patients. Blinding of the E-FAST performer and CT reporter were confirmed. The results of both the NEXUS algorithm and E-FAST were compared with CT chest results. Results: The NEXUS algorithm had 100% sensitivity and 15.3% specificity, and E-FAST had 70% sensitivity and 96.7% specificity, in the detection of pneumothorax.In the detection of hemothorax, the sensitivity and specificity of the NEXUS algorithm were 90% and 7.5%, respectively, whereas E-FAST had a lower sensitivity of 80% and a higher specificity of 97.5%. Conclusion: E-FAST is highly specific for the detection of hemothorax, pneumothorax, and chest injuries compared with the NEXUS chest algorithm, which demonstrated the lowest specificity. However, the NEXUS chest algorithm showed a higher sensitivity than E-FAST and hence can be used effectively to rule out thoracic injury.","journal":"African Journal of Emergency Medicine","year":2023,"id":360339,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9505,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1112190,"name":"Nashwa M. Abd Elgeleel","orcid":null,"position":1,"is_corresponding":false},{"id":586154,"name":"Hazem M. El-Hariri","orcid":"0000-0001-9886-2087","position":2,"is_corresponding":false},{"id":1112191,"name":"Gouda El-labban","orcid":null,"position":3,"is_corresponding":false},{"id":765875,"name":"Maged El‐Setouhy","orcid":"0000-0002-4572-8439","position":4,"is_corresponding":false},{"id":419924,"name":"Jon Mark Hirshon","orcid":"0000-0002-5247-529X","position":5,"is_corresponding":false},{"id":586153,"name":"Adel Elbaih","orcid":"0000-0002-3347-5163","position":6,"is_corresponding":false},{"id":394636,"name":"Mohamed El‐Shinawi","orcid":"0000-0003-3645-2343","position":7,"is_corresponding":false},{"id":1112189,"name":"Yasmin Z. Attia","orcid":null,"position":0,"is_corresponding":true}],"reference_count":33,"raw_metadata":null,"created_at":"2026-07-19T01:14:01.896928Z","pmid":"36937618","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}