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Development of a prediction model for emergency medical service witnessed traumatic out-of-hospital cardiac arrest: A multicenter cohort study.
Wang, Shao-An; Chang, Chih-Jung; Do Shin, Shan; Chu, Sheng-En; Huang, Chun-Yen; Hsu, Li-Min; Lin, Hao-Yang; Hong, Ki Jeong; Jamaluddin, Sabariah Faizah; Son, Do Ngoc; Ramakrishnan, T V; Chiang, Wen-Chu; Sun, Jen-Tang; Huei-Ming Ma, Matthew.
Afiliación
  • Wang SA; Department of Emergency Medicine, Far Eastern Memorial Hospital, No. 21, Sec. 2, Nan Ya South Rd, Banqiao Dist, New Taipei City, Taiwan.
  • Chang CJ; Department of Emergency Medicine, Far Eastern Memorial Hospital, No. 21, Sec. 2, Nan Ya South Rd, Banqiao Dist, New Taipei City, Taiwan.
  • Do Shin S; Department of Emergency Medicine, Seoul National University College of Medicine and Hospital, Seoul, South Korea.
  • Chu SE; Department of Emergency Medicine, Far Eastern Memorial Hospital, No. 21, Sec. 2, Nan Ya South Rd, Banqiao Dist, New Taipei City, Taiwan.
  • Huang CY; Department of Emergency Medicine, Far Eastern Memorial Hospital, No. 21, Sec. 2, Nan Ya South Rd, Banqiao Dist, New Taipei City, Taiwan.
  • Hsu LM; Department of Traumatology and Critical Care, National Taiwan University Hospital, Taipei, Taiwan.
  • Lin HY; Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan.
  • Hong KJ; Department of Emergency Medicine, Seoul National University College of Medicine and Hospital, Seoul, South Korea.
  • Jamaluddin SF; Faculty of Medicine, Universiti Teknologi MARA, Malaysia.
  • Son DN; Center for Emergency Medicine, Bach Mai Hospital, Hanoi, Viet Nam.
  • Ramakrishnan TV; Emergency Medicine, Sri Ramachandra Medical College, Chennai, India.
  • Chiang WC; Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan; Department of Emergency Medicine, National Taiwan University Hospital, Yun-Lin Branch, Taipei, Taiwan. Electronic address: drchiang.tw@gmail.com.
  • Sun JT; Department of Emergency Medicine, Far Eastern Memorial Hospital, No. 21, Sec. 2, Nan Ya South Rd, Banqiao Dist, New Taipei City, Taiwan; Department of Nursing, Cardinal Tien Junior College of Healthcare and Management, Yilan, Taiwan. Electronic address: tangtang05231980@hotmail.com.
  • Huei-Ming Ma M; Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan; Department of Emergency Medicine, National Taiwan University Hospital, Yun-Lin Branch, Taipei, Taiwan.
J Formos Med Assoc ; 123(1): 23-35, 2024 Jan.
Article en En | MEDLINE | ID: mdl-37573159
BACKGROUND/PURPOSE: To develop a prediction model for emergency medical technicians (EMTs) to identify trauma patients at high risk of deterioration to emergency medical service (EMS)-witnessed traumatic cardiac arrest (TCA) on the scene or en route. METHODS: We developed a prediction model using the classical cross-validation method from the Pan-Asia Trauma Outcomes Study (PATOS) database from 1 January 2015 to 31 December 2020. Eligible patients aged ≥18 years were transported to the hospital by the EMS. The primary outcome (EMS-witnessed TCA) was defined based on changes in vital signs measured on the scene or en route. We included variables that were immediately measurable as potential predictors when EMTs arrived. An integer point value system was built using multivariable logistic regression. The area under the receiver operating characteristic (AUROC) curve and Hosmer-Lemeshow (HL) test were used to examine discrimination and calibration in the derivation and validation cohorts. RESULTS: In total, 74,844 patients were eligible for database review. The model comprised five prehospital predictors: age <40 years, systolic blood pressure <100 mmHg, respiration rate >20/minute, pulse oximetry <94%, and levels of consciousness to pain or unresponsiveness. The AUROC in the derivation and validation cohorts was 0.767 and 0.782, respectively. The HL test revealed good calibration of the model (p = 0.906). CONCLUSION: We established a prediction model using variables from the PATOS database and measured them immediately after EMS personnel arrived to predict EMS-witnessed TCA. The model allows prehospital medical personnel to focus on high-risk patients and promptly administer optimal treatment.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Reanimación Cardiopulmonar / Servicios Médicos de Urgencia / Auxiliares de Urgencia / Paro Cardíaco Extrahospitalario Tipo de estudio: Clinical_trials / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adolescent / Adult / Humans Idioma: En Revista: J Formos Med Assoc Asunto de la revista: MEDICINA Año: 2024 Tipo del documento: Article País de afiliación: Taiwán Pais de publicación: Singapur
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Reanimación Cardiopulmonar / Servicios Médicos de Urgencia / Auxiliares de Urgencia / Paro Cardíaco Extrahospitalario Tipo de estudio: Clinical_trials / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adolescent / Adult / Humans Idioma: En Revista: J Formos Med Assoc Asunto de la revista: MEDICINA Año: 2024 Tipo del documento: Article País de afiliación: Taiwán Pais de publicación: Singapur