Agustín Julián-Jiménez1, Juan González Del Castillo2,3, Eric Jorge García-Lamberechts4,5, Itziar Huarte Sanz6, Carmen Navarro Bustos7, Rafael Rubio Díaz1, Josep María Guardiola Tey8, Ferrán Llopis-Roca9, Pascual Piñera Salmerón10, Mikel de Martín-Ortiz de Zarate11, Jesús Álvarez-Manzanares12, Julio Javier Gamazo-Del Rio13, Marta Álvarez Alonso14, Begoña Mora Ordoñez15, Oscar Álvarez López16, María Del Mar Ortega Romero17, María Del Mar Sousa Reviriego18, Ramón Perales Pardo19, Henrique Villena García Del Real20, María José Marchena González21, José María Ferreras Amez22, Félix González Martínez23, Francisco Javier Martín-Sánchez4,5, Pedro Beneyto Martín24, Francisco Javier Candel González25, Antonio Jesús Díaz-Honrubia26. 1. Emergency Department, Complejo Hospitalario Universitario de Toledo, Universidad de Castilla La Mancha, Toledo, Spain. 2. Emergency Department, Hospital Universitario Clínico San Carlos, Calle Profesor Martín Lagos Calle Profesor Martín Lagos, 28040, Madrid, Spain. jgonzalezcast@gmail.com. 3. Health Research Institute (IdISSC), Hospital Universitario San Carlos, Madrid, Spain. jgonzalezcast@gmail.com. 4. Emergency Department, Hospital Universitario Clínico San Carlos, Calle Profesor Martín Lagos Calle Profesor Martín Lagos, 28040, Madrid, Spain. 5. Health Research Institute (IdISSC), Hospital Universitario San Carlos, Madrid, Spain. 6. Emergency Department, Hospital Universitario de Donostia, San Sebastian, Spain. 7. Emergency Department, Hospital Universitario Virgen de La Macarena, Sevilla, Spain. 8. Emergency Department, Hospital Universitario Sant Pau, Barcelona, Spain. 9. Emergency Department, Hospital Universitario de Bellvitge, Barcelona, Spain. 10. Emergency Department, Hospital Universitario Reina Sofía, Murcia, Spain. 11. Emergency Department, Hospital Universitario de Basurto, Bilbao, Spain. 12. Emergency Department, Hospital Universitario Rio Hortega, Valladolid, Spain. 13. Emergency Department, Hospital Universitario de Galdakao-Usansolo, Bizkaia, Spain. 14. Emergency Department, Hospital Universitario de Fuenlabrada, Fuenlabrada, Spain. 15. Emergency Department, Hospital Virgen de La Victoria, Málaga, Spain. 16. Emergency Department, Hospital Universitario de Móstoles, Madrid, Spain. 17. Emergency Department, Hospital Clínic, Barcelona, Spain. 18. Emergency Department, Hospital Nuestra Señora del Prado, Talavera de La Reina, Spain. 19. Emergency Department, Complejo Hospitalario Universitario de Albacete, Albacete, Spain. 20. Emergency Department, Complejo Hospitalario Universitario de Santiago de Compostela, Santiago de Compostela , Spain. 21. Emergency Department, Hospital Juan Ramón Jiménez de Huelva, Huelva, Spain. 22. Emergency Department, Hospital Clínico Universitario Lozano Blesa de Zaragoza, Zaragoza, Spain. 23. Emergency Department, Hospital Virgen de La Luz de Cuenca, Cuenca, Spain. 24. Research Unit, Complejo Hospitalario Universitario de Toledo, Toledo, Spain. 25. Clinical Microbiology Department, Hospital Universitario Clínico San Carlos, Madrid, Spain. 26. Biomedical Technology Center - E.T.S. of Computer Engineers, Universidad Politécnica de Madrid, Madrid, Spain.
Abstract
OBJECTIVE: Design a risk model to predict bacteraemia in patients attended in emergency departments (ED) for an episode of infection. METHODS: This was a national, prospective, multicentre, observational cohort study of blood cultures (BC) collected from adult patients (≥ 18 years) attended in 71 Spanish EDs from October 1 2019 to March 31, 2020. Variables with a p value < 0.05 were introduced in the univariate analysis together with those of clinical significance. The final selection of variables for the scoring scale was made by logistic regression with selection by introduction. The results obtained were internally validated by dividing the sample in a derivation and a validation cohort. RESULTS: A total of 4,439 infectious episodes were included. Of these, 899 (20.25%) were considered as true bacteraemia. A predictive model for bacteraemia was defined with seven variables according to the Bacteraemia Prediction Model of the INFURG-SEMES group (MPB-INFURG-SEMES). The model achieved an area under the curve-receiver operating curve of 0.924 (CI 95%:0.914-0.934) in the derivation cohort, and 0.926 (CI 95%: 0.910-0.942) in the validation cohort. Patients were then split into ten risk categories, and had the following rates of risk: 0.2%(0 points), 0.4%(1 point), 0.9%(2 points), 1.8%(3 points), 4.7%(4 points), 19.1% (5 points), 39.1% (6 points), 56.8% (7 points), 71.1% (8 points), 82.7% (9 points) and 90.1% (10 points). Findings were similar in the validation cohort. The cut-off point of five points provided the best precision with a sensitivity of 95.94%, specificity of 76.28%, positive predictive value of 53.63% and negative predictive value of 98.50%. CONCLUSION: The MPB-INFURG-SEMES model may be useful for the stratification of risk of bacteraemia in adult patients with infection in EDs, together with clinical judgement and other variables independent of the process and the patient.
OBJECTIVE: Design a risk model to predict bacteraemia in patients attended in emergency departments (ED) for an episode of infection. METHODS: This was a national, prospective, multicentre, observational cohort study of blood cultures (BC) collected from adult patients (≥ 18 years) attended in 71 Spanish EDs from October 1 2019 to March 31, 2020. Variables with a p value < 0.05 were introduced in the univariate analysis together with those of clinical significance. The final selection of variables for the scoring scale was made by logistic regression with selection by introduction. The results obtained were internally validated by dividing the sample in a derivation and a validation cohort. RESULTS: A total of 4,439 infectious episodes were included. Of these, 899 (20.25%) were considered as true bacteraemia. A predictive model for bacteraemia was defined with seven variables according to the Bacteraemia Prediction Model of the INFURG-SEMES group (MPB-INFURG-SEMES). The model achieved an area under the curve-receiver operating curve of 0.924 (CI 95%:0.914-0.934) in the derivation cohort, and 0.926 (CI 95%: 0.910-0.942) in the validation cohort. Patients were then split into ten risk categories, and had the following rates of risk: 0.2%(0 points), 0.4%(1 point), 0.9%(2 points), 1.8%(3 points), 4.7%(4 points), 19.1% (5 points), 39.1% (6 points), 56.8% (7 points), 71.1% (8 points), 82.7% (9 points) and 90.1% (10 points). Findings were similar in the validation cohort. The cut-off point of five points provided the best precision with a sensitivity of 95.94%, specificity of 76.28%, positive predictive value of 53.63% and negative predictive value of 98.50%. CONCLUSION: The MPB-INFURG-SEMES model may be useful for the stratification of risk of bacteraemia in adult patients with infection in EDs, together with clinical judgement and other variables independent of the process and the patient.
Authors: Agustín Julián-Jiménez; Mark Supino; Jesús Daniel López Tapia; Carolina Ulloa González; Luis Eduardo Vargas Téllez; Juan González Del Castillo; Alejandro Moyá Álvarez; Luis Loro Chero; Ulises González Bascuñán; Francisco Javier Candel González; Olinda Giselle Garza Sáenz; Fabián Andrés Rosas Romero; Luis Antonio Gorordo Delsol Journal: Emergencias Date: 2019 Abr Impact factor: 3.881
Authors: Andrew Rhodes; Laura E Evans; Waleed Alhazzani; Mitchell M Levy; Massimo Antonelli; Ricard Ferrer; Anand Kumar; Jonathan E Sevransky; Charles L Sprung; Mark E Nunnally; Bram Rochwerg; Gordon D Rubenfeld; Derek C Angus; Djillali Annane; Richard J Beale; Geoffrey J Bellinghan; Gordon R Bernard; Jean-Daniel Chiche; Craig Coopersmith; Daniel P De Backer; Craig J French; Seitaro Fujishima; Herwig Gerlach; Jorge Luis Hidalgo; Steven M Hollenberg; Alan E Jones; Dilip R Karnad; Ruth M Kleinpell; Younsuk Koh; Thiago Costa Lisboa; Flavia R Machado; John J Marini; John C Marshall; John E Mazuski; Lauralyn A McIntyre; Anthony S McLean; Sangeeta Mehta; Rui P Moreno; John Myburgh; Paolo Navalesi; Osamu Nishida; Tiffany M Osborn; Anders Perner; Colleen M Plunkett; Marco Ranieri; Christa A Schorr; Maureen A Seckel; Christopher W Seymour; Lisa Shieh; Khalid A Shukri; Steven Q Simpson; Mervyn Singer; B Taylor Thompson; Sean R Townsend; Thomas Van der Poll; Jean-Louis Vincent; W Joost Wiersinga; Janice L Zimmerman; R Phillip Dellinger Journal: Intensive Care Med Date: 2017-01-18 Impact factor: 17.440
Authors: L Yunquera-Romero; I Márquez-Gómez; A Henares-López; M J Morales-Lara; C Gallego Fernández; R Asensi-Díez Journal: Rev Esp Quimioter Date: 2018-05-16 Impact factor: 1.553