المؤلفون: Jessica González, Jordi de Batlle, Iván D. Benítez, Gerard Torres, Sally Santisteve, Adriano D.S. Targa, Clara Gort-Paniello, Anna Moncusí-Moix, Maria Aguilà, Fatty Seck, Adrián Ceccato, Ricard Ferrer, Anna Motos, Jordi Riera, Laia Fernández, Rosario Menéndez, José Ángel Lorente, Oscar Peñuelas, Dario Garcia-Gasulla, Yhivian Peñasco, Pilar Ricart, Elena Abril Palomares, Luciano Aguilera, Alejandro Rodríguez, Maria Victoria Boado Varela, Belén Beteré, Juan Carlos Pozo-Laderas, Jordi Solé-Violan, Inmaculada Salvador-Adell, Mariana Andrea Novo, José Barberán, Rosario Amaya Villar, José Garnacho-Montero, José M. Gómez, Aaron Blandino Ortiz, Luis Tamayo Lomas, Alejandro Úbeda, Mercedes Catalán-González, Angel Sánchez-Miralles, Ignacio Martínez Varela, Ruth Noemí Jorge García, Nieves Franco, Víctor D. Gumucio-Sanguino, Elena Bustamante-Munguira, Luis Jorge Valdivia, Jesús Caballero, Elena Gallego, Covadonga Rodríguez, Álvaro Castellanos-Ortega, Josep Trenado, Judith Marin-Corral, Guillermo M. Albaiceta, Maria del Carmen de la Torre, Ana Loza-Vázquez, Pablo Vidal, Jose M. Añón, Cristina Carbajales Pérez, Victor Sagredo, Nieves Carbonell, Lorenzo Socias, Carme Barberà, Angel Estella, Emili Diaz, David de Gonzalo-Calvo, Antoni Torres, Ferran Barbé, María Aguilar Cabello, Victoria Alcaraz-Serrano, Cesar Aldecoa, Cynthia Alegre, Ángela Algaba Calderón, Sergio Álvarez, Antonio Álvarez Ruiz, Ruth Andrea, Maria de Alba Aparicio, Marta Arrieta, J. Ignacio Ayestarán, Joan Ramon Badia, Mariona Badía, Orville Báez Pravia, Ana Balan Mariño, Begoña Balsera, Laura Barbena, Enric Barbeta, Tommaso Bardi, Patricia Barral Segade, Marta Barroso, José Ángel Berezo García, Jesus Bermejo, Judit Bigas, Rafael Blancas, María Luisa Blasco Cortés, María Bodi Saera, Neus Bofill, María Teresa Bouza Vieiro, Leticia Bueno, Juan Bustamante-Munguira, Cecilia del Busto Martínez, David Campi Hermoso, Sandra Campos Fernández, Iosune Cano, Joan Canseco, Pablo Cardinal Fernández, Laura Carrión García, Sulamita Carvalho, Manuel Castellà, Andrea Castellví, Pedro Castro, María José Centelles-Serrano, Ramon Cicuendez Ávila, Catia Cillóniz, Luisa Clar, Cristina Climent, Jordi Codina, Pamela Conde, Sofía Contreras, Raul de Frutos Parra, Raul de Pablo Sánchez, Diego De Mendoza, Yolanda Díaz, María Digna Rivas Vilas, Cristina Dólera Moreno, Irene Dot, Pedro Enríquez Giraudo, Inés Esmorís Arijón, Teresa Farre Monjo, Javier Fernández, Carlos Ferrando, Albert Figueras, Lorena Forcelledo Espina, Enric Franquesa, Àngels Furro, Albert Gabarrus, Cristóbal Galbán, Felipe García, Beatriz García, Emilio García Prieto, Carlos García Redruello, Amaia García Sagastume, Maria Luisa Gascón Castillo, Gemma Gomà, Vanesa Gómez Casal, Silvia Gómez, Carmen Gómez Gonzalez, Federico Gordo, Maria Pilar Gracia, María José Gutierrez Fernández, Alba Herraiz, Rubén Herrán-Monge, Mercedes Ibarz, Silvia Iglesias, Maria Teresa Janer, Gabriel Jiménez, Mar Juan Díaz, Karsa Kiarostami, Juan I. Lazo Álvarez, Miguel León, Alexandre López-Gavín, Desiree Macias Guerrero, Nuria Mamolar Herrera, Rafael Mañez Mendiluce, Cecilia L. Mantellini, Gregorio Marco Naya, Iris Marco Barcos, Pilar Marcos, Enrique Marmol Peis, Marta Martín Cuadrado, María Cruz Martin Delgado, Paula Martín Vicente, María Martínez, Carmen Eulalia Martínez Fernández, Maria Dolores Martínez Juan, Basilisa Martínez Palacios, Juan Fernando Masa Jimenez, Joan Ramon Masclans, Emilio Maseda, Eva María Menor Fernández, Priscila Metora Banderas, Olga Minguez, Mar Miralbés, Josman Monclou, Juan Carlos Montejo-González, Neus Montserrat, María Mora Aznar, Dulce Morales, Sara Guadalupe Moreno Cano, David Mosquera Rodríguez, Rosana Muñoz-Bermúdez, José María Nicolás, Ramon Nogue Bou, Rafaela Nogueras Salinas, Marta Ocón, Ana Ortega, Sergio Ossa, Pablo Pagliarani, Francisco Parrilla, José Pedregosa-Díaz, Leire Pérez Bastida, Purificación Pérez, Felipe Pérez-García, Gloria Pérez Planelles, Eva Pérez Rubio, David Pestaña Laguna, Javier Prados, Andrés Pujol, Núria Ramon Coll, Gloria Renedo Sanchez-Giron, Ferran Roche-Campo, Laura Rodriguez, Felipe Rodríguez de Castro, Silvia Rodríguez, Covadonga Rodríguez Ruiz, Jorge Rubio, Alberto Rubio López, Ángela Leonor Ruiz-García, Miriam Ruiz Miralles, Pablo Ryan Murúa, Eva Saborido Paz, Ana Salazar Degracia, Miguel Sanchez, Ana Sánchez, Susana Sancho Chinesta, Bitor Santacoloma, Maria Teresa Sariñena, Marta Segura Pensado, Lidia Serra, Mireia Serra-Fortuny, Ainhoa Serrano Lázaro, Lluís Servià, Laura Soliva, Carla Speziale, Adrián Tormos, Mateu Torres, Celia Tranque-Liberal, Sandra Trefler, Javier Trujillano, Rafaela Vaca, Estela Val, Luis Valdivia Ruiz, Montserrat Vallverdú, Maria Van der Hofstadt Martin-Montalvo, Sabela Vara Adrio, Nil Vázquez, Javier Vengoechea, Clara Vilà-Vilardel, Judit Vilanova, Tatiana Villada Warrington, Hua Yang, Minlan Yang, Ana Zapatero

المصدر: Archivos de Bronconeumología. 59:205-215

مصطلحات موضوعية: Pulmonary and Respiratory Medicine

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::35db638e43c7829061d3aa2ed59a3fb8Test
https://doi.org/10.1016/j.arbres.2022.12.017Test

المؤلفون: Luis Serviá (11808706), Juan Antonio Llompart-Pou (11808709), Mario Chico-Fernández (11808712), Neus Montserrat (5848904), Mariona Badia (5848901), Jesús Abelardo Barea-Mendoza (11808715), María Ángeles Ballesteros-Sanz (11808718), Javier Trujillano (11808721)

مصطلحات موضوعية: Medicine, Genetics, Biotechnology, Cancer, Infectious Diseases, Trauma and injury severity score, Intensive care unit, Mortality, Prognostic scoring systems

الوصف: Additional file 1: Screenshots of the web application and the list of variables collected in RETRAUCI.

العلاقة: https://figshare.com/articles/journal_contribution/Additional_file_1_of_Development_of_a_new_score_for_early_mortality_prediction_in_trauma_ICU_patients_RETRASCORE/17141293Test

الإتاحة: https://doi.org/10.6084/m9.figshare.17141293.v1Test

المؤلفون: Luis Serviá (11808706), Juan Antonio Llompart-Pou (11808709), Mario Chico-Fernández (11808712), Neus Montserrat (5848904), Mariona Badia (5848901), Jesús Abelardo Barea-Mendoza (11808715), María Ángeles Ballesteros-Sanz (11808718), Javier Trujillano (11808721)

مصطلحات موضوعية: Medicine, Genetics, Biotechnology, Cancer, Infectious Diseases, Trauma and injury severity score, Intensive care unit, Mortality, Prognostic scoring systems

الوصف: Additional file 2: Figure S2-1. Flow diagram for selection of patients. Figure S2-2: Selection of variables using LASSO (Least Absolute Shrinkage and Selection Operator) binary logistic regression model. Figure S2-3. Performance evaluation of the logistic regression (LR) model. Figure S2-4. Performance evaluation of the TRISS model. Figure S2-5. Performance evaluation of the RETRASCORE model.

العلاقة: https://figshare.com/articles/journal_contribution/Additional_file_2_of_Development_of_a_new_score_for_early_mortality_prediction_in_trauma_ICU_patients_RETRASCORE/17141299Test

الإتاحة: https://doi.org/10.6084/m9.figshare.17141299.v1Test

المؤلفون: Luis Serviá (11808706), Juan Antonio Llompart-Pou (11808709), Mario Chico-Fernández (11808712), Neus Montserrat (5848904), Mariona Badia (5848901), Jesús Abelardo Barea-Mendoza (11808715), María Ángeles Ballesteros-Sanz (11808718), Javier Trujillano (11808721)

مصطلحات موضوعية: Medicine, Genetics, Biotechnology, Cancer, Infectious Diseases, Trauma and injury severity score, Intensive care unit, Mortality, Prognostic scoring systems

الوصف: Additional file 3: Comparative analysis between temporal and random partitions in the selection of variables and calculated coefficients.

العلاقة: https://figshare.com/articles/journal_contribution/Additional_file_3_of_Development_of_a_new_score_for_early_mortality_prediction_in_trauma_ICU_patients_RETRASCORE/17141305Test

الإتاحة: https://doi.org/10.6084/m9.figshare.17141305.v1Test

المؤلفون: Luis Serviá, Juan Antonio Llompart-Pou, Mario Chico-Fernández, Neus Montserrat, Mariona Badia, Jesús Abelardo Barea-Mendoza, María Ángeles Ballesteros-Sanz, Javier Trujillano

المصدر: Critical Care, Vol 25, Iss 1, Pp 1-10 (2021)

مصطلحات موضوعية: Trauma and injury severity score, Intensive care unit, Mortality, Prognostic scoring systems, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9

الوصف: Background Severity scores are commonly used for outcome adjustment and benchmarking of trauma care provided. No specific models performed only with critically ill patients are available. Our objective was to develop a new score for early mortality prediction in trauma ICU patients. Methods This is a retrospective study using the Spanish Trauma ICU registry (RETRAUCI) 2015–2019. Patients were divided and analysed into the derivation (2015–2017) and validation sets (2018–2019). We used as candidate variables to be associated with mortality those available in RETRAUCI that could be collected in the first 24 h after ICU admission. Using logistic regression methodology, a simple score (RETRASCORE) was created with points assigned to each selected variable. The performance of the model was carried out according to global measures, discrimination and calibration. Results The analysis included 9465 patients: derivation set 5976 and validation set 3489. Thirty-day mortality was 12.2%. The predicted probability of 30-day mortality was determined by the following equation: 1/(1 + exp (− y)), where y = 0.598 (Age 50–65) + 1.239 (Age 66–75) + 2.198 (Age > 75) + 0.349 (PRECOAG) + 0.336 (Pre-hospital intubation) + 0.662 (High-risk mechanism) + 0.950 (unilateral mydriasis) + 3.217 (bilateral mydriasis) + 0.841 (Glasgow ≤ 8) + 0.495 (MAIS-Head) − 0.271 (MAIS-Thorax) + 1.148 (Haemodynamic failure) + 0.708 (Respiratory failure) + 0.567 (Coagulopathy) + 0.580 (Mechanical ventilation) + 0.452 (Massive haemorrhage) − 5.432. The AUROC was 0.913 (0.903–0.923) in the derivation set and 0.929 (0.918–0.940) in the validation set. Conclusions The newly developed RETRASCORE is an early, easy-to-calculate and specific score to predict in-hospital mortality in trauma ICU patients. Although it has achieved adequate internal validation, it must be externally validated.

العلاقة: https://doi.org/10.1186/s13054-021-03845-6Test; https://doaj.org/toc/1364-8535Test; https://doaj.org/article/b8024683f7424ad9968cc5d31c0647b7Test

الإتاحة: https://doi.org/10.1186/s13054-021-03845-6Test
https://doaj.org/article/b8024683f7424ad9968cc5d31c0647b7Test

المؤلفون: Mariona Badia, José Manuel Casanova, Lluís Serviá, Neus Montserrat, Jordi Codina, Javier Trujillano

المصدر: Critical Care Research and Practice, Vol 2020 (2020)

مصطلحات موضوعية: Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9

الوصف: Dermatological problems are not usually related to intensive medicine because they are considered to have a low impact on the evolution of critical patients. Despite this, dermatological manifestations (DMs) are relatively frequent in critically ill patients. In rare cases, DMs will be the main diagnosis and will require intensive treatment due to acute skin failure. In contrast, DMs can be a reflection of underlying systemic diseases, and their identification may be key to their diagnosis. On other occasions, DMs are lesions that appear in the evolution of critical patients and are due to factors derived from the stay or intensive treatment. Lastly, DMs can accompany patients and must be taken into account in the comprehensive pathology management. Several factors must be considered when addressing DMs: on the one hand, the moment of appearance, morphology, location, and associated treatment and, on the other hand, aetiopathogenesis and classification of the cutaneous lesion. DMs can be classified into 4 groups: life-threatening DMs (uncommon but compromise the patient's life); DMs associated with systemic diseases where skin lesions accompany the pathology that requires admission to the intensive care unit (ICU); DMs secondary to the management of the critical patient that considers the cutaneous manifestations that appear in the evolution mainly of infectious or allergic origin; and DMs previously present in the patient and unrelated to the critical process. This review provides a characterization of DMs in ICU patients to establish a better identification and classification and to understand their interrelation with critical illnesses.

العلاقة: http://dx.doi.org/10.1155/2020/9729814Test; https://doaj.org/toc/2090-1305Test; https://doaj.org/toc/2090-1313Test; https://doaj.org/article/2a605da0130d44ba9ffec587c47eff31Test

الإتاحة: https://doi.org/10.1155/2020/9729814Test
https://doaj.org/article/2a605da0130d44ba9ffec587c47eff31Test

المؤلفون: Luis Serviá, Neus Montserrat, Mariona Badia, Juan Antonio Llompart-Pou, Jesús Abelardo Barea-Mendoza, Mario Chico-Fernández, Marcelino Sánchez-Casado, José Manuel Jiménez, Dolores María Mayor, Javier Trujillano

المصدر: BMC Medical Research Methodology, Vol 20, Iss 1, Pp 1-12 (2020)

مصطلحات موضوعية: Intensive care unit, Machine learning techniques, Supervised algorithms, Traumatic patient, Mortality, Medicine (General), R5-920

الوصف: Background Interest in models for calculating the risk of death in traumatic patients admitted to ICUs remains high. These models use variables derived from the deviation of physiological parameters and/or the severity of anatomical lesions with respect to the affected body areas. Our objective is to create different predictive models of the mortality of critically traumatic patients using machine learning techniques. Methods We used 9625 records from the RETRAUCI database (National Trauma Registry of 52 Spanish ICUs in the period of 2015–2019). Hospital mortality was 12.6%. Data on demographic variables, affected anatomical areas and physiological repercussions were used. The Weka Platform was used, along with a ten-fold cross-validation for the construction of nine supervised algorithms: logistic regression binary (LR), neural network (NN), sequential minimal optimization (SMO), classification rules (JRip), classification trees (CT), Bayesian networks (BN), adaptive boosting (ADABOOST), bootstrap aggregating (BAGGING) and random forest (RFOREST). The performance of the models was evaluated by accuracy, specificity, precision, recall, F-measure, and AUC. Results In all algorithms, the most important factors are those associated with traumatic brain injury (TBI) and organic failures. The LR finds thorax and limb injuries as independent protective factors of mortality. The CT generates 24 decision rules and uses those related to TBI as the first variables (range 2.0–81.6%). The JRip detects the eight rules with the highest risk of mortality (65.0–94.1%). The NN model uses a hidden layer of ten nodes, which requires 200 weights for its interpretation. The BN find the relationships between the different factors that identify different patient profiles. Models with the ensemble methodology (ADABOOST, BAGGING and RandomForest) do not have greater performance. All models obtain high values in accuracy, specificity, and AUC, but obtain lower values in recall. The greatest precision is achieved by the SMO ...

العلاقة: http://link.springer.com/article/10.1186/s12874-020-01151-3Test; https://doaj.org/toc/1471-2288Test; https://doaj.org/article/6d75261d3d944f5e988c4f772cad17dcTest

الإتاحة: https://doi.org/10.1186/s12874-020-01151-3Test
https://doaj.org/article/6d75261d3d944f5e988c4f772cad17dcTest

المؤلفون: Catia Cillóniz, Anna Motos, Tatiana Castañeda, Albert Gabarrús, Ferran Barbé, Antoni Torres, Víctor D. Gumucio-Sanguino, Rafael Mañez, Jordi Solé-Violan, Felipe Rodríguez de Castro, Fernando Suarez-Sipmann, Ruth Noemí Jorge García, María Mora Aznar, Mateu Torres, María Martinez, Cynthia Alegre, Jordi Riera, Sofía Contreras, Juan Manuel Pericas, Ricard Ferrer, Jesús Caballero, Javier Trujillano, Montse Vallverdú, Miguel León, Mariona Badía, Begoña Balsera, Lluís Servià, Judit Vilanova, Silvia Rodríguez, Neus Montserrat, Silvia Iglesias, Javier Prados, Sula Carvalho, Mar Miralbés, Josman Monclou, Gabriel Jiménez, Jordi Codina, Estela Val, Pablo Pagliarani, Jorge Rubio, Dulce Morales, Andrés Pujol, Àngels Furro, Beatriz García, Gerard Torres, Javier Vengoechea, David de Gonzalo-Calvo, Jessica González, Silvia Gomez, José M. Gómez, Nieves Franco, José Barberán, Guillermo M Albaiceta, Lorena Forcelledo Espina, Emilio García Prieto, Paula Martín Vicente, Cecilia del Busto Martínez, Pablo Vidal-Cortés, José Luis García Garmendia, María Aguilar Cabello, Carmen Eulalia Martínez Fernández, Nieves Carbonell, María Luisa Blasco Cortés, Ainhoa Serrano Lázaro, Mar Juan Díaz, Aaron Blandino Ortiz, Rosario Menendez, Luis Jorge Valdivia, María Victoria Boado, Susana Sancho Chinesta, Maria del Carmen de la Torre, Ignacio Martínez Varela, María Teresa Bouza Vieiro, Inés Esmorís Arijón, David Campi Hermoso, Rafaela Nogueras Salinas, Teresa Farre Monjo, Ramon Nogue Bou, Gregorio Marco Naya, Carme Barberà, Núria Ramon Coll, Mercedes Catalán-González, Juan Carlos Montejo-González, Gloria Renedo Sanchez-Giron, Juan Bustamante-Munguira, Elena Bustamante-Munguira, Ramon Cicuendez Avila, Nuria Mamolar Herrera, Raquel Almansa, Alicia Ortega, Jesús Bermejo-Martin, Víctor Sagredo, Jose Añon, Alexander Agrifoglio, Lucia Cachafeiro, Emilio Maseda, Lorenzo Socias, Mariana Andrea Novo, Albert Figueras, Maria Teresa Janer, Laura Soliva, Marta Ocón, Luisa Clar, J Ignacio Ayestarán, Yhivian Peñasco, Sandra Campos Fernández, Mireia Serra-Fortuny, Eva Forcadell-Ferreres, Immaculada Salvador-Adell, Neus Bofill, Berta Adell-Serrano, Josep Pedregosa Díaz, Núria Casacuberta-Barberà, Luis Urrelo-Cerrón, Àngels Piñol-Tena, Ferran Roche-Campo, Amalia Martínez de la Gándara, Pablo Ryan Murúa, Covadonga Rodríguez Ruíz, Laura Carrión García, Juan I Lazo Álvarez, José Ángel Lorente, Ana Loza-Vázquez, Desire Macias Guerrero, Arturo Huerta, Daniel Tognetti, Carlos García Redruello, David Mosquera Rodríguez, Eva María Menor Fernández, Sabela Vara Adrio, Vanesa Gómez Casal, Marta Segura Pensado, María Digna Rivas Vilas, Amaia García Sagastume, Raul de Pablo Sánchez, David Pestaña Laguna, Tommaso Bardi, Rosario Amaya Villar, Carmen Gómez Gonzalez, Maria Luisa Gascón Castillo, José Garnacho-Montero, María Luisa Cantón-Bulnes, Judith Marin-Corral, Cristina Carbajales Pérez, Joan Ramon Masclans, Ana Salazar Degracia, Judit Bigas, Rosana Muñoz-Bermúdez, Clara Vilà-Vilardel, Francisco Parrilla, Irene Dot, Ana Zapatero, Yolanda Díaz, María Pilar Gracia, Purificación Pérez, Andrea Castellví, Cristina Climent, Lidia Serra, Laura Barbena, Iosune Cano, Pilar Ricart, Alba Herraiz, Pilar Marcos, Laura Rodríguez, Maria Teresa Sariñena, Ana Sánchez, Alejandro Úbeda, María Cruz Martin Delgado, Elena Gallego, Juan Fernando Masa Jimenez, Gemma Gomà, Emi Díaz, Mercedes Ibarz, Diego De Mendoza, Enric Barbeta, Victoria Alcaraz-Serrano, Joan Ramon Badia, Manuel Castella, Leticia Bueno, Adrian Ceccato, Andrea Palomeque, Laia Fernandez Barat, Pamela Conde, Javier Fernández, Albert Gabarrus, Karsa Kiarostami, Alexandre López-Gavín, Cecilia L Mantellini, Carla Speziale, Nil Vázquez, Hua Yang, Minlan Yang, Carlos Ferrando, Pedro Castro, Marta Arrieta, Jose Maria Nicolas, Rut Andrea, Marta Barroso, Raquel Pérez, Sergio Álvarez, Dario Garcia-Gasulla, Adrián Tormos, Luis Tamayo Lomas, Cesar Aldecoa, Rubén Herrán-Monge, José Ángel Berezo García, Pedro Enríquez Giraudo, Pablo Cardinal Fernández, Alberto Rubio López, Orville Báez Pravia, Juan López Messa, Leire Pérez Bastida, Antonjo Alvarez Ruiz, José Trenado, Anna Parera Pous, Cristóbal Galbán, Ana López Lago, Eva Saborido Paz, Patricia Barral Segade, Ana Balan Mariño, Manuel Valledor Mendez, Raúl de Frutos, Luciano Aguilera, Felipe Pérez-García, Esther López-Ramos, Ángela Leonor Ruiz-García, Belén Beteré, Rafael Blancas, Cristina Dólera, Gloria Perez Planelles, Enrique Marmol Peis, Maria Dolores Martinez Juan, Miriam Ruiz Miralles, Eva Perez Rubio, Maria Van der Hofstadt Martin-Montalvo, Ángel Sánchez-Miralles, Tatiana Villada Warrington, Juan Carlos Pozo-Laderas, Angel Estrella, Sara Guadalupe Moreno Cano, Federico Gordo, Basilisa Martinez Palacios, Maite Nieto, Maria Teresa Nieto, Sergio Ossa, Ana Ortega, Miguel Sanchez, Bitor Santacoloma

المصدر: The Journal of infection.

مصطلحات موضوعية: Microbiology (medical), Infectious Diseases

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::78cab90016867a251c2111b455556fd1Test
https://pubmed.ncbi.nlm.nih.gov/36596315Test

المؤلفون: Luis Servia, José C E Serrano, Reinald Pamplona, Mariona Badia, Neus Montserrat, Manuel Portero-Otin, Javier Trujillano

المصدر: PLoS ONE, Vol 13, Iss 10, p e0205519 (2018)

مصطلحات موضوعية: Medicine, Science

الوصف: Though circulating antioxidant capacity in plasma is homeostatically regulated, it is not known whether acute stressors (i.e. trauma) affecting different anatomical locations could have quantitatively different impacts. For this reason, we evaluated the relationship between the anatomical location of trauma and plasma total antioxidant capacity (TAC) in a prospective study, where the anatomical locations of trauma in polytraumatic patients (n = 66) were categorized as primary affecting the brain -traumatic brain injury (TBI)-, thorax, abdomen and pelvis or extremities. We measured the following: plasma TAC by 2 independent methods, the contribution of selected antioxidant molecules (uric acid, bilirubin and albumin) to these values and changes after 1 week of progression. Surprisingly, TBI lowered TAC (919 ± 335 μM Trolox equivalents (TE)) in comparison with other groups (thoracic trauma 1187 ± 270 μM TE; extremities 1025 ± 276 μM TE; p = 0.004). The latter 2 presented higher hypoxia (PaO2/FiO2 272 ± 87 mmHg) and hemodynamic instability (inotrope use required in 54.5%) as well. Temporal changes in TAC are also dependent on anatomical location, as thoracic and extremity trauma patients' TAC values decreased (1187 ± 270 to 1045 ± 263 μM TE; 1025 ± 276 to 918 ± 331 μM TE) after 1 week (p < 0.01), while in TBI these values increased (919 ± 335 to 961 ± 465 μM TE). Our results show that the response of plasma antioxidant capacity in trauma patients is strongly dependent on time after trauma and location, with TBI failing to induce such a response.

العلاقة: http://europepmc.org/articles/PMC6181391?pdf=renderTest; https://doaj.org/toc/1932-6203Test; https://doaj.org/article/13aef97fd67942559329120ac52329c5Test

الإتاحة: https://doi.org/10.1371/journal.pone.0205519Test
https://doaj.org/article/13aef97fd67942559329120ac52329c5Test

المؤلفون: Javier Trujillano, Antonio Sarria-Santamera, Aureli Esquerda, Mariona Badia, Matilde Palma, Jaume March

المصدر: Gaceta Sanitaria, Vol 22, Iss 1, Pp 65-72 (2008)

مصطلحات موضوعية: Árboles de decisión, Red neuronal artificial, Regresión logística, Classification and Regression Trees, Artificial Neural Networks, Logistic Regression, Public aspects of medicine, RA1-1270

الوصف: Objetivo: : Realizar una aproximación a la metodología de árboles de decisión tipo CART (Classification and Regression Trees) desarrollando un modelo para calcular la probabilidad de muerte hospitalaria en infarto agudo de miocardio (IAM). Método: Se utiliza el conjunto mínimo básico de datos al alta hospitalaria (CMBD) de Andalucía, Cataluña, Madrid y País Vasco de los años 2001 y 2002, que incluye los casos con IAM como diagnóstico principal. Los 33.203 pacientes se dividen aleatoriamente (70 y 30 %) en grupo de desarrollo (GD = 23.277) y grupo de validación (GV = 9.926). Como CART se utiliza un modelo inductivo basado en el algoritmo de Breiman, con análisis de sensibilidad mediante el índice de Gini y sistema de validación cruzada. Se compara con un modelo de regresión logística (RL) y una red neuronal artificial (RNA) (multilayer perceptron). Los modelos desarrollados se contrastan en el GV y sus propiedades se comparan con el área bajo la curva ROC (ABC) (intervalo de confianza del 95%). Resultados: En el GD el CART con ABC = 0,85 (0,86-0,88), RL 0,87 (0,86-0,88) y RNA 0,85 (0,85-0,86). En el GV el CART con ABC = 0,85 (0,85-0,88), RL 0,86 (0,85-0,88) y RNA 0,84 (0,83-0,86). Conclusiones: Los 3 modelos obtienen resultados similares en su capacidad de discriminación. El modelo CART ofrece como ventaja su simplicidad de uso y de interpretación, ya que las reglas de decisión que generan pueden aplicarse sin necesidad de procesos matemáticos. Objective: To provide an overview of decision trees based on CART (Classification and Regression Trees) methodology. As an example, we developed a CART model intended to estimate the probability of intrahospital death from acute myocardial infarction (AMI). Method: We employed the minimum data set (MDS) of Andalusia, Catalonia, Madrid and the Basque Country (2001-2002), which included 33,203 patients with a diagnosis of AMI. The 33,203 patients were randomly divided (70% and 30%) into the development (DS; n = 23,277) and the validation (VS; n = 9,926) sets. The CART ...

العلاقة: http://scielo.isciii.es/scielo.php?script=sci_arttext&pid=S0213-91112008000100013Test; https://doaj.org/toc/0213-9111Test; https://doaj.org/article/83d17a00d44b4b9ba78e312581ce4080Test

الإتاحة: https://doaj.org/article/83d17a00d44b4b9ba78e312581ce4080Test