Neus Montserrat - Academia.edu (original) (raw)

Papers by Neus Montserrat

Research paper thumbnail of Machine learning techniques for mortality prediction in critical traumatic patients: anatomic and physiologic variables from the RETRAUCI study

BMC Medical Research Methodology

Background Interest in models for calculating the risk of death in traumatic patients admitted to... more 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 (ADAB...

Research paper thumbnail of Classification of dermatological disorders in critical care patients: A prospective observational study

Journal of Critical Care, 2013

The objective of this study was to identify dermatological disorders detected in the intensive ca... more The objective of this study was to identify dermatological disorders detected in the intensive care unit (ICU), to analyze their specific characteristics, and to define a useful classification for intensive care physicians. This was a prospective, observational study over a 3-year period (2006-2009) in a mixed ICU. This included all patients presenting with dermatological disorders that were detected at the time of ICU admission or developed along the ICU stay. We recorded the specific characteristics of the disorders and its evolution and treatment, which enabled us to classify the different observed conditions. As general variables, we analyzed demographic factors, the principal diagnosis, ICU procedures, the severity score (Acute Physiology and Chronic Health Evaluation II), length of stay, and mortality. One hundred thirty-three patients showed at least one dermatological disorder (9.3%) and were classified into (1) preexisting dermatological disorders, (2) life-threatening dermatologic disorders, (3) systemic dermatological disorders, (4) infectious dermatological disorders, (5) reactive dermatological disorders, and (6) others. Dermatological disorders are a frequent problem in the ICU, and their recognition is key to set up an appropriate care plan. We propose a classification and description of the different types of dermatological disorders that are most commonly found in ICUs.

Research paper thumbnail of Time spent in the emergency department and mortality rates in severely injured patients admitted to the intensive care unit: An observational study

Journal of Critical Care, 2012

Purpose: The aim of this study was to identify the determinants of a shorter emergency department... more Purpose: The aim of this study was to identify the determinants of a shorter emergency department time (EDt) in patients with severe trauma (STPs) admitted to the intensive care unit and determine whether EDt influences mortality. Patients and Methods: A prospective observational study of STPs (2005STPs ( -2007 was conducted. With the variables available from the ED, 2 multiple logistic regression models (MLRM) were created: one for the factors associated with EDt less than or equal to median and the other with mortality. Results: A total of 243 patients were included. The mean age was 43 years; 76% were male. The overall mortality rate was 20%. The median EDt was 120 minutes. The independent factors that were associated with the MLRM for an EDt of 120 minutes or less included age less than 60 years, mechanical ventilation, severe traumatic brain injury, and a trauma and injury severity score of 20 or higher. The MLRM for mortality was age greater than 60 years, mechanical ventilation, traumatic brain injury and shock. An EDt of 120 minutes or less was associated with an increased risk of death in the univariate analysis but not in the MLRM. Conclusions: Patients in the ED with indicators of high trauma severity have a reduced EDt but a higher mortality rate. Advanced age increases both mortality and EDt. With the factors included in the model, EDt was not an independent factor for mortality in STPs.

Research paper thumbnail of Machine learning techniques for mortality prediction in critical traumatic patients: anatomic and physiologic variables from the RETRAUCI study

BMC Medical Research Methodology

Background Interest in models for calculating the risk of death in traumatic patients admitted to... more 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 (ADAB...

Research paper thumbnail of Classification of dermatological disorders in critical care patients: A prospective observational study

Journal of Critical Care, 2013

The objective of this study was to identify dermatological disorders detected in the intensive ca... more The objective of this study was to identify dermatological disorders detected in the intensive care unit (ICU), to analyze their specific characteristics, and to define a useful classification for intensive care physicians. This was a prospective, observational study over a 3-year period (2006-2009) in a mixed ICU. This included all patients presenting with dermatological disorders that were detected at the time of ICU admission or developed along the ICU stay. We recorded the specific characteristics of the disorders and its evolution and treatment, which enabled us to classify the different observed conditions. As general variables, we analyzed demographic factors, the principal diagnosis, ICU procedures, the severity score (Acute Physiology and Chronic Health Evaluation II), length of stay, and mortality. One hundred thirty-three patients showed at least one dermatological disorder (9.3%) and were classified into (1) preexisting dermatological disorders, (2) life-threatening dermatologic disorders, (3) systemic dermatological disorders, (4) infectious dermatological disorders, (5) reactive dermatological disorders, and (6) others. Dermatological disorders are a frequent problem in the ICU, and their recognition is key to set up an appropriate care plan. We propose a classification and description of the different types of dermatological disorders that are most commonly found in ICUs.

Research paper thumbnail of Time spent in the emergency department and mortality rates in severely injured patients admitted to the intensive care unit: An observational study

Journal of Critical Care, 2012

Purpose: The aim of this study was to identify the determinants of a shorter emergency department... more Purpose: The aim of this study was to identify the determinants of a shorter emergency department time (EDt) in patients with severe trauma (STPs) admitted to the intensive care unit and determine whether EDt influences mortality. Patients and Methods: A prospective observational study of STPs (2005STPs ( -2007 was conducted. With the variables available from the ED, 2 multiple logistic regression models (MLRM) were created: one for the factors associated with EDt less than or equal to median and the other with mortality. Results: A total of 243 patients were included. The mean age was 43 years; 76% were male. The overall mortality rate was 20%. The median EDt was 120 minutes. The independent factors that were associated with the MLRM for an EDt of 120 minutes or less included age less than 60 years, mechanical ventilation, severe traumatic brain injury, and a trauma and injury severity score of 20 or higher. The MLRM for mortality was age greater than 60 years, mechanical ventilation, traumatic brain injury and shock. An EDt of 120 minutes or less was associated with an increased risk of death in the univariate analysis but not in the MLRM. Conclusions: Patients in the ED with indicators of high trauma severity have a reduced EDt but a higher mortality rate. Advanced age increases both mortality and EDt. With the factors included in the model, EDt was not an independent factor for mortality in STPs.