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Noera G, Bertolini A, Calzà L, Gori M, Pitino A, D'Arrigo G, Egan CG, Tripepi G. Effect of early administration of tetracosactide on mortality and host response in critically ill patients requiring rescue surgery: a sensitivity analysis of the STOPSHOCK phase 3 randomized controlled trial. Mil Med Res 2024; 11:56. [PMID: 39160574 PMCID: PMC11331742 DOI: 10.1186/s40779-024-00555-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 07/12/2024] [Indexed: 08/21/2024] Open
Abstract
BACKGROUND Undifferentiated shock is recognized as a criticality state that is transitional in immune-mediated topology for casual risk of lethal microcirculatory dysfunction. This was a sensitivity analysis of a drug (tetracosactide; TCS10) targeting melanocortin receptors (MCRs) in a phase 3 randomized controlled trial to improve cardiovascular surgical rescue outcome by reversing mortality and hemostatic disorders. METHODS Sensitivity analysis was based on a randomized, two-arm, multicenter, double-blind, controlled trial. The Naïve Bayes classifier was performed by density-based sensitivity index for principal strata as proportional hazard model of 30-day surgical risk mortality according to European System for Cardiac Operative Risk Evaluation inputs-outputs in 100 consecutive cases (from August to September 2013 from Emilia Romagna region, Italy). Patients included an agent-based TCS10 group (10 mg, single intravenous bolus before surgery; n = 56) and control group (n = 44) and the association with cytokines, lactate, and bleeding-blood transfusion episodes with the prior-risk log-odds for mortality rate in time-to-event was analyzed. RESULTS Thirty-day mortality was significantly improved in the TCS10 group vs. control group (0 vs. 8 deaths, P < 0.0001). Baseline levels of interleukin (IL)-6, IL-10, and lactate were associated with bleeding episodes, independent of TCS10 treatment [odds ratio (OR) = 1.90, 95% confidence interval (CI) 1.39-2.79; OR = 1.53, 95%CI 1.17-2.12; and OR = 2.92, 95%CI 1.40-6.66, respectively], while baseline level of Fms-like tyrosine kinase 3 ligand (Flt3L) was associated with lower bleeding rates in TCS10-treated patients (OR = 0.31, 95%CI 0.11-0.90, P = 0.03). For every 8 TCS10-treated patients, 1 bleeding case was avoided. Blood transfusion episodes were significantly reduced in the TCS10 group compared to the control group (OR = 0.32, 95%CI 0.14-0.73, P = 0.01). For every 4 TCS10-treated patients, 1 transfusion case was avoided. CONCLUSIONS Sensitivity index underlines the quality target product profile of TCS10 in the runway of emergency casualty care. To introduce the technology readiness level in real-life critically ill patients, further large-scale studies are required. TRIAL REGISTRATION European Union Drug Regulating Authorities Clinical Trials Database (EudraCT Number: 2007-006445-41 ).
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Affiliation(s)
- Giorgio Noera
- Health Ricerca e Sviluppo, Global Contractor for STOPSHOCK National Plan of Military Research Ministry of Defence, Rome, 00187, Italy.
| | - Alfio Bertolini
- Department of Medicine and Division of Clinical Pharmacology, School of Medicine, UNIMORE, Policlinico, Modena, 41124, Italy
| | - Laura Calzà
- IRET Foundation, Ozzano Dell' Emilia, Bologna, 40064, Italy
| | - Mercedes Gori
- Institute of Clinical Physiology (IFC-CNR), Section of Rome, Rome, 00185, Italy
| | - Annalisa Pitino
- Institute of Clinical Physiology (IFC-CNR), Section of Rome, Rome, 00185, Italy
| | - Graziella D'Arrigo
- National Research Council-Institute of Clinical Physiology, Reggio Calabria, 89124, Italy
| | | | - Giovanni Tripepi
- National Research Council-Institute of Clinical Physiology, Reggio Calabria, 89124, Italy
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Sun C, Zhao T, Yang W, Guo G, Wang H, Li C, Hui Y, Cui B, Wang X, Fan X, Zhao X. Reduced muscle strength is closely linked to computed tomography-defined myosteatosis among inpatients with cirrhosis. Postgrad Med J 2023; 100:12-19. [PMID: 37827533 DOI: 10.1093/postmj/qgad097] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/20/2023] [Accepted: 09/20/2023] [Indexed: 10/14/2023]
Abstract
BACKGROUND Myosteatosis indicates pathological fat infiltration in muscles and is regarded as a distinct disease from sarcopenia. This muscular condition exhibits a link to muscle fiber disarrangement coinciding with disrupted muscle contractility and weakened mechanical action, mirrored as decreased muscle quality. However, the relationship between handgrip strength (HGS) and computed tomography-defined myosteatosis among cirrhosis is unclear. We aimed to investigate the association between HGS and myosteatosis and determine gender-specific cutoffs regarding HGS to identify myosteatotic subjects. METHODS We prospectively recruited 221 cirrhotic patients. The presence of myosteatosis was determined according to intramuscular adipose tissue content. The relationship between HGS and myosteatosis was evaluated according to Spearman correlation coefficient, area under the ROC curve, and multivariate logistic regression analysis. Moreover, a model based on the classification and regression tree method was generated. RESULTS Our results showed that HGS exhibits modestly negative correlation with intramuscular adipose tissue content in the entire cohort (rs = -0.269, P < .001) and across diverse subgroups precluding extremely deteriorating conditions. After controlling for multiple clinical features and biochemical parameters, HGS (odds ratio = 0.921, P = .010) was independently associated with myosteatosis in addition to age and body mass index. On applying the Japan Society of Hepatology-recommended cutoffs, an area under the ROC curve of HGS was 0.627 with a sensitivity of 77.4% and a specificity of 47.9%. The decision tree including body mass index and low HGS correctly classified ~85% of the cases in development and validation sets. CONCLUSIONS HGS was in close relation to myosteatosis among inpatients with cirrhosis.
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Affiliation(s)
- Chao Sun
- Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Anshan Road 154, Heping District, Tianjin 300052, China
- Tianjin Institute of Digestive Disease, Tianjin Medical University General Hospital , Anshan Road 154, Heping District, Tianjin 300052, China
| | - Tianming Zhao
- Department of Gastroenterology, Nanjing Drum Tower Hospital, Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences & Peking Union Medical College, Jiangsu, Nanjing, 210008, China
| | - Wanting Yang
- Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Anshan Road 154, Heping District, Tianjin 300052, China
- Tianjin Institute of Digestive Disease, Tianjin Medical University General Hospital , Anshan Road 154, Heping District, Tianjin 300052, China
| | - Gaoyue Guo
- Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Anshan Road 154, Heping District, Tianjin 300052, China
- Tianjin Institute of Digestive Disease, Tianjin Medical University General Hospital , Anshan Road 154, Heping District, Tianjin 300052, China
| | - Han Wang
- Department of Health Management, Tianjin Hospital, No. 406 Jiefang South Road, Hexi District, Tianjin 300211, China
| | - Chaoqun Li
- Department of Internal Medicine, Tianjin Hexi Hospital, Qiongzhou Road 43, Hexi District, Tianjin 300202, China
| | - Yangyang Hui
- Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Anshan Road 154, Heping District, Tianjin 300052, China
- Tianjin Institute of Digestive Disease, Tianjin Medical University General Hospital , Anshan Road 154, Heping District, Tianjin 300052, China
| | - Binxin Cui
- Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Anshan Road 154, Heping District, Tianjin 300052, China
- Department of Gastroenterology, Tianjin Medical University General Hospital Airport Hospital, East Street 6, Tianjin Airport Economic Area, Tianjin 300308, China
| | - Xiaoyu Wang
- Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Anshan Road 154, Heping District, Tianjin 300052, China
- Tianjin Institute of Digestive Disease, Tianjin Medical University General Hospital , Anshan Road 154, Heping District, Tianjin 300052, China
| | - Xiaofei Fan
- Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Anshan Road 154, Heping District, Tianjin 300052, China
- Tianjin Institute of Digestive Disease, Tianjin Medical University General Hospital , Anshan Road 154, Heping District, Tianjin 300052, China
| | - Xingliang Zhao
- Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Anshan Road 154, Heping District, Tianjin 300052, China
- Tianjin Institute of Digestive Disease, Tianjin Medical University General Hospital , Anshan Road 154, Heping District, Tianjin 300052, China
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Montserrat Ortiz N, Trujillano Cabello J, Badia Castelló M, Vilanova Corsellas J, Jimenez Jimenez G, Rubio Ruiz J, Pujol Freire A, Morales Hernandez D, Servia Goixart L. Implementation of a major trauma team. Analysis of activation and care times in patients admitted to the ICU. Med Intensiva 2023; 47:427-436. [PMID: 36470735 DOI: 10.1016/j.medine.2022.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 08/27/2022] [Indexed: 06/17/2023]
Abstract
OBJECTIVE To analyze the factors associated with the activation of the severe trauma care team (STAT) in patients admitted to the ICU, to measure its impact on care times, and to analyze the groups of patients according to activation and level of anatomical involvement. DESIGN Prospective cohort study of severe trauma admitted to the ICU. From June 2017 to May 2019. Risk factors for the activation of the STAT analysed with logistic regression and CART type classification tree. SETTING Second level hospital ICU. PATIENTS Patients admitted consecutively. INTERVENTIONS No. MAIN VARIABLES OF INTEREST STAT activation. Demographic variables. Injury severity (ISS), intentionality, mechanism, assistance times, evolutionary complications, and mortality. RESULTS A total of 188 patients were admitted (46.8% of STAT activation), median age of 52 (37-64) years (activated 47 (27-62) vs not activated 55 (42-67) P = 0.023), males 84.0%. No difference in mortality according to activation. The logistic model finds as factors: care (16.6 (2.1-13.2)) and prehospital intubation (4.2 (1.8-9.8)) and severe lower extremity injury (4.4 (1.6-12.3)). Accidental fall (0.2 (0.1-0.6)) makes activation less likely. The CART model selects the type of trauma mechanism and can separate high and low energy trauma. CONCLUSIONS Factors associated with STAT activation were prehospital care, requiring prior intubation, high-energy mechanisms, and severe lower extremity injuries. Shorter care times if activated without influencing mortality. We must improve activation in older patients with low-energy trauma and without prehospital care.
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Affiliation(s)
- N Montserrat Ortiz
- Servicio de Medicina Intensiva, Hospital Arnau de Vilanova de Lleida, Spain; IRBLLeida (Institut de Recerca Biomèdica de Lleida. Fundació Dr. Pifarré), Spain
| | - J Trujillano Cabello
- Servicio de Medicina Intensiva, Hospital Arnau de Vilanova de Lleida, Spain; IRBLLeida (Institut de Recerca Biomèdica de Lleida. Fundació Dr. Pifarré), Spain
| | - M Badia Castelló
- Servicio de Medicina Intensiva, Hospital Arnau de Vilanova de Lleida, Spain; IRBLLeida (Institut de Recerca Biomèdica de Lleida. Fundació Dr. Pifarré), Spain
| | - J Vilanova Corsellas
- Servicio de Medicina Intensiva, Hospital Arnau de Vilanova de Lleida, Spain; IRBLLeida (Institut de Recerca Biomèdica de Lleida. Fundació Dr. Pifarré), Spain
| | - G Jimenez Jimenez
- Servicio de Medicina Intensiva, Hospital Arnau de Vilanova de Lleida, Spain; IRBLLeida (Institut de Recerca Biomèdica de Lleida. Fundació Dr. Pifarré), Spain
| | - J Rubio Ruiz
- Servicio de Medicina Intensiva, Hospital Arnau de Vilanova de Lleida, Spain; IRBLLeida (Institut de Recerca Biomèdica de Lleida. Fundació Dr. Pifarré), Spain
| | - A Pujol Freire
- Servicio de Medicina Intensiva, Hospital Arnau de Vilanova de Lleida, Spain; IRBLLeida (Institut de Recerca Biomèdica de Lleida. Fundació Dr. Pifarré), Spain
| | - D Morales Hernandez
- Servicio de Medicina Intensiva, Hospital Arnau de Vilanova de Lleida, Spain; IRBLLeida (Institut de Recerca Biomèdica de Lleida. Fundació Dr. Pifarré), Spain
| | - L Servia Goixart
- Servicio de Medicina Intensiva, Hospital Arnau de Vilanova de Lleida, Spain; IRBLLeida (Institut de Recerca Biomèdica de Lleida. Fundació Dr. Pifarré), Spain.
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Lehr AR, Hébert P, Fergusson D, Sabri E, Lacroix J. Association Between Length of Storage of Transfused Packed RBC Units and Outcome of Surgical Critically Ill Adults: A Subgroup Analysis of the Age of Blood Evaluation Randomized Trial. Crit Care Med 2023; 51:e73-e80. [PMID: 36728823 DOI: 10.1097/ccm.0000000000005775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVES The Age of Blood Evaluation (ABLE) study reported no clinical benefit in fresher compared with standard delivery RBC units (length of storage: 6.9 ± 4.1 vs 22.0 ± 8.4 d, respectively). Perioperative patients are often anemic, at risk of blood loss, and more exposed to RBC transfusions. We address the question whether fresh RBC units are safer than standard delivery RBC units in perioperative ICU patients. DESIGN Subgroup analysis of surgical nontrauma adults enrolled in the ABLE randomized controlled trial. SETTING ICUs. PATIENTS Three hundred twenty surgical patients among the 2,510 ICU adults recruited in the ABLE study who had a request for a first RBC transfusion in the first week in ICU stay and an anticipated length of mechanical ventilation greater than or equal to 48 hours. We included perioperative patients but excluded elective cardiac surgery and trauma. INTERVENTIONS Surgical participants were allocated to receive either RBC units stored less than or equal to 7 days or standard issue RBC. MEASUREMENTS AND MAIN RESULTS The primary outcome was 90-day all-cause mortality. One hundred seventy-two perioperative patients were allocated to the fresh and 148 to the standard group. Baseline data were similar. The length of storage was 7.2 ± 6.4 in fresh and 20.6 ± 8.4 days in standard group ( p < 0.0001). The 90-day mortality was 29.7% and 28.4%, respectively (absolute risk difference: 0.01; 95% CI -0.09 to 0.11; p = 0.803). No significant differences were observed for all secondary outcomes, including 6-month mortality, even after adjustment for age, country, and Acute Physiology and Chronic Health Evaluation score. CONCLUSIONS There was no evidence that fresh red cells improved outcomes as compared to standard issue red cells in critically ill surgical patients, consistent with other patients enrolled in the ABLE trial.
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Affiliation(s)
- Anab Rebecca Lehr
- Department of Pediatrics, Montreal Children Hospital, McGill University, Montreal, QC, Canada
| | - Paul Hébert
- Department of Medicine, Bruyere Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - Dean Fergusson
- Ottawa Hospital Research Institute, Department of Clinical Epidemiology Program and University of Ottawa, Ottawa, ON, Canada
- Departments of Medicine, Surgery, Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Elham Sabri
- Ottawa Hospital Research Institute, Department of Clinical Epidemiology Program and University of Ottawa, Ottawa, ON, Canada
| | - Jacques Lacroix
- Centre Hospitalier Universitaire Sainte Justine, Département de Pédiatrie de l'Université de Montréal, Montréal, QC, Canada
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Montserrat Ortiz N, Trujillano Cabello J, Badia Castelló M, Vilanova Corsellas J, Jimenez Jimenez G, Rubio Ruiz J, Pujol Freire A, Morales Hernandez D, Servia Goixart L. Implantación de un equipo de asistencia al trauma grave. Análisis de la activación y tiempos de asistencia en pacientes ingresados en UCI. Med Intensiva 2022. [DOI: 10.1016/j.medin.2022.08.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Employing biochemical biomarkers for building decision tree models to predict bipolar disorder from major depressive disorder. J Affect Disord 2022; 308:190-198. [PMID: 35439462 DOI: 10.1016/j.jad.2022.03.080] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 03/08/2022] [Accepted: 03/18/2022] [Indexed: 12/20/2022]
Abstract
BACKGROUND Conventional biochemical parameters may have predictive values for use in clinical identification between bipolar disorder (BD) and major depressive disorder (MDD). METHODS This study enrolled 2470 hospitalized patients with BD (n = 1333) or MDD (n = 1137) at reproductive age from 2009 to 2018 in China. We extracted 8 parameters, uric acid (UA), direct bilirubin (DBIL), indirect bilirubin (IDBIL), lactic dehydrogenase (LDH), free triiodothyronine (FT3), thyroid-stimulating hormone (TSH), high-density lipoprotein (HDL) and prealbumin of male, patients and 12 parameters, UA, DBIL, IBIL, LDH, FT3, TSH, glutamic-pyruvic transaminase (GPT), white blood cell (WBC), alkaline phosphatase (ALP), fasting blood glucose (FBG), triglyceride and low-density lipoprotein (LDL) of female patients. Backward stepwise multivariate regression analysis and the Chi-Square Automatic Interaction Detection (CHAID) segmentation analysis via SPSS Decision Tree were implemented to define the discrimination of BD and MDD. RESULTS DBIL was extracted as the first splitting variable, with LDH and IBIL as the second, TSH and prealbumin as the third in the model of male patients (p-value < .05). For the model of female patients, DBIL was also extracted as the first splitting variable, with UA, LDH, and IBIL as the second, triglyceride and FT3 as the third (p-value < .05). The predictive accuracies of the Decision Tree and multiple logistic regression models were similar (74.9% vs 76.9% in males; 74.4% vs 79.5% in females). CONCLUSIONS This study suggests the value of the Decision Tree models, which employ biochemical parameters as diagnostic predictors for BD and MDD. The CHAID Decision Tree identified that patients with concomitantly increased LDH, IBIL, and decreased DBIL could be in the group that showed the highest risk of being diagnosed as BD.
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Abstract
In meta-analysis, heterogeneity often exists between studies. Knowledge about study features (i.e., moderators) that can explain the heterogeneity in effect sizes can be useful for researchers to assess the effectiveness of existing interventions and design new potentially effective interventions. When there are multiple moderators, they may amplify or attenuate each other's effect on treatment effectiveness. However, in most meta-analysis studies, interaction effects are neglected due to the lack of appropriate methods. The method meta-CART was recently proposed to identify interactions between multiple moderators. The analysis result is a tree model in which the studies are partitioned into more homogeneous subgroups by combinations of moderators. This paper describes the R-package metacart, which provides user-friendly functions to conduct meta-CART analyses in R. This package can fit both fixed- and random-effects meta-CART, and can handle dichotomous, categorical, ordinal and continuous moderators. In addition, a new look ahead procedure is presented. The application of the package is illustrated step-by-step using diverse examples.
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Affiliation(s)
- Xinru Li
- Mathematical Institute, Leiden University, P.O. Box 9512, 2300, RA, Leiden, The Netherlands
| | - Elise Dusseldorp
- Institute of Psychology, Leiden University, P.O. Box 9555, 2300, RB, Leiden, The Netherlands.
| | - Xiaogang Su
- Department of Mathematical Sciences, University of Texas at El Paso, Austin, TX, 78712, USA
| | - Jacqueline J Meulman
- Mathematical Institute, Leiden University, P.O. Box 9512, 2300, RA, Leiden, The Netherlands
- Department of Statistics, Stanford University, Stanford, CA, 94305, USA
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Serviá L, Montserrat N, Badia M, Llompart-Pou JA, Barea-Mendoza JA, Chico-Fernández M, Sánchez-Casado M, Jiménez JM, Mayor DM, Trujillano J. Machine learning techniques for mortality prediction in critical traumatic patients: anatomic and physiologic variables from the RETRAUCI study. BMC Med Res Methodol 2020; 20:262. [PMID: 33081694 PMCID: PMC7576744 DOI: 10.1186/s12874-020-01151-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Accepted: 10/15/2020] [Indexed: 02/07/2023] Open
Abstract
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 model, and the BN obtains the best recall, F-measure, and AUC. Conclusion Machine learning techniques are useful for creating mortality classification models in critically traumatic patients. With clinical interpretation, the algorithms establish different patient profiles according to the relationship between the variables used, determine groups of patients with different evolutions, and alert clinicians to the presence of rules that indicate the greatest severity.
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Affiliation(s)
- Luis Serviá
- Servei de Medicina Intensiva, Hospital Universitari Arnau de Vilanova, Universitat de Lleida, IRBLleida, Avda Rovira Roure 80, 25198, Lleida, Spain
| | - Neus Montserrat
- Servei de Medicina Intensiva, Hospital Universitari Arnau de Vilanova, Universitat de Lleida, IRBLleida, Avda Rovira Roure 80, 25198, Lleida, Spain
| | - Mariona Badia
- Servei de Medicina Intensiva, Hospital Universitari Arnau de Vilanova, Universitat de Lleida, IRBLleida, Avda Rovira Roure 80, 25198, Lleida, Spain
| | - Juan Antonio Llompart-Pou
- Servei de Medicina Intensiva, Hospital Universitari Son Espases, Institut de Investigació Sanitària Illes Balears, Palma de Mallorca, Spain
| | - Jesús Abelardo Barea-Mendoza
- UCI de Trauma y Emergencias, Servicio de Medicina Intensiva, Hospital Universitario 12 de Octubre, Madrid, Spain
| | - Mario Chico-Fernández
- UCI de Trauma y Emergencias, Servicio de Medicina Intensiva, Hospital Universitario 12 de Octubre, Madrid, Spain
| | | | - José Manuel Jiménez
- Servicio de Medicina Intensiva, Hospital Universitario Puerta del Mar, Cádiz, Spain
| | - Dolores María Mayor
- Servicio de Medicina Intensiva, Complejo hospitalario de Torrecárdenas, Almería, Spain
| | - Javier Trujillano
- Servei de Medicina Intensiva, Hospital Universitari Arnau de Vilanova, Universitat de Lleida, IRBLleida, Avda Rovira Roure 80, 25198, Lleida, Spain.
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Gravedad en pacientes traumáticos ingresados en UCI. Modelos fisiológicos y anatómicos. Med Intensiva 2019; 43:26-34. [DOI: 10.1016/j.medin.2017.11.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Revised: 10/28/2017] [Accepted: 11/14/2017] [Indexed: 11/20/2022]
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Chen W, Sun C, Wei R, Zhang Y, Ye H, Chi R, Zhang Y, Hu B, Lv B, Chen L, Zhang X, Lan H, Chen C. Establishing Decision Trees for Predicting Successful Postpyloric Nasoenteric Tube Placement in Critically Ill Patients. JPEN J Parenter Enteral Nutr 2018; 42:132-138. [PMID: 29505136 DOI: 10.1177/0148607116667282] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Accepted: 08/08/2016] [Indexed: 01/09/2023]
Abstract
BACKGROUND Despite the use of prokinetic agents, the overall success rate for postpyloric placement via a self-propelled spiral nasoenteric tube is quite low. METHODS This retrospective study was conducted in the intensive care units of 11 university hospitals from 2006 to 2016 among adult patients who underwent self-propelled spiral nasoenteric tube insertion. Success was defined as postpyloric nasoenteric tube placement confirmed by abdominal x-ray scan 24 hours after tube insertion. Chi-square automatic interaction detection (CHAID), simple classification and regression trees (SimpleCart), and J48 methodologies were used to develop decision tree models, and multiple logistic regression (LR) methodology was used to develop an LR model for predicting successful postpyloric nasoenteric tube placement. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of these models. RESULTS Successful postpyloric nasoenteric tube placement was confirmed in 427 of 939 patients enrolled. For predicting successful postpyloric nasoenteric tube placement, the performance of the 3 decision trees was similar in terms of the AUCs: 0.715 for the CHAID model, 0.682 for the SimpleCart model, and 0.671 for the J48 model. The AUC of the LR model was 0.729, which outperformed the J48 model. CONCLUSION Both the CHAID and LR models achieved an acceptable discrimination for predicting successful postpyloric nasoenteric tube placement and were useful for intensivists in the setting of self-propelled spiral nasoenteric tube insertion.
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Affiliation(s)
- Weisheng Chen
- Department of Critical Care Medicine, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Cheng Sun
- Department of Critical Care Medicine, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Ru Wei
- Department of Child Health Care, Guangzhou Women and Children's Medical Center, Guangzhou, China
| | - Yanlin Zhang
- Department of Critical Care Medicine, Xinjiang Kashgar Region's First People's Hospital, Kashgar, China
| | - Heng Ye
- Department of Critical Care Medicine, Guangzhou Nansha Central Hospital, Guangzhou, China
| | - Ruibin Chi
- Department of Critical Care Medicine, Xiaolan People's Hospital of Zhongshan, Zhongshan, China
| | - Yichen Zhang
- Department of Critical Care Medicine, Guangzhou Red Cross Hospital, Guangzhou, China
| | - Bei Hu
- Department of Critical Care Medicine, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Bo Lv
- Department of Critical Care Medicine, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Lifang Chen
- Department of Critical Care Medicine, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xiunong Zhang
- Department of Critical Care Medicine, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Huilan Lan
- Department of Critical Care Medicine, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Chunbo Chen
- Department of Critical Care Medicine, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
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Last M, Tosas O, Gallo Cassarino T, Kozlakidis Z, Edgeworth J. Evolving classification of intensive care patients from event data. Artif Intell Med 2016; 69:22-32. [PMID: 27235802 DOI: 10.1016/j.artmed.2016.04.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Revised: 04/16/2016] [Accepted: 04/19/2016] [Indexed: 10/21/2022]
Abstract
OBJECTIVE This work aims at predicting the patient discharge outcome on each hospitalization day by introducing a new paradigm-evolving classification of event data streams. Most classification algorithms implicitly assume the values of all predictive features to be available at the time of making the prediction. This assumption does not necessarily hold in the evolving classification setting (such as intensive care patient monitoring), where we may be interested in classifying the monitored entities as early as possible, based on the attributes initially available to the classifier, and then keep refining our classification model at each time step (e.g., on daily basis) with the arrival of additional attributes. MATERIALS AND METHODS An oblivious read-once decision-tree algorithm, called information network (IN), is extended to deal with evolving classification. The new algorithm, named incremental information network (IIN), restricts the order of selected features by the temporal order of feature arrival. The IIN algorithm is compared to six other evolving classification approaches on an 8-year dataset of adult patients admitted to two Intensive Care Units (ICUs) in the United Kingdom. RESULTS Retrospective study of 3452 episodes of adult patients (≥16years of age) admitted to the ICUs of Guy's and St. Thomas' hospitals in London between 2002 and 2009. Random partition (66:34) into a development (training) set n=2287 and validation set n=1165. Episode-related time steps: Day 0-time of ICU admission, Day x-end of the x-th day at ICU. The most accurate decision-tree models, based on the area under curve (AUC): Day 0: IN (AUC=0.652), Day 1: IIN (AUC=0.660), Day 2: J48 decision-tree algorithm (AUC=0.678), Days 3-7: regenerative IN (AUC=0.717-0.772). Logistic regression AUC: 0.582 (Day 0)-0.827 (Day 7). CONCLUSIONS Our experimental results have not identified a single optimal approach for evolving classification of ICU episodes. On Days 0 and 1, the IIN algorithm has produced the simplest and the most accurate models, which incorporate the temporal order of feature arrival. However, starting with Day 2, regenerative approaches have reached better performance in terms of predictive accuracy.
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Affiliation(s)
- Mark Last
- Department of Information Systems Engineering, Ben-Gurion University of the Negev, Marcus Family Campus, Rager St., Beer-Sheva 84105, Israel.
| | - Olga Tosas
- Department of Infectious Diseases, Guy's and St. Thomas' NHS foundation Trust, Westminster Bridge Road, London SE1 7EH, United Kingdom.
| | - Tiziano Gallo Cassarino
- The Farr Institute of Health Informatics Research, University College London, 222 Euston Road, London NW1 2DA, United Kingdom.
| | - Zisis Kozlakidis
- The Farr Institute of Health Informatics Research, University College London, 222 Euston Road, London NW1 2DA, United Kingdom.
| | - Jonathan Edgeworth
- Department of Infectious Diseases, Guy's and St. Thomas' NHS foundation Trust, Westminster Bridge Road, London SE1 7EH, United Kingdom.
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[Mortality predictive factors in patients with urinary sepsis associated to upper urinary tract calculi]. Med Intensiva 2014; 39:290-7. [PMID: 25444058 DOI: 10.1016/j.medin.2014.07.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2014] [Revised: 07/05/2014] [Accepted: 07/14/2014] [Indexed: 11/21/2022]
Abstract
PURPOSE The aims of this study were to determine the clinical characteristics of patients with urinary sepsis associated to ureteral calculi admitted to the Intensive Care Unit (ICU), and to identify predictors of mortality in the first 24 hours of admission. DESIGN A retrospective observational study covering a 16-year period (2006-2011) was carried out. SETTING The combined clinical/surgical ICU of a secondary-level University hospital. PATIENTS All patients admitted to the ICU due to obstructive urinary sepsis. INTERVENTIONS None. MAIN VARIABLES We analyzed general clinical and laboratory test and urological data. The diagnostic technique, affected side, decompression technique, isolated microorganism and antibiotic therapy used were also considered. The assessment of risk factors was performed by multiple logistic regression analysis. RESULTS A total of 107 patients admitted to the ICU were included in the study, with a mortality rate of 19.6%. The diagnosis was mainly established by ultrasound, and the most commonly used decompression technique was retrograde JJ stenting. Microorganisms were isolated in 48.6% of the patients. In total, 20.6% of the patients had bacteremia. Multivariate analysis found age, acute renal failure and the use of vasoactive drugs administered continuously for the first 24 hours of admission to be independently associated to mortality. CONCLUSIONS Advanced age, acute renal failure and the need for vasoactive drugs were associated to an increased risk of mortality in patients with urinary sepsis associated to upper urinary tract calculi.
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Bellury L, Ellington L, Beck SL, Pett MA, Clark J, Stein K. Older breast cancer survivors: can interaction analyses identify vulnerable subgroups? A report from the American Cancer Society Studies of Cancer Survivors. Oncol Nurs Forum 2014; 40:325-36. [PMID: 23803266 DOI: 10.1188/13.onf.325-336] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
PURPOSE/OBJECTIVES To explore interactions among personal, cancer, aging, and symptom variables relative to physical function (PF) in older adult breast cancer survivors to better identify vulnerable subgroups. DESIGN Secondary analysis of the American Cancer Society Studies of Cancer Survivors II. SETTING U.S. population-based mail and telephone survey. SAMPLE 2,885 breast cancer survivors from 14 different state cancer registries stratified by cancer type and time since diagnosis. A total of 184 female breast cancer survivors, aged 70 years or older, had complete data on variables of interest and were, therefore, included in this analysis. METHODS Chi-Square Automatic Interaction Detector (CHAID) analysis was used to examine variable interactions. MAIN RESEARCH VARIABLES PF, symptom bother, comorbidity, social support, length of survivorship, treatment, stage, body mass index, physical activity, emotional health, and personal characteristics. FINDINGS An interaction effect between symptom bother and comorbidity was found in 39% of older adult breast cancer survivors, and an interaction effect between symptom bother and marital status was found in 40%. The most vulnerable group (8%) had high symptom bother and more than four comorbid conditions. CONCLUSIONS Symptom bother, comorbidity, and marital status were found to have significant interactions such that high comorbidity and high symptom bother were significantly related to lower PF. Married participants with lower symptom bother had significantly higher PF scores. Comorbidity may be the best predictor of PF for the extreme ends of the symptom bother continuum. Advancing age alone was not a sufficient predictor of PF in this analysis. IMPLICATIONS FOR NURSING Specific attention to symptom reports, comorbidity, and marital status can guide identification of older adult cancer survivors in need of ongoing survivorship care. The findings support use of a comprehensive assessment and tailored approach to care based on factors other than age. KNOWLEDGE TRANSLATION CHAID interaction analysis may be useful in exploring complex nursing problems, such as the needs of older adult cancer survivors, and help oncology nurses develop appropriate interventions and referrals.
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Affiliation(s)
- Lanell Bellury
- Georgia Baptist College of Nursing, Mercer University, Atlanta, GA, USA.
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Castelló González M, Bueno Rodríguez JC, Hernández Moore E, Aguilar Atanay D. Predictors of recurrent appendicitis after non-operative management of children with perforated appendicitis presenting with an appendicular inflammatory mass. Arch Dis Child 2014; 99:154-7. [PMID: 24214939 DOI: 10.1136/archdischild-2012-303400] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
AIM To determine clinical and imaging predictors of recurrent appendicitis after non-operative management for children with perforated appendicitis presenting with an appendicular inflammatory mass. METHODS A case-control study was carried out of children with clinical and ultrasonographic diagnosis of an appendicular inflammatory mass. Patients were divided into two groups according to the presence or not of recurrent appendicitis (or predisposing pathological findings during interval appendectomy). Several clinical and imaging factors were compared between both groups using an independent and progressive analysis to identify which were the most relevant predictors. RESULTS The persistence of symptoms after resolution of the appendicular inflammatory mass, as well as its time of resolution (p<0.001), were the most relevant factors during group classification. The identification of an ultrasonographic image of an appendicolith and the initial size of the mass were also identified as independent predictors (p<0.018 and p<0.01). The presence of the first two factors in a patient was strongly associated with recurrent appendicitis. CONCLUSIONS Persistent symptoms after the recovery of the initial episode, associated with a slow resolution of the appendicular inflammatory mass, are indications for an interval appendectomy. A previous history of appendicitis or detection of an ultrasonographic image of an appendicolith is the other indication for an interval appendectomy.
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Affiliation(s)
- Mauro Castelló González
- Department of Pediatric Surgery, Pediatric Hospital "Dr. Eduardo Agramonte Piña", Camagüey, Cuba
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Jarvis SW, Kovacs C, Badriyah T, Briggs J, Mohammed MA, Meredith P, Schmidt PE, Featherstone PI, Prytherch DR, Smith GB. Development and validation of a decision tree early warning score based on routine laboratory test results for the discrimination of hospital mortality in emergency medical admissions. Resuscitation 2013; 84:1494-9. [DOI: 10.1016/j.resuscitation.2013.05.018] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2013] [Revised: 05/11/2013] [Accepted: 05/24/2013] [Indexed: 11/24/2022]
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Alge JL, Karakala N, Neely BA, Janech MG, Tumlin JA, Chawla LS, Shaw AD, Arthur JM. Association of elevated urinary concentration of renin-angiotensin system components and severe AKI. Clin J Am Soc Nephrol 2013; 8:2043-52. [PMID: 24009222 DOI: 10.2215/cjn.03510413] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
BACKGROUND Prognostic biomarkers that predict the severity of AKI at an early time point are needed. Urinary angiotensinogen was recently identified as a prognostic AKI biomarker. The study hypothesis is that urinary renin could also predict AKI severity and that in combination angiotensinogen and renin would be a strong predictor of prognosis at the time of AKI diagnosis. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS In this multicenter, retrospective cohort study, urine was obtained from 204 patients who developed AKI after cardiac surgery from August 2008 to June 1, 2012. All patients were classified as having Acute Kidney Injury Network (AKIN) stage 1 disease by serum creatinine criteria at the time of sample collection. Urine output was not used for staging. Urinary angiotensinogen and renin were measured, and the area under the receiver-operating characteristic curve (AUC) was used to test for prediction of progression to AKIN stage 3 or in-hospital 30-day mortality. These biomarkers were added stepwise to a clinical model, and improvement in prognostic predictive performance was evaluated by category free net reclassification improvement (cfNRI) and chi-squared automatic interaction detection (CHAID). RESULTS Both the urinary angiotensinogen-to-creatinine ratio (uAnCR; AUC, 0.75; 95% confidence interval [CI], 0.65 to 0.85) and the urinary renin-to-creatinine ratio (uRenCR; AUC, 0.70; 95% CI, 0.57 to 0.83) predicted AKIN stage 3 or death. Addition of uAnCR to a clinical model substantially improved prediction of the outcome (AUC, 0.85; cfNRI, 0.673), augmenting sensitivity and specificity. Further addition of uRenCR increased the sensitivity of the model (cfNRI(events), 0.44). CHAID produced a highly accurate model (AUC, 0.91) and identified the combination of uAnCR >337.89 ng/mg and uRenCR >893.41 pg/mg as the strongest predictors (positive predictive value, 80.4%; negative predictive value, 90.7%; accuracy, 90.2%). CONCLUSION The combination of urinary angiotensinogen and renin predicts progression to very severe disease in patients with early AKI after cardiac surgery.
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Affiliation(s)
- Joseph L Alge
- Medical University of South Carolina, Charleston, South Carolina;, †University of Tennessee College of Medicine in Chattanooga, Chattanooga, Tennessee;, ‡George Washington University, Washington, DC;, §Duke University, Durham, North Carolina;, ‖Durham Veterans Affairs Medical Center, Durham, North Carolina, ¶Ralph H. Johnson Veterans Affairs Medical Center, Charleston, South Carolina
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Serviá Goixart L, Badia Castelló M, Montserrat Ortiz N, Bello Rodriguez G, Vicario Izquierdo E, Vilanova Corselles J, Trujillano Cabello J. [Risk factors for the deterioration of quality of life in critical trauma patients. Assessment at 6 and 12 months after discharge from the intensive care unit]. Med Intensiva 2013; 38:1-10. [PMID: 23306607 DOI: 10.1016/j.medin.2012.10.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2012] [Revised: 10/02/2012] [Accepted: 10/20/2012] [Indexed: 12/01/2022]
Abstract
OBJECTIVE To evaluate factors influencing the deterioration of health-related quality of life (HRQoL) in trauma patients admitted to an ICU. DESIGN A prospective observational study was carried out. SETTING The combined medical/surgical ICU in a university secondary hospital with 24-hour neurosurgery service. PATIENTS Trauma patients admitted to the ICU during a two-year period. HRQoL assessment prior to admission to the ICU, and at 6 and 12 months after discharge. MAIN VARIABLES Demographic variables, type and severity of injury (AIS), severity (APACHE II, ISS, TRISS), length of stay, procedures, mortality and HRQoL according to the SF-36 and EQ-5D. RESULTS We completed the monitoring of 110 patients that showed significant impairment of their HRQoL in all the dimensions assessed. According to the SF-36, physical role was more deteriorated at 12 months, but the mental component decreased more than the physical component after 6 months. The VAS scale of the EQ-5D decreased to 55 at 6 months (19) and increased to 66 at 12 months (17). In the multiple logistic regression analysis, the variables associated with poorer HRQoL were age > 45 years, TRISS > 10, previous porer quality of life, and serious injuries in the extremities. CONCLUSIONS Patients showed marked deterioration of their HRQoL at 6 months, followed by overall improvement at 12 months, though without reaching their previous state. The factors that determine poorer quality of life include age, severity, previous HRQoL, and severe injuries in the extremities.
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Affiliation(s)
- L Serviá Goixart
- Servicio de Medicina Intensiva, Hospital Universitario Arnau de Vilanova, Lleida, España.
| | - M Badia Castelló
- Servicio de Medicina Intensiva, Hospital Universitario Arnau de Vilanova, Lleida, España
| | - N Montserrat Ortiz
- Servicio de Medicina Intensiva, Hospital Universitario Arnau de Vilanova, Lleida, España
| | - G Bello Rodriguez
- Servicio de Medicina Intensiva, Hospital Universitario Arnau de Vilanova, Lleida, España
| | - E Vicario Izquierdo
- Servicio de Medicina Intensiva, Hospital Universitario Arnau de Vilanova, Lleida, España
| | - J Vilanova Corselles
- Servicio de Medicina Intensiva, Hospital Universitario Arnau de Vilanova, Lleida, España
| | - J Trujillano Cabello
- Servicio de Medicina Intensiva, Hospital Universitario Arnau de Vilanova, Lleida, España; Departamento de Ciencias Médicas Básicas, Universidad de Lleida, IRBLLEIDA, Lleida, España
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Avilés-Jurado FX, León X. Prognostic factors in head and neck squamous cell carcinoma: comparison of CHAID decision trees technology and Cox analysis. Head Neck 2012; 35:877-83. [PMID: 22711263 DOI: 10.1002/hed.23058] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/21/2012] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND The purpose of this study was to compare the risk factors obtained from a classical statistical method (Cox proportional hazards model) and the results obtained with classification trees (Chi-square Automatic Interaction Detection [CHAID] model) in head and neck squamous cell carcinoma (HNSCC). METHODS We conducted a retrospective study of 3373 patients with HNSCC and a follow-up longer than 2 years. RESULTS The most decisive variable classified by CHAID was T category. N classification was an important prognostic factor in the Cox analysis, but this was not considered in CHAID except in T2 and supraglottic T3. CHAID also indicated that women with oral cavity T3/T4 to N0 tumors had poorer prognosis (28%) than men (58.5%; p value < .001). In oropharynx location, men had lower survival than women (41% vs 72%; p value < .001). CONCLUSIONS The main benefit of CHAID analysis is that it identifies a relatively small number of patients with a singular behavior, which is more discriminatory for an optimal diagnosis and treatment.
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Affiliation(s)
- Francesc Xavier Avilés-Jurado
- Otorhinolaryngology Head-Neck Surgery Department, Hospital Universitari de Tarragona Joan XXIII, Tarragona, Catalonia, Spain.
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A simple classification model for hospital mortality in patients with acute lung injury managed with lung protective ventilation. Crit Care Med 2012; 39:2645-51. [PMID: 21725235 DOI: 10.1097/ccm.0b013e3182266779] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
OBJECTIVE Despite improvements in the care of critically ill patients, hospital mortality rate for acute lung injury remains high at approximately 40%. We developed a classification rule to stratify mechanically ventilated patients with acute lung injury according to hospital mortality and compared this rule with the Acute Physiology and Chronic Health Evaluation III prediction. PATIENTS We used data of 2,022 participants in Acute Respiratory Distress Syndrome Network trials to build a classification rule based on 54 variables collected before randomization. DESIGN We used a classification tree approach to stratify patients according to hospital mortality using a training subset of 1800 participants and estimated expected prediction errors using tenfold crossvalidation. We validated our classification tree using a subset of 222 participants not included in model building and calculated areas under the receiver operating characteristic curves. MEASUREMENTS AND MAIN RESULTS We identified combinations of age (>63 yrs), blood urea nitrogen (>15 mg/dL), shock, respiratory rate (>21 breaths/min), and minute ventilation (>13.9 L/min) as important predictors of hospital mortality at 90 days. The classification tree had a similar expected prediction error in the training set (28% vs. 26%; p = .18) and areas under the receiver operating characteristic curve in the validation set (0.71 vs. 0.73; p = .71) as did a model based on Acute Physiology and Chronic Health Evaluation III. CONCLUSIONS Our tree-based classification rule performed similarly to Acute Physiology and Chronic Health Evaluation III in stratifying patients according to hospital mortality, is simpler to use, contains risk factors that may be specific to acute lung injury, and identified minute ventilation as a potential novel predictor of death in patients with acute lung injury.
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Hijosa-Valsero M, Sidrach-Cardona R, Martín-Villacorta J, Cruz Valsero-Blanco M, Bayona JM, Bécares E. Statistical modelling of organic matter and emerging pollutants removal in constructed wetlands. BIORESOURCE TECHNOLOGY 2011; 102:4981-4988. [PMID: 21324677 DOI: 10.1016/j.biortech.2011.01.063] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2010] [Revised: 01/18/2011] [Accepted: 01/19/2011] [Indexed: 05/30/2023]
Abstract
Multiple regression models, clustering tree diagrams, regression trees (CHAID) and redundancy analysis (RDA) were applied to the study of the removal of organic matter and pharmaceuticals and personal care products (PPCPs) from urban wastewater by means of constructed wetlands (CWs). These four statistical analyses pointed out the importance of physico-chemical parameters, plant presence and chemical structure in the elimination of most pollutants. Temperature, pH values, dissolved oxygen concentration, redox potential and conductivity were related to the removal of the studied substances. Plant presence (Typha angustifolia and Phragmites australis) enhanced the removal of organic matter and some PPCPs. Multiple regression equations and CHAID trees provided numerical estimations of pollutant removal efficiencies in CWs. These models were validated and they could be a useful and interesting tool for the quick estimation of removal efficiencies in already working CWs and for the design of new systems which must fulfil certain quality requirements.
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Affiliation(s)
- María Hijosa-Valsero
- Departamento de Química y Física Aplicadas, Facultad de Ciencias Biológicas y Ambientales, Universidad de León, Campus de Vegazana, E-24071 León, Spain.
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Hamilton EF, Smith S, Yang L, Warrick P, Ciampi A. Third- and fourth-degree perineal lacerations: defining high-risk clinical clusters. Am J Obstet Gynecol 2011; 204:309.e1-6. [PMID: 21349493 DOI: 10.1016/j.ajog.2010.12.048] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2010] [Revised: 12/01/2010] [Accepted: 12/30/2010] [Indexed: 11/16/2022]
Abstract
OBJECTIVE Statistical methods that measure the independent contribution of individual factors for third-/fourth-degree perineal laceration (TFPL) fall short when the clinician is faced with a combination of factors. Our objective was to demonstrate how a statistical technique, classification and regression trees (CART), can identify high-risk clinical clusters. STUDY DESIGN We performed multivariable logistic regression, and CART analysis on data from 25,150 term vaginal births. RESULTS Multivariable analyses found strong associations with the use of episiotomy, forceps, vacuum, nulliparity, and birthweight. CART ranked episiotomy, operative delivery, and birthweight as the more discriminating factors and defined distinct risk groups with TFPL rates that ranged from 0-100%. For example, without episiotomy, the rate of TFPL was 2.2%. In the presence of an episiotomy, forceps, and birthweight of >3634 g, the rate of TFPL was 68.9%. CONCLUSION CART showed that certain combinations held low risk, where as other combinations carried extreme risk, which clarified how choices on delivery options can markedly affect the rate of TFPL for specific mothers.
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A classification and regression tree to assist clinical decision making in airway management for patients with cervical spinal cord injury. Spinal Cord 2010; 49:244-50. [PMID: 20697418 DOI: 10.1038/sc.2010.97] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
STUDY DESIGN This was a prospective observational study. OBJECTIVES To review airway management of patients with acute cervical spinal cord injury (CSCI) who are admitted to the intensive care unit (ICU) and to develop a classification and regression tree (CART) to direct clinical decision making in airway management. SETTING This study was carried out in Australia. METHODS All patients with CSCI who required intubation and mechanical ventilation and who were admitted to ICU in three tertiary hospitals in Melbourne between October 2004 and May 2009 and two other interstate hospitals between December 2004 and December 2005 were included. Airway management was recorded. RESULTS A total of 114 patients were included. Tracheostomy insertion occurred in 68 patients (59.7%). Using CART analysis, it was found that the variables forced vital capacity, the volume of pulmonary secretion and gas exchange were predictive of airway management on 82.3% occasions with an 8.7% extubation failure rate. CONCLUSION A CART can be useful in clinical decision making regarding airway management in CSCI.
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