Development of a new score for early mortality prediction in trauma ICU patients: RETRASCORE.

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.

Machine learning techniques for mortality prediction in critical traumatic patients: anatomic and physiologic variables from the RETRAUCI study.

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.

Left carotid adventitial vasa vasorum signal correlates directly with age and with left carotid intima-media thickness in individuals without atheromatous risk factors.

OBJECTIVE: The early identification of the onset of subclinical atheromatosis is essential in reducing the high mortality risk from cardiovascular disease (CVD) worldwide. Although carotid intima-media thickness (cIMT) is the most commonly used early predictor of ongoing atherosclerosis, an experimental model of atherosclerosis, demonstrated that increases in adventitial microvessels (vasa vasorum (VV)) precede endothelial dysfunction. Using the reported accuracy of contrast-enhanced ultrasound (CEU) to measure carotid adventitial VV, this study assessed whether measurements of carotid adventitial VV serve as a marker of subclinical atherosclerotic lesions in a control population with none of the classical risk factors for CVD. METHODS AND RESULTS: Measurements of cIMT (B-mode ultrasound) and adventitial VV (CEU) were conducted in 65 subjects, 30-70 years old, 48% men, with none of the classical risk factors for CVD. Adventitial VV strongly correlated with its own cIMT only in the left carotid artery. Importantly, the left carotid adventitial VV directly correlated with age. CONCLUSIONS: The increases with age in left carotid adventitial VV in individuals with zero risk for atheromatosis suggest that the measurement of carotid adventitial VV could be an accurate and sensitive marker for the diagnosis of subclinical atheromatosis and therefore a prominent tool for monitoring the efficacy of anti-atheromatous therapies.

Epidemiology of hamstring injuries in 538 cases from an FC Barcelona multi sports club.

OBJECTIVES: Hamstring injuries are the most common muscle injuries in team sports. The aims of this study were to describe the epidemiology of hamstring muscle injuries in the professional and amateur sport sections of a multi-sport club Football Club Barcelona (FCB) and to determine any potential correlation between return-to-play (RTP) and injury location, severity of connective tissue damage, age, sex, and athlete's level of competition. METHODS: This descriptive epidemiological study with data collected from September 2007 to September 2017 stored in the FCB database. The study included non-contact hamstring injuries sustained during training or competition. RESULTS: A total of 538 hamstring injuries were reported in the club's database, of which 240 were structurally verified by imaging as hamstring injuries. The overall incidence for the 17 sports studied was 1.29 structurally verified hamstring injuries per 100 athletes per year. The muscle most commonly involved in hamstring injuries was the biceps femoris, and the connective tissue most frequently involved was the myofascial. There was no evidence of a statistically significant association between age and RTP after injury, and no statistically significant difference between sex and RTP. However, the time loss by professionals was shorter than for amateurs, and proximal hamstring injuries took longer RTP than distal ones. CONCLUSION: In the 17 sports practiced at multi-sport club, the incidence of hamstring injury was 1.29 per 100 athletes per year. Players from sports in which high-speed sprinting and kicking are necessary, and amateurs, were at higher risk of suffering a hamstring injury. In addition, proximally located hamstring injuries involving tendinous connective tissue showed the longest RTP time. Age did not seem to have any influence on RTP. Documenting location and the exact tissue involved in hamstring injuries may be beneficial for determining the prognosis and RTP.

Assessment of Quality of Life Using the Kidslife Scale in Individuals With Cornelia de Lange Syndrome.

BACKGROUND: Cornelia de Lange syndrome (CdLS) is a rare polymalformative genetic disorder with multisystemic involvement. Despite numerous clinical and molecular studies, the specific evaluation of the quality of life (QoL) and its relationship with syndrome-specific risk factors has not been explored. METHODS: The QoL of 33 individuals diagnosed with CdLS, aged between 4 and 21 years, was assessed using the Kidslife questionnaire. Specifically, the influence of 14 risk factors on overall QoL and 8 of its domains was analyzed. RESULTS: The study revealed below-median QoL (45.3 percentile), with the most affected domains being physical well-being, personal development, and self-determination. When classifying patients based on their QoL and affected domains, variants in the NIPBL gene, clinical scores ≥11, and severe behavioral and communication issues were found to be the main risk factors. CONCLUSIONS: We emphasize the need for a comprehensive approach to CdLS that encompasses clinical, molecular, psychosocial, and emotional aspects. The "Kidslife questionnaire" proved to be a useful tool for evaluating QoL, risk factors, and the effectiveness of implemented strategies. In this study, we underscore the importance of implementing corrective measures to improve the clinical score. Furthermore, we highlight the necessity of applying specific therapies for behavioral problems after ruling out underlying causes such as pain or gastroesophageal reflux and implementing measures that facilitate communication and promote social interaction.

Preventive isolation criteria for the detection of multidrug-resistant bacteria in patients admitted to the Intensive Care Unit: A multicenter study within the Zero Resistance program.

OBJECTIVE: To verify the validity of a checklist of risk factors (RFs) proposed by the Spanish "Zero Resistance" project (ZR) in the detection of multidrug-resistant bacteria (MRB), and to identify other possible RFs for colonization and infection by MRB on admission to the Intensive Care Unit (ICU). DESIGN: A prospective cohort study, conducted in 2016. SETTING: Multicenter study, patients requiring admission to adult ICUs that applied the ZR protocol and accepted the invitation for participating in the study. PATIENTS OR PARTICIPANTS: Consecutive sample of patients admitted to the ICU and who underwent surveillance (nasal, pharyngeal, axillary and rectal) or clinical cultures. INTERVENTIONS: Analysis of the RFs of the ZR project, in addition to other comorbidities, included in the ENVIN registry. A univariate and multivariate analysis was performed, with binary logistic regression methodology (significance considered for p < 0.05). Sensitivity and specificity analyses were performed for each of the selected factors. MAIN VARIABLES OF INTEREST: Carrier of MRB on admission to the ICU, RFs (previous MRB colonization/infection, hospital admission in the previous 3 months, antibiotic use in the past month, institutionalization, dialysis, and other chronic conditions) and comorbidities. RESULTS: A total of 2270 patients from 9 Spanish ICUs were included. We identified MRB in 288 (12.6% of the total patients admitted). In turn, 193 (68.2%) had some RF (OR 4.6, 95%CI: 3.5-6.0). All 6 RFs from the checklist reached statistical significance in the univariate analysis (sensitivity 66%, specificity 79%). Immunosuppression, antibiotic use on admission to the ICU and the male gender were additional RFs for MRB. MRB were isolated in 87 patients without RF (31.8%). CONCLUSIONS: Patients with at least one RF had an increased risk of being carriers of MRB. However, almost 32% of the MRB were isolated in patients without RFs. Other comorbidities such as immunosuppression, antibiotic use on admission to the ICU and the male gender could be considered as additional RFs.

Comparison of heart, grace and TIMI scores to predict major adverse cardiac events from chest pain in a Spanish health care region.

Acute non-traumatic chest pain (ANTCP) is the second cause of consultation in the Emergency department (ED). About 70% of all Acute Myocardial Infarctions present as non persistent ST-elevation acute coronary syndrome (NSTE-ACS) in the electrocardiogram. Our aim was to compare whether the HEART risk score is more effective than the GRACE and TIMI scores for the diagnosis and prognosis of Major Adverse Cardiac Events (MACE) at six weeks in patients with ANTCP and NSTE-ACS. A prospective cohort study was conducted with patients with ANTCP that attended an ED and a Primary Care Emergency Center (PCEC) from April 2018 to December 2020. The primary outcome was MACE at six weeks. Diagnostic performance was calculated for each scale as the Area under the Receiver Operating Characteristic (ROC) curve (AUC), sensitivity (SE), specificity (SP), and predictive values (PV). Qualitative variables were compared using the Chi-square test, and continuous variables were compared using the nonparametric Kruskal-Wallis test. We adjusted a logistic regression for risk groups, age, and gender to determine the effect of the HEART, GRACE, and TIMI scores on MACE. The degree of agreement (kappa index) was calculated in the categorical classification of patients according to the three risk scales. Cox proportional hazards regressions were performed for each scale and were compared using partial likelihood ratio tests for non-nested models. From a sample of 317 patients with ANTCP, 14.82% had MACE at six weeks. The AUC was 0.743 (95% CI 0.67-0.81) for the HEART score, 0.717 (95% CI 0.64-0.79) for the TIMI score, and 0.649 (95% CI 0.561-0.738) for the GRACE score. The HEART scale identified low-risk patients with a higher SE and negative PV than the GRACE and TIMI scores. The HEART scale was better than the GRACE and TIMI scores at diagnosing and predicting MACE at six weeks in patients with ANTCP and probable NSTE-ACS. It was also a reliable tool for risk stratification in low-risk patients. Its application is feasible in EDs and PCECs, avoiding the need for complementary tests and their associated costs without compromising patient health.

[Incidence of hyponatremia and its causes in neurological patients]. / Incidencia de la hiponatremia y de sus causas en pacientes neurológicos.

INTRODUCTION: Hyponatremia is considered the most frequent electrolyte disorder found in hospitalized patients and seems to be a prognostic factor during hospitalization. METHODS: A prospective observational study was carried out in consecutive neurological patients admitted to our hospital over a 3-month period. Blood and urinary ionogram and osmolality were determined at entry and 3-5 days after admission in all patients with hyponatremia. RESULTS: Of the 130 patients admitted, 19 (14.6%) had hyponatremia. The causes of hyponatremia were as follows: inappropriate fluid replacement in 4 patients (21%), antihypertensive drugs in 4 (21%), syndrome of inappropriate secretion of antidiuretic hormone in 4 (21%), cerebral salt wasting syndrome in 2 (10%), and edematous status caused by liver disease in one and digestive loss in one (5%) each. Mortality was one (5%) and 0 (0%) among patients with and without hyponatremia, respectively. CONCLUSION: Hyponatremia is common in hospitalized neurological patients and can be misdiagnosed as a worsening of the main illness.

Dermatological Manifestations in the Intensive Care Unit: A Practical Approach.

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.

A prediction rule for estimating the risk of bacteremia in patients with community-acquired pneumonia.

BACKGROUND: We endeavored to construct a simple score based entirely on epidemiological and clinical variables that would stratify patients who require hospital admission because of community-acquired pneumonia into groups with a low or high risk of developing bacteremia. METHODS: Derivation and internal validation cohorts were obtained by retrospective analysis of a database that included 3116 consecutive patients with community-acquired pneumonia from 2 university hospitals. Potential predictive factors were determined by means of a multivariate logistic regression equation applied to a cohort consisting of 60% of the patients. Points were assigned to significant parameters to generate the score. It was then internally validated with the remaining 40% of patients and was externally validated using an independent multicenter cohort of 1369 patients. RESULTS: The overall rates of bacteremia were 12%-16% in the cohorts. The clinical probability estimate of developing bacteremia was based on 6 variables: liver disease, pleuritic pain, tachycardia, tachypnea, systolic hypotension, and absence of prior antibiotic treatment. For the score, 1 point was assigned to each predictive factor. In the derivation cohort, a cutoff score of 2 best identified the risk of bacteremia. In the validation cohorts, rates of bacteremia were <8% for patients with a score 1 (43%-49% of patients), whereas blood culture results were positive in 14%-63% of cases for patients with a score 2. CONCLUSIONS: This clinical score, based on readily available and objective variables, provides a useful tool to predict bacteremia. The score has been internally and externally validated and may be useful to guide diagnostic decisions for community-acquired pneumonia.

Stratification of the severity of critically ill patients with classification trees.

BACKGROUND: Development of three classification trees (CT) based on the CART (Classification and Regression Trees), CHAID (Chi-Square Automatic Interaction Detection) and C4.5 methodologies for the calculation of probability of hospital mortality; the comparison of the results with the APACHE II, SAPS II and MPM II-24 scores, and with a model based on multiple logistic regression (LR). METHODS: Retrospective study of 2864 patients. Random partition (70:30) into a Development Set (DS) n = 1808 and Validation Set (VS) n = 808. Their properties of discrimination are compared with the ROC curve (AUC CI 95%), Percent of correct classification (PCC CI 95%); and the calibration with the Calibration Curve and the Standardized Mortality Ratio (SMR CI 95%). RESULTS: CTs are produced with a different selection of variables and decision rules: CART (5 variables and 8 decision rules), CHAID (7 variables and 15 rules) and C4.5 (6 variables and 10 rules). The common variables were: inotropic therapy, Glasgow, age, (A-a)O2 gradient and antecedent of chronic illness. In VS: all the models achieved acceptable discrimination with AUC above 0.7. CT: CART (0.75(0.71-0.81)), CHAID (0.76(0.72-0.79)) and C4.5 (0.76(0.73-0.80)). PCC: CART (72(69-75)), CHAID (72(69-75)) and C4.5 (76(73-79)). Calibration (SMR) better in the CT: CART (1.04(0.95-1.31)), CHAID (1.06(0.97-1.15) and C4.5 (1.08(0.98-1.16)). CONCLUSION: With different methodologies of CTs, trees are generated with different selection of variables and decision rules. The CTs are easy to interpret, and they stratify the risk of hospital mortality. The CTs should be taken into account for the classification of the prognosis of critically ill patients.

[Risk factors of the hepatic dysfunction associated with parenteral nutrition]. / Factores de riesgo de la disfunción hepática asociada a la nutrición parenteral.

BACKGROUND AND OBJECTIVE: The objective of this study is to describe the incidence of hepatic dysfunction (HD) in our hospital and evaluate the possible risk factors associated with HD development as an improvement of the caring process received by patients treated with parenteral nutrition (PN). PATIENTS AND METHOD: A prospective study of patients (n=994) who required PN during the period 2000-2004. HD is the identification of an increase above 1,5 of the top reference value of alkaline phosphatase (40-450U/l) and gamma glutamyl transpeptidase (11-49U/l) associated with an increase of transaminases (5-32U/l) and a total bilirrubin higher than 1,2mg/dl. RESULTS: The incidence of HD was 4,9% (n=49). Days with PN were significantly higher in the HD group: median (interquartile range): 30 (20-59) vs 15 (8-25) days (p<0.001). In the univariated HD analysis, the variables that reached significant odds ratio were: the critical patient condition, the PN duration, the total calorie contribution higher than 25kcal/kg, to exceed 3g of carbohydrates/kg, to administer more than 0.8g/kg of lipids and to exceed 0.16g of nitrogen/kg. In the multivariated analysis, the variables selected as independent risk factors were: to exceed 3 weeks of PN, to be a critical patient and a contribution over 0.16g of nitrogen/kg. CONCLUSIONS: The present profiles of the patients who will develop HD are those with prolonged PN. These patients undergo processes and critical therapy, where the specialists must monitor, not only calorie contribution, carbohydrates or lipids, but proteins as well.

A prospective pilot study using metabolomics discloses specific fatty acid, catecholamine and tryptophan metabolic pathways as possible predictors for a negative outcome after severe trauma.

BACKGROUND: We wanted to define metabolomic patterns in plasma to predict a negative outcome in severe trauma patients. METHODS: A prospective pilot study was designed to evaluate plasma metabolomic patterns, established by liquid chromatography coupled to mass spectrometry, in patients allocated to an intensive care unit (in the University Hospital Arnau de Vilanova, Lleida, Spain) in the first hours after a severe trauma (n = 48). Univariate and multivariate statistics were employed to establish potential predictors of mortality. RESULTS: Plasma of patients non surviving to trauma (n = 5) exhibited a discriminating metabolomic pattern, involving basically metabolites belonging to fatty acid and catecholamine synthesis as well as tryptophan degradation pathways. Thus, concentration of several metabolites exhibited an area under the receiver operating curve (ROC) higher than 0.84, including 3-indolelactic acid, hydroxyisovaleric acid, phenylethanolamine, cortisol, epinephrine and myristic acid. Multivariate binary regression logistic revealed that patients with higher myristic acid concentrations had a non-survival odds ratio of 2.1 (CI 95% 1.1-3.9). CONCLUSIONS: Specific fatty acids, catecholamine synthesis and tryptophan degradation pathways could be implicated in a negative outcome after trauma. The metabolomic study of severe trauma patients could be helpful for biomarker proposal.

Pleural fluid interleukin-8 and C-reactive protein for discriminating complicated non-purulent from uncomplicated parapneumonic effusions.

BACKGROUND AND OBJECTIVE: This study was designed to test the hypothesis that measurement of IL-8 and CRP in pleural fluid could improve the identification of patients with non-purulent parapneumonic effusions that ultimately require chest tube drainage. METHODS: We assessed IL-8, CRP and three classical parameters (pH, glucose and LDH) in the pleural fluid of 100 patients with parapneumonic effusions. Forty-nine of these patients had non-purulent complicated effusions (complicated parapneumonic pleural effusion, CPPE), and 51 had uncomplicated parapneumonic pleural effusions (UPPE). Receiver-operating characteristic curves were used to assess the sensitivity and specificity of pleural fluid biochemical parameters for differentiating among the two patient groups. IL-8 production was determined using a commercially available ELISA kit, and CRP was measured by immunoassay. RESULTS: At a cutoff value of 1000 pg/mL, IL-8 differentiated CPPE from UPPE with a sensitivity of 84% and a specificity of 82%. Likewise, CRP levels were higher in CPPE than in UPPE, and showed 72% sensitivity and 71% specificity at a cutoff value of 80 mg/L. We found that all five pleural fluid tests showed similar diagnostic accuracies when evaluated by receiver-operating characteristic analysis. However, multivariate analysis indicated that the size of the effusion, as well as pleural fluid pH and IL-8 concentration, were the best discriminatory parameters, with likelihood ratios of 6.4, 4.4 and 3.9, respectively. CONCLUSIONS: Pleural fluid IL-8 is an accurate marker for the identification of non-purulent CPPE.

[Approach to the methodology of classification and regression trees]. / Aproximación a la metodología basada en árboles de decisión (CART). Mortalidad hospitalaria del infarto agudo de miocardio.

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 inductive model was based on Breiman's algorithm, with a sensitivity analysis based on the Gini index and cross-validation. We compared the results with those obtained by using both logistic regression (LR) and artificial neural network (ANN) (multilayer perceptron) models. The developed models were contrasted with the VS and their properties were evaluated with the area under the ROC curve (AUC) (95% confidence interval [CI]). RESULTS: In the DS, the CART showed an AUC = 0.85 (0.86-0.88), LR 0.87 (0.86-0.88) and ANN 0.85 (0.85-0.86). In the VS, the CART showed an AUC = 0.85 (0.85-0.88), LR 0.86 (0.85-0.88) and ANN 0.84 (0.83-0.86). CONCLUSIONS: None of the methods tested outperformed the others in terms of discriminative ability. We found that the CART model was much easier to use and interpret, because the decision rules generated could be applied without the need for mathematical calculations.

Location-dependent effects of trauma on oxidative stress in humans.

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.

A more flexible parametric estimation of univariate reference intervals: a new method based on the GS-distribution.

BACKGROUND: Reference interval estimation is an important issue in clinical laboratories. Present methods are based either on data transformation or on non-parametric approaches. METHODS: We present a new technique based in a family of statistical distributions known as GS-distributions that provide a suitable model for continuous unimodal variables. We compare, both by simulation studies an on actual data, the reference intervals estimated by using non-parametric methods and data transformations suggested by the IFCC and those obtained by fitting a GS-distribution. Simulated data are generated from various distributions to evaluate the accuracy of these methods. In each case, confidence intervals for the resulting reference intervals are obtained by bootstrap. RESULTS: In all the cases, the GS-distribution based method provides comparable or more accurate results than the non-parametric methods. In most cases, the proposed method produces better results than those obtained by transforming the original data. CONCLUSIONS: Our results suggest that the method for computing reference intervals based on GS-distribution is a valid alternative for the current non-parametric methods.

The Spanish Adaptation of the Palliative Performance Scale (Version 2) Among Cancer Patients at the End of Life: Psychometric Properties.

BACKGROUND: Palliative Performance Scale (PPS) is a reliable tool to assess performance status in cancer patients receiving palliative care (PC). Spanish validated and culturally adapted tools are needed. OBJECTIVES: The objectives are to develop PPS translation and cross-cultural adaptation into Spanish and to assess its psychometric properties. DESIGN: Translation process with cross-cultural adaptation to produce Spanish Palliative Performance Scale (PPS-SPANISH). SETTINGS: PC Team at one University hospital in Spain. PARTICIPANTS: Fifteen advanced cancer patients (60 assessments) were included for PPS translation and validation and 250 patients for cross-sectional analysis. All participants were recruited at oncology ward, emergency area, and outpatient clinic by PC team professionals. Informed consent was given. Average age was 66.4 ± 13 years (60% men). METHODS: The process is designed in three steps. In Step 1, PPS translation and reverse translation into Spanish (three bilingual speakers) and linguistic complexity measurement were performed. In Step 2, readability and intelligibility assessment was carried out. In Step 3, a pilot study was conducted to assess test-retest reliability followed by a cross-sectional study to measure internal consistency. Inclusion criteria were the same for two samples. Demographic data were also analyzed by descriptive statistics. RESULTS: Following cultural, linguistic, and grammatical adaptation, PPS-SPANISH was readable and reliable. The analysis of the test-retest reliability after 48 hours showed intraclass correlations >0.60. Cronbach's alpha coefficient was 0.99 (0.988-0.992). There was high agreement with other functional assessment tools (Barthel Index and Karnofsky Performance Status Index). CONCLUSIONS: PPS-SPANISH showed reliability and validity, and it is suitable to assess performance status in cancer patients receiving PC.

[Methodological approach to the use of artificial neural networks for predicting results in medicine]. / Aproximación metodológica al uso de redes neuronales artificiales para la predicción de resultados en medicina.

In clinical practice, there is an increasing interest in obtaining adequate models of prediction. Within the possible available alternatives, the artificial neural networks (ANN) are progressively more used. In this review we first introduce the ANN methodology, describing the most common type of ANN, the Multilayer Perceptron trained with backpropagation algorithm (MLP). Then we compare the MLP with the Logistic Regression (LR). Finally, we show a practical scheme to make an application based on ANN by means of an example with actual data. The main advantage of the RN is its capacity to incorporate nonlinear effects and interactions between the variables of the model without need to include them a priori. As greater disadvantages, they show a difficult interpretation of their parameters and large empiricism in their process of construction and training. ANN are useful for the computation of probabilities of a given outcome based on a set of predicting variables. Furthermore, in some cases, they obtain better results than LR. Both methodologies, ANN and LR, are complementary and they help us to obtain more valid models.