Hacia el bienestar psicológico en el ejercicio físico acuático

[ES] El objetivo del estudio ha sido comprobar el poder de predicción de la pasión que transmite el técnico deportivo, los mediadores psicológicos y la motivación autodeterminada sobre el bienestar psicológico.

La distribuzione del potere tra le Istituzioni Europee e la procedura di co-decisione. Il caso della riforma della Politica Agricola Comune

Questa ricerca analizza le implicazioni derivanti dall’introduzione della procedura di co-decisione come procedura legislativa ordinaria nel processo di riforma della politica agricola comune. La diversa distribuzione dei poteri tra le istituzioni europee modifica gli assetti istituzionali e fornisce al Parlamento il ruolo di colegislatore in materia agricola. La forma assunta dalla nuova politica agricola europea scaturisce dalla configurazione dei poteri di contrattazione che ciascun attore ha mostrato nella sede dei triloghi negoziali. La ricerca tenta di verificare la accuratezza predittiva di diversi modelli di contrattazione legislativa attraverso il confronto e la verifica degli errori di predizione sui risultati finali di alcune questioni salienti della riforma della Politica Agricola Comune e allo stesso tempo, cerca di identificare il peso del potere del Parlamento europeo in veste di co-legislatore nel processo di riforma della PAC post-2013.

Prediction of Psychosis by Mismatch Negativity

BACKGROUND: To develop risk-adapted prevention of psychosis, an accurate estimation of the individual risk of psychosis at a given time is needed. Inclusion of biological parameters into multilevel prediction models is thought to improve predictive accuracy of models on the basis of clinical variables. To this aim, mismatch negativity (MMN) was investigated in a sample clinically at high risk, comparing individuals with and without subsequent conversion to psychosis. METHODS: At baseline, an auditory oddball paradigm was used in 62 subjects meeting criteria of a late risk at-state who remained antipsychotic-naive throughout the study. Median follow-up period was 32 months (minimum of 24 months in nonconverters, n = 37). Repeated-measures analysis of covariance was employed to analyze the MMN recorded at frontocentral electrodes; additional comparisons with healthy controls (HC, n = 67) and first-episode schizophrenia patients (FES, n = 33) were performed. Predictive value was evaluated by a Cox regression model. RESULTS: Compared with nonconverters, duration MMN in converters (n = 25) showed significantly reduced amplitudes across the six frontocentral electrodes; the same applied in comparison with HC, but not FES, whereas the duration MMN in in nonconverters was comparable to HC and larger than in FES. A prognostic score was calculated based on a Cox regression model and stratified into two risk classes, which showed significantly different survival curves. CONCLUSIONS: Our findings demonstrate the duration MMN is significantly reduced in at-risk subjects converting to first-episode psychosis compared with nonconverters and may contribute not only to the prediction of conversion but also to a more individualized risk estimation and thus risk-adapted prevention.

Predicting the transition from acute to persistent low back pain

BACKGROUND: Most people experience low back pain (LBP) at least once in their lifetime. Only a minority of them go on to develop persistent LBP. However, the socioeconomic costs of persistent LBP significantly exceed the costs of the initial acute LBP episode. AIMS: To identify factors that influence the progression of acute LBP to the persistent state at an early stage. METHODS: Prospective inception cohort study of patients attending a health practitioner for their first episode of acute LBP or recurrent LBP after a pain free period of at least 6 months. Patients were assessed at baseline addressing occupational and psychological factors as well as pain, disability, quality of life and physical activity and followed up at 3, 6, 12 weeks and 6 months. Variables were combined to the three indices 'working condition', 'depression and maladaptive cognitions' and 'pain and quality of life'. RESULTS: The index 'depression and maladaptive cognitions' was found to be a significant baseline predictor for persistent LBP up to 6 months (OR 5.1; 95% CI: 1.04-25.1). Overall predictive accuracy of the model was 81%. CONCLUSIONS: In this study of patients with acute LBP in a primary care setting psychological factors at baseline correlated with a progression to persistent LBP up to 6 months. The benefit of including factors such as 'depression and maladaptive cognition' in screening tools is that these factors can be addressed in primary and secondary prevention.

Predicting the transition from acute to persistent low back pain

BACKGROUND: Most people experience low back pain (LBP) at least once in their lifetime. Only a minority of them go on to develop persistent LBP. However, the socioeconomic costs of persistent LBP significantly exceed the costs of the initial acute LBP episode. AIMS: To identify factors that influence the progression of acute LBP to the persistent state at an early stage. METHODS: Prospective inception cohort study of patients attending a health practitioner for their first episode of acute LBP or recurrent LBP after a pain free period of at least 6 months. Patients were assessed at baseline addressing occupational and psychological factors as well as pain, disability, quality of life and physical activity and followed up at 3, 6, 12 weeks and 6 months. Variables were combined to the three indices 'working condition', 'depression and maladaptive cognitions' and 'pain and quality of life'. RESULTS: The index 'depression and maladaptive cognitions' was found to be a significant baseline predictor for persistent LBP up to 6 months (OR 5.1; 95% CI: 1.04-25.1). Overall predictive accuracy of the model was 81%. CONCLUSIONS: In this study of patients with acute LBP in a primary care setting psychological factors at baseline correlated with a progression to persistent LBP up to 6 months. The benefit of including factors such as 'depression and maladaptive cognition' in screening tools is that these factors can be addressed in primary and secondary prevention.

The significance of at-risk symptoms for psychosis in children and adolescents

The early detection and treatment of people at risk for psychosis is currently regarded as a promising strategy in fighting the devastating consequences of psychotic disorders. Currently, the 2 most broadly used sets of at-risk criteria, that is, ultra-high risk (UHR) and basic symptom criteria, were developed mainly in adult samples. We review the data regarding the presence and relevance of at-risk symptoms for psychosis in children and adolescents. The few existing studies suggest that attenuated psychotic symptoms (APS) and brief limited intermittent psychotic symptoms (BLIPS) do have some clinical relevance in young adolescents from the general population. Nevertheless, their differentiation from atypical psychotic symptoms or an emerging schizotypal personality disorder, as well as their stability and predictive accuracy for psychosis, are still unclear. Further, standard interviews for UHR criteria do not define a minimum age for the assessment of APS and BLIPS or guidelines as to when and how to include information from parents. APS and basic symptoms may be predictive of conversion to psychosis in help-seeking young adolescents. Nevertheless, the rate and timing, and thus the required observation time, need further study. Moreover, no study has yet addressed the issue of how to treat children and adolescents presenting with at-risk symptoms and criteria. Further research is urgently needed to examine if current at-risk criteria and approaches have to be tailored to the special needs of children and adolescents. A preliminary rationale for how to deal with at-risk symptoms for psychosis in clinical practice is provided.

Concordance Probability and Discriminatory Power in Proportional Hazards Regression

The concordance probability is used to evaluate the discriminatory power and the predictive accuracy of nonlinear statistical models. We derive an analytic expression for the concordance probability in the Cox proportional hazards model. The proposed estimator is a function of the regression parameters and the covariate distribution only and does not use the observed event and censoring times. For this reason it is asymptotically unbiased, unlike Harrell's c-index based on informative pairs. The asymptotic distribution of the concordance probability estimate is derived using U-statistic theory and the methodology is applied to a predictive model in lung cancer.

Survival Analysis with Large Dimensional Covariates: An Application in Microarray Studies

Use of microarray technology often leads to high-dimensional and low- sample size data settings. Over the past several years, a variety of novel approaches have been proposed for variable selection in this context. However, only a small number of these have been adapted for time-to-event data where censoring is present. Among standard variable selection methods shown both to have good predictive accuracy and to be computationally efficient is the elastic net penalization approach. In this paper, adaptation of the elastic net approach is presented for variable selection both under the Cox proportional hazards model and under an accelerated failure time (AFT) model. Assessment of the two methods is conducted through simulation studies and through analysis of microarray data obtained from a set of patients with diffuse large B-cell lymphoma where time to survival is of interest. The approaches are shown to match or exceed the predictive performance of a Cox-based and an AFT-based variable selection method. The methods are moreover shown to be much more computationally efficient than their respective Cox- and AFT- based counterparts.

Validation of the estimation of physiologic ability and surgical stress (E-PASS) score in liver surgery

BACKGROUND: The estimation of physiologic ability and surgical stress (E-PASS) has been used to produce a numerical estimate of expected mortality and morbidity after elective gastrointestinal surgery. The aim of this study was to validate E-PASS in a selected cohort of patients requiring liver resections (LR). METHODS: In this retrospective study, E-PASS predictor equations for morbidity and mortality were applied to the prospective data from 243 patients requiring LR. The observed rates were compared with predicted rates using Fisher's exact test. The discriminative capability of E-PASS was evaluated using receiver-operating characteristic (ROC) curve analysis. RESULTS: The observed and predicted overall mortality rates were both 3.3% and the morbidity rates were 31.3 and 26.9%, respectively. There was a significant difference in the comprehensive risk scores for deceased and surviving patients (p = 0.043). However, the scores for patients with or without complications were not significantly different (p = 0.120). Subsequent ROC curve analysis revealed a poor predictive accuracy for morbidity. CONCLUSIONS: The E-PASS score seems to effectively predict mortality in this specific group of patients but is a poor predictor of complications. A new modified logistic regression might be required for LR in order to better predict the postoperative outcome.

Early Detection and Treatment of Psychosis: The Bern Child and Adolescent Psychiatric Perspective

Commonly conceptualized as neurodevelopmental disorders of yet poorly understood aetiology, schizophrenia and other nonorganic psychoses remain one of the most debilitating illnesses with often poor outcome despite all progress in treatment of the manifest disorder. Drawing on the frequent poor outcome of psychosis and its association with the frequently extended periods of untreated first-episode psychosis (FEP) including its prodrome, an early detection and treatment of both the FEP and the preceding at-risk mental state (ARMS) have been increasingly studied. Thereby both approaches are confronted with different problems, for example, treatment engagement in FEP and predictive accuracy in ARMS. They share, however, the problems related to the lack of understanding of developmental, that is, age-related, peculiarities and of the presentation and natural course of their cardinal symptoms in the community. Most research on early detection and intervention in FEP and ARMS is still related to clinical psychiatric samples, and little is known about symptom presentation and burden and help-seeking in the general population related to these experiences. Furthermore, in particular in the early detection of an ARMS, studies often address adolescents and young adults alike without consideration of developmental characteristics, thereby applying risk criteria that have been developed predominately in adults. Combining our earlier experiences described in this paper in child and adolescent, and general psychiatry as well as in both lines of research, that is, on early psychosis and its treatment and on the early detection of psychosis, in particular in its very early states by subjective disturbances in terms of basic symptoms, age-related developmental and epidemiological aspects have therefore been made the focus of our current studies in Bern, thus making our line of research unique

Stratification of high-risk prostate cancer into prognostic categories: a European multi-institutional study

BACKGROUND High-risk prostate cancer (PCa) is an extremely heterogeneous disease. A clear definition of prognostic subgroups is mandatory. OBJECTIVE To develop a pretreatment prognostic model for PCa-specific survival (PCSS) in high-risk PCa based on combinations of unfavorable risk factors. DESIGN, SETTING, AND PARTICIPANTS We conducted a retrospective multicenter cohort study including 1360 consecutive patients with high-risk PCa treated at eight European high-volume centers. INTERVENTION Retropubic radical prostatectomy with pelvic lymphadenectomy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Two Cox multivariable regression models were constructed to predict PCSS as a function of dichotomization of clinical stage (< cT3 vs cT3-4), Gleason score (GS) (2-7 vs 8-10), and prostate-specific antigen (PSA; ≤ 20 ng/ml vs > 20 ng/ml). The first "extended" model includes all seven possible combinations; the second "simplified" model includes three subgroups: a good prognosis subgroup (one single high-risk factor); an intermediate prognosis subgroup (PSA >20 ng/ml and stage cT3-4); and a poor prognosis subgroup (GS 8-10 in combination with at least one other high-risk factor). The predictive accuracy of the models was summarized and compared. Survival estimates and clinical and pathologic outcomes were compared between the three subgroups. RESULTS AND LIMITATIONS The simplified model yielded an R(2) of 33% with a 5-yr area under the curve (AUC) of 0.70 with no significant loss of predictive accuracy compared with the extended model (R(2): 34%; AUC: 0.71). The 5- and 10-yr PCSS rates were 98.7% and 95.4%, 96.5% and 88.3%, 88.8% and 79.7%, for the good, intermediate, and poor prognosis subgroups, respectively (p = 0.0003). Overall survival, clinical progression-free survival, and histopathologic outcomes significantly worsened in a stepwise fashion from the good to the poor prognosis subgroups. Limitations of the study are the retrospective design and the long study period. CONCLUSIONS This study presents an intuitive and easy-to-use stratification of high-risk PCa into three prognostic subgroups. The model is useful for counseling and decision making in the pretreatment setting.

Prediction of Post-Weaning Fibrinogen Status during Cardiopulmonary Bypass: An Observational Study in 110 Patients.

BACKGROUND After cardiac surgery with cardiopulmonary bypass (CPB), acquired coagulopathy often leads to post-CPB bleeding. Though multifactorial in origin, this coagulopathy is often aggravated by deficient fibrinogen levels. OBJECTIVE To assess whether laboratory and thrombelastometric testing on CPB can predict plasma fibrinogen immediately after CPB weaning. PATIENTS / METHODS This prospective study in 110 patients undergoing major cardiovascular surgery at risk of post-CPB bleeding compares fibrinogen level (Clauss method) and function (fibrin-specific thrombelastometry) in order to study the predictability of their course early after termination of CPB. Linear regression analysis and receiver operating characteristics were used to determine correlations and predictive accuracy. RESULTS Quantitative estimation of post-CPB Clauss fibrinogen from on-CPB fibrinogen was feasible with small bias (+0.19 g/l), but with poor precision and a percentage of error >30%. A clinically useful alternative approach was developed by using on-CPB A10 to predict a Clauss fibrinogen range of interest instead of a discrete level. An on-CPB A10 ≤10 mm identified patients with a post-CPB Clauss fibrinogen of ≤1.5 g/l with a sensitivity of 0.99 and a positive predictive value of 0.60; it also identified those without a post-CPB Clauss fibrinogen <2.0 g/l with a specificity of 0.83. CONCLUSIONS When measured on CPB prior to weaning, a FIBTEM A10 ≤10 mm is an early alert for post-CPB fibrinogen levels below or within the substitution range (1.5-2.0 g/l) recommended in case of post-CPB coagulopathic bleeding. This helps to minimize the delay to data-based hemostatic management after weaning from CPB.

Selection bias and the cross-validation of regression models for prediction

Strategies are compared for the development of a linear regression model with stochastic (multivariate normal) regressor variables and the subsequent assessment of its predictive ability. Bias and mean squared error of four estimators of predictive performance are evaluated in simulated samples of 32 population correlation matrices. Models including all of the available predictors are compared with those obtained using selected subsets. The subset selection procedures investigated include two stopping rules, C$\sb{\rm p}$ and S$\sb{\rm p}$, each combined with an 'all possible subsets' or 'forward selection' of variables. The estimators of performance utilized include parametric (MSEP$\sb{\rm m}$) and non-parametric (PRESS) assessments in the entire sample, and two data splitting estimates restricted to a random or balanced (Snee's DUPLEX) 'validation' half sample. The simulations were performed as a designed experiment, with population correlation matrices representing a broad range of data structures.^ The techniques examined for subset selection do not generally result in improved predictions relative to the full model. Approaches using 'forward selection' result in slightly smaller prediction errors and less biased estimators of predictive accuracy than 'all possible subsets' approaches but no differences are detected between the performances of C$\sb{\rm p}$ and S$\sb{\rm p}$. In every case, prediction errors of models obtained by subset selection in either of the half splits exceed those obtained using all predictors and the entire sample.^ Only the random split estimator is conditionally (on $\\beta$) unbiased, however MSEP$\sb{\rm m}$ is unbiased on average and PRESS is nearly so in unselected (fixed form) models. When subset selection techniques are used, MSEP$\sb{\rm m}$ and PRESS always underestimate prediction errors, by as much as 27 percent (on average) in small samples. Despite their bias, the mean squared errors (MSE) of these estimators are at least 30 percent less than that of the unbiased random split estimator. The DUPLEX split estimator suffers from large MSE as well as bias, and seems of little value within the context of stochastic regressor variables.^ To maximize predictive accuracy while retaining a reliable estimate of that accuracy, it is recommended that the entire sample be used for model development, and a leave-one-out statistic (e.g. PRESS) be used for assessment. ^

External validation study of a clinical prediction rule for ambulation outcomes after traumatic spinal cord injury

The main objective of this study was to determine the external validity of a clinical prediction rule developed by the European Multicenter Study on Human Spinal Cord Injury (EM-SCI) to predict the ambulation outcomes 12 months after traumatic spinal cord injury. Data from the North American Clinical Trials Network (NACTN) data registry with approximately 500 SCI cases were used for this validity study. The predictive accuracy of the EM-SCI prognostic model was evaluated using calibration and discrimination based on 231 NACTN cases. The area under the receiver-operating-characteristics curve (ROC) curve was 0.927 (95% CI 0.894 – 0.959) for the EM-SCI model when applied to NACTN population. This is lower than the AUC of 0.956 (95% CI 0.936 – 0.976) reported for the EM-SCI population, but suggests that the EM-SCI clinical prediction rule distinguished well between those patients in the NACTN population who were able to achieve independent ambulation and those who did not achieve independent ambulation. The calibration curve suggests that higher the prediction score is, the better the probability of walking with the best prediction for AIS D patients. In conclusion, the EM-SCI clinical prediction rule was determined to be generalizable to the adult NACTN SCI population.^