Los tribunales castellanos en los siglos XVI y XVII.

Sin resume

Time-dependent ROC methodology to evaluate the predictive accuracy of semiparametric multi-state models in the presence of competing risks: An application to peritoneal dialysis programme

The evaluation of peritoneal dialysis (PD) programmes requires the use of statistical methods that suit the complexity of such programmes. Multi-state regression models taking competing risks into account are a good example of suitable approaches. In this work, multi-state structured additive regression (STAR) models combined with penalized splines (P-splines) are proposed to evaluate peritoneal dialysis programmes. These models are very flexible since they may consider smooth estimates of baseline transition intensities and the inclusion of time-varying and smooth covariate effects at each transition. A key issue in survival analysis is the quantification of the time-dependent predictive accuracy of a given regression model, which is typically assessed using receiver operating characteristic (ROC)’based methodologies. The main objective of the present study is to adapt the concept of time-dependent ROC curve, and their corresponding area under the curve (AUC), to a multi-state competing risks framework. All statistical methodologies discussed in this work were applied to PD survival data. Using a multi-state competing risks framework, this study explored the effects of major clinical covariates on survival such as age, sex, diabetes and previous renal replacement therapy. Such multi-state model was composed of one transient state (peritonitis) and several absorbing states (death, transfer to haemodialysis and renal transplantation). The application of STAR models combined with time-dependent ROC curves revealed important conclusions not previously reported in the nephrology literature when using standard statistical methodologies. For practical application, all the statistical methods proposed in this article were implemented in R and we wrote and made available a script named as NestedCompRisks

Determinantes de la duración de la incapacidad temporal y la vuelta al trabajo en un área sanitaria de Galicia

ObjetivoDeterminar los factores asociados con la incidencia y la duración de la incapacidad temporal (IT) en un área sanitaria.DiseñoDescriptivo, retrospectivo.EmplazamientoÁrea Sanitaria Sur de la provincia de Lugo.ParticipantesUna muestra de 1.513 episodios de IT seleccionada aleatoriamente entre el total de éstos, durante un período de 3 años.Mediciones principalesSe analizaron las características sociodemográficas del paciente, el régimen de la seguridad social (SS), el diagnóstico que justifica la IT y la fecha de la prescripción; del médico prescriptor se analizaron la edad, el sexo, la formación especializada, la antigüedad en la plaza y los años de ejercicio. La comparación de medias se realizó mediante el análisis de la varianza y el test de Kruskal-Wallis. El efecto relativo de cada variable sobre la probabilidad de volver al trabajo se estimó mediante modelos de regresión de Cox.ResultadosLa duración media de los episodios de IT fue de 74 ± 103 días. Los diagnósticos más frecuentes fueron los del sistema osteomioarticular (SOMA), las lesiones y envenenamientos (LYE) y las enfermedades respiratorias (NML). Se reduce la probabilidad de volver al trabajo con el incremento de la edad, en los regímenes de seguridad social autónomos y agrarios por cuenta propia, en los diagnósticos de enfermedades mentales y del aparato circulatorio, y cuando el médico prescriptor es de mayor edad o menos antiguo en la plaza.ConclusionesLa duración media de los episodios de IT es superior a la de otros estudios españoles. Los factores que más influyen en la reincorporación al trabajo son la edad del paciente, el régimen de la seguridad social y la enfermedad diagnosticada.ObjectiveTo determine the factors associated with the incidence and duration of temporary work incapacity (TWI) in a health district.DesignDescriptive and retrospective study.SettingSouth health district of the province of Lugo, Spain.ParticipantsA random sample of 1513 cases was selected among the total of episodes of TWI, during 3 years period.Main measuresThe main factors analyzed are, on the one hand, the socio-demographic characteristics of the patient, his or her social security (SS) scheme, diagnosis that justifies the TWD, and the prescription date; and, on the other hand, the age, sex, specialised training, time in the post and years in practice of the physician who prescribes the TWI. The comparison of the means was carried out using variance analysis and the Kruskal-Wallis test. The relative effect of each variable on the probability of returning to the work was estimated through Cox regression models.ResultsThe mean duration of the episodes of TWI was of 74±103 days. The most frequent diagnoses were those of the bones-muscles and joints (BMAJ), injuries and poisonings (IAP), and respiratory diseases (RD). The probability of returning to work is reduced with the increase of the age, with agrarian and autonomous SS affiliates, with diagnoses of mental disease or diagnoses of the circulatory system, and in cases prescribed by older doctors or less time in the post.ConclusionsThe mean duration of the episodes of TWD is higher than that of other Spanish studies. The most influential factors in the return to work are the age of the patient, the SS scheme and the diagnosed illness

Train unit scheduling guided by historic capacity provisions and passenger count surveys

Train unit scheduling concerns the assignment of train unit vehicles to cover all the journeys in a fixed timetable. Coupling and decoupling activities are allowed in order to achieve optimal utilization while satisfying passenger demands. While the scheduling methods usually assume unique and well-defined train capacity requirements, in practice most UK train operators consider different levels of capacity provisions. Those capacity provisions are normally influenced by information such as passenger count surveys, historic provisions and absolute minimums required by the authorities. In this paper, we study the problem of train unit scheduling with bi-level capacity requirements and propose a new integer multicommodity flow model based on previous research. Computational experiments on real-world data show the effectiveness of our proposed methodology

Impact of the first wave of the SARS-CoV-2 pandemic on the outcome of neurosurgical patients: A nationwide study in Spain

Objective To assess the effect of the first wave of the SARS-CoV-2 pandemic on the outcome of neurosurgical patients in Spain. Settings The initial flood of COVID-19 patients overwhelmed an unprepared healthcare system. Different measures were taken to deal with this overburden. The effect of these measures on neurosurgical patients, as well as the effect of COVID-19 itself, has not been thoroughly studied. Participants This was a multicentre, nationwide, observational retrospective study of patients who underwent any neurosurgical operation from March to July 2020. Interventions An exploratory factorial analysis was performed to select the most relevant variables of the sample. Primary and secondary outcome measures Univariate and multivariate analyses were performed to identify independent predictors of mortality and postoperative SARS-CoV-2 infection. Results Sixteen hospitals registered 1677 operated patients. The overall mortality was 6.4%, and 2.9% (44 patients) suffered a perioperative SARS-CoV-2 infection. Of those infections, 24 were diagnosed postoperatively. Age (OR 1.05), perioperative SARS-CoV-2 infection (OR 4.7), community COVID-19 incidence (cases/10 5 people/week) (OR 1.006), postoperative neurological worsening (OR 5.9), postoperative need for airway support (OR 5.38), ASA grade =3 (OR 2.5) and preoperative GCS 3-8 (OR 2.82) were independently associated with mortality. For SARS-CoV-2 postoperative infection, screening swab test <72 hours preoperatively (OR 0.76), community COVID-19 incidence (cases/10 5 people/week) (OR 1.011), preoperative cognitive impairment (OR 2.784), postoperative sepsis (OR 3.807) and an absence of postoperative complications (OR 0.188) were independently associated. Conclusions Perioperative SARS-CoV-2 infection in neurosurgical patients was associated with an increase in mortality by almost fivefold. Community COVID-19 incidence (cases/10 5 people/week) was a statistically independent predictor of mortality. Trial registration number CEIM 20/217

Leakage of nitrous oxide emissions within the Spanish agro-food system in 1961-2009

Abstract In this paper we examine the trends of nitrous oxide (N2O) emissions of the Spanish agricultural sector related to national production and consumption in the 1961?2009 period.The comparison between production- and consumption-based emissions at the national level provides a complete overview of the actual impact resulting from the dietary choices of a given country and allows the evaluation of potential emission leakages. On average, 1.5 % of the new reactive nitrogen that enters Spain every year is emitted as N2O. Production- and consumption-based emissions have both significantly increased in the period studied and nowadays consumption-based emissions are 45 % higher than production-based emissions. A large proportion of the net N2O emissions associated with imported agricultural godos comes from countries that are not committers for the United Nations Framework Convention on Climate Change Kyoto Protocol Annex I. An increase in feed consumption is the main driver of the changes observed, leading to a arkable emission leakage in the Spanish agricultural sector. The complementary approach used here is essential to achieve an effective mitigation of Spanish greenhouse gas emissions