Development and validation of predictive models for unplanned hospitalization in the Basque Country: analyzing the variability of non-deterministic algorithms.

Background: The progressive ageing in developed countries entails an increase in multimorbidity. Population-wide predictive models for adverse health outcomes are crucial to address these growing healthcare needs. The main objective of this study is to develop and validate a population-based prognostic model to predict the probability of unplanned hospitalization in the Basque Country, through comparing the performance of a logistic regression model and three families of machine learning models.

Analysis of the impact of social determinants and primary care morbidity on population health outcomes by combining big data: A research protocol.

Background: In recent years, different tools have been developed to facilitate analysis of social determinants of health (SDH) and apply this to health policy. The possibility of generating predictive models of health outcomes which combine a wide range of socioeconomic indicators with health problems is an approach that is receiving increasing attention. Our objectives are twofold: (1) to predict population health outcomes measured as hospital morbidity, taking primary care (PC) morbidity adjusted for SDH as predictors; and (2) to analyze the geographic variability of the impact of SDH-adjusted PC morbidity on hospital morbidity, by combining data sourced from electronic health records and selected operations of the National Statistics Institute ().

Multidimensional adaptive P-splines with application to neurons' activity studies.

The receptive field (RF) of a visual neuron is the region of the space that elicits neuronal responses. It can be mapped using different techniques that allow inferring its spatial and temporal properties. Raw RF maps (RFmaps) are usually noisy, making it difficult to obtain and study important features of the RF.

A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data.

High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical analyses in which longitudinal genetic signals need to be estimated against a background of spatio-temporal noise processes. We propose a two-stage approach for the analysis of such longitudinal HTP data.

Reconstruction of Networks with Direct and Indirect Genetic Effects.

Genetic variance of a phenotypic trait can originate from direct genetic effects, or from indirect effects, , through genetic effects on other traits, affecting the trait of interest. This distinction is often of great importance, for example, when trying to improve crop yield and simultaneously control plant height. As suggested by Sewall Wright, assessing contributions of direct and indirect effects requires knowledge of (1) the presence or absence of direct genetic effects on each trait, and (2) the functional relationships between the traits.

Bootstrap-based procedures for inference in nonparametric receiver-operating characteristic curve regression analysis.

Prior to using a diagnostic test in a routine clinical setting, the rigorous evaluation of its diagnostic accuracy is essential. The receiver-operating characteristic curve is the measure of accuracy most widely used for continuous diagnostic tests. However, the possible impact of extra information about the patient (or even the environment) on diagnostic accuracy also needs to be assessed.

Comparing Some Production Functions for Inpatient Health Services in Selected Public Hospitals in Spain.

To investigate the adequacy of the widely used Cobb-Douglas and transcendental logarithmic (translog) models of the production functions of hospital inpatient services, the authors fitted these and additive models to data for the four most productive health services of 10 public hospitals in Galicia, Spain (the same four in each). Production, measured as admissions weighted in accordance with their diagnosis-related groups (DRGs), was treated as a function of physician full-time equivalents as surrogate labor factor and number of beds as surrogate capital factor. The results suggest that while the Cobb-Douglas and translog models suffice to represent the production functions of services with low average DRG weight, the greater flexibility of additive models is required for services with higher average DRG weight when only these two inputs are considered.

Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model.

A flexible and user-friendly spatial method called SpATS performed comparably to more elaborate and trial-specific spatial models in a series of sorghum breeding trials. Adjustment for spatial trends in plant breeding field trials is essential for efficient evaluation and selection of genotypes. Current mixed model methods of spatial analysis are based on a multi-step modelling process where global and local trends are fitted after trying several candidate spatial models.

Assessment of morbidity in gynaecologic oncology laparoscopy and identification of possible risk factors.

Background: The aim of this study was to ascertain the incidence of and the risk factors associated with morbidity in laparoscopy performed on patients with cervical cancer and endometrial cancer.

Methods: This was an observational study of a cohort of 128 women, 89 with endometrial cancer and 39 with cervical cancer from January 2000 to December 2011. We used the Student's t-test or the Mann-Whitney U test for continuous variables, and the Chi-square or Fisher's exact test for categorical variables.

ME20-S as a Potential Biomarker for the Evaluation of Uveal Melanoma.

Purpose: We previously identified the presence of the melanocyte-specific secreted (ME20-S) glycoprotein in secretomes of uveal melanoma (UM) cultures. The aim of this study was to test for the presence and levels of ME20-S in the serum of patients with choroidal nevi and UM and correlate these levels with individual clinical data.

Methods: Serum ME20-S levels were determined by ELISA in 111 patients distributed into four categories (53 choroidal nevi, 30 untreated UM, 11 10-year disease-free [DF] UM, 17 hepatic metastatic UM) and 32 age- and sex-matched controls.

Nonparametric estimation of time-dependent ROC curves conditional on a continuous covariate.

The receiver-operating characteristic (ROC) curve is the most widely used measure for evaluating the performance of a diagnostic biomarker when predicting a binary disease outcome. The ROC curve displays the true positive rate (or sensitivity) and the false positive rate (or 1-specificity) for different cut-off values used to classify an individual as healthy or diseased. In time-to-event studies, however, the disease status (e.

A new approach to categorising continuous variables in prediction models: Proposal and validation.

When developing prediction models for application in clinical practice, health practitioners usually categorise clinical variables that are continuous in nature. Although categorisation is not regarded as advisable from a statistical point of view, due to loss of information and power, it is a common practice in medical research. Consequently, providing researchers with a useful and valid categorisation method could be a relevant issue when developing prediction models.

Prevalence and genetic diversity of Salmonella spp. in a river in a tropical environment in Mexico.

The capability of Salmonella to survive outside a host is especially relevant in tropical regions, where the environmental conditions could be more suitable for its long-term persistence. This study investigated the prevalence and genetic diversity of salmonellae within rivers of the Culiacan Valley in the northwestern region of Mexico. From July 2008 to June 2009, a total of 138 water samples were evaluated for the presence of Salmonella spp.

Relationship between macular bending and foveoschisis in myopic patients.

Purpose: To investigate factors associated with myopic foveoschisis and macular bending and to determine how the presence of macular bending affects the development of myopic foveoschisis.

Methods: In a prospective study of 194 eyes of 105 patients with high myopia, we performed complete ophthalmic examinations, optical coherence tomography (OCT), and A-scan ultrasounds. Patients were divided into three groups according to the OCT results.

Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study.

Background: Insulin resistance has been associated with metabolic and hemodynamic alterations and higher cardio metabolic risk. There is great variability in the threshold homeostasis model assessment of insulin resistance (HOMA-IR) levels to define insulin resistance. The purpose of this study was to describe the influence of age and gender in the estimation of HOMA-IR optimal cut-off values to identify subjects with higher cardio metabolic risk in a general adult population.

Serum DJ-1/PARK 7 is a potential biomarker of choroidal nevi transformation.

Purpose: There is substantial evidence that intraocular melanomas arise from benign nevi in the uveal tract. Previous studies performed by the authors revealed that uveal melanoma cells secrete the oncoprotein DJ-1/PARK7 into the extracellular environment and circulation. The aim of this study was to determine whether circulating DJ-1 serum levels correlate with known clinical risk factors of nevi growth.

Insulin resistance index (HOMA-IR) levels in a general adult population: curves percentile by gender and age. The EPIRCE study.

Aims: To describe the distribution of HOMA-IR levels in a general nondiabetic population and its relationships with metabolic and lifestyles characteristics.

Methods: Cross-sectional study. Data from 2246 nondiabetic adults in a random Spanish population sample, stratified by age and gender, were analyzed.

Admission and fasting plasma glucose for estimating risk of death of diabetic and nondiabetic patients with acute coronary syndrome: nonlinearity of hazard ratios and time-dependent comparison.

Background: In patients with acute coronary syndrome (ACS), increased plasma glucose levels are associated with worse outcome. Our aim is to ascertain the values of admission and fasting glucose for prediction of death among patients with ACS; and to compare their predictive capacities.

Methods: The relationships of mortality to plasma glucose levels among 811 consecutive patients hospitalized with ACS were estimated using spline Cox models.