The effect of smoking on clinical parameters and structural damage in patients with axial spondyloarthritis: a systematic literature review.

Objectives: To evaluate the association between smoking and clinical parameters and structural damage in axial spondyloarthritis (axSpA). Methods: We systematically searched MEDLINE, EMBASE and Cochrane Library up to November 2015. We selected articles that analysed the smoking impact on disease activity, functional status, structural damage, physical mobility and life quality. Independent extraction of articles by 2 authors using predefined data fields was performed. Studies quality was graded according to the Oxford Level of Evidence scale. Results: A total of 17 articles were selected for inclusion: 2 case-control, 11 cross sectional and 4 prospective cohort studies, which analysed 4,694 patients. Weak evidence suggested a smoking effect on pain, overall assessment of health, disease activity, physical mobility and life quality in ankylosing spondylitis (AS). Moderate-good evidence revealed higher HAQ-AS among smokers (0.025 units/yr, 95%CI: 0.0071-0.0429, p=0.007). Every additional unit of ASDAS resulted in an increase of 1.9 vs. 0.4 mSASSS units/2 yr in AS smokers vs. non-smokers. Good evidence revealed that cigarette smoking and smoking intensity was associated with spinal radiographic progression in axSpA [mSASSS ≥2 units/2 yr: OR=2.75, 95%CI: 1.25-6.05, p=0.012; mSASSS progression in heavy smokers (> 10 cigarettes/day): OR=3.57, 95%IC: 1.33-9.60, p=0.012]. Conclusions: Published data indicate that smoking has a dose-dependent impact on structural damage progression in axSpA. There is worse HAQ among AS smokers compared to non-smokers. Respect to pain, overall assessment of health, disease activity, physical mobility and life quality, although the evidence level is poor, all evidence points in the same direction: smoking AS patients are worse than non-smoking.pre-print260 K

Characteristics associated with the perception of high-impact disease (PsAID ≥4) in patients with recent-onset psoriatic arthritis. Machine learning-based model

To evaluate which patient and disease characteristics are associated with the perception of high-impact disease (PsAID ≥4) in recent-onset psoriatic arthritis. We performed a multicenter observational prospective study (2-year follow-up, regular annual visits). The study population comprised patients aged ≥18 years who fulfilled the CASPAR criteria and less than 2 years since the onset of symptoms. The dataset was generated using data for each patient at the 3 visits (baseline, first year, and second year of follow-up) matched with the PsAID values at each of the 3 visits. PsAID was categorized into two groups (<4 and ≥4). We trained a logistic regression model and random forest-type and XGBoost machine learning algorithms to analyze the association between the outcome measure and the variables selected in the bivariate analysis. A k-fold cross-validation with k = 5 was performed. The sample comprised 158 patients. Of the patients who attended the clinic, 45.8% scored PsAID ≥4 at baseline; 27.1%, at the first follow-up visit, and in 23.0%, at the second follow-up visit. The variables associated with PsAID ≥4 were, in decreasing order of importance: HAQ, pain, educational level, and physical activity. Higher HAQ (logistic regression coefficient 10.394; IC95% 7.777,13.011), higher pain (5.668; 4.016, 7.320), lower educational level (-2.064; -3.515, -0.613) and high level of physical activity (1.221; 0.158, 2.283) were associated with a higher frequency of PsAID ≥4. The mean values of the measures of validity of the algorithms were all ≥85%. Despite the higher weight given to pain when scoring PsAID, we observed a greater influence of physical function on disease impact

Assessing individual and population variability in degenerative joint disease prevalence using generalized linear mixed models

Objectives In this paper, we introduce the use of generalized linear mixed models (GLMM) as a better alternative to traditional statistical methods for studying factors associated to the prevalence of degenerative joint disease (DJD) in bioarchaeological contexts. Materials and Methods DJD prevalence was assessed for the appendicular joints and the spine of a Spanish population dated from the 15th to the 18th century. Data were analyzed using contingency tables, logistic regression models, and logistic GLMM. Results In general, results from GLMMs find agreement in other methods. However, by being able to analyze the data at the level of individual bones instead of aggregated joints or limbs, GLMMs are capable of revealing associations that are not evident in other frameworks. Discussion Currently widely available in statistical analysis software, GLMMs can accommodate a wide array of data distributions, account for hierarchical correlations, and return estimates of DJD prevalence within individuals and skeletal locations that are unbiased by the effect of covariates. This gives clear advantages for the analysis of bioarchaeological datasets which can lead to more robust and comparable analyses across populations

Minimal disease activity (MDA) in patients with recent-onset psoriatic arthritis : predictive model based on machine learning

Very few data are available on predictors of minimal disease activity (MDA) in patients with recent-onset psoriatic arthritis (PsA). Such data are crucial, since the therapeutic measures used to change the adverse course of PsA are more likely to succeed if we intervene early. In the present study, we used predictive models based on machine learning to detect variables associated with achieving MDA in patients with recent-onset PsA. We performed a multicenter observational prospective study (2-year follow-up, regular annual visits). The study population comprised patients aged ≥18 years who fulfilled the CASPAR criteria and less than 2 years since the onset of symptoms. The dataset contained data for the independent variables from the baseline visit and from follow-up visit number 1. These were matched with the outcome measures from follow-up visits 1 and 2, respectively. We trained a random forest-type machine learning algorithm to analyze the association between the outcome measure and the variables selected in the bivariate analysis. In order to understand how the model uses the variables to make its predictions, we applied the SHAP technique. We used a confusion matrix to visualize the performance of the model. The sample comprised 158 patients. 55.5% and 58.3% of the patients had MDA at the first and second follow-up visit, respectively. In our model, the variables with the greatest predictive ability were global pain, impact of the disease (PsAID), patient global assessment of disease, and physical function (HAQ-Disability Index). The percentage of hits in the confusion matrix was 85.94%. A key objective in the management of PsA should be control of pain, which is not always associated with inflammatory burden, and the establishment of measures to better control the various domains of PsA

Anales de Edafología y Agrobiología Tomo 48 Número 1-2

Efectos de la lluvia ácida: lixiviación de constituyentes en suelos contaminados. Por F. Romero, C. Elejalde y H. Sabin.-- Evaluación de diversas soluciones extractantes de metales Pesados en suelos como indicadoras de las fomas asimilables para las plantas. Por V. Cala, y J. R. Sanchidrian.-- Adsorción de clorprofan (CIPC) por suelos. II. Adsorción por las distintas fracciones granulométricas. Por G. Dios Cancela, J. A. Guillén Alfaro y S. González Careza.-- Influencia del material de partida del suelo y de los tipos de vegetación sobre las lombrices de tierra. Por S. Mato, D. Trigo y D. J. Díaz Cosin.-- Singularidades edafológicas en la comarca La Plana de Requena - Utiel (Valencia). Por R. Boluda Hernández, V. Andréu Pérez, M. Moraleda Esteve y J. Sánchez Díaz.-- Características de los suelos rojos fersialíticos, en la cuenca de México. Por J. F. Cervantes, G. Alfaro Sánchez y M. Meza Sánchez.-- Rasgos micromorfológicos de una catena de suelos afectados por hidromorfía. Por M. Simón, l. Garcfa y J. Fernández.-- Recuperación edáfica de las escombreras de minas de lignito en Galicia. 1)Caracterización de los materiales estériles. Por Mª C. Leirós de la Peña, F. Gil Sotres, M. Carballas Fernández, C. Codesido López, M. a V. González Sangregorio, S. Seoane Lavandeira y F. Guitián Ojea.-- Recuperación edáfica de las escombreras de minas de lignito en Galicia. 2) Influencia del encalado sobre las formas de acidez. Por F. Gil Sotres, Mª C. Leirós de la Peña, Ma V. González Sangregorio, S. Seoane Lavandeira, C. Codesido López y F. Guitián Ojea.-- Influencia de la dolomita en la naturaleza de los suelos. Por J. González Parra, C. González Huecas y A. López Lajilente.-- Producción frente a contaminación en la utilización agrícola de composts urbanos. Por J. M. Murillo, J. M. Hernández, M. Barroso y R. López.-- Efecto del aporte de molibdeno sobre el crecimiento y actividad nitrato -reductasa de Phaseolus vulgaris L. Por M. a S. Martín Gómez y M. a D. Saco Sierra.-- Aplicación de la voltametría de barrido para la determinación de Cd, Pb y Cu en material vegetal. Por R. González Cuesta.-- Diversos aspectos sobre el papel de la materia orgánica humificada en la formación y estabilización de los agregados del suelo. Por C. Fortún y A. Fortún. Influencia de los inviernos cálidos en la adaptación de variedades de melocotonero. Por J. Egea, T. Berenguer, L. Egea y J. E. GarcíaPeer reviewe