Soil organic carbon stocks in European croplands and grasslands: How much have we lost in the past decade?

The EU Soil Strategy 2030 aims to increase soil organic carbon (SOC) in agricultural land to enhance soil health and support biodiversity as well as to offset greenhouse gas emissions through soil carbon sequestration. Therefore, the quantification of current SOC stocks and the spatial identification of the main drivers of SOC changes is paramount in the preparation of agricultural policies aimed at enhancing the resilience of agricultural systems in the EU. In this context, changes of SOC stocks (Δ SOCs) for the EU + UK between 2009 and 2018 were estimated by fitting a quantile generalized additive model (qGAM) on data obtained from the revisited points of the Land Use/Land Cover Area Frame Survey (LUCAS) performed in 2009, 2015 and 2018. The analysis of the partial effects derived from the fitted qGAM model shows that land use and land use change observed in the 2009, 2015 and 2018 LUCAS campaigns (i.e. continuous grassland [GGG] or cropland [CCC], conversion grassland to cropland (GGC or GCC) and vice versa [CGG or CCG]) was one of the main drivers of SOC changes. The CCC was the factor that contributed to the lowest negative change on Δ SOC with an estimated partial effect of -0.04 ± 0.01 g C kg-1 year-1 , while the GGG the highest positive change with an estimated partial effect of 0.49 ± 0.02 g C kg-1 year-1 . This confirms the C sequestration potential of converting cropland to grassland. However, it is important to consider that local soil and environmental conditions may either diminish or enhance the grassland's positive effect on soil C storage. In the EU + UK, the estimated current (2018) topsoil (0-20 cm) SOC stock in agricultural land below 1000 m a.s.l was 9.3 Gt, with a Δ SOC of -0.75% in the period 2009-2018. The highest estimated SOC losses were concentrated in central-northern countries, while marginal losses were observed in the southeast.

A flexible copula regression model with Bernoulli and Tweedie margins for estimating the effect of spending on mental health.

We develop a flexible two-equation copula model to address endogeneity of medical expenditures in a distribution regression for health. The expenditure margin uses the compound gamma distribution, a special case of the Tweedie family of distributions, to account for a spike at zero and a highly skewed continuous part. An efficient estimation algorithm offers flexible choices of copulae and link functions, including logit, probit and cloglog for the health margin. Our empirical application revisits data from the Rand Health Insurance Experiment. In the joint model, using random insurance plan assignment as instrument for spending, a $1000 increase is estimated to reduce the probability of a low post-program mental health index by 1.9 percentage points. The effect is not statistically significant. Ignoring endogeneity leads to a spurious positive effect estimate.

Absolute Versus Relative Changes in Cardiac Troponin T: Corresponding Cutoffs Based on Quantile Generalized Additive Models (QGAM).

BACKGROUND: The diagnosis of myocardial injury/infarction (MI) mainly relies on relative changes in cardiac troponin. However, absolute change cutoffs provide greater diagnostic sensitivity. We determined the absolute changes in high-sensitive cardiac troponin T concentrations (absΔhs-cTnT) corresponding to the main relative cutoffs (relΔhs-cTnT), using a quantile generalized additive model (qgam). METHODS: Plasma Δhs-cTnT from patients selected with a time variation of 1 to 6 hours were collected over a 6-year period. The absΔhs-cTnT-to-relΔhs-cTnT relationship was fitted using qgam, after ordered quantile-based normalization (OQN) to reduce the influence of extreme values. RESULTS: The qgam regression curve was nonlinear. Classifying patients (n = 9,753) above the recommended relΔhs-cTnT and predicted absΔhs-cTnT cutoffs as positive, the MI diagnosis rates were similar, and more reliable using the OQN-transformed data-based qgam, as compared to the untransformed data-based one. CONCLUSIONS: Through an optimized qgam-based approach accounting for heavy-tailed distributions, absolute Δhs-cTnT are provided for the corresponding relative Δhs-cTnT cutoffs.

Relationships between renal function variations and relative changes in cardiac troponin T concentrations based on quantile generalized additive models (qgam).

OBJECTIVES: The relationship between high-sensitive cardiac troponin T concentration (hs-cTnT) and renal markers levels is known. However, the extent to which their variations are associated remains to be explored. Objective: model the relationship between relative changes in hs-cTnT (Δhs-cTnT) and variations in creatinine (Δcre) or estimated glomerular filtration rate (ΔeGFR), using a quantile generalized additive model (qgam). METHODS: Concomitant plasma Δhs-cTnT and Δcre from patients aged 18-100 years, selected with a time variation (Δtime) of 3 h-7 days, were collected over a 5.8-year period. Relationships between Δhs-cTnT and covariates Δcre (A) or ΔeGFR (B), including age, Δtime, hour of blood sampling (HSB) and covariates interactions were fitted using qgam. RESULTS: On the whole (n=106567), Δhs-cTnT was mainly associated with Δcre, in a positive and nonlinear way (-21, -6, +5, +20, +55% for -50, -20, +20, +50, +100%, respectively), but to a lesser extent with age (min -9%, max +2%), Δtime (min -4%, max +8%), and HSB (min -5%, max +7%). Δhs-cTnT was negatively associated with ΔeGFR (+46, +7, -5, -11, -20% for -50, -20, +20, +50, +100%, respectively). Classifying Δhs-cTnT as consistent or not with myocardial injury based on recommendations, an interpretation of Δhs-cTnT adjusted for model A or B led to statistically significant but small diagnostic discrepancies (<2%), as compared to an interpretation based on Δhs-cTnT only. CONCLUSIONS: From a laboratory and statistical standpoint, considering renal function variations when interpreting relative changes in cardiac troponin T has a minor impact on the diagnosis rate of myocardial injury.

A generalized Fellner-Schall method for smoothing parameter optimization with application to Tweedie location, scale and shape models.

We consider the optimization of smoothing parameters and variance components in models with a regular log likelihood subject to quadratic penalization of the model coefficients, via a generalization of the method of Fellner (1986) and Schall (1991). In particular: (i) we generalize the original method to the case of penalties that are linear in several smoothing parameters, thereby covering the important cases of tensor product and adaptive smoothers; (ii) we show why the method's steps increase the restricted marginal likelihood of the model, that it tends to converge faster than the EM algorithm, or obvious accelerations of this, and investigate its relation to Newton optimization; (iii) we generalize the method to any Fisher regular likelihood. The method represents a considerable simplification over existing methods of estimating smoothing parameters in the context of regular likelihoods, without sacrificing generality: for example, it is only necessary to compute with the same first and second derivatives of the log-likelihood required for coefficient estimation, and not with the third or fourth order derivatives required by alternative approaches. Examples are provided which would have been impossible or impractical with pre-existing Fellner-Schall methods, along with an example of a Tweedie location, scale and shape model which would be a challenge for alternative methods, and a sparse additive modeling example where the method facilitates computational efficiency gains of several orders of magnitude. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Demographic and Clinical Characteristics to Predict Paroxysmal Atrial Fibrillation: Insights from an Implantable Loop Recorder Population.

BACKGROUND: There is growing interest in detecting paroxysmal atrial fibrillation (PAF) to identify patients at high risk of thromboembolic stroke. The implantable loop recorder (ILR) is emerging as a powerful new tool in the diagnosis of PAF. Widespread implantation has significant cost implications and their use must be targeted at those patients at most risk. METHODS: We retrospectively studied a population of 200 adult patients who underwent ILR implantation for the investigation of syncope or palpitations. Clinical data, baseline electrocardiogram (ECG) characteristics, and echocardiographic data were collected. All ECGs and electrograms (EGMs) were scrutinized by two blinded investigators. PAF incidence was defined as episodes lasting >30 seconds on EGMs recorded in ILR memory. RESULTS: Our ILR population consists of 200 patients, 111 (56%) male, with a mean age of 61.4 years (range 19-95). PAF was detected in 42 patients. The following factors were significant predictors of PAF by multivariate logistic regression analysis: cigarette smoking (odds ratio [OR] = 3.73, 95% confidence interval [CI] = 1.40-10.24, P = 0.009) and incomplete right bundle branch block (IRBBB; OR = 9.04, 95% CI = 2.51-34.64, P = 0.00088). Significant differences included incidence of IRBBB (P = 0.012), cigarette smoking (P = 0.026), hypercholesterolemia (P = 0.015), age (P = 0.002), estimated glomerular filtration rate (P = 0.031), left atrial volume (P = 0.019), and PR interval (P = 0.031). The PAF group had significantly higher CHA2 DS2 -VASc scores (P = 0.01). CONCLUSIONS: Our study reports predictive factors for PAF in an ILR population. We suggest that cigarette smoking and IRBBB are independently associated with paroxysmal AF in patients presenting with palpitations or syncope.

Clinical Predictors of Pacemaker Implantation in Patients with Syncope Receiving Implantable Loop Recorder with or without ECG Conduction Abnormalities.

BACKGROUND: Implantable loop recorders (ILR) allow prolonged cardiac rhythm monitoring and improved diagnostic yield in syncope patients. Predictive factors for pacemaker (PM) implantation in the ILR population with unexplained syncope have not been adequately investigated. In this single center, retrospective, observational study we investigated factors that predict PM implantation in this population. METHODS: We retrospectively analyzed our ILR database of patients aged over 18 years who underwent ILR implantation for unexplained syncope between January 2009 and June 2013. Patient case notes were examined for demographics, history, electrocardiogram (ECG) abnormalities, investigations, and events during follow-up. The primary end-point was the detection of a symptomatic or asymptomatic bradycardia requiring PM implantation. RESULTS: During a period of 4.5 years, 200 patients were implanted with ILR for unexplained syncope, of who n = 33 (16.5%) had clinically significant bradycardia requiring PM implantation. After multivariable analysis, history of injury secondary to syncope was found to be the strongest independent predictor for PM implantation (odds ratio [OR]:9.1; P < 0.001; 95% confidence interval [CI]: (3.26-26.81). Other significant predictors included female sex, PR interval > 200msec, and age >75 years. In patients without conduction abnormalities on the ECG, history of injury secondary to syncope was found to be the strongest independent predictor for PM implantation (OR: 8.16; P = 0.00027; 95% [CI]: (2.67-26.27). CONCLUSIONS: A history of injury secondary to syncope and female sex were independent predictive factors for bradycardia necessitating PM implantation in patients receiving an ILR for syncope with or without ECG conduction abnormalities.

Ambulatory blood pressure as risk factor for long-term kidney function decline in the general population: a distributional regression approach.

The results of randomized controlled trials are unclear about the long-term effect of blood pressure (BP) on kidney function assessed as the glomerular filtration rate (GFR) in persons without chronic kidney disease or diabetes. The limited duration of follow-up and use of imprecise methods for assessing BP and GFR are important reasons why this issue has not been settled. Since a long-term randomized trial is unlikely, we investigated the association between 24-h ambulatory BP (ABP) and measured GFR in a cohort study with a median follow-up of 11 years. The Renal Iohexol Clearance Survey (RENIS) cohort is a representative sample of persons aged 50 to 62 years without baseline cardiovascular disease, diabetes, or kidney disease from the general population of Tromsø in northern Norway. ABP was measured at baseline, and iohexol clearance at baseline and twice during follow-up. The study population comprised 1589 persons with 4127 GFR measurements. Baseline ABP or office BP components were not associated with the GFR change rate in multivariable adjusted conventional regression models. In generalized additive models for location, scale, and shape (GAMLSS), higher daytime systolic, diastolic, and mean arterial ABP were associated with a slight shift of the central part of the GFR distribution toward lower GFR and with higher probability of GFR < 60 mL/min/1.73 m2 during follow-up (p < 0.05). The use of a distributional regression method and precise methods for measuring exposure and outcome were necessary to detect an unfavorable association between BP and GFR in this study of the general population.