Impact of preoperative clopidogrel in off pump coronary artery bypass surgery: A propensity score analysis

ObjectiveThe aim of our study was to evaluate the impact of recent clopidrogel use before off-pump coronary artery bypass grafting on the postoperative risk of bleeding.MethodsDuring the period January 2003 to December 2006, 1104 consecutive patients underwent off-pump coronary artery bypass grafting. Patients were divided into two groups according to the recent use of clopidrogel (within 7 days). We performed a propensity score to further adjust for differences between the patients with and without recent use of clopidrogel.ResultsMean age was 64 ± 14 years and 87% were male. The clopidrogel group had a greater incidence of patients in unstable condition, requiring emergency coronary bypass grafting, and with a high EuroSCORE. Propensity score analysis selected 88 patients with and 176 without recent use of clopidrogel. By propensity score, the clopidrogel group had higher requirements for fresh frozen plasma units (18.1% vs 8.5%; P = .02), reoperation owing to bleeding (5.6% vs 0.5%; P = .009), and higher need for postoperative mechanical ventilation (4% vs 10%; P = .04), whereas mortality and length of stay were similar between groups.ConclusionRecent use of clopidogrel before off-pump coronary artery bypass grafting is associated with greater risk for bleeding with similar mortality rate

Evaluating the Sensitivity of Mortality Attributable to Pollution to Modeling Choices: A Case Study for Colorado

We evaluated the sensitivity of estimated PM2.5 and NO2 health impacts to varying key input parameters and assumptions including: 1) the spatial scale at which impacts are estimated, 2) using either a single concentration-response function (CRF) or using racial/ethnic group specific CRFs from the same epidemiologic study, 3) assigning exposure to residents based on home, instead of home and work locations. This analysis was carried out for the state of Colorado. We found that the spatial scale of the analysis influences the magnitude of NO2, but not PM2.5, attributable deaths. Using county-level predictions instead of 1 km2 predictions of NO2 resulted in a lower estimate of mortality attributable to NO2 by ~ 50% for all of Colorado for each year between 2000-2020. Using an all-population CRF instead of racial/ethnic group specific CRFs results in a higher estimate of annual mortality attributable to PM2.5 by a factor 1.3 for the white population and a lower estimate of mortality attributable to PM2.5 by factors of 0.4 and 0.8 for Black and Hispanic residents, respectively. Using racial/ethnic group specific CRFs did not result in a different estimation of NO2 attributable mortality for white residents, but led to lower estimates of mortality by a factor of ~ 0.5 for Black residents, and by a factor of 2.9 for to Hispanic residents. Using NO2 based on home instead of home and workplace locations results in a smaller estimate of annual mortality attributable to NO2 for all of Colorado by ~0.980 each year and 0.997 for PM2.5.Comment: 24 pages, 6 figures, 2 table

The influence of soil communities on the temperature sensitivity of soil respiration

Soil respiration represents a major carbon flux between terrestrial ecosystems and the atmosphere, and is expected to accelerate under climate warming. Despite its importance in climate change forecasts, however, our understanding of the effects of temperature on soil respiration (RS) is incomplete. Using a metabolic ecology approach we link soil biota metabolism, community composition and heterotrophic activity, to predict RS rates across five biomes. We find that accounting for the ecological mechanisms underpinning decomposition processes predicts climatological RS variations observed in an independent dataset (n = 312). The importance of community composition is evident because without it RS is substantially underestimated. With increasing temperature, we predict a latitudinal increase in RS temperature sensitivity, with Q10 values ranging between 2.33 ±0.01 in tropical forests to 2.72 ±0.03 in tundra. This global trend has been widely observed, but has not previously been linked to soil communities

Relationship between ecosystem productivity and photosynthetically-active radiation for northern peatlands

We analyzed the relationship between net ecosystem exchange of carbon dioxide (NEE) and irradiance (as photosynthetic photon flux density or PPFD), using published and unpublished data that have been collected during midgrowing season for carbon balance studies at seven peatlands in North America and Europe. NEE measurements included both eddy-correlation tower and clear, static chamber methods, which gave very similar results. Data were analyzed by site, as aggregated data sets by peatland type (bog, poor fen, rich fen, and all fens) and as a single aggregated data set for all peatlands. In all cases, a fit with a rectangular hyperbola (NEE = α PPFD Pmax/(α PPFD + Pmax) + R) better described the NEE-PPFD relationship than did a linear fit (NEE = β PPFD + R). Poor and rich fens generally had similar NEE-PPFD relationships, while bogs had lower respiration rates (R = −2.0μmol m−2s−1 for bogs and −2.7 μmol m−2s−1 for fens) and lower NEE at moderate and high light levels (Pmax = 5.2 μmol m−2s−1 for bogs and 10.8 μmol m−2s−1 for fens). As a single class, northern peatlands had much smaller ecosystem respiration (R = −2.4 μmol m−2s−1) and NEE rates (α = 0.020 and Pmax = 9.2μmol m−2s−1) than the upland ecosystems (closed canopy forest, grassland, and cropland) summarized by Ruimy et al. [1995]. Despite this low productivity, northern peatland soil carbon pools are generally 5–50 times larger than upland ecosystems because of slow rates of decomposition caused by litter quality and anaerobic, cold soils

The effects of CO2, climate and land-use on terrestrial carbon balance, 1920-1992: An analysis with four process-based ecosystem models

The concurrent effects of increasing atmospheric CO2 concentration, climate variability, and cropland establishment and abandonment on terrestrial carbon storage between 1920 and 1992 were assessed using a standard simulation protocol with four process-based terrestrial biosphere models. Over the long-term(1920–1992), the simulations yielded a time history of terrestrial uptake that is consistent (within the uncertainty) with a long-term analysis based on ice core and atmospheric CO2 data. Up to 1958, three of four analyses indicated a net release of carbon from terrestrial ecosystems to the atmosphere caused by cropland establishment. After 1958, all analyses indicate a net uptake of carbon by terrestrial ecosystems, primarily because of the physiological effects of rapidly rising atmospheric CO2. During the 1980s the simulations indicate that terrestrial ecosystems stored between 0.3 and 1.5 Pg C yr−1, which is within the uncertainty of analysis based on CO2 and O2 budgets. Three of the four models indicated (in accordance with O2 evidence) that the tropics were approximately neutral while a net sink existed in ecosystems north of the tropics. Although all of the models agree that the long-term effect of climate on carbon storage has been small relative to the effects of increasing atmospheric CO2 and land use, the models disagree as to whether climate variability and change in the twentieth century has promoted carbon storage or release. Simulated interannual variability from 1958 generally reproduced the El Niño/Southern Oscillation (ENSO)-scale variability in the atmospheric CO2 increase, but there were substantial differences in the magnitude of interannual variability simulated by the models. The analysis of the ability of the models to simulate the changing amplitude of the seasonal cycle of atmospheric CO2 suggested that the observed trend may be a consequence of CO2 effects, climate variability, land use changes, or a combination of these effects. The next steps for improving the process-based simulation of historical terrestrial carbon include (1) the transfer of insight gained from stand-level process studies to improve the sensitivity of simulated carbon storage responses to changes in CO2 and climate, (2) improvements in the data sets used to drive the models so that they incorporate the timing, extent, and types of major disturbances, (3) the enhancement of the models so that they consider major crop types and management schemes, (4) development of data sets that identify the spatial extent of major crop types and management schemes through time, and (5) the consideration of the effects of anthropogenic nitrogen deposition. The evaluation of the performance of the models in the context of a more complete consideration of the factors influencing historical terrestrial carbon dynamics is important for reducing uncertainties in representing the role of terrestrial ecosystems in future projections of the Earth system

The NR4A2/VGF pathway fuels inflammation-induced neurodegeneration via promoting neuronal glycolysis

A disturbed balance between excitation and inhibition (E/I balance) is increasingly recognized as a key driver of neurodegeneration in multiple sclerosis (MS), a chronic inflammatory disease of the central nervous system. To understand how chronic hyperexcitability contributes to neuronal loss in MS, we transcriptionally profiled neurons from mice lacking inhibitory metabotropic glutamate signaling with shifted E/I balance and increased vulnerability to inflammation-induced neurodegeneration. This revealed a prominent induction of the nuclear receptor NR4A2 in neurons. Mechanistically, NR4A2 increased susceptibility to excitotoxicity by stimulating continuous VGF secretion leading to glycolysis-dependent neuronal cell death. Extending these findings to people with MS (pwMS), we observed increased VGF levels in serum and brain biopsies. Notably, neuron-specific deletion of Vgf in a mouse model of MS ameliorated neurodegeneration. These findings underscore the detrimental effect of a persistent metabolic shift driven by excitatory activity as a fundamental mechanism in inflammation-induced neurodegeneration

Effectiveness of a telephone-based intervention for smoking cessation in patients with severe mental disorders : Study protocol for a randomized controlled trial

Background: Up to 75% of inpatients with mental disorders smoke, and their life expectancy is decreased by up to 25 years compared to the general population. Hospitalized patients without monitoring after discharge quickly return to prehospitalization levels of tobacco use. The aim of the 061 QuitMental study is to assess the effectiveness of a multicomponent and motivational telephone-based intervention to stop smoking through a quitline addressed to smokers discharged from mental health hospital wards. Methods: A pragmatic randomized controlled trial, single blinded, will include 2:1 allocation to the intervention group (IG) and the control group (CG). The IG will receive telephone assistance to quit smoking (including psychological and psychoeducational support, and pharmacological treatment advice if required) proactively for 12 months, and the CG will receive only brief advice after discharge. The sample size, calculated with an expected difference of 15 points on smoking abstinence between groups (IG, 20% and CG, 5%), α = 0.05, β = 0.10, and 20% loss, will be 334 participants (IG) and 176 participants (CG). Participants are adult smokers discharged from psychiatric units of five acute hospitals. Measurements include dependent variables (self-reported 7-day point prevalence smoking abstinence (carbon monoxide verified), duration of abstinence, number of quit attempts, motivation, and self-efficacy to quit) and independent variables (age, sex, and psychiatric diagnoses). In data analysis, IG and CG data will be compared at 48 h and 1, 6, and 12 months post discharge. Multivariate logistic regression (odds ratio; 95% confidence interval) of dependent variables adjusted for potential confounding variables will be performed. The number needed to treat to achieve one abstinence outcome will be calculated. We will compare the abstinence rate of enrolled patients between groups. Discussion: This trial evaluates an innovative format of a quitline for smokers with severe mental disorders regardless of their motivation to quit. If effective, the pragmatic nature of the study will permit transfer to routine clinical practice in the National Health System. Trial registration: ClinicalTrials.gov, NCT03230955. Registered on 24 July 2017

Effectiveness of a telephone-based intervention for smoking cessation in patients with severe mental disorders: study protocol for a randomized controlled trial

Background: up to 75% of inpatients with mental disorders smoke, and their life expectancy is decreased by up to 25 years compared to the general population. Hospitalized patients without monitoring after discharge quickly return to prehospitalization levels of tobacco use. The aim of the 061 QuitMental study is to assess the effectiveness of a multicomponent and motivational telephone-based intervention to stop smoking through a quitline addressed to smokers discharged from mental health hospital wards. Methods: a pragmatic randomized controlled trial, single blinded, will include 2:1 allocation to the intervention group (IG) and the control group (CG). The IG will receive telephone assistance to quit smoking (including psychological and psychoeducational support, and pharmacological treatment advice if required) proactively for 12 months, and the CG will receive only brief advice after discharge. The sample size, calculated with an expected difference of 15 points on smoking abstinence between groups (IG, 20% and CG, 5%), α = 0.05, β = 0.10, and 20% loss, will be 334 participants (IG) and 176 participants (CG). Participants are adult smokers discharged from psychiatric units of five acute hospitals. Measurements include dependent variables (self-reported 7-day point prevalence smoking abstinence (carbon monoxide verified), duration of abstinence, number of quit attempts, motivation, and self-efficacy to quit) and independent variables (age, sex, and psychiatric diagnoses). In data analysis, IG and CG data will be compared at 48 h and 1, 6, and 12 months post discharge. Multivariate logistic regression (odds ratio; 95% confidence interval) of dependent variables adjusted for potential confounding variables will be performed. The number needed to treat to achieve one abstinence outcome will be calculated. We will compare the abstinence rate of enrolled patients between groups. Discussion: this trial evaluates an innovative format of a quitline for smokers with severe mental disorders regardless of their motivation to quit. If effective, the pragmatic nature of the study will permit transfer to routine clinical practice in the National Health System

Carbon isotope discrimination of arctic and boreal biomes inferred from remote atmospheric measurements and a biosphere-atmosphere model

Estimating discrimination against ^(13)C during photosynthesis at landscape, regional, and biome scales is difficult because of large-scale variability in plant stress, vegetation composition, and photosynthetic pathway. Here we present estimates of ^(13)C discrimination for northern biomes based on a biosphere-atmosphere model and on National Oceanic and Atmospheric Administration Climate Monitoring and Diagnostics Laboratory and Institute of Arctic and Alpine Research remote flask measurements. With our inversion approach, we solved for three ecophysiological parameters of the northern biosphere (^(13)C discrimination, a net primary production light use efficiency, and a temperature sensitivity of heterotrophic respiration (a Q10 factor)) that provided a best fit between modeled and observed δ^(13)C and CO_2. In our analysis we attempted to explicitly correct for fossil fuel emissions, remote C4 ecosystem fluxes, ocean exchange, and isotopic disequilibria of terrestrial heterotrophic respiration caused by the Suess effect. We obtained a photosynthetic discrimination for arctic and boreal biomes between 19.0 and 19.6‰. Our inversion analysis suggests that Q10 and light use efficiency values that minimize the cost function covary. The optimal light use efficiency was 0.47 gC MJ^(−1) photosynthetically active radiation, and the optimal Q10 value was 1.52. Fossil fuel and ocean exchange contributed proportionally more to month-to-month changes in the atmospheric growth rate of δ^(13)C and CO_2 during winter months, suggesting that remote atmospheric observations during the summer may yield more precise estimates of the isotopic composition of the biosphere