Encouraging Use of Seasonal Climate Forecasts by Farmers

What encourages use of seasonal climate forecasts? Considerable effort is being applied in developing seasonal climate forecasts and demonstrating the potential benefits available to farmers from using seasonal climate forecasts. This study examines three factors underlying the use of seasonal climate forecasts by farmers: the level of forecast understanding by farmers, the format presentation of the forecasts, and the attitude of farmers towards the usefulness of forecasts as indicators of future rainfall. Using judgement analysis, the use of forecasts in cropping decisions was determined for 73 Australian farmers. Then a moderated regression analysis was used to predict forecast use from the three underlying factors. The study found that a good understanding of the forecast was more important than the forecast format in predicting its use. However, this main effect of good understanding on higher use was qualified by a three-way interaction, such that seasonal climate forecasts and the forecasts were presented in a frequency format. Thus, the study found all three factors were important in predicting the use of seasonal climate forecasts by farmers. However, relatively little is known about farmer attitudes toward the usefulness of seasonal climate forecasts and how these attitudes arise, and further research is recommended in these areas

Autonomic impairment of patients in coma with different Glasgow coma score assessed with heart rate variability

Primary objective: The objective of this study is to assess the functional state of the autonomic nervous system in healthy individuals and in individuals in coma using measures of heart rate variability (HRV) and to evaluate its efficiency in predicting mortality. Design and Methods: Retrospective group comparison study of patients in coma classified into two subgroups, according to their Glasgow coma score, with a healthy control group. HRV indices were calculated from 7 min of artefact-free electrocardiograms using the Hilbert–Huang method in the spectral range 0.02–0.6 Hz. A special procedure was applied to avoid confounding factors. Stepwise multiple regression logistic analysis (SMLRA) and ROC analysis evaluated predictions. Results: Progressive reduction of HRV was confirmed and was associated with deepening of coma and a mortality score model that included three spectral HRV indices of absolute power values of very low, low and very high frequency bands (0.4-0.6 Hz). The SMLRA model showed sensitivity of 95.65%, specificity of 95.83%, positive predictive value of 95.65%, and overall efficiency of 95.74%. Conclusions: HRV is a reliable method to assess the integrity of the neural control of the caudal brainstem centres on the hearts of patients in coma and to predict patient mortality

J Am Heart Assoc

Background Research links blood pressure variability (BPV) with stroke; however, the association with cerebral small‐vessel disease (CSVD) remains unclear. As BPV and mean blood pressure are interrelated, it remains uncertain whether BPV adds additional information to understanding cerebrovascular morphological characteristics. Methods and Results A systematic review was performed from inception until March 3, 2019. Eligibility criteria included population, adults without stroke (<4 weeks); exposure, BPV quantified by any metric over any duration; comparison, (1) low versus high or mean BPV and (2) people with versus without CSVD; and outcomes, (1) CSVD as subcortical infarct, lacunae, white matter hyperintensities, cerebral microbleeds, or enlarged perivascular spaces; and (2) standardized mean difference in BPV. A total of 27 articles were meta‐analyzed, comprising 12 309 unique brain scans. A total of 31 odds ratios (ORs) were pooled, indicating that higher systolic BPV was associated with higher odds for CSVD (OR, 1.27; 95% CI, 1.14–1.42; I2=85%) independent of mean systolic pressure. Likewise, higher diastolic BPV was associated with higher odds for CSVD (OR, 1.30; 95% CI, 1.14–1.48; I2=53%) independent of mean diastolic pressure. There was no evidence of a pairwise interaction between systolic/diastolic and BPV/mean ORs (P=0.47), nor a difference between BPV versus mean pressure ORs (P=0.58). Fifty‐four standardized mean differences were pooled and provided similar results for pairwise interaction (P=0.38) and difference between standardized mean differences (P=0.70). Conclusions On the basis of the available studies, BPV was associated with CSVD independent of mean blood pressure. However, more high‐quality longitudinal data are required to elucidate whether BPV contributes unique variance to CSVD morphological characteristics