Falling admissions to hospital with febrile seizures in the UK

Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.Peer reviewedPostprin

Comparison of the ICare® rebound tonometer with the Goldmann tonometer in a normal population

The aim of this study was to evaluate the accuracy of measurement of intraocular pressure (IOP) using a new induction/impact rebound tonometer (ICare) in comparison with the Goldmann applanation tonometer (AT). The left eyes of 46 university students were assessed with the two tonometers, with induction tonometry being performed first. The ICare was handled by an optometrist and the Goldmann tonometer by an ophthalmologist. In this study, statistically significant differences were found when comparing the ICare rebound tonometer with applanation tonometry (AT) (p < 0.05). The mean difference between the two tonometers was 1.34 +/- 2.03 mmHg (mean +/- S.D.) and the 95% limits of agreement were +/-3.98 mmHg. A frequency distribution of the differences demonstrated that in more than 80% of cases the IOP readings differed by <3 mmHg between the ICare and the AT. In the present population the ICare overestimates the IOP value by 1.34 mmHg on average when compared with Goldmann tonometer. Nevertheless, the ICare tonometer may be helpful as a screening tool when Goldmann applanation tonometry is not applicable or not recommended, as it is able to estimate IOP within a range of +/-3.00 mmHg in more than 80% of the populatio

Prospective evaluation of a primary care referral pathway for patients with non-alcoholic fatty liver disease.

BACKGROUND & AIMS: We aimed to develop and evaluate a pathway for management of patients with non-alcoholic fatty liver disease (NAFLD) using blood tests to stratify patients in primary care to improve detection of cases of advanced fibrosis and cirrhosis, and avoid unnecessary referrals to secondary care. METHODS: This was a prospective longitudinal cohort study with before-and-after analysis and comparison to unexposed controls. We used a two-step algorithm combining the use of FIB-4 followed by the ELF test if required RESULTS: In total, 3,012 patients were analysed. Use of the pathway detected 5 times more cases of advanced fibrosis (Kleiner F3) and cirrhosis (OR=5.18; 95%CI=2.97 to 9.04; p<0.0001). Unnecessary referrals from primary care to secondary care fell by 81% (OR=0.193; 95%CI 0.111 to 0.337; p<0.0001). Three times more cases of cirrhosis were diagnosed (OR=3.14; 95%CI=1.57 to 24; p=0.00011). Although it was used for only 48% of referrals, significant benefits were observed across all referrals from the practices exposed to the pathway. Unnecessary referrals fell by 77% (OR=0.23; 95% CI=0.658 to 0.082; p=0.006) with a 4-fold improvement in detection of cases of advanced fibrosis and cirrhosis (OR=4.32; 95% CI=1.52 to 12.25; p=0.006). Compared to referrals made before introduction of the pathway, unnecessary referrals fell from 79/83 referrals (95.2%) to 107/152 (70.4%) representing an 88% reduction in unnecessary referrals when the pathway was followed (OR=0.12; 95%CI=0.042 to 0.349; p<0.0001). CONCLUSIONS: The use of non-invasive blood tests for liver fibrosis to stratify patients with NAFLD improves the detection of cases of advanced fibrosis and cirrhosis and reduces unnecessary referrals to secondary care of patients with lesser degrees of liver fibrosis. This strategy improves resource use and benefits patients. LAY SUMMARY: Non-alcoholic fatty liver disease effects up to 30% of the population but only a minority of cases develop liver disease. Our study has shown that established blood tests can be used in primary care to stratify patients with fatty liver disease to reduce unnecessary referrals by 80% and improve the detection of cases of advanced fibrosis 5 fold and cirrhosis 3 fold

Abundances of metal-weak thick-disc candidates

High resolution spectra of 5 candidate metal-weak thick-disc stars suggested by Beers & Sommer-Larsen (1995) are analyzed to determine their chemical abundances. The low abundance of all the objects has been confirmed with metallicity reaching [Fe/H]=-2.9. However, for three objects, the astrometric data from the Hipparcos catalogue suggests they are true halo members. The remaining two, for which proper-motion data are not available, may have disc-like kinematics. It is therefore clear that it is useful to address properties of putative metal-weak thick-disc stars only if they possess full kinematic data. For CS 22894-19 the abundance pattern similar to those of typical halo stars is found, suggesting that chemical composition is not a useful discriminant between thick-disc and halo stars. CS 29529-12 is found to be C enhanced with [C/Fe]=+1.0; other chemical peculiarities involve the s process elements: [Sr/Fe]=-0.65 and [Ba/Fe]=+0.62, leading to a high [Ba/Sr] considerably larger than what is found in more metal-rich carbon-rich stars, but similar to LP 706-7 and LP 625-44 discussed by Norris et al (1997a). Hipparcos data have been used to calculate the space velocities of 25 candidate metal-weak thick-disc stars, thus allowing us to identify 3 bona fide members, which support the existence of a metal-poor tail of the thick-disc, at variance with a claim to the contrary by Ryan & Lambert (1995).Comment: to be published in MNRA

Modeling Long-Term Corn Yield Response to Nitrogen Rate and Crop Rotation

Improved prediction of optimal N fertilizer rates for corn (Zea mays L.) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean (Glycine max L.) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha-1) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR’s were within the historical N rate error range (40–50 kg N ha-1). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward agronomic, economic, and environmental sustainability

A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time (R2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity (R2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined (n = 31) with an average error range of ±38 kg N ha−1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather years to forecast (RRMSE was on average 3%lower). Overall, the proposed approach of using the crop model as a forecasting tool could improve year-to-year predictability of corn yields and optimum N rates. Further improvements in modeling and set-up protocols are needed toward more accurate forecast, especially for extreme weather years with the most significant economic and environmental cost