Simplified Symptom Pattern Method for verbal autopsy analysis: multisite validation study using clinical diagnostic gold standards

Background: Verbal autopsy can be a useful tool for generating cause of death data in data-sparse regions around the world. The Symptom Pattern (SP) Method is one promising approach to analyzing verbal autopsy data, but it has not been tested rigorously with gold standard diagnostic criteria. We propose a simplified version of SP and evaluate its performance using verbal autopsy data with accompanying true cause of death.Methods: We investigated specific parameters in SP's Bayesian framework that allow for its optimal performance in both assigning individual cause of death and in determining cause-specific mortality fractions. We evaluated these outcomes of the method separately for adult, child, and neonatal verbal autopsies in 500 different population constructs of verbal autopsy data to analyze its ability in various settings.Results: We determined that a modified, simpler version of Symptom Pattern (termed Simplified Symptom Pattern, or SSP) performs better than the previously-developed approach. Across 500 samples of verbal autopsy testing data, SSP achieves a median cause-specific mortality fraction accuracy of 0.710 for adults, 0.739 for children, and 0.751 for neonates. In individual cause of death assignment in the same testing environment, SSP achieves 45.8% chance-corrected concordance for adults, 51.5% for children, and 32.5% for neonates.Conclusions: The Simplified Symptom Pattern Method for verbal autopsy can yield reliable and reasonably accurate results for both individual cause of death assignment and for determining cause-specific mortality fractions. The method demonstrates that verbal autopsies coupled with SSP can be a useful tool for analyzing mortality patterns and determining individual cause of death from verbal autopsy data

Energy Content of Seeds of Common Sunflowers (Helianthus annuus) in the Diet of Scaled Quail (Callipepla squamata) in Southeastern New Mexico

We analyzed the energy content of seeds of common sunflowers (Helianthus annuus) obtained from the crops of scaled quail (Callipepla squamata) collected from plains-mesa sand-scrub habitat in Eddy and Lea counties, New Mexico. Seeds were removed from crops and dried for 48 hours at 60°C to remove moisture and to standardize masses. Seeds were then analyzed for gross caloric value (i.e., energy content) in an oxygen bomb calorimeter. Energy content of seeds of common sunflowers from New Mexico was greater than that of many seeds previously reported from the diet of scaled quail and other granivorous birds and comparable to previous measurements of seeds of the same species made in Kansas

Energy Content of Seeds of Texas Doveweed (Croton texensis) from the Diet of Mourning Doves (Zenaida macroura) from Southeastern New Mexico

We analyzed the energy content of seeds of Texas doveweed (Croton texensis) obtained from the crops of mourning doves (Zenaida macroura) collected from plains-mesa sand-scrub habitat in Eddy and Lea counties, New Mexico. Seeds were removed from crops and dried for 48 hours at 60°C to remove moisture and to standardize masses. Seeds were then analyzed for gross caloric value (i.e., energy content) in an oxygen bomb calorimeter. Energy content of seeds of Texas doveweed was greater than many seeds previously reported from the diet of mourning doves

Robust metrics for assessing the performance of different verbal autopsy cause assignment methods in validation studies

<p>Abstract</p> <p>Background</p> <p>Verbal autopsy (VA) is an important method for obtaining cause of death information in settings without vital registration and medical certification of causes of death. An array of methods, including physician review and computer-automated methods, have been proposed and used. Choosing the best method for VA requires the appropriate metrics for assessing performance. Currently used metrics such as sensitivity, specificity, and cause-specific mortality fraction (CSMF) errors do not provide a robust basis for comparison.</p> <p>Methods</p> <p>We use simple simulations of populations with three causes of death to demonstrate that most metrics used in VA validation studies are extremely sensitive to the CSMF composition of the test dataset. Simulations also demonstrate that an inferior method can appear to have better performance than an alternative due strictly to the CSMF composition of the test set.</p> <p>Results</p> <p>VA methods need to be evaluated across a set of test datasets with widely varying CSMF compositions. We propose two metrics for assessing the performance of a proposed VA method. For assessing how well a method does at individual cause of death assignment, we recommend the average chance-corrected concordance across causes. This metric is insensitive to the CSMF composition of the test sets and corrects for the degree to which a method will get the cause correct due strictly to chance. For the evaluation of CSMF estimation, we propose CSMF accuracy. CSMF accuracy is defined as one minus the sum of all absolute CSMF errors across causes divided by the maximum total error. It is scaled from zero to one and can generalize a method's CSMF estimation capability regardless of the number of causes. Performance of a VA method for CSMF estimation by cause can be assessed by examining the relationship across test datasets between the estimated CSMF and the true CSMF.</p> <p>Conclusions</p> <p>With an increasing range of VA methods available, it will be critical to objectively assess their performance in assigning cause of death. Chance-corrected concordance and CSMF accuracy assessed across a large number of test datasets with widely varying CSMF composition provide a robust strategy for this assessment.</p

Complexity of coordinated beamforming and scheduling for OFDMA based heterogeneous networks

Coordination is foreseen to be an important component of future mobile radio networks. It is especially relevant in heterogeneous networks, where high power base stations produce strong interference to an underlying layer of low power base stations. This work investigates in detail the achievable performance gains for one coordination technique—coordinated beamforming. It reveals the main factors that influence the throughput of the mobile stations. These findings are combined with an analysis of the computational complexity. As a result, a heuristic algorithm is presented that achieves results close to an exhaustive search with significantly less calculations. Detailed simulation analysis is presented on a realistic network layout