Soil penetration resistance analysis by multivariate and geostatistical methods

The penetration resistance (PR) is a soil attribute that allows identifies areas with restrictions due to compaction, which results in mechanical impedance for root growth and reduced crop yield. The aim of this study was to characterize the PR of an agricultural soil by geostatistical and multivariate analysis. Sampling was done randomly in 90 points up to 0.60 m depth. It was determined spatial distribution models of PR, and defined areas with mechanical impedance for roots growth. The PR showed a random distribution to 0.55 and 0.60 m depth. PR in other depths analyzed showed spatial dependence, with adjustments to exponential and spherical models. The cluster analysis that considered sampling points allowed establishing areas with compaction problem identified in the maps by kriging interpolation. The analysis with main components identified three soil layers, where the middle layer showed the highest values of PR.La resistencia a la penetración (RP) es un atributo del suelo que permite identificar zonas con restricciones debido a la compactación, que se traduce en impedancia mecánica para el desarrollo de las raíces y en una menor productividad de los cultivos. El objetivo del presente trabajo fue caracterizar la RP de un suelo agrícola, mediante análisis geoestadístico y multivariado. El muestreo se realizó de manera aleatoria en 90 puntos, hasta una profundidad de 0,60 m. Se determinaron los modelos de distribución espacial de la RP y se delimitaron áreas con problemas de impedancia mecánica de las raíces. La RP presentó distribución aleatoria a 0,55 y 0,60 m de profundidad. La RP en las otras profundidades analizadas mostraron dependencia espacial, con ajustes a modelos exponenciales y esféricos. El análisis jerárquico que consideró puntos de muestreo, permitió establecer zonas con problemas de compactación, identificadas en los mapas obtenidos mediante interpolación por kriging. El análisis de componentes principales permitió identificar tres capas de suelo, donde la capa intermedia fue la que presentó los mayores valores de RP

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran