A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables

Light Detection and Ranging (LiDAR) is a remote sensor able to extract three-dimensional information. Environmental models in forest areas have been benefited by the use of LiDAR-derived information in the last years. A multiple linear regression (MLR) with previous stepwise feature selection is the most common method in the literature to develop those models. MLR defines the relation between the set of field measurements and the statistics extracted from a LiDAR flight. Machine learning has emerged as a suitable tool to improve classic stepwise MLR results on LiDAR. Unfortunately, few studies have been proposed to compare the quality of the multiple machine learning approaches. This paper presents a comparison between the classic MLR-based methodology and regression techniques in machine learning (neural networks, support vector machines, nearest neighbour, ensembles such as random forests) with special emphasis on regression trees. The selected techniques are applied to real LiDAR data from two areas in the province of Lugo (Galizia, Spain). The results confirm that classic MLR is outperformed by machine learning techniques and concretely, our experiments suggest that Support Vector Regression with Gaussian kernels statistically outperforms the rest of the techniques.Ministerio de Ciencia y Tecnología TIN2011-28956-C02Junta de Andalucía P12- TIC-1728Universidad Pablo de Olavide APPB81309

Efficacy and Safety of Anakinra Plus Standard of Care for Patients With Severe COVID-19: A Randomized Phase 2/3 Clinical Trial

Efficacy; Safety; COVID-19Eficacia; Seguridad; COVID-19Eficàcia; Seguretat; COVID-19Importance COVID-19 pneumonia is often associated with hyperinflammation. The efficacy and safety of anakinra in treating patients with severe COVID-19 pneumonia and hyperinflammation are still unclear. Objective To assess the efficacy and safety of anakinra vs standard of care alone for patients with severe COVID-19 pneumonia and hyperinflammation. Design, Setting, and Participants The Clinical Trial of the Use of Anakinra in Cytokine Storm Syndrome Secondary to COVID-19 (ANA-COVID-GEAS) was a multicenter, randomized, open-label, 2-group, phase 2/3 clinical trial conducted at 12 hospitals in Spain between May 8, 2020, and March 1, 2021, with a follow-up of 1 month. Participants were adult patients with severe COVID-19 pneumonia and hyperinflammation. Hyperinflammation was defined as interleukin-6 greater than 40 pg/mL, ferritin greater than 500 ng/mL, C-reactive protein greater than 3 mg/dL (rationale, ≥5 upper normal limit), and/or lactate dehydrogenase greater than 300 U/L. Severe pneumonia was considered if at least 1 of the following conditions was met: ambient air oxygen saturation 94% or less measured with a pulse oximeter, ratio of partial pressure O2 to fraction of inspired O2 of 300 or less, and/or a ratio of O2 saturation measured with pulse oximeter to fraction of inspired O2 of 350 or less. Data analysis was performed from April to October 2021. Interventions Usual standard of care plus anakinra (anakinra group) or usual standard of care alone (SoC group). Anakinra was given at a dose of 100 mg 4 times a day intravenously. Main Outcomes and Measures The primary outcome was the proportion of patients not requiring mechanical ventilation up to 15 days after treatment initiation, assessed on an intention-to-treat basis. Results A total of 179 patients (123 men [69.9%]; mean [SD] age, 60.5 [11.5] years) were randomly assigned to the anakinra group (92 patients) or to the SoC group (87 patients). The proportion of patients not requiring mechanical ventilation up to day 15 was not significantly different between groups (64 of 83 patients [77.1%] in the anakinra group vs 67 of 78 patients [85.9%] in the SoC group; risk ratio [RR], 0.90; 95% CI, 0.77-1.04; P = .16). Anakinra did not result in any difference in time to mechanical ventilation (hazard ratio, 1.72; 95% CI, 0.82-3.62; P = .14). There was no significant difference between groups in the proportion of patients not requiring invasive mechanical ventilation up to day 15 (RR, 0.99; 95% CI, 0.88-1.11; P > .99). Conclusions and Relevance In this randomized clinical trial, anakinra did not prevent the need for mechanical ventilation or reduce mortality risk compared with standard of care alone among hospitalized patients with severe COVID-19 pneumonia.Funding for this study was received from the Regional Government of Navarra, Spain (project 0011-3597-2020-000028 to Dr Fanlo), and drugs were provided by the company Swedish Orphan Biovitrum (Sobi)

A Predictive Model and Risk Factors for Case Fatality of COVID-19

This study aimed to create an individualized analysis model of the risk of intensive care unit (ICU) admission or death for coronavirus disease 2019 (COVID-19) patients as a tool for the rapid clinical management of hospitalized patients in order to achieve a resilience of medical resources. This is an observational, analytical, retrospective cohort study with longitudinal follow-up. Data were collected from the medical records of 3489 patients diagnosed with COVID-19 using RT-qPCR in the period of highest community transmission recorded in Europe to date: February-June 2020. The study was carried out in in two health areas of hospital care in the Madrid region: the central area of the Madrid capital (Hospitales de Madrid del Grupo HM Hospitales (CH-HM), n = 1931) and the metropolitan area of Madrid (Hospital Universitario Príncipe de Asturias (MH-HUPA) n = 1558). By using a regression model, we observed how the different patient variables had unequal importance. Among all the analyzed variables, basal oxygen saturation was found to have the highest relative importance with a value of 20.3%, followed by age (17.7%), lymphocyte/leukocyte ratio (14.4%), CRP value (12.5%), comorbidities (12.5%), and leukocyte count (8.9%). Three levels of risk of ICU/death were established: low-risk level (20%). At the high-risk level, 13% needed ICU admission, 29% died, and 37% had an ICU-death outcome. This predictive model allowed us to individualize the risk for worse outcome for hospitalized patients affected by COVID-19

Inter-Rater Variability in the Evaluation of Lung Ultrasound in Videos Acquired from COVID-19 Patients

12 páginas, 7 figuras, 1 tablaLung ultrasound (LUS) allows for the detection of a series of manifestations of COVID-19, such as B-lines and consolidations. The objective of this work was to study the inter-rater reliability (IRR) when detecting signs associated with COVID-19 in the LUS, as well as the performance of the test in a longitudinal or transverse orientation. Thirty-three physicians with advanced experience in LUS independently evaluated ultrasound videos previously acquired using the ULTRACOV system on 20 patients with confirmed COVID-19. For each patient, 24 videos of 3 s were acquired (using 12 positions with the probe in longitudinal and transverse orientations). The physicians had no information about the patients or other previous evaluations. The score assigned to each acquisition followed the convention applied in previous studies. A substantial IRR was found in the cases of normal LUS (κ = 0.74), with only a fair IRR for the presence of individual B-lines (κ = 0.36) and for confluent B-lines occupying 50% (κ = 0.50). No statistically significant differences between the longitudinal and transverse scans were found. The IRR for LUS of COVID-19 patients may benefit from more standardized clinical protocols.This research was partially funded by CDTI (Spanish acronym: Centre for Industrial Tech- nological Development), funding number COI-20201153. Partially supported by the Google Cloud Research Credits program with the funding number GCP19980904, by the project RTI2018-099118- A-I00 founded by MCIU/AEI/FEDER UE and by the European Commission–NextGenerationEU, through CSIC’s Global Health Platform (PTI Salud Global)

Healthcare workers hospitalized due to COVID-19 have no higher risk of death than general population. Data from the Spanish SEMI-COVID-19 Registry

Aim To determine whether healthcare workers (HCW) hospitalized in Spain due to COVID-19 have a worse prognosis than non-healthcare workers (NHCW). Methods Observational cohort study based on the SEMI-COVID-19 Registry, a nationwide registry that collects sociodemographic, clinical, laboratory, and treatment data on patients hospitalised with COVID-19 in Spain. Patients aged 20-65 years were selected. A multivariate logistic regression model was performed to identify factors associated with mortality. Results As of 22 May 2020, 4393 patients were included, of whom 419 (9.5%) were HCW. Median (interquartile range) age of HCW was 52 (15) years and 62.4% were women. Prevalence of comorbidities and severe radiological findings upon admission were less frequent in HCW. There were no difference in need of respiratory support and admission to intensive care unit, but occurrence of sepsis and in-hospital mortality was lower in HCW (1.7% vs. 3.9%; p = 0.024 and 0.7% vs. 4.8%; p<0.001 respectively). Age, male sex and comorbidity, were independently associated with higher in-hospital mortality and healthcare working with lower mortality (OR 0.211, 95%CI 0.067-0.667, p = 0.008). 30-days survival was higher in HCW (0.968 vs. 0.851 p<0.001). Conclusions Hospitalized COVID-19 HCW had fewer comorbidities and a better prognosis than NHCW. Our results suggest that professional exposure to COVID-19 in HCW does not carry more clinical severity nor mortality

100 años investigando el mar. El IEO en su centenario (1914-2014).

Se trata de un libro que pretende divulgar a la sociedad las principales investigaciones multidisciplinares llevadas a cabo por el Instituto Español de Oceanografía durante su primer siglo de vida, y dar a conocer la historia del organismo, de su Sede Central y de los nueve centros oceanográficos repartidos por los litorales mediterráneo y atlántico, en la península y archipiélagos.Kongsberg 20

Importancia de la asociación entre la enfermedad de Kikuchi y el lupus erimatoso sistémico

Necrotizing histiocytic lymphadenopathy or Kikuchi's Disease (KD) is a rare clinical entity that is occasionally associated with systemic lupus erythematosus (SLE). The histologic features of the disorder have been considered indistinguishable to lymphadenitis in patients with SLE, and the clinical symptoms of the two disorders share common features. This article presents a clinical case of a 23-year-old woman with a history of KD who later developed SLE.La linfadenopatía histiocítica necrotizante o enfermedad de Kikuchi (EK) es una entidad clínica que se observa con poca frecuencia y que en ocasiones se asocia con lupus eritematoso sistémico (LES). Se ha considerado que las características histológicas del trastorno son indistinguibles de las de la linfadenitis en sujetos con LES, y los síntomas clínicos de los dos trastornos comparten características comunes. En este artículo se presenta un caso clínico de una mujer de 23 años con antecedente de EK que posteriormente desarrolla LES.