additive models
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2022 ◽  
Author(s):  
Flavio Azevedo Figueiredo ◽  
Lucas Emanuel Ferreira Ramos ◽  
Rafael Tavares Silva ◽  
Magda Carvalho Pires ◽  
Daniela Ponce ◽  
...  

Background: Acute kidney injury (AKI) is frequently associated with COVID–19 and the need for kidney replacement therapy (KRT) is considered an indicator of disease severity. This study aimed to develop a prognostic score for predicting the need for KRT in hospitalized COVID–19 patients. Methods: This study is part of the multicentre cohort, the Brazilian COVID–19 Registry. A total of 5,212 adult COVID–19 patients were included between March/2020 and September/2020. We evaluated four categories of predictor variables: (1) demographic data; (2) comorbidities and conditions at admission; (3) laboratory exams within 24 h; and (4) the need for mechanical ventilation at any time during hospitalization. Variable selection was performed using generalized additive models (GAM) and least absolute shrinkage and selection operator (LASSO) regression was used for score derivation. The accuracy was assessed using the area under the receiver operating characteristic curve (AUCROC). Risk groups were proposed based on predicted probabilities: non-high (up to 14.9%), high (15.0 to 49.9%), and very high risk (≥ 50.0%). Results: The median age of the model–derivation cohort was 59 (IQR 47–70) years, 54.5% were men, 34.3% required ICU admission, 20.9% evolved with AKI, 9.3% required KRT, and 15.1% died during hospitalization. The validation cohort had similar age, sex, ICU admission, AKI, required KRT distribution and in–hospital mortality. Thirty–two variables were tested and four important predictors of the need for KRT during hospitalization were identified using GAM: need for mechanical ventilation, male gender, higher creatinine at admission, and diabetes. The MMCD score had excellent discrimination in derivation (AUROC = 0.929; 95% CI 0.918–0.939) and validation (AUROC = 0.927; 95% CI 0.911–0.941) cohorts an good overall performance in both cohorts (Brier score: 0.057 and 0.056, respectively). The score is implemented in a freely available online risk calculator (https://www.mmcdscore.com/). Conclusion: The use of the MMCD score to predict the need for KRT may assist healthcare workers in identifying hospitalized COVID–19 patients who may require more intensive monitoring, and can be useful for resource allocation.


2022 ◽  
Author(s):  
Zhigang Hu ◽  
Yufeng Tian ◽  
Xinyu Song ◽  
Fanjun Zeng ◽  
Ailan Yang

Abstract Background Sarcopenia was listed as a treatment trait in behavioral/risk factors of severe asthma, but studies between asthma and sarcopenia were scant. This study plans to determine the associations between sarcopenia with asthmatic prevalence, symptoms, lung function and comorbidity. Methods 15404 individuals from the China Health and Retirement Longitudinal Study(CHARLS) and 10263 individuals from Study on global AGEing and adult health(SAGE) in China were included in this study. Four components of this study were respectively used to assess bidirectional association in the prevalence between sarcopenia with asthma, and estimate the relationships between sarcopenia with asthmatic symptoms, lung function and comorbidity via generalized additive models. The 10-item Center for Epidemiological Studies–Depression Scale≥12 scores was classified as depression in CHARLS. Results In CHARLS and SAGE, the prevalence of sarcopenia in asthmatics was higher than those without asthma. Asthmatics with sarcopenia had a significantly increased prevalence of severe shortness of breath(sarcopenia yes vs no, adjusted OR=3.71, 95%CI: 1.43-9.60) and airway obstruction in SAGE(sarcopenia yes vs no, adjusted OR=6.82, 95%CI: 2.54-18.34) and an obvious reduction of PEF in CHARLS and SAGE(sarcopenia yes vs no, adjusted RR=0.86, 95%CI: 0.82-0.91) compared to asthmatics without sacropenia. The presence of sarcopenia was positively associated with the prevalence of chronic obstructive pulmonary disease(sarcopenia yes vs no, adjusted OR=5.76, 95%CI:2.01-16.5) and depression(sarcopenia yes vs no, adjusted OR=1.87, 95%CI:1.11-3.14) in asthmatics. Conclusions Our findings indicated that sarcopenia partakes in the development of asthma by affecting lung function and comorbidity and maybe considered a treatable trait of asthma management.


Author(s):  
Oskar Allerbo ◽  
Rebecka Jörnsten

AbstractNon-parametric, additive models are able to capture complex data dependencies in a flexible, yet interpretable way. However, choosing the format of the additive components often requires non-trivial data exploration. Here, as an alternative, we propose PrAda-net, a one-hidden-layer neural network, trained with proximal gradient descent and adaptive lasso. PrAda-net automatically adjusts the size and architecture of the neural network to reflect the complexity and structure of the data. The compact network obtained by PrAda-net can be translated to additive model components, making it suitable for non-parametric statistical modelling with automatic model selection. We demonstrate PrAda-net on simulated data, where we compare the test error performance, variable importance and variable subset identification properties of PrAda-net to other lasso-based regularization approaches for neural networks. We also apply PrAda-net to the massive U.K. black smoke data set, to demonstrate how PrAda-net can be used to model complex and heterogeneous data with spatial and temporal components. In contrast to classical, statistical non-parametric approaches, PrAda-net requires no preliminary modeling to select the functional forms of the additive components, yet still results in an interpretable model representation.


Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 159
Author(s):  
Horacio Ernesto Zagarese ◽  
Nadia R. Diovisalvi ◽  
María de los Ángeles González Sagrario ◽  
Irina Izaguirre ◽  
Paulina Fermani ◽  
...  

Phytoplankton size structure has profound consequences on food-web organization and energy transfer. Presently, picocyanobacteria (size < 2 µm) represent a major fraction of the autotrophic plankton of Pampean lakes. Glyphosate is known to stimulate the development of picocyanobacteria capable of degrading the herbicide. Due to the worldwide adoption of glyphosate-resistant crops, herbicide usage has increased sharply since the mid-1990s. Unfortunately, there are very few studies (none for the Pampa region) reporting picocyanobacteria abundance before 2000. The proliferation of µm sized particles should decrease Secchi disc depth (ZSD). Therefore ZSD, conditional to chlorophyll-a, may serve as an indicator of picocyanobacteria abundance. We use generalized additive models (GAMs) to analyze a “validation” dataset consisting of 82 records of ZSD, chlorophyll-a, and picocyanobacteria abundance from two Pampean lakes surveys (2009 and 2015). In support of the hypothesis, ZSD was negatively related to picocyanobacteria after accounting for the effect of chlorophyll-a. We then fitted a “historical” dataset using hierarchical GAMs to compare ZSD conditional to chlorophyll-a, before and after 2000. We estimated that ZSD levels during 2000–2021 were, on average, only about half as deep as those during 1980–1999. We conclude that the adoption of glyphosate-resistant crops has stimulated outbreaks of picocyanobacteria populations, resulting in lower water transparency.


eLife ◽  
2022 ◽  
Vol 11 ◽  
Author(s):  
David Bann ◽  
Liam Wright ◽  
Tim J Cole

Background: Risk factors or interventions may affect the variability as well as the mean of health outcomes. Understanding this can aid aetiological understanding and public health translation, in that interventions which shift the outcome mean and reduce variability are typically preferable to those which affect only the mean. However, most commonly used statistical tools do not test for differences in variability. Tools that do have few epidemiological applications to date, and fewer applications still have attempted to explain their resulting findings. We thus provide a tutorial for investigating this using GAMLSS (Generalised Additive Models for Location, Scale and Shape). Methods: The 1970 British birth cohort study was used, with body mass index (BMI; N=6,007) and mental wellbeing (Warwick-Edinburgh Mental Wellbeing Scale; N=7,104) measured in midlife (42-46 years) as outcomes. We used GAMLSS to investigate how multiple risk factors (sex, childhood social class and midlife physical inactivity) related to differences in health outcome mean and variability. Results: Risk factors were related to sizable differences in outcome variability-for example males had marginally higher mean BMI yet 28% lower variability; lower social class and physical inactivity were each associated with higher mean and higher variability (6.1% and 13.5% higher variability, respectively). For mental wellbeing, gender was not associated with the mean while males had lower variability (-3.9%); lower social class and physical inactivity were each associated with lower mean yet higher variability (7.2% and 10.9% higher variability, respectively). Conclusions: The results highlight how GAMLSS can be used to investigate how risk factors or interventions may influence the variability in health outcomes. This underutilised approach to the analysis of continuously distributed outcomes may have broader utility in epidemiologic, medical, and psychological sciences. A tutorial and replication syntax is provided online to facilitate this (https://osf.io/5tvz6/). Funding: DB is supported by the Economic and Social Research Council (grant number ES/M001660/1), The Academy of Medical Sciences / Wellcome Trust ('Springboard Health of the Public in 2040' award: HOP001/1025); DB and LW are supported by the Medical Research Council (MR/V002147/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


2022 ◽  
Vol 12 ◽  
Author(s):  
Ryan Tangney ◽  
David J. Merritt ◽  
Ben P. Miller

Changes in fire regimes due to climate change and fire management practices are affecting the timing, length, and distribution of vegetation fires throughout the year. Plant species responses and tolerances to fire differ from season to season and are influenced by species-specific phenological processes. The ability of seeds to tolerate extreme temperatures associated with fire is one of these processes, with survival linked to seed moisture content at the time of exposure. As fire is more often occurring outside historic dry fire seasons, the probability of fire occurring when seeds are hydrated may also be increasing. In this study, we set out to understand the seasonal dynamics of seed hydration for seeds of Banksia woodland species, and how certain seed traits interact with environmental conditions to influence survival of high temperatures associated with fire. We measured the moisture content of seeds buried to 2 cm in the soil seed bank for four common native species and one invasive species on a weekly basis throughout 2017, along with soil moisture content and environmental correlates. We determined water sorption isotherms at 20°C for seeds of each species and used these functions to model weekly variation in seed water activity and predict when seeds are most sensitive to soil heating. Using Generalised additive models (GAMs), we were able to describe approximately 67% of the weekly variance in seed water activity and explored differences in seed hydration dynamics between species. Seed water activity was sufficiently high (i.e., ≥ 0.85 aw) so as to have created an increased risk of mortality if a fire had occurred during an almost continuous period between May and November in the study period (i.e., 2017). There were brief windows when seeds may have been in a dry state during early winter and late spring, and also when they may have been in a wet state during summer and late autumn. These data, and the associated analyses, provide an opportunity to develop approaches to minimize seed mortality during fire and maximize the seed bank response.


2022 ◽  
Vol 119 (2) ◽  
pp. e2113032119
Author(s):  
Anaïs Médieu ◽  
David Point ◽  
Takaaki Itai ◽  
Hélène Angot ◽  
Pearse J. Buchanan ◽  
...  

Pacific Ocean tuna is among the most-consumed seafood products but contains relatively high levels of the neurotoxin methylmercury. Limited observations suggest tuna mercury levels vary in space and time, yet the drivers are not well understood. Here, we map mercury concentrations in skipjack tuna across the Pacific Ocean and build generalized additive models to quantify the anthropogenic, ecological, and biogeochemical drivers. Skipjack mercury levels display a fivefold spatial gradient, with maximum concentrations in the northwest near Asia, intermediate values in the east, and the lowest levels in the west, southwest, and central Pacific. Large spatial differences can be explained by the depth of the seawater methylmercury peak near low-oxygen zones, leading to enhanced tuna mercury concentrations in regions where oxygen depletion is shallow. Despite this natural biogeochemical control, the mercury hotspot in tuna caught near Asia is explained by elevated atmospheric mercury concentrations and/or mercury river inputs to the coastal shelf. While we cannot ignore the legacy mercury contribution from other regions to the Pacific Ocean (e.g., North America and Europe), our results suggest that recent anthropogenic mercury release, which is currently largest in Asia, contributes directly to present-day human mercury exposure.


2022 ◽  
Vol 802 ◽  
pp. 149927
Author(s):  
Marcus W. Beck ◽  
Perry de Valpine ◽  
Rebecca Murphy ◽  
Ian Wren ◽  
Ariella Chelsky ◽  
...  

2022 ◽  
pp. 102937
Author(s):  
Nathan M. Muncy ◽  
Adam Kimbler ◽  
Ariana M. Hedges-Muncy ◽  
Dana L. McMakin ◽  
Aaron T. Mattfeld

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