Additive Model Research Articles

A comparison of statistical and machine learning models for spatio-temporal prediction of ambient air pollutant concentrations in Scotland

AbstractThe spatio-temporal prediction of air pollutant concentrations is vital for assessing regulatory compliance and for producing exposure estimates in epidemiological studies. Numerous approaches have been utilised for making such predictions, including land use regression models, additive models, spatio-temporal smoothing models and machine learning prediction algorithms. However, relatively few studies have compared the predictive performance of these models thoroughly, which is one of the novel contributions of this paper. For the specific challenge of predicting monthly average concentrations of NO$$_{2}$$ 2 , PM$$_{10}$$ 10 and $$\hbox {PM}_{2.5}$$ PM 2.5 in Scotland, we find that random forests typically outperform (or are as good as) more traditional statistical prediction approaches. Additionally, we utilise the best performing model to provide a new data resource, namely, predictions of monthly average concentrations (with uncertainty quantification) of the above pollutants on a regular 1 km$$^{2}$$ 2 grid for all of Scotland between 2016 and 2020.

Immunity Dynamics of Neisseria meningitidis Serogroups ACYW from Birth and Following Vaccination

Background: Serosurveillance of epidemic cerebrospinal meningitis (ECM) in healthy individuals is crucial for assessing disease risk and evaluating the effectiveness of vaccinations. However, this practical work is rare in China. Methods: We conducted cross-section serosurveillance in Guangzhou, Zhanjiang, and Heyuan in Guangdong Province, measuring Anti-Nm IgG with serogroups A, C, Y, and W, and analyzed the trends using a generalized additive model (GAM). Results: During 2019–2022, 7752 participants were included. The overall antibody positivity rate for serogroups A, C, Y, and W were 60.75%, 15.51%, 32.83%, and 14.56%, respectively. High Anti-Nm IgG was in children aged 0–5 and 5–10 years old. Geometric mean concentrations (GMCs) of Anti-Nm IgG were higher and correlated positively with vaccine doses compared with unvaccinated individuals. The GMC showed a consistent decrease trend in the vaccinated and a U-shaped curve in populations. The declined rates of GMC were 1.59 (95% CI: 1.03, 2.14) µg/mL, 1.65 (95% CI: 1.28, 2.03), 0.62 (95% CI: 0.22, 1.03), and 0.31 (95% CI: 0.08, 0.53) µg/mL per year for serogroups A, C, Y, and W, respectively. Conclusions: There were differences in antibody positivity rate and GMC for the four serogroups of ECM in the healthy individuals of Guangdong Province, with serogroup A showing the highest, and the demographic differences highlighted the high seroprevalence of Neisseria meningitidis in younger people. The variable prevalence rates among serogroups A, C, Y, and W and the observed decline in antibody titers underscore the need for adjustments in the immunization program targeting the meningococcal vaccine.

Phrasal frequency and literacy as predictors of individual differences in on-line processing and comprehension of english complex NP subject-verb agreement

AbstractWe present experimental evidence suggesting that frequency and literacy predict online processing and comprehension of subject-verb agreement constructions by adult native speakers of English. We measured participants’ eye fixations, reaction times, and response accuracy in a forced-choice task using audio-visual eye-tracking paradigm. Participants completed a battery of tasks, inc. the Literacy Rating Scale (Tarone et al., Literacy and Second Language Oracy-Oxford Applied Linguistics, Oxford University Press, 2013), Agreement Judgement Task (e.g., Veenstra et al., Frontiers in Psychology 5:783, 2014). The AJT involved matching an auditorily presented subject phrase to one of two images of easily distinguishable colours presented on a computer screen (e.g., stars, circles). Participants heard 42 test sentences, counterbalanced across the three types: Type 1 (e.g., ‘The stars with the circles are blue’), Type 2 (e.g., ‘The star with the circles is blue’) and Type 3 (e.g., ‘The star with the circles are blue’*. Type 1 and Type 2 constructions are considerably more frequent in writing than in speech (Miller et al., Spontaneous spoken language: Syntax and discourse, Oxford University Press on Demand, 1998) with Type 2 producing more attraction errors (Bock et al., Cognitive Psychology 43:83–128, 2001; Becker, L., & Dąbrowska, E. (2020). Does experience with written language influence grammaticality intuitions? UK Cognitive Linguistics Conference: University of Birmingham [conference presentation].). Data were analysed with linear mixed effects models and generalised additive models. Results show lower literacy participants took longer to process sentential cues and made more attraction errors. These findings support usage-based research showing frequency and experience effects on online comprehension of canonical and non-canonical constructions (Farmer, T. A., Misyak, J. B., & Christiansen, M. H. (2012). Individual differences in sentence processing. In Cambridge handbook of psycholinguistics (pp. 353-364)., Street, Language Sciences 59:192–203, 2017), detection and production of agreement attraction errors (Becker, L., & Dąbrowska, E. (2020). Does experience with written language influence grammaticality intuitions? UK Cognitive Linguistics Conference: University of Birmingham [conference presentation].) and demonstrate how linguistic and attentional processes interact (Tomlin and Myachykov, Attention and salience, Handbook of Cognitive Linguistics, 2015). They also complement corpus-based studies by providing evidence that native speakers are sensitive to observed distributions (Miller et al., Spontaneous spoken language: Syntax and discourse, Oxford University Press on Demand, 1998).

Assessment of fuzzy logic to enhance species distribution modelling of two cryptic wood boring beetle species in Australia

AbstractFuzzy logic presents a promising approach for Species Distribution Modelling by generating a value that can be used for comparative purposes termed ‘environmental favourability’. In contrast to ‘presence probability’, ‘environmental favourability’ remains robust regardless of species prevalence. This characteristic facilitates effective comparisons across species with varying levels of prevalence. In this study, presence probability was predicted using three commonly used Species Distribution Models: Generalised Linear Model, Generalised Additive Modelling, and Boosted Regression Trees for two beetle species, Euwallacea fornicatus and Euwallacea perbrevis in Australia. Fuzzy logic was then employed to derive environmental favourability values based on these models. Additionally, Maxent modelling was included to compare prediction outputs and facilitate a comprehensive analysis. Model performance was evaluated using standard metrics (Area under the receiver operating characteristic curve, True statistical skill, Correct classification rate), as well as Hosmer-Lemeshow test. The research explored fuzzy similarity, fuzzy intersection and potential biotic interaction of these closely related borers, and revealed a favourable distribution pattern for Euwallacea fornicatus across Australia. This study supports the efficacy of fuzzy logic in Species Distribution Modelling and highlights the value of environmental favourability function in enhancing the comparative analysis of the geographical relationship across species. This approach offers a more nuanced perspective on Species Distribution Modelling.

Rock glacier inventory and predictive modeling in the Mackenzie Mountains: predicting rock glacier likelihood with a generalized additive model

Rock glaciers have been the subject of extensive research in recent years due to their potential to serve as indicators of past and present climate conditions and their potential impacts on water resources. Location and descriptive rock glacier data within the Mackenzie Mountains were used to build a rock glacier inventory that will serve as a valuable resource for future research and monitoring efforts. Additionally, this study maps the likelihood of rock glacier presence using extracted variables in a generalized additive model (GAM). The model incorporates attribute data, including potential incoming solar radiation (PISR), topographic position index (TPI), slope, elevation, and lithology as controls for rock glacier development. Topographic data were compiled for three study regions of the Mackenzie Mountains from a 30 m digital elevation model (DEM). The analysis of the GAM showed that the most significant explanatory variables were PISR, elevation, slope, and TPI. The GAM model had an accuracy of 0.87 with a sensitivity of 0.92. This study provides important insights into the controls, distribution, and dynamics of rock glaciers in the Mackenzie Mountains, as well as both the limitations and the potential of statistical models in predicting their occurrence.

Species Traits and Island Biogeography: Wing Metrics Linked to Avian Dispersal Ability Predict Species Occurrence on Remote Islands Worldwide

ABSTRACTAimWe assessed the influence of island isolation on the composition of insular bird assemblages with a particular focus on species traits associated with dispersal. To do so, we tested whether ecomorphological metrics of dispersal ability, namely hand‐wing index and Kipp's distance, increase with increasing island isolation.LocationGlobal.TaxonBirds.MethodsWe integrated global datasets of island characteristics with distribution and ecomorphological trait information of birds; our final dataset comprised information for 2034 native, resident and terrestrial species inhabiting 2399 islands. Species restricted to islands were removed to avoid potentially confounding effects of speciation, such as the evolution of flightlessness or poor flight on islands. Using the generalised additive models, we tested for the relationship between hand‐wing index or Kipp's distance and island isolation, accounting for the effects of island area and spatial autocorrelation. We performed the analyses separately for (i) continental and oceanic islands and (ii) for all terrestrial birds and for passerine birds only.ResultsHand‐wing index and Kipp's distance were positively related to island isolation on oceanic islands, that is bird communities on more isolated oceanic islands were composed of species with wings that had a higher aspect ratio and were more elongated. However, this relationship did not hold for continental islands. We found these patterns to be consistent for all terrestrial birds as well as for passerine birds only.Main ConclusionOur study provides strong evidence that island isolation influences the trait composition of island bird assemblages at a global scale. Our results highlight the variation of dispersal‐related ecomorphological traits among bird assemblages on islands, suggesting that these traits play an important role in mediating the influence of island isolation on community assembly processes on islands.

Shedding light on trawl fishing activity in the Mediterranean Sea with remote sensing data

Abstract This study uses Synthetic Aperture Radar (SAR) vessel detections and Automatic Identification System (AIS) to predict trawl fishing intensity and distribution of fishing activity in areas where public AIS data are not available. By processing SAR data, considering spatial and temporal autocorrelation, and building a General Additive Model, a statistical relationship between SAR vessel detections and AIS fishing activity was established. The study provides spatially explicit estimates of trawler fishing activity, compared with official fleet records published by the General Fisheries Commission of the Mediterranean, revealing the distribution and intensity of trawl fishing activity not previously publicly tracked. Fishing grounds in the Strait of Sicily along the coast of Tunisia and North of Egypt showed an intensity of trawl fishing activity similar to the Adriatic Sea. This area is historically known to be subject to the highest trawling pressure in the Mediterranean, and also as one of the most heavily trawled regions in the world. The study shows that the integration of remote sensing data, such as SAR, offers a promising avenue to overcome data gaps and improve fisheries management in the Mediterranean where only a portion of the fishing fleet is publicly tracked.

Duration Models for Subduction Earthquakes

ABSTRACT An empirical model for the significant duration of acceleration for subduction zone earthquakes is developed based on the normalized Arias intensity. The data set is a subset from the Next Generation Attenuation-Subduction database (Bozorgnia and Stewart, 2020). The functional form of the duration model uses an additive model for the source, path, and site terms with three lognormally distributed random effects for the source, path, and site. The remaining aleatory variability is modeled by a power-normal distribution. There are two parts of the duration model: a model for the D5–75 duration and a model for the D5–X/D5–75 ratio, which can be combined with the D5–75 model to estimate the DY–X for any interval. The D5–75 model includes regionalized coefficients for Japan, New Zealand, South America, and Taiwan. The large-magnitude (M >7) scaling of the D5–75 model is much weaker than the recent duration model by Bahrampouri et al. (2021). The residuals of the D5–75 model are negatively correlated with the lnPGA residuals with a correlation coefficient of −0.50 such that above-average peak ground acceleration values are associated with below-average duration values.

Abstract 4126628: Worse Cardiac Structure and Function is Associated with Decline in Multiple Domains of Cognitive Function: the Atherosclerosis Risk in Communities (ARIC) Study

Background: Cognitive impairment is cross-sectionally associated with worse cardiac structure/function. However, limited data exist regarding cardiac structure/function and longitudinal changes in cognitive function. Objective: Determine the association of cardiac structure and function with longitudinal changes in cognitive performance in late life. Methods: Among HF- and dementia-free participants in the community-based ARIC study who attended the 5th study visit (V5; 2011-2013), underwent protocol echocardiography, and completed a neurocognitive test battery at both V5 and study Visit 6 (V6; 2015-17), we assessed associations of cardiac structure and function measures with changes in both domain-specific and global cognitive scores between V5 and V6 using multivariable linear regression. Models were initially adjusted for demographics and education level, with additional models further adjusting for cardiovascular risk factors and disease at both V5 and V6. The neuropsychological test battery consisted of 10 neuropsychological tests that covered 3 domains of cognitive function: memory, executive functioning, and language. Factor scores were constructed for each cognitive domain, and their average represented a global composite score. Results: Among 2,988 included participants, mean age was 74±5 years, 60% were female, 20% reported Black race, and mean LVEF was 66±6%. Over a mean of 4.9±0.6 years (the V5 to V6 interval), raw scores declined for all neuropsychological tests. In fully adjusted models, worse diastolic function (larger LAVi) and LV remodeling (greater LV mass index) were associated with decline in executive function. Lower LVEF was associated with decline in language function, while worse LV longitudinal strain – a more sensitive measure of systolic dysfunction – was associated with decline in executive function, language function, and global cognition performance (all p<0.05; Table). Conclusion: Subclinical LV remodeling and dysfunction is associated with greater declines in cognitive function over 5 years in late life. Differential associations were observed by cognitive domains, with executive function decline most uniformly associated with impairments in cardiac structure/function.

Excess Mortality Estimation

Estimating the mortality associated with a specific mortality crisis event (for example, a pandemic, natural disaster, or conflict) is clearly an important public health undertaking. In many situations, deaths may be directly or indirectly attributable to the mortality crisis event, and both contributions may be of interest. The totality of the mortality impact on the population (direct and indirect deaths) includes the knock-on effects of the event, such as a breakdown of the health care system, or increased mortality due to shortages of resources. Unfortunately, estimating the deaths directly attributable to the event is frequently problematic. Hence, the excess mortality, defined as the difference between the observed mortality and that which would have occurred in the absence of the crisis event, is an estimation target. If the region of interest contains a functioning vital registration system, so that the mortality is fully observed and reliable, then the only modeling required is to produce the expected deaths counts, but this is a nontrivial exercise. In low- and middle-income countries it is common for there to be incomplete (or nonexistent) mortality data, and one must then use additional data and/or modeling, including predicting mortality using auxiliary variables. We describe and review each of these aspects, give examples of excess mortality studies, and provide a case study on excess mortality across states of the United States during the COVID-19 pandemic.

A Study of Loss Model Parameter Sensitivity in Compressor Unsteady Flow Simulations

Abstract This article presents results from a comprehensive sensitivity analysis focused on loss models used in a recently developed compressor unsteady mean line flow model for a transonic axial-centrifugal compressor. The mean line flow model treats flow through rotors and stators in their respective reference frames (rotating or stationary), and the compressor performance is determined by the kinetic energy addition and various physics-based loss models in relative frames. In this paper, we describe the modeling approach of the compressor flow model, as well as the loss models that are used to obtain a relatively good match against test data. Sensitivity studies of selected loss model parameters are presented to show the effect of individual loss model parameters on the overall compressor characteristics in the entire speed range. The effects of losses on unsteady flow transients are assessed by comparing the transient responses when a step reduction of throttle area is applied. The comparisons show that the change in loss magnitude has weak effects on transient response if the change of loss does not significantly change the system stability.

AMMI Biplot Analysis for Stability of Grain Yield in Foxtail Millet [Setaria italica (L.) P. Beauv.] Genotypes

Background: Foxtail millet cultivation in India’s NEH region holds promise due to its adaptation to diverse environments and high-quality grain. Studying G × E interaction in this region will guide breeding programs to develop foxtail millet varieties adapted to local conditions. The objective of this study was to find out foxtail millet genotypes that produce high yield in diverse environments and to identify ideal mega-environments using additive main effects and multiplicative interaction stability model analysis. Methods: In this study, 30 genotypes were evaluated at the Research Farm of the SAS, Nagaland University, Medziphema, India. The experiment was conducted during July 2022 to May 2023 involving four different environments. Two environments were rainfed and two were irrigated with weekly intervals. The experiment was conducted in randomized complete block design (RCBD) with three replications in all the environments. Result: Genotype-environment interactions significantly influenced grain yield across four environments, while replicates were non-significant. Pooled analysis revealed significant genotypic effects and seasonal impacts. AMMI analysis revealed significant effect on environmental and genotypic influences on grain yield and explained 23.47% and 27.94% variability respectively. The AMMI model effectively decomposed the intricate genotype-environment interaction into three principal components (PC1, PC2and PC3), explaining 54.5%, 28.7%and 16.8% of the interaction variance, respectively. AMMI model exposed genotypes viz G8, G9, G21and G22 as best performer and stable. AMMI stability value revealed G10 with highest stability (ASV = 0.34) followed by G15, G7, G29, G6and G13 in decreasing order indicating their consistent performance in grain yield across different environments.

Abstract 4124289: Changes in high-sensitivity cardiac troponin I and associated cardiovascular risk: Analyses From the FOURIER Trial

Background: Circulating high-sensitivity cardiac troponin I (hs-cTnI) is associated with the risk of future cardiovascular (CV) events in stable patients (pts). Data are scarce regarding changes of hs-cTnI in a stable setting. Aims: To study baseline and changes of hs-cTnI in pts with atherosclerotic CV disease (ASCVD), and the association with risk of major CV events. Methods: We measured hs-cTnI (Abbott ARCHITECT) at baseline (BL) and 24 weeks (wks) in 20,718 pts enrolled in a nested biomarker study of the FOURIER trial, which tested the PCSK9i evolocumab vs. placebo in pts with ASCVD on statin and LDL > 70 or non-HDL > 100 mg/dL. The primary endpoint was an adjudicated composite of CV death, MI, stroke, hosp. for unstable angina, or coronary revascularization. The HR (95% CI) across percent-change of hs-cTnI was investigated in pts with quantifiable hs-cTnI at BL and 24 wks (lower limit of quantification (LLOQ) 3.6ng/L) using restricted-cubic splines and Cox-PH models, adjusted for sex, age, LDL at BL, prior MI, randomized treatment, eGFR, DM, HTN, prior HF, and BMI. A Generalized Additive Model was used to predict event rates as a function of hs-cTnI BL and absolute change, flexibly evaluated with a non-linear interaction. All models were based on 3-year follow-up using landmark analysis from 24 wks. Results: Median age was 63 yrs (25 th , 75 th percentiles: 56, 69), 75.5% were male, 86.1% had CAD, 13.7% PAD, and 19.0% a prior stroke. Of these pts, 11,021 (46.8%) had hs-cTnI > LLOQ at BL and 24 wks. The median hs-cTnI at 24 wks was 6.6ng/L (5 th , 25 th , 75 th , 95 th percentiles are: 3.7, 4.7, 11.9, 51.1 ng/L). The absolute event rate of the primary endpoint across hs-cTnI BL and depending on absolute hs-cTnI change to 24 wks is shown in Fig. A . Higher Hs-cTnI BL was associated with higher event rates (p < 0.001). Additionally, absolute reductions and increases of hs-cTnI from BL to 24 wks resulted in reduced and increased event rates, respectively, across hs-cTnI BL . Additionally, relative decrease and increase of hs-cTnI from BL to 24 wks were associated with reduced and increased relative risk, respectively (p for overall effect < 0.001, Fig. B ). Conclusion: Changes in hs-cTnI are associated with the risk of future CV events. Serial measurements of hs-cTnI may aid in reclassification of CV risk and the identification of pts whose CV risk changes with time.

Abstract 4136025: Establishing normal values for central systolic blood pressure and augmentation index in healthy young people

Background: The process of cardiovascular disease (CVD), a leading cause of death worldwide, commences in childhood. Increasing evidence indicates that early exposure to CVD risk factors in childhood is associated with impaired arterial distensibility and other vascular alterations, suggesting that vascular ageing biomarkers, that capture the deterioration in vascular structure and function, can be used to identify children at risk. However, the identification of early vascular alterations in the young is hampered by the lack of a recognized, vascular biomarker that can be used in clinical practice. The Youth Vascular Consortium, an international collaborative open resource has been established to answer these gaps by analysing different biomarkers, including central systolic blood pressure (cSBP) and augmentation index (AIx). These two non-invasive measures are related to CVD and end-organ damage, however, their assessment in clinical practice is limited by the lack of established normal values. Aims: We aimed to establish cSBP and AIx normal values in a young, healthy, international population. Methods: The Consortium collected data on 36,973 participants from 24 countries. We included 14,476 and 5,047 subjects respectively for the cSBP and AIx populations. Subjects were free of any CVD or cardiovascular risk factors. Data were collected from participants aged from 1 to 40 years. Normal values of cSBP and AIx were calculated as percentiles stratified by age and sex. Percentiles curves were generated using generalised additive models. Results: The cSBP percentile curves increase with the same trend for both males and females until age 13 years. Over this age, males experience greater cSBP than females. This is in contrast to AIx, which decreases with the same trend in both sexes until 15 years of age, after which females experience increased AIx. Conclusion: Normal values of cSBP and AIx in healthy young are now available according to age and sex with a wide geographical representation. Incorporating these values into clinical practice for young could facilitate their utilization as targets for the introduction and monitoring of interventions.

Seasonal distribution of cetaceans in the European Atlantic and Mediterranean waters

As apex predators, cetaceans play an essential ecological role in marine ecosystems. Fluctuations in the abundance of these top predators linked to human activities can have detrimental consequences for the entire ecosystem. Cetaceans face numerous anthropogenic threats that can have both short and long-term effects. To ensure their conservation, it is necessary to identify changes in seasonal distributions at small and large scales. We aimed to model the seasonal distribution of the most abundant cetacean species in the European Atlantic waters and the Mediterranean Sea by assembling datasets collected over 16 years of surveys using a standardised line-transect protocol. Data were homogenised, detection functions fitted and effective strip widths estimated. We extracted environmental variables integrated over the water column, which we transformed using a principal component analysis (PCA). The dimensions of the PCA were then integrated as explanatory variables in a generalised additive model, taking seasonal and spatial effects into account to predict the seasonal cetacean distribution. We were able to highlight changes in the spatial distribution and/or density of cetaceans throughout the year at a large scale, considering environmental extrapolation areas to predict where environmental variables were sampled during the surveys. For minke (Balaenoptera acutorostrata) and fin (B. physalus) whales, densities varied over the seasons but not the distribution, suggesting a seasonal migration outside the survey areas. For common dolphins (Delphinus delphis), bottlenose dolphins (Tursiops truncatus) and harbour porpoises (Phocoena phocoena), densities varied little but distributions did over the seasons. Finally, pilot whales (Globicephala spp), Risso’s (Grampus griseus) and striped (Stenella coeruleoalba) dolphins showed little seasonal variation in their distribution. Using monthly dynamic environmental variables at depth and PCA dimensions in habitat models, we produced maps of the seasonal distribution of cetaceans in the Mediterranean Sea and the European Atlantic waters to help fill gaps in our knowledge of cetacean distribution.

Reconstructing hail days in Switzerland with statistical models (1959–2022)

Abstract. Hail is one of the costliest natural hazards in Switzerland and causes extensive damage to agriculture, cars, and infrastructure each year. In a warming climate, hail frequency and its patterns of occurrence are expected to change, which is why understanding the long-term variability and its drivers is essential. This study presents new multidecadal daily hail time series for northern and southern Switzerland from 1959 to 2022. Daily radar hail proxies and environmental predictor variables from ERA5 reanalysis are used to build an ensemble statistical model for predicting past hail occurrence. Hail days are identified from operational radar-derived probability of hail (POH) data for two study domains, the north and south of the Swiss Alps. We use data from 2002 to 2022 during the convective season from April to September. A day is defined as a hail day when POH surpasses 80 % for a minimum footprint area of the two domains. Separate logistic regression and logistic generalized additive models (GAMs) are built for each domain and combined in an ensemble prediction to reconstruct the final time series. Overall, the models are able to describe the observed time series well. Historical hail reports are used for comparing years with the most and least hail days. For the northern and southern domains, the time series both show a significant positive trend in yearly aggregated hail days from 1959 to 2022. The trend is still positive and significant when considering only the period of 1979–2022. In all models, the trends are driven by moisture and instability predictors. The last 2 decades show a considerable increase in hail days, which is the strongest in May and June. The seasonal cycle has not shifted systematically across decades. This time series allows us to study the local and remote drivers of the interannual variability and seasonality of Swiss hail occurrence.

Synthesis of a hydrological, water chemistry, and contaminants research program in the Peace-Athabasca Delta (Canada) to inform long-term monitoring of shallow lakes

In a multistressor world, evidence-based stewardship of aquatic ecosystems requires long-term monitoring data to understand the timing and magnitude of environmental change and potential causes. At the Peace-Athabasca Delta (PAD; northeastern Alberta, Canada), concern for aquatic ecosystem degradation has triggered renewed and urgent calls by Indigenous, national, and international governance bodies for implementation of a long-term lake monitoring program capable of tracking changes in hydrological conditions and contaminant deposition attributable to major energy projects located upstream, climate change, and other unnatural and natural processes. Challenges imposed by the delta's size, hydrological complexity, inaccessibility of lakes, and other factors, however, have long impeded implementation of a delta-wide lake monitoring program. To address this pressing need, here we review and synthesize results obtained during 7 years (2015–2021) of intensive, multifaceted research at 60 shallow lakes spanning the delta's broad hydroecological gradients to inform an integrated hydrology, water chemistry, and contaminants monitoring program. The research involved systematic, repeated measurements of water isotope composition, water depth variation, water chemistry and turbidity, and metal(loid) concentrations in lake surface sediment and periphytic biofilm. Results reveal marked spatial and temporal variation of hydrological processes and their affects on lake water balance and depth, strong association between hydrological processes and lake water chemistry, and that concentrations of nickel and vanadium (key oil sands indicators) remain within the range of natural variation. Correspondence of generalized additive model trendlines for isotope-derived lake evaporation-to-inflow ratios and water chemistry with climate indices (Pacific Decadal Oscillation, Oceanic Niño Index) demonstrates the sensitivity, and predictability, of lake ecosystem processes in the delta to large-scale climatic patterns. We provide recommendations for field sampling, sample analysis, data display, and integration of information for ongoing monitoring at the PAD. These approaches are readily transferable to other complex landscapes with abundant shallow waterbodies threatened by multiple stressors that may alter hydrological regimes and contaminant delivery.

Abstract 4127664: Influences of Age on Improvement of Health-Related Quality of Life in Patients with Atrial Fibrillation following Initial Treatment

Background: The prevalence of Atrial Fibrillation (AF), the most cardiac common arrhythmia, increases with age. Various treatment strategies are available to improve health-related quality of life (HRQoL) in patients with AF; however, the impact of age on HRQoL treatment benefits is unknown. Aims: To investigate the association of age with HRQoL benefit across different treatment strategies. Methods: Using data from a multicenter registry for outpatients with early recognized AF, HRQoL at enrollment and 1 year later was measured with the Atrial Fibrillation Effect on Quality-of-life quesTionnaire (AFEQT). The association between age and the 1-year changes in AFEQT-overall summary (OS) and subdomain scores with either rate or rhythm control strategies were assessed using generalized additive models (GAM) to address non-linear relationships. To support clinical interpretation, multivariable linear regression models were performed with categories of age ranges. Results: Among 2786 patients (31.7% women, 54.7% rhythm control); 946 were <65 of age, 1019 were ≥65–75, and 821 were ≥75 years old. Rhythm (vs. rate) control was pursued in 76.6%, 58.0%, and 33.6% and mean AFEQT-OS changes were 11.1 (SD 16.6), 8.0 (17.0), and 4.7 (18.2) in those aged <65, 65–74, and ≥75, respectively. The GAM showed improvements in AFEQT-OS attenuated with advancing age with both treatment strategies ( Figure ). Linear regression analyses showed lesser improvements in AFEQT-OS as higher age categories (≥65–75 vs. <65, β -1.12 [95% CI, -2.33 – 0.09]; ≥75 vs. <65, β -3.86 [-5.29 – -2.42]), which were mainly driven by lesser improvement in AFEQT-daily activities scores, without differences in AFEQT scores for symptom or treatment concerns ( Table ). Conclusions: In AF patients, HRQoL benefits after treatment were attenuated by advancing age, primarily driven by less improvement in functional limitations, underscoring the need for further research to identify optimal treatment strategies for older adults.

Abstract 4136967: Congestive Heart Failure Impedes Effective Fluid Resuscitation in Sepsis

Background: Fluid resuscitation is recommended in patients with sepsis. Sepsis, however, may be associated with myocardial dysfunction. Additionally, myocardial dysfunction and insufficient cardiac reserves in patients with congestive heart failure (CHF) may complicate fluid resuscitation in the setting of sepsis. We aimed to determine whether CHF would affect fluid resuscitation in septic patients admitted to intensive care unit. Outcome of patients with and without CHF were compared. Methods: Unmatched and propensity score matched septic patients with or without CHF were examined in a retrospective cohort of critically ill adults from the MIMIC-IV database by multivariable logistic regression. Mortality and length of stay were compared. Generalized additive models were used for assessing association between fluid resuscitation and in-hospital mortality. Results: Of 24,376 critically ill patients with sepsis, 6838 (28.1%) were also diagnosed with CHF. CHF in septic patients was associated with higher in-hospital mortality with an adjusted odds ratios of 1.25 (95% confidence interval (CI)=1.14-1.37; p<0.001) in unmatched analysis. Compared with patients without CHF, those with CHF had higher in-hospital mortality (14.3% vs. 9.8%, p < 0.001) and received less IV fluid in the first 24 hours of ICU stay (median=1936 ml, IQR=808-3654 vs. 3037, IQR=1810-4585 ml, p<0.001). Similar results were obtained in propensity score matched septic patients with or without CHF. We also found that fluid resuscitation had a U-shaped association with in-hospital mortality with a lowest mortality at roughly 60 ml/kg in the first 24 hours of ICU stay in septic patients without CHF. In septic patients with CHF, liberal fluid resuscitation did not reduce mortality, while restrictive fluid resuscitation was associated with an increased mortality rate. Conclusions: CHF was significantly associated with higher in-hospital mortality among septic patients. Adequate fluid resuscitation improved in-hospital mortality in septic patients without but not with CHF.

Forecasting the Worldwide Impact of Stroke for individuals aged 45 and above

Background:We aimed to assess the global impact of stroke in people aged 45 years and older between 1990 and 2030, focusing on morbidity, mortality and disability-adjusted life years (DALYs). Methods:Generalized additive models (GAM) were used to project disease burden from 2020 to 2030. Additionally, the association between sociodemographic index (SDI) and stroke burden was investigated, and regional differences were assessed by Mann U test-Whitney. Results:The overall age-standardized stroke incidence rate (ASIR) among adults aged 45 years and older is projected to increase from 2020 to 2030, with an estimated annual percentage change (EAPC) of 1.29. Conversely, the age-standardized death rate (ASDR) in EAPC is expected to decrease by -1.48, and the age-standardized DALY in EAPC is expected to decrease by -1.66. By 2030, men are expected to have higher ASIR (181.81) and ASDR (87.31) than women (ASIR: 151.85, ASDR: 65.20). Regional differences are large. East Asia is expected to have the highest ASIR in 2030 (265.55). Age estimates show that older age groups, particularly those aged 75 to 79, are at higher risk of stroke. In addition, there is a significant inverse relationship between SDI and stroke severity, with areas with higher SDI tending to have lower morbidity, mortality, and DALYs. Conclusion: From 1990 to 2030, ASIR is expected to upgrade, especially in East Asia and regions with lower SDI. Men will bear a greater burden than women.