Unexplained Variation Research Articles

Relating weather radar data to migrating waterfowl abundance in the Rainwater Basin of Nebraska

AbstractWaterfowl migrations are large‐scale events that involve millions of birds moving over broad geographic extents, which make them difficult to quantify and study. Historically, wildlife managers have relied mostly on field surveys, such as visual counts from the ground or air that sample at small spatial or temporal extents, or both. Combining field surveys with remote sensing data comprehensively collected over large spatial extents at high temporal frequency may improve the study of migrating waterfowl distributions. We tested the strength of the relationship between broad‐scale weather surveillance radar data and fine‐scale field surveys of waterfowl abundance at wetlands within the Rainwater Basin of Nebraska, USA, from 2017–2019. Radar reflectivity of waterfowl at the peak exodus of evening flights was positively correlated with diurnal waterfowl count data, although there was unexplained variation in the relationship. The association was also very similar across various time scales ranging from daily to monthly averages of waterfowl abundance. We suggest that human‐based ground surveys can calibrate and leverage more comprehensive remote sensing data to get a broad understanding of waterfowl distributions during migration. Several confounding factors, such as spatial displacement between radar and survey observation, individual variation in orientation and body size, and identification of avian species sampled by radar, remain on the path to improving radar‐based waterfowl estimates.

Tailored inference for finite populations: conditional validity and transfer across distributions

Summary Parameters of subpopulations can be more relevant than those of superpopulations. For example, a healthcare provider may be interested in the effect of a treatment plan for a specific subset of their patients; policymakers may be concerned with the impact of a policy in a particular state within a given population. In these cases, the focus is on a specific finite population, as opposed to an infinite superpopulation. Such a population can be characterized by fixing some attributes that are intrinsic to them, leaving unexplained variations like measurement error as random. Inference for a population with fixed attributes can then be modelled as inferring parameters of a conditional distribution. Accordingly, it is desirable that confidence intervals are conditionally valid for the realized population, instead of marginalizing over many possible draws of populations. We provide a statistical inference framework for parameters of finite populations with known attributes. Leveraging the attribute information, our estimators and confidence intervals closely target a specific finite population. When the data are from the population of interest, our confidence intervals attain asymptotic conditional validity, given the attributes, and are shorter than those for superpopulation inference. In addition, we develop procedures to infer parameters of new populations with differing covariate distributions; the confidence intervals are also conditionally valid for the new populations under mild conditions. Our methods extend to situations where the fixed information has a weaker structure or is only partially observed. We demonstrate the validity and applicability of our methods using simulated data and a real-word dataset for predicting car prices.

The COVID-19 pandemic as an opportunity for unravelling the causative association between respiratory viruses and pneumococcus-associated disease in young children: a prospective study.

In young children, rates of lower respiratory infections (LRI) and invasive pneumococcal disease (IPD) have been associated with respiratory syncytial virus (RSV), human metapneumovirus (hMPV), influenza (flu), and parainfluenza (PIV) (collectively termed here as pneumonia and pneumococcal disease-associated viruses [PDA-viruses]). However, their contribution to the pathogenesis of these disease endpoints has not yet been elucidated. The COVID-19 pandemic provided a unique opportunity to examine the question. This prospective study comprised all children <5 years, living in southern Israel, during 2016 through 2021. The data were previously collected in multiple ongoing prospective surveillance programs and include: hospital visits for community-acquired alveolar pneumonia (CAAP), non-CAAP LRI; nasopharyngeal pneumococcal carriage (<3 years of age); respiratory virus activity; and nationwide, all-ages COVID-19 episodes and IPD in children <5 years. A hierarchical statistical model was developed to estimate the proportion of the different clinical endpoints attributable to each virus from monthly time series data, stratified by age and ethnicity. A separate model was fit for each endpoint, with covariates that included a linear time trend, 12-month harmonic variables to capture unexplained seasonal variations, and the proportion of tests positive for each virus in that month. During 2016 through 2021, 3,204, 26,695, 257, and 619 episodes of CAAP, non-CAAP LRI, pneumococcal bacteremic pneumonia and non-pneumonia IPD, respectively, were reported. Compared to 2016-2019, broad declines in the disease endpoints were observed shortly after the pandemic surge, coincident with a complete disappearance of all PDA-viruses and continued circulation of rhinovirus (RhV) and adenovirus (AdV). From April 2021, off-season and abrupt surges of all disease endpoints occurred, associated with similar dynamics among the PDA-viruses, which re-emerged sequentially. Using our model fit to the entire 2016-2021 period, 82% (95% CI, 75-88%) of CAAP episodes in 2021 were attributable to the common respiratory viruses, as were 22%-31% of the other disease endpoints. Virus-specific contributions to CAAP were: RSV, 49% (95% CI, 43-55%); hMPV, 13% (10-17%); PIV, 11% (7-15%); flu, 7% (1-13%). RhV and AdV did not contribute. RSV was the main contributor in all endpoints, especially in infants. Pneumococcal carriage prevalence remained largely stable throughout the study. RSV and hMPV play a critical role in the burden of CAAP and pneumococcal disease in children. Interventions targeting these viruses could have a secondary effect on the burden of disease typically attributed to bacteria. There was no funding for this study.

Hospital-level variation in risk-standardized admission rates for emergency care-sensitive conditions among older and younger Veterans.

Research examining emergency department (ED) admission practices within the Department of Veterans Affairs (VA) is limited. This study investigates facility-level variation in risk-standardized admission rates (RSARs) for emergency care-sensitive conditions (ECSCs) among older (≥65 years) and younger (<65 years) Veterans across VA EDs. Veterans presenting to a VA ED for an ECSC between October 1, 2016 and September 30, 2019 were identified and the 10 most common ECSCs established. ECSC-specific RSARs were calculated using hierarchical generalized linear models, adjusting for Veteran and encounter characteristics. The interquartile range ratio (IQR ratio) and coefficient of variation were measures of dispersion for each condition and were stratified by age group. Associations with facility characteristics were also examined in condition-specific multivariable models. The overall cohort included 651,336 ED visits across 110 VA facilities for the 10 most common ECSCs-chronic obstructive pulmonary disease (COPD), heart failure, pneumonia, volume depletion, tachyarrhythmias, acute diabetes mellitus, gastrointestinal (GI) bleeding, asthma, sepsis, and myocardial infarction (MI). After adjusting for case mix, the ECSCs with the greatest variation (IQR ratio, coefficient of variation) in RSARs were asthma (1.43, 32.12), COPD (1.39, 24.64), volume depletion (1.38, 23.67), and acute diabetes mellitus (1.28, 17.52), whereas those with the least variation were MI (1.01, 0.87) and sepsis (1.02, 2.41). Condition-specific RSARs were not qualitatively different between age subgroups. Association with facility characteristics varied across ECSCs and within condition-specific age subgroups. We identified unexplained facility-level variation in RSARs for Veterans presenting with the 10 most common ECSCs to VA EDs. The magnitude of variation did not appear to be qualitatively different between older and younger Veteran subgroups. Variation in RSARs for ECSCs may be an important target for systems-based levers to improve value in VA emergency care.

Defining and Measuring Quality in Colorectal Surgery.

Over the past 20 years, there has been a growing focus on quality and safety in both medicine and surgery. Many argue that this was ignited in 1999 following the publication of To Err is Human: Building a Safer Health System, which highlighted that up to 100,000 deaths per year could be attributed to preventable errors in health care delivery.[1] Coupling this with the unexplained variation in care across regions[2] and publicly reported patient outcomes, researchers have prioritized identifying actionable opportunities for improvement. To make improvements, however, we must first be able to define quality.

Determinants of Cost for Outpatient Hysterectomy for Benign Indications in a Nationwide Sample.

To identify surgeon-level variation in cost to produce an outpatient hysterectomy for benign indications in the United States. A sample of patients undergoing outpatient hysterectomy in October 2015 to December 2021, excluding those with a diagnosis of gynecologic malignancy, was obtained from the Vizient Clinical Database. The primary outcome was total direct hysterectomy cost, which is a modeled cost to produce care. Patient, hospital, and surgeon covariates were analyzed with mixed-effects regression, which included surgeon-level random effects to capture unobserved differences influencing cost variation. The final sample included 264,717 cases performed by 5,153 surgeons. The median total direct cost of hysterectomy was $4,705 (interquartile range $3,522-6,234). Cost was highest for robotic hysterectomy ($5,412) and lowest for vaginal hysterectomy ($4,147). After all variables were included in the regression model, approach was the strongest of the observed predictors, but 60.5% of the variance in costs was attributable to unexplained surgeon-level differences, implying a difference in costs between the 10th and 90th percentiles of surgeons of $4,063. The largest observed determinant of cost to produce an outpatient hysterectomy for benign indications in the United States is approach, but differences in cost are attributable primarily to unexplained differences among surgeons. Standardization of surgical approach and technique and surgeon awareness of surgical supply costs could address these unexplained cost variations.

Dissolved organic matter transformations in a freshwater rivermouth

River-to-lake transitional areas are biogeochemically active ecosystems that can alter the amount and composition of dissolved organic matter (DOM) as it moves through the aquatic continuum. However, few studies have directly measured carbon processing and assessed the carbon budget of freshwater rivermouths. We compiled measurements of dissolved organic carbon (DOC) and DOM in several water column (light and dark) and sediment incubation experiments conducted in the mouth of the Fox river (Fox rivermouth) upstream from Green Bay, Lake Michigan. Despite variation in the direction of DOC fluxes from sediments, we found that the Fox rivermouth was a net sink of DOC where water column DOC mineralization outweighed the release of DOC from sediments at the rivermouth scale. Although we found DOM composition also changed during our experiments, alterations in DOM optical properties were largely independent of the direction of sediment DOC fluxes. We found a consistent decrease in humic-like and fulvic-like terrestrial DOM and a consistent increase in the overall microbial composition of rivermouth DOM during our incubations. Moreover, greater ambient total dissolved phosphorus concentrations were positively associated with the consumption of terrestrial humic-like, microbial protein-like, and more recently derived DOM but had no effect on bulk DOC in the water column. Unexplained variation indicates that other environmental controls and water column processes affect the processing of DOM in this rivermouth. Nonetheless, the Fox rivermouth appears capable of substantial DOM transformation with implications for the composition of DOM entering Lake Michigan.

Differential attainment in specialty training recruitment in the UK: an observational analysis of the impact of psychometric testing assessment in Public Health postgraduate selection

ObjectivesTo determine how current psychometric testing approaches used in selection of postgraduate training in UK Public Health are associated with socioeconomic and sociocultural background of applicants (including ethnicity).DesignObservational study using...

Abstract P471: Predictors of Referral to Community-Based Rehabilitation Following Stroke

Background: While several studies have examined care transitions following stroke, few have assessed use of rehabilitation. We explored factors predictive of referral to community-based rehabilitation following stroke. Setting: 40 NC acute care hospitals that participated in the COMprehensive Post-Acute Stroke Services study from 2016-2019. Participants: Adults discharged home following stroke or TIA (N=11,195) Methods: Guided by an a priori conceptual framework, 41 predictors of referral to community-based rehabilitation were grouped into 3 patient-level domains: demographics, stroke severity, and medical history (e.g., prior stroke); 2 hospital-level domains: structural characteristics (e.g., bed size) and stroke-specific characteristics (e.g., stroke center status); and 1 community-level domain (county-level therapist supply). We estimated predictors of referral using a logistic mixed model with a hospital-specific random effect. We used a hierarchical backward selection approach, first performing domain-specific model selection, then entering retained variables into a complete model. Results: The cohort was 49% female, 72% white, with a mean age of 66.8 (SD=14.0) years and overall low stroke severity [mean [SD] NIHSS 2.4 [3.8]). Thirty-six percent of patients were referred to rehabilitation. Referral varied across hospitals, ranging from 3-78%, with a median of 35%. In the final model, older age, female sex, non-white race, higher stroke severity, longer length of stay, previous stroke, current smoking, and heart failure were associated with higher odds of referral as was hospital-employed vs. external-contracted OT services (Table). Discussion: Approximately one-third of stroke survivors discharged home were referred to community-based rehabilitation. Women and non-white patients had higher odds of referral. Hospital and community factors were largely not independent predictors of referral. Unmeasured process measures may play a role in unexplained hospital variation.

Revisiting fall armyworm population movement in the United States and Canada.

Biophysical approaches validated against haplotype and trap catch patterns have modeled the migratory trajectory of fall armyworms at a semi-continental scale, from their natal origins in Texas or Florida through much of the United States east of the Rocky Mountains. However, unexplained variation in the validation analysis was present, and misalignments between the simulated movement patterns of fall armyworm populations and the haplotype ratios at several locations, especially in the northeastern US and Canada, have been reported. Using an expanded dataset extending into Canada, we assess the consistency of haplotype patterns that relate overwintered origins of fall armyworm populations to hypothesized dispersal trajectories in North America and compare the geographic distribution of these patterns with previous model projections. We confirm the general accuracy of previous modeling efforts, except for late in the season where our data suggests a higher proportion of Texas populations invading the northeast, extending into eastern Canada. We delineate geographic limits to the range of both overwintering populations and show that substantial intermixing of the Texas and Florida migrants routinely occurs north of South Carolina. We discuss annual variation to these migratory trajectories and test the hypothesis that the Appalachian Mountains influence geographic patterns of haplotypes. We discuss how these results may limit gene flow between the Texas and Florida natal populations and limit the hereditary consequences of interbreeding between these populations.

The Relationship between Socioeconomic Factors at Different Administrative Levels and Forest Fire Occurrence Density Using a Multilevel Model

Wildfires are among the main factors that disturb terrestrial ecosystems, landscapes, and the environment. Understanding the differences that the socioeconomic factors of different administrative levels have on fire occurrence remains critical to inform the driving function of ignition sources. In this study, we collected socioeconomic and land use data for 21 cities and 81 counties in the study area from 2001 to 2019 and applied a multilevel model to explore the relationship between wildfire occurrence density and the driving factors. We estimated the fixed and random effect of the factors at different levels and built three hierarchical linear models (HLMs) to quantify the impacts of socioeconomic drivers on wildfires. The results showed that the variance among cities contributed to 14.01% of the unexplained variation of random effects at the county level. At the county level, the densities of middle school student populations, gross domestic product (GDP), and impervious surface areas were significantly positively correlated with fire occurrence density. At the city level, GDP and its interaction with county-level factors were significantly negatively correlated with fire occurrence density. This study provides a new method and findings for the research of wildfire occurrence and risk.

Phenotypic Analysis of Fourier-Transform Infrared Milk Spectra in Dairy Goats.

The infrared spectrum of bovine milk is used to predict many interesting traits, whereas there have been few studies on goat milk in this regard. The objective of this study was to characterize the major sources of variation in the absorbance of the infrared spectrum in caprine milk samples. A total of 657 goats belonging to 6 breeds and reared on 20 farms under traditional and modern dairy systems were milk-sampled once. Fourier-transform infrared (FTIR) spectra were taken (2 replicates per sample, 1314 spectra), and each spectrum contained absorbance values at 1060 different wavenumbers (5000 to 930 × cm-1), which were treated as a response variable and analyzed one at a time (i.e., 1060 runs). A mixed model, including the random effects of sample/goat, breed, flock, parity, stage of lactation, and the residual, was used. The pattern and variability of the FTIR spectrum of caprine milk was similar to those of bovine milk. The major sources of variation in the entire spectrum were as follows: sample/goat (33% of the total variance); flock (21%); breed (15%); lactation stage (11%); parity (9%); and the residual unexplained variation (10%). The entire spectrum was segmented into five relatively homogeneous regions. Two of them exhibited very large variations, especially the residual variation. These regions are known to be affected by the absorbance of water, although they also exhibited wide variations in the other sources of variation. The average repeatability of these two regions were 45% and 75%, whereas for the other three regions it was about 99%. The FTIR spectrum of caprine milk could probably be used to predict several traits and to authenticate the origin of goat milk.

Association of Unmet Social Needs With Level of Capability in People With Persistent Knee Pain.

Musculoskeletal providers are increasingly recognizing the importance of social factors and their association with health outcomes as they aim to develop more comprehensive models of care delivery. Such factors may account for some of the unexplained variation between pathophysiology and level of pain intensity and incapability experienced by people with common conditions, such as persistent nontraumatic knee pain secondary to osteoarthritis (OA). Although the association of one's social position (for example, income, employment, or education) with levels of pain and capability are often assessed in OA research, the relationship between aspects of social context (or unmet social needs) and such symptomatic and functional outcomes in persistent knee pain are less clear. (1) Are unmet social needs associated with the level of capability in patients experiencing persistently painful nontraumatic knee conditions, accounting for sociodemographic factors? (2) Do unmet health-related social needs correlate with self-reported quality of life? We performed a prospective, cross-sectional study between January 2021 and August 2021 at a university academic medical center providing comprehensive care for patients with persistent lower extremity joint pain secondary to nontraumatic conditions such as age-related knee OA. A final 125 patients were included (mean age 62 ± 10 years, 65% [81 of 125] women, 47% [59 of 125] identifying as White race, 36% [45 of 125] as Hispanic or Latino, and 48% [60 of 125] with safety-net insurance or Medicaid). We measured patient-reported outcomes of knee capability (Knee injury and Osteoarthritis Outcome Score for Joint Replacement), quality of life (Patient-Reported Outcome Measure Information System [PROMIS] Global Physical Health and PROMIS Global Mental Health), and unmet social needs (Accountable Health Communities Health-Related Social Needs Survey, accounting for insufficiencies related to housing, food, transportation, utilities, and interpersonal violence), as well as demographic factors. After controlling for demographic factors such as insurance status, education attained, and household income, we found that reduced knee-specific capability was moderately associated with experiencing unmet social needs (including food insecurity, housing instability, transportation needs, utility needs, or interpersonal safety) (standardized beta regression coefficient [β] = -4.8 [95% confidence interval -7.9 to -1.7]; p = 0.002 and substantially associated with unemployment (β = -13 [95% CI -23 to -3.8]; p = 0.006); better knee-specific capability was substantially associated with having Medicare insurance (β = 12 [95% CI 0.78 to 23]; p = 0.04). After accounting for factors such as insurance status, education attained, and household income, we found that older age was associated with better general mental health (β = 0.20 [95% CI 0.0031 to 0.39]; p = 0.047) and with better physical health (β = 0.004 [95% CI 0.0001 to 0.008]; p = 0.04), but effect sizes were small to negligible, respectively. There is an association of unmet social needs with level of capability and unemployment in patients with persistent nontraumatic knee pain. This finding signals a need for comprehensive care delivery for patients with persistent knee pain that screens for and responds to potentially modifiable social risk factors, including those based on one's social circumstances and context, to achieve better outcomes. Level II, prognostic study.

Hierarchical causal variance decomposition for institution and provider comparisons in healthcare

Disease-specific quality indicators are used to compare institutions and health care providers in terms of processes or outcomes relevant to treatment of a particular condition. In the context of surgical cancer treatments, the performance variations can be due to hospital and/or surgeon level differences, creating a hierarchical clustering. We consider how the observed variation in care received at patient level can be decomposed into that causally explained by the hospital performance, surgeon performance within hospital, patient case-mix, and unexplained (residual) variation. For this purpose, we derive a four-way variance decomposition, with particular attention to the causal interpretation of the components. For estimation, we use inputs from a mixed-effect model with nested random hospital/surgeon-specific effects, and a multinomial logistic model for the hospital/surgeon-specific patient populations. We investigate the performance of our methods in a simulation study and demonstrate them through analysis of administrative data on kidney cancer care in Ontario.

Stochastic phenotypes in RAS-dependent developmental diseases

Germline mutations upregulating RAS signaling are associated with multiple developmental disorders. A hallmark of these conditions is that the same mutation may present vastly different phenotypes in different individuals, even in monozygotic twins. Here, we demonstrate how the origins of such largely unexplained phenotypic variations may be dissected using highly controlled studies in Drosophila that have been gene edited to carry activating variants of MEK, a core enzyme in the RAS pathway. This allowed us to measure the small but consistent increase in signaling output of such alleles invivo. The fraction of mutation carriers reaching adulthood was strongly reduced, but most surviving animals had normal RAS-dependent structures. We rationalize these results using a stochastic signaling model and support it by quantifying cell fate specification errors in bilaterally symmetric larval trachea, a RAS-dependent structure that allows us to isolate the effects of mutations from potential contributions of genetic modifiers and environmental differences. We propose that the small increase in signaling output shifts the distribution of phenotypes into a regime, where stochastic variation causes defects in some individuals, but not in others. Our findings shed light on phenotypic heterogeneity of developmental disorders caused by deregulated RAS signaling and offer a framework for investigating causal effects of other pathogenic alleles and mild mutations in general.

Learning from Our Study Organisms about Sexual Selection: Lessons from the Ocellated Wrasse.

AbstractSexual selection is a powerful force shaping not only the details but also the breadth of what we see in nature. Yet so much unexplained variation remains. Organisms often solve the "problem" of how to pass on their genes in ways that do not fit our current expectations. I argue here that integrating empirical surprises will push our understanding of sexual selection forward. Such "nonmodel" organisms (i.e., species that do not do what we think they should do) challenge us to think deeply, integrate puzzling results, question our assumptions, and consider the new (and arguably better) questions these unexpected patterns pose. In this article, I share how puzzling observations from my long-term research on the ocellated wrasse (Symphodus ocellatus) have shaped my understanding of sexual selection and suggested new questions about the interplay among sexual selection, plasticity, and social interactions. My general premise, however, is not that others should study these questions. Instead, I argue for a change in the culture of our field-to consider unexpected results a welcome opportunity to generate new questions and learn new things about sexual selection. Those of us in positions of power (e.g., as editors, reviewers, and authors) need to lead the way.

Impacts of the match-mismatch hypothesis across three trophic levels—a case study in the North Sea

AbstractSustainable fishery practices require accurate predictions of fish recruitment—the abundance of a new year class entering a fishery. A key driver of recruitment is the impact predator-prey dynamics experienced during early life stages has on their survival at later stages, as in the Match-Mismatch Hypothesis (MMH). MMH states that predator survival depends on the match (or mismatch) between the timing of predator feeding and that of prey availability. This study aims to understand how predator-prey spatio-temporal overlap explains the variation in a pelagic fish population. We explore the predator-prey overlap between each pair of three trophic levels in the North Sea (NS) from 1982–2017: herring (Clupea harengus) larvae, zooplankton (Temora longicornis, Oithona sp.,Pseudocalanus spp., and Acartia spp.), and a phytoplankton index. We found that MMH explained 23% of recruitment (1-year-old) of NS autumn-spawning (NSAS) herring, performed similarly (21–26%) when using different trophic levels, and that there was a spatial pattern in both the overlap and the negative relationship between the overlap and recruitment, similar to the variation of habitat use of NS herring. Our results characterize how the MMH, including spatial variability, plays in controlling herring recruitment, while also considering unexplained variation for future study.

Digital Ethnic Enclaves: Mate Preferences and Platform Choices Among Chinese Immigrant Online Daters in Vancouver

In light of the growing racialized immigrant population in Canada and advances in dating technologies, this study examines Chinese immigrants' partner preferences and mate selection processes through the lens of online dating. We draw on in-depth interviews with 31 Chinese immigrants who have used online dating services in Metro Vancouver to search for different-sex partners. Chinese immigrant online daters show strong preferences for dating Chinese. They emphasize permanent residency status and similarity in age at arrival when evaluating potential partners. Given their preferences, Chinese immigrants strategically choose the dating platforms they primarily use. Men exhibit higher selectivity in their preferences and choices of platforms. Notably, platforms catering to Chinese users create "digital ethnic enclaves" where Chinese immigrant daters congregate. The findings illuminate the intersection of race, gender, immigrant status, and age at arrival in shaping divergent experiences of mate selection and immigrant assimilation in the digital era.

Predictors of Intraoperative Echocardiography: Analysis of The Society of Thoracic Surgeons Database

BackgroundIntraoperative transesophageal echocardiography (TEE) is associated with improved outcomes after cardiac surgery, but unexplained practice pattern variation exists. This study aimed to identify and quantify the predictors of intraoperative TEE use among patients undergoing isolated coronary artery bypass graft surgery (CABG) or cardiac valve surgery. MethodsThis observational cohort study used The Society of Thoracic Surgeon (STS) Adult Cardiac Surgery Database data to identify and quantify the predictors of intraoperative TEE use among adult patients aged 18 years or more undergoing either isolated CABG or open cardiac valve repair or replacement surgery between January 1, 2011, and December 31, 2019. Generalized linear mixed models were used to measure the relationship between intraoperative TEE and patient characteristics, surgical volume, and geographic location, while accounting for clustering within hospitals (primary analysis) or surgeons (secondary analysis). ResultsOf 1,973,655 patients, 1,365,708 underwent isolated CABG and 607,947 underwent cardiac valve surgery. Overall, intraoperative TEE was used in 62% of surgeries. The primary hospital-level generalized linear mixed models analysis demonstrated that the strongest predictor of intraoperative TEE use was the hospital where the surgery occurred—with a median odds ratio for TEE of 10.13 in isolated CABG and 5.30 in cardiac valve surgery. The secondary surgeon-level generalized linear mixed models analysis demonstrated similar findings. ConclusionsIntraoperative TEE use (vs lack of use) during surgery was more strongly associated with hospital and surgeon practice patterns than with any patient-level factor, surgical volume, or geographic location.

Integrating pH into the metabolic theory of ecology to predict bacterial diversity in soil.

Microorganisms play essential roles in soil ecosystem functioning and maintenance, but methods are currently lacking for quantitative assessments of the mechanisms underlying microbial diversity patterns observed across disparate systems and scales. Here we established a quantitative model to incorporate pH into metabolic theory to capture and explain some of the unexplained variation in the relationship between temperature and soil bacterial diversity. We then tested and validated our newly developed models across multiple scales of ecological organization. At the species level, we modeled the diversification rate of the model bacterium Pseudomonas fluorescens evolving under laboratory media gradients varying in temperature and pH. At the community level, we modeled patterns of bacterial communities in paddy soils across a continental scale, which included natural gradients of pH and temperature. Last, we further extended our model at a global scale by integrating a meta-analysis comprising 870 soils collected worldwide from a wide range of ecosystems. Our results were robust in consistently predicting the distributional patterns of bacterial diversity across soil temperature and pH gradients-with model variation explaining from 7 to 66% of the variation in bacterial diversity, depending on the scale and system complexity. Together, our study represents a nexus point for the integration of soil bacterial diversity and quantitative models with the potential to be used at distinct spatiotemporal scales. By mechanistically representing pH into metabolic theory, our study enhances our capacity to explain and predict the patterns of bacterial diversity and functioning under current or future climate change scenarios.