Post-acute and Chronic Kidney Function Outcomes of COVID-19 in Children and Adolescents: An EHR Cohort Study from the RECOVER Initiative.

We investigated the risks of post-acute and chronic adverse kidney outcomes of SARS-CoV-2 infection in the pediatric population via a retrospective cohort study using data from the RECOVER program. We included 1,864,637 children and adolescents under 21 from 19 children's hospitals and health institutions in the US with at least six months of follow-up time between March 2020 and May 2023. We divided the patients into three strata: patients with pre-existing chronic kidney disease (CKD), patients with acute kidney injury (AKI) during the acute phase (within 28 days) of SARS-CoV-2 infection, and patients without pre-existing CKD or AKI. We defined a set of adverse kidney outcomes for each stratum and examined the outcomes within the post-acute and chronic phases after SARS-CoV-2 infection. In each stratum, compared with the non-infected group, patients with COVID-19 had a higher risk of adverse kidney outcomes. For patients without pre-existing CKD, there were increased risks of CKD stage 2+ (HR 1.20; 95% CI: 1.13-1.28) and CKD stage 3+ (HR 1.35; 95% CI: 1.15-1.59) during the post-acute phase (28 days to 365 days) after SARS-CoV-2 infection. Within the post-acute phase of SARS-CoV-2 infection, children and adolescents with pre-existing CKD and those who experienced AKI were at increased risk of progression to a composite outcome defined by at least 50% decline in estimated glomerular filtration rate (eGFR), eGFR <15 mL/min/1.73m2, End Stage Kidney Disease diagnosis, dialysis, or transplant.

Metatranscriptomic response of deep ocean microbial populations to infusions of oil and/or synthetic chemical dispersant.

Oil spills are a frequent perturbation to the marine environment that has rapid and significant impacts on the local microbiome. Previous studies have shown that exposure to synthetic dispersant alone did not enhance heterotrophic microbial activity or oxidation rates of specific hydrocarbon components but increased the abundance of some taxa (e.g., Colwellia). In contrast, exposure to oil, but not dispersants, increased the abundance of other taxa (e.g., Marinobacter) and stimulated hydrocarbon oxidation rates. Here, we advance these findings by interpreting metatranscriptomic data from this experiment to explore how and why specific components of the microbial community responded to distinct organic carbon exposure regimes. Dispersant alone was selected for a unique community and for dominant organisms that reflected treatment- and time-dependent responses. Dispersant amendment also led to diverging functional profiles among the different treatments. Similarly, oil alone was selected for a community that was distinct from treatments amended with dispersants. The presence of oil and dispersants with added nutrients led to substantial differences in microbial responses, likely suggesting increased fitness driven by the presence of additional inorganic nutrients. The oil-only additions led to a marked increase in the expression of phages, prophages, transposable elements, and plasmids (PPTEPs), suggesting that aspects of microbial community response to oil are driven by the "mobilome," potentially through viral-associated regulation of metabolic pathways in ciliates and flagellates that would otherwise throttle the microbial community through grazing.IMPORTANCEMicrocosm experiments simulated the April 2010 Deepwater Horizon oil spill by applying oil and synthetic dispersants (Corexit EC9500A and EC9527A) to deep ocean water samples. The exposure regime revealed severe negative alterations in the treatments' heterotrophic microbial activity and hydrocarbon oxidation rates. We expanded these findings by exploring metatranscriptomic signatures of the microbial communities during the chemical amendments in the microcosm experiments. Here we report how dominant organisms were uniquely associated with treatment- and time-dependent trajectories during the exposure regimes; nutrient availability was a significant factor in driving changes in metatranscriptomic responses. Remarkable signals associated with PPTEPs showed the potential role of mobilome and viral-associated survival responses. These insights underscore the time-dependent environmental perturbations of fragile marine environments under oil and anthropogenic stress.

Electronic Health Record-Based Nudge Intervention and Axillary Surgery in Older Women With Breast Cancer: A Nonrandomized Controlled Trial.

Importance: Choosing Wisely recommendations advocate against routine use of axillary staging in older women with early-stage, clinically node-negative (cN0), hormone receptor-positive (HR+), and HER2-negative breast cancer. However, rates of sentinel lymph node biopsy (SLNB) in this population remain persistently high. Objective: To evaluate whether an electronic health record (EHR)-based nudge intervention targeting surgeons in their first outpatient visit with patients meeting Choosing Wisely criteria decreases rates of SLNB. Design, Setting, and Participants: This nonrandomized controlled trial was a hybrid type 1 effectiveness-implementation study with subsequent postintervention semistructured interviews and lasted from October 2021 to October 2023. Data came from EHRs at 8 outpatient clinics within an integrated health care system; participants included 7 breast surgical oncologists. Data were collected for female patients meeting Choosing Wisely criteria for omission of SLNB (aged ≥70 years with cT1 and cT2, cN0, HR+/HER2- breast cancer). The study included a 12-month preintervention control period; baseline surveys assessing perceived acceptability, appropriateness, and feasibility of the designed intervention; and a 12-month intervention period. Intervention: A column nudge was embedded into the surgeon's schedule in the EHR identifying patients meeting Choosing Wisely criteria for potential SLNB omission. Main Outcomes and Measures: The primary outcome was rate of SLNB following nudge deployment into the EHR. Results: Similar baseline demographic and tumor characteristics were observed before (control period, n = 194) and after (intervention period, n = 193) nudge deployment. Patients in both the control and intervention period had a median (IQR) age of 75 (72-79) years. Compared with the control period, unadjusted rates of SLNB decreased by 23.1 percentage points (46.9% SLNB rate prenudge to 23.8% after; 95% CI, -32.9 to -13.8) in the intervention period. An interrupted time series model showed a reduction in the rate of SLNB following nudge deployment (adjusted odds ratio, 0.26; 95% CI, 0.07 to 0.90; P = .03). The participating surgeons scored the intervention highly on acceptability, appropriateness, and feasibility. Dominant themes from semistructured interviews indicated that the intervention helped remind the surgeons of potential Choosing Wisely applicability without the need for additional clicks or actions on the day of the patient visit, which facilitated use. Conclusions and Relevance: This study showed that a nudge intervention in the EHR significantly decreased low-value axillary surgery in older women with early-stage, cN0, HR+/HER2- breast cancer. This user-friendly and easily implementable EHR-based intervention could be a beneficial approach for decreasing low-value care in other practice settings or patient populations. Trial Registration: ClinicalTrials.gov Identifier: NCT06006910.

Phylogenetic inference of inter-population transmission rates for infectious diseases.

Estimating transmission rates is a challenging yet essential aspect of comprehending and controlling the spread of infectious diseases. Various methods exist for estimating transmission rates, each with distinct assumptions, data needs, and constraints. This study introduces a novel phylogenetic approach called transRate, which integrates genetic information with traditional epidemiological approaches to estimate inter-population transmission rates. The phylogenetic method is statistically consistent as the sample size (i.e. the number of pathogen genomes) approaches infinity under the multi-population susceptible-infected-recovered model. Simulation analyses indicate that transRate can accurately estimate the transmission rate with a sample size of 200 ~ 400 pathogen genomes. Using transRate, we analyzed 40,028 high-quality sequences of SARS-CoV-2 in human hosts during the early pandemic. Our analysis uncovered significant transmission between populations even before widespread travel restrictions were implemented. The development of transRate provides valuable insights for scientists and public health officials to enhance their understanding of the pandemic's progression and aiding in preparedness for future viral outbreaks. As public databases for genomic sequences continue to expand, transRate is increasingly vital for tracking and mitigating the spread of infectious diseases.

The clock in growing hyphae and their synchronization in Neurospora crassa.

Utilizing a microfluidic chip with serpentine channels, we inoculated the chip with an agar plug with Neurospora crassa mycelium and successfully captured individual hyphae in channels. For the first time, we report the presence of an autonomous clock in hyphae. Fluorescence of a mCherry reporter gene driven by a clock-controlled gene-2 promoter (ccg-2p) was measured simultaneously along hyphae every half an hour for at least 6 days. We entrained single hyphae to light over a wide range of day lengths, including 6,12, 24, and 36 h days. Hyphae tracked in individual serpentine channels were highly synchronized (K = 0.60-0.78). Furthermore, hyphae also displayed temperature compensation properties, where the oscillation period was stable over a physiological range of temperatures from 24 °C to 30 °C (Q10 = 1.00-1.10). A Clock Tube Model developed could mimic hyphal growth observed in the serpentine chip and provides a mechanism for the stable banding patterns seen in race tubes at the macroscopic scale and synchronization through molecules riding the growth wave in the device.

Pediatric Gastrointestinal Outcomes During the Post-Acute Phase of COVID-19: Findings from RECOVER Initiative from 29 Hospitals in the US.

Importance: The profile of gastrointestinal (GI) outcomes that may affect children in post-acute and chronic phases of COVID-19 remains unclear. Objective: To investigate the risks of GI symptoms and disorders during the post-acute phase (28 days to 179 days after SARS-CoV-2 infection) and the chronic phase (180 days to 729 days after SARS-CoV-2 infection) in the pediatric population. Design: We used a retrospective cohort design from March 2020 to Sept 2023. Setting: twenty-nine healthcare institutions. Participants: A total of 413,455 patients aged not above 18 with SARS-CoV-2 infection and 1,163,478 patients without SARS-CoV-2 infection. Exposures: Documented SARS-CoV-2 infection, including positive polymerase chain reaction (PCR), serology, or antigen tests for SARS-CoV-2, or diagnoses of COVID-19 and COVID-related conditions. Main Outcomes and Measures: Prespecified GI symptoms and disorders during two intervals: post-acute phase and chronic phase following the documented SARS-CoV-2 infection. The adjusted risk ratio (aRR) was determined using a stratified Poisson regression model, with strata computed based on the propensity score. Results: Our cohort comprised 1,576,933 patients, with females representing 48.0% of the sample. The analysis revealed that children with SARS-CoV-2 infection had an increased risk of developing at least one GI symptom or disorder in both the post-acute (8.64% vs. 6.85%; aRR 1.25, 95% CI 1.24-1.27) and chronic phases (12.60% vs. 9.47%; aRR 1.28, 95% CI 1.26-1.30) compared to uninfected peers. Specifically, the risk of abdominal pain was higher in COVID-19 positive patients during the post-acute phase (2.54% vs. 2.06%; aRR 1.14, 95% CI 1.11-1.17) and chronic phase (4.57% vs. 3.40%; aRR 1.24, 95% CI 1.22-1.27). Conclusions and Relevance: In the post-acute phase or chronic phase of COVID-19, the risk of GI symptoms and disorders was increased for COVID-positive patients in the pediatric population.

Computer vision models enable mixed linear modeling to predict arbuscular mycorrhizal fungal colonization using fungal morphology.

The presence of Arbuscular Mycorrhizal Fungi (AMF) in vascular land plant roots is one of the most ancient of symbioses supporting nitrogen and phosphorus exchange for photosynthetically derived carbon. Here we provide a multi-scale modeling approach to predict AMF colonization of a worldwide crop from a Recombinant Inbred Line (RIL) population derived from Sorghum bicolor and S. propinquum. The high-throughput phenotyping methods of fungal structures here rely on a Mask Region-based Convolutional Neural Network (Mask R-CNN) in computer vision for pixel-wise fungal structure segmentations and mixed linear models to explore the relations of AMF colonization, root niche, and fungal structure allocation. Models proposed capture over 95% of the variation in AMF colonization as a function of root niche and relative abundance of fungal structures in each plant. Arbuscule allocation is a significant predictor of AMF colonization among sibling plants. Arbuscules and extraradical hyphae implicated in nutrient exchange predict highest AMF colonization in the top root section. Our work demonstrates that deep learning can be used by the community for the high-throughput phenotyping of AMF in plant roots. Mixed linear modeling provides a framework for testing hypotheses about AMF colonization phenotypes as a function of root niche and fungal structure allocations.

Long COVID incidence in adults and children between 2020 and 2023: a real-world data study from the RECOVER Initiative.

Estimates of post-acute sequelae of SARS-CoV-2 infection (PASC) incidence, also known as Long COVID, have varied across studies and changed over time. We estimated PASC incidence among adult and pediatric populations in three nationwide research networks of electronic health records (EHR) participating in the RECOVER Initiative using different classification algorithms (computable phenotypes). Overall, 7% of children and 8.5%-26.4% of adults developed PASC, depending on computable phenotype used. Excess incidence among SARS-CoV-2 patients was 4% in children and ranged from 4-7% among adults, representing a lower-bound incidence estimation based on two control groups - contemporary COVID-19 negative and historical patients (2019). Temporal patterns were consistent across networks, with peaks associated with introduction of new viral variants. Our findings indicate that preventing and mitigating Long COVID remains a public health priority. Examining temporal patterns and risk factors of PASC incidence informs our understanding of etiology and can improve prevention and management.

Species-specific responses of marine bacteria to environmental perturbation.

Environmental perturbations shape the structure and function of microbial communities. Oil spills are a major perturbation and resolving spills often requires active measures like dispersant application that can exacerbate the initial disturbance. Species-specific responses of microorganisms to oil and dispersant exposure during such perturbations remain largely unknown. We merged metatranscriptomic libraries with pangenomes to generate Core-Accessory Metatranscriptomes (CA-Metatranscriptomes) for two microbial hydrocarbon degraders that played important roles in the aftermath of the Deepwater Horizon oil spill. The Colwellia CA-Metatranscriptome illustrated pronounced dispersant-driven acceleration of core (~41%) and accessory gene (~59%) transcription, suggesting an opportunistic strategy. Marinobacter responded to oil exposure by expressing mainly accessory genes (~93%), suggesting an effective hydrocarbon-degrading lifestyle. The CA-Metatranscriptome approach offers a robust way to identify the underlying mechanisms of key microbial functions and highlights differences of specialist-vs-opportunistic responses to environmental disturbance.

External validity in distributed data networks.

PURPOSE: While much has been written about how distributed networks address internal validity, external validity is rarely discussed. We aimed to define key terms related to external validity, discuss how they relate to distributed networks, and identify how three networks (the US Food and Drug Administration's Sentinel System, the Canadian Network for Observational Drug Effect Studies [CNODES], and the National Patient Centered Clinical Research Network [PCORnet]) deal with external validity. METHODS: We define external validity, target populations, target validity, generalizability, and transportability and describe how each relates to distributed networks. We then describe Sentinel, CNODES, and PCORnet and how each approaches these concepts, including a sample case study. RESULTS: Each network approaches external validity differently. As its target population is US citizens and it includes only US data, Sentinel primarily worries about lack of external validity by not including some segments of the population. The fact that CNODES includes Canadian, United States, and United Kingdom data forces them to seriously consider whether the United States and United Kingdom data will be transportable to Canadian citizens when they meta-analyze database-specific estimates. PCORnet, with its focus on study-specific cohorts and pragmatic trials, conducts more case-by-case explorations of external validity for each new analytic data set it generates. CONCLUSIONS: There is no one-size-fits-all approach to external validity within distributed networks. With these networks and comparisons between their findings becoming a key part of pharmacoepidemiology, there is a need to adapt tools for improving external validity to the distributed network setting.

The species coalescent indicates possible bat and pangolin origins of the COVID-19 pandemic.

A consensus species tree is reconstructed from 11 gene trees for human, bat, and pangolin beta coronaviruses from samples taken early in the pandemic (prior to April 1, 2020). Using coalescent theory, the shallow (short branches relative to the hosts) consensus species tree provides evidence of recent gene flow events between bat and pangolin beta coronaviruses predating the zoonotic transfer to humans. The consensus species tree was also used to reconstruct the ancestral sequence of human SARS-CoV-2, which was 2 nucleotides different from the Wuhan sequence. The time to most recent common ancestor was estimated to be Dec 8, 2019 with a bat origin. Some human, bat, and pangolin coronavirus lineages found in China are phylogenetically distinct, a rare example of a class II phylogeography pattern (Avise et al. in Ann Rev Eco Syst 18:489-422, 1987). The consensus species tree is a product of evolutionary factors, providing evidence of repeated zoonotic transfers between bat and pangolin as a reservoir for future zoonotic transfers to humans.

Virtually the Same? Evaluating the Effectiveness of Remote Undergraduate Research Experiences.

In-person undergraduate research experiences (UREs) promote students' integration into careers in life science research. In 2020, the COVID-19 pandemic prompted institutions hosting summer URE programs to offer them remotely, raising questions about whether undergraduates who participate in remote research can experience scientific integration and whether they might perceive doing research less favorably (i.e., not beneficial or too costly). To address these questions, we examined indicators of scientific integration and perceptions of the benefits and costs of doing research among students who participated in remote life science URE programs in Summer 2020. We found that students experienced gains in scientific self-efficacy pre- to post-URE, similar to results reported for in-person UREs. We also found that students experienced gains in scientific identity, graduate and career intentions, and perceptions of the benefits of doing research only if they started their remote UREs at lower levels on these variables. Collectively, students did not change in their perceptions of the costs of doing research despite the challenges of working remotely. Yet students who started with low cost perceptions increased in these perceptions. These findings indicate that remote UREs can support students' self-efficacy development, but may otherwise be limited in their potential to promote scientific integration.

Tropical sharks feasting on and swimming through microplastics: First evidence from Malaysia.

Plastic can be degraded into microplastic (<5 mm) and has been polluting worldwide marine environment and negatively impact human health. Microplastics in marine organisms are still understudied in Malaysia, let alone from a subclass Elasmobranchii. Five tropical shark species (Carcharhinus dussumieri, Carcharhinus sorrah, Chiloscyllium hasseltii, Chiloscyllium punctatum, and Scoliodon laticaudus) were examined for the presence of microplastics. 74 sharks were sampled from the local wet market and 100 % of samples contained microplastics. A total of 2211 plastic particles were found in gastrointestinal tracts (GIT) and gills, where 29.88 ± 2.34 particles per shark (mean ± SEM). Black (40.07 %) and fiber (84.44 %) microplastics were the most dominant. Extracted microplastic sizes ranged from 0.007 mm to 4.992 mm. This study suggests that microplastic uptake is gender-related for some shark species. A subsample of microplastics (10 %) was used for polymer type identification, where polyester was recorded the highest (43.95 %).

The ACTIV-6 Stakeholder Advisory Committee: a model for virtual engagement in decentralized clinical trials.

Introduction: Engaging patients, caregivers, and other stakeholders to help guide the research process is a cornerstone of patient-centered research. Lived expertise may help ensure the relevance of research questions, promote practices that are satisfactory to research participants, improve transparency, and assist with disseminating findings. Methods: Traditionally engagement has been conducted face-to-face in the local communities in which research operates. Decentralized platform trials pose new challenges for the practice of engagement. We used a remote model for stakeholder engagement, relying on Zoom meetings and blog communications. Results: Here we describe the approach used for research partnership with patients, caregivers, and clinicians in the planning and oversight of the ACTIV-6 trial and the impact of this work. We also present suggestions for future remote engagement. Conclusions: The ACTIV-6 experience may inform proposed strategies for future engagement in decentralized trials.

Vancomycin Loading Doses and Nephrotoxicity on Medicine Teaching Services.

Background: Infectious Disease Society of America (IDSA) guidelines recommend the usage of a loading dose when using vancomycin for seriously ill patients. While the relationship between vancomycin and nephrotoxicity is the focus of many studies, few studies have examined the relationship between vancomycin loading doses and nephrotoxicity. Methods: We performed a retrospective cohort study examining vancomycin dosing for internal medicine teaching services' patients over the 2014-15 academic year at one academic medical center. We generated a list of all hospitalized patients aged 18-85 who received vancomycin and were admitted to a teaching service. Nephrotoxicity was determined by 7-day acute kidney injury (AKI) rate. Patients in the loading dose cohort were compared with those in the standard-dose cohort. Primary modeling used multivariable logistic regression with AKI as our outcome of interest. Results: Four hundred and thirty-eight patients were included for analysis. The loading dose (n = 365, 83%) and standard dosing (n = 73, 17%) cohorts were not significantly different regarding demographics, GFR, nephrotoxic drug exposure, total vancomycin received, trough levels, or comorbidities and were only significantly different regarding body mass index (BMI). The 7-day AKI rate was not significantly different between the two arms (6.3% in the standard dosing arm and 8.2% in the loading dose arm, p = 0.6). Conclusion: Few studies have examined the relationship between nephrotoxicity and vancomycin loading doses. The results of this study provide evidence that the use of loading doses is not significantly associated with increased 7-day AKI rate.

Rare occurrence of Guillain-Barré syndrome after Moderna vaccine.

A Caucasian man in his 60s with a medical history significant for ruptured left middle cerebral artery aneurysm status post clipping 2005 with residual right eye blindness and right leg weakness with gait instability presented with loss of balance, weakness of his legs and fatigue for 3 days. No other antecedent event was identified other than receiving Moderna COVID-19 vaccine 4 weeks before the presentation and 3 days before symptom onset. CT head and CT angiogram of the head and neck were performed and demonstrated no acute intracranial bleeding and no vascular abnormalities. With the findings of diffuse hyporeflexia and cerebrospinal fluid showing albumino-cytological dissociation, Guillain-Barré syndrome was high on the differentials. Electromyogram showed evidence of demyelination. He was treated with intravenous immune globulin (IVIG) and was discharged to rehab with complete symptom resolution.

Uncovering in vivo biochemical patterns from time-series metabolic dynamics.

System biology relies on holistic biomolecule measurements, and untangling biochemical networks requires time-series metabolomics profiling. With current metabolomic approaches, time-series measurements can be taken for hundreds of metabolic features, which decode underlying metabolic regulation. Such a metabolomic dataset is untargeted with most features unannotated and inaccessible to statistical analysis and computational modeling. The high dimensionality of the metabolic space also causes mechanistic modeling to be rather cumbersome computationally. We implemented a faster exploratory workflow to visualize and extract chemical and biochemical dependencies. Time-series metabolic features (about 300 for each dataset) were extracted by Ridge Tracking-based Extract (RTExtract) on measurements from continuous in vivo monitoring of metabolism by NMR (CIVM-NMR) in Neurospora crassa under different conditions. The metabolic profiles were then smoothed and projected into lower dimensions, enabling a comparison of metabolic trends in the cultures. Next, we expanded incomplete metabolite annotation using a correlation network. Lastly, we uncovered meaningful metabolic clusters by estimating dependencies between smoothed metabolic profiles. We thus sidestepped the processes of time-consuming mechanistic modeling, difficult global optimization, and labor-intensive annotation. Multiple clusters guided insights into central energy metabolism and membrane synthesis. Dense connections with glucose 1-phosphate indicated its central position in metabolism in N. crassa. Our approach was benchmarked on simulated random network dynamics and provides a novel exploratory approach to analyzing high-dimensional metabolic dynamics.

The macroscopic limit to synchronization of cellular clocks in single cells of Neurospora crassa.

We determined the macroscopic limit for phase synchronization of cellular clocks in an artificial tissue created by a "big chamber" microfluidic device to be about 150,000 cells or less. The dimensions of the microfluidic chamber allowed us to calculate an upper limit on the radius of a hypothesized quorum sensing signal molecule of 13.05 nm using a diffusion approximation for signal travel within the device. The use of a second microwell microfluidic device allowed the refinement of the macroscopic limit to a cell density of 2166 cells per fixed area of the device for phase synchronization. The measurement of averages over single cell trajectories in the microwell device supported a deterministic quorum sensing model identified by ensemble methods for clock phase synchronization. A strong inference framework was used to test the communication mechanism in phase synchronization of quorum sensing versus cell-to-cell contact, suggesting support for quorum sensing. Further evidence came from showing phase synchronization was density-dependent.

Characterizing the gene-environment interaction underlying natural morphological variation in Neurospora crassa conidiophores using high-throughput phenomics and transcriptomics.

Neurospora crassa propagates through dissemination of conidia, which develop through specialized structures called conidiophores. Recent work has identified striking variation in conidiophore morphology, using a wild population collection from Louisiana, United States of America to classify 3 distinct phenotypes: Wild-Type, Wrap, and Bulky. Little is known about the impact of these phenotypes on sporulation or germination later in the N. crassa life cycle, or about the genetic variation that underlies them. In this study, we show that conidiophore morphology likely affects colonization capacity of wild N. crassa isolates through both sporulation distance and germination on different carbon sources. We generated and crossed homokaryotic strains belonging to each phenotypic group to more robustly fit a model for and estimate heritability of the complex trait, conidiophore architecture. Our fitted model suggests at least 3 genes and 2 epistatic interactions contribute to conidiophore phenotype, which has an estimated heritability of 0.47. To uncover genes contributing to these phenotypes, we performed RNA-sequencing on mycelia and conidiophores of strains representing each of the 3 phenotypes. Our results show that the Bulky strain had a distinct transcriptional profile from that of Wild-Type and Wrap, exhibiting differential expression patterns in clock-controlled genes (ccgs), the conidiation-specific gene con-6, and genes implicated in metabolism and communication. Combined, these results present novel ecological impacts of and differential gene expression underlying natural conidiophore morphological variation, a complex trait that has not yet been thoroughly explored.

Empiric segmentation of high-risk patients: a structured literature review.

OBJECTIVES: Empiric segmentation is a rapidly growing, learning health system approach that uses large health care system data sets to identify groups of high-risk patients who may benefit from similar interventions. We aimed to review studies that used data-driven approaches to segment high-risk patient populations and describe how their designs and findings can inform health care leaders who are interested in applying similar techniques to their patient populations. STUDY DESIGN: Structured literature review. METHODS: We searched for original research articles published since 2000 that identified high-risk adult patient populations and applied data-driven analyses to segment the population. Two reviewers independently extracted study population source and criteria for high-risk designation, segmentation method, data types included, model selection criteria, and model results from the identified studies. RESULTS: Our search identified 224 articles, 12 of which met criteria for full review. Of these, 8 segmented high-risk patients and 4 segmented diagnoses without assigning patients to unique groups. Studies segmenting patients more often had clinically interpretable results. Common groups were defined by high prevalence of diabetes, cardiovascular disease, psychiatric conditions including substance use disorders, and neurologic disease (eg, stroke). Few studies incorporated patients' functional or social factors. Resulting patient and diagnosis clusters varied in ways closely linked to the model inputs, patient population inclusion criteria, and health care system context. CONCLUSIONS: Empiric segmentation can yield clinically relevant groups of patients with complex medical needs. Segmentation results are context dependent, suggesting the need for careful design and interpretation of segmentation models to ensure that results can inform clinical care and program design in the target setting.