Lessons in clinical reasoning - pitfalls, myths, and pearls: a case of persistent dysphagia and patient partnership

OBJECTIVES

Diagnostic excellence underscores the patient-centered diagnosis and patient engagement in the diagnostic process. In contrast to a patient-centered diagnosis, a doctor-centered diagnosis with a lack of patient engagement may inhibit the diagnostic process due to the lack of responsibility, disrupted information, and increased effect of cognitive biases, particularly in a situation where multiple physicians are involved. In this paper, we suggest a promising idea to enhance patient engagement in the diagnostic process by using written information by a patient about their perspective and experience, which can fill the gaps needed for diagnosis that doctors cannot find alone.

CASE PRESENTATION

A 38-year-old woman developed chest pain, which gradually worsened during the following two years. For two years, she was evaluated in multiple departments; however, no definitive diagnosis was made, and her condition did not improve. During this evaluation, she searched her symptoms and image findings online. She reached a possible diagnosis of 'esophageal achalasia.' Still, she could not tell her concerns to any physicians because she felt that her concerns were not correctly recognized, although she showed her notes that her symptoms were recorded. She finally consulted the department of internal medicine, where her notes and previous test results were thoroughly reviewed. The final diagnosis of esophageal achalasia was confirmed.

CONCLUSIONS

Doctors must organize an environment where patients can freely express their thoughts, emotions, and ideas regarding their diagnosis. Cogenerating visit notes using patient input through written communication can be a promising idea to facilitate patient engagement in the diagnostic process.

High-quality chromosome scale genome assemblies of two important Sorghum inbred lines, Tx2783 and RTx436

Sorghum bicolor (L.) Moench is a significant grass crop globally, known for its genetic diversity. High quality genome sequences are needed to capture the diversity. We constructed high-quality, chromosome-level genome assemblies for two vital sorghum inbred lines, Tx2783 and RTx436. Through advanced single-molecule techniques, long-read sequencing and optical maps, we improved average sequence continuity 19-fold and 11-fold higher compared to existing Btx623 v3.0 reference genome and obtained 19 and 18 scaffolds (N50 of 25.6 and 14.4) for Tx2783 and RTx436, respectively. Our gene annotation efforts resulted in 29 612 protein-coding genes for the Tx2783 genome and 29 265 protein-coding genes for the RTx436 genome. Comparative analyses with 26 plant genomes which included 18 sorghum genomes and 8 outgroup species identified around 31 210 protein-coding gene families, with about 13 956 specific to sorghum. Using representative models from gene trees across the 18 sorghum genomes, a total of 72 579 pan-genes were identified, with 14% core, 60% softcore and 26% shell genes. We identified 99 genes in Tx2783 and 107 genes in RTx436 that showed functional enrichment specifically in binding and metabolic processes, as revealed by the GO enrichment Pearson Chi-Square test. We detected 36 potential large inversions in the comparison between the BTx623 Bionano map and the BTx623 v3.1 reference sequence. Strikingly, these inversions were notably absent when comparing Tx2783 or RTx436 with the BTx623 Bionano map. These inversion were mostly in the pericentromeric region which is known to have low complexity regions and harder to assemble and suggests the presence of potential artifacts in the public BTx623 reference assembly. Furthermore, in comparison to Tx2783, RTx436 exhibited 324 883 additional Single Nucleotide Polymorphisms (SNPs) and 16 506 more Insertions/Deletions (INDELs) when using BTx623 as the reference genome. We also characterized approximately 348 nucleotide-binding leucine-rich repeat (NLR) disease resistance genes in the two genomes. These high-quality genomes serve as valuable resources for discovering agronomic traits and structural variation studies.

The inseparability of context and clinical reasoning

Early descriptions of clinical reasoning have described a dual process model that relies on analytical or nonanalytical approaches to develop a working diagnosis. In this classic research, clinical reasoning is portrayed as an individual-driven cognitive process based on gathering information from the patient encounter, forming mental representations that rely on previous experience and engaging developed patterns to drive working diagnoses and management plans. Indeed, approaches to patient safety, as well as teaching and assessing clinical reasoning focus on the individual clinician, often ignoring the complexity of the system surrounding the diagnostic process. More recent theories and evidence portray clinical reasoning as a dynamic collection of processes that takes place among and between persons across clinical settings. Yet, clinical reasoning, taken as both an individual and a system process, is insufficiently supported by theories of cognition based on individual clinicals and lacks the specificity needed to describe the phenomenology of clinical reasoning. In this review, we reinforce that the modern healthcare ecosystem - with its people, processes and technology - is the context in which health care encounters and clinical reasoning take place.

Homophily and social mixing in a small community: Implications for infectious disease transmission

Community mixing patterns by sociodemographic traits can inform the risk of epidemic spread among groups, and the balance of in- and out-group mixing affects epidemic potential. Understanding mixing patterns can provide insight about potential transmission pathways throughout a community. We used a snowball sampling design to enroll people recently diagnosed with SARS-CoV-2 in an ethnically and racially diverse county and asked them to describe their close contacts and recruit some contacts to enroll in the study. We constructed egocentric networks of the participants and their contacts and assessed age-mixing, ethnic/racial homophily, and gender homophily. The total size of the egocentric networks was 2,544 people (n = 384 index cases + n = 2,160 recruited peers or other contacts). We observed high rates of in-group mixing among ethnic/racial groups compared to the ethnic/racial proportions of the background population. Black or African-American respondents interacted with a wider range of ages than other ethnic/racial groups, largely due to familial relationships. The egocentric networks of non-binary contacts had little age diversity. Black or African-American respondents in particular reported mixing with older or younger family members, which could increase the risk of transmission to vulnerable age groups. Understanding community mixing patterns can inform infectious disease risk, support analyses to predict epidemic size, or be used to design campaigns such as vaccination strategies so that community members who have vulnerable contacts are prioritized.

Medical correlates of first-term attrition in US Navy personnel

INTRODUCTION

First-term attrition (FTA), or failure of a military service member to complete their initial service contract, is a major financial burden and source of lost manpower in the US Navy. The objective of the present study was to examine medical correlates of FTA using healthcare and disability rating data.

METHODS

In this retrospective cohort study, all US Navy-enlisted personnel between the years 2003 and 2018 with FTA (n=58 777) and regular discharge (n=203 084) were identified for analysis from accession dates in the Career History Archival Medical and Personnel System. Medical diagnoses from outpatient and inpatient records were abstracted from the Military Health System Data Repository. For a subgroup of the study population discharged with a disability rating (n=12 880), diagnoses were identified from the Integrated Disability Evaluation System. The FTA and regular discharge groups were compared using relative risks (RRs) and 95% CIs, and per cent differences for the disability subgroup analysis.

RESULTS

Compared with regular discharges, those with FTA were more likely to have outpatient and inpatient diagnoses for mental health disorders. Personality disorder yielded the strongest association with FTA in both outpatient (RR=10.45, 95% CI 9.79 to 11.16) and inpatient settings (RR=18.97, 95% CI 14.16 to 25.42). Other disorders associated with FTA included schizophrenia, substance-related disorders, poisoning by psychotropic agents and adjustment disorders. In the disability analysis, the FTA group relative to regular discharges had the largest per cent differences for 'arthritis, degenerative (hypertrophic or osteoarthritis)' (10.8% vs 2.5%) and 'tibia and fibula, impairment' (3.0% vs 0.4%).

CONCLUSIONS

This study provides evidence that FTA is associated with both mental and physical health conditions. Mental and physical factors related to FTA require further examination, particularly whether pre-enlistment screening or early career intervention could lead to mitigation strategies. Future research should extend this analysis to other services and population subgroups.

Phonological impairments in Hindi aphasics: Error analyses and cross-linguistic comparisons

We assessed phonological and apraxic impairments in Hindi persons with aphasia (PwA) and compared them to Italian PwA reported in previous studies. Overall, we found strong similarities. Phonological errors were present across production tasks (repetition, reading and naming), most errors were non-lexical and, among those, a majority involved individual phonemes. There were significant effects of length, but not frequency. Hindi PwA, like the Italian PwA, showed strong effects of syllabic structure, with most errors occurring on consonants and weak syllabic positions, preserving syllable structure and simplifying phonemes or syllabic templates. These similarities were modulated by some language-specific patterns. Vowel insertions were more common in Hindi, possibly due to the presence of a central vowel, and segmental simplifications concentrated on marked aspiration and retroflection features. We hope our study will encourage further research in Hindi and other Indian languages. This will improve clinical diagnosis and our understanding of cross-linguistic differences.

Exploring Competency-Based Medical Education Through the Lens of the UME-GME Transition: A Qualitative Study

PURPOSE

Competency-based medical education (CBME) represents a shift to a paradigm with shared definitions, explicit outcomes, and assessments of competence. The groundwork has been laid to ensure all learners achieve the desired outcomes along the medical education continuum using the principles of CBME. However, this continuum spans the major transition from undergraduate medical education (UME) to graduate medical education (GME) that is also evolving. This study explores the experiences of medical educators working to use CBME assessments in the context of the UME-GME transition and their perspectives on the existing challenges.

METHOD

This study used a constructivist-oriented qualitative methodology. In-depth, semistructured interviews of UME and GME leaders in CBME were performed between February 2019 and January 2020 via Zoom. When possible, each interviewee was interviewed by 2 team members, one with UME and one with GME experience, which allowed follow-up questions to be pursued that reflected the perspectives of both UME and GME educators more fully. A multistep iterative process of thematic analysis was used to analyze the transcripts and identify patterns across interviews.

RESULTS

The 9 interviewees represented a broad swath of UME and GME leadership positions, though most had an internal medicine training background. Analysis identified 4 overarching themes: mistrust (a trust chasm exists between UME and GME); misaligned goals (the residency selection process is antithetical to CBME); inadequate communication (communication regarding competence is infrequent, often unidirectional, and lacks a shared language); and inflexible timeframes (current training timeframes do not account for individual learners' competency trajectories).

CONCLUSIONS

Despite the mutual desire and commitment to move to CBME across the continuum, mistrust, misaligned goals, inadequate communication, and inflexible timeframes confound such efforts of individual schools and programs. If current efforts to improve the UME-GME transition address the themes identified, educators may be more successful implementing CBME along the continuum.

Characterization of antibiotic overuse for common infectious disease states at hospital discharge

Objective

To evaluate rates of and outcomes associated with antibiotic overuse at hospital discharge for patients with common infectious diseases states.

Design

Single-center, respective cohort study.

Setting

A large, academic medical center in the Midwest United States.

Patients

Adult patients who received antibiotics for community-acquired pneumonia (CAP), uncomplicated cystitis, or mild, non-purulent cellulitis. Patients were excluded if they did not receive antibiotic(s) upon hospital discharge, were pregnant, severely immunocompromised, had concomitant infections, died during hospitalization, or were transferred to another hospital or to an intensive care unit.

Methods

Data were abstracted from the electronic medical record of ambulatory antibiotic orders for included patients based on inpatient encounters from August 1, 2021 through July 31, 2022.

Results

Of the 182 patients included in the study, antibiotic overuse was common for all three infectious disease states: CAP (n = 87/125, 69.6%), uncomplicated cystitis (n = 21/28, 75.0%), mild, non-purulent cellulitis (n = 28/29, 96.6%). The prevailing reason for overuse was excessive antibiotic duration (n = 127/182, 69.8%; mean antibiotic duration 5.39 vs. 8.32 days, p = 0.001). Antibiotic overuse was associated with approximately one additional day in the hospital (2.48 vs. 3.32 days, p = 0.001), and an increase in emergency department visits within 30 days after discharge (1 vs. 31, p = 0.001) compared to patients without antibiotic overuse at discharge.

Conclusion

Antibiotic overuse was prevalent upon hospital discharge for these three common infectious disease states. Transitions of care should be prioritized as an area for antimicrobial stewardship intervention.

Scalable Strategies to Increase Efficiency and Augment Public Health Activities During Epidemic Peaks

OBJECTIVE

Scalable strategies to reduce the time burden and increase contact tracing efficiency are crucial during early waves and peaks of infectious transmission.

DESIGN

We enrolled a cohort of SARS-CoV-2-positive seed cases into a peer recruitment study testing social network methodology and a novel electronic platform to increase contact tracing efficiency.

SETTING

Index cases were recruited from an academic medical center and requested to recruit their local social contacts for enrollment and SARS-CoV-2 testing.

PARTICIPANTS

A total of 509 adult participants enrolled over 19 months (384 seed cases and 125 social peers).

INTERVENTION

Participants completed a survey and were then eligible to recruit their social contacts with unique "coupons" for enrollment. Peer participants were eligible for SARS-CoV-2 and respiratory pathogen screening.

MAIN OUTCOME MEASURES

The main outcome measures were the percentage of tests administered through the study that identified new SARS-CoV-2 cases, the feasibility of deploying the platform and the peer recruitment strategy, the perceived acceptability of the platform and the peer recruitment strategy, and the scalability of both during pandemic peaks.

RESULTS

After development and deployment, few human resources were needed to maintain the platform and enroll participants, regardless of peaks. Platform acceptability was high. Percent positivity tracked with other testing programs in the area.

CONCLUSIONS

An electronic platform may be a suitable tool to augment public health contact tracing activities by allowing participants to select an online platform for contact tracing rather than sitting for an interview.

Mitigating Racial And Ethnic Bias And Advancing Health Equity In Clinical Algorithms: A Scoping Review

In August 2022 the Department of Health and Human Services (HHS) issued a notice of proposed rulemaking prohibiting covered entities, which include health care providers and health plans, from discriminating against individuals when using clinical algorithms in decision making. However, HHS did not provide specific guidelines on how covered entities should prevent discrimination. We conducted a scoping review of literature published during the period 2011-22 to identify health care applications, frameworks, reviews and perspectives, and assessment tools that identify and mitigate bias in clinical algorithms, with a specific focus on racial and ethnic bias. Our scoping review encompassed 109 articles comprising 45 empirical health care applications that included tools tested in health care settings, 16 frameworks, and 48 reviews and perspectives. We identified a wide range of technical, operational, and systemwide bias mitigation strategies for clinical algorithms, but there was no consensus in the literature on a single best practice that covered entities could employ to meet the HHS requirements. Future research should identify optimal bias mitigation methods for various scenarios, depending on factors such as patient population, clinical setting, algorithm design, and types of bias to be addressed.

Machine learning functional impairment classification with electronic health record data

BACKGROUND

Poor functional status is a key marker of morbidity, yet is not routinely captured in clinical encounters. We developed and evaluated the accuracy of a machine learning algorithm that leveraged electronic health record (EHR) data to provide a scalable process for identification of functional impairment.

METHODS

We identified a cohort of patients with an electronically captured screening measure of functional status (Older Americans Resources and Services ADL/IADL) between 2018 and 2020 (N = 6484). Patients were classified using unsupervised learning K means and t-distributed Stochastic Neighbor Embedding into normal function (NF), mild to moderate functional impairment (MFI), and severe functional impairment (SFI) states. Using 11 EHR clinical variable domains (832 variable input features), we trained an Extreme Gradient Boosting supervised machine learning algorithm to distinguish functional status states, and measured prediction accuracies. Data were randomly split into training (80%) and test (20%) sets. The SHapley Additive Explanations (SHAP) feature importance analysis was used to list the EHR features in rank order of their contribution to the outcome.

RESULTS

Median age was 75.3 years, 62% female, 60% White. Patients were classified as 53% NF (n = 3453), 30% MFI (n = 1947), and 17% SFI (n = 1084). Summary of model performance for identifying functional status state (NF, MFI, SFI) was AUROC (area under the receiving operating characteristic curve) 0.92, 0.89, and 0.87, respectively. Age, falls, hospitalization, home health use, labs (e.g., albumin), comorbidities (e.g., dementia, heart failure, chronic kidney disease, chronic pain), and social determinants of health (e.g., alcohol use) were highly ranked features in predicting functional status states.

CONCLUSION

A machine learning algorithm run on EHR clinical data has potential utility for differentiating functional status in the clinical setting. Through further validation and refinement, such algorithms can complement traditional screening methods and result in a population-based strategy for identifying patients with poor functional status who need additional health resources.

How does work environment relate to diagnostic quality? A prospective, mixed methods study in primary care

OBJECTIVES

The quest to measure and improve diagnosis has proven challenging; new approaches are needed to better understand and measure key elements of the diagnostic process in clinical encounters. The aim of this study was to develop a tool assessing key elements of the diagnostic assessment process and apply it to a series of diagnostic encounters examining clinical notes and encounters' recorded transcripts. Additionally, we aimed to correlate and contextualise these findings with measures of encounter time and physician burnout.

DESIGN

We audio-recorded encounters, reviewed their transcripts and associated them with their clinical notes and findings were correlated with concurrent Mini Z Worklife measures and physician burnout.

SETTING

Three primary urgent-care settings.

PARTICIPANTS

We conducted in-depth evaluations of 28 clinical encounters delivered by seven physicians.

RESULTS

Comparing encounter transcripts with clinical notes, in 24 of 28 (86%) there was high note/transcript concordance for the diagnostic elements on our tool. Reliably included elements were red flags (92% of notes/encounters), aetiologies (88%), likelihood/uncertainties (71%) and follow-up contingencies (71%), whereas psychosocial/contextual information (35%) and mentioning common pitfalls (7%) were often missing. In 22% of encounters, follow-up contingencies were in the note, but absent from the recorded encounter. There was a trend for higher burnout scores being associated with physicians less likely to address key diagnosis items, such as psychosocial history/context.

CONCLUSIONS

A new tool shows promise as a means of assessing key elements of diagnostic quality in clinical encounters. Work conditions and physician reactions appear to correlate with diagnostic behaviours. Future research should continue to assess relationships between time pressure and diagnostic quality.

Development and psychometric testing of the Diagnostic Competency During Simulation-based (DCDS) learning tool

BACKGROUND

Despite diagnostic errors impacting an estimated 12 million people yearly in the United States, educational strategies that foster diagnostic performance among nurse practitioner (NP) students remain elusive. One possible solution is to focus explicitly on competencies fundamental for diagnostic excellence. Currently, no educational tools were found that comprehensively address individual diagnostic reasoning competencies during simulated-based learning experiences.

PURPOSE

Our research team developed and explored psychometric properties of the "Diagnostic Competency During Simulation-based (DCDS) Learning Tool."

METHOD

Items and domains were developed based on existing frameworks. Content validity was determined by a convenience sample of eight experts. Inter-rater reliability was determined by four faculty rating eight simulation scenarios.

RESULTS

Final individual competency domain scale content validity index (CVI) scores ranged between 0.9175 and 1.0; total scale CVI score was 0.98. The intra-class correlation coefficient (ICC) for the tool was 0.548 (p < 0.0001, 95 % confidence interval CI [0.482-0.612]).

CONCLUSIONS

Results suggest that the DCDS Learning Tool is relevant to diagnostic reasoning competencies and may be implemented with moderate reliability across varied simulation scenarios and performance levels. The DCDS tool expands the landscape of diagnostic reasoning assessment by providing NP educators with granular, actionable, competency-specific assessment measures to foster improvement.

Predictive Value of Early Autism Detection Models Based on Electronic Health Record Data Collected Before Age 1 Year

Importance

Autism detection early in childhood is critical to ensure that autistic children and their families have access to early behavioral support. Early correlates of autism documented in electronic health records (EHRs) during routine care could allow passive, predictive model-based monitoring to improve the accuracy of early detection.

Objective

To quantify the predictive value of early autism detection models based on EHR data collected before age 1 year.

Design, Setting, and Participants

This retrospective diagnostic study used EHR data from children seen within the Duke University Health System before age 30 days between January 2006 and December 2020. These data were used to train and evaluate L2-regularized Cox proportional hazards models predicting later autism diagnosis based on data collected from birth up to the time of prediction (ages 30-360 days). Statistical analyses were performed between August 1, 2020, and April 1, 2022.

Main Outcomes and Measures

Prediction performance was quantified in terms of sensitivity, specificity, and positive predictive value (PPV) at clinically relevant model operating thresholds.

Results

Data from 45 080 children, including 924 (1.5%) meeting autism criteria, were included in this study. Model-based autism detection at age 30 days achieved 45.5% sensitivity and 23.0% PPV at 90.0% specificity. Detection by age 360 days achieved 59.8% sensitivity and 17.6% PPV at 81.5% specificity and 38.8% sensitivity and 31.0% PPV at 94.3% specificity.

Conclusions and Relevance

In this diagnostic study of an autism screening test, EHR-based autism detection achieved clinically meaningful accuracy by age 30 days, improving by age 1 year. This automated approach could be integrated with caregiver surveys to improve the accuracy of early autism screening.

Ten new high-quality genome assemblies for diverse bioenergy sorghum genotypes

Introduction

Sorghum (Sorghum bicolor (L.) Moench) is an agriculturally and economically important staple crop that has immense potential as a bioenergy feedstock due to its relatively high productivity on marginal lands. To capitalize on and further improve sorghum as a potential source of sustainable biofuel, it is essential to understand the genomic mechanisms underlying complex traits related to yield, composition, and environmental adaptations.

Methods

Expanding on a recently developed mapping population, we generated de novo genome assemblies for 10 parental genotypes from this population and identified a comprehensive set of over 24 thousand large structural variants (SVs) and over 10.5 million single nucleotide polymorphisms (SNPs).

Results

We show that SVs and nonsynonymous SNPs are enriched in different gene categories, emphasizing the need for long read sequencing in crop species to identify novel variation. Furthermore, we highlight SVs and SNPs occurring in genes and pathways with known associations to critical bioenergy-related phenotypes and characterize the landscape of genetic differences between sweet and cellulosic genotypes.

Discussion

These resources can be integrated into both ongoing and future mapping and trait discovery for sorghum and its myriad uses including food, feed, bioenergy, and increasingly as a carbon dioxide removal mechanism.

The impact of metabolic control on cognition, neurophysiology, and well-being in PKU: A systematic review and meta-analysis of the within-participant literature

Phenylketonuria (PKU) is a metabolic disease where Phenylalanine (Phe) rises much above normal levels. Cross-sectional and correlational studies provide valuable information on the importance of maintaining low blood-Phe to achieve good outcomes, but they may be confounded, at least partially, by differences in participant demographics. Moreover, the effect of Phe at older ages is difficult to ascertain because of strong associations between Phe levels across ages. Within-participant studies avoid confounding issues. We have reviewed these studies. We followed PRISMA guidelines to search the literature for studies reporting the impact of Phe changes within participants. Phe was either increased or decreased through diet relaxation/resumption or through pharmacological interventions. Forty-six separate articles reported, singly or in combination, results on cognition (N = 37), well-being (N = 22) and neurophysiological health (N = 14). For all studies, we established, in a binary way, whether a benefit of lower Phe was or was not demonstrated and compared numbers showing benefit versus a null or negative outcome. We then analyzed whether critical parameters (e.g., length of the study/condition for the change, size of Phe change achieved) influenced presence or absence of benefit. For a subset of studies that reported quantitative cognitive outcomes, we carried out a meta-analysis to estimate the size of change in cognitive performance associated with a change in Phe and its significance. There were significantly more studies with benefits than no benefits, both for cognitive and well-being outcomes, and a trend in this direction for neurophysiological outcomes. The meta-analysis showed a highly significant effect size both overall (0.55) and when studies with adults/adolescents were considered separately (0.57). There was some indication that benefits were easier to demonstrate when differences in Phe were larger and achieved across a longer period, but these effects were not always consistent. These results reinforce results from the literature by demonstrating the importance of lower Phe in children as well as in adolescents and adults, even when confounding factors in group composition are eliminated. The field would benefit from further studies where Phe levels are contrasted within-participants to ascertain how much Phe needs to be changed and for how long to see a difference and which measures demonstrate a difference (e.g., which cognitive tasks).

Meta-analyses of cognitive functions in early-treated adults with phenylketonuria

Our study estimated size of impairment for different cognitive functions in early-treated adults with PKU (AwPKU) by combining literature results in a meta-analytic way. We analysed a large set of functions (N = 19), each probed by different measures (average = 12). Data were extracted from 26 PKU groups and matched controls, with 757 AwPKU contributing 220 measures. Effect sizes (ESs) were computed using Glass' ∆ where differences in performance between clinical/PKU and control groups are standardized using the mean and standard deviation of the control groups. Significance was assessed using measures nested within independent PKU groups as a random factor. The weighted Glass' ∆ was - 0.44 for all functions taken together, and - 0.60 for IQ, both highly significant. Separate, significant impairments were found for most functions, but with great variability (ESs from -1.02 to -0.18). The most severe impairments were in reasoning, visual-spatial attention speed, sustained attention, visuo-motor control, and flexibility. Effect sizes were larger with speed than accuracy measures, and with visuo-spatial than verbal stimuli. Results show a specific PKU profile that needs consideration when monitoring the disease.

Improving hospital sepsis care using PAs and NPs on a rapid response team

ABSTRACT

Sepsis carries a high mortality in the United States. Hospitals across the country are working to find new ways to recognize, treat, and streamline care for patients with sepsis. At an academic medical center in the Midwest, a quality improvement project was developed using a sepsis rapid response team with physician associates/assistants (PAs) and NPs. This improved hospital adherence to sepsis evaluation and order set use from 48% to 86%. The added evaluation of the patient by a PA or NP, along with ensuring adherence to the sepsis order set, made an effective first step to improve care of patients with sepsis in this hospital.

Role of a ZF-HD Transcription Factor in miR157-Mediated Feed-Forward Regulatory Module That Determines Plant Architecture in Arabidopsis

In plants, vegetative and reproductive development are associated with agronomically important traits that contribute to grain yield and biomass. Zinc finger homeodomain (ZF-HD) transcription factors (TFs) constitute a relatively small gene family that has been studied in several model plants, including Arabidopsis thaliana L. and Oryza sativa L. The ZF-HD family members play important roles in plant growth and development, but their contribution to the regulation of plant architecture remains largely unknown due to their functional redundancy. To understand the gene regulatory network controlled by ZF-HD TFs, we analyzed multiple loss-of-function mutants of ZF-HD TFs in Arabidopsis that exhibited morphological abnormalities in branching and flowering architecture. We found that ZF-HD TFs, especially HB34, negatively regulate the expression of miR157 and positively regulate SQUAMOSA PROMOTER BINDING-LIKE 10 (SPL10), a target of miR157. Genome-wide chromatin immunoprecipitation sequencing (ChIP-Seq) analysis revealed that miR157D and SPL10 are direct targets of HB34, creating a feed-forward loop that constitutes a robust miRNA regulatory module. Network motif analysis contains overrepresented coherent type IV feedforward motifs in the amiR zf-HD and hbq mutant background. This finding indicates that miRNA-mediated ZF-HD feedforward modules modify branching and inflorescence architecture in Arabidopsis. Taken together, these findings reveal a guiding role of ZF-HD TFs in the regulatory network module and demonstrate its role in plant architecture in Arabidopsis.

Metabolic engineering of oleaginous yeast Rhodotorula toruloides for overproduction of triacetic acid lactone

The plant‐sourced polyketide triacetic acid lactone (TAL) has been recognized as a promising platform chemical for the biorefinery industry. However, its practical application was rather limited due to low natural abundance and inefficient cell factories for biosynthesis. Here, we report the metabolic engineering of oleaginous yeast Rhodotorula toruloides for TAL overproduction. We first introduced a 2‐pyrone synthase gene from Gerbera hybrida (GhPS) into R. toruloides and investigated the effects of different carbon sources on TAL production. We then systematically employed a variety of metabolic engineering strategies to increase the flux of acetyl‐CoA by enhancing its biosynthetic pathways and disrupting its competing pathways. We found that overexpression of ATP‐citrate lyase (ACL1) improved TAL production by 45% compared to the GhPS overexpressing strain, and additional overexpression of acetyl‐CoA carboxylase (ACC1) further increased TAL production by 29%. Finally, we characterized the resulting strain I12‐ACL1‐ACC1 using fed‐batch bioreactor fermentation in glucose or oilcane juice medium with acetate supplementation and achieved a titer of 28 or 23 g/L TAL, respectively. This study demonstrates that R. toruloides is a promising host for the production of TAL and other acetyl‐CoA‐derived polyketides from low‐cost carbon sources.

Effects of delay, length, and frequency on onset RTs and word durations: Articulatory planning uses flexible units but cannot be prepared

There is debate regarding whether most articulatory planning occurs offline (rather than online) and whether the products of off-line processing are stored in a separate articulatory buffer until a large enough chunk is ready for production. This hypothesis predicts that delayed naming conditions should reduce not only onset RTs but also word durations because articulatory plans will be buffered and kept ready. We have tested this hypothesis with young control speakers, an aphasic speaker , and an age and education-matched speaker, using repetition, reading and picture-naming tasks. Contrary to the off-line hypothesis, delayed conditions strongly reduced onset RTs, but had no benefit for word durations. In fact, we found small effects in the opposite direction. Moreover, frequency and imageability affected word durations even in delayed conditions, consistent with articulatory processing continuing on-line. The same pattern of results was found in CS and in control participants, strengthening confidence in our results. There is debate regarding whether most articulatory planning occurs offline (rather than online) and whether the results of off-line processing are stored in a separate articulatory buffer until a large enough chunk is ready for production. This hypothesis predicts that delayed naming conditions should reduce not only onset RTs but also word durations because articulatory plans will be buffered and kept ready. We have tested young control speakers, an aphasic speaker, and an age and education matched speaker, using repetition, reading and picture naming tasks. Contrary to the off-line hypothesis, delayed conditions strongly reduced onset RTs, but had no benefit for word durations. In fact, we found small effects in the opposite direction. Moreover, frequency and imageability affected word durations even in delayed conditions, consistent with articulatory processing continuing on-line. The same pattern of results was found in CS and in control participants, strengthening confidence in our results.

Comparison of Outcomes and Process of Care for Patients Treated at Hospitals Dedicated for COVID-19 Care vs Other Hospitals

IMPORTANCE

Early in the SARS-CoV-2 pandemic, the M Health Fairview Hospital System established dedicated hospitals for establishing cohorts and caring for patients with COVID-19, yet the association between treatment at COVID-19-dedicated hospitals and mortality and complications is not known.

OBJECTIVE

To analyze the mortality rate and complications associated with treatment at the COVID-19-dedicated hospitals.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study evaluated data prospectively collected from March 1, 2020, through June 30, 2021, from 11 hospitals in Minnesota, including 2 hospitals created solely to care for patients with COVID-19. Data obtained included demographic characteristics, treatments, and outcomes of interest for all patients with a confirmed COVID-19 infection admitted to this hospital system during the study period.

EXPOSURES

Patients were grouped based on whether they received treatment from 1 of the 2 COVID-19-dedicated hospitals compared with the remainder of the hospitals within the hospital system.

MAIN OUTCOMES AND MEASURES

Multivariate analyses, including risk-adjusted logistic regression and propensity score matching, were performed to evaluate the primary outcome of in-hospital mortality and secondary outcomes, including complications and use of COVID-specific therapeutics.

RESULTS

There were 5504 patients with COVID-19 admitted during the study period (median age, 62.5 [IQR, 45.0-75.6] years; 2854 women [51.9%]). Of these, 2077 patients (37.7%) (median age, 63.4 [IQR, 50.7-76.1] years; 1080 men [52.0%]) were treated at 1 of the 2 COVID-19-dedicated hospitals compared with 3427 (62.3%; median age, 62.0 [40.0-75.1] years; 1857 women (54.2%) treated at other hospitals. The mortality rate was 11.6% (n = 241) at the dedicated hospitals compared with 8.0% (n = 274) at the other hospitals (P < .001). However, risk-adjusted in-hospital mortality was significantly lower for patients in the COVID-19-dedicated hospitals in both the unmatched group (n = 2077; odds ratio [OR], 0.75; 95% CI, 0.59-0.95) and the propensity score-matched group (n = 1317; OR, 0.78; 95% CI, 0.58-0.99). The rate of overall complications in the propensity score-matched group was significantly lower (OR, 0.81; 95% CI, 0.66-0.99) and the use of COVID-19-specific therapeutics including deep vein thrombosis prophylaxis (83.9% vs 56.9%; P < .001), high-dose corticosteroids (56.1% vs 22.2%; P < .001), remdesivir (61.5% vs 44.5%; P < .001), and tocilizumab (7.9% vs 2.0; P < .001) was significantly higher.

CONCLUSIONS AND RELEVANCE

In this cohort study, COVID-19-dedicated hospitals had multiple benefits, including providing high-volume repetitive treatment and isolating patients with the infection. This experience suggests improved in-hospital mortality for patients treated at dedicated hospitals owing to improved processes of care and supports the use of establishing cohorts for future pandemics.

SorghumBase: a web-based portal for sorghum genetic information and community advancement

SorghumBase provides a community portal that integrates genetic, genomic, and breeding resources for sorghum germplasm improvement. Public research and development in agriculture rely on proper data and resource sharing within stakeholder communities. For plant breeders, agronomists, molecular biologists, geneticists, and bioinformaticians, centralizing desirable data into a user-friendly hub for crop systems is essential for successful collaborations and breakthroughs in germplasm development. Here, we present the SorghumBase web portal ( https://www.sorghumbase.org ), a resource for the sorghum research community. SorghumBase hosts a wide range of sorghum genomic information in a modular framework, built with open-source software, to provide a sustainable platform. This initial release of SorghumBase includes: (1) five sorghum reference genome assemblies in a pan-genome browser; (2) genetic variant information for natural diversity panels and ethyl methanesulfonate (EMS)-induced mutant populations; (3) search interface and integrated views of various data types; (4) links supporting interconnectivity with other repositories including genebank, QTL, and gene expression databases; and (5) a content management system to support access to community news and training materials. SorghumBase offers sorghum investigators improved data collation and access that will facilitate the growth of a robust research community to support genomics-assisted breeding.

Ensembl Genomes 2022: an expanding genome resource for non-vertebrates

Ensembl Genomes (https://www.ensemblgenomes.org) provides access to non-vertebrate genomes and analysis complementing vertebrate resources developed by the Ensembl project (https://www.ensembl.org). The two resources collectively present genome annotation through a consistent set of interfaces spanning the tree of life presenting genome sequence, annotation, variation, transcriptomic data and comparative analysis. Here, we present our largest increase in plant, metazoan and fungal genomes since the project's inception creating one of the world's most comprehensive genomic resources and describe our efforts to reduce genome redundancy in our Bacteria portal. We detail our new efforts in gene annotation, our emerging support for pangenome analysis, our efforts to accelerate data dissemination through the Ensembl Rapid Release resource and our new AlphaFold visualization. Finally, we present details of our future plans including updates on our integration with Ensembl, and how we plan to improve our support for the microbial research community. Software and data are made available without restriction via our website, online tools platform and programmatic interfaces (available under an Apache 2.0 license). Data updates are synchronised with Ensembl's release cycle.