Phenylpropanoids Following Wounding and Infection of Sweet Sorghum Lines Differing in Responses to Stalk Pathogens.

Sweet sorghum (Sorghum bicolor) lines M81-E and Colman were previously shown to differ in responses to Fusarium thapsinum and Macrophomina phaseolina, stalk rot pathogens that can reduce the yields and quality of biomass and extracted sugars. Inoculated tissues were compared for transcriptomic, phenolic metabolite, and enzymatic activity during disease development 3 and 13 days after inoculation (DAI). At 13 DAI, M81-E had shorter mean lesion lengths than Colman when inoculated with either pathogen. Transcripts encoding monolignol biosynthetic and modification enzymes were associated with transcriptional wound (control) responses of both lines at 3 DAI. Monolignol biosynthetic genes were differentially coexpressed with transcriptional activator SbMyb76 in all Colman inoculations, but only following M. phaseolina inoculation in M81-E, suggesting that SbMyb76 is associated with lignin biosynthesis during pathogen responses. In control inoculations, defense-related genes were expressed at higher levels in M81-E than Colman. Line, treatment, and timepoint differences observed in phenolic metabolite and enzyme activities did not account for observed differences in lesions. However, generalized additive models were able to relate metabolites, but not enzyme activities, to lesion length for quantitatively modeling disease progression: in M81-E, but not Colman, sinapic acid levels positively predicted lesion length at 3 DAI when cell wall-bound syringic acid was low, soluble caffeic acid was high, and lactic acid was high, suggesting that sinapic acid may contribute to responses at 3 DAI. These results provide potential gene targets for development of sweet sorghum varieties with increased stalk rot resistance to ensure biomass and sugar quality.

Structural and Interactional Analysis of the Flavonoid Pathway Proteins: Chalcone Synthase, Chalcone Isomerase and Chalcone Isomerase-like Protein.

Chalcone synthase (CHS) and chalcone isomerase (CHI) catalyze the first two committed steps of the flavonoid pathway that plays a pivotal role in the growth and reproduction of land plants, including UV protection, pigmentation, symbiotic nitrogen fixation, and pathogen resistance. Based on the obtained X-ray crystal structures of CHS, CHI, and chalcone isomerase-like protein (CHIL) from the same monocotyledon, Panicum virgatum, along with the results of the steady-state kinetics, spectroscopic/thermodynamic analyses, intermolecular interactions, and their effect on each catalytic step are proposed. In addition, PvCHI's unique activity for both naringenin chalcone and isoliquiritigenin was analyzed, and the observed hierarchical activity for those type-I and -II substrates was explained with the intrinsic characteristics of the enzyme and two substrates. The structure of PvCHS complexed with naringenin supports uncompetitive inhibition. PvCHS displays intrinsic catalytic promiscuity, evident from the formation of p-coumaroyltriacetic acid lactone (CTAL) in addition to naringenin chalcone. In the presence of PvCHIL, conversion of p-coumaroyl-CoA to naringenin through PvCHS and PvCHI displayed ~400-fold increased Vmax with reduced formation of CTAL by 70%. Supporting this model, molecular docking, ITC (Isothermal Titration Calorimetry), and FRET (Fluorescence Resonance Energy Transfer) indicated that both PvCHI and PvCHIL interact with PvCHS in a non-competitive manner, indicating the plausible allosteric effect of naringenin on CHS. Significantly, the presence of naringenin increased the affinity between PvCHS and PvCHIL, whereas naringenin chalcone decreased the affinity, indicating a plausible feedback mechanism to minimize spontaneous incorrect stereoisomers. These are the first findings from a three-body system from the same species, indicating the importance of the macromolecular assembly of CHS-CHI-CHIL in determining the amount and type of flavonoids produced in plant cells.

Large-scale real-world data analyses of cancer risks among patients with rheumatoid arthritis.

Rheumatoid arthritis (RA) affects 24.5 million people worldwide and has been associated with increased cancer risks. However, the extent to which the observed risks are related to the pathophysiology of rheumatoid arthritis or its treatments is unknown. Leveraging nationwide health insurance claims data with 85.97 million enrollees across 8 years, we identified 92 864 patients without cancers at the time of rheumatoid arthritis diagnoses. We matched 68 415 of these patients with participants without rheumatoid arthritis by sex, race, age and inferred health and economic status and compared their risks of developing all cancer types. By 12 months after the diagnosis of rheumatoid arthritis, rheumatoid arthritis patients were 1.21 (95% confidence interval [CI] [1.14, 1.29]) times more likely to develop any cancer compared with matched enrollees without rheumatoid arthritis. In particular, the risk of developing lymphoma is 2.08 (95% CI [1.67, 2.58]) times higher in the rheumatoid arthritis group, and the risk of developing lung cancer is 1.69 (95% CI [1.32, 2.13]) times higher. We further identified the five most commonly used drugs in treating rheumatoid arthritis, and the log-rank test showed none of them is implicated with a significantly increased cancer risk compared with rheumatoid arthritis patients without that specific drug. Our study suggested that the pathophysiology of rheumatoid arthritis, rather than its treatments, is implicated in the development of subsequent cancers. Our method is extensible to investigating the connections among drugs, diseases and comorbidities at scale.

A novel function for CDK2 activity at meiotic crossover sites.

Genetic diversity in offspring is induced by meiotic recombination, which is initiated between homologs at >200 sites originating from meiotic double-strand breaks (DSBs). Of this initial pool, only 1-2 DSBs per homolog pair will be designated to form meiotic crossovers (COs), where reciprocal genetic exchange occurs between parental chromosomes. Cyclin-dependent kinase 2 (CDK2) is known to localize to so-called "late recombination nodules" (LRNs) marking incipient CO sites. However, the role of CDK2 kinase activity in the process of CO formation remains uncertain. Here, we describe the phenotype of 2 Cdk2 point mutants with elevated or decreased activity, respectively. Elevated CDK2 activity was associated with increased numbers of LRN-associated proteins, including CDK2 itself and the MutL homolog 1 (MLH1) component of the MutLγ complex, but did not lead to increased numbers of COs. In contrast, reduced CDK2 activity leads to the complete absence of CO formation during meiotic prophase I. Our data suggest an important role for CDK2 in regulating MLH1 focus numbers and that the activity of this kinase is a key regulatory factor in the formation of meiotic COs.

Dynamic Reconfiguration of Switchgrass Proteomes in Response to Rust (Puccinia novopanici) Infection.

Switchgrass (Panicum virgatum L.) can be infected by the rust pathogen (Puccinia novopanici) and results in lowering biomass yields and quality. Label-free quantitative proteomics was conducted on leaf extracts harvested from non-infected and infected plants from a susceptible cultivar (Summer) at 7, 11, and 18 days after inoculation (DAI) to follow the progression of disease and evaluate any plant compensatory mechanisms to infection. Some pustules were evident at 7 DAI, and their numbers increased with time. However, fungal DNA loads did not appreciably change over the course of this experiment in the infected plants. In total, 3830 proteins were identified at 1% false discovery rate, with 3632 mapped to the switchgrass proteome and 198 proteins mapped to different Puccinia proteomes. Across all comparisons, 1825 differentially accumulated switchgrass proteins were identified and subjected to a STRING analysis using Arabidopsis (A. thaliana L.) orthologs to deduce switchgrass cellular pathways impacted by rust infection. Proteins associated with plastid functions and primary metabolism were diminished in infected Summer plants at all harvest dates, whereas proteins associated with immunity, chaperone functions, and phenylpropanoid biosynthesis were significantly enriched. At 18 DAI, 1105 and 151 proteins were significantly enriched or diminished, respectively. Many of the enriched proteins were associated with mitigation of cellular stress and defense.

Structural Similarities and Overlapping Activities among Dihydroflavonol 4-Reductase, Flavanone 4-Reductase, and Anthocyanidin Reductase Offer Metabolic Flexibility in the Flavonoid Pathway.

Flavonoids are potent antioxidants that play a role in defense against pathogens, UV-radiation, and the detoxification of reactive oxygen species. Dihydroflavonol 4-reductase (DFR) and flavanone 4-reductase (FNR) reduce dihydroflavonols and flavanones, respectively, using NAD(P)H to produce flavan-(3)-4-(di)ols in flavonoid biosynthesis. Anthocyanidin reductase (ANR) reduces anthocyanidins to flavan-3-ols. In addition to their sequences, the 3D structures of recombinant DFR, FNR and ANR from sorghum and switchgrass showed a high level of similarity. The catalytic mechanism, substrate-specificity and key residues of three reductases were deduced from crystal structures, site-directed mutagenesis, molecular docking, kinetics, and thermodynamic ana-lyses. Although DFR displayed its highest activity against dihydroflavonols, it also showed activity against flavanones and anthocyanidins. It was inhibited by the flavonol quercetin and high concentrations of dihydroflavonols/flavonones. SbFNR1 and SbFNR2 did not show any activity against dihydroflavonols. However, SbFNR1 displayed activity against flavanones and ANR activity against two anthocyanidins, cyanidin and pelargonidin. Therefore, SbFNR1 and SbFNR2 could be specific ANR isozymes without delphinidin activity. Sorghum has high concentrations of 3-deoxyanthocyanidins in vivo, supporting the observed high activity of SbDFR against flavonols. Mining of expression data indicated substantial induction of these three reductase genes in both switchgrass and sorghum in response to biotic stress. Key signature sequences for proper DFR/ANR classification are proposed and could form the basis for future metabolic engineering of flavonoid metabolism.

Less-well known functions of cyclin/CDK complexes.

Cyclin-dependent kinases (CDKs) are activated by cyclins, which play important roles in dictating the actions of CDK/cyclin complexes. Cyclin binding influences the substrate specificity of these complexes in addition to their susceptibility to inhibition or degradation. CDK/cyclin complexes are best known to promote cell cycle progression in the mitotic cell cycle but are also crucial for important cellular processes not strictly associated with cellular division. This chapter primarily explores the understudied topic of CDK/cyclin complex functionality during the DNA damage response. We detail how CDK/cyclin complexes perform dual roles both as targets of DNA damage checkpoint signaling as well as effectors of DNA repair. Additionally, we discuss the potential CDK-independent roles of cyclins in these processes and the impact of such roles in human diseases such as cancer. Our goal is to place the spotlight on these important functions of cyclins either acting as independent entities or within CDK/cyclin complexes which have attracted less attention in the past. We consider that this will be important for a more complete understanding of the intricate functions of cell cycle proteins in the DNA damage response.

CDK2 kinase activity is a regulator of male germ cell fate.

The ability of men to remain fertile throughout their lives depends upon establishment of a spermatogonial stem cell (SSC) pool from gonocyte progenitors, and thereafter balancing SSC renewal versus terminal differentiation. Here, we report that precise regulation of the cell cycle is crucial for this balance. Whereas cyclin-dependent kinase 2 (Cdk2) is not necessary for mouse viability or gametogenesis stages prior to meiotic prophase I, mice bearing a deregulated allele (Cdk2Y15S ) are severely deficient in spermatogonial differentiation. This allele disrupts an inhibitory phosphorylation site (Tyr15) for the kinase WEE1. Remarkably, Cdk2Y15S/Y15S mice possess abnormal clusters of mitotically active SSC-like cells, but these are eventually removed by apoptosis after failing to differentiate properly. Analyses of lineage markers, germ cell proliferation over time, and single cell RNA-seq data revealed delayed and defective differentiation of gonocytes into SSCs. Biochemical and genetic data demonstrated that Cdk2Y15S is a gain-of-function allele causing elevated kinase activity, which underlies these differentiation defects. Our results demonstrate that precise regulation of CDK2 kinase activity in male germ cell development is crucial for the gonocyte-to-spermatogonia transition and long-term spermatogenic homeostasis.

A fast divide-and-conquer sparse Cox regression.

We propose a computationally and statistically efficient divide-and-conquer (DAC) algorithm to fit sparse Cox regression to massive datasets where the sample size $n_0$ is exceedingly large and the covariate dimension $p$ is not small but $n_0\gg p$. The proposed algorithm achieves computational efficiency through a one-step linear approximation followed by a least square approximation to the partial likelihood (PL). These sequences of linearization enable us to maximize the PL with only a small subset and perform penalized estimation via a fast approximation to the PL. The algorithm is applicable for the analysis of both time-independent and time-dependent survival data. Simulations suggest that the proposed DAC algorithm substantially outperforms the full sample-based estimators and the existing DAC algorithm with respect to the computational speed, while it achieves similar statistical efficiency as the full sample-based estimators. The proposed algorithm was applied to extraordinarily large survival datasets for the prediction of heart failure-specific readmission within 30 days among Medicare heart failure patients.

Effect of cultivar and temperature on the synergistic interaction between panicum mosaic virus and satellite panicum mosaic virus in switchgrass.

Panicum mosaic virus (PMV), the type member of the genus Panicovirus in the family Tombusviridae, naturally infects switchgrass (Panicum virgatum L.). PMV and its molecular partner, satellite panicum mosaic virus (SPMV), interact synergistically in coinfected millets to exacerbate the disease phenotype and increase the accumulation of PMV compared to plants infected with PMV alone. In this study, we examined the reaction of switchgrass cvs. Summer and Kanlow to PMV and PMV+SPMV infections at 24°C and 32°C. Switchgrass cv. Summer was susceptible to PMV at both temperatures. In contrast, cv. Kanlow was tolerant to PMV at 24°C, but not at 32°C, suggesting that Kanlow harbors temperature-sensitive resistance to PMV. At 24°C, PMV was readily detected in inoculated leaves, but not in upper uninoculated leaves of Kanlow, suggesting that resistance to PMV was likely mediated by abrogation of long-distance virus transport. Coinfection by PMV and SPMV at 24°C and 32°C in cv. Summer, but not in Kanlow, caused increased symptomatic systemic infection and mild disease synergism with slightly increased PMV accumulation compared to plants infected with PMV alone. These data suggest that the interaction between PMV and SPMV in switchgrass is cultivar-dependent, manifested in Summer but not in Kanlow. However, co-inoculation of cv. Kanlow with PMV+SPMV caused an enhanced asymptomatic infection, suggesting a role of SPMV in enhancement of symptomless infection in a tolerant cultivar. These data suggest that enhanced asymptomatic infections in a virus-tolerant switchgrass cultivar could serve as a source of virus spread and play an important role in panicum mosaic disease epidemiology under field conditions. Our data reveal that the cultivar, coinfection with SPMV, and temperature influence the severity of symptoms elicited by PMV in switchgrass.

SurvMaximin: Robust federated approach to transporting survival risk prediction models.

OBJECTIVE: For multi-center heterogeneous Real-World Data (RWD) with time-to-event outcomes and high-dimensional features, we propose the SurvMaximin algorithm to estimate Cox model feature coefficients for a target population by borrowing summary information from a set of health care centers without sharing patient-level information. MATERIALS AND METHODS: For each of the centers from which we want to borrow information to improve the prediction performance for the target population, a penalized Cox model is fitted to estimate feature coefficients for the center. Using estimated feature coefficients and the covariance matrix of the target population, we then obtain a SurvMaximin estimated set of feature coefficients for the target population. The target population can be an entire cohort comprised of all centers, corresponding to federated learning, or a single center, corresponding to transfer learning. RESULTS: Simulation studies and a real-world international electronic health records application study, with 15 participating health care centers across three countries (France, Germany, and the U.S.), show that the proposed SurvMaximin algorithm achieves comparable or higher accuracy compared with the estimator using only the information of the target site and other existing methods. The SurvMaximin estimator is robust to variations in sample sizes and estimated feature coefficients between centers, which amounts to significantly improved estimates for target sites with fewer observations. CONCLUSIONS: The SurvMaximin method is well suited for both federated and transfer learning in the high-dimensional survival analysis setting. SurvMaximin only requires a one-time summary information exchange from participating centers. Estimated regression vectors can be very heterogeneous. SurvMaximin provides robust Cox feature coefficient estimates without outcome information in the target population and is privacy-preserving.

Cognitive impairment and edentulism among older adults: an observational study using claims data.

BACKGROUND: The scientific link between mastication strength and cognitive function has not yet been strongly corroborated in population studies. Utilizing large-scale claims, we aim to investigate the association between edentulism and cognitive impairment in older American adults. METHODS: Using de-identified claims from a commercial insurer from 2015-2019, we conducted a retrospective cohort study using multilevel regression models to evaluate the association between denture status and clinically diagnosed cognitive impairment. Secondary analysis included symptomatic cognitive impairment in the outcome. RESULTS: Adjusting for individual-level risk factors, denture status was significantly associated with clinical cognitive impairment with odds ratios of 1.13 (95%CI: 1.02-1.25) and 1.26, (95%CI: 1.09-1.45) for complete dentures on one or both jaws, respectively. Including symptomatic cognitive impairment in the analysis did not substantially change our fundamental findings. CONCLUSION: Prevention and treatment of oral diseases should be considered a key component in preserving the overall wellness of older adults.

Transcriptomic and volatile signatures associated with maize defense against corn leaf aphid.

BACKGROUND: Maize (Zea mays L.) is a major cereal crop, with the United States accounting for over 40% of the worldwide production. Corn leaf aphid [CLA; Rhopalosiphum maidis (Fitch)] is an economically important pest of maize and several other monocot crops. In addition to feeding damage, CLA acts as a vector for viruses that cause devastating diseases in maize. We have shown previously that the maize inbred line Mp708, which was developed by classical plant breeding, provides heightened resistance to CLA. However, the transcriptomic variation conferring CLA resistance to Mp708 has not been investigated. RESULTS: In this study, we contrasted the defense responses of the resistant Mp708 genotype to those of the susceptible Tx601 genotype at the transcriptomic (mRNA-seq) and volatile blend levels. Our results suggest that there was a greater transcriptomic remodeling in Mp708 plants in response to CLA infestation compared to the Tx601 plants. These transcriptomic signatures indicated an activation of hormonal pathways, and regulation of sesquiterpenes and terpenoid synthases in a constitutive and inducible manner. Transcriptomic analysis also revealed that the resistant Mp708 genotype possessed distinct regulation of ethylene and jasmonic acid pathways before and after aphid infestation. Finally, our results also highlight the significance of constitutive production of volatile organic compounds (VOCs) in Mp708 and Tx601 plants that may contribute to maize direct and/or indirect defense responses. CONCLUSIONS: This study provided further insights to understand the role of defense signaling networks in Mp708's resistance to CLA.

Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant.

BACKGROUND: As effects of global climate change intensify, the interaction of biotic and abiotic stresses increasingly threatens current agricultural practices. The secondary cell wall is a vanguard of resistance to these stresses. Fusarium thapsinum (Fusarium stalk rot) and Macrophomina phaseolina (charcoal rot) cause internal damage to the stalks of the drought tolerant C4 grass, sorghum (Sorghum bicolor (L.) Moench), resulting in reduced transpiration, reduced photosynthesis, and increased lodging, severely reducing yields. Drought can magnify these losses. Two null alleles in monolignol biosynthesis of sorghum (brown midrib 6-ref, bmr6-ref; cinnamyl alcohol dehydrogenase, CAD; and bmr12-ref; caffeic acid O-methyltransferase, COMT) were used to investigate the interaction of water limitation with F. thapsinum or M. phaseolina infection. RESULTS: The bmr12 plants inoculated with either of these pathogens had increased levels of salicylic acid (SA) and jasmonic acid (JA) across both watering conditions and significantly reduced lesion sizes under water limitation compared to adequate watering, which suggested that drought may prime induction of pathogen resistance. RNA-Seq analysis revealed coexpressed genes associated with pathogen infection. The defense response included phytohormone signal transduction pathways, primary and secondary cell wall biosynthetic genes, and genes encoding components of the spliceosome and proteasome. CONCLUSION: Alterations in the composition of the secondary cell wall affect immunity by influencing phenolic composition and phytohormone signaling, leading to the action of defense pathways. Some of these pathways appear to be activated or enhanced by drought. Secondary metabolite biosynthesis and modification in SA and JA signal transduction may be involved in priming a stronger defense response in water-limited bmr12 plants.

Accelerating diagnosis of Parkinson's disease through risk prediction.

BACKGROUND: Characterization of prediagnostic Parkinson's Disease (PD) and early prediction of subsequent development are critical for preventive interventions, risk stratification and understanding of disease pathology. This study aims to characterize the role of the prediagnostic period in PD and, using selected features from this period as novel interception points, construct a prediction model to accelerate the diagnosis in a real-world setting. METHODS: We constructed two sets of machine learning models: a retrospective approach highlighting exposures up to 5 years prior to PD diagnosis, and an alternative model that prospectively predicted future PD diagnosis from all individuals at their first diagnosis of a gait or tremor disorder, these being features that appeared to represent the initiation of a differential diagnostic window. RESULTS: We found many novel features captured by the retrospective models; however, the high accuracy was primarily driven from surrogate diagnoses for PD, such as gait and tremor disorders, suggesting the presence of a distinctive differential diagnostic period when the clinician already suspected PD. The model utilizing a gait/tremor diagnosis as the interception point, achieved a validation AUC of 0.874 with potential time compression to a future PD diagnosis of more than 300 days. Comparisons of predictive diagnoses between the prospective and prediagnostic cohorts suggest the presence of distinctive trajectories of PD progression based on comorbidity profiles. CONCLUSIONS: Overall, our machine learning approach allows for both guiding clinical decisions such as the initiation of neuroprotective interventions and importantly, the possibility of earlier diagnosis for clinical trials for disease modifying therapies.

Association between maternal periodontal disease and adverse pregnancy outcomes: an analysis of claims data.

BACKGROUND: While a number of studies have explored the link between periodontal disease and adverse pregnancy outcomes, both epidemiological studies and intervention trials have reached contradictory results with relatively small sample sizes. Utilizing large-scale claims data, we aim to investigate the association between maternal periodontal disease and adverse pregnancy outcomes. OBJECTIVE: Utilizing large-scale claims data, we aim to investigate the association between maternal periodontal disease and adverse pregnancy outcomes. METHODS: Using de-identified claims data from a national commercial insurer in the USA, records of all observed pregnancies from 2015 to 2019 were included in this retrospective cohort study. Adverse pregnancy outcomes, including low birthweight (LBW) of the newborn, preterm birth (PTB) and spontaneous abortion, were primary outcomes. To evaluate the association between periodontal disease and pregnancy outcomes, logistic mixed-effect model was estimated with periodontal disease status, age, existing clinical conditions of mothers and geographic location as covariates. RESULTS: Out of 748 792 observed pregnancy records, 18.66% resulted in adverse pregnancy outcomes; 5.92% in LBW, 14.46% in PTB and 2.22 % in spontaneous abortion. Adjusting for individual-level risk factors, periodontal disease was significantly associated with maternal complications with odds ratios of 1.19 (95% CI:1.15, 1.24) for any adverse pregnancy outcomes, 1.10 (95% CI:1.03, 1.17) for LBW, 1.15 (95% CI:1.10, 1.19) for PTB and 1.34 (95% CI:1.23, 1.46) for spontaneous abortions. CONCLUSIONS: Maternal periodontal disease may be associated with an increased risk of maternal complications and neonatal morbidity. A timely diagnosis and treatment of periodontal disease during pregnancy should be encouraged by considering oral health as part of routine prenatal care.

Emergency department visits for dental problems among adults with private dental insurance: A national observational study.

OBJECTIVE: Dental insurance may be a protective factor in reducing unnecessary emergency department (ED) use for nontraumatic dental pain. The purpose of this study was to 1) characterize patient demographics and identify risk factors associated with ED utilization for dental problems among individuals dually enrolled in medical and dental insurance and 2) investigate antibiotic and opioid prescription patterns among these patients following discharge. Further study of this unique population may provide insight into other causes of unmet dental need beyond lack of dental insurance. METHODS: Claims data from a large national managed health care plan from 2015 to 2018 were used to evaluate ED use for dental problems in patients with synchronous medical and dental insurance. National counts for ED visits, total visit costs, primary diagnoses, and outpatient treatments for antibiotics and opioids were assessed. Multivariable regression was used to assess any associated demographic and health-related variables. RESULTS: 1492 unique patients were admitted to the ED for dental pain and 429,376 unique patients presented for other symptoms. Utilization rates for nontraumatic dental pain were estimated to be 0.4% of all ED visits, with an average cost of $1487 per visit. Within three days following discharge from the ED, 58% of patients filled an opioid prescription and 38% filled an antibiotic prescription. Patients who presented for dental ED pain were more likely to be younger, live in a ZIP code with a lower median household income, have more medical comorbidities, and receive fewer preventive dental procedures within the prior year. CONCLUSION: Our findings demonstrate a low rate of ED utilization for nontraumatic dental pain among dentally insured patients and highlight the protective value of prior dental visits for reducing ED use. Given high rates of antibiotic and opioid prescription fill following discharge, comprehensive ED guidelines regarding appropriate antibiotic and opioid treatment pathways may be helpful to provide more definitive care to patients with dental insurance.

What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask.

Coincident with the tsunami of COVID-19-related publications, there has been a surge of studies using real-world data, including those obtained from the electronic health record (EHR). Unfortunately, several of these high-profile publications were retracted because of concerns regarding the soundness and quality of the studies and the EHR data they purported to analyze. These retractions highlight that although a small community of EHR informatics experts can readily identify strengths and flaws in EHR-derived studies, many medical editorial teams and otherwise sophisticated medical readers lack the framework to fully critically appraise these studies. In addition, conventional statistical analyses cannot overcome the need for an understanding of the opportunities and limitations of EHR-derived studies. We distill here from the broader informatics literature six key considerations that are crucial for appraising studies utilizing EHR data: data completeness, data collection and handling (eg, transformation), data type (ie, codified, textual), robustness of methods against EHR variability (within and across institutions, countries, and time), transparency of data and analytic code, and the multidisciplinary approach. These considerations will inform researchers, clinicians, and other stakeholders as to the recommended best practices in reviewing manuscripts, grants, and other outputs from EHR-data derived studies, and thereby promote and foster rigor, quality, and reliability of this rapidly growing field.

International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study.

BACKGROUND: Many countries have experienced 2 predominant waves of COVID-19-related hospitalizations. Comparing the clinical trajectories of patients hospitalized in separate waves of the pandemic enables further understanding of the evolving epidemiology, pathophysiology, and health care dynamics of the COVID-19 pandemic. OBJECTIVE: In this retrospective cohort study, we analyzed electronic health record (EHR) data from patients with SARS-CoV-2 infections hospitalized in participating health care systems representing 315 hospitals across 6 countries. We compared hospitalization rates, severe COVID-19 risk, and mean laboratory values between patients hospitalized during the first and second waves of the pandemic. METHODS: Using a federated approach, each participating health care system extracted patient-level clinical data on their first and second wave cohorts and submitted aggregated data to the central site. Data quality control steps were adopted at the central site to correct for implausible values and harmonize units. Statistical analyses were performed by computing individual health care system effect sizes and synthesizing these using random effect meta-analyses to account for heterogeneity. We focused the laboratory analysis on C-reactive protein (CRP), ferritin, fibrinogen, procalcitonin, D-dimer, and creatinine based on their reported associations with severe COVID-19. RESULTS: Data were available for 79,613 patients, of which 32,467 were hospitalized in the first wave and 47,146 in the second wave. The prevalence of male patients and patients aged 50 to 69 years decreased significantly between the first and second waves. Patients hospitalized in the second wave had a 9.9% reduction in the risk of severe COVID-19 compared to patients hospitalized in the first wave (95% CI 8.5%-11.3%). Demographic subgroup analyses indicated that patients aged 26 to 49 years and 50 to 69 years; male and female patients; and black patients had significantly lower risk for severe disease in the second wave than in the first wave. At admission, the mean values of CRP were significantly lower in the second wave than in the first wave. On the seventh hospital day, the mean values of CRP, ferritin, fibrinogen, and procalcitonin were significantly lower in the second wave than in the first wave. In general, countries exhibited variable changes in laboratory testing rates from the first to the second wave. At admission, there was a significantly higher testing rate for D-dimer in France, Germany, and Spain. CONCLUSIONS: Patients hospitalized in the second wave were at significantly lower risk for severe COVID-19. This corresponded to mean laboratory values in the second wave that were more likely to be in typical physiological ranges on the seventh hospital day compared to the first wave. Our federated approach demonstrated the feasibility and power of harmonizing heterogeneous EHR data from multiple international health care systems to rapidly conduct large-scale studies to characterize how COVID-19 clinical trajectories evolve.

Authorship Correction: International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study.

[This corrects the article DOI: 10.2196/31400.].