Electronic health records (EHR) are rich heterogeneous collections of patient health information, whose broad adoption provides clinicians and researchers unprecedented opportunities for health ...informatics, disease-risk prediction, actionable clinical recommendations, and precision medicine. However, EHRs present several modeling challenges, including highly sparse data matrices, noisy irregular clinical notes, arbitrary biases in billing code assignment, diagnosis-driven lab tests, and heterogeneous data types. To address these challenges, we present MixEHR, a multi-view Bayesian topic model. We demonstrate MixEHR on MIMIC-III, Mayo Clinic Bipolar Disorder, and Quebec Congenital Heart Disease EHR datasets. Qualitatively, MixEHR disease topics reveal meaningful combinations of clinical features across heterogeneous data types. Quantitatively, we observe superior prediction accuracy of diagnostic codes and lab test imputations compared to the state-of-art methods. We leverage the inferred patient topic mixtures to classify target diseases and predict mortality of patients in critical conditions. In all comparison, MixEHR confers competitive performance and reveals meaningful disease-related topics.
Abstract Objective To report the design and implementation of the first 3 years of enrollment of the Mayo Clinic Biobank. Patients and Methods Preparations for this biobank began with a 4-day ...Deliberative Community Engagement with local residents to obtain community input into the design and governance of the biobank. Recruitment, which began in April 2009, is ongoing, with a target goal of 50,000. Any Mayo Clinic patient who is 18 years or older, able to consent, and a US resident is eligible to participate. Each participant completes a health history questionnaire, provides a blood sample, and allows access to existing tissue specimens and all data from their Mayo Clinic electronic medical record. A community advisory board provides ongoing advice and guidance on complex decisions. Results After 3 years of recruitment, 21,736 individuals have enrolled. Fifty-eight percent (12,498) of participants are female and 95% (20,541) of European ancestry. Median participant age is 62 years. Seventy-four percent (16,171) live in Minnesota, with 42% (9157) from Olmsted County, where the Mayo Clinic in Rochester, Minnesota, is located. The 5 most commonly self-reported conditions are hyperlipidemia (8979, 41%), hypertension (8174, 38%), osteoarthritis (6448, 30%), any cancer (6224, 29%), and gastroesophageal reflux disease (5669, 26%). Among patients with self-reported cancer, the 5 most common types are nonmelanoma skin cancer (2950, 14%), prostate cancer (1107, 12% in men), breast cancer (941, 4%), melanoma (692, 3%), and cervical cancer (240, 2% in women). Fifty-six percent (12,115) of participants have at least 15 years of electronic medical record history. To date, more than 60 projects and more than 69,000 samples have been approved for use. Conclusion The Mayo Clinic Biobank has quickly been established as a valuable resource for researchers.
Public health and epidemiologic research have established that social connectedness promotes overall health. Yet there have been no recent reviews of findings from research examining social ...connectedness as a determinant of mental health. The goal of this review was to evaluate recent longitudinal research probing the effects of social connectedness on depression and anxiety symptoms and diagnoses in the general population. A scoping review was performed of PubMed and PsychInfo databases from January 2015 to December 2021 following PRISMA-ScR guidelines using a defined search strategy. The search yielded 66 unique studies. In research with other than pregnant women, 83% (19 of 23) studies reported that social support benefited symptoms of depression with the remaining 17% (5 of 23) reporting minimal or no evidence that lower levels of social support predict depression at follow-up. In research with pregnant women, 83% (24 of 29 studies) found that low social support increased postpartum depressive symptoms. Among 8 of 9 studies that focused on loneliness, feeling lonely at baseline was related to adverse outcomes at follow-up including higher risks of major depressive disorder, depressive symptom severity, generalized anxiety disorder, and lower levels of physical activity. In 5 of 8 reports, smaller social network size predicted depressive symptoms or disorder at follow-up. In summary, most recent relevant longitudinal studies have demonstrated that social connectedness protects adults in the general population from depressive symptoms and disorders. The results, which were largely consistent across settings, exposure measures, and populations, support efforts to improve clinical detection of high-risk patients, including adults with low social support and elevated loneliness.
Background We recently reported an increased risk of herpes zoster (shingles or zoster) in children with asthma, but little is known about whether the same is true for adults with asthma. Objective ...We determined whether asthma is associated with an increased risk of zoster in adults. Methods This study was designed as a population-based case-control study. Zoster cases during the study period were identified among adults (aged ≥50 years) who resided in Olmsted County, Minnesota. We compared the frequency of asthma between zoster cases and birthday- and sex-matched control subjects (1:2 matching) without a history of zoster. Asthma status was ascertained based on predetermined criteria. A conditional logistic regression model was used to assess the association of asthma with risk of zoster. Results A total of 371 zoster cases and their 742 matched control subjects were enrolled. Of the 371 cases, 246 (66%) were female, 348 (94%) were white, and the mean ± SD age was 66.8 ± 10.7 years. Twenty-three percent (n = 87) of zoster cases had a history of asthma compared with 15% (n = 114) of control subjects. Controlling for pertinent covariates and confounders, there was a significant association between a history of asthma and risk of zoster (adjusted odds ratio, 1.70; 95% CI, 1.20-2.42; P = .003). The population attributable risk percentage for asthma was about 10%. Conclusions Asthma is an unrecognized risk factor for zoster in adults. Consideration should be given to immunizing adults with asthma aged more than 50 years as a target group.
E2-2 protein and Fuchs's corneal dystrophy Baratz, Keith H; Tosakulwong, Nirubol; Ryu, Euijung ...
The New England journal of medicine,
09/2010, Letnik:
363, Številka:
11
Journal Article
Recenzirano
Odprti dostop
Fuchs's corneal dystrophy (FCD) is a leading cause of corneal transplantation and affects 5% of persons in the United States who are over the age of 40 years. Clinically visible deposits called ...guttae develop under the corneal endothelium in patients with FCD. A loss of endothelial cells and deposition of an abnormal extracellular matrix are observed microscopically. In advanced disease, the cornea swells and becomes cloudy because the remaining endothelial cells are not sufficient to keep the cornea dehydrated and clear. Although rare genetic variation that contributes to both early-onset and typical late-onset forms of FCD has been identified, to our knowledge, no common variants have been reported.
We performed a genomewide association study and replicated the most significant observations in a second, independent group of subjects.
Alleles in the transcription factor 4 gene (TCF4), encoding a member of the E-protein family (E2-2), were associated with typical FCD (P=2.3x10(-26)). The association increased the odds of having FCD by a factor of 30 for persons with two copies of the disease variants (homozygotes) and discriminated between case subjects and control subjects with about 76% accuracy. At least two regions of the TCF4 locus were associated independently with FCD. Alleles in the gene encoding protein tyrosine phosphatase receptor type G (PTPRG) were associated with FCD (P=4.0x10(-7)), but the association did not reach genomewide significance.
Genetic variation in TCF4 contributes to the development of FCD. (Funded by the National Eye Institute and others.)
Difficulty of asthma ascertainment and its associated methodologic heterogeneity have created significant barriers to asthma care and research.
We evaluated the validity of an existing natural ...language processing (NLP) algorithm for asthma criteria to enable an automated chart review using electronic medical records (EMRs).
The study was designed as a retrospective birth cohort study using a random sample of 500 subjects from the 1997-2007 Mayo Birth Cohort who were born at Mayo Clinic and enrolled in primary pediatric care at Mayo Clinic Rochester. Performance of NLP-based asthma ascertainment using predetermined asthma criteria was assessed by determining both criterion validity (chart review of EMRs by abstractor as a gold standard) and construct validity (association with known risk factors for asthma, such as allergic rhinitis).
After excluding three subjects whose respiratory symptoms could be attributed to other conditions (e.g., tracheomalacia), among the remaining eligible 497 subjects, 51% were male, 77% white persons, and the median age at last follow-up date was 11.5 years. The asthma prevalence was 31% in the study cohort. Sensitivity, specificity, positive predictive value, and negative predictive value for NLP algorithm in predicting asthma status were 97%, 95%, 90%, and 98%, respectively. The risk factors for asthma (e.g., allergic rhinitis) that were identified either by NLP or the abstractor were the same.
Asthma ascertainment through NLP should be considered in the era of EMRs because it can enable large-scale clinical studies in a more time-efficient manner and improve the recognition and care of childhood asthma in practice.
Clinical decision support (CDS) tools leveraging electronic health records (EHRs) have been an approach for addressing challenges in asthma care but remain under-studied through clinical trials.
To ...assess the effectiveness and efficiency of Asthma-Guidance and Prediction System (A-GPS), an Artificial Intelligence (AI)-assisted CDS tool, in optimizing asthma management through a randomized clinical trial (RCT).
This was a single-center pragmatic RCT with a stratified randomization design conducted for one year in the primary care pediatric practice of the Mayo Clinic, MN. Children (<18 years) diagnosed with asthma receiving care at the study site were enrolled along with their 42 primary care providers. Study subjects were stratified into three strata (based on asthma severity, asthma care status, and asthma diagnosis) and were blinded to the assigned groups.
Intervention was a quarterly A-GPS report to clinicians including relevant clinical information for asthma management from EHRs and machine learning-based prediction for risk of asthma exacerbation (AE). Primary endpoint was the occurrence of AE within 1 year and secondary outcomes included time required for clinicians to review EHRs for asthma management.
Out of 555 participants invited to the study, 184 consented for the study and were randomized (90 in intervention and 94 in control group). Median age of 184 participants was 8.5 years. While the proportion of children with AE in both groups decreased from the baseline (P = 0.042), there was no difference in AE frequency between the two groups (12% for the intervention group vs. 15% for the control group, Odds Ratio: 0.82; 95%CI 0.374-1.96; P = 0.626) during the study period. For the secondary end points, A-GPS intervention, however, significantly reduced time for reviewing EHRs for asthma management of each participant (median: 3.5 min, IQR: 2-5), compared to usual care without A-GPS (median: 11.3 min, IQR: 6.3-15); p<0.001). Mean health care costs with 95%CI of children during the trial (compared to before the trial) in the intervention group were lower than those in the control group (-$1,036 -$2177, $44 for the intervention group vs. +$80 -$841, $1000 for the control group), though there was no significant difference (p = 0.12). Among those who experienced the first AE during the study period (n = 25), those in the intervention group had timelier follow up by the clinical care team compared to those in the control group but no significant difference was found (HR = 1.93; 95% CI: 0.82-1.45, P = 0.10). There was no difference in the proportion of duration when patients had well-controlled asthma during the study period between the intervention and the control groups.
While A-GPS-based intervention showed similar reduction in AE events to usual care, it might reduce clinicians' burden for EHRs review resulting in efficient asthma management. A larger RCT is needed for further studying the findings.
ClinicalTrials.gov Identifier: NCT02865967.
Abstract Purpose Accidental falls are a major public health concern among people of all ages. Little is known about whether an individual-level housing-based socioeconomic status (SES) measure is ...associated with the risk of accidental falls. Methods Among 12,286 Mayo Clinic Biobank participants residing in Olmsted County, Minnesota, subjects who experienced accidental falls between the biobank enrollment and September 2014 were identified using ICD-9 codes evaluated at emergency departments. HOUSES (HOUsing-based Index of SocioEconomic Status), a SES status measure based on individual housing features, was also calculated. Cox regression models were utilized to assess the association of the HOUSES (in quartiles) with accidental fall risk. Results 711 (5.8%) participants had at least one emergency room visit due to an accidental fall during the study period. Subjects with higher HOUSES were less likely to experience falls in a dose-response manner (hazard ratio: 0.58; 95% confidence interval: 0.44-0.76 for comparing the highest to the lowest quartile). In addition, the HOUSES was positively associated with better health behaviors, social support, and functional status. Conclusions The HOUSES is inversely associated with accidental fall risk requiring emergency care in a dose-response manner. The HOUSES may capture falls-related risk factors through housing features and socioeconomic status-related psychosocial factors.
Public health and epidemiologic research have established that social connectedness promotes overall health. Yet there have been no recent reviews of findings from research examining social ...connectedness as a determinant of mental health. The goal of this review was to evaluate recent longitudinal research probing the effects of social connectedness on depression and anxiety symptoms and diagnoses in the general population. A scoping review was performed of PubMed and PsychInfo databases from January 2015 to December 2021 following PRISMA-ScR guidelines using a defined search strategy. The search yielded 66 unique studies. In research with other than pregnant women, 83% (19 of 23) studies reported that social support benefited symptoms of depression with the remaining 17% (5 of 23) reporting minimal or no evidence that lower levels of social support predict depression at follow-up. In research with pregnant women, 83% (24 of 29 studies) found that low social support increased postpartum depressive symptoms. Among 8 of 9 studies that focused on loneliness, feeling lonely at baseline was related to adverse outcomes at follow-up including higher risks of major depressive disorder, depressive symptom severity, generalized anxiety disorder, and lower levels of physical activity. In 5 of 8 reports, smaller social network size predicted depressive symptoms or disorder at follow-up. In summary, most recent relevant longitudinal studies have demonstrated that social connectedness protects adults in the general population from depressive symptoms and disorders. The results, which were largely consistent across settings, exposure measures, and populations, support efforts to improve clinical detection of high-risk patients, including adults with low social support and elevated loneliness.
The clinical utility of microbiome biomarkers depends on the reliable and reproducible nature of comparative results. Underappreciation of the variation associated with common demographic, health, ...and behavioral factors may confound associations of interest and generate false positives. Here, we present the Midwestern Reference Panel (MWRP), a resource for comparative gut microbiome studies conducted in the Midwestern United States. We analyzed the relationships between demographic and health behavior-related factors and the microbiota in this cohort, and estimated their effect sizes. Most variables investigated were associated with the gut microbiota. Specifically, body mass index (BMI), race, sex, and alcohol use were significantly associated with microbial β-diversity (P < 0.05, unweighted UniFrac). BMI, race and alcohol use were also significantly associated with microbial α-diversity (P < 0.05, species richness). Tobacco use showed a trend toward association with the microbiota (P < 0.1, unweighted UniFrac). The effect sizes of the associations, as quantified by adjusted R(2) values based on unweighted UniFrac distances, were small (< 1% for all variables), indicating that these factors explain only a small percentage of overall microbiota variability. Nevertheless, the significant associations between these variables and the gut microbiota suggest that they could still be potential confounders in comparative studies and that controlling for these variables in study design, which is the main objective of the MWRP, is important for increasing reproducibility in comparative microbiome studies.
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