An evaluation of clinical risk factors for estimating fracture risk in postmenopausal osteoporosis using an electronic medical record database

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

BACKGROUND

Electronic health records (EHRs) enable health data exchange across interconnected systems from varied settings. Epic is among the 5 leading EHR providers and is the most adopted EHR system across the globe. Despite its global reach, there is a gap in the literature detailing how EHR systems such as Epic have been used for health care research.

OBJECTIVE

The objective of this scoping review is to synthesize the available literature on use cases of the Epic EHR for research in various areas of clinical and health sciences.

METHODS

We used established scoping review methods and searched 9 major information repositories, including databases and gray literature sources. To categorize the research data, we developed detailed criteria for 5 major research domains to present the results.

RESULTS

We present a comprehensive picture of the method types in 5 research domains. A total of 4669 articles were screened by 2 independent reviewers at each stage, while 206 articles were abstracted. Most studies were from the United States, with a sharp increase in volume from the year 2015 onwards. Most articles focused on clinical care, health services research and clinical decision support. Among research designs, most studies used longitudinal designs, followed by interventional studies implemented at single sites in adult populations. Important facilitators and barriers to the use of Epic and EHRs in general were identified. Important lessons to the use of Epic and other EHRs for research purposes were also synthesized.

CONCLUSIONS

The Epic EHR provides a wide variety of functions that are helpful toward research in several domains, including clinical and population health, quality improvement, and the development of clinical decision support tools. As Epic is reported to be the most globally adopted EHR, researchers can take advantage of its various system features, including pooled data, integration of modules and developing decision support tools. Such research opportunities afforded by the system can contribute to improving quality of care, building health system efficiencies, and conducting population-level studies. Although this review is limited to the Epic EHR system, the larger lessons are generalizable to other EHRs.

Deciphering the Core Metabolites of Fanconi Anemia by Using a Multi-Omics Composite Network

Deciphering the metabolites of human diseases is an important objective of biomedical research. Here, we aimed to capture the core metabolites of Fanconi anemia (FA) using the bioinformatics method of a multi-omics composite network. Based on the assumption that metabolite levels can directly mirror the physiological state of the human body, we used a multi-omics composite network that integrates six types of interactions in humans (gene-gene, disease phenotype-phenotype, disease-related metabolite-metabolite, gene-phenotype, gene-metabolite, and metabolite-phenotype) to procure the core metabolites of FA. This method is applicable in predicting and prioritizing disease candidate metabolites and is effective in a network without known disease metabolites. In this report, we first singled out the differentially expressed genes upon different groups that were related with FA and then constructed the multi-omics composite network of FA by integrating the aforementioned six networks. Ultimately, we utilized random walk with restart (RWR) to screen the prioritized candidate metabolites of FA, and meanwhile the co-expression gene network of FA was also obtained. As a result, the top 5 metabolites of FA were tenormin (TN), guanosine 5'-triphosphate, guanosine 5'-diphosphate, triphosadenine (DCF) and adenosine 5'-diphosphate, all of which were reported to have a direct or indirect relationship with FA. Furthermore, the top 5 co-expressed genes were CASP3, BCL2, HSPD1, RAF1 and MMP9. By prioritizing the metabolites, the multi-omics composite network may provide us with additional indicators closely linked to FA.

Efficacy and Safety of Postmenopausal Osteoporosis Treatments: A Systematic Review and Network Meta-Analysis of Randomized Controlled Trials

Although a range of pharmacological interventions is available, it remains uncertain which treatment for osteoporosis is more effective. This network meta-analysis study aimed to compare different drug efficacy and safety in randomized controlled trials (RCTs) for the treatment of postmenopausal osteoporosis. PubMed, EMBASE, MEDLINE, Clinicaltrial.gov, Cochrane library, Google scholar were searched up to 31 October 2020. Randomized placebo-controlled trials that reported measures of bone mineral density (BMD) percentage change and/or numbers of adverse events of postmenopausal osteoporosis patients were included. Network meta-analysis was conducted using frequentist approach. Ninety-four RCTs comprising 15,776 postmenopausal osteoporosis females were included in the network meta-analysis. Compared with placebo, most interventions showed increase in BMD change. According to surfaces under the cumulative ranking curves (SUCRAs), strontium ranelate, fluoride, and hormone replacement therapy were most effective in increasing total hip, lumbar spine, and distal radius BMD, respectively. Parathyroid hormone (PTH) was most effective in preventing new hip fracture. When taking into account all anatomic sites, bisphosphonate (BP), monoclonal antibody (mAb), and fluoride have a balanced efficacy in increasing BMD at all sites. Considering both the effectiveness of increasing BMD and preventing hip fracture, mAb, BP, and PTH are more favorable among all interventions. The treatment effects of different medications on BMD percentage change are anatomic site-dependent. After weighing anti-osteoporosis treatment efficacy against risk of complications, BP and mAb are the more favorable interventions to increase BMD at all sites and reduce the risks of hip fracture and death.

Predicting treatment recommendations in postmenopausal osteoporosis

We designed, implemented, and tested a clinical decision support system at the Research Center for the Study of Menopause and Osteoporosis within the University of Ferrara (Italy). As an independent module of our system, we implemented an original machine learning system for rule extraction, enriched with a hierarchical extraction methodology and a novel rule evaluation technique. Such a module is used in everyday operation protocol, and it allows physicians to receive suggestions for prevention and treatment of osteoporosis. In this paper, we design and execute an experiment based on two years of data, in order to evaluate and report the reliability of our suggestion system. Our results are encouraging, and in some cases reach expected accuracies of around 90%.

Use of an electronic medical record dashboard to identify gaps in osteoporosis care

Using an electronic medical record (EMR)-based dashboard, this study explored osteoporosis care gaps in primary care. Eighty-four physicians shared their practice activities related to bone mineral density testing, 10-year fracture risk calculation and treatment for those at high risk. Significant gaps in fracture risk calculation and osteoporosis management were identified.

PURPOSE

To identify care gaps in osteoporosis management focusing on Canadian clinical practice guidelines (CPG) related to bone mineral density (BMD) testing, 10-year fracture risk calculation and treatment for those at high risk.

METHODS

The ADVANTAGE OP EMR tool consists of an interactive algorithm to facilitate assessment and management of fracture risk using CPG. The FRAX® and Canadian Association of Radiologists and Osteoporosis Canada (CAROC) tools were embedded to facilitate 10-year fracture risk calculation. Physicians managed patients as clinically indicated but with EMR reminders of guideline recommendations; participants shared practice level data on management activities after 18-month use of the tool.

RESULTS

Eighty-four physicians (54%) of 154 who agreed to participate in this study shared their aggregate practice activities. Across all practices, there were 171,310 adult patients, 40 years of age and older, of whom 17,214 (10%) were at elevated risk for fracture. Sixty-two percent of patients potentially at elevated risk for fractures did not have BMD testing completed; most common reasons for this were intention to order BMD later (48%), physician belief that BMD was not required (15%) and patient refusal (20%). For patients with BMD completed, fracture risk was calculated in 29%; 19% were at high risk, of whom 37% were not treated with osteoporosis medications as recommended by CPG.

CONCLUSION

Despite access to CPG and fracture risk calculators through the ADVANTAGE OP EMR tool, significant gaps remain in fracture risk calculation and osteoporosis management. Additional strategies are needed to address this clinical inertia among family physicians.

Summary perioperative risk metrics within the electronic medical record predict patient-level cost variation in pancreaticoduodenectomy

BACKGROUND

Automated data extraction from the electronic medical record is fast, scalable, and inexpensive compared with manual abstraction. However, concerns regarding data quality and control for underlying patient variation when performing retrospective analyses exist. This study assesses the ability of summary electronic medical record metrics to control for patient-level variation in cost outcomes in pancreaticoduodenectomy.

METHODS

Patients that underwent pancreaticoduodenectomy from 2014 to 2018 at a single institution were identified within the electronic medical record and linked with the National Surgical Quality Improvement Program. Variables in both data sets were compared using interrater reliability. Logistic and linear regression modelling of complications and costs were performed using combinations of comorbidities/summary metrics. Models were compared using the adjusted R² and Akaike information criterion.

RESULTS

A total of 117 patients populated the final data set. A total of 31 (26.5%) patients experienced a complication identified by the National Surgical Quality Improvement Program. The median direct variable cost for the encounter was US$14,314. Agreement between variables present in the electronic medical record and the National Surgical Quality Improvement Program was excellent. Stepwise linear regression models of costs, using only electronic medical record-extractable variables, were non-inferior to those created with manually abstracted individual comorbidities (R² = 0.67 vs 0.30, Akaike information criterion 2,095 vs 2,216). Model performance statistics were minimally impacted by the addition of comorbidities to models containing electronic medical record summary metrics (R² = 0.67 vs 0.70, Akaike information criterion 2,095 vs 2,088).

CONCLUSION

Summary electronic medical record perioperative risk metrics predict patient-level cost variation as effectively as individual comorbidities in the pancreaticoduodenectomy population. Automated electronic medical record data extraction can expand the patient population available for retrospective analysis without the associated increase in human and fiscal resources that manual data abstraction requires.

Abnormal sub-pathways competitively regulated by lncRNAs contribute to postmenopausal osteoporosis

Abnormal sub-pathways competitively regulated by long non-coding RNAs (lncRNAs) for postmenopausal osteoporosis (PO) based on integration of lncRNA-mRNA expression data and pathway network topologies were investigated. Interesting lncRNA-mRNA pairs were selected by Pearsons correlation coefficient (PCC) algorithm on the basis of lncRNA-miRNA and miRNA-mRNA interactions and gene expression profiles. Then, lncRNAs in interesting pairs were embedded into pathway graphs as signature nodes by linking to their regulated-mRNAs, and lncRNA competitively regulated pathways (LCRPs) were gained for PO patients. Moreover, sub-pathways were detected dependent on the shortest distance similarity and the pathway topology. The abnormal sub-pathways were determined utilizing the Wallenius approximation methods through evaluating the statistical significance of sub-pathways. In total 75 interesting lncRNA-mRNA pairs (representing 17 lncRNAs and 74 mRNAs) were identified. Subsequently, 42 LCRPs were extracted from pathway graphs by signature lncRNA regulated mRNAs. Moreover, 14 abnormal sub-pathways with P<0.05 were obtained between PO patients and controls, such as sub-pathways of PI3K-Akt signaling pathway and long-term potentiation. This finding may facilitate understanding the molecular mechanism of PO, and point a new direction to identify potential biomarkers for treatment and prevention of the disease.

Hub genes and gene functions associated with postmenopausal osteoporosis predicted by an integrated method

Postmenopausal osteoporosis (PO) imposes great burden on individuals and society. This study predicted hub genes and gene functions for PO by an integration of the convergent evidence (CE) method, rank product (RP) algorithm and the combing of P-values. Using the gene expression data, genes were ranked by the CE method, RP algorithm and combing P-values, respectively. Subsequently, the top 100 genes were selected from each of the three gene lists, and then the common genes for two or three methods were denoted as informative genes of PO. A mutual information network (MIN) was constructed for the informative genes utilizing the context likelihood of relatedness algorithm. Topological centrality (degree) analysis was conducted on the MIN to investigate hub genes. Then we performed Gene Ontology (GO) enrichment analysis dependent upon the Biological Networks Gene Ontology tool (BiNGO) plugin of Cytoscape to investigate hub gene functions for PO patients. Consequently, a total of 82 informative genes were obtained by integrating the results of the three methods. There were 82 nodes and 1,741 edges in the MIN, of which 8 hub genes were identified, such as PFN1, EEF2 and S100A9. The result of GO enrichment analysis showed that 49 GO terms with P<0.001 were detected, especially the top 5 gene sets were defined as hub gene functions of PO, for instance, translational elongation, translation and cellular macromolecule biosynthetic process. In conclusion, we have predicted 8 hub genes and 5 hub gene functions associated with PO patients. The findings might help understand the molecular mechanism underlying PO.

High prevalence of risk factors for low bone mineral density and estimated fracture and fall risk among elderly medical inpatients: a missed opportunity

AIMS

(1) To calculate the absolute fracture risk by using the fracture risk assessment (FRAX) model among elderly medical inpatients; (2) to assess the risk of falls, especially among patients with increased risk of fractures; and (3) to design and implement a bone health protocol to improve the assessment of fracture risk.

METHODS

The study participants were all inpatients admitted to the medical wards at University Hospital Kerry, Ireland. All consecutive eligible patients aged ≥ 65 years were prospectively evaluated to populate clinical risk factor variables used in the FRAX model and the fall assessment was made by using Fracture Risk Questionnaire.

RESULTS

Consecutive 465 medical inpatients were screened, and 200 eligible medical inpatients were evaluated. The mean age of the cohort was 73.8 ± 9 years and 56% were male. The body mass index of the cohort was 27 ± 5, and only 21% (n = 42) of patients reported having ever had a DXA scan. Previous personal history of low fragility fracture was present in 20.5% (n = 41) of the patients. The absolute 10-year risk of major osteoporotic and hip fracture was 15 ± 12 and 7.6 ± 11, respectively, and 25.5% (n = 51) and 64.5% (n = 129) respectively of the cohort had fracture risks exceeding the National Osteoporosis Federation (NOF) thresholds for treatment. High fall risk was noted in 63% of the cohort.

CONCLUSIONS

A very high prevalence of fracture and fall risk was noted. A medical inpatient stay offers a window of opportunity for assessment of osteoporotic fracture risk. With these findings, a bone health protocol has been developed.

Fracture Risk Assessment With FRAX Using Real-World Data in a Population-Based Cohort From Israel

The predictive value of the World Health Organization's Fracture Risk Assessment Tool (FRAX) was evaluated using real-world community data. A population-based cohort of 141,320 women aged 50-90 years (median age, 58 years; interquartile range, 54-67) in 2004 was extracted from the central database of a large Israeli health-care services provider and insurer. Retrospective FRAX scores were calculated using computerized health records and compared with actual incidence of major osteoporotic fractures (MOFs) during the following 10 years. Fracture proportions of 6.9% for MOFs and 2.2% for hip fractures were expected, as opposed to 13.5% and 2.9% observed. The area under the receiver operating characteristic curve (AUC) of FRAX scores calculated without the inclusion of bone mineral density (BMD) data was 0.65 (95% confidence interval: 0.65, 0.66) for MOF and 0.82 (95% confidence interval: 0.81, 0.82) for hip fracture. A total of 16,578 subjects had BMD data at the index date, and their risk estimates based solely on BMD exhibited lower predictive performance for both MOFs (AUC = 0.62 vs. 0.65; P = 0.003) and hip fractures (AUC = 0.78 vs. 0.84; P < 0.001) as compared with FRAX. FRAX scores based on electronic health records provided reasonable discrimination despite some underestimation of the absolute risk of nonhip fractures. Integration of FRAX with routine clinical systems could increase implementation in daily practice and improve risk detection, especially for patients without BMD data.

Efficacy and safety of bazedoxifene in postmenopausal women with osteoporosis: A systematic review and meta-analysis

INTRODUCTION

Bazedoxifene may be promising to treat osteoporosis of postmenopausal women. We conducted a systematic review and meta-analysis to explore the efficacy and safety of bazedoxifene in postmenopausal women with osteoporosis.

METHODS

PubMed, EMbase, Web of science, EBSCO, and Cochrane library databases were systematically searched. Randomized controlled trials (RCTs) assessing the effect of bazedoxifene on osteoporosis of postmenopausal women were included. Two investigators independently searched articles, extracted data, and assessed the quality of included studies. The primary outcomes were vertebral fracture and spine BMD at 3 and 7 years.

RESULTS

Four RCTs are included in the meta-analysis. Overall, compared with placebo intervention in postmenopausal women with osteoporosis, bazedoxifene intervention can significantly reduce the risk of vertebral fracture [risk risks (RRs) = 0.69; 95% confidence interval (95% CI) = 0.52-0.93; P = .01], and increase spine BMD at 3 years (Std. mean difference = 1.71; 95% CI = 1.55-1.87; P < .005) and 7 years (Std. mean difference = 8.31; 95% CI = 8.07-8.55; P < .005). Bazedoxifene intervention results in no increase in adverse events (RR = 1.00; 95% CI = 0.99-1.00; P = .34), serious adverse events (RR = 1.04; 95% CI = 0.97-1.12; P = .31), myocardial infarction (RR = 0.88; 95% CI = 0.51-1.52; P = .64), stroke (RR = 0.97; 95% CI = 0.64-1.46; P = .87), venous thromboembolic event (RR = 1.56; 95% CI = 0.92-2.64; P = .10), and breast carcinoma (RR = 1.03; 95% CI = 0.59-1.79; P = .92).

CONCLUSIONS

Compared with placebo intervention for the osteoporosis of postmenopausal women, bazedoxifene intervention is found to significantly reduce the incidence of vertebral fracture and increase spine BMD at 3 and 7 years, and results in no increase in adverse events, serious adverse events, myocardial infarction, stroke, venous thromboembolic event, and breast carcinoma.

Impact of FRAX-based osteoporosis intervention using real world data

OBJECTIVES

To estimate the implications and accuracy of the most common fracture prevention strategies: (1) fixed threshold by the National Osteoporosis Foundation (NOF), (2) age-dependent threshold by the National Osteoporosis Guideline Group (NOGG) and (3) osteoporotic bone mineral density (BMD).

METHODS

A retrospective cohort of all 50-90years old female members in a nationally representative payer provider healthcare organization in Israel, with 10years of follow-up on incident events of major osteoporotic fractures. Since events are less frequent than non-events, balanced accuracy (the average between the accuracy obtained for patients with and without events) was used to measure performance.

RESULTS

Overall among 141,320 women NOF and NOGG would recommend therapy for 17.3% and 2.8% respectively, with NOF exhibiting higher balanced accuracy: 74.1% vs. 54.2% for incident hip fractures detection and 60.0% vs. 51.6% for a composite outcome of major osteoporotic fractures. In patients with available BMD (n=16,578) the treatment intervention criteria of NOF, NOGG, osteoporotic femur neck or vertebral BMD were met by 30.5%, 9.3% and 24.6% of the population, with balanced accuracy of 70.1%, 56.5% and 62.3% respectively for hip fractures and 61.4%, 52.8%, 58.1% for major osteoporotic fractures. At the age of 75years or older the NOF hip fracture risk threshold (3%) was exceeded in most women regardless of risk factors other than age.

CONCLUSIONS

In this large population-based study, detection of patients at high risk of sustaining a major osteoporotic fracture within 10 years was more accurate with the NOF fixed threshold criteria as compared with the age-varying NOGG or BMD-only. However, special consideration and further studies are warranted in patients aged 75years or older with preserved bone density, which may benefit from non-medicinal interventions.

The relationship between postmenopausal women's sclerostin levels and their bone density, age, body mass index, hormonal status, and smoking and consumption of coffee and dairy products

PURPOSE

To investigate the relationship between postmenopausal women's sclerostin levels and bone density and the factors that may affect this relationship.

MATERIALS AND METHODS

135 postmenopausal patients' ages, BMIs, hormonal statuses, BMD values, and smoking, and consumption of coffee and dairy products were compared with their sclerostin levels.

RESULTS

No statistical relationship was found between sclerostin level and age in the group with osteoporosis (p = 0.204, r = -0.305). There was a positive, high-level relationship between sclerostin levels and BMI in the osteoporosis group and it was found to be statistically significant (p < 0.001, r = 0.786). No statistical relationship was found between sclerostin level and age in the non-osteoporosis group with (p = 0.496, r = -0.88). There was a positive, moderate relationship between sclerostin levels and BMI in the non-osteoporosis group and it was found to be statistically significant (p < 0.001, r = 0.505). No statistically significant relationship could be found between sclerostin levels and vitamin D (p = 0.723), PTH (p = 0.112), FSH (p = 0.795), E₂ (p = 0.627), TSH (p = 0.517), T₃ (p = 0.788), and T₄ (p = 0.664) blood levels. No significant difference was found among the groups formed by smoking, consumption of coffee and milk, and dairy products, either (p = 0.405; p = 0.626; p = 0.234, respectively). It was monitored that sclerostin's negative effect observed on BMD scores was independent from age; however, it had a positive correlation with BMI.

CONCLUSION

As blood sclerostin levels increase, bone mineral density decreases. This negative effect of sclerostin on bone density increases as BMI increases, too. Effects of sclerostin levels on bone density are independent from age, and they are not affect by levels of vitamin D: PTH, FSH, E₂ and thyroid hormones, and daily activities, such as smoking and consumption of coffee and milk and dairy products, either.

LC-MS/MS Measurement of Parathyroid Hormone-Related Peptide

INTRODUCTION

Parathyroid hormone-related peptide (PTHrP) is involved in activating pathways, allowing tumor cells to form bone metastases. Measurement of PTHrP is used for the diagnosis and clinical management of patients suspected of hypercalcemia of malignancy. We developed an LC-MS/MS method for measuring PTHrP, established sex-specific reference intervals, and assessed the method's performance.

METHODS

PTHrP was enriched from plasma samples with rabbit polyclonal anti-PTHrP antibody conjugated to magnetic beads. Enriched PTHrP was digested with trypsin, and PTHrP-specific tryptic peptide was analyzed with 2-dimensional LC-MS/MS in multiple reaction monitoring mode.

RESULTS

The lower limit of quantification was 0.6 pmol/L, and the upper limit of linearity was 600 pmol/L. Total imprecision was <10%. Very poor agreement was observed with the RIA (n = 207; Deming regression RIA = 0.059 × LC-MS/MS - 1.8, r = 0.483; Sy|x = 3.9). Evaluation of the clinical performance of the assay using samples from patients with and without hypercalcemia (n = 199) resulted in an area under the ROC curve of 0.874. In sets of consecutively analyzed routine samples of patients assessed for hypercalcemia, the PTHrP positivity rate by RIA (n = 1376) was 1.9%, and 26.6% by LC-MS/MS (n = 1705). Concentrations were below the lower limit of quantification in 95.6% of the samples by RIA and 2.0% by LC-MS/MS.

CONCLUSIONS

PTHrP is a normal constituent in circulating blood and its concentrations are substantially underestimated by commercial RIAs, causing false-negative results in samples from patients suspected of hypercalcemia. Our observations suggest a link between increased concentrations of PTHrP in postmenopausal women with low body mass index and increased incidence of osteoporosis.