Electronic health record data use in the assessment of quality indicators for glucocorticoid osteoporosis screening in systemic lupus erythematosus.

OBJECTIVE: To determine whether electronic health record (EHR) data components could be identified and used to assess bone health quality indicators in patients with systemic lupus erythematosus as a foundation for population health management. METHODS: We identified patients in our EHR system who had diagnosis codes for lupus from 2012 to 2017 and characterized them based on the frequency and dosage of prescribed glucocorticoid medications. The medical records of patients who received repeated high-dose glucocorticoid orders were further reviewed for osteoporosis, osteoporotic fractures, receipt of appropriate preventive screening, and orders for protective medications based on established quality indicators. Descriptive statistics were calculated to summarize results. RESULTS: We identified 617 patients with a lupus diagnosis; 414 received glucocorticoid prescriptions, 189 received chronic, high-dose; and 83 received chronic, low-dose prescription orders. Of those with chronic high-dose glucocorticoid prescriptions, 14% had an osteoporosis diagnosis, 3% had an osteoporotic fracture, 51% received a prescription for calcium/vitamin D, 43% had bone mineral density screening orders, 20% received a spine radiograph order, 29% had a documented T-score, 12% received a prescription for osteoporosis medication, and 6% had a documented osteoporosis screening. We were able to identify data elements in the EHR for all nine components of the osteoporosis management quality indicator. CONCLUSIONS: It is possible to identify data in the EHR for all attributes of the quality indicator for osteoporosis in lupus patients who receive chronic high-dose glucocorticoids. However, missing data and need to extract data from text-based notes may make development of population management tools challenging.

Detecting the presence of an indwelling urinary catheter and urinary symptoms in hospitalized patients using natural language processing.

OBJECTIVE: To develop a natural language processing pipeline to extract positively asserted concepts related to the presence of an indwelling urinary catheter in hospitalized patients from the free text of the electronic medical note. The goal is to assist infection preventionists and other healthcare professionals in determining whether a patient has an indwelling urinary catheter when a catheter-associated urinary tract infection is suspected. Currently, data on indwelling urinary catheters is not consistently captured in the electronic medical record in structured format and thus cannot be reliably extracted for clinical and research purposes. MATERIALS AND METHODS: We developed a lexicon of terms related to indwelling urinary catheters and urinary symptoms based on domain knowledge, prior experience in the field, and review of medical notes. A reference standard of 1595 randomly selected documents from inpatient admissions was annotated by human reviewers to identify all positively and negatively asserted concepts related to indwelling urinary catheters. We trained a natural language processing pipeline based on the V3NLP framework using 1050 documents and tested on 545 documents to determine agreement with the human reference standard. Metrics reported are positive predictive value and recall. RESULTS: The lexicon contained 590 terms related to the presence of an indwelling urinary catheter in various categories including insertion, care, change, and removal of urinary catheters and 67 terms for urinary symptoms. Nursing notes were the most frequent inpatient note titles in the reference standard document corpus; these also yielded the highest number of positively asserted concepts with respect to urinary catheters. Comparing the performance of the natural language processing pipeline against the human reference standard, the overall recall was 75% and positive predictive value was 99% on the training set; on the testing set, the recall was 72% and positive predictive value was 98%. The performance on extracting urinary symptoms (including fever) was high with recall and precision greater than 90%. CONCLUSIONS: We have shown that it is possible to identify the presence of an indwelling urinary catheter and urinary symptoms from the free text of electronic medical notes from inpatients using natural language processing. These are two key steps in developing automated protocols to assist humans in large-scale review of patient charts for catheter-associated urinary tract infection. The challenges associated with extracting indwelling urinary catheter-related concepts also inform the design of electronic medical record templates to reliably and consistently capture data on indwelling urinary catheters.

Investigating the nucleic acid interactions and antimicrobial mechanism of buforin II.

Buforin II (BF2) is an antimicrobial peptide that is hypothesized to kill bacteria by entering cells and binding nucleic acids. To further investigate this proposed mechanism, we used computer modeling and experimental measurements to consider the interactions between BF2 and DNA. Computational and experimental results imply that the peptide forms specific interactions with DNA. Moreover, we observe a general correlation between DNA affinity and antimicrobial activity for a series of BF2 variants. Thus, our results support the proposed mechanism for BF2 and provide a useful approach for evaluating the nucleic acid interactions of other antimicrobial peptides.

A putative coiled-coil domain of prohibitin is sufficient to repress E2F1-mediated transcription and induce apoptosis.

Prohibitin is a potential tumor suppressor protein that can repress E2F-mediated transcription and arrest cell proliferation. We had shown previously that prohibitin could bind to the Rb protein as well as E2F and this binding was necessary to suppress cell proliferation. Here we show that the E2F1 binding domain of prohibitin has the potential to fold into a coiled-coil structure. This coiled-coil domain by itself could physically interact with E2F1 and block its transcriptional activity. Like full-length prohibitin, the coiled-coil domain also recruited histone deacetylase 1 to repress E2F1. The coiled-coil domain also exhibited growth suppressive properties and we observed a 64% reduction in colony numbers when transfected into T47D cells. Interestingly, a synthetic peptide corresponding to the coiled-coil domain induced apoptosis in four different human cell lines. It is possible that agents that can mimic this peptide would be of value in controlling proliferative disorders.