Development and Validation of a Natural Language Processing Algorithm to Extract Descriptors of Microbial Keratitis From the Electronic Health Record

PURPOSE: The purpose of this article was to develop and validate a natural language processing (NLP) algorithm to extract qualitative descriptors of microbial keratitis (MK) from electronic health records. METHODS: In this retrospective cohort study, patients with MK diagnoses from 2 academic centers were identified using electronic health records. An NLP algorithm was created to extract MK centrality, depth, and thinning. A random sample of patient with MK encounters were used to train the algorithm (400 encounters of 100 patients) and compared with expert chart review. The algorithm was evaluated in internal (n = 100) and external validation data sets (n = 59) in comparison with masked chart review. Outcomes were sensitivity and specificity of the NLP algorithm to extract qualitative MK features as compared with masked chart review performed by an ophthalmologist. RESULTS: Across data sets, gold-standard chart review found centrality was documented in 64.0% to 79.3% of charts, depth in 15.0% to 20.3%, and thinning in 25.4% to 31.3%. Compared with chart review, the NLP algorithm had a sensitivity of 80.3%, 50.0%, and 66.7% for identifying central MK, 85.4%, 66.7%, and 100% for deep MK, and 100.0%, 95.2%, and 100% for thin MK, in the training, internal, and external validation samples, respectively. Specificity was 41.1%, 38.6%, and 46.2% for centrality, 100%, 83.3%, and 71.4% for depth, and 93.3%, 100%, and was not applicable (n = 0) to the external data for thinning, in the samples, respectively. CONCLUSIONS: MK features are not documented consistently showing a lack of standardization in recording MK examination elements. NLP shows promise but will be limited if the available clinical data are missing from the chart

Ocular Findings Aid in Diagnosis of West Nile Virus

INTRODUCTION: West Nile virus disease, which is endemic to the United States, is a rarely reported systemic infection that can be difficult to diagnose. Chorioretinitis is an uncommon manifestation of West Nile virus but has pathognomonic ocular findings that can aid in diagnosis. CASE PRESENTATION: A 66-year-old man presented with acute onset fever, chills, and dyspnea. He underwent an extensive but nondiagnostic workup during hospitalization. New visual complaints prompted ophthalmology consultation. Funduscopic examination showed macular hemorrhages and midperipheral chorioretinal lesions. Fluorescein angiography revealed target-like lesions in a radial distribution, which is pathognomonic for West Nile virus chorioretinitis. Serology confirmed the diagnosis of West Nile virus disease. Systemic and ocular symptoms improved with supportive care. DISCUSSION: West Nile virus disease has many nonspecific manifestations. History of recent mosquito exposure is not always readily elicited. In patients with visual symptoms, eye examination can help in its diagnosis. CONCLUSIONS: West Nile virus should be considered in patients with acute febrile or neurological illness during mosquito season

Daily Minutes of Unprotected Sun Exposure (MUSE) Inventory: Measure description and comparisons to UVR sensor and sun protection survey data

One in five US adults will be diagnosed with skin cancer. As most skin cancers are attributable to sun exposure, this risk factor is an important target for research and intervention. Most sun exposure measures assess frequency of specific sun-protection behaviors, which does not account for the use of multiple, potentially overlapping sun-protection methods. In contrast, the Daily Minutes of Unprotected Sun Exposure (MUSE) Inventory assesses sun-protection behavior during self-reported activities, providing several useful metrics, including duration of unprotected sun exposure on 17 body sites, combined to yield an overall MUSE score weighted by percent of body exposed. The present study was conducted July–September 2017, in Chicago, IL USA. For 10 days, participants (39 melanoma survivors; Mage = 58.59, 64.5% female) wore an ultraviolet radiation (UVR) sensor and completed the Daily MUSE Inventory each evening. The Sun Habits Survey was completed at the end of the study. Outdoor time reported in the MUSE Inventory significantly predicted outdoor time recorded by UVR sensors, B = 0.53, p < .001. For all sun-protection behaviors except shade, reports from the Daily MUSE Inventory (i.e., percentage of outdoor time a particular strategy was used) correlated with frequency ratings of the same strategy from the Sun Habits Survey (rs = 0.66–0.75, p < .05). In sum, the Daily MUSE Inventory corresponds with sensor and survey data, and provides a novel metric of unprotected sun exposure that will be useful for evaluating overall extent of sun exposure, including exposure on several smaller body sites that are at high risk for skin cancer. Keywords: Measurement, Sun protection, Concurrent validity, Self-report assessment, UVR, Skin cance