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BACKGROUND - Time to tumor recurrence may be associated with outcomes following resection of hepatobiliary cancers. The objective of the current study was to investigate risk factors and prognosis among patients with early versus late recurrence of hilar cholangiocarcinoma (HCCA) after curative-intent resection.
METHODS - A total of 225 patients who underwent curative-intent resection for HCCA were identified from 10 academic centers in the USA. Data on clinicopathologic characteristics, pre-, intra-, and postoperative details and overall survival (OS) were analyzed. The slope of the curves identified by linear regression was used to categorize recurrences as early versus late.
RESULTS - With a median follow-up of 18.0 months, 99 (44.0%) patients experienced a tumor recurrence. According to the slope of the curves identified by linear regression, the functions of the two straight lines were y = -0.465x + 16.99 and y = -0.12x + 7.16. The intercept value of the two lines was 28.5 months, and therefore, 30 months (2.5 years) was defined as the cutoff to differentiate early from late recurrence. Among 99 patients who experienced recurrence, the majority (n = 80, 80.8%) occurred within the first 2.5 years (early recurrence), while 19.2% of recurrences occurred beyond 2.5 years (late recurrence). Early recurrence was more likely present as distant disease (75.1% vs. 31.6%, p = 0.001) and was associated with a worse OS (Median OS, early 21.5 vs. late 50.4 months, p < 0.001). On multivariable analysis, poor tumor differentiation (HR 10.3, p = 0.021), microvascular invasion (HR 3.3, p = 0.037), perineural invasion (HR 3.9, p = 0.029), lymph node metastases (HR 5.0, p = 0.004), and microscopic positive margin (HR 3.5, p = 0.046) were independent risk factors associated with early recurrence.
CONCLUSIONS - Early recurrence of HCCA after curative resection was common (~35.6%). Early recurrence was strongly associated with aggressive tumor characteristics, increased risk of distant metastatic recurrence and a worse long-term survival.

PURPOSE - Data about maternal recall accuracy for classifying early pregnancy medication exposure are meager. Nonetheless, studies often rely on recall to evaluate potential impact of pharmaceuticals on the developing fetus.
METHODS - Right from the Start is a community-based pregnancy cohort that enrolled women from North Carolina, Tennessee, and Texas. A subset of 318 women participated in daily medication diaries initiated before conception (2006-2012). We examined nonsteroidal anti-inflammatory drugs (NSAIDs) as an example of a drug type that is difficult to study due to its intermittent and primarily over-the-counter use as well as its incomplete documentation in medical and pharmaceutical records. Selective serotonin reuptake inhibitors (SSRI) were assessed as a prescription medication comparator. Maternal recall of NSAID and SSRI use in early pregnancy was examined by comparing diary data (gold standard) to first-trimester interview.
RESULTS - Sensitivity and specificity for recall of NSAID exposure were 78.6% and 62.3%, respectively (kappa statistic: 0.41), with 72.3% agreement for exposure classification. Sensitivity and specificity for recall of SSRI exposure were 77.8% and 99.0%, respectively (kappa statistic: 0.79), with 97.8% agreement.
CONCLUSIONS - Our findings suggest the validity of maternal recall varies with medication type and prospective data collection should be prioritized when studying early pregnancy drug exposures.
Copyright © 2016 Elsevier Inc. All rights reserved.

OBJECTIVES - Registry-based clinical research in nephrolithiasis is critical to advancing quality in urinary stone disease management and ultimately reducing stone recurrence. A need exists to develop Health Insurance Portability and Accountability Act (HIPAA)-compliant registries that comprise integrated electronic health record (EHR) data using prospectively defined variables. An EHR-based standardized patient database-the Registry for Stones of the Kidney and Ureter (ReSKU™)-was developed, and herein we describe our implementation outcomes.
MATERIALS AND METHODS - Interviews with academic and community endourologists in the United States, Canada, China, and Japan identified demographic, intraoperative, and perioperative variables to populate our registry. Variables were incorporated into a HIPAA-compliant Research Electronic Data Capture database linked to text prompts and registration data within the Epic EHR platform. Specific data collection instruments supporting New patient, Surgery, Postoperative, and Follow-up clinical encounters were created within Epic to facilitate automated data extraction into ReSKU.
RESULTS - The number of variables within each instrument includes the following: New patient-60, Surgery-80, Postoperative-64, and Follow-up-64. With manual data entry, the mean times to complete each of the clinic-based instruments were (minutes) as follows: New patient-12.06 ± 2.30, Postoperative-7.18 ± 1.02, and Follow-up-8.10 ± 0.58. These times were significantly reduced with the use of ReSKU structured clinic note templates to the following: New patient-4.09 ± 1.73, Postoperative-1.41 ± 0.41, and Follow-up-0.79 ± 0.38. With automated data extraction from Epic, manual entry is obviated.
CONCLUSIONS - ReSKU is a longitudinal prospective nephrolithiasis registry that integrates EHR data, lowering the barriers to performing high quality clinical research and quality outcome assessments in urinary stone disease.

The process of scientific discovery is rapidly evolving. The funding climate has influenced a favorable shift in scientific discovery toward the use of existing resources such as the electronic health record. The electronic health record enables long-term outlooks on human health and disease, in conjunction with multidimensional phenotypes that include laboratory data, images, vital signs, and other clinical information. Initial work has confirmed the utility of the electronic health record for understanding mechanisms and patterns of variability in disease susceptibility, disease evolution, and drug responses. The addition of biobanks and genomic data to the information contained in the electronic health record has been demonstrated. The purpose of this statement is to discuss the current challenges in and the potential for merging electronic health record data and genomics for cardiovascular research.
© 2016 American Heart Association, Inc.

BACKGROUND - Biomedical research has traditionally been conducted via surveys and the analysis of medical records. However, these resources are limited in their content, such that non-traditional domains (eg, online forums and social media) have an opportunity to supplement the view of an individual's health.
OBJECTIVE - The objective of this study was to develop a scalable framework to detect personal health status mentions on Twitter and assess the extent to which such information is disclosed.
METHODS - We collected more than 250 million tweets via the Twitter streaming API over a 2-month period in 2014. The corpus was filtered down to approximately 250,000 tweets, stratified across 34 high-impact health issues, based on guidance from the Medical Expenditure Panel Survey. We created a labeled corpus of several thousand tweets via a survey, administered over Amazon Mechanical Turk, that documents when terms correspond to mentions of personal health issues or an alternative (eg, a metaphor). We engineered a scalable classifier for personal health mentions via feature selection and assessed its potential over the health issues. We further investigated the utility of the tweets by determining the extent to which Twitter users disclose personal health status.
RESULTS - Our investigation yielded several notable findings. First, we find that tweets from a small subset of the health issues can train a scalable classifier to detect health mentions. Specifically, training on 2000 tweets from four health issues (cancer, depression, hypertension, and leukemia) yielded a classifier with precision of 0.77 on all 34 health issues. Second, Twitter users disclosed personal health status for all health issues. Notably, personal health status was disclosed over 50% of the time for 11 out of 34 (33%) investigated health issues. Third, the disclosure rate was dependent on the health issue in a statistically significant manner (P<.001). For instance, more than 80% of the tweets about migraines (83/100) and allergies (85/100) communicated personal health status, while only around 10% of the tweets about obesity (13/100) and heart attack (12/100) did so. Fourth, the likelihood that people disclose their own versus other people's health status was dependent on health issue in a statistically significant manner as well (P<.001). For example, 69% (69/100) of the insomnia tweets disclosed the author's status, while only 1% (1/100) disclosed another person's status. By contrast, 1% (1/100) of the Down syndrome tweets disclosed the author's status, while 21% (21/100) disclosed another person's status.
CONCLUSIONS - It is possible to automatically detect personal health status mentions on Twitter in a scalable manner. These mentions correspond to the health issues of the Twitter users themselves, but also other individuals. Though this study did not investigate the veracity of such statements, we anticipate such information may be useful in supplementing traditional health-related sources for research purposes.

OBJECTIVE - To identify sources of general and mental health information for rural women to inform the development of public health nursing interventions that consider preferences for obtaining information.
DESIGN AND SAMPLE - One thousand women (mean age = 57 years; 96.9% White) living in primarily nonmetropolitan areas of Western Kentucky participated via a random-digit-dial survey.
MEASURES - Data were collected on demographics, sources of health information, depression, and stigma.
RESULTS - Most participants preferred anonymous versus interpersonal sources for both general (68.1%) and mental health (69.4%) information. All participants reported at least one source of general health information, but 20.8% indicated not seeking or not knowing where to seek mental health information. The Internet was the most preferred anonymous source. Few women cited health professionals as the primary information source for general (11.4%) or mental (9.9%) health. Public stigma was associated with preferring anonymous sources and not seeking information.
CONCLUSIONS - Public health nurses should understand the high utilization of anonymous sources, particularly for mental health information, and focus efforts on helping individuals to navigate resources to ensure they obtain accurate information about symptoms, effective treatments, and obtaining care. Reducing stigma should remain a central focus of prevention and education in rural areas.
© 2014 Wiley Periodicals, Inc.