Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department

BACKGROUND: Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, emergency department encounters in order to deliver appropriate care and referrals. Unfortunately, falls are difficult to identify without manual chart review, a time intensive process infeasible for many applications including surveillance and quality reporting. Here we describe a pragmatic NLP approach to automating fall identification. METHODS: In this single center retrospective review, 500 emergency department provider notes from older adult patients (age 65 and older) were randomly selected for analysis. A simple, rules-based NLP algorithm for fall identification was developed and evaluated on a development set of 1084 notes, then compared with identification by consensus of trained abstractors blinded to NLP results. RESULTS: The NLP pipeline demonstrated a recall (sensitivity) of 95.8%, specificity of 97.4%, precision of 92.0%, and F1 score of 0.939 for identifying fall events within emergency physician visit notes, as compared to gold standard manual abstraction by human coders. CONCLUSIONS: Our pragmatic NLP algorithm was able to identify falls in ED notes with excellent precision and recall, comparable to that of more labor-intensive manual abstraction. This finding offers promise not just for improving research methods, but as a potential for identifying patients for targeted interventions, quality measure development and epidemiologic surveillance

Acute encephalitis syndrome surveillance, Kushinagar district, Uttar Pradesh, India, 2011-2012

In India, quality surveillance for acute encephalitis syndrome (AES), including laboratory testing, is necessary for understanding the epidemiology and etiology of AES, planning interventions, and developing policy. We reviewed AES surveillance data for January 2011-June 2012 from Kushinagar District, Uttar Pradesh, India. Data were cleaned, incidence was determined, and demographic characteristics of cases and data quality were analyzed. A total of 812 AES case records were identified, of which 23\% had illogical entries. AES incidence was highest among boys<6 years of age, and cases peaked during monsoon season. Records for laboratory results (available for Japanese encephalitis but not AES) and vaccination history were largely incomplete, so inferences about the epidemiology and etiology of AES could not be made. The low-quality AES/Japanese encephalitis surveillance data in this area provide little evidence to support development of prevention and control measures, estimate the effect of interventions, and avoid the waste of public health resources

Recruitment and Retention of Underrepresented Populations in Alzheimer’s Disease Research: A Systematic Review

Introduction: Alzheimer’s disease and related dementias (ADRD) disproportionately impact racial and ethnic minority and socioeconomically disadvantaged adults. Yet, these populations are significantly underrepresented in research. Methods: We systematically reviewed the literature for published reports describing recruitment and retention of individuals from underrepresented backgrounds in ADRD research or underrepresented participants’ perspectives regarding ADRD research participation. Relevant evidence was synthesized and evaluated for quality. Results: We identified 22 eligible studies. Seven studies focused on recruitment/retention approaches, all of which included multifaceted efforts and at least one community outreach component. There was considerable heterogeneity in approaches used, specific activities and strategies, outcome measurement, and conclusions regarding effectiveness. Despite limited use of prospective evaluation strategies, most authors reported improvements in diverse representation in ADRD cohorts. Studies evaluating participant views focused largely on predetermined explanations of participation including attitudes, barriers/facilitators, education, trust, and religiosity. Across all studies, the strength of evidence was low. Discussion: Overall, the quantity and quality of available evidence to inform best practices in recruitment, retention, and inclusion of underrepresented populations in ADRD research are low. Further efforts to systematically evaluate the success of existing and emergent approaches will require improved methodological standards and uniform measures for evaluating recruitment, participation, and inclusivity

A comparison of machine learning classifiers for pediatric epilepsy using resting-state functional MRI latency data

Epilepsy affects 1 in 150 children under the age of 10 and is the most common chronic pediatric neurological condition; poor seizure control can irreversibly disrupt normal brain development. The present study compared the ability of different machine learning algorithms trained with resting-state functional MRI (rfMRI) latency data to detect epilepsy. Preoperative rfMRI and anatomical MRI scans were obtained for 63 patients with epilepsy and 259 healthy controls. The normal distribution of latency z-scores from the epilepsy and healthy control cohorts were analyzed for overlap in 36 seed regions. In these seed regions, overlap between the study cohorts ranged from 0.44-0.58. Machine learning features were extracted from latency z-score maps using principal component analysis. Extreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), and Random Forest algorithms were trained with these features. Area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, specificity and F1-scores were used to evaluate model performance. The XGBoost model outperformed all other models with a test AUC of 0.79, accuracy of 74%, specificity of 73%, and a sensitivity of 77%. The Random Forest model performed comparably to XGBoost across multiple metrics, but it had a test sensitivity of 31%. The SVM model did not perform \u3e70% in any of the test metrics. The XGBoost model had the highest sensitivity and accuracy for the detection of epilepsy. Development of machine learning algorithms trained with rfMRI latency data could provide an adjunctive method for the diagnosis and evaluation of epilepsy with the goal of enabling timely and appropriate care for patients

Post-stroke inhibition of induced NADPH oxidase type 4 prevents oxidative stress and neurodegeneration

Ischemic stroke is the second leading cause of death worldwide. Only one moderately effective therapy exists, albeit with contraindications that exclude 90% of the patients. This medical need contrasts with a high failure rate of more than 1,000 pre-clinical drug candidates for stroke therapies. Thus, there is a need for translatable mechanisms of neuroprotection and more rigid thresholds of relevance in pre-clinical stroke models. One such candidate mechanism is oxidative stress. However, antioxidant approaches have failed in clinical trials, and the significant sources of oxidative stress in stroke are unknown. We here identify NADPH oxidase type 4 (NOX4) as a major source of oxidative stress and an effective therapeutic target in acute stroke. Upon ischemia, NOX4 was induced in human and mouse brain. Mice deficient in NOX4 (Nox4(-/-)) of either sex, but not those deficient for NOX1 or NOX2, were largely protected from oxidative stress, blood-brain-barrier leakage, and neuronal apoptosis, after both transient and permanent cerebral ischemia. This effect was independent of age, as elderly mice were equally protected. Restoration of oxidative stress reversed the stroke-protective phenotype in Nox4(-/-) mice. Application of the only validated low-molecular-weight pharmacological NADPH oxidase inhibitor, VAS2870, several hours after ischemia was as protective as deleting NOX4. The extent of neuroprotection was exceptional, resulting in significantly improved long-term neurological functions and reduced mortality. NOX4 therefore represents a major source of oxidative stress and novel class of drug target for stroke therapy

Policy of foreign direct investment liberalisation in India: implications for retail sector

This study has analysed the impact of liberalisation of Indian economy and FDI policy on the retail sector since its implementation in the 1990s. It also further analyses sub-categories by investigating its impact on the unorganised retail sector and the flow of FDI in single-brand retail and multi-brand retail sectors. A comprehensive and critical review of the existing evidence on the subject was carried out, and descriptive statistical analysis of data from 1991 to 2013 was performed which leads to conclude that the policy of FDI liberalisation has proved to provide diversification and sustainable development to the Indian economy and specifically retail sector which is considered to be one of the significant pillars of economy. Furthermore, for continuous growth of the economy, it seems vital to encourage more investment in other sectors by liberalising the restrictive policies

Discovery of common and rare genetic risk variants for colorectal cancer.

To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P < 5 × 10-8, bringing the number of known independent signals for CRC to ~100. New signals implicate lower-frequency variants, Krüppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.Goncalo R Abecasis has received compensation from 23andMe and Helix. He is currently an employee of Regeneron Pharmaceuticals. Heather Hampel performs collaborative research with Ambry Genetics, InVitae Genetics, and Myriad Genetic Laboratories, Inc., is on the scientific advisory board for InVitae Genetics and Genome Medical, and has stock in Genome Medical. Rachel Pearlman has participated in collaborative funded research with Myriad Genetics Laboratories and Invitae Genetics but has no financial competitive interest

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase&nbsp;1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation&nbsp;disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age&nbsp; 6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score&nbsp; 652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc&nbsp;= 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N&nbsp;= 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in&nbsp;Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in&nbsp;Asia&nbsp;and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

A Protocol for a Pan-Canadian Prospective Observational Study on Active Surveillance or Surgery for Very Low Risk Papillary Thyroid Cancer

BackgroundThe traditional management of papillary thyroid cancer (PTC) is thyroidectomy (total or partial removal of the thyroid). Active surveillance (AS) may be considered as an alternative option for small, low risk PTC. AS involves close follow-up (including regularly scheduled clinical and radiological assessments), with the intention of intervening with surgery for disease progression or patient preference.MethodsThis is a protocol for a prospective, observational, long-term follow-up multi-centre Canadian cohort study. Consenting eligible adults with small, low risk PTC (&lt; 2cm in maximal diameter, confined to the thyroid, and not immediately adjacent to critical structures in the neck) are offered the choice of AS or surgery for management of PTC. Patient participants are free to choose either option (AS or surgery) and the disease management course is thus not assigned by the investigators. Surgery is provided as usual care by a surgeon in an institution of the patient’s choice. Our primary objective is to determine the rate of ‘failure’ of disease management in respective AS and surgical arms as defined by: i) AS arm – surgery for progression of PTC, and ii) surgical arm - surgery or other treatment for disease persistence or progression after completing initial treatment. Secondary outcomes include long-term thyroid oncologic and treatment outcomes, as well as patient-reported outcomes.DiscussionThe results from this study will provide long-term clinical and patient reported outcome evidence regarding active surveillance or immediate surgery for management of small, low risk PTC. This will inform future clinical trials in disease management of small, low risk papillary thyroid cancer.Registration detailsThis prospective observational cohort study is registered on clinicaltrials.gov (NCT04624477), but it should not be considered a clinical trial as there is no assigned intervention and patients are free to choose either AS or surgery