Hospital Readmission Rates in Patients With Neuromyelitis Optica Spectrum Disorder.

BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is an aggressive central nervous system astrocytopathy often resulting in rapid neurologic decline. Patients have recurrent flares that require immunomodulatory therapy for relapse prevention. These patients are usually hospitalized and may need rehospitalization after decline. Hospital readmission rates are important indicators that can be used to gauge health care quality and have direct implications on hospital compensation. This study aims to identify high-risk characteristics of patients with NMOSD that can be used to predict hospital readmissions. METHODS: The 2017 Nationwide Readmissions Database was searched for hospital admissions for NMOSD in the United States. All patients with hospital readmission within 30 days of discharge from the index hospitalization were included. RESULTS: The 30-day all-cause readmission rate for NMOSD was 11.9% (95% CI, 10.6%-13.3%). Patients aged 65 to 74 years had higher odds of readmission; those with private insurance had decreased odds. Sex did not affect readmission. Several comorbidities, such as respiratory failure, peripheral vascular disease, neurocognitive disorders, and neurologic blindness, were predictive of readmissions. Plasma exchange increased the odds of readmission, whereas intravenous immunoglobulin and immunomodulatory infusions, such as chemotherapies and monoclonal antibodies, did not affect readmission. CONCLUSIONS: The most common etiologies for 30-day read-mission were neurologic, infectious, and respiratory. Treatment targeted toward these etiologies may result in reduced overall readmission, thereby decreasing overall disease burden.

All-cause unplanned readmissions in the United States: insights from the Nationwide Readmission Database.

BACKGROUND: There are few studies looking into adult, all-cause and age-group-specific unplanned readmissions. The predictors of such unplanned readmissions for all inpatient encounters remain obscure. AIMS: To describe the incidence and factors associated with unplanned readmissions in all inpatient encounters in the United States. METHODS: The US Nationwide Readmission Database (NRD) is a representative sample of hospitalisations in the United States (from approximately 28 states) accounting for approximately 60% of the US population. All inpatient encounters during January-November 2017 in the NRD were evaluated for the rates, predictors and costs of unplanned 30 days readmissions for age groups 18-44 years, 45-64 years, 65-75 years and ≥75 years. Elective readmissions and those patients who died on their index hospitalisations were excluded. Weighted analysis was performed to obtain nationally representative data. RESULTS: We identified 28 942 224 inpatient encounters with a total of 3 051 189 (10.5%) unplanned readmissions within 30 days. The age groups 18-44 years, 45-64 years, 65-74 years and ≥75 years had 7.0%, 12.0%, 11.7% and 12.3% readmissions respectively. Female gender, private insurance and elective admissions were negative predictors for readmissions. For the group aged 18-44 years, schizophrenia and diabetes mellitus complications were the most frequent primary diagnosis for readmissions, while in all older age groups septicaemia and heart failure were the most frequent primary diagnosis for readmissions. CONCLUSIONS: Thirty-day unplanned readmissions are common in patients over age 45 years, leading to significant morbidity. Effective strategies for reducing unplanned readmission may help to improve quality of care, outcomes and higher value care.

Readmissions in patients with cerebral cavernous malformations: a national readmission database study.

BACKGROUND: Cerebral cavernous malformations (CCMs) are microvascular CNS lesions prone to hemorrhage leading to neurological sequela such as stroke and seizure. A subset of CCM patients have aggressive disease leading to multiple bleeding events, likely resulting multiple hospitalizations. Hospital admission rates are an important metric that has direct financial impact on hospitals and an indicator of overall disease burden. Furthermore, analysis of hospital readmissions can lead to early identification of high-risk patients and provides insight into the pathogenesis of CCM lesions. The purpose of this study is to identify high risk CCM patients with increased all cause readmission and comorbidities associated with increased readmissions. METHODS: All US hospital admissions due to CCMs were searched using the 2017 National Readmission Database (NRD). Patients with readmissions within 30 days of discharge from index hospitalization were identified and analyzed, relative to the remaining population. RESULTS: Among all patients hospitalized for CCM, 14.9% (13.7-16.2%) required all cause readmission within 30 days. Multivariate logistical regression analysis showed that substance abuse (P=0.003), diabetes (P=0.018), gastrointestinal bleed (P=0.002), renal failure (P=0.027), and coronary artery disease (P=0.010) were predictive of all cause readmissions, while age group 65-74 (P=0.042), private insurance (P<0.001), and treatment at a metropolitan teaching institution (P=0.039) were protective. Approximately half of all readmissions are caused by neurological (33.9%) and infectious (14.6%) etiologies. The 30-day lesion bleeding rate after index hospitalization is 0.8% (0.5-1.2%). CONCLUSIONS: All identified comorbidities associated with increased risks of readmission contribute to vascular stress, suggesting its role in lesion pathogenesis. This is the first and only study to analyze readmission metrics for CCMs in order to identify high risk patient factors to date.

Potential Cardiac Tamponade Development Secondary to SARS-CoV-2 Infection.

Upon initial discovery in late 2019, severe acute respiratory syndrome coronavirus 2, SARS-CoV-2, has managed to spread across the planet. A plethora of symptoms affecting multiple organ systems have been described, with the most common being nonspecific upper respiratory symptoms: cough, dyspnea, and wheezing. However, the cardiovascular system is also at risk following COVID-19 infection. Numerous cardiovascular complications have been reported by physicians globally, in particular cardiac tamponade Physicians must hold a high index of suspicion in identifying and treating patients with cardiac tamponade who may have contracted the novel coronavirus. This review will describe the current epidemiology and pathophysiology of SARS-CoV-2 and cardiac tamponade, highlighting their clinical course progression and the implications it may have for the severity of both illnesses. The paper will also review published case reports of cardiac tamponade, clinical presentation, and treatment of this complication, as well as the disease as a whole.

Readmission Rates in Patients With Multiple Sclerosis: A Nationwide Cohort Study.

BACKGROUND: Multiple sclerosis (MS) is an inflammatory central nervous system demyelinating disorder resulting in neurologic decline. Patients predominantly have a relapsing and remitting disease course requiring multiple hospitalizations and, occasionally, rehospitalizations. Hospitalization readmission rates are important metrics that have direct financial implications for hospitals and serve as an indicator of disease burden on patients and society. We sought to analyze hospital readmissions of patients with MS and identify the subsequent predictive characteristics/comorbidities for readmission. METHODS: All hospital admissions due to MS were queried using the 2017 Nationwide Readmissions Database. All patients with nonelective rehospitalization within 30 days of discharge were examined. RESULTS: The 30-day readmission rate for MS is 10.6% (range, 10.4%-10.8%). Female sex has a protective role in readmission rates, and age has no effect. Comorbidities, including heart failure, acute kidney injury, chronic obstructive pulmonary disease, chronic kidney disease, respiratory failure, substance abuse, diabetes, hypertension, peripheral artery disease, liver failure, anemia, coagulation disorders, cancer, depression, and infections, are predictive of readmissions, whereas sleep apnea is protective. No effect is seen with neurologic blindness, plasma exchange, or intravenous immunoglobulin treatment. CONCLUSIONS: Several medical comorbidities are predictive of hospital readmission of patients with MS. Most rehospitalizations are due to infectious and neurologic etiologies; thus, targeted interventions may lead to lower readmission rates.

Risk Factors, Trends, and Preventive Measures for 30-Day Unplanned Diabetic Ketoacidosis Readmissions in the Pediatric Population.

Background There has been a steady rise in types 1 and 2 diabetes mellitus among the youth in the USA from 2001 to 2017. Diabetic ketoacidosis (DKA) is a common and preventable presentation of both types of diabetes mellitus. According to the Centers for Disease Control and Prevention's (CDC) United States Diabetes Surveillance System, during 2004-2019 an increase in DKA hospitalization rates by 59.4% was noted, with people aged less than 45 years having the highest rates. Readmissions reflect the quality of disease management, which is integrally tied to care coordination and communication with the patient and their families. This study analyzes the trends and risk factors contributing to 30-day unplanned DKA readmissions in the pediatric age group and looks into possible preventive measures to decrease them. Methods A retrospective study was performed using the National Readmission Database (NRD) from January 1, 2017, to December 1, 2017. Pediatric patients aged 18 years and younger with the primary diagnosis of DKA were included using the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code E10.10. All statistical analysis was performed using IBM SPSS Statistics for Windows, version 1.0.0.1327 (IBM Corp., Armonk, NY, USA). Pearson's chi-square test was used for categorical variables and Mann-Whitney U test was used for continuous variables. To independently determine the predictors of readmission within each clinical variable, multiple logistic regressions with values presented as odds ratios (OR) with 95% confidence intervals (CI) were performed. Results A weighted total of 19,519 DKA-related pediatric index admissions were identified from the 2017 NRD. Of these pediatric patients, 831 (4.3%) had 30-day DKA readmission. The median age of a child for readmission was 16 years with an interquartile range of 0 to 18 years. A sharp rise in 30-day DKA readmissions was noted for ages 16 years and over. Females in the 0-25th percentile median household income category, with Medicaid covered, large metropolitan areas with at least 1 million residents, and metropolitan teaching hospitals were found to have a statistically significant higher percentage of readmissions. The mean length of stay for those who had a DKA readmission was 2.06 days, with a standard deviation of 1.84 days. The mean hospital charges for those who had a DKA readmission were $ 20,339.70. The 30-day DKA readmission odds were seen to be increased for female patients, Medicaid-insured patients, admissions at metropolitan non-teaching hospitals, and children from 0-25th percentile median household income category. Conclusion There has not been much of a change in the trend and risk factors contributing to the 30-day unplanned DKA readmissions over the years despite the steady rise in cases of diabetes mellitus. The length of stay for those who did not get readmitted within 30 days was longer than for those who did. This could reflect more comprehensive care and discharge planning that may have prevented them from readmission. Diabetes mellitus is a chronic disease that demands a team effort from the patient, family, healthcare personnel, insurance companies, and lawmakers. There is scope for a lot of improvement with the way our patients are being managed, and a more holistic approach needs to be devised.

Treatment of Inferior Vena Cava Thrombosis by Endovascular Stenting: A Case Report.

Optimal treatment of inferior vena cava (IVC) thrombosis remains unclear, especially given the contraindications to anticoagulation use and because interventional options remain limited. We present a case of a 62-year-old man with advanced liver cirrhosis who developed IVC thrombosis with symptoms of severe abdominal pain and leg swelling. IVC flow was restored via successful recanalization with a transjugular and common femoral approach after deploying a 22 × 70 mm Wallstent. On follow-up, the patient had a resolution of his symptoms.

Demographics and Risk Factors of Pediatric Pulmonary Hypertension Readmissions.

BACKGROUND AND OBJECTIVES: Pulmonary hypertension (PH) leads to significant morbidity and mortality in pediatric patients and increases the readmission rates for hospitalizations. This study evaluates the risk factors and comorbidities associated with an increase in 30-day readmissions among pediatric PH patients. METHODS: National Readmission Database (NRD) 2017 was searched for patients less than 18 years of age who were diagnosed with PH based on the International Classification of Diseases, 10th Revision (ICD-10). Statistical Package for the Social Sciences (SPSS) software v25.0 (IBM Corp., Armonk, NY) was used for statistical analysis. RESULTS: Of 5.52 million pediatric encounters, 10,501 patients met the selection criteria. The 30-day readmission rate of 14.43% (p < 0.001) was higher than hospitalizations from other causes {Odds Ratio (OR) 4.02 (3.84-4.20), p < 0.001}. The comorbidities of sepsis {OR 0.75 (0.64-0.89), p < 0.02} and respiratory infections {OR 0.75 (0.67-0.85), p < 0.001} were observed to be associated with lower 30-day readmissions. Patients who required invasive mechanical ventilation via endotracheal tube {OR 1.66 (1.4-1.96), p < 0.001} or tracheostomy tube {OR 1.35 (1.15-1.6), p < 0.001} had increased unplanned readmissions. Patients with higher severity of illness based on All Patients Refined Diagnosis Related Groups (APR-DRG) were more likely to get readmitted {OR 7.66 (3.13-18.76), p < 0.001}. CONCLUSION: PH was associated with increased readmission rates compared to the other pediatric diagnoses, but the readmission rate in this study was lower than one previous pediatric study. Invasive mechanical ventilation, Medicaid insurance, higher severity of illness, and female gender were associated with a higher likelihood of readmission within 30 days.

Assessment of independent clinical predictors of early readmission after percutaneous endoluminal left atrial appendage closure with the Watchman device using National Readmission Database.

BACKGROUND: Percutaneous endoluminal left atrial appendage closure (pLAAC) procedure has been used to prevent strokes in patients who are not eligible for long-term prophylactic anticoagulation. Since its approval, multiple studies have looked at its efficacy with comparable outcomes to anticoagulation, the current standard of care. OBJECTIVES: To assess the readmission rate and determine the factors associated with readmission after the endocardial pLAAC procedure using the Watchman device. METHODS: Data was obtained from the National Readmission Database (NRD), and we used SPSS software to determine statistically significant clinical predictors affecting readmission after implantation of the Watchman device at 30 days. RESULTS: The rate of readmission was found to be 9.2%. The true median cost of index hospitalization for the total population in the study was found to be [median (interquartile range = IQR), p] USD 24594 (USD 18883-31,041), whereas the true median cost of admission for those who were getting readmitted after 30 days was [median (IQR)] USD 7699 (USD 4955-14,243). Multivariate analysis of all clinically relevant predictors showed adjusted ratio for [adjusted odds ratio (OR), 95% confidence interval (95% CI), p-value] female genders (1.288, 1.104-1.503, p = 0.001), discharge to home health care (6.155, 1.509-25.096, p = 0.01), chronic kidney disease (CKD) (1.847,1.511-2.258, p < 0.001), chronic lung disease (1.419, 1.194-1.686, p < 0.001), heart failure (1.280, 1.040-1.574, p = 0.02), pericardial disorders (1.485, 1.011-2.179, p = 0.04), fluid and electrolyte disorders (1.456,1.050-2.018, p = 0.02) in those who were getting readmitted at 30-days compared to those who were not readmitted. The median length of stay for the index hospitalization was found to be one day, whereas the median length of stay at the 30-day readmission was reported to be [Median (IQR)] 4 days (2-6 days). Major cardiac reasons for readmission were heart failure, arrhythmias, and pericardial disorders. CONCLUSION: Our study aims to assess 30-day outcomes in the US population after pLAAC using a Watchman device. Our analysis showed that one in ten patients were getting readmitted. In addition, chronic kidney disease, chronic obstructive pulmonary disease, heart failure, and pericardial disorders were associated with higher readmission rates. These findings will help us assess clinical correlations and predict which patients are more at risk of readmission after a Watchman procedure.

Predictors of 30-Day Unplanned Readmission After Carotid Artery Stenting Using Artificial Intelligence.

INTRODUCTION: This study aimed to describe the rates and causes of unplanned readmissions within 30 days following carotid artery stenting (CAS) and to use artificial intelligence machine learning analysis for creating a prediction model for short-term readmissions. The prediction of unplanned readmissions after index CAS remains challenging. There is a need to leverage deep machine learning algorithms in order to develop robust prediction tools for early readmissions. METHODS: Patients undergoing inpatient CAS during the year 2017 in the US Nationwide Readmission Database (NRD) were evaluated for the rates, predictors, and costs of unplanned 30-day readmission. Logistic regression, support vector machine (SVM), deep neural network (DNN), random forest, and decision tree models were evaluated to generate a robust prediction model. RESULTS: We identified 16,745 patients who underwent CAS, of whom 7.4% were readmitted within 30 days. Depression [p < 0.001, OR 1.461 (95% CI 1.231-1.735)], heart failure [p < 0.001, OR 1.619 (95% CI 1.363-1.922)], cancer [p < 0.001, OR 1.631 (95% CI 1.286-2.068)], in-hospital bleeding [p = 0.039, OR 1.641 (95% CI 1.026-2.626)], and coagulation disorders [p = 0.007, OR 1.412 (95% CI 1.100-1.813)] were the strongest predictors of readmission. The artificial intelligence machine learning DNN prediction model has a C-statistic value of 0.79 (validation 0.73) in predicting the patients who might have all-cause unplanned readmission within 30 days of the index CAS discharge. CONCLUSIONS: Machine learning derived models may effectively identify high-risk patients for intervention strategies that may reduce unplanned readmissions post carotid artery stenting. CENTRAL ILLUSTRATION: Figure 2: ROC and AUPRC analysis of DNN prediction model with other classification models on 30-day readmission data for CAS subjects.

We present a novel deep neural network-based artificial intelligence prediction model to help identify a subgroup of patients undergoing carotid artery stenting who are at risk for short-term unplanned readmissions. Prior studies have attempted to develop prediction models but have used mainly logistic regression models and have low prediction ability. The novel model presented in this study boasts 79% capability to accurately predict individuals for unplanned readmissions post carotid artery stenting within 30 days of discharge.

Age- and Diagnosis-Based Trends for Unplanned Pediatric Rehospitalizations in the United States.

BACKGROUND AND OBJECTIVES: Hospital readmission rate helps to highlight the effectiveness of post-discharge care. There remains a paucity of plausible age-based categorization especially for ages below one year for hospital readmission rates. METHODS: Data from the 2017 Healthcare Cost and Utilization Project National Readmissions Database was analyzed for ages 0-18 years. Logistic regression analysis was performed to identify predictors for unplanned early readmissions.  Results: We identified 5,529,389 inpatient pediatric encounters which were further divided into age group cohorts. The overall rate of readmissions was identified at 3.2%. Beyond infancy, the readmission rate was found to be 6.7%. Across all age groups, the major predictors of unplanned readmission were cancers, diseases affecting transplant recipients and sickle cell patients. It was determined that reflux, milk protein allergy, hepatitis and inflammatory bowel diseases were significant diagnoses leading to readmission. Anxiety, depression and suicidal ideation depicted higher readmission rates in those older than 13 years. Across ages one to four years, dehydration, asthma and bronchiolitis were negative predictors of unplanned readmission.  Conclusions: Thirty-day unplanned readmissions remain a problem leading to billions of taxpayer dollars lost per annum. Effective strategies for mandatory outpatient follow-up may help the financial aspect of care while also enhancing the quality of care.

Prediction of the number of COVID-19 confirmed cases based on K-means-LSTM.

COVID-19 is a pandemic disease that began to rapidly spread in the US, with the first case detected on January 19, 2020, in Washington State. March 9, 2020, and then quickly increased with total cases of 25,739 as of April 20, 2020. Although most people with coronavirus 81%, according to the U.S. Centers for Disease Control and Prevention (CDC), will have little to mild symptoms, others may rely on a ventilator to breathe or not at all. SEIR models have broad applicability in predicting the outcome of the population with a variety of diseases. However, many researchers use these models without validating the necessary hypotheses. Far too many researchers often "overfit" the data by using too many predictor variables and small sample sizes to create models. Models thus developed are unlikely to stand validity check on a separate group of population and regions. The researcher remains unaware that overfitting has occurred, without attempting such validation. In the paper, we present a combination algorithm that combines similar days features selection based on the region using Xgboost, K-Means, and long short-term memory (LSTM) neural networks to construct a prediction model (i.e., K-Means-LSTM) for short-term COVID-19 cases forecasting in Louisana state USA. The weighted k-means algorithm based on extreme gradient boosting is used to evaluate the similarity between the forecasts and past days. The results show that the method with K-Means-LSTM has a higher accuracy with an RMSE of 601.20 whereas the SEIR model with an RMSE of 3615.83.

Early vs Late Discharge in Low-Risk ST-Elevation Myocardial Infarction Patients Treated With Percutaneous Coronary Intervention: A Systematic Review and Meta-Analysis.

BACKGROUND: For low-risk patients with ST-elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention (PCI) the recommended optimal discharge timing is inconsistent in guidelines. The European Society of Cardiology guidelines recommend early discharge within 48-72 h, while the American College of Cardiology guidelines do not recommend a specific discharge strategy. In this systematic review and meta-analysis we compared outcomes with early discharge (≤3 days) versus late discharge (>3 days). METHODS: Randomized controlled trials (RCTs) and observational studies were selected after searching MEDLINE and EMBASE database. Meta-analysis was stratified according to study design. Outcomes were reported as random effects risk ratios (RR) with 95% confidence intervals. RESULTS: Seven RCTs comprising 1780 patients and 4 observational studies comprising 39,288 patients were selected. The RCT-restricted analysis did not demonstrate significant differences in terms of all-cause mortality (RR, 0.97 [0.23-4.05]) and major adverse cardiac events (MACE) (RR, 0.84 [0.56-1.26]). Conversely, observational study restricted analysis showed that early vs late discharge strategy was associated with a reduction in all-cause mortality (RR, 0.40 [0.23-0.71]) and MACE (RR, 0.45 [0.26-0.78]). There were no significant differences in hospital readmissions between early vs late discharge in both RCT or observational study analyses. CONCLUSIONS: Early discharge strategy in appropriately selected low-risk patients with STEMI undergoing PCI is safe and it has the potential to improve cost of care.

Refractory Angina: the Current State of Mechanical Therapies.

PURPOSE OF REVIEW: Refractory angina (RA), which is characterized by tissue ischemia along with neurological, mitochondrial, and psychogenic dysfunction, is becoming a major cause of morbidity in patients with advanced coronary artery disease. In this review, we discuss in detail the invasive mechanical non-cell therapy-based options, the evidence behind these therapies, and future trends. RECENT FINDINGS: There is extensive ongoing research in the areas of spinal-cord stimulation, transmyocardial laser revascularization, sympathectomy, angiogenesis, and other non-cell-based therapies to explore the best therapy for refractory angina. There is conflicting data in the literature suggesting subjective improvement in angina, but very few studies boast improvement in core objective parameters such as myocardial blood flow, survival, or rehospitalizations. Patients with refractory angina are a complex group of patients that need novel approaches to help alleviate their symptoms and reduce mortality. A carefully selected sequence of therapies may provide the best results in this patient population.

Trends in authorship based on gender and nationality in published neuroscience literature.

OBJECTIVE: To evaluate the disparity in authorship based on gender and nationality of institutional affiliation among journals from developed and developing countries. MATERIALS AND METHODS: Original articles from two neuroscience journals, with a 5 year impact factor >15 (Neuron and Nature Neuroscience) and from two neurology journals from a developing country (Neurology India and Annals of Indian Academy of Neurology) were categorized by gender and institutional affiliation of first and senior authors. Articles were further divided by the type of research (basic/translational/clinical), study/target population (adult/pediatrics/both) and field of neurology. Data was collected for the years 2002 and 2012. RESULTS: There are large disparities in authorship by women and from developing countries in high impact factor neuroscience journals. However, there was a non-statistical rise in female first and senior authorship over a 10 year period. Additionally there was a significant increase in first authorship from institutions based in developing countries in the two neuroscience journals examined (P < 0.05). In the two neurology journals based in India there was a significant increase in the number of articles published by international investigators between 2002 and 2012 (P < 0.05). CONCLUSIONS: Over the last decade, there has been a non-statistical increase in proportion of female first and senior authors, and a significant increase in authors from developing countries in high impact factor neuroscience journals. However they continue to constitute a minority. The disparity in authorship based on gender also exists in neurology journals based in a developing country (India).

Smart phone applications as a source of information on stroke.

BACKGROUND AND PURPOSE: Smartphone applications have been increasingly identified as a novel platform for dissemination of healthcare related information. However, there have been no studies done to evaluate the availability and content of stroke related apps. PURPOSE: This study aims to identify and analyze stroke-related applications available on the Apple iTunes and Android Google Play Store. METHODS: The Apple iTunes store and Android Google Play Store were searched for stroke-related applications on July 27, 2013 using keywords: stroke, brain attack, intracranial hemorrhage, subarachnoid hemorrhage, cerebral infarction. The content of the applications was analyzed by two independent investigators. RESULTS: A total of 93 relevant applications (46.2% android and 53.8% iPhone) were identified of which 47.3% were available free of cost. 92% of apps were identified as useful by users and over 60% had scientifically valid information. There is a significant participation of healthcare agencies in dissemination of stroke related information through apps with 47.3% apps being uploaded by them. Over half of all stroke related apps were aimed towards health care workers (51.6%), 75% of which could be utilized as bedside tools for patient care and remainder had information related to recent research advances. The difference in scientific validity between the apps aimed at general population versus healthcare professionals was statistically significant (P<0.01). There was no statistical association between cost of app and scientific validity or usefulness. CONCLUSIONS: Smartphone apps are a significant source of information related to stroke. An increasing participation of healthcare agencies should be encouraged to promote dissemination of scientifically valid information.

Analysis of YouTube as a source of information for West Nile Virus infection.

INTRODUCTION: A major outbreak of West Nile Virus was seen last year in different parts of the United States. Adequate dissemination of correct information about the disease would have helped decrease its spread and the associated panic in the general population. In this study, we looked into the use of YouTube as a resource for providing information about West Nile Virus infection. OBJECTIVE: This study aims to identify and evaluate YouTube as resource for providing information on West Nile Virus infection to the general public. METHODS: YouTube was searched on November 25, 2012, using the keywords West Nile Virus epidemic, West Nile Virus infection, and West Nile Virus prevention for videos uploaded in the past 6 months containing relevant information about the disease. The videos were classified as useful, misleading, or as news updates based on the type of information contained. Total viewership, number of days since upload, total duration of videos, and source of upload were noted. RESULTS: A total of 106 videos with information on West Nile Virus infection were included in the study, with 79.24% having useful information about the disease. Among the useful videos, 51/84 (60.71%) had information on disease prevention, and 29/84 (34.52%) contained information on news and research updates. The majority of these videos were uploaded by individuals (54.6%) or news agencies (41.8 %). Healthcare agencies contributed only 3.4 % of the total videos. Even though the useful videos represented 72% of all videos, there was significantly higher total viewership and viewership per day for the non-useful videos (P<0.05). CONCLUSIONS: YouTube may be a significant resource for dissemination of information on public health issues like West Nile virus infection and should be targeted by healthcare agencies for this use. The major drawback of this medium is lack of verification by authorized healthcare professionals before these videos are made available for viewing by the community. Hence, a strict caution should be exercised in obtaining the information from unauthorized videos posted on YouTube.