BackgroundPsychiatric comorbidities in epilepsy impose significant burdens on patients and their families. It affects their quality of life and medical care and results in cost increases. This study reports the impact of various psychiatric comorbidities in epilepsy patients regarding hospital outcomes and in-hospital mortality.MethodsWe used the Nationwide Inpatient Sample (NIS) from the Healthcare Cost and Utilization Project (HCUP) from years 2013-2014. We identified epilepsy as the primary diagnosis and psychiatric comorbidities, namely, alcohol abuse, depression, drug abuse, and psychosis, using validated International Classification of Diseases, 9th Revision, Clinical Modification (ICD-­9-­CM) codes. The differences in comorbidities were quantified using chi-square (χ2) tests and the multinomial logistic regression model was used to quantify associations among comorbidities using the adjusted Odds Ratio (aOR). ResultsWe analyzed 397,440 hospitalizations with epilepsy as the primary diagnosis. The most prevalent psychiatric comorbidities present in epilepsy were depression (13%) followed by psychosis (10.4%). The risk of inpatient death was only seen in epilepsy with comorbid alcohol abuse (aOR 1.164; 95%CI 1.043 – 1.300; p-value =0.007). Epilepsy with comorbid depression (aOR 1.473; 95% CI 1.391 – 1.559; p-value <0.001) was associated with a higher risk of a length of stay of more than three days (median), followed by comorbid psychosis (aOR 1.290; 95% CI 1.258 – 1.322; p-value <0.001). Epilepsy with comorbid depression (aOR 1.242; 95% CI 1.172 – 1.317; p-value <0.001) was associated with a higher risk of inpatient total charge of more than $21,000 (median), followed by comorbid psychosis (aOR 1.071; 95% CI 1.045 – 1.098; p-value <0.001).ConclusionPsychiatric comorbidities are influential factors that must be considered in models of Health-Related Quality of Life (HRQOL) in epilepsy. Further, efforts to improve HRQOL and reduce the burden of epilepsy require greater emphasis on the early diagnosis and treatment of comorbid psychopathology.

The coronavirus disease 2019 (COVID-19) pandemic has resulted in nationwide stay-at-home orders in an effort to slow the spread severely impacting the healthcare sector. Telepsychiatry provides a platform bridging the gap through advanced technologies connecting mental health providers and patients who need their services, overcoming previous barriers of great distances, lack of transportation, and even time constraints. The most obvious benefit is increased accessibility to mental healthcare, especially in underserved and remote areas where there is no easy access for in-person care. It is important to note that benefits are not limited to patients, but also allow clinicians greater flexibility in scheduling and reduced practice overhead costs, both of which aid with physician burnout and burden. Telepsychiatry during COVID-19 provides its own unique advantages over in-person visits. The risk of exposure to healthcare workers and patients receiving care is reduced, allowing immunocompromised patients to receive muchneeded psychiatric care. Without the need to meet in person, self-isolating psychiatrists can still provide care, decreasing strain on their co-workers. Although telepsychiatry is relatively new, it has already exhibited considerable success in its effectiveness at treating psychiatric conditions and widespread corollary benefits. Telepsychiatric consults may be carried out synchronously and asynchronously, each having benefits and setbacks. Different mobile application interventions have been explored, which are available for the purpose of both monitoring/assessing patients and/or providing treatment. The scope of conditions these applications address is broad, from anxiety disorders to schizophrenia to depression. As promising and beneficial telepsychiatry may seem, it is necessary to recognize that building the program can be challenging. It involves adapting to new methods in medicine. We highlighted barriers to general telepsychiatry, the most prominent being technological literacy of both physician and patient, and possible negative effects of eliminating the in-person patient-doctor interaction.

Background Recent legalization of therapeutic and recreational cannabis use makes it imperative to have an insight into odds and trends in young-onset stroke-related hospitalizations among cannabis users (18–49 years). Methods The National Inpatient Sample dataset (2007–2014) was utilized to assess national trends, odds of young-onset stroke-related hospitalizations, and outcomes among cannabis users vs. nonusers using provided discharge weights, strata, and cluster design. The rates are described per 100,000 hospitalizations among cannabis users and non-users. Results A total of 3,307,310 hospitalizations were identified among young adults with current or previous cannabis use. Of these, 34,857 (1.1%) were related to young-onset stroke. A relative increase of 13.92% (553 in 2007 to 630 in 2014; ptrend < 0.001) in young-onset stroke admissions was reported among cannabis users. The odds of any stroke (OR 1.16, 95% CI 1.14–1.19, p < 0.001) and acute ischemic stroke (OR 1.41, 95% CI 1.31–1.51, p < 0.001) hospitalizations were considerably higher among cannabis users as compared to nonusers. In-hospital mortality rates were increasing (3.7% to 4.3%) among cannabis users whereas decreasing (7.7% to 5.9%) in nonusers from 2007 to 2014 ( ptrend < 0.001). The mean length of stay and the hospitalization charges showed increasing trends in cannabis-related young-onset stroke admissions. There was an increasing trend in young-onset stroke admissions among male cannabis users (578 to 701; ptrend < 0.001) but not among females (516 to 457; ptrend = 0.14). The maximum rise in the young-onset stroke-related admissions was seen in African Americans (743 to 996; ptrend < 0.001). Conclusions We identified rising trends and higher risk (16% higher of overall young-onset stroke, 41% higher of acute ischemic stroke) of stroke-related hospitalizations and worse outcomes among cannabis users aged 18–49 years from 2007 to 2014.