COVID-19-Related Neuropsychiatric Symptoms in Patients With Alcohol Abuse Conditions During the SARS-CoV-2 Pandemic: A Retrospective Cohort Study Using Real World Data From Electronic Health Records of a Tertiary Hospital.

Patients with an alcohol abuse disorder exhibit several medical characteristics and social determinants, which suggest a greater vulnerability to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and a worse course of the coronavirus disease 2019 (COVID-19) once infected. During the first wave of the COVID-19, most of the countries have register an increase in alcohol consumption. However, studies on the impact of alcohol addiction on the risk of COVID-19 infection are very scarce and inconclusive. This research offers a descriptive observational retrospective cohort study using real world data obtained from the Electronic Health Records. We found that patients with a personal history of alcohol abuse were 8% more likely to extend their hospitalization length of stay for 1 day (95% CI = 1.04-1.12) and 15% more likely to extend their Intensive Care Unit (ICU) length of stay (95% CI = 1.01-1.30). They were also 5.47 times more at risk of needing an ICU admission (95% CI = 1.61-18.57) and 3.54 times (95% CI = 1.51-8.30) more at risk of needing a respirator. Regarding COVID-19 symptoms, patients with a personal history of alcohol abuse were 91% more likely of exhibiting dyspnea (95% CI = 1.03-3.55) and 3.15 times more at risk of showing at least one neuropsychiatric symptom (95% CI = 1.61-6.17). In addition, they showed statistically significant differences in the number of neuropsychiatric symptoms developed during the COVID-19 infection. Therefore, we strongly recommend to warn of the negative consequences of alcohol abuse over COVID-19 complications. For this purpose. Clinicians should systematically assess history of alcohol issues and drinking habits in all patients, especially for those who seek medical advice regarding COVID-19 infection, in order to predict its severity of symptoms and potential complications. Moreover, this information should be included, in a structured field, into the Electronic Health Record to facilitate the automatic extraction of data, in real time, useful to evaluate the decision-making process in a dynamic context.