Micronized/ultramicronized palmitoylethanolamide improves depression and fatigue in coronavirus disease 2019 (COVID-19) survivors.

Coronavirus disease 2019 (COVID-19) may lead to neuropsychiatric sequelae. Palmitoylethanolamide (PEA) is an anti-inflammatory and neuroprotective amide used in depressive syndromes. Here we investigate whether micronized/ultramicronized (m/um) PEA improves neuropsychiatric sequelae in COVID-19 survivors. Patients evaluated at our post-COVID-19 outpatient clinic between February and August 2021 and presenting neuropsychiatric manifestations (n = 98) were offered treatment with m/umPEA 600 mg twice daily for 3 months. Those accepting m/umPEA therapy (n = 57) were compared with those who did not (n = 41), in terms of depression, fatigue, chronic pain and subjective well-being, through validated scales administered pre- and posttreatment. The two groups did not differ in terms of demographics, comorbidities, psychiatric history, antidepressant therapy, acute COVID-19 severity and baseline neuropsychiatric status. Patients receiving m/umPEA showed a greater improvement in depression and fatigue (both P < 0.05). Conversely, no association was found with changes in chronic pain or subjective well-being. At multivariable logistic regression, m/umPEA predicted neuropsychiatric improvement independently of age, sex and baseline neuropsychiatric status. Worse pretreatment fatigue and subjective well-being identified those who most likely benefited from treatment. In conclusion, despite its retrospective nature, our study suggests that m/umPEA may improve depression and fatigue in COVID-19 survivors, justifying future research in this setting.

Physical and psychological sequelae at three months after acute illness in COVID-19 survivors.

BACKGROUND: Coronavirus disease 2019 (COVID-19) may leave behind an altered health status early after recovery. We evaluated the clinical status of COVID-19 survivors at three months after hospital discharge. METHODS: In this prospective observational cohort study, hospitalized patients aged ≥18 years, evaluated at one (M1) and three (M3) months post-discharge were enrolled. 251 patients (71.3% males, median [IQR] age 61.8 [53.5-70.7] years) were included. Median (IQR) time from discharge to M3 was 89 (79.5-101) days. Primary outcome was residual respiratory dysfunction (RRD), defined by tachypnea, moderate to very severe dyspnea, or peripheral oxygen saturation ≤95% on room air at M3. RESULTS: RRD was found in 30.4% of patients, with no significant difference compared with M1. Chronic obstructive pulmonary disease and length of stay were independent predictors of RRD at multivariable logistic regression (OR [95% CI]: 4.13 [1.17-16.88], P=0.033; OR [95% CI]: 1.02 [1.00-1.04], P=0.047, respectively). Obesity and C-reactive protein levels upon admission were additional predictors at regression tree analysis. Impaired quality of life (QoL) was reported by 53.2% of patients. Anxiety and insomnia were each present in 25.5% of patients, and PTSD in 22.4%. No difference was found between M1 and M3 in QoL, anxiety or PTSD. Insomnia decreased at M3. Current major psychiatric disorder as well as anxiety, insomnia and PSTD at M1 independently predicted PTSD at M3. CONCLUSIONS: Clinical damage may persist at three months after discharge in COVID-19 survivors. Post-recovery follow-up is an essential component of patient management.

Predictors and outcomes of delirium in the emergency department during the first wave of the COVID-19 pandemic in Milan.

BACKGROUND: Respiratory infections can be complicated by acute brain failure. We assessed delirium prevalence, predictors and outcomes in COVID-19 ED patients. METHODS: This was a retrospective observational study conducted at the San Raffaele ED (Italy). Patients age >18 years attending the ED between 26 February 2020 and 30 May 2020 and who had a positive molecular nasopharyngeal swab for SARS-CoV-2 were included. The Chart-Based Delirium Identification Instrument (CHART-DEL) was used to retrospectively assess delirium. Univariable and multivariable logistic regression analyses were used to evaluate delirium predictors. Univariable binary logistic regression analyses, linear regression analyses and Cox regression analyses were used to assess the association between delirium and clinical outcomes. Age-adjusted and sex-adjusted models were then run for the significant predictors of the univariable models. RESULTS: Among the 826 included patients, 123 cases (14.9%) of delirium were retrospectively detected through the CHART-DEL method. Patients with delirium were older (76.9±13.15 vs 61.3±14.27 years, p<0.001) and more frequently living in a long-term health facility (32 (26%) vs 22 (3.1%), p<0.001). Age (OR 1.06, 95% CI 1.04 to 1.09, p<0.001), dementia (OR 17.5, 95% CI 7.27 to 42.16, p<0.001), epilepsy (OR 6.96, 95% CI 2.48 to 19.51, p<0.001) and the number of chronic medications (OR 1.09, 95% CI 1.01 to 1.17, p=0.03) were significant predictors of delirium in multivariable analyses. Delirium was associated with increased in-hospital mortality (adjusted HR 2.16, 95% CI 1.55 to 3.03, p<0.001) and with a reduced probability of being discharged home compared with being institutionalised (adjusted OR 0.39, 95% CI 0.25 to 0.61, p<0.001). CONCLUSIONS: Chart review frequently identified ED delirium in patients with COVID-19. Age, dementia, epilepsy and polypharmacy were significant predictors of ED delirium. Delirium was associated with an increased in-hospital mortality and with a reduced probability of being discharged home after hospitalisation. The findings of this single-centre retrospective study require validation in future studies.

A novel evidence-based algorithm to predict thromboembolism in patients with COVID-19: preliminary data from a single-center cohort.

BACKGROUND: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-related disease (COVID-19) is an infectious disease characterized by systemic inflammation, which might enhance baseline thrombotic risk, especially in hospitalized patients. Little is, however, known about predictors of thrombotic complications in patients with COVID-19. METHODS: We prospectively followed up 180 hospitalized COVID-19 patients. Demographics, clinical and laboratory features at presentation and past medical history were tested as predictors of the first thrombotic complication through multivariate Cox regression analysis and a categorical score generated based on the results. RESULTS: Sixty-four thromboses were recorded in 54 patients, of whom seven with thrombosis on admission and 47 with thrombosis during hospitalization. Patients with thrombosis were mainly Caucasian and diabetic, had marked baseline signs of inflammation and organ damage, lower PaO2/FiO2 ratio, higher D-dimer levels and history of major hemorrhages. The latter three variables were independently associated to thrombotic complications and concurred to a 0-5 score, which accounted for 80% of the total sample variability. Patients with three or more points of the newly generated score were at higher risk for thrombotic complications (HR=4.9, P<0.001). Patients with thrombotic complications were more likely to be admitted to intensive care and/or to die (HR=1.9, P=0.036). Five of 180 patients were diagnosed with disseminated intravascular coagulation and three of them died. Eleven minor and no major bleeding events were observed. CONCLUSIONS: Patients with COVID-19 are at increased risk for thrombosis and might be stratified on admission based on lower Pao2/FiO2 ratio, higher D-dimer levels and history of major hemorrhages.

Thromboembolism risk among patients with diabetes/stress hyperglycemia and COVID-19.

PURPOSE: Individuals with diabetes/stress hyperglycemia carry an increased risk for adverse clinical outcome in case of SARS-CoV-2 infection. The purpose of this study was to evaluate whether this risk is, at least in part, modulated by an increase of thromboembolic complications. METHODS: We prospectively followed 180 hospitalized patients with confirmed COVID-19 pneumonia admitted to the Internal Medicine Units of San Raffaele Hospital. Data from 11 out of 180 patients were considered incomplete and excluded from the analysis. We analysed inflammation, tissue damage biomarkers, hemostatic parameters, thrombotic events (TEs) and clinical outcome according to the presence of diabetes/stress hyperglycemia. RESULTS: Among 169 patients, 51 (30.2%) had diabetes/stress hyperglycemia. Diabetes/stress hyperglycemia and fasting blood glucose (FBG) were associated with increased inflammation and tissue damage circulating markers, higher D-dimer levels, increased prothrombin time and lower antithrombin III activity. Forty-eight venous and 10 arterial TEs were identified in 49 (29%) patients. Diabetes/stress hyperglycemia (HR 2.71, p = 0.001), fasting blood glucose (HR 4.32, p < 0.001) and glucose variability (HR 1.6, p < 0.009) were all associated with an increased risk of thromboembolic complication. TEs significantly increased the risk for an adverse clinical outcome only in the presence of diabetes/stress hyperglycemia (HR 3.05, p = 0.010) or fasting blood glucose ≥7 mmol/L (HR 3.07, p = 0.015). CONCLUSIONS: Thromboembolism risk is higher among patients with diabetes/stress hyperglycemia and COVID-19 pneumonia and is associated to poor clinical outcome. In case of SARS-Cov-2 infection patients with diabetes/stress hyperglycemia could be considered for a more intensive prophylactic anticoagulation regimen.