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.

Weight trajectories and abdominal adiposity in COVID-19 survivors with overweight/obesity.

BACKGROUND: COVID-19 is associated with unintentional weight loss. Little is known on whether and how patients regain the lost weight. We assessed changes in weight and abdominal adiposity over a three-month follow-up after discharge in COVID-19 survivors. METHODS: In this sub-study of a large prospective observational investigation, we collected data from individuals who had been hospitalized for COVID-19 and re-evaluated at one (V1) and three (V2) months after discharge. Patient characteristics upon admission and anthropometrics, waist circumference and hunger levels assessed during follow-up were analyzed across BMI categories. RESULTS: One-hundred-eighty-five COVID-19 survivors (71% male, median age 62.1 [54.3; 72.1] years, 80% with overweight/obesity) were included. Median BMI did not change from admission to V1 in normal weight subjects (-0.5 [-1.2; 0.6] kg/m2, p = 0.08), but significantly decreased in subjects with overweight (-0.8 [-1.8; 0.3] kg/m2, p < 0.001) or obesity (-1.38 [-3.4; -0.3] kg/m2, p < 0.001; p < 0.05 vs. normal weight or obesity). Median BMI did not change from V1 to V2 in normal weight individuals (+0.26 [-0.34; 1.15] kg/m2, p = 0.12), but significantly increased in subjects with overweight (+0.4 [0.0; 1.0] kg/m2, p < 0.001) or obesity (+0.89 [0.0; 1.6] kg/m2, p < 0.001; p = 0.01 vs. normal weight). Waist circumference significantly increased from V1 to V2 in the whole group (p < 0.001), driven by the groups with overweight or obesity. At multivariable regression analyses, male sex, hunger at V1 and initial weight loss predicted weight gain at V2. CONCLUSIONS: Patients with overweight or obesity hospitalized for COVID-19 exhibit rapid, wide weight fluctuations that may worsen body composition (abdominal adiposity). CLINICALTRIALS. GOV REGISTRATION: NCT04318366.

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.

A Nomogram-Based Model to Predict Respiratory Dysfunction at 6 Months in Non-Critical COVID-19 Survivors.

Objective: To assess the prevalence of respiratory sequelae of Coronavirus disease 2019 (COVID-19) survivors at 6 months after hospital discharge and develop a model to identify at-risk patients. Patients and Methods: In this prospective cohort study, hospitalized, non-critical COVID-19 patients evaluated at 6-month follow-up between 26 August, 2020 and 16 December, 2020 were included. Primary outcome was respiratory dysfunction at 6 months, defined as at least one among tachypnea at rest, percent predicted 6-min walking distance at 6-min walking test (6MWT) ≤ 70%, pre-post 6MWT difference in Borg score ≥ 1 or a difference between pre- and post-6MWT oxygen saturation ≥ 5%. A nomogram-based multivariable logistic regression model was built to predict primary outcome. Validation relied on 2000-resample bootstrap. The model was compared to one based uniquely on degree of hypoxemia at admission. Results: Overall, 316 patients were included, of whom 118 (37.3%) showed respiratory dysfunction at 6 months. The nomogram relied on sex, obesity, chronic obstructive pulmonary disease, degree of hypoxemia at admission, and non-invasive ventilation. It was 73.0% (95% confidence interval 67.3-78.4%) accurate in predicting primary outcome and exhibited minimal departure from ideal prediction. Compared to the model including only hypoxemia at admission, the nomogram showed higher accuracy (73.0 vs 59.1%, P < 0.001) and greater net-benefit in decision curve analyses. When the model included also respiratory data at 1 month, it yielded better accuracy (78.2 vs. 73.2%) and more favorable net-benefit than the original model. Conclusion: The newly developed nomograms accurately identify patients at risk of persistent respiratory dysfunction and may help inform clinical priorities.

QTc interval prolongation, inflammation, and mortality in patients with COVID-19.

PURPOSE: Systemic inflammation has been associated with corrected QT (QTc) interval prolongation. The role of inflammation on QTc prolongation in COVID-19 patients was investigated. METHODS: Patients with a laboratory-confirmed SARS-CoV-2 infection admitted to IRCCS San Raffaele Scientific Institute (Milan, Italy) between March 14, 2020, and March 30, 2020 were included. QTc-I was defined as the QTc interval by Bazett formula in the first ECG performed during the hospitalization, before any new drug treatment; QTc-II was the QTc in the ECG performed after the initiation of hydroxychloroquine drug treatment. RESULTS: QTc-I was long in 45 patients (45%) and normal in 55 patients (55%). Patients with long QTc-I were older and more frequently males. C-Reactive protein (CRP) and white blood cell (WBC) count at hospitalization were higher in patients with long QTc-I and long QTc-II. QTc-I was significantly correlated with CRP levels at hospitalization. After a median follow-up of 83 days, 14 patients (14%) died. There were no deaths attributed to ventricular arrhythmias. Patients with long QTc-I and long QTc-II had a shorter survival, compared with normal QTc-I and QTc-II patients, respectively. In Cox multivariate analysis, independent predictors of mortality were age (HR = 1.1, CI 95% 1.04-1.18, p = 0.002) and CRP at ECG II (HR 1.1, CI 95% 1.0-1.1, p = 0.02). CONCLUSIONS: QTc at hospitalization is a simple risk marker of mortality risk in COVID-19 patients and reflects the myocardial inflammatory status.