Prognostic performance of blood neurofilament light chain protein in hospitalized COVID-19 patients without major central nervous system manifestations: an individual participant data meta-analysis.

BACKGROUND AND AIMS: To investigate the prognostic value of blood neurofilament light chain protein (NfL) levels in the acute phase of coronavirus disease 2019 (COVID-19). METHODS: We conducted an individual participant data (IPD) meta-analysis after screening on MEDLINE and Scopus to May 23rd 2022. We included studies with hospitalized adult COVID-19 patients without major COVID-19-associated central nervous system (CNS) manifestations and with a measurement of blood NfL in the acute phase as well as data regarding at least one clinical outcome including intensive care unit (ICU) admission, need of mechanical ventilation (MV) and death. We derived the age-adjusted measures NfL Z scores and conducted mixed-effects modelling to test associations between NfL Z scores and other variables, encompassing clinical outcomes. Summary receiver operating characteristic curves (SROCs) were used to calculate the area under the curve (AUC) for blood NfL. RESULTS: We identified 382 records, of which 7 studies were included with a total of 669 hospitalized COVID-19 cases (mean age 66.2 ± 15.0 years, 68.1% males). Median NfL Z score at admission was elevated compared to the age-corrected reference population (2.37, IQR: 1.13-3.06, referring to 99th percentile in healthy controls). NfL Z scores were significantly associated with disease duration and severity. Higher NfL Z scores were associated with a higher likelihood of ICU admission, need of MV, and death. SROCs revealed AUCs of 0.74, 0.80 and 0.71 for mortality, need of MV and ICU admission, respectively. CONCLUSIONS: Blood NfL levels were elevated in the acute phase of COVID-19 patients without major CNS manifestations and associated with clinical severity and poor outcome. The marker might ameliorate the performance of prognostic multivariable algorithms in COVID-19.

Biobanking for COVID-19 research.

BACKGROUND: Biobanks are imperative infrastructures, particularly during outbreaks, when there is an obligation to acquire and share knowledge as quick as possible to allow for implementation of science-based preventive, diagnostic, prognostic, and therapeutic strategies. METHODS: We established a COVID-19 biobank with the aim of collecting high-quality and well-annotated human biospecimens, in the effort to understand the pathogenic mechanisms underlying COVID-19 and identify therapeutic targets (COVID-BioB, NCT04318366). Here we describe our experience and briefly review the characteristics of the biobanks for COVID-19 that have been so far established. RESULTS: A total of 46,677 samples have been collected from 913 participants (63.3% males, median [IQR] age 62.2 [51.2-74.0] years) since the beginning of the program. Most patients (66.9%) had been admitted to hospital for COVID-19, with a median length of stay of 15.0 (9.0-27.0) days. A minority of patients (13.3% of the total) had been admitted for other reasons and subsequently tested positive for SARS-CoV-2. The remainder were managed at home after being seen at the Emergency Department. CONCLUSIONS: Having a solid research infrastructure already in place, along with flexibility and adaptability to new requirements, allowed for the quick building of a COVID-19 biobank that will help expand and share the knowledge of SARS-CoV-2.

A longitudinal analysis of humoral, T cellular response and influencing factors in a cohort of healthcare workers: Implications for personalized SARS-CoV-2 vaccination strategies.

Introduction: SARS-CoV-2 mRNA vaccinations elicit both virus-specific humoral and T-cell responses, but a complex interplay of different influencing factors, such as natural immunity, gender, and age, guarantees host protection. The present study aims to assess the immune dynamics of humoral, T-cell response, and influencing factors to stratify individual immunization status up to 10 months after Comirnaty-vaccine administration. Methods: To this aim, we longitudinally evaluated the magnitude and kinetics of both humoral and T-cell responses by serological tests and enzyme-linked immunospot assay at 5 time points. Furthermore, we compared the course over time of the two branches of adaptive immunity to establish an eventual correlation between adaptive responses. Lastly, we evaluated putative influencing factors collected by an anonymized survey administered to all participants through multiparametric analysis. Among 984 healthcare workers evaluated for humoral immunity, 107 individuals were further analyzed to describe SARS-CoV-2-specific T-cell responses. Participants were divided into 4 age groups: <40 and ≥40 years for men, <48 and ≥48 years for women. Furthermore, results were segregated according to SARS-CoV-2-specific serostatus at baseline. Results: The disaggregated evaluation of humoral responses highlighted antibody levels decreased in older subjects. The humoral responses were higher in females than in males (p=0.002) and previously virus-exposed subjects compared to naïve subjects (p<0.001). The vaccination induced a robust SARS-CoV-2 specific T-cell response at early time points in seronegative subjects compared to baseline levels (p<0.0001). However, a contraction was observed 6 months after vaccination in this group (p<0.01). On the other hand, the pre-existing specific T-cell response detected in natural seropositive individuals was longer-lasting than the response of the seronegative subjects, decreasing only 10 months after vaccination. Our data suggest that T-cell reactiveness is poorly impacted by sex and age. Of note, SARS-CoV-2-specific T-cell response was not correlated to the humoral response at any time point. Discussion: These findings suggest prospects for rescheduling vaccination strategies by considering individual immunization status, personal characteristics, and the appropriate laboratory tests to portray immunity against SARS-CoV-2 accurately. Deepening our knowledge about T and B cell dynamics might optimize the decision-making process in vaccination campaigns, tailoring it to each specific immune response.

Profiling Covid-19 patients with respect to level of severity: an integrated statistical approach.

A full understanding of the characteristics of Covid-19 patients with a better chance of experiencing poor vital outcomes is critical for implementing accurate and precise treatments. In this paper, two different advanced data-driven statistical approaches along with standard statistical methods have been implemented to identify groups of patients most at-risk for death or severity of respiratory distress. First, the tree-based analysis allowed to identify profiles of patients with different risk of in-hospital death (by Survival Tree-ST analysis) and severity of respiratory distress (by Classification and Regression Tree-CART analysis), and to unravel the role on risk stratification of highly dependent covariates (i.e., demographic characteristics, admission values and comorbidities). The ST analysis identified as the most at-risk group for in-hospital death the patients with age > 65 years, creatinine [Formula: see text] 1.2 mg/dL, CRP [Formula: see text] 25 mg/L and anti-hypertensive treatment. Based on the CART analysis, the subgroups most at-risk of severity of respiratory distress were defined by patients with creatinine level [Formula: see text] 1.2 mg/dL. Furthermore, to investigate the multivariate dependence structure among the demographic characteristics, the admission values, the comorbidities and the severity of respiratory distress, the Bayesian Network analysis was applied. This analysis confirmed the influence of creatinine and CRP on the severity of respiratory distress.

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.

Prevalence of Long COVID-19 Symptoms After Hospital Discharge in Frail and Robust Patients.

Background: A motley postacute symptomatology may develop after COVID-19, irrespective of the acute disease severity, age, and comorbidities. Frail individuals have reduced physiological reserves and manifested a worse COVID-19 course, during the acute setting. However, it is still unknown, whether frailty may subtend some long COVID-19 manifestations. We explored the prevalence of long COVID-19 disturbs in COVID-19 survivals. Methods: This was an observational study. Patients aged 65 years or older were followed-up 1, 3, and 6 months after hospitalization for COVID-19 pneumonia. Results: A total of 382 patients were enrolled. Frail patients were more malnourished (median Mini Nutritional Assessment Short Form score 8 vs. 9, p = 0.001), at higher risk of sarcopenia [median Strength, Assistance with walking, Rising from a chair, Climbing stairs, and Falls (SARC-F) score 3 vs. 1.5, p = 0.003], and manifested a worse physical performance [median Short Physical Performance Battery (SPPB) score 10 vs. 11, p = 0.0007] than robust individuals, after hospital discharge following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia. Frailty was significantly associated with: (i) confusion, as a presenting symptom of COVID-19 [odds ratio (OR) 77.84, 95% CI 4.23-1432.49, p = 0.003]; (ii) malnutrition (MNA-SF: adjusted B -5.63, 95% CI -8.39 to -2.87, p < 0.001), risk of sarcopenia (SARC-F: adjusted B 9.11, 95% CI 3.10-15.13, p = 0.003), impaired muscle performance (SPPB: B -3.47, 95% CI -6.33 to -0.61, p = 0.02), complaints in mobility (adjusted OR 1674200.27, 95% CI 4.52-619924741831.25, p = 0.03), in self-care (adjusted OR 553305.56, 95% CI 376.37-813413358.35, p < 0.001), and in performing usual activities of daily living (OR 71.57, 95% CI 2.87-1782.53, p = 0.009) at 1-month follow-up; (iii) dyspnea [modified Medical Research Council (mMRC): B 4.83, 95% CI 1.32-8.33, p = 0.007] and risk of sarcopenia (SARC-F: B 7.12, 95% CI 2.17-12.07, p = 0.005) at 3-month follow-up; and (iv) difficulties in self-care (OR 2746.89, 95% CI 6.44-1172310.83, p = 0.01) at the 6-month follow-up. In a subgroup of patients (78 individuals), the prevalence of frailty increased at the 1-month follow-up compared to baseline (p = 0.009). Conclusion: The precocious identification of frail COVID-19 survivors, who manifest more motor and respiratory complaints during the follow-up, could improve the long-term management of these COVID-19 sequelae.

Prevalence, trajectory over time, and risk factor of post-COVID-19 fatigue.

Fatigue is one of the most commonly reported symptoms in the context of the post-COVID-19 syndrome. Notably, fatigue is characterised by overlapping physical and psychopathological symptoms, and questions about its trajectory over time and possible predictors remained unanswered. Thus, in the present study we aim to investigate the prevalence, the course over time, and the risk factors of post-COVID fatigue. We included 495 patients recovered from COVID-19. For all of them we collected one month demographic, clinical and psychopathological characteristics. We evaluated fatigue severity at one, three, six, and twelve-months according to Fatigue Severity Scale (FSS). We explored the potential predictor of long-term post-COVID fatigue (six or twelve months FSS) by implementing 5000 non-parametric bootstraps enhanced elastic net penalised regression. We found that 22%, 27%, 30%, and 34% of patients self-rated fatigue symptoms in the pathological range at one, three, six, and twelve months respectively. We detected a worsening of fatigue symptomatology over time. From the elastic net regression results, only depressive symptomatology at one month (ZSDS and BDI-13) predicted the presence of post-COVID-19 long-term fatigue. No other clinical or demographic variable was found to predict post-COVID fatigue. We suggest that, rather independent of COVID-19 severity, depression after COVID-19 is associated with persistent fatigue. Clarifying mechanisms and risk factors of post-COVID fatigue will allow to identify the target population and to tailor specific treatment and rehabilitation interventions to foster recovery.

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.

Prevalence of Long COVID-19 Symptoms After Hospital Discharge in Frail and Robust Patients

Background A motley postacute symptomatology may develop after COVID-19, irrespective of the acute disease severity, age, and comorbidities. Frail individuals have reduced physiological reserves and manifested a worse COVID-19 course, during the acute setting. However, it is still unknown, whether frailty may subtend some long COVID-19 manifestations. We explored the prevalence of long COVID-19 disturbs in COVID-19 survivals. Methods This was an observational study. Patients aged 65 years or older were followed-up 1, 3, and 6 months after hospitalization for COVID-19 pneumonia. Results A total of 382 patients were enrolled. Frail patients were more malnourished (median Mini Nutritional Assessment Short Form score 8 vs. 9, p = 0.001), at higher risk of sarcopenia [median Strength, Assistance with walking, Rising from a chair, Climbing stairs, and Falls (SARC-F) score 3 vs. 1.5, p = 0.003], and manifested a worse physical performance [median Short Physical Performance Battery (SPPB) score 10 vs. 11, p = 0.0007] than robust individuals, after hospital discharge following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia. Frailty was significantly associated with: (i) confusion, as a presenting symptom of COVID-19 [odds ratio (OR) 77.84, 95% CI 4.23–1432.49, p = 0.003];(ii) malnutrition (MNA-SF: adjusted B –5.63, 95% CI –8.39 to –2.87, p < 0.001), risk of sarcopenia (SARC-F: adjusted B 9.11, 95% CI 3.10–15.13, p = 0.003), impaired muscle performance (SPPB: B –3.47, 95% CI –6.33 to –0.61, p = 0.02), complaints in mobility (adjusted OR 1674200.27, 95% CI 4.52–619924741831.25, p = 0.03), in self-care (adjusted OR 553305.56, 95% CI 376.37–813413358.35, p < 0.001), and in performing usual activities of daily living (OR 71.57, 95% CI 2.87–1782.53, p = 0.009) at 1-month follow-up;(iii) dyspnea [modified Medical Research Council (mMRC): B 4.83, 95% CI 1.32–8.33, p = 0.007] and risk of sarcopenia (SARC-F: B 7.12, 95% CI 2.17–12.07, p = 0.005) at 3-month follow-up;and (iv) difficulties in self-care (OR 2746.89, 95% CI 6.44–1172310.83, p = 0.01) at the 6-month follow-up. In a subgroup of patients (78 individuals), the prevalence of frailty increased at the 1-month follow-up compared to baseline (p = 0.009). Conclusion The precocious identification of frail COVID-19 survivors, who manifest more motor and respiratory complaints during the follow-up, could improve the long-term management of these COVID-19 sequelae.

A Pilot Study of the Efficacy and Economical Sustainability of Acute Coronavirus Disease 2019 Patient Management in an Outpatient Setting.

Objective: To report a preliminary experience of outpatient management of patients with Coronavirus disease 2019 (COVID-19) through an innovative approach of healthcare delivery. Patients and Methods: Patients evaluated at the Mild-to-Moderate COVID-19 Outpatient clinics (MMCOs) of San Raffaele University Hospital and Luigi Sacco University Hospital in Milan, Italy, from 1 October 2020 to 31 October 2021 were included. Patients were referred by general practitioners (GPs), Emergency Department (ED) physicians or hospital specialists (HS) in case of moderate COVID-19. A classification and regression tree (CART) model predicting ED referral by MMCO physicians was developed to aid GPs identify those deserving immediate ED admission. Cost-effectiveness analysis was also performed. Results: A total of 660 patients were included. The majority (70%) was referred by GPs, 21% by the ED and 9% by HS. Patients referred by GPs had more severe disease as assessed by peripheral oxygen saturation (SpO2), ratio of arterial oxygen partial pressure to fractional inspired oxygen (PaO2/FiO2), C-reactive protein (CRP) levels and interstitial involvement at lung ultrasound. Among them, 18% were addressed to the ED following MMCO assessment. CART analysis identified three independent predictors, namely home-measured SpO2, age and body mass index (BMI), that robustly divide patients into risk groups of COVID-19 severity. Home-measured SpO2 < 95% and BMI ≥ 33 Kg/m2 defined the high-risk group. The model yielded an accuracy (95% CI) of 83 (77-88)%. Outpatient management of COVID-19 patients allowed the national healthcare system to spare 1,490,422.05 € when compared with inpatient care. Conclusion: Mild-to-moderate COVID-19 outpatient clinics were effective and sustainable in managing COVID-19 patients and allowed to alleviate pressure on EDs and hospital wards, favoring effort redirection toward non-COVID-19 patients.

Chitinase-3-like protein-1 at hospital admission predicts COVID-19 outcome: a prospective cohort study.

Infectious and inflammatory stimuli elicit the generation of chitinase-3-like protein-1 (CHI3L1), involved in tissue damage, repair and remodeling. We evaluated whether plasma CHI3L1 at disease onset predicts clinical outcome of patients with Coronavirus 2019 (COVID-19) disease. Blood from 191 prospectively followed COVID-19 patients were collected at hospital admission between March 18th and May 5th, 2020. Plasma from 80 survivors was collected one month post-discharge. Forty age- and sex-matched healthy volunteers served as controls. Primary outcome was transfer to intensive care unit (ICU) or death. CHI3L1 was higher in COVID-19 patients than controls (p < 0.0001). Patients with unfavorable outcome (41 patients admitted to ICU, 47 died) had significantly higher CHI3L1 levels than non-ICU survivors (p < 0.0001). CHI3L1 levels abated in survivors one month post-discharge, regardless of initial disease severity (p < 0.0001), although remaining higher than controls (p < 0.05). Cox regression analysis revealed that CHI3L1 levels predict primary outcome independently of age, sex, comorbidities, degree of respiratory insufficiency and systemic inflammation or time from symptom onset to sampling (p < 0.0001). Kaplan-Meier curve analysis confirmed that patients with CHI3L1 levels above the median (361 ng/mL) had a poorer prognosis (log rank test, p < 0.0001). Plasma CHI3L1 is increased in COVID-19 patients and predicts adverse outcome.

Myosteatosis Significantly Predicts Persistent Dyspnea and Mobility Problems in COVID-19 Survivors.

Background: Persistent symptoms including dyspnea and functional impairment are common in COVID-19 survivors. Poor muscle quality (myosteatosis) associates with poor short-term outcomes in COVID-19 patients. The aim of this observational study was to assess the relationship between myosteatosis diagnosed during acute COVID-19 and patient-reported outcomes at 6 months after discharge. Methods: Myosteatosis was diagnosed based on CT-derived skeletal muscle radiation attenuation (SM-RA) measured during hospitalization in 97 COVID-19 survivors who had available anthropometric and clinical data upon admission and at the 6-month follow-up after discharge. Dyspnea in daily activities was assessed using the modified Medical Research Council (mMRC) scale for dyspnea. Health-related quality of life was measured using the European quality of life questionnaire three-level version (EQ-5D-3L). Results: Characteristics of patients with (lowest sex- and age-specific tertile of SM-RA) or without myosteatosis during acute COVID-19 were similar. At 6 months, patients with myosteatosis had greater rates of obesity (48.4 vs. 27.7%, p = 0.046), abdominal obesity (80.0 vs. 47.6%, p = 0.003), dyspnea (32.3 vs. 12.5%, p = 0.021) and mobility problems (32.3 vs. 12.5%, p = 0.004). Myosteatosis diagnosed during acute COVID-19 was the only significant predictor of persistent dyspnea (OR 3.19 [95% C.I. 1.04; 9.87], p = 0.043) and mobility problems (OR 3.70 [95% C.I. 1.25; 10.95], p = 0.018) at 6 months at logistic regression adjusted for sex, age, and BMI. Conclusion: Myosteatosis diagnosed during acute COVID-19 significantly predicts persistent dyspnea and mobility problems at 6 months after hospital discharge independent of age, sex, and body mass. Clinical Trial Registration: [www.ClinicalTrials.gov], identifier [NCT04318366].

Chromogranin A plasma levels predict mortality in COVID-19.

BACKGROUND: Chromogranin A (CgA) and its fragment vasostatin I (VS-I) are secreted in the blood by endocrine/neuroendocrine cells and regulate stress responses. Their involvement in Coronavirus 2019 disease (COVID-19) has not been investigated. METHODS: CgA and VS-I plasma concentrations were measured at hospital admission from March to May 2020 in 190 patients. 40 age- and sex-matched healthy volunteers served as controls. CgA and VS-I levels relationship with demographics, comorbidities and disease severity was assessed through Mann Whitney U test or Spearman correlation test. Cox regression analysis and Kaplan Meier survival curves were performed to investigate the impact of the CgA and VS-I levels on in-hospital mortality. RESULTS: Median CgA and VS-I levels were higher in patients than in healthy controls (CgA: 0.558 nM [interquartile range, IQR 0.358-1.046] vs 0.368 nM [IQR 0.288-0.490] respectively, p = 0.0017; VS-I: 0.357 nM [IQR 0.196-0.465] vs 0.144 nM [0.144-0.156] respectively, p<0.0001). Concentration of CgA, but not of VS-I, significantly increased in patients who died (n = 47) than in survivors (n = 143) (median 0.948 nM [IQR 0.514-1.754] vs 0.507 nM [IQR 0.343-0.785], p = 0.00026). Levels of CgA were independent predictors of in-hospital mortality (hazard ratio 1.28 [95% confidence interval 1.077-1.522], p = 0.005) when adjusted for age, number of comorbidities, respiratory insufficiency degree, C-reactive protein levels and time from symptom onset to sampling. Kaplan Meier curves revealed a significantly increased mortality rate in patients with CgA levels above 0.558 nM (median value, log rank test, p = 0.001). CONCLUSION: Plasma CgA levels increase in COVID-19 patients and represent an early independent predictor of mortality.

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.

Evaluation of Muscle Mass and Stiffness with Limb Ultrasound in COVID-19 Survivors.

BACKGROUND: acute illnesses, like COVID-19, can act as a catabolic stimulus on muscles. So far, no study has evaluated muscle mass and quality through limb ultrasound in post-COVID-19 patients. METHODS: cross sectional observational study, including patients seen one month after hospital discharge for SARS-CoV-2 pneumonia. The patients underwent a multidimensional evaluation. Moreover, we performed dominant medial gastrocnemius ultrasound (US) to characterize their muscle mass and quality. RESULTS: two hundred fifty-nine individuals (median age 67, 59.8% males) were included in the study. COVID-19 survivors with reduced muscle strength had a lower muscle US thickness (1.6 versus 1.73 cm, p =0.02) and a higher muscle stiffness (87 versus 76.3, p = 0.004) compared to patients with normal muscle strength. Also, patients with reduced Short Physical Performance Battery (SPPB) scores had a lower muscle US thickness (1.3 versus 1.71 cm, p = 0.01) and a higher muscle stiffness (104.9 versus 81.07, p = 0.04) compared to individuals with normal SPPB scores. The finding of increased muscle stiffness was also confirmed in patients with a pathological value (≥ 4) at the sarcopenia screening tool SARC-F (103.0 versus 79.55, p < 0.001). Muscle stiffness emerged as a significant predictor of probable sarcopenia (adjusted OR 1.02, 95% C.I. 1.002 - 1.04, p = 0.03). The optimal ultrasound cut-offs for probable sarcopenia were 1.51 cm for muscle thickness (p= 0.017) and 73.95 for muscle stiffness (p = 0.004). DISCUSSION: we described muscle ultrasound characteristics in post COVID-19 patients. Muscle ultrasound could be an innovative tool to assess muscle mass and quality in this population. Our preliminary findings need to be confirmed by future studies comparing muscle ultrasound with already validated techniques for measuring muscle mass and quality.

Brain correlates of depression, post-traumatic distress, and inflammatory biomarkers in COVID-19 survivors: A multimodal magnetic resonance imaging study.

Psychiatric sequelae substantially contribute to the post-acute burden of disease associated with COVID-19, persisting months after clearance of the virus. Brain imaging shows white matter (WM) hypodensities/hyperintensities, and the involvement of grey matter (GM) in prefrontal, anterior cingulate (ACC) and insular cortex after COVID, but little is known about brain correlates of persistent psychopathology. With a multimodal approach, we studied whole brain voxel-based morphometry, diffusion-tensor imaging, and resting-state connectivity, to correlate MRI measures with depression and post-traumatic distress (PTSD) in 42 COVID-19 survivors without brain lesions, at 90.59 â€‹± â€‹54.66 days after COVID. Systemic immune-inflammation index (SII) measured in the emergency department, which reflects the immune response and systemic inflammation based on peripheral lymphocyte, neutrophil, and platelet counts, predicted worse self-rated depression and PTSD, widespread lower diffusivity along the main axis of WM tracts, and abnormal functional connectivity (FC) among resting state networks. Self-rated depression and PTSD inversely correlated with GM volumes in ACC and insula, axial diffusivity, and associated with FC. We observed overlapping associations between severity of inflammation during acute COVID-19, brain structure and function, and severity of depression and post-traumatic distress in survivors, thus warranting interest for further study of brain correlates of the post-acute COVID-19 syndrome. Beyond COVID-19, these findings support the hypothesis that regional GM, WM microstructure, and FC could mediate the relationship between a medical illness and its psychopathological sequelae, and are in agreement with current perspectives on the brain structural and functional underpinnings of depressive psychopathology.

Six-month respiratory outcomes and exercise capacity of COVID-19 acute respiratory failure patients treated with continuous positive airway pressure.

BACKGROUND: COVID-19 long-term sequelae are ill-defined since only a few studies have explored the long-term consequences of this disease so far. AIMS: To evaluate the 6-month respiratory outcome and exercise capacity of COVID-19 acute respiratory failure (ARF) patients treated with continuous positive airway pressure (CPAP) during the first wave of the ongoing COVID-19 pandemic. METHODS: A retrospective observational study included COVID-19 patients with ARF. Interventions included CPAP during hospitalisation and 6-month follow up. Frailty assessment was carried out through frailty index (FI), pO2 /FiO2 during hospitalisation and at follow up, respiratory parameters, 6-min walking test (6MWT) and the modified British Medical Research Council (mMRC) and Borg scale at follow up. RESULTS: More than half of the patients had no dyspnoea according to the mMRC scale. Lower in-hospital pO2 /FiO2 correlated with higher Borg scale levels after 6MWT (ρ 0.27; P 0.04) at the follow-up visit. FI was positively correlated with length of hospitalisation (ρ 0.3; P 0.03) and negatively with the 6MWT distance walked (ρ -0.36; P 0.004). CONCLUSIONS: Robust and frail patients with COVID-19 ARF treated with CPAP outside the intensive care unit setting had good respiratory parameters and exercise capacity at 6-month follow up, although more severe patients had slightly poorer respiratory performance compared with patients with higher PaO2 /FiO2 and lower FI.

One-year mental health outcomes in a cohort of COVID-19 survivors.

COVID-19 survivors are at increased risk of persistent psychopathology after the infection. Despite long-term sequelae are an increasing concern, long-term neuropsychiatric consequences remain largely unclear. This cohort study aimed at investigating the psychopathological impact of COVID-19 in Italy one year after infection, outlining the trajectory of symptomatology at one, six-, and twelve-months follow-up. We evaluated 402, 216, and 192 COVID-19 survivors respectively at one, six, and 12 months. A subgroup of 95 patients was evaluated longitudinally both at one, six, and 12 months. Validated self-report questionnaires were administered to assess depression, fatigue, anxiety, and post-traumatic distress. Socio-demographics and setting of care information were gathered for each participant. At six and twelve months, respectively 94 (44%) and 86 (45%) patients self-rated in the clinical range in at least one psychopathological dimension. Pathological fatigue at twelve months was detected in 63 patients (33%). Considering the longitudinal cohort an interaction effect of sex and time was observed for depression (F = 8.63, p < 0.001) and anxiety (F = 5.42, p = 0.005) with males showing a significant increasing trend of symptoms, whereas an opposite course was observed in females. High prevalence of psychiatric sequelae six and 12 months after COVID-19 was reported for the first time. These findings confirm the need to provide integrated multidisciplinary services to properly address long-lasting mental health sequelae of COVID-19 and to treat them with the aim of reducing the disease burden and related years of life lived with disability.