Post-COVID-19 Cardiopulmonary Symptoms: Predictors and Imaging Features in Patients after Hospital Discharge. / Sintomas Cardiopulmonares Pós-COVID-19: Preditores e Características de Imagem de Pacientes após a Alta Hospitalar.

BACKGROUND: Most of the evidence about the impact of the post-acute COVID-19 Syndrome (PACS) reports individual symptoms without correlations with related imaging. OBJECTIVES: To evaluate cardiopulmonary symptoms, their predictors and related images in COVID-19 patients discharged from hospital. METHODS: Consecutive patients who survived COVID-19 were contacted 90 days after discharge. The Clinic Outcome Team structured a questionnaire evaluating symptoms and clinical status (blinded for hospitalization data). A multivariate analysis was performed to address the course of COVID-19, comorbidities, anxiety, depression, and post-traumatic stress during hospitalization, and cardiac rehabilitation after discharge. The significance level was set at 5%. RESULTS: A total of 480 discharged patients with COVID-19 (age: 59±14 years, 67.5% males) were included; 22.3% required mechanical ventilation. The prevalence of patients with PACS-related cardiopulmonary symptoms (dyspnea, tiredness/fatigue, cough, and chest discomfort) was 16.3%. Several parameters of chest computed tomography and echocardiogram were similar in patients with and without cardiopulmonary symptoms. The multivariate analysis showed that PACS-related cardiopulmonary-symptoms were independently related to female sex (OR 3.023; 95% CI 1.319-6.929), in-hospital deep venous thrombosis (OR 13.689; 95% CI 1.069-175.304), elevated troponin I (OR 1.355; 95% CI 1.048-1.751) and C-reactive protein during hospitalization (OR 1.060; 95% CI 1.023-1.097) and depression (OR 6.110; 95% CI 2.254-16.558). CONCLUSION: PACS-related cardiopulmonary symptoms 90 days post-discharge are common and multifactorial. Beyond thrombotic and markers of inflammation/myocardial injury during hospitalization, female sex and depression were independently associated with cardiopulmonary-related PACS. These results highlighted the need for a multifaceted approach targeting susceptible patients.

FUNDAMENTO: A maioria da evidência sobre o impacto da síndrome COVID pós-aguda (PACS, do inglês, post-acute COVID-19 syndrome) descreve sintomas individuais sem correlacioná-los com exames de imagens. OBJETIVOS: Avaliar sintomas cardiopulmonares, seus preditores e imagens relacionadas em pacientes com COVID-19 após alta hospitalar. MÉTODOS: Pacientes consecutivos, que sobreviveram à COVID-19, foram contatados 90 dias após a alta hospitalar. A equipe de desfechos clínicos (cega quanto aos dados durante a internação) elaborou um questionário estruturado avaliando sintomas e estado clínico. Uma análise multivariada foi realizada abordando a evolução da COVID-19, comorbidades, ansiedade, depressão, e estresse pós-traumático durante a internação, e reabilitação cardíaca após a alta. O nível de significância usado nas análises foi de 5%. RESULTADOS: Foram incluídos 480 pacientes (idade 59±14 anos, 67,5% do sexo masculino) que receberam alta hospitalar por COVID-19; 22,3% necessitaram de ventilação mecânica. A prevalência de pacientes com sintomas cardiopulmonares relacionados à PACS (dispneia, cansaço/fadiga, tosse e desconforto no peito) foi de 16,3%. Vários parâmetros de tomografia computadorizada do tórax e de ecocardiograma foram similares entre os pacientes com e sem sintomas cardiopulmonares. A análise multivariada mostrou que sintomas cardiopulmonares foram relacionados de maneira independente com sexo feminino (OR 3,023; IC95% 1,319-6,929), trombose venosa profunda durante a internação (OR 13,689; IC95% 1,069-175,304), nível elevado de troponina (OR 1,355; IC95% 1,048-1,751) e de proteína C reativa durante a internação (OR 1,060; IC95% 1,023-1,097) e depressão (OR 6,110; IC95% 2,254-16,558). CONCLUSÃO: Os sintomas cardiopulmonares relacionados à PACS 90 dias após a alta hospitalar são comuns e multifatoriais. Além dos marcadores trombóticos, inflamatórios e de lesão miocárdica durante a internação, sexo feminino e depressão foram associados independentemente com sintomas cardiopulmonares relacionados à PACS. Esses resultados destacaram a necessidade de uma abordagem multifacetada direcionada a pacientes susceptíveis.

Young and lonely? Results from the COMET study

Introduction: The sudden changes in daily routine due to the containment measures adopted for facing the COVID-19 pandemic have had an impact on the mental health of the general population. In particular, young adults are exposed to a higher risk compared to the general population to suffer from the consequences of the pandemic, in terms of anger and irritability, depressive symptoms and somatic complaints, insomnia, lack of motivation and loneliness. In particular, loneliness can be particularly pronounced during young adulthood. Objective(s): This study aimed to describe the levels of loneliness in a sample of Italian young people during the national lockdown in 2020, evaluating clinical and socio-demographic differences and the role of coping strategies and levels of resilience. Method(s): A sub-analysis of a sample of adults aged 18-34 years has been drawn on a larger cross-sectional observational national trial (COMET, 2020) in which, among other psychopathological dimensions, the levels of loneliness have been assessed by the UCLA scale short version. Result(s): Levels of lonelinesswere particularly severe in a third of cases (risk factors: unemployment, low income and vulnerability inmental health), in association with depression, anxiety, stress, OCD symptoms, higher rates of suicidal ideation, sleep disturbance and excessive use of Internet. Levels of loneliness tended to increase over time. Conclusion(s): Overall, during the Italian COVID-19 lockdown young people have experienced quite high levels of loneliness: this dimension could represent a useful domain to assess in routine clinical practice.

Preexisting mild cognitive impairment as a risk factor for COVID-19 infection: A scoping review and case reports

Introduction: SARS-Co-V2 neuroinvasive ability might be the basis for the onset of delirium and neuropsychiatric outcomes. Objective(s): We hypothesized that some infected patients with preexisting cognitive dysfunction may present delirium as unique manifestation of COVID-19 infection or as a prodrome of a new episode consistent with the psychiatric history. Method(s): We conducted a PubMed literature search to verify whether cognitive impairment might predispose to COVID-19. We included three patients with mild cognitive impairment and delirium at admission for SARS-Co-V2 suspected infection. Delirium was diagnosed according to DSM-5 criteria, Cognitive Assessment Method and Coma Glasgow Scale. Result(s): Literature analysis evidenced patients presenting delirium or delirium-like symptoms as clinical manifestation of COVID-19, plus a cognitive impairment, from mild to severe, which preexisted or was evidenced during the acute phase or after the infection. Most studies described delirium in patients with a past neurological/ psychiatric history. Contrasting data emerged on the potential link between COVID-19 and delirium in patients with cognitive impairment and without a past neuropsychiatric history. Our patients had no history of other medical complications. Our first patient had no psychiatric history, the second reported only a depressive episode, and the third had story of bipolar disorder. Delirium resolved completely after 2 days in the first patient. The other patients required 4 and 14 days to resolve: delirium appeared as the prodrome of a new psychiatric episode in line with their past history. Conclusion(s): Clinicians should acknowledge the possibility that COVID-19 infection may appear as delirium and acute psychiatric sequelae as unique manifestation.

How can resilience moderate the effects of the COVID-19 pandemic on mental health?

Introduction: The COVID-19 pandemic represents a new form of trauma, which is impacting on the mental health of the general population. However, the effects of this new trauma are variable, being mediated by individual factors such as the levels of resilience and the coping strategies. Objective(s): The aims of the present study are: 1) describe the levels of resilience and the type of coping strategies adopted by the Italian general adult population during the first wave of the pandemic;2) evaluate the protective role of coping strategies and resilience on the levels of depressive, anxiety and stress symptoms. Method(s): An online survey has been developed, which includes several validated self-reported questionnaires for the evaluation of participants' mental health condition, coping strategies and levels of resilience. The main outcome measure is the Depression Anxiety and Stress Scale-21 (DASS-21). Result(s): The finale sample consists of 20,720 participants, more than half reported low levels of resilience, which were not associated with age or gender. The levels of resilience did not differ among the general population, patients with pre-existing mental disorders and those infected by COVID-19. People with low levels of resilience rarely used adaptive coping strategies. The levels of resilience did not have any influence on stress, depressive or anxiety symptoms. Conclusion(s): The presence of low levels of resilience in the general population may be the missing link between the pandemic and increasing concerns on mental health problems. This could be important for the development of ad-hoc supportive and preventive psychosocial interventions.

Mortality Prediction Analysis among COVID-19 Inpatients Using Clinical Variables and Deep Learning Chest Radiography Imaging Features.

The emergence of the COVID-19 pandemic over a relatively brief interval illustrates the need for rapid data-driven approaches to facilitate clinical decision making. We examined a machine learning process to predict inpatient mortality among COVID-19 patients using clinical and chest radiographic data. Modeling was performed with a de-identified dataset of encounters prior to widespread vaccine availability. Non-imaging predictors included demographics, pre-admission clinical history, and past medical history variables. Imaging features were extracted from chest radiographs by applying a deep convolutional neural network with transfer learning. A multi-layer perceptron combining 64 deep learning features from chest radiographs with 98 patient clinical features was trained to predict mortality. The Local Interpretable Model-Agnostic Explanations (LIME) method was used to explain model predictions. Non-imaging data alone predicted mortality with an ROC-AUC of 0.87 ± 0.03 (mean ± SD), while the addition of imaging data improved prediction slightly (ROC-AUC: 0.91 ± 0.02). The application of LIME to the combined imaging and clinical model found HbA1c values to contribute the most to model prediction (17.1 ± 1.7%), while imaging contributed 8.8 ± 2.8%. Age, gender, and BMI contributed 8.7%, 8.2%, and 7.1%, respectively. Our findings demonstrate a viable explainable AI approach to quantify the contributions of imaging and clinical data to COVID mortality predictions.

Platelet Reactivity and Coagulation Markers in Patients with COVID-19.

INTRODUTION: COVID-19 is associated with an increased risk of thrombotic events. However, the contribution of platelet reactivity (PR) to the aetiology of the increased thrombotic risk associated with COVID-19 remains unclear. Our aim was to evaluate PR in stable patients diagnosed with COVID-19 and hospitalized with respiratory symptoms (mainly dyspnoea and dry cough), in comparison with a control group comprised of non-hospitalized healthy controls. METHODS: Observational, case control study that included patients with confirmed COVID-19 (COVID-19 group, n = 60) and healthy individuals matched by age and sex (control group, n = 60). Multiplate electrode aggregometry (MEA) tests were used to assess PR with adenosine diphosphate (MEA-ADP, low PR defined as < 53 AUC), arachidonic acid (MEA-ASPI, low PR < 86 AUC) and thrombin receptor-activating peptide 6 (MEA-TRAP, low PR < 97 AUC) in both groups. RESULTS: The rates of low PR with MEA-ADP were 27.5% in the COVID-19 group and 21.7% in the control group (OR = 1.60, p = 0.20); with MEA-ASPI, the rates were, respectively, 37.5% and 22.5% (OR = 3.67, p < 0.001); and with MEA-TRAP, the incidences were 48.5% and 18.8%, respectively (OR = 9.58, p < 0.001). Levels of D-dimer, fibrinogen, and plasminogen activator inhibitor 1 (PAI-1) were higher in the COVID-19 group in comparison with the control group (all p < 0.05). Thromboelastometry was utilized in a subgroup of patients and showed a hypercoagulable state in the COVID-19 group. CONCLUSION: Patients hospitalized with non-severe COVID-19 had lower PR compared to healthy controls, despite having higher levels of D-dimer, fibrinogen, and PAI-1, and hypercoagulability by thromboelastometry. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT04447131.

Case Report: A Severe SARS-CoV-2 Infection in a Teenager With Angelman Syndrome.

Teenagers generally present mild to no symptoms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In the present report, we present the case of a 14-year-old boy with Angelman syndrome (AS) who presented with severe COVID-19 symptoms. He spent 20 days in the ICU with elevated inflammatory biomarkers (C-reactive protein and D-dimer) and increased peaks of neutrophil-to-lymphocyte ratio, which is uncommon for teenagers diagnosed with COVID-19. Although he showed physiological instability, he was able to produce neutralizing antibodies, suggesting a functional immune response. The literature concerning the immune response to infections in patients with AS is still poor, and to our knowledge, this was the first report of a patient with AS diagnosed with COVID-19. As such, the present study may alert other patients with AS or other rare diseases that they lack a competent immune response and could suffer severe consequences of SARS-CoV-2 infection.

Psychosocial factors and hospitalisations for COVID-19: Prospective cohort study based on a community sample.

BACKGROUND: While certain infectious diseases have been linked to socioeconomic disadvantage, mental health problems, and lower cognitive function, relationships with COVID-19 are either uncertain or untested. Our objective was to examine the association of a range of psychosocial factors with hospitalisation for COVID-19. METHODS: UK Biobank, a prospective cohort study, comprises around half a million people who were aged 40-69 years at study induction between 2006 and 2010 when information on psychosocial factors and covariates were captured. Hospitalisations for COVID-19 were ascertained between 16th March and 26th April 2020. RESULTS: There were 908 hospitalisations for COVID-19 in an analytical sample of 431,051 England-based study members. In age- and sex-adjusted analyses, an elevated risk of COVID-19 was related to disadvantaged levels of education (odds ratio; 95% confidence interval: 2.05; 1.70, 2.47), income (2.00; 1.63, 2,47), area deprivation (2.20; 1.86, 2.59), occupation (1.39; 1.14, 1.69), psychological distress (1.58; 1.32, 1.89), mental health (1.50; 1.25, 1.79), neuroticism (1.19; 1.00, 1.42), and performance on two tests of cognitive function - verbal and numerical reasoning (2.66; 2.06, 3.34) and reaction speed (1.27; 1.08, 1.51). These associations were graded (p-value for trend ≤ 0.038) such that effects were apparent across the full psychosocial continua. After mutual adjustment for these characteristics plus ethnicity, comorbidity, and lifestyle factors, only the relationship between lower cognitive function as measured using the reasoning test and risk of the infection remained (1.98; 1.38, 2.85). CONCLUSIONS: A range of psychosocial factors revealed associations with hospitalisation for COVID-19 of which the relation with cognitive function, a marker of health literacy, was most robust.