Multicentre study on the accuracy of lung ultrasound in the diagnosis and monitoring of respiratory sequelae in the medium and long term in patients with COVID-19.

Introduction: Lung ultrasound (LUS) has proven to be a more sensitive tool than radiography (X-ray) to detect alveolar-interstitial involvement in COVID-19 pneumonia. However, its usefulness in the detection of possible pulmonary alterations after overcoming the acute phase of COVID-19 is unknown. In this study we proposed studying the utility of LUS in the medium- and long-term follow-up of a cohort of patients hospitalized with COVID-19 pneumonia. Materials and methods: This was a prospective, multicentre study that included patients, aged over 18 years, at 3 ± 1 and 12 ± 1 months after discharge after treatment for COVID-19 pneumonia. Demographic variables, the disease severity, and analytical, radiographic, and functional clinical details were collected. LUS was performed at each visit and 14 areas were evaluated and classified with a scoring system whose global sum was referred to as the "lung score." Two-dimensional shear wave elastography (2D-SWE) was performed in 2 anterior areas and in 2 posterior areas in a subgroup of patients. The results were compared with high-resolution computed tomography (CT) images reported by an expert radiologist. Results: A total of 233 patients were included, of whom 76 (32.6%) required Intensive Care Unit (ICU) admission; 58 (24.9%) of them were intubated and non-invasive respiratory support was also necessary in 58 cases (24.9%). Compared with the results from CT images, when performed in the medium term, LUS showed a sensitivity (S) of 89.7%, specificity (E) 50%, and an area under the curve (AUC) of 78.8%, while the diagnostic usefulness of X-ray showed an S of 78% and E of 47%. Most of the patients improved in the long-term evaluation, with LUS showing an efficacy with an S of 76% and E of 74%, while the X-ray presented an S of 71% and E of 50%. 2D-SWE data were available in 108 (61.7%) patients, in whom we found a non-significant tendency toward the presentation of a higher shear wave velocity among those who developed interstitial alterations, with a median kPa of 22.76 ± 15.49) versus 19.45 ± 11.39; p = 0.1). Conclusion: Lung ultrasound could be implemented as a first-line procedure in the evaluation of interstitial lung sequelae after COVID-19 pneumonia.

Evolution and long­term respiratory sequelae after severe COVID-19 pneumonia: nitric oxide diffusion measurement value.

INTRODUCTION: There are no published studies assessing the evolution of combined determination of the lung diffusing capacity for both nitric oxide and carbon monoxide (DLNO and DLCO) 12 months after the discharge of patients with COVID-19 pneumonia. METHODS: Prospective cohort study which included patients who were assessed both 3 and 12 months after an episode of SARS-CoV-2 pneumonia. Their clinical status, health condition, lung function testings (LFTs) results (spirometry, DLNO-DLCO analysis, and six-minute walk test), and chest X-ray/computed tomography scan images were compared. RESULTS: 194 patients, age 62 years (P25-75, 51.5-71), 59% men, completed the study. 17% required admission to the intensive care unit. An improvement in the patients' exercise tolerance, the extent of the areas of ground-glass opacity, and the LFTs between 3 and 12 months following their hospital discharge were found, but without a decrease in their degree of dyspnea or their self-perceived health condition. DLNO was the most significantly altered parameter at 12 months (19.3%). The improvement in DLNO-DLCO mainly occurred at the expense of the recovery of alveolar units and their vascular component, with the membrane factor only improving in patients with more severe infections. CONCLUSIONS: The combined measurement of DLNO-DLCO is the most sensitive LFT for the detection of the long-term sequelae of COVID-19 pneumonia and it explain better their pathophysiology.

Long COVID in hospitalized and non-hospitalized patients in a large cohort in Northwest Spain, a prospective cohort study.

Survivors to COVID-19 have described long-term symptoms after acute disease. These signs constitute a heterogeneous group named long COVID or persistent COVID. The aim of this study is to describe persisting symptoms 6 months after COVID-19 diagnosis in a prospective cohort in the Northwest Spain. This is a prospective cohort study performed in the COHVID-GS. This cohort includes patients in clinical follow-up in a health area of 569,534 inhabitants after SARS-CoV-2/COVID-19 diagnosis. Clinical and epidemiological characteristics were collected during the follow up. A total of 248 patients completed 6 months follow-up, 176 (69.4%) required hospitalization and 29 (10.2%) of them needed critical care. At 6 months, 119 (48.0%) patients described one or more persisting symptoms. The most prevalent were: extra-thoracic symptoms (39.1%), chest symptoms (27%), dyspnoea (20.6%), and fatigue (16.1%). These symptoms were more common in hospitalized patients (52.3% vs. 38.2%) and in women (59.0% vs. 40.5%). The multivariate analysis identified COPD, women gender and tobacco consumption as risk factors for long COVID. Persisting symptoms are common after COVID-19 especially in hospitalized patients compared to outpatients (52.3% vs. 38.2%). Based on these findings, special attention and clinical follow-up after acute SARS-CoV-2 infection should be provided for hospitalized patients with previous lung diseases, tobacco consumption, and women.

Aptamer Sandwich Assay for the Detection of SARS-CoV-2 Spike Protein Antigen.

The novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) emerged at the end of 2019, resulting in the ongoing COVID-19 pandemic. The high transmissibility of the virus and the substantial number of asymptomatic individuals have led to an exponential rise in infections worldwide, urgently requiring global containment strategies. Reverse transcription-polymerase chain reaction is the gold standard for the detection of SARS-CoV-2 infections. Antigen tests, targeting the spike (S) or nucleocapsid (N) viral proteins, are considered as complementary tools. Despite their shortcomings in terms of sensitivity and specificity, antigen tests could be deployed for the detection of potentially contagious individuals with high viral loads. In this work, we sought to develop a sandwich aptamer-based assay for the detection of the S protein of SARS-CoV-2. A detailed study on the binding properties of aptamers to the receptor-binding domain of the S protein in search of aptamer pairs forming a sandwich is presented. Screening of aptamer pairs and optimization of assay conditions led to the development of a laboratory-based sandwich assay able to detect 21 ng/mL (270 pM) of the protein with negligible cross-reactivity with the other known human coronaviruses. The detection of 375 pg of the protein in viral transport medium demonstrates the compatibility of the assay with clinical specimens. Finally, successful detection of the S antigen in nasopharyngeal swab samples collected from suspected patients further establishes the suitability of the assay for screening purposes as a complementary tool to assist in the control of the pandemic.

Dendritic cell deficiencies persist seven months after SARS-CoV-2 infection.

Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV)-2 infection induces an exacerbated inflammation driven by innate immunity components. Dendritic cells (DCs) play a key role in the defense against viral infections, for instance plasmacytoid DCs (pDCs), have the capacity to produce vast amounts of interferon-alpha (IFN-α). In COVID-19 there is a deficit in DC numbers and IFN-α production, which has been associated with disease severity. In this work, we described that in addition to the DC deficiency, several DC activation and homing markers were altered in acute COVID-19 patients, which were associated with multiple inflammatory markers. Remarkably, previously hospitalized and nonhospitalized patients remained with decreased numbers of CD1c+ myeloid DCs and pDCs seven months after SARS-CoV-2 infection. Moreover, the expression of DC markers such as CD86 and CD4 were only restored in previously nonhospitalized patients, while no restoration of integrin ß7 and indoleamine 2,3-dyoxigenase (IDO) levels were observed. These findings contribute to a better understanding of the immunological sequelae of COVID-19.

Validity of Lung Ultrasound: Is an Image Worth More Than a Thousand Sounds?

INTRODUCTION: There is debate as to whether lung-ultrasound (LUS) can replace lung-auscultation (LA) in the assessment of respiratory diseases. METHODOLOGY: The diagnostic validity, safety, and reliability of LA and LUS were analyzed in patients admitted in a pulmonary ward due to decompensated obstructive airway diseases, decompensated interstitial diseases, and pulmonary infections, in a prospective study. Standard formulas were used to calculate the diagnostic sensitivity, specificity, and accuracy. The interobserver agreement with respect to the LA and LUS findings was evaluated based on the Kappa coefficient (ᴋ). RESULTS: A total of 115 patients were studied. LUS was more sensitive than the LA in evaluating pulmonary infections (93.59% vs. 77.02%; p = 0.001) and more specifically in the case of decompensated obstructive airway diseases (95.6% vs. 19.10%; p = 0.001). The diagnostic accuracy of LUS was also greater in the case of pulmonary infections (75.65% vs. 60.90%; p = 0.02). The sensitivity and specificity of the combination of LA and LUS was 95.95%, 50% in pulmonary infections, 76.19%, 100% in case of decompensated obstructive airway diseases, and (100%, 88.54%) in case of interstitial diseases. (ᴋ) was 0.71 for an A-pattern, 0.73 for pathological B-lines, 0.94 for condensations, 0.89 for pleural-effusion, 0.63 for wheezes, 0.38 for rhonchi, 0.68 for fine crackles, 0.18 for coarse crackles, and 0.29 for a normal LA. CONCLUSIONS: There is a greater interobserver agreement in the interpretation of LUS-findings compared to that of LA-noises, their combined use improves diagnostic performance in all diseases examined.

Characterization of COPD Admissions During the First COVID-19 Outbreak.

Purpose: Exacerbations of COPD (ECOPD) are a frequent cause of hospitalization that seemed to ameliorate during the COVID outbreak. We aimed to evaluate the clinical characteristics of COPD-related hospital admissions and mortality in relation to the presence of COVID-19. Patients and Methods: We conducted a case-control study of patients admitted in four teaching hospitals throughout Spain between March 15 and April 30, 2020. Hospital admissions of respiratory cause with and without PCR-proven SARS-CoV-2 infection in patients with COPD were evaluated. Baseline and episode-related clinical characteristics were analyzed. Logistic regression analysis was performed to evaluate the risk for mortality. Results: During the study period, 2101 patients were admitted for respiratory worsening, 1200 (57.1%) with COVID-19. A total of 228 (10.8%) were admitted due to COPD worsening, of whom 52 (22.8%) tested positive for COVID-19. COPD patients with COVID-19, when compared to those without COVID-19, were more frequently males with better lung function (FEV1 postbronchodilator 71% vs 46% respectively, p<0.001) and had higher mortality (44.9% vs 13.6% respectively, p<0.001) despite similar age, comorbidities, total days of hospitalization and admission to intensive care unit. COVID-19 and eosinopenia were the strongest risk factors for mortality in the multivariate analysis in the overall COPD population. Inhaled corticosteroid use was not associated to mortality. Conclusion: Hospitalizations for ECOPD without COVID-19 were more frequent than COPD with COVID-19 during the first outbreak, but the latter were associated with higher mortality and low eosinophil counts that warrant further analysis.

Alterations in Respiratory Function Test Three Months after Hospitalisation for COVID-19 Pneumonia: Value of Determining Nitric Oxide Diffusion.

Three to four months after hospitalisation for COVID-19 pneumonia, the most frequently described alteration in respiratory function tests (RFTs) is decreased carbon monoxide transfer capacity (DLCO). METHODS: This is a prospective cohort study that included patients hospitalised because of SARS-CoV-2 pneumonia, three months after their discharge. A clinical evaluation, analytical parameters, chest X-ray, six-minute walk test, spirometry and DLCO-DLNO analysis were performed. Demographic variables, comorbidities, and variables related to the severity of the admission were recorded. RESULTS: Two hundred patients completed the study; 59.5% men, age 62 years, 15.5% admitted to the intensive care unit. The most frequent functional alteration, in 27% of patients, was in the DLCO-DLNO combination. This alteration was associated with age, male sex, degree of dyspnoea, poorer perception of health, and limited ability for physical effort. These patients also presented higher levels of D-Dimer and more residual radiological alterations. In 42% of the patients with diffusion alterations, only reduced DLNO was presented, along with lower D-Dimer levels and less capillary volume involvement. The severity of the process was associated with the reduction in DLCO-DLNO. CONCLUSIONS: The most sensitive RFT for the detection of the sequelae of COVID-19 pneumonia was the combined measurement of DLCO-DLNO and this factor was related to patient health status and their capacity for physical exertion. In 40% of these cases, there was only a reduction in DLNO, a finding that may indicate less pulmonary vascular involvement.

[Lung Ultrasound to Predict Unfavorable Progress in Patients Hospitalized for COVID-19]. / Predicción de evolución desfavorable en pacientes hospitalizados por COVID-19 mediante ecografía pulmonar.

OBJECTIVE: Thoracic ultrasound has been shown to be useful in the diagnosis of COVID-19 pulmonary involvement. Several scores for quantifying the degree of involvement have been described, although there is no evidence to show that they have any capacity for predicting unfavorable progress. METHODOLOGY: Prospective cohort study of patients hospitalized for COVID-19. The sample was stratified according to clinical course, and patients requiring invasive or non-invasive respiratory support were classified as having unfavorable progress. Biomarkers were analyzed at admission and on the same day that thoracic ultrasound was performed. Prognostic scales were also determined at admission. The ultrasound score was obtained in 8 or 14 areas, depending on the patient's ability to sit. RESULTS: We included 44 patients, 13 (29,5%) of whom subsequently needed ventilatory support. Eight areas were explored in all patients and 14 areas in 35 (79.5%). The most affected areas were the posterior lower lobes. Significant differences were found between the 2 groups on the SOFA and quick SOFA multidimensional scales, and PCR and LDH on the same day as thoracic ultrasound, and the ultrasound scores. The best area under the ROC curve (AUC) was obtained with the 14-area score, with a result of 0.88 (95% CI: 0.75-0.99). Its sensitivity and specificity for a cut-off score of 13.5 were 100% and 61.5%, respectively. CONCLUSIONS: The use of scores to quantify lung involvement measured by thoracic ultrasound provides useful information, facilitating risk stratification in patients hospitalized with COVID-19.

Use of conventional chest imaging and artificial intelligence in covid-19 infection. A review of the literature

ABSTRACT The coronavirus disease caused by SARS-Cov-2 is a pandemic with millions of confirmed cases around the world and a high death toll. Currently, the real-time polymerase chain reaction (RT-PCR) is the standard diagnostic method for determining COVID-19 infection. Various failures in the detection of the disease by means of laboratory samples have raised certain doubts about the characterization of the infection and the spread of contacts.In clinical practice, chest radiography (RT) and chest computed tomography (CT) are extremely helpful and have been widely used in the detection and diagnosis of COVID-19. RT is the most common and widely available diagnostic imaging technique, however, its reading by less qualified personnel, in many cases with work overload, causes a high number of errors to be committed. Chest CT can be used for triage, diagnosis, assessment of severity, progression, and response to treatment. Currently, artificial intelligence (AI) algorithms have shown promise in image classification, showing that they can reduce diagnostic errors by at least matching the diagnostic performance of radiologists.This review shows how AI applied to thoracic radiology speeds up and improves diagnosis, allowing to optimize the workflow of radiologists. It can provide an objective evaluation and achieve a reduction in subjectivity and variability. AI can also help to optimize the resources and increase the efficiency in the management of COVID-19 infection. RESUMEN La enfermedad causada por el coronavirus SARS-Cov-2 es una pandemia con millones de casos confirmados en todo el mundo y un alto número de fallecimientos. Actualmente, la reacción en cadena de la polimerasa en tiempo real (RT-PCR) es el método de diagnóstico estándar para determinar la infección por COVID-19. Diversos fracasos en la detección de la enfermedad por medio de muestras de laboratorio han planteado ciertas dudas sobre la caracterización de la infección y la propagación a los contactos.En la práctica clínica, la radiografía de tórax (RT) y la tomografía computarizada de tórax (TC) son extremadamente útiles y se han utilizado extensamente en la detección y diagnóstico de la COVID-19. La RT es la técnica de diagnóstico por imagen más común y la que está más ampliamente disponible, sin embargo, su lectura por personal menos cualificado, en muchos casos con sobrecarga de trabajo, hace que se cometa un gran número de errores. La tomografía computarizada del tórax se puede utilizar para el triaje, el diagnóstico, la evaluación de la gravedad, la progresión y la respuesta al tratamiento. Actualmente, los algoritmos de inteligencia artificial (IA) han resultado prometedores en la clasificación de imágenes, mostrando que pueden reducir los errores de diagnóstico, como mínimo igualando el rendimiento diagnóstico de los radiólogos.Esta revisión muestra cómo la IA aplicada a la radiología torácica acelera y mejora el diagnóstico, lo que permite optimizar el flujo de trabajo de los radiólogos. Puede proporcionar una evaluación objetiva y lograr una reducción de la subjetividad y la variabilidad. La IA también puede ayudar a optimizar los recursos y aumentar la eficiencia en la gestión de la infección por COVID-19.

Hospital Epidemics Tracker (HEpiTracker): Description and pilot study of a mobile app to track COVID-19 in hospital workers.

BACKGROUND: Hospital workers have been the most frequently and severely affected professional group during the COVID-19 pandemic, and have a big impact on transmission. In this context, innovative tools are required to measure the symptoms compatible with COVID-19, the spread of infection, and testing capabilities within hospitals in real time. OBJECTIVE: We aimed to develop and test an effective and user-friendly tool to identify and track symptoms compatible with COVID-19 in hospital workers. METHODS: We developed and pilot tested Hospital Epidemics Tracker (HEpiTracker), a newly designed app to track the spread of COVID-19 among hospital workers. Hospital staff in 9 hospital centers across 5 Spanish regions (Andalusia, Balearics, Catalonia, Galicia, and Madrid) were invited to download the app on their phones and to register their daily body temperature, COVID-19-compatible symptoms, and general health score, as well as any polymerase chain reaction and serological test results. RESULTS: A total of 477 hospital staff participated in the study between April 8 and June 2, 2020. Of note, both health-related (n=329) and non-health-related (n=148) professionals participated in the study; over two-thirds of participants (68.8%) were health workers (43.4% physicians and 25.4% nurses), while the proportion of non-health-related workers by center ranged from 40% to 85%. Most participants were female (n=323, 67.5%), with a mean age of 45.4 years (SD 10.6). Regarding smoking habits, 13.0% and 34.2% of participants were current or former smokers, respectively. The daily reporting of symptoms was highly variable across participating hospitals; although we observed a decline in adherence after an initial participation peak in some hospitals, other sites were characterized by low participation rates throughout the study period. CONCLUSIONS: HEpiTracker is an already available tool to monitor COVID-19 and other infectious diseases in hospital workers. This tool has already been tested in real conditions. HEpiTracker is available in Spanish, Portuguese, and English. It has the potential to become a customized asset to be used in future COVID-19 pandemic waves and other environments. TRIAL REGISTRATION: ClinicalTrials.gov NCT04326400; https://clinicaltrials.gov/ct2/show/NCT04326400.