Data-driven, cross-disciplinary collaboration: lessons learned at the largest academic health center in Latin America during the COVID-19 pandemic.

Introduction: The COVID-19 pandemic has prompted global research efforts to reduce infection impact, highlighting the potential of cross-disciplinary collaboration to enhance research quality and efficiency. Methods: At the FMUSP-HC academic health system, we implemented innovative flow management routines for collecting, organizing and analyzing demographic data, COVID-related data and biological materials from over 4,500 patients with confirmed SARS-CoV-2 infection hospitalized from 2020 to 2022. This strategy was mainly planned in three areas: organizing a database with data from the hospitalizations; setting-up a multidisciplinary taskforce to conduct follow-up assessments after discharge; and organizing a biobank. Additionally, a COVID-19 curated collection was created within the institutional digital library of academic papers to map the research output. Results: Over the course of the experience, the possible benefits and challenges of this type of research support approach were identified and discussed, leading to a set of recommended strategies to enhance collaboration within the research institution. Demographic and clinical data from COVID-19 hospitalizations were compiled in a database including adults and a minority of children and adolescents with laboratory confirmed COVID-19, covering 2020-2022, with approximately 350 fields per patient. To date, this database has been used in 16 published studies. Additionally, we assessed 700 adults 6 to 11 months after hospitalization through comprehensive, multidisciplinary in-person evaluations; this database, comprising around 2000 fields per subject, was used in 15 publications. Furthermore, thousands of blood samples collected during the acute phase and follow-up assessments remain stored for future investigations. To date, more than 3,700 aliquots have been used in ongoing research investigating various aspects of COVID-19. Lastly, the mapping of the overall research output revealed that between 2020 and 2022 our academic system produced 1,394 scientific articles on COVID-19. Discussion: Research is a crucial component of an effective epidemic response, and the preparation process should include a well-defined plan for organizing and sharing resources. The initiatives described in the present paper were successful in our aim to foster large-scale research in our institution. Although a single model may not be appropriate for all contexts, cross-disciplinary collaboration and open data sharing should make health research systems more efficient to generate the best evidence.

Diagnostic reference level quantities for adult chest and abdomen-pelvis CT examinations: correlation with organ doses.

OBJECTIVES: To evaluate correlations between DRL quantities (DRLq) stratified into patient size groups for non-contrast chest and abdomen-pelvis CT examinations in adult patients and the corresponding organ doses. METHODS: This study presents correlations between DRLq  (CTDIvol, DLP and SSDE) stratified into patient size ranges and corresponding organ doses shared in four groups: inside, peripheral, distributed and outside. The demographic, technical and dosimetric parameters were used to identify the influence of these quantities in organ doses. A robust statistical method was implemented in order to establish these correlations and its statistical significance. RESULTS: Median values of the grouped organ doses are presented according to the effective diameter ranges. Organ doses in the regions inside the imaged area are higher than the organ doses in peripheral, distributed and outside regions, excepted to the peripheral doses associated with chest examinations. Different levels of statistical significance between organ doses and the DRLq were presented. CONCLUSIONS: Correlations between DRLq and target-organ doses associated with clinical practice can support guidance's to the establishment of optimization criteria. SSDE demonstrated to be significant in the evaluation of organ doses is also highlighted. The proposed model allows the design of optimization actions with specific risk-reduction results.

Tomographic pleuropulmonary manifestations in rheumatoid arthritis: a pictorial essay.

Rheumatoid arthritis (RA) is an autoimmune inflammatory and heterogeneous disease that affects several systems, especially the joints. Among the extra-articular manifestations of RA, pleuropulmonary involvement occurs frequently, with different presentations, potentially in all anatomic thoracic compartments, and may determine high morbidity and mortality. The most common pleuropulmonary manifestations in patients with RA include interstitial lung disease (ILD), pleural disease, pulmonary arterial hypertension, rheumatoid lung nodules, airway disease (bronchiectasis and bronchiolitis), and lymphadenopathy. Pulmonary hypertension and ILD are the manifestations with the greatest negative impact in prognosis. HRCT of the chest is essential in the evaluation of patients with RA with respiratory symptoms, especially those with higher risk factors for ILD, such as male gender, smoking, older age, high levels of rheumatoid factor, or positive anti-cyclic citrullinated peptide antibody results. Additionally, other etiologies that may determine tomographic pleuropulmonary manifestations in patients with RA are infections, neoplasms, and drug-induced lung disease. In these scenarios, clinical presentation is heterogeneous, varying from being asymptomatic to having progressive respiratory failure. Knowledge on the potential etiologies causing tomographic pleuropulmonary manifestations in patients with RA coupled with proper clinical reasoning is crucial to diagnose and treat these patients.

Long-term respiratory follow-up of ICU hospitalized COVID-19 patients: Prospective cohort study.

BACKGROUND: Coronavirus disease (COVID-19) survivors exhibit multisystemic alterations after hospitalization. Little is known about long-term imaging and pulmonary function of hospitalized patients intensive care unit (ICU) who survive COVID-19. We aimed to investigate long-term consequences of COVID-19 on the respiratory system of patients discharged from hospital ICU and identify risk factors associated with chest computed tomography (CT) lesion severity. METHODS: A prospective cohort study of COVID-19 patients admitted to a tertiary hospital ICU in Brazil (March-August/2020), and followed-up six-twelve months after hospital admission. Initial assessment included: modified Medical Research Council dyspnea scale, SpO2 evaluation, forced vital capacity, and chest X-Ray. Patients with alterations in at least one of these examinations were eligible for CT and pulmonary function tests (PFTs) approximately 16 months after hospital admission. Primary outcome: CT lesion severity (fibrotic-like or non-fibrotic-like). Baseline clinical variables were used to build a machine learning model (ML) to predict the severity of CT lesion. RESULTS: In total, 326 patients (72%) were eligible for CT and PFTs. COVID-19 CT lesions were identified in 81.8% of patients, and half of them showed mild restrictive lung impairment and impaired lung diffusion capacity. Patients with COVID-19 CT findings were stratified into two categories of lesion severity: non-fibrotic-like (50.8%-ground-glass opacities/reticulations) and fibrotic-like (49.2%-traction bronchiectasis/architectural distortion). No association between CT feature severity and altered lung diffusion or functional restrictive/obstructive patterns was found. The ML detected that male sex, ICU and invasive mechanic ventilation (IMV) period, tracheostomy and vasoactive drug need during hospitalization were predictors of CT lesion severity(sensitivity,0.78±0.02;specificity,0.79±0.01;F1-score,0.78±0.02;positive predictive rate,0.78±0.02; accuracy,0.78±0.02; and area under the curve,0.83±0.01). CONCLUSION: ICU hospitalization due to COVID-19 led to respiratory system alterations six-twelve months after hospital admission. Male sex and critical disease acute phase, characterized by a longer ICU and IMV period, and need for tracheostomy and vasoactive drugs, were risk factors for severe CT lesions six-twelve months after hospital admission.

Lung ultrasound versus chest computed tomography for pregnant inpatients with COVID-19.

PURPOSE: To compare lung ultrasound (US) and computed tomography (CT) in the assessment of pregnant women with COVID-19. METHODS: Prospective study comprising 39 pregnant inpatients with COVID-19 who underwent pulmonary assessment with CT and US with a maximum span of 48 h between the exams. The thorax was divided into 12 regions and assessed in terms of the following: the presence of B-lines (>2), coalescent B-lines, consolidation on US; presence of interlobular thickening, ground glass, consolidation on CT. The two methods were scored by adding up the scores from each thoracic region. RESULTS: A significant correlation was found between the scores obtained by the two methods (rICC = 0.946; p < 0.001). They were moderately in agreement concerning the frequency of altered pulmonary regions (weighted kappa = 0.551). In US, a score over 15, coalescent B-lines, and consolidation were predictors of the need for oxygen, whereas the predictors in CT were a lung score over 16 and consolidation. The two methods, US (p < 0.001; AUC = 0.915) and CT (p < 0.001; AUC = 0.938), were fairly accurate in predicting the need for oxygen. CONCLUSION: In pregnant women, lung US and chest CT are of similar accuracy in assessing lungs affected by COVID-19 and can predict the need for oxygen.

Challenges, Characteristics, and Outcomes of Chronic Pulmonary Aspergillosis: A 11-Year Experience in A Middle-Income Country.

OBJECTIVES: Chronic pulmonary aspergillosis (CPA) is a research priority in fungal diseases with a need for new studies to reduce misdiagnosis with more common diseases, discuss improvement in diagnostic methods and better characterize gaps in antifungal and surgical treatments to improve clinical outcomes. METHODS: In this retrospective study, we reviewed medical records of patients diagnosed with CPA from January 2010 to June 2021 at University of São Paulo, São Paulo, Brazil. We evaluated clinical characteristics, radiological findings, serology, treatment, and outcomes. RESULTS: The study included 91 participants, with 43 (47.3%) patients who underwent surgery and 69 (75.8%) received antifungal therapy. We found a predominance of middle-aged adults (median 51 years), males (n = 58, 64%) with lower BMI (median 21.3 kg/m2). The most common underlying lung disease was pulmonary tuberculosis (n = 70, 76.9%). The commonest symptoms were cough (n = 67, 74%), haemoptysis, and dyspnea (n = 63, 70%). The most common chest computerized tomography abnormalities were cavity (n = 86, 94.5%), with a predominance of mycetomas (n = 78, 91%). The serology was positive in 81% (61/75). The one-year mortality was low (3.3%). Clinical improvement and stability occurred in 89% of participants for constitucional symptoms and 86% for pulmonary symptoms. While serological improvement and stability occurred in 71%. Radiological improvement and stability occurred in 75%. CONCLUSION: We observed a good outcome after 1-year follow-up, in which the majority had improvement or stability of pulmonary and constitutional symptoms, decrease in CIE titers and low mortality.

Sensitivity of Antigen, Serology, and Microbiology Assays for Diagnosis of the Subtypes of Chronic Pulmonary Aspergillosis at a Teaching Hospital in São Paulo, Brazil.

Chronic pulmonary aspergillosis (CPA) is divided into five subtypes. The diagnosis of CPA is complicated due to poor sensitivity of the laboratory tests. Diagnostic performance of different antigen, serological, and microbiological methods in subtypes of CPA is unknown. The purpose of this study was to evaluate the diagnostic performance in different subtypes of CPA. A total of 91 participants with CPA were included, and the study was performed at Hospital das Clínicas of University of São Paulo. Bronchoalveolar lavage galactomannan (73%, 11/15), serology by immunodiffusion test (81%, 61/75), and histology (78%, 39/50) had the best sensitivity. The counterimmunoelectrophoresis (CIE) titers had a significant statistical difference between the CPA subtypes (P < 0.001), in which the forms chronic fibrosing pulmonary aspergillosis (CFPA) and subacute invasive aspergillosis (SAIA) had higher titers: 1/64 (interquartile range [IQR]: 1/32-1/256) and 1/64 (1/32-1/128). C-reactive protein generally presented lower values (median 15 mg/L, IQR: 6-33), with higher values in SAIA and lower values for Aspergillus nodule. Overall, we found a low diagnostic sensitivity of current tests. Regarding the CPA subtypes, we did not find great differences in the performance of the tests, but it is observed that the inflammatory markers and CIE titers tend to be higher in forms of the more extensive lung parenchyma involvement, such as SAIA and CFPA.

Tomographic pleuropulmonary manifestations in rheumatoid arthritis: a pictorial essay / Manifestações pleuropulmonares tomográficas na artrite reumatoide: ensaio pictórico

ABSTRACT Rheumatoid arthritis (RA) is an autoimmune inflammatory and heterogeneous disease that affects several systems, especially the joints. Among the extra-articular manifestations of RA, pleuropulmonary involvement occurs frequently, with different presentations, potentially in all anatomic thoracic compartments, and may determine high morbidity and mortality. The most common pleuropulmonary manifestations in patients with RA include interstitial lung disease (ILD), pleural disease, pulmonary arterial hypertension, rheumatoid lung nodules, airway disease (bronchiectasis and bronchiolitis), and lymphadenopathy. Pulmonary hypertension and ILD are the manifestations with the greatest negative impact in prognosis. HRCT of the chest is essential in the evaluation of patients with RA with respiratory symptoms, especially those with higher risk factors for ILD, such as male gender, smoking, older age, high levels of rheumatoid factor, or positive anti-cyclic citrullinated peptide antibody results. Additionally, other etiologies that may determine tomographic pleuropulmonary manifestations in patients with RA are infections, neoplasms, and drug-induced lung disease. In these scenarios, clinical presentation is heterogeneous, varying from being asymptomatic to having progressive respiratory failure. Knowledge on the potential etiologies causing tomographic pleuropulmonary manifestations in patients with RA coupled with proper clinical reasoning is crucial to diagnose and treat these patients.

RESUMO A artrite reumatoide (AR) é uma doença inflamatória autoimune e heterogênea que afeta vários sistemas, principalmente as articulações. Dentre as manifestações extra-articulares da AR, o acometimento pleuropulmonar ocorre com frequência, com diferentes apresentações, potencialmente em todos os compartimentos anatômicos do tórax e pode determinar alta morbidade e mortalidade. As manifestações pleuropulmonares mais comuns em pacientes com AR incluem doença pulmonar intersticial (DPI), doença pleural, hipertensão arterial pulmonar, nódulos pulmonares reumatoides, doença das vias aéreas (bronquiectasia e bronquiolite) e linfadenopatia. A hipertensão pulmonar e a DPI são as manifestações com maior impacto negativo no prognóstico. A TCAR de tórax é essencial na avaliação de pacientes com AR sintomáticos respiratórios, principalmente aqueles com fatores de risco maiores para DPI, como sexo masculino, tabagismo, idade mais avançada, níveis elevados de fator reumatoide ou anticorpos antipeptídeos citrulinados cíclicos positivos. Além disso, outras etiologias que podem determinar manifestações pleuropulmonares tomográficas em pacientes com AR são infecções, neoplasias e doença pulmonar induzida por drogas. Nesses cenários, a apresentação clínica é heterogênea, variando de ausência de sintomas a insuficiência respiratória progressiva. O conhecimento das possíveis etiologias causadoras de manifestações pleuropulmonares tomográficas em pacientes com AR, aliado a um raciocínio clínico adequado, é fundamental para o diagnóstico e tratamento desses pacientes.

Chronic lung lesions in COVID-19 survivors: predictive clinical model.

OBJECTIVE: This study aimed to propose a simple, accessible and low-cost predictive clinical model to detect lung lesions due to COVID-19 infection. DESIGN: This prospective cohort study included COVID-19 survivors hospitalised between 30 March 2020 and 31 August 2020 followed-up 6 months after hospital discharge. The pulmonary function was assessed using the modified Medical Research Council (mMRC) dyspnoea scale, oximetry (SpO2), spirometry (forced vital capacity (FVC)) and chest X-ray (CXR) during an in-person consultation. Patients with abnormalities in at least one of these parameters underwent chest CT. mMRC scale, SpO2, FVC and CXR findings were used to build a machine learning model for lung lesion detection on CT. SETTING: A tertiary hospital in Sao Paulo, Brazil. PARTICIPANTS: 749 eligible RT-PCR-confirmed SARS-CoV-2-infected patients aged ≥18 years. PRIMARY OUTCOME MEASURE: A predictive clinical model for lung lesion detection on chest CT. RESULTS: There were 470 patients (63%) that had at least one sign of pulmonary involvement and were eligible for CT. Almost half of them (48%) had significant pulmonary abnormalities, including ground-glass opacities, parenchymal bands, reticulation, traction bronchiectasis and architectural distortion. The machine learning model, including the results of 257 patients with complete data on mMRC, SpO2, FVC, CXR and CT, accurately detected pulmonary lesions by the joint data of CXR, mMRC scale, SpO2 and FVC (sensitivity, 0.85±0.08; specificity, 0.70±0.06; F1-score, 0.79±0.06 and area under the curve, 0.80±0.07). CONCLUSION: A predictive clinical model based on CXR, mMRC, oximetry and spirometry data can accurately screen patients with lung lesions after SARS-CoV-2 infection. Given that these examinations are highly accessible and low cost, this protocol can be automated and implemented in different countries for early detection of COVID-19 sequelae.

Clinical, radiological, and transbronchial biopsy findings in patients with long COVID-19: a case series.

This brief communication demonstrates the correlation of persistent respiratory symptoms with functional, tomographic, and transbronchial pulmonary biopsy findings in patients with COVID-19 who had a long follow-up period. We report a series of six COVID-19 patients with pulmonary involvement who presented with persistent dyspnea within 4-15 months of discharge. We performed transbronchial biopsies, and the histopathological pattern consistently demonstrated peribronchial remodeling with interstitial pulmonary fibrosis. Therefore, lung biopsy may be useful in the approach of patients with long COVID-19, although the type of procedure, its precise indication, and the moment to perform it are yet to be clarified. (Brazilian Registry of Clinical Trials-ReBEC; identifier: RBR-8j9kqy [http://www.ensaiosclinicos.gov.br]).

Post-acute sequelae of SARS-CoV-2 infection: relationship of central nervous system manifestations with physical disability and systemic inflammation.

BACKGROUND: Despite the multitude of clinical manifestations of post-acute sequelae of SARS-CoV-2 infection (PASC), studies applying statistical methods to directly investigate patterns of symptom co-occurrence and their biological correlates are scarce. METHODS: We assessed 30 symptoms pertaining to different organ systems in 749 adults (age = 55 ± 14 years; 47% female) during in-person visits conducted at 6-11 months after hospitalization due to coronavirus disease 2019 (COVID-19), including six psychiatric and cognitive manifestations. Symptom co-occurrence was initially investigated using exploratory factor analysis (EFA), and latent variable modeling was then conducted using Item Response Theory (IRT). We investigated associations of latent variable severity with objective indices of persistent physical disability, pulmonary and kidney dysfunction, and C-reactive protein and D-dimer blood levels, measured at the same follow-up assessment. RESULTS: The EFA extracted one factor, explaining 64.8% of variance; loadings were positive for all symptoms, and above 0.35 for 16 of them. The latent trait generated using IRT placed fatigue, psychiatric, and cognitive manifestations as the most discriminative symptoms (coefficients > 1.5, p < 0.001). Latent trait severity was associated with decreased body weight and poorer physical performance (coefficients > 0.240; p ⩽ 0.003), and elevated blood levels of C-reactive protein (coefficient = 0.378; 95% CI 0.215-0.541; p < 0.001) and D-dimer (coefficient = 0.412; 95% CI 0.123-0.702; p = 0.005). Results were similar after excluding subjects with pro-inflammatory comorbidities. CONCLUSIONS: Different symptoms that persist for several months after moderate or severe COVID-19 may unite within one latent trait of PASC. This trait is dominated by fatigue and psychiatric symptoms, and is associated with objective signs of physical disability and persistent systemic inflammation.

A Convolutional Neural Network Approach to Quantify Lung Disease Progression in Patients with Fibrotic Hypersensitivity Pneumonitis (HP).

Rationale and Objectives To evaluate associations between longitudinal changes of quantitative CT parameters and spirometry in patients with fibrotic hypersensitivity pneumonitis (HP). Materials and Methods Serial CT images and spirometric data were retrospectively collected in a group of 25 fibrotic HP patients. Quantitative CT analysis included histogram parameters (median, interquartile range, skewness, and kurtosis) and a pretrained convolutional neural network (CNN)-based textural analysis, aimed at quantifying the extent of consolidation (C), fibrosis (F), ground-glass opacity (GGO), low attenuation areas (LAA) and healthy tissue (H). Results At baseline, FVC was 61(44-70) %pred. The median follow-up period was 1.4(0.8-3.2) years, with 3(2-4) visits per patient. Over the study, 8 patients (32%) showed a FVC decline of more than 5%, a significant worsening of all histogram parameters (p≤0.015) and an increased extent of fibrosis via CNN (p=0.038). On histogram analysis, decreased skewness and kurtosis were the parameters most strongly associated with worsened FVC (respectively, r2=0.63 and r2=0.54, p<0.001). On CNN classification, increased extent of fibrosis and consolidation were the measures most strongly correlated with FVC decline (r2=0.54 and r2=0.44, p<0.001). Conclusion CT histogram and CNN measurements provide sensitive measures of functional changes in fibrotic HP patients over time. Increased fibrosis was associated with FVC decline, providing index of disease progression. CNN may help improve fibrotic HP follow-up, providing a sensitive tool for progressive interstitial changes, which can potentially contribute to clinical decisions for individualizing disease management.

Quantitative CT Analysis in Chronic Hypersensitivity Pneumonitis: A Convolutional Neural Network Approach.

RATIONALE AND OBJECTIVES: Chronic hypersensitivity pneumonitis (cHP) is a heterogeneous condition, where both small airway involvement and fibrosis may simultaneously occur. Computer-aided analysis of CT lung imaging is increasingly used to improve tissue characterization in interstitial lung diseases (ILD), quantifying disease extension, and progression. We aimed to quantify via a convolutional neural network (CNN) method the extent of different pathological classes in cHP, and to determine their correlation to pulmonary function tests (PFTs) and mosaic attenuation pattern. MATERIALS AND METHODS: The extension of six textural features, including consolidation (C), ground glass opacity (GGO), fibrosis (F), low attenuation areas (LAA), reticulation (R) and healthy regions (H), was quantified in 27 cHP patients (age: 56 ± 11.5 years, forced vital capacity [FVC]% = 57 ± 17) acquired at full-inspiration via HRCT. Each class extent was correlated to PFTs and to mosaic attenuation pattern. RESULTS: H showed a positive correlation with FVC%, FEV1% (forced expiratory volume), total lung capacity%, and diffusion of carbon monoxide (DLCO)% (r = 0.74, r = 0.78, r = 0.73, and r = 0.60, respectively, p < 0.001). GGO, R and C negatively correlated with FVC% and FEV1% with the highest correlations found for R (r = -0.44, and r = -0.46 respectively, p < 0.05); F negatively correlated with DLCO% (r = -0.42, p < 0.05). Patients with mosaic attenuation pattern had significantly more H (p = 0.04) and lower R (p = 0.02) and C (p = 0.0009) areas, and more preserved lung function indices (higher FVC%; p = 0.04 and DLCO%; p = 0.05), but did not show more air trapping in lung function tests. CONCLUSION: CNN quantification of pathological tissue extent in cHP improves its characterization and shows correlation with PFTs. LAA can be overestimated by visual, qualitative CT assessment and mosaic attenuation pattern areas in cHP represents patchy ILD rather than small-airways disease.