Tele-Intensive Care Unit Program in Brazil: Implementation and Expansion.

In this scientific report, we aimed to describe the implementation and expansion of a Tele-Intensive Care Unit (Tele-ICU) program in Brazil, highlighting the pillars of success, improvements, and perspectives. Tele-ICU program emerged during the COVID-19 pandemic at the Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP), focusing on clinical case discussions and training of health practitioners in public hospitals of the state of São Paulo in Brazil, to support health care professionals for treating COVID-19 patients. The success of implementing this initiative endorsed the project expansion to other five hospitals from different macroregions of the country, leading to the Tele-ICU-Brazil. These projects assisted 40 hospitals, allowing more than 11,500 teleinterconsultations (exchange of medical information between health care professionals using a licensed online platform) and training more than 14,800 health care professionals, reducing mortality and length of hospitalized patients. A segment in telehealth for the obstetrics health care was implemented after detecting these were a susceptible group of patients to COVID-19 severity. As a perspective, this segment will be expanded to 27 hospitals in the country. The Tele-ICU projects reported here were the largest digital health ICU programs ever established in Brazilian National Health System until know. Their results were unprecedented and proved to be crucial for supporting health care professionals nationwide during the COVID-19 pandemic and guide future initiatives in digital health in Brazil's National Health System.

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.

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.

Post-acute sequelae of SARS-CoV-2 infection (PASC): a protocol for a multidisciplinary prospective observational evaluation of a cohort of patients surviving hospitalisation in Sao Paulo, Brazil.

INTRODUCTION: COVID-19 may lead to persistent and potentially incapacitating clinical manifestations (post-acute sequelae of SARS-CoV-2 infection (PASC)). Using easy-to-apply questionnaires and scales (often by telephone interviewing), several studies evaluated samples of COVID-19 inpatients from 4 weeks to several months after discharge. However, studies conducting systematic multidisciplinary assessments of PASC manifestations are scarce, with thorough in-person objective evaluations restricted to modestly sized subsamples presenting greatest disease severity. METHODS AND ANALYSES: We will conduct a prospective observational study of surviving individuals (above 18 years of age) from a cohort of over 3000 subjects with laboratory-confirmed COVID-19 who were treated as inpatients at the largest academic health centre in Sao Paulo, Brazil (Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo). All eligible subjects will be consecutively invited to undergo a 1-2-day series of multidisciplinary assessments at 2 time-points, respectively, at 6-9 months and 12-15 months after discharge. Assessment schedules will include detailed multidomain questionnaires applied by medical research staff, self-report scales, objective evaluations of cardiopulmonary functioning, physical functionality and olfactory status, standardised neurological, psychiatric and cognitive examinations, as well as diagnostic laboratory, muscle ultrasound and chest imaging exams. Remaining material from blood tests will be incorporated by a local biobank for use in future investigations on inflammatory markers, genomics, transcriptomics, peptidomics and metabolomics. ETHICS AND DISSEMINATION: All components of this programme have been approved by local research ethics committees. We aim to provide insights into the frequency and severity of chronic/post-COVID multiorgan symptoms, as well as their interrelationships and associations with acute disease features, sociodemographic variables and environmental exposures. Findings will be disseminated in peer-reviewed journals and at scientific meetings. Additionally, we aim to provide a data repository to allow future pathophysiological investigations relating clinical PASC features to biomarker data extracted from blood samples. TRIAL REGISTRATION NUMBER: RBR-8z7v5wc; Pre-results.