Impact of COVID-19 on healthcare-associated infections: Antimicrobial consumption does not follow antimicrobial resistance.

BACKGROUND: This study aimed to analyze the Healthcare-Associated Infections (HAI) rates and antimicrobial consumption in Intensive Care Units (ICU) in São Paulo city during the COVID-19 pandemic and compare them with the pre-pandemic period. METHODS: This cohort included all hospitals that reported HAI rates (Central-Line-Associated Bloodstream Infection ‒ CLABSI and Ventilator-Associated Pneumonia ‒ VAP), the proportion of microorganisms that caused CLABSI, the proportion of resistant microorganisms, and antimicrobial consumption from January 2017 ‒ December 2020. Hospitals were stratified by the number of beds, Central Venous Catheter (CVC) utilization rate, Mechanical-Ventilation (MV) utilization rate, and type of funding. Statistical analyses were based on time-series plots and regression models. RESULTS: 220 ICUs were included. The authors observed an abrupt increase in CLABSI rates after the pandemic onset. High CLABSI rates during the pandemic were associated with hospital size, funding (public and non-profit private), and low CVC use (≤ 50%). An increase in VAP rates was associated with public hospitals, and high MV use (> 35%). The susceptibility profile of microorganisms did not differ from that of the pre-pandemic period. polymyxin, glycopeptides, and antifungal use increased, especially in COVID-19 ICUs. CONCLUSIONS: HAI increased during COVID-19. The microorganisms' susceptibility profile did not change with the pandemic, but the authors observed a disproportionate increase in large-spectrum antimicrobial drug use.

Risk factors for reduction in adherence to protective measures following coronavirus disease 2019 (COVID-19) vaccination and vaccine perceptions among healthcare workers, in São Paulo, Brazil.

A survey evaluated 2,300 healthcare workers following the first dose of a coronavirus disease 2019 (COVID-19) vaccine in a tertiary-quaternary hospital in São Paulo, Brazil. Adherence to protective measures following vaccination was compared to previous non-work-related behaviors. Younger age, previous COVID-19, and burnout symptoms were associated with reduced adherence to mitigation measures.

Healthcare-associated infections on the ICU in 21 Brazilian hospitals during the early months of the COVID-19 pandemic: an ecological study.

OBJECTIVE: The COVID-19 pandemic has caused a global health crisis and may have affected healthcare-associated infections (HAI) prevention strategies. This study aims to evaluate the impact of the COVID-19 pandemic on HAI incidence in Brazilian ICUs. METHODS: This ecological study compared adult patients admitted to the ICU from April through June 2020 (pandemic period) with the same period in 2019 (pre-pandemic period) in 21 Brazilian hospitals. The difference in microbiologically confirmed central line-associated bloodstream infection (CLABSI) and ventilator-associated pneumonia (VAP) incidence density (cases per 1,000 patient days), the proportion of organisms that caused HAI, and antibiotic consumption (DDD) between the pandemic and the pre pandemic periods were compared in a pairwise analysis using the Wilcoxon signed rank sum test. RESULTS: We observed a significant increase in median CLABSI incidence during the pandemic (1.60 [0.44-4.20] vs. 2.81 [1.35-6.89], p = 0.002). There was no difference in VAP incidence between the two periods. In addition, there was a significant increase in the proportion of CLABSI caused by Enterococcus faecalis and Candida species during the pandemic, although only the latter retained statistical significance after correction for multiple comparisons. There was no significant change in ceftriaxone, piperacillin/tazobactam, meropenem, or vancomycin consumption between the studied periods. CONCLUSIONS: There was an increase in CLABSI incidence in Brazilian ICUs during the first months of COVID-19 pandemic. Additionally, we observed an increase in the proportion of CLABSI caused by E. faecalis and Candida species in this period. CLABSI prevention strategies must be reinforced in ICUs during the COVID-19 pandemic.

Fundamental frequency related parameters in Brazilians with COVID-19.

This study compares fundamental frequency (fo) and fundamental frequency standard deviation (foSD) of COVID-19 patients with the same parameters in the speech of subjects without COVID-19, and verifies whether there is an effect of age and sex in the patient group. Both groups, subjects with and without COVID-19, are formed by Brazilian Portuguese speakers. Speech samples were obtained from 100 patients with mild to severe symptoms of COVID-19, and 100 healthy subjects. A single 31-syllable Portuguese sentence was used as the elicitation material for all subjects. The recordings were divided into four age groups. The acoustic measures were semi-automatically extracted and analyzed by a series of analyses of variance. Patients with COVID-19 present vocal differences in fo-related parameters when compared to healthy subjects, that is, patient voices presented higher fo and foSD with respect to control voices. In addition, for patient voices, there was an age and sex effect on fo SD values. Vocal parameters of women and elderly subjects showed more marked differences in fo-related parameters, indicating that patient voices are higher-pitched and have a higher variation of fo SD. Consequently, fo-related parameters may be tested as vocal biomarkers in the screening of respiratory insufficiency by voice analysis, in patients with severe symptoms of COVID-19.

Reinfection rate in a cohort of healthcare workers over 2 years of the COVID-19 pandemic.

In this large cohort of healthcare workers, we aimed to estimate the rate of reinfections by SARS-CoV-2 over 2 years of the COVID-19 pandemic. We investigated the proportion of reinfections among all the cases of SARS-CoV-2 infection from March 10, 2020 until March 10, 2022. Reinfection was defined as the appearance of new symptoms that on medical evaluation were suggestive of COVID-19 and confirmed by a positive RT-PCR. Symptoms had to occur more than 90 days after the previous infection. These 2 years were divided into time periods based on the different variants of concern (VOC) in the city of São Paulo. There were 37,729 medical consultations due to COVID-19 at the hospital's Health Workers Services; and 25,750 RT-PCR assays were performed, of which 23% (n = 5865) were positive. Reinfection by SARS-CoV-2 was identified in 5% (n = 284) of symptomatic cases. Most cases of reinfection occurred during the Omicron period (n = 251; 88%), representing a significant increase on the SARS-CoV-2 reinfection rate before and during the Omicron variant period (0.8% vs. 4.3%; p < 0.001). The mean interval between SARS-CoV-2 infections was 429 days (ranged from 122 to 674). The Omicron variant spread faster than Gamma and Delta variant. All SARS-CoV-2 reinfections were mild cases.

Evaluation of eleven immunochromatographic assays for SARS-CoV-2 detection: investigating the dengue cross-reaction.

COVID-19 disease is spread worldwide and diagnostic techniques have been studied in order to contain the pandemic. Immunochromatographic (IC) assays are feasible and a low-cost alternative especially in low and middle-income countries, which lack structure to perform certain diagnostic techniques. Here we evaluate the sensitivity and specificity of eleven different IC tests in 145 serum samples from confirmed cases of COVID-19 using RT-PCR and 100 negative serum samples from blood donors collected in February 2019. We also evaluated the cross-reactivity with dengue using 20 serum samples from patients with confirmed diagnosis for dengue collected in early 2019 through four different tests. We found high sensitivity (92%), specificity (100%) and an almost perfect agreement (Kappa 0.92) of IC assay, especially when we evaluated IgG and IgM combined after 10 days from the onset of symptoms with RT-PCR. However, we detected cross-reactivity between dengue and COVID-19 mainly with IgM antibodies (5 to 20% of cross-reaction) and demonstrated the need for better studies about diagnostic techniques for these diseases.

Characterization of Severe Acute Respiratory Syndrome Coronavirus 2 Omicron Variant Shedding and Predictors of Viral Culture Positivity on Vaccinated Healthcare Workers With Mild Coronavirus Disease 2019.

In this prospective cohort of 30 vaccinated healthcare workers with mild Omicron variant infection, we evaluated viral culture, rapid antigen test (RAT), and real-time reverse-transcription polymerase chain reaction (RT-PCR) of respiratory samples at days 5, 7, 10, and 14. Viral culture was positive in 46% (11/24) and 20% (6/30) of samples at days 5 and 7, respectively. RAT and RT-PCR (Ct ≤35) showed 100% negative predictive value (NPV), with positive predictive values (PPVs) of 32% and 17%, respectively, for predicting viral culture positivity. A lower RT-PCR threshold (Ct ≤24) improved culture prediction (PPV = 39%; NPV = 100%). Vaccinated persons with mild Omicron infection are potentially transmissible up to day 7. RAT and RT-PCR might be useful tools for shortening the isolation period.

The health facility as a risk factor for multidrug-resistant gram-negative bacteria in critically ill patients with COVID-19.

BACKGROUND: The relationship between Multidrug Resistant-Gram Negative Bacteria (MDR-GNB) infection and colonization in critically ill COVID-19 patients has been observed, however, it is still poorly understood. This study evaluated the risk factors for acquiring MDR-GNB in patients with severe COVID-19 in Intensive Care Units (ICU). METHODS: This is a nested case-control study in a cohort of 400 adult patients (≥ 18 years old) with COVID-19, hospitalized in the ICU of 4 hospitals in the city of Curitiba, Brazil. Cases were critical COVID-19 patients with one or more MDR GNB from any surveillance and/or clinical cultures were taken during their ICU stay. Controls were patients from the same units with negative cultures for MDR-GNB. Bivariate and multivariate analyses were done. RESULTS: Sixty-seven cases and 143 controls were included. Independent risk factors for MDR bacteria were: male gender (OR = 2.6; 95% CI 1.28‒5.33; p = 0.008); the hospital of admission (OR = 3.24; 95% CI 1.39‒7.57; p = 0.006); mechanical ventilation (OR = 25.7; 95% CI 7.26‒91; p < 0.0001); and desaturation on admission (OR = 2.6; 95% CI 1.27‒5.74; p = 0.009). CONCLUSIONS: Male gender, desaturation, mechanical ventilation, and the hospital of admission were the independent factors associated with MDR-GNB in patients in the ICU with COVID-19. The only modifiable factor was the hospital of admission, where a newly opened hospital posed a higher risk. Therefore, coordinated actions toward a better quality of care for critically ill COVID-19 patients are essential.

Mortality over time among COVID-19 patients hospitalized during the first surge of the pandemic: A large cohort study.

BACKGROUND: Capacity strain negatively impacts patient outcome, and the effects of patient surge are a continuous threat during the COVID-19 pandemic. Evaluating changes in mortality over time enables evidence-based resource planning, thus improving patient outcome. Our aim was to describe baseline risk factors associated with mortality among COVID-19 hospitalized patients and to compare mortality rates over time. METHODS: We conducted a retrospective cohort study in the largest referral hospital for COVID-19 patients in Sao Paulo, Brazil. We investigated risk factors associated with mortality during hospitalization. Independent variables included age group, sex, the Charlson Comorbidity Index, admission period according to the stage of the first wave of the epidemic (early, peak, and late), and intubation. RESULTS: We included 2949 consecutive COVID-19 patients. 1895 of them were admitted to the ICU, and 1473 required mechanical ventilation. Median length of stay in the ICU was 10 (IQR 5-17) days. Overall mortality rate was 35%, and the adjusted odds ratios for mortality increased with age, male sex, higher Charlson Comorbidity index, need for mechanical ventilation, and being admitted to the hospital during the wave peak of the epidemic. Being admitted to the hospital during the wave peak was associated with a 33% higher risk of mortality. CONCLUSIONS: In-hospital mortality was independently affected by the epidemic period. The recognition of modifiable operational variables associated with patient outcome highlights the importance of a preparedness plan and institutional protocols that include evidence-based practices and allocation of resources.

Correlating drug prescriptions with prognosis in severe COVID-19: first step towards resource management.

BACKGROUND: Optimal COVID-19 management is still undefined. In this complicated scenario, the construction of a computational model capable of extracting information from electronic medical records, correlating signs, symptoms and medical prescriptions, could improve patient management/prognosis. METHODS: The aim of this study is to investigate the correlation between drug prescriptions and outcome in patients with COVID-19. We extracted data from 3674 medical records of hospitalized patients: drug prescriptions, outcome, and demographics. The outcome evaluated was hospital outcome. We applied correlation analysis using a Logistic Regression algorithm for machine learning with Lasso and Matthews correlation coefficient. RESULTS: We found correlations between drugs and patient outcomes (death/discharged alive). Anticoagulants, used very frequently during all phases of the disease, were associated with good prognosis only after the first week of symptoms. Antibiotics very frequently prescribed, especially early, were not correlated with outcome, suggesting that bacterial infections may not be important in determining prognosis. There were no differences between age groups. CONCLUSIONS: In conclusion, we achieved an important result in the area of Artificial Intelligence, as we were able to establish a correlation between concrete variables in a real and extremely complex environment of clinical data from COVID-19. Our results are an initial and promising contribution in decision-making and real-time environments to support resource management and forecasting prognosis of patients with COVID-19.

Understanding the Potential Impact of Different Drug Properties on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Transmission and Disease Burden: A Modelling Analysis.

BACKGROUND: The public health impact of the coronavirus disease 2019 (COVID-19) pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. METHODS: Using a mathematical model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care. RESULTS: The impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R = 1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalization) could have much greater benefits, particularly in resource-poor settings facing large epidemics. CONCLUSIONS: Advances in the treatment of COVID-19 to date have been focused on hospitalized-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority.

CARACTERIZAÇÃO DA INFECTIVIDADE DA VARIANTE ÔMICRON E PREDITORES DE POSITIVIDADE DE CULTURA VIRAL EM PROFISSIONAIS DE SAÚDE COM COVID-19 LEVE

Introdução A variante Ômicron do vírus SARS-CoV-2 (B.1.1.529) foi designada uma variante preocupante (VOC) devido à alta transmissibilidade e capacidade de escapar da imunidade natural e induzida por vacina. Objetivo Caracterizar a duração da infectividade da variante Ômicron em indivíduos vacinados com sintomas leves de COVID-19. Método Estudo transversal com 30 indivíduos vacinados com COVID-19 para avaliar a duração da infectividade da Ômicron comparando o isolamento viral com o teste rápido de antígeno (RAT) e os valores de Ct da reação em cadeia da polimerase em tempo real (RT-PCR) de amostras respiratórias nos dias 5, 7, 10 e 14 a partir do início dos sintomas. Resultados O crescimento viral foi observado em 46% (11/24) das amostras dos indivíduos vacinados no dia 5 dos sintomas e 20% (6/30) no dia 7, nenhuma amostra teve isolamento viral no dia 10. A carga de RNA viral permaneceu detectável em 97% (29/30) e 57% (17/30) dos participantes nos dias 10 e 14, respectivamente. Entre as amostras com isolamento viral, todas (n = 17) foram RAT e RT-PCR positivas. Por outro lado, amostras sem isolamento viral (n = 97) foram RAT e RT-PCR positivas em 36 (37%) e 83 (86%), respectivamente. RAT e RT-PCR evidenciaram sensibilidade global e valores preditivos negativos de 100%, porém, RAT apresentou 63% de especificidade global e 32% de valor preditivo positivo (VPP), enquanto RT-PCR evidenciou menor especificidade (14%) e VPP (17%) para predizer a infectividade. Conclusão Indivíduos vacinados imunocompetentes com infecção por Ômicron ainda podem transmitir o vírus no 7° dia de sintomas, portanto, é altamente improvável que estejam transmitindo o vírus infeccioso no dia 10. Testes rápidos de antígeno podem ser usados para estimar a duração da infectividade dos casos de Ômicron. Ag. Financiadora Instituto todos pela saúde do Banco Itaú.

PREDITORES DE PROTEÇÃO CONTRA INFECÇÃO POR SARS-COV-2 APÓS DUAS DOSES DE CORONAVAC EM UMA COORTE DE PROFISSIONAIS DE SAÚDE

Introdução A elucidação dos preditores de proteção contra infecção pelo SARS-CoV-2 após a vacinação contra o mesmo pode auxiliar no controle da pandemia. Objetivo Identificar fatores de proteção contra infecção por SARS-CoV-2 após recebimento de duas doses de CoronaVac. Método Trata-se de uma coorte prospectiva de profissionais de saúde (PS) do HC-FMUSP vacinados com 2 doses da CoronaVac. O desfecho avaliado foi infecção pelo SARS-CoV-2 (confirmada por RT-PCR) desde 10 semanas após a segunda dose da vacina até pararem de trabalhar no HC-FMUSP ou até a data 08/03/2022. A infecção pelo SARS-CoV-2 foi verificada através dos registros do Centro de Atendimento ao Colaborador (CEAC) e do Núcleo de Vigilância Epidemiológica (NUVE) do HCFMUSP e através de entrevistas aos participantes do estudo. Os PS foram submetidos a sorologia para o SARS-CoV-2 para detecção de IgG anti-S (Liaison®/DiaSorin). Fatores de proteção contra infecção pelo SARS-CoV-2 foram avaliados com modelos de regressão de Cox. Os participantes assinaram um TCLE antes de ingressarem no estudo e o projeto foi aprovado no CEP do HC-FMUSP. Resultados Entre a 2ª e a 3ª dose da vacina, 3.979 PS foram avaliados. A idade mediana foi 44 anos e 79% era do sexo feminino. Casos de COVID-19 antes da 1ª dose da vacina foram detectados em 18% dos participantes. Sorologia reagente (título ≥ 33,8) foi detectada em 90% dos participantes em um teste realizado 10 semanas após a 2ª dose da vacina e houve 247 (6%) casos de COVID-19 entre a coleta desta sorologia e o recebimento da 3ª dose da vacina. Fatores de proteção contra infecção pelo SARS-CoV-2 neste período foram: diagnóstico de COVID-19 antes da 1ª dose da vacina (adjHR = 0,35), sorologia reagente coletada 10 semanas após 2ª dose da vacina (adjHR = 0,50) e idade entre 50-70 anos (adjHR = 0,52). Após a 3ª dose da vacina, 1305 PS foram avaliados. Sorologia reagente foi detectada em 99,8% dos participantes em um teste realizado 8 semanas após a 3ª dose da vacina e houve 159 (12%) casos de COVID-19 entre a coleta desta sorologia e o término do seguimento. Fatores de proteção contra infecção pelo SARS-CoV-2 no período foram: diagnóstico de COVID-19 antes da 3ª dose da vacina (adjHR = 0,57) e altos títulos da sorologia coletada 8 semanas após a terceira dose da vacina (adjHR = 0,99). Conclusão Diagnóstico prévio de COVID-19 e altos títulos de IgG contra o SARS-CoV-2 8-10 semanas após a vacinação são fatores protetores de infecção pelo SARS-CoV-2 em PS vacinados com CoronaVac. Ag. Financiadora: Instituto todos pela saúde. Nr. Processo: C1864.

Personal protective equipment implementation in healthcare: A scoping review.

BACKGROUND: Adherence to infection prevention and control (IPC) measures, including the proper use of protective personal equipment (PPE), in health care is complex and is influenced by many factors. Isolated interventions do not have the potential to achieve optimal PPE adherence and appropriate provision, leading to incomplete PPE implementation. OBJECTIVE: To map PPE implementation in health care with a focus on its barriers and facilitators. METHODS: A scoping review was conducted across 14 electronic databases using the Joanna Briggs Institute methodology. RESULTS: Seventy-four papers were included in the review. Findings were analyzed and synthesized into categories to match the Consolidated Framework for Implementation Research domains. The content was then synthesized into barriers for PPE implementation and interventions to address them. The main barriers were discomfort in clinical work; shortage, supply and logistics problems; inadequacies in facilities infrastructure, weakness in policies and communication procedures; and health workers' (HW) psychological issues and lack of preparedness. Implementation interventions reported were related to HW wellbeing assurance; work reorganization; IPC protocols; adoption of strategies to improve communication and HW training; and adoption of structural and organizational changes to improve PPE adherence. CONCLUSIONS: PPE implementation, which is critical IPC programs, involves multilevel transdisciplinary complexity. It relies on the development of context-driven implementation strategies to inform and harmonize IPC policy in collaboration with local and international health bodies.

Clinical, sociodemographic and environmental factors impact post-COVID-19 syndrome.

Background: Sociodemographic and environmental factors are associated with incidence, severity, and mortality of COVID-19. However, little is known about the role of such factors in persisting symptoms among recovering patients. We designed a cohort study of hospitalized COVID-19 survivors to describe persistent symptoms and identify factors associated with post-COVID-19 syndrome. Methods: We included patients hospitalized between March to August 2020 who were alive six months after hospitalization. We collected individual and clinical characteristics during hospitalization and at follow-up assessed ten symptoms with standardized scales, 19 yes/no symptoms, a functional status and a quality-of-life scale and performed four clinical tests. We examined individual exposure to greenspace and air pollution and considered neighbourhood´s population density and socioeconomic conditions as contextual factors in multilevel regression analysis. Results: We included 749 patients with a median follow-up of 200 (IQR = 185-235) days, and 618 (83%) had at least one of the ten symptoms measured with scales. Pain (41%), fatigue (38%) and posttraumatic stress disorder (35%) were the most frequent. COVID-19 severity, comorbidities, BMI, female sex, younger age, and low socioeconomic position were associated with different symptoms. Exposure to ambient air pollution was associated with higher dyspnoea and fatigue scores and lower functional status. Conclusions: We identified a high frequency of persistent symptoms among COVID-19 survivors that were associated with clinical, sociodemographic, and environmental variables. These findings indicate that most patients recovering from COVID-19 will need post-discharge care, and an additional burden to health care systems, especially in LMICs, should be expected.

Predicting the outcome for COVID-19 patients by applying time series classification to electronic health records.

BACKGROUND: COVID-19 caused more than 622 thousand deaths in Brazil. The infection can be asymptomatic and cause mild symptoms, but it also can evolve into a severe disease and lead to death. It is difficult to predict which patients will develop severe disease. There are, in the literature, machine learning models capable of assisting diagnose and predicting outcomes for several diseases, but usually these models require laboratory tests and/or imaging. METHODS: We conducted a observational cohort study that evaluated vital signs and measurements from patients who were admitted to Hospital das Clínicas (São Paulo, Brazil) between March 2020 and October 2021 due to COVID-19. The data was then represented as univariate and multivariate time series, that were used to train and test machine learning models capable of predicting a patient's outcome. RESULTS: Time series-based machine learning models are capable of predicting a COVID-19 patient's outcome with up to 96% general accuracy and 81% accuracy considering only the first hospitalization day. The models can reach up to 99% sensitivity (discharge prediction) and up to 91% specificity (death prediction). CONCLUSIONS: Results indicate that time series-based machine learning models combined with easily obtainable data can predict COVID-19 outcomes and support clinical decisions. With further research, these models can potentially help doctors diagnose other diseases.

Frequency and factors associated with hospital readmission after COVID-19 hospitalization: the importance of post-COVID diarrhea.

PURPOSE: The aim of this study was to describe the incidence and risk factors for hospital readmission and infection during the months after COVID-19 hospital admission. METHODS: This prospective study included adult patients who were hospitalized due to COVID-19 and had been discharged from April 2020 to August 2020. All patients had a medical evaluation with a structured questionnaire 6 to 11 months after hospital admission. The authors included only patients with confirmed COVID-19 by RT-PCR. Patients with pregnant/postpartum women, with a proven COVID-19 reinfection or incapable of answering the questionnaire were excluded. RESULTS: A total of 822 patients completed the follow-up assessment, and 68% reported at least one recurrent symptom related to COVID-19. The most frequent symptom was myalgia (42%). Thirty-two percent of patients visited an emergency room after COVID-19 hospitalization, and 80 (10%) patients required re-hospitalization. Risk factors for hospital readmission were orotracheal intubation during COVID-19 hospitalization (p = 0.003, OR = 2.14), Charlson score (p = 0.002, OR = 1.21), congestive heart failure (p = 0.005, OR = 2.34), peripheral artery disease (p = 0.06, OR = 2.06) and persistent diarrhea after COVID-19 hospitalization discharge (p = 0.02, OR = 1.91). The main cause of hospital readmission was an infection, 43 (54%). Pneumonia was the most frequent infection (29%). CONCLUSIONS: The presence of symptoms after six months of COVID-19 diagnosis was frequent, and hospital readmission was relatively high.

Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Gamma variant of concern has spread rapidly across Brazil since late 2020, causing substantial infection and death waves. Here we used individual-level patient records after hospitalization with suspected or confirmed coronavirus disease 2019 (COVID-19) between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed the spread of Gamma across 14 state capitals, during which typically more than half of hospitalized patients aged 70 years and older died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed before the detection of Gamma. Using a Bayesian fatality rate model, we found that the geographic and temporal fluctuations in Brazil's COVID-19 in-hospital fatality rates were primarily associated with geographic inequities and shortages in healthcare capacity. We estimate that approximately half of the COVID-19 deaths in hospitals in the 14 cities could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization and pandemic preparedness are critical to minimize population-wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries.

Performance of NEWS, qSOFA, and SIRS Scores for Assessing Mortality, Early Bacterial Infection, and Admission to ICU in COVID-19 Patients in the Emergency Department.

SARS-CoV-2 infection has a wide spectrum of presentations, from asymptomatic to pneumonia and sepsis. Risk scores have been used as triggers for protocols that combine several interventions for early management of sepsis. This study tested the accuracy of the score SIRS, qSOFA, and NEWS in predicting outcomes, including mortality and bacterial infection, in patients admitted to the emergency department (ED) during the COVID-19 pandemic. We described 2,473 cases of COVID-19 admitted to the ED of the largest referral hospital for severe COVID-19 in Brazil during the pandemic. SIRS, qSOFA and NEWS scores showed a poor performance as prognostic scores. However, NEWS score had a high sensitivity to predict in-hospital death (0.851), early bacterial infection (0.851), and ICU admission (0.868), suggesting that it may be a good screening tool for severe cases of COVID-19, despite its low specificity.