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.

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.

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.

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.

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.

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.

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.

Statewide evaluation of infection control measures for preventing coronavirus disease 2019 in hemodialysis facilities.

OBJECTIVE: This study aimed to evaluate the occurrence of coronavirus disease 2019 (COVID-19) in hemodialysis facilities and the occurrence of and risk factors for clustering of COVID-19 cases. METHODS: We conducted a cross-sectional online survey between March and July 2020, in all dialysis facilities in São Paulo state, using Google Forms. The online questionnaire contained questions addressing specific components of infection prevention and control practices and the number of cases during the COVID-19 pandemic. RESULTS: A total of 1,093 (5%) COVID-19 cases were reported among 20,984 patients; approximately 56% of the facilities had ≥1 cluster. Most facilities implemented various measures (such as allocation of dedicated COVID-19 areas/shifts, symptom screening, environmental disinfection, and maintenance of adequate ventilation) to prevent the transmission of severe acute respiratory syndrome coronavirus 2. Clustering of COVID-19 cases was suspected in only 7% of dialysis facilities. The only variable associated with this event was the performance of aerosol-generating procedures (odds ratio: 4.74; 95% confidence interval: 1.75-12.86). CONCLUSION: Attention should be paid to avoiding the performance of aerosol-generating procedures in dialysis facilities and monitoring the clustering of cases.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Seroprevalence and Risk Factors Among Oligo/Asymptomatic Healthcare Workers: Estimating the Impact of Community Transmission.

We evaluated the seroprevalence of SARS-CoV-2 and risk factors among 4987 oligo/asymptomatic healthcare workers; seroprevalence was 14% and factors associated with SARS-CoV-2 infection were lower educational level (aOR, 1.93; 95% CI, 1.03-3.60), using public transport to work (aOR, 1.65; 95% CI, 1.07-2.62), and working in cleaning or security (aOR, 2.05; 95% CI, 1.04-4.03).

SARS-CoV-2 in a stream running through an underprivileged, underserved, urban settlement in São Paulo, Brazil: A 7-month follow-up.

COVID-19 pandemic has led to concerns on the circulation of SARS-CoV-2 in the environment, its infectivity from the environment and, the relevance of transmission via environmental compartments. During 31 weeks, water samples were collected from a heavily contaminated stream going through an urban, underprivileged community without sewage collection. Our results showed a statistically significant correlation between cases of COVID-19 and SARS in the community, and SARS-CoV-2 concentrations in the water. Based on the model, if the concentrations of SARS-CoV-RNA (N1 and N2 target regions) increase 10 times, there is an expected increase of 104% [95%CI: (62-157%)] and 92% [95%CI: (51-143%)], respectively, in the number of cases of COVID-19 and SARS. We believe that differences in concentration of the virus in the environment reflect the epidemiological status in the community, which may be important information for surveillance and controlling dissemination in areas with vulnerable populations and poor sanitation. None of the samples were found infectious based cultures. Our results may be applicable globally as similar communities exist worldwide.

Corrigendum: Determinants of Health and Physical Activity Levels Among Breast Cancer Survivors During the COVID-19 Pandemic: A Cross-Sectional Study.

[This corrects the article DOI: 10.3389/fphys.2021.624169.].

In-depth analysis of laboratory parameters reveals the interplay between sex, age, and systemic inflammation in individuals with COVID-19.

BACKGROUND: The progression and severity of COVID-19 vary significantly in the population. While the hallmarks of SARS-CoV-2 and severe COVID-19 within routine laboratory parameters are emerging, the impact of sex and age on these profiles is still unknown. METHODS: A multidimensional analysis was performed involving millions of records of laboratory parameters and diagnostic tests for 178 887 individuals from Brazil, of whom 33 266 tested positive for SARS-CoV-2. Analyzed data included those relating to complete blood cell count, electrolytes, metabolites, arterial blood gases, enzymes, hormones, cancer biomarkers, and others. FINDINGS: COVID-19 induced similar alterations in laboratory parameters in males and females. CRP and ferritin were increased, especially in older men with COVID-19, whereas abnormal liver function tests were common across several age groups, except for young women. Low peripheral blood basophils and eosinophils were more common in the elderly with COVID-19. Both male and female COVID-19 patients admitted to intensive care units displayed alterations in the coagulation system, and higher values for neutrophils, CRP, and lactate dehydrogenase. CONCLUSIONS: Our study uncovered the laboratory profiles of a large cohort of COVID-19 patients, which formed the basis of discrepancies influenced by aging and biological sex. These profiles directly linked COVID-19 disease presentation to an intricate interplay between sex, age, and immune activation.

Determinants of Health and Physical Activity Levels Among Breast Cancer Survivors During the COVID-19 Pandemic: A Cross-Sectional Study.

Background: Increased exercise and physical activity levels are recommended throughout cancer therapy and survivorship. Nonetheless, the COVID-19 pandemic and consequent social distancing are likely to cause a decline in physical activity. Objective: to evaluate the level of unsupervised physical activity of breast cancer survivors during the COVID-19 pandemic, and the factors associated with difficulties in engaging and maintaining recommended physical activity levels. Methods: This is a cross-sectional epidemiological study with a sample of 37 breast cancer survivors. They participated in a canoeing training program (project Remama) at the University of São Paulo before the COVID-19 pandemic. Socioeconomic aspects, engagement in physical activity, motivation, and potential exposure to COVID-19 were investigated through an online survey, administered in September of 2020. Results: During the pandemic, participants increased their body weight (5 ± 3.4 kg); 90% reported decreasing physical activity levels associated with increased sedentary time. Twenty-one (58%) participants exhibited some COVID-19-related symptoms, most used public transportation (59%), or returned to work during the period of a high incidence of COVID-19. The only factor associated with perceived difficulty in engaging in physical activities was having had more than three cancer treatments (RR: 2.14; 95% CI: 1.07-4.27). Conclusion: The COVID-19 pandemic led to a group of previously active breast cancer survivors to decrease their physical activity, gain weight, and have sedentary behavior. Specific tailored-care interventions are needed to prevent these occurrences, as overweight and physical inactivity may impose an additional risk for breast cancer recurrence and a severe course of COVID-19 in cancer patients.