To describe the clinical characteristics, laboratory results, imaging findings, and in-hospital outcomes of COVID-19 patients admitted to Brazilian hospitals. Methods: A cohort study of laboratory-confirmed COVID-19 patients who were hospitalized from March 2020 to September 2020 in 25 hospitals. Data were collected from medical records using Research Electronic Data Capture (REDCap) tools. A multivariate Poisson regression model was used to assess the risk factors for in-hospital mortality. Results: For a total of 2,054 patients (52.6% male; median age of 58 years), the in-hospital mortality was 22.0%; this rose to 47.6% for those treated in the intensive care unit (ICU). Hypertension (52.9%), diabetes (29.2%), and obesity (17.2%) were the most prevalent comorbidities. Overall, 32.5% required invasive mechanical ventilation, and 12.1% required kidney replacement therapy. Septic shock was observed in 15.0%, nosocomial infection in 13.1%, thromboembolism in 4.1%, and acute heart failure in 3.6%. Age >= 65 years, chronic kidney disease, hypertension, C-reactive protein ! 100 mg/dL, platelet count < 100 Â 10 9 /L, oxygen saturation < 90%, the need for supplemental oxygen, and invasive mechanical ventilation at admission were independently associated with a higher risk of in-hospital mortality. The overall use of antimicrobials was 87.9%. Conclusions: This study reveals the characteristics and in-hospital outcomes of hospitalized patients with confirmed COVID-19 in Brazil. Certain easily assessed parameters at hospital admission were independently associated with a higher risk of death. The high frequency of antibiotic use points to an over-use of antimicrobials in COVID-19 patients.
Objectives The majority of available scores to assess mortality risk of coronavirus disease 19 (COVID-19) patients in the emergency department have high risk of bias. Therefore, our aim was to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients, and to compare this score with other existing ones. Methods Consecutive patients (≥18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March-July, 2020. The model was validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. Results Median (25th-75th percentile) age of the model-derivation cohort was 60 (48-72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO 2 /FiO 2 ratio, platelet count and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829 to 0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833 to 0.885]) and Spanish (0.894 [95% CI 0.870 to 0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions We designed and validated an easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation, for early stratification for in-hospital mortality risk of patients with COVID-19.
Background The RESILIENT trial demonstrated the clinical benefit of mechanical thrombectomy in patients presenting acute ischemic stroke secondary to anterior circulation large vessel occlusion in Brazil. Aims This economic evaluation aims to assess the cost-utility of mechanical thrombectomy in the RESILIENT trial from a public healthcare perspective. Methods A cost-utility analysis was applied to compare mechanical thrombectomy plus standard medical care (n = 78) vs. standard medical care alone (n = 73), from a subset sample of the RESILIENT trial (151 of 221 patients). Real-world direct costs were considered, and utilities were imputed according to the Utility-Weighted modified Rankin Score. A Markov model was structured, and probabilistic and deterministic sensitivity analyses were performed to evaluate the robustness of results. Results The incremental costs and quality-adjusted life years gained with mechanical thrombectomy plus standard medical care were estimated at Int$ 7440 and 1.04, respectively, compared to standard medical care alone, yielding an incremental cost-effectiveness ratio of Int$ 7153 per quality-adjusted life year. The deterministic sensitivity analysis demonstrated that mRS-6 costs of the first year most affected the incremental cost-effectiveness ratio. After 1000 simulations, most of results were below the cost-effective threshold. Conclusions The intervention's clear long-term benefits offset the initially higher costs of mechanical thrombectomy in the Brazilian public healthcare system. Such therapy is likely to be cost-effective and these results were crucial to incorporate mechanical thrombectomy in the Brazilian public stroke centers.
Introduction:Extracorporeal circulatory membrane oxygenation (ECMO) is a technology that allows recovery of adults in cardiorespiratory failure with encouraging results, but is not available in the Brazilian universal public health system (SUS) due to high implementation costs. Time-driven activity based costing (TDABC) is applied to measure processes in an economic perspective by identifying opportunities to make processes more efficient through the reduction of resources used in each activity. The literature has explored the use of TDABC to measure costs related with clinical procedures and technologies in microcosting studies, identifying opportunities to improve the process by making it more efficient. This research measures the real costs to implement ECMO in Brazil to compare with the current public reimbursement system.Methods:This study applied TDABC using data from 6 patients to measure costs of ECMO intervention considering the public perspective in Brazil. In sequence, standard price payed by SUS was used to estimate the current reimbursement amount received by the hospital for ECMO procedure. Cost variable analysis was conducted to understand when and how patients receiving ECMO are using hospital resources. Cost data were collected from an academic public hospital using an average of 18 months (2016–2017) for the department costs.Results:The real average cost was USD 128,923. Most significant resource costs was medical staff, particularly for the three survivor patients, and the ECMO equipment presented the second highest cost. ECMO activities were separated into: before implantation of ECMO, period using ECMO, intensive care post-ECMO and rehabilitation, being the period where ECMO is the most expensive, particularly in nurse and physician costs. The SUS average was USD 31,437, which shows a difference of USD 97,485 between the real ECMO cost and the public reimbursement in Brazil.Conclusions:A critical element of the propagation of ECMO in Brazil and its reimbursement by public health system is the high cost and out-of-date standard payments by the Ministry of Health. Effort to implement a trustworthy method to guide decisions of SUS for the adoption and financing new technologies is essential to contribute to the optimization of public health policies in a country with a universal health system and limited resources dedicated to health sectors.
Rationale Preoperative care is one of the main areas in which to address low‐value care. A detailed definition of what low‐value care is in this period of the surgical care journey paves the way for new scientific research, clinical improvements, and reduction of unnecessary costs in this field. Aims and Objective To identify how low‐value care in low‐risk preoperative population has been defined in the scientific literature and propose a low‐value care framework with potential consequences in this setting. Methods Scoping review of theoretical studies and peer‐reviewed papers, including reviews, commentaries, or expert opinions, were considered eligible for inclusion. The following databases were consulted: MEDLINE (via PubMed), EMBASE, and SCOPUS (from inception to July 24, 2021), using a structured search with the keywords “low value care”, “clinical waste”, “preoperative”, and “elective procedures.” Two independent reviewers performed study selection and data extraction. The definition of low‐value care in the preoperative period and their consequences were described after extracting previous low‐value care concepts and summarising the contents. Also, a visual framework was built with this information. Results From 1519 publications identified in the initial searches, 22 underwent full‐text assessment, and 11 conceptual studies were included in the review. A total of four studies (36%) presented a general low‐value care definition, and all studies report some situations considered low‐value care in the preoperative field of low‐risk surgeries. The most common example of preoperative low‐value care, listed in nine studies (81%), was having asymptomatic patients undergo screening tests before surgery. The main clinical and nonclinical consequences of low‐value care in the preoperative phase included false‐positive results from exams as well as psychological distress, increased costs, and delay in surgery. Conclusions Revisiting and integrating previous definitions of low‐value care in low‐risk surgery into a scoping review is a starting point for de‐implementing unnecessary care and promoting improvements in surgical pathways.
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