ABSTRACT Objective: To evaluate survival and direct medical costs of patients admitted in private hospitals with COVID-19 during the first wave. Methods: A retrospective, observational study analyzing survival and the economic data retrieved on hospitalized patients with COVID-19. Data from March 2020 to December 2020. The direct cost of hospitalization was estimated using the microcosting method with each individual hospitalization. Results: 342 cases were evaluated. Median age of 61.0 (95% CI 57.0-65.0). 194 (56.7%) were men. The mortality rate was higher in the female sex (p = 0.0037), ICU (p < 0.001), mechanical ventilation (p<0.001) and elderly groups. 143 (41.8%) patients were admitted to the ICU (95% CI 36.6%-47.1%), of which 60 (41.9%) required MV (95% CI 34.0%-50.0%). Global LOS presented median of 6.7 days (95% CI 6.0-7.2). Mean costs were US$ 7,060,00 (95% CI 5,300.94-8,819,00) for each patient. Mean cost for patients discharged alive and patients deceased was US$ 5,475.53 (95% CI 3,692.91-7,258.14) and US$ 12,955.19 (95% CI 8,106.61 -17,803.76), respectively (p < 0.001). Conclusions: Patients admitted with COVID-19 in these private hospitals point to great economic impact, mainly in the elderly and high-risk patients. It is key to better understand such costs in order to be prepared to make wise decisions during the current and future global health emergencies. Objective COVID19 COVID 19 COVID-1 wave Methods retrospective COVID19. 19. 202 Results 34 evaluated 610 61 0 61. 95% 95 (95 57.065.0. 570650 57.0 65.0 . 57 65 57.0-65.0) 56.7% 567 56 7 (56.7% men p 0.0037, 00037 0.0037 , 0037 0.0037) 0.001, 0001 0.001 001 0.001) p<0.001 p0001 (p<0.001 groups 14 41.8% 418 41 8 (41.8% 36.6%47.1%, 366471 36.6% 47.1% 36 6 47 1 36.6%-47.1%) 41.9% 419 9 (41.9% 34.0%50.0%. 340500 34.0% 50.0% 50 34.0%-50.0%) 67 6. 6.07.2. 6072 6.0 7.2 2 6.0-7.2) US 706000 060 00 7,060,0 5,300.948,819,00 530094881900 5,300.94 8,819,00 5 300 94 819 5,300.94-8,819,00 patient 547553 475 53 5,475.5 3,692.917,258.14 369291725814 3,692.91 7,258.14 3 692 91 258 3,692.91-7,258.14 1295519 12 955 12,955.1 810661 106 8,106.6 17,803.76, 1780376 17,803.76 17 803 76 -17,803.76) 0.001. Conclusions impact highrisk high risk emergencies COVID1 COVID- 20 (9 065 57.065.0 57065 570 57. 650 65. 57.0-65.0 56.7 (56.7 0003 0.003 003 000 0.00 p<0.00 p000 (p<0.00 41.8 4 (41.8 36.6%47.1% 36647 366 36.6 471 47.1 36.6%-47.1% 41.9 (41.9 34.0%50.0% 34050 340 34.0 500 50.0 34.0%-50.0% 07 6.07.2 607 72 7. 6.0-7.2 70600 06 7,060, 948 5,300.948,819,0 53009488190 530094 5,300.9 881900 8,819,0 30 81 5,300.94-8,819,0 54755 5,475. 917 3,692.917,258.1 36929172581 369291 3,692.9 725814 7,258.1 69 25 3,692.91-7,258.1 129551 12,955. 81066 10 8,106. 178037 17,803.7 80 -17,803.76 ( 57.065. 5706 57.0-65. 56. (56. 0.0 p<0.0 p00 (p<0.0 41. (41. 36.6%47.1 3664 36. 47. 36.6%-47.1 34.0%50.0 3405 34. 50. 34.0%-50.0 6.07. 6.0-7. 7060 7,060 5,300.948,819, 5300948819 53009 5,300. 88190 8,819, 5,300.94-8,819, 5475 5,475 3,692.917,258. 3692917258 36929 3,692. 72581 7,258. 3,692.91-7,258. 12955 12,955 8106 8,106 17803 17,803. -17,803.7 57.065 57.0-65 (56 0. p<0. p0 (p<0. (41 36.6%47. 36.6%-47. 34.0%50. 34.0%-50. 6.07 6.0-7 706 7,06 5,300.948,819 530094881 5300 5,300 8819 8,819 5,300.94-8,819 547 5,47 3,692.917,258 369291725 3692 3,692 7258 7,258 3,692.91-7,258 1295 12,95 810 8,10 1780 17,803 -17,803. 57.06 57.0-6 (5 p<0 (p<0 (4 36.6%47 36.6%-47 34.0%50 34.0%-50 6.0- 70 7,0 5,300.948,81 53009488 530 5,30 881 8,81 5,300.94-8,81 54 5,4 3,692.917,25 36929172 369 3,69 725 7,25 3,692.91-7,25 129 12,9 8,1 178 17,80 -17,803 57.0- p< (p< 36.6%4 36.6%-4 34.0%5 34.0%-5 7, 5,300.948,8 5300948 5,3 88 8,8 5,300.94-8,8 5, 3,692.917,2 3692917 3,6 7,2 3,692.91-7,2 12, 8, 17,8 -17,80 36.6%- 34.0%- 5,300.948, 5,300.94-8, 3,692.917, 3, 3,692.91-7, 17, -17,8 5,300.948 5,300.94-8 3,692.917 3,692.91-7 -17, 5,300.94- 3,692.91- -17 -1 -

Abstract Purpose The aim of this study was to compare pharmacokinetic characteristics between intermittent infusion and continuous infusion of vancomycin for critically ill patients admitted to intensive care units. Methods Intermittent therapy was administered for 60 minutes and prescribed as a loading dose of 30 mg/kg and continued with 15 mg/kg q12 h. Continuous infusion was prescribed as a loading dose of 30 mg/kg followed by 30 mg/kg on constant infusion pump. Blood samples from vancomycin intermittent infusion group were collected 1 h before third dose, 1 h, 8 h and 24 h after third dose infusion. Blood samples from vancomycin continuous infusion group were collected 1 h after loading dose, 12 h, 24 h, 36 h, and 48 h after continuous infusion initiation. Results Median serum concentration of continuous infusion group at 24-hour was 23.59 µg/mL [14.52–28.97], while of intermittent infusion group at 23-hour was 12.30 µg/mL [7.27–18.12] and on 25-hour was 17.58 µg/mL [12.5–22.5]. Medians AUC24–48h were 357.2 mg.h/L and 530.2 mg.h/L for intermittent infusion and continuous infusion groups, respectively (p = 0.559). Conclusion Vancomycin CI reached steady state earlier, which guaranteed therapeutic levels from the first day and made it possible to manage therapeutic drug monitoring faster.

ABSTRACT Background: Antimicrobial stewardship programs are an efficient way to reduce inappropriate use of antimicrobials and costs; however, supporting data are scarce in middle-income countries. The aim of this study was to evaluate antibiotic use, bacterial susceptibility profiles, and the economic impact following implementation of a broad-spectrum beta-lactam-sparing antimicrobial stewardship program. Methods: An interrupted time-series analysis was performed to evaluate antibiotic use and expenditure over a 24-month period (12 months before the antimicrobial stewardship program and in the 12 months after implementation of the antimicrobial stewardship program). Antibiotics were classified into one of two groups: beta-lactam antibiotics and beta-lactam-sparing antibiotics. We also compared the antimicrobial susceptibility profiles of key pathogens in each period. Results: Beta-lactam antibiotics use decreased by 43.04 days of therapy/1000 patient-days (p = 0.04) immediately following antimicrobial stewardship program implementation, whereas beta-lacta-sparing antibiotics use increased during the intervention period (slope change 6.17 days of therapy/1000 patient-days, p < 0.001). Expenditure decreased by $2089.99 (p < 0.001) immediately after intervention and was maintained at this level over the intervention period ($−38.45; p = 0.24). We also observed that a greater proportion of pathogens were susceptible to cephalosporins and aminoglycosides after the antimicrobial stewardship program. Conclusions: The antimicrobial stewardship program significantly reduced the use of broad-spectrum beta-lactam-antibiotics associated with a decrease in expenditure and maintenance of the susceptibility profile in Gram-negative bacteria.

Abstract Consumption of carbapenem has increased due to extended-spectrum beta-lactamase-producing bacteria spreading. Ertapenem has been suggested as a not carbapenem-resistance inducer. We performed a scoping review of carbapenem-sparing stewardship with ertapenem and its impact on the antibiotic resistance of Gram-negative bacilli. We searched PubMed for studies that used ertapenem as a strategy to reduce resistance to carbapenems and included epidemiologic studies with this strategy to evaluate susceptibility patterns to cephalosporins, quinolones, and carbapenems in Gram-negative-bacilli. The search period included only studies in English, up to February 2018. From 1294 articles, 12 studies were included, mostly from the Americas. Enterobacteriaceae resistance to quinolones and cephalosporins was evaluated in 6 studies and carbapenem resistance in 4 studies. Group 2 carbapenem (imipenem/meropenem/doripenem) resistance on A. baumannii was evaluated in 6 studies. All studies evaluated P. aeruginosa resistance to Group 2 carbapenem. Resistance profiles of Enterobacteriaceae and P. aeruginosa to Group 2 carbapenems were not associated with ertapenem consumption. The resistance rate of A. baumannii to Group 2 carbapenems after ertapenem introduction was not clear due to a lack of studies without bias. In summary, ertapenem as a strategy to spare use of Group 2 carbapenems may be an option to stewardship programs without increasing resistance of Enterobacteriaceae and P. aeruginosa. More studies are needed to evaluate the influence of ertapenem on A. baumannii.

ABSTRACT Background: Technologies applied to mobile devices can be an important strategy in antibiotic stewardship programs. Objective: The aim of this study was to determine the impact of a decision-making application on antibiotic prescription. Methods: This was an observational, analytical and longitudinal study on the implementation of an antimicrobial guide for mobile application. This study analyzed the period of 12 months before and 12 months after the app implementation at a university hospital based on local epidemiology, avoiding high cost drugs and reducing the potential for drug resistance including carbapenem. Antimicrobials consumption was evaluated in Daily Defined Dose/1000 patients-day and direct expenses converted into USD. Results: The monthly average consumption of aminoglycosides and cefepime had a statistically significant increase (p < 0.05), while the consumption of piperacillin/tazobactam and meropenem was significantly decreased (p < 0.05). The sensitivity to meropenem as well as to polymyxin increased after the app implementation. A decrease in sensitivity to cefepime was observed after introduction of this antibiotic as a substitute of piperacillin/tazobactam for treating intra-hospital infections.There was a net saving of USD 296,485.90 (p < 0.05). Conclusion: An antibiotic protocol in the app can help antibiotic stewardship reducing cost, changing the microbiological profile and antimicrobial consumption.