Prevalence, predictors, and patient-reported outcomes of long COVID in hospitalized and non-hospitalized patients from the city of São Paulo, Brazil.

Background: Robust data comparing long COVID in hospitalized and non-hospitalized patients in middle-income countries are limited. Methods: A retrospective cohort study was conducted in Brazil, including hospitalized and non-hospitalized patients. Long COVID was diagnosed at 90-day follow-up using WHO criteria. Demographic and clinical information, including the depression screening scale (PHQ-2) at day 30, was compared between the groups. If the PHQ-2 score is 3 or greater, major depressive disorder is likely. Logistic regression analysis identified predictors and protective factors for long COVID. Results: A total of 291 hospitalized and 1,118 non-hospitalized patients with COVID-19 were included. The prevalence of long COVID was 47.1% and 49.5%, respectively. Multivariable logistic regression showed female sex (odds ratio [OR] = 4.50, 95% confidence interval (CI) 2.51-8.37), hypertension (OR = 2.90, 95% CI 1.52-5.69), PHQ-2 > 3 (OR = 6.50, 95% CI 1.68-33.4) and corticosteroid use during hospital stay (OR = 2.43, 95% CI 1.20-5.04) as predictors of long COVID in hospitalized patients, while female sex (OR = 2.52, 95% CI 1.95-3.27) and PHQ-2 > 3 (OR = 3.88, 95% CI 2.52-6.16) were predictors in non-hospitalized patients. Conclusion: Long COVID was prevalent in both groups. Positive depression screening at day 30 post-infection can predict long COVID. Early screening of depression helps health staff to identify patients at a higher risk of long COVID, allowing an early diagnosis of the condition.

Use of a trigger tool to detect adverse drug reactions in an emergency department.

BACKGROUND: Although there are systems for reporting adverse drug reactions (ADR), these safety events remain under reported. The low-cost, low-tech trigger tool method is based on the detection of events through clues, and it seems to increase the detection of adverse events compared to traditional methodologies. This study seeks to estimate the prevalence of adverse reactions to drugs in patients seeking care in the emergency department. METHODS: Retrospective study from January to December, 2014, applying the Institute for Healthcare Improvement (IHI) trigger tool methodology for patients treated at the emergency room of a tertiary care hospital. RESULTS: The estimated prevalence of adverse reactions in patients presenting to the emergency department was 2.3% [CI95 1.3% to 3.3%]; 28.6% of cases required hospitalization at an average cost of US$ 5698.44. The most common triggers were hydrocortisone (57% of the cases), diphenhydramine (14%) and fexofenadine (14%). Anti-infectives (19%), cardiovascular agents (14%), and musculoskeletal drugs (14%) were the most common causes of adverse reactions. According to the Naranjo Scale, 71% were classified as possible and 29% as probable. There was no association between adverse reactions and age and sex in the present study. CONCLUSIONS: The use of the trigger tool to identify adverse reactions in the emergency department was possible to identify a prevalence of 2.3%. It showed to be a viable method that can provide a better understanding of adverse drug reactions in this patient population.

Implementation of an antibiotic prophylaxis protocol in an intensive care unit.

BACKGROUND: When properly employed, the prophylactic use of antimicrobials is associated with a reduction in surgical site infections (SSIs). We found that the appropriate use of antimicrobial prophylaxis was only 50.5% (53/105) among patients undergoing surgery in the adult intensive care unit of our hospital. In 2001, a protocol was designed to improve compliance with recommended practice. METHODS: We used a prospective interventional study and a case control study carried out between 2001 and 2007, including follow-up and daily intervention to improve compliance with antimicrobial prophylaxis guidelines and to monitor antimicrobial consumption and SSI rates. Cases of noncompliance to the prophylaxis protocol (group I) were matched to controls (group II) with appropriate prophylaxis and compared with regards to type of surgery, operative duration, intraoperative antimicrobial use, type of antimicrobial used, length of hospital stay, severity of illness, comorbidities, invasive devices, possible adverse reactions, and death. RESULTS: Compliance with antimicrobial prophylaxis metrics reached 85%; however, we were unable to detect a change in SSI rate or consumption and cost of antimicrobials. Inappropriate use was not associated with higher likelihood of death. There were no other significant differences between the 2 groups. CONCLUSION: Our intervention increased compliance with appropriate antimicrobial surgical prophylaxis with no negative impact on patient safety.

The effect of limiting antimicrobial therapy duration on antimicrobial resistance in the critical care setting.

BACKGROUND: Using antimicrobial agents for prolonged periods of time and/or in heavy densities is known to contribute to antimicrobial resistance. METHODS: A quasiexperimental, before and after study to limit the duration of antimicrobial therapy to 14 days was conducted in a medical-surgical intensive care unit (ICU). An intervention to optimize antimicrobial therapy was performed when antimicrobial agents had been prescribed for more than 14 days. We then compared antimicrobial utilization using the defined daily dose (DDD) per 1000 patient-days, as well as resistance rates in selected organisms in the intervention phase to the previous 10-month period. RESULTS: In the intervention phase, doctors approved to discontinue the antimicrobial therapy before 14 days in 89.8% (415/462) of the prescribed antibiotics in the ICU. Comparing the 2 time periods, we found a reduction in carbapenems (24.5% decrease), vancomycin (14.3% decrease), and cephalosporins (12.2% decrease) in the intervention phase. Imipenem resistance decreased in Acinetobacter baumannii from 88.5% to 20.0% (P