Antimicrobials are frequently used for palliation during end-of-life care, but adverse effects, such as antimicrobial resistance, are a concern. Shared decision-making is beneficial in end-of-life care conversations to help align antimicrobial-prescribing with patient preferences. However, there is limited data regarding optimal incorporation of antimicrobial-prescribing discussions into shared decision-making conversations. We explored healthcare provider, patient, and support caregiver (eg, family member/friend) perceptions of barriers and facilitators to discussing antimicrobial-prescribing during the end-of-life period.

Qualitative study.

Healthcare providers; palliative care/hospice care patients/caregivers.

We conducted semi-structured interviews on shared attitudes/beliefs about antimicrobial-prescribing during end-of-life patient care at one acute-care and one long-term-care facility. Interviews were analyzed for thematic content.

Fifteen providers and 13 patients/caregivers completed interviews. Providers recognized the potential benefit of leveraging shared decision-making to guide antimicrobial-prescribing decisions. Barriers included limited face-to-face time with the patient and uncertainty of end-of-life prognosis. Patients/caregivers cited trust, comprehension, and feeling heard as important characteristics which act as facilitators in fostering effective shared decision-making around antimicrobial use. Communication in which providers ensure patients are involved in shared decision-making discussions could be increased to ensure patients and their providers develop a mutually agreeable care plan.

Shared decision-making is a practice that can guide antimicrobial-prescribing decisions during end-of-life care, thus potentially minimizing antimicrobial-related adverse effects. Our findings highlight opportunities for increased shared decision-making around antimicrobial use during end-of-life care. Interventions designed to address the identified barriers to shared decision-making have the potential to improve antimicrobial-prescribing practices at end-of-life.

We performed a systematic literature review and meta-analysis on the effectiveness of coronavirus disease 2019 (COVID-19) vaccination against post-COVID conditions (long COVID) in the pediatric population.

Systematic literature review/meta-analysis.

We searched PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), EMBASE, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science from December 1, 2019, to August 14, 2023, for studies evaluating the COVID-19 vaccine effectiveness against post-COVID conditions among vaccinated individuals < 21 years old who received at least 1 dose of COVID-19 vaccine. A post-COVID condition was defined as any symptom that was present 4 or more weeks after COVID-19 infection. We calculated the pooled diagnostic odds ratio (DOR) (95% CI) for post-COVID conditions between vaccinated and unvaccinated individuals.

Eight studies with 23,995 individuals evaluated the effect of vaccination on post-COVID conditions, of which 5 observational studies were included in the meta-analysis. The prevalence of children who did not receive COVID-19 vaccines ranged from 65% to 97%. The pooled prevalence of post-COVID conditions was 21.3% among those unvaccinated and 20.3% among those vaccinated at least once. The pooled DOR for post-COVID conditions among individuals vaccinated with at least 1 dose and those vaccinated with 2 doses were 1.07 (95% CI, 0.77–1.49) and 0.82 (95% CI, 0.63–1.08), respectively.

A significant proportion of children and adolescents were unvaccinated, and the prevalence of post-COVID conditions was higher than reported in adults. While vaccination did not appear protective, conclusions were limited by the lack of randomized trials and selection bias inherent in observational studies.

We performed a systematic literature review and meta-analysis on the effectiveness of coronavirus disease 2019 (COVID-19) vaccination against post-COVID conditions (long COVID) among fully vaccinated individuals.

Systematic literature review/meta-analysis.

We searched PubMed, Cumulative Index to Nursing and Allied Health, EMBASE, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science from December 1, 2019, to June 2, 2023, for studies evaluating the COVID-19 vaccine effectiveness (VE) against post-COVID conditions among fully vaccinated individuals who received two doses of COVID-19 vaccine. A post-COVID condition was defined as any symptom that was present four or more weeks after COVID-19 infection. We calculated the pooled diagnostic odds ratio (DOR) (95% confidence interval) for post-COVID conditions between fully vaccinated and unvaccinated individuals. Vaccine effectiveness was estimated as 100% x (1-DOR).

Thirty-two studies with 775,931 individuals evaluated the effect of vaccination on post-COVID conditions, of which, twenty-four studies were included in the meta-analysis. The pooled DOR for post-COVID conditions among fully vaccinated individuals was 0.680 (95% CI: 0.523–0.885) with an estimated VE of 32.0% (11.5%–47.7%). Vaccine effectiveness was 36.9% (23.1%–48.2%) among those who received two doses of COVID-19 vaccine before COVID-19 infection and 68.7% (64.7%–72.2%) among those who received three doses before COVID-19 infection. The stratified analysis demonstrated no protection against post-COVID conditions among those who received COVID-19 vaccination after COVID-19 infection.

Receiving a complete COVID-19 vaccination prior to contracting the virus resulted in a significant reduction in post-COVID conditions throughout the study period, including during the Omicron era. Vaccine effectiveness demonstrated an increase when supplementary doses were administered.

To evaluate the impact of a multicenter, try automated dashboard on ASP activities and its acceptance among ASP leaders.

Frontline stewards were asked to participate in semi-structured interviews before and after implementation of a web-based ASP information dashboard providing risk-adjusted benchmarking, longitudinal trends, and analysis of antimicrobial usage patterns at each facility.

The study was performed at Iowa City VA Health Care System.

ASP team members from nine medical centers in the VA Midwest Health Care Network (VISN 23).

Semi-structured interviews were conducted pre- and post-implementation, with interview guides informed by clinical experiences and the Consolidated Framework for Implementation Research (CFIR). Participants evaluated the dashboard’s ease of use, applicability to ongoing ASP activities, perceived validity and reliability, and relative advantage over other ASP monitoring systems.

Compared to established stewardship data collection and reporting methods, participants found the dashboard more intuitive and accessible, allowing them to reduce dependence on other systems and staff to obtain and share data. Standardized and risk-adjusted rankings were largely accepted as a valuable benchmarking method; however, participants felt their facility’s characteristics significantly influenced the rankings’ validity. Participants recognized staffing, training, and uncertainty with using the dashboard as an intervention tool as barriers to consistent and comprehensive dashboard implementation.

Participants generally accepted the dashboard’s risk-adjusted metrics and appreciated its usability. While creating automated tools to rigorously benchmark antimicrobial use across hospitals can be helpful, the displayed metrics require further validation, and the longitudinal utility of the dashboard warrants additional study.

To compare the long-term vaccine effectiveness between those receiving viral vector [Oxford-AstraZeneca (ChAdOx1)] or inactivated viral (CoronaVac) primary series (2 doses) and those who received an mRNA booster (Pfizer/BioNTech) (the third dose) among healthcare workers (HCWs).

We conducted a retrospective cohort study among HCWs (aged ≥18 years) in Brazil from January 2021 to July 2022. To assess the variation in the effectiveness of booster dose over time, we estimated the effectiveness rate by taking the log risk ratio as a function of time.

Of 14,532 HCWs, coronavirus disease 2019 (COVID-19) was confirmed in 56.3% of HCWs receiving 2 doses of CoronaVac vaccine versus 23.2% of HCWs receiving 2 doses of CoronaVac vaccine with mRNA booster (P < .001), and 37.1% of HCWs receiving 2 doses of ChAdOx1 vaccine versus 22.7% among HCWs receiving 2 doses of ChAdOx1 vaccine with mRNA booster (P < .001). The highest vaccine effectiveness with mRNA booster was observed 30 days after vaccination: 91% for the CoronaVac vaccine group and 97% for the ChAdOx1 vaccine group. Vacine effectiveness declined to 55% and 67%, respectively, at 180 days. Of 430 samples screened for mutations, 49.5% were SARS-CoV-2 delta variants and 34.2% were SARS-CoV-2 omicron variants.

Heterologous COVID-19 vaccines were effective for up to 180 days in preventing COVID-19 in the SARS-CoV-2 delta and omicron variant eras, which suggests the need for a second booster.

To determine risk factors for the development of long coronavirus disease 2019 (COVID-19) in healthcare personnel (HCP).

We conducted a case–control study among HCP who had confirmed symptomatic COVID-19 working in a Brazilian healthcare system between March 1, 2020, and July 15, 2022. Cases were defined as those having long COVID according to the Centers for Disease Control and Prevention definition. Controls were defined as HCP who had documented COVID-19 but did not develop long COVID. Multiple logistic regression was used to assess the association between exposure variables and long COVID during 180 days of follow-up.

Of 7,051 HCP diagnosed with COVID-19, 1,933 (27.4%) who developed long COVID were compared to 5,118 (72.6%) who did not. The majority of those with long COVID (51.8%) had 3 or more symptoms. Factors associated with the development of long COVID were female sex (OR, 1.21; 95% CI, 1.05–1.39), age (OR, 1.01; 95% CI, 1.00–1.02), and 2 or more SARS-CoV-2 infections (OR, 1.27; 95% CI, 1.07–1.50). Those infected with the SARS-CoV-2 δ (delta) variant (OR, 0.30; 95% CI, 0.17–0.50) or the SARS-CoV-2 o (omicron) variant (OR, 0.49; 95% CI, 0.30–0.78), and those receiving 4 COVID-19 vaccine doses prior to infection (OR, 0.05; 95% CI, 0.01–0.19) were significantly less likely to develop long COVID.

Long COVID can be prevalent among HCP. Acquiring >1 SARS-CoV-2 infection was a major risk factor for long COVID, while maintenance of immunity via vaccination was highly protective.

Although multiple studies have revealed that coronavirus disease 2019 (COVID-19) vaccines can reduce COVID-19–related outcomes, little is known about their impact on post–COVID-19 conditions. We performed a systematic literature review and meta-analysis on the effectiveness of COVID-19 vaccination against post–COVID-19 conditions (ie, long COVID).

We searched PubMed, CINAHL, EMBASE, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science from December 1, 2019, to April 27, 2022, for studies evaluating COVID-19 vaccine effectiveness against post–COVID-19 conditions among individuals who received at least 1 dose of Pfizer/BioNTech, Moderna, AstraZeneca, or Janssen vaccine. A post–COVID-19 condition was defined as any symptom that was present 3 or more weeks after having COVID-19. Editorials, commentaries, reviews, study protocols, and studies in the pediatric population were excluded. We calculated the pooled diagnostic odds ratios (DORs) for post–COVID-19 conditions between vaccinated and unvaccinated individuals. Vaccine effectiveness was estimated as 100% × (1 − DOR).

In total, 10 studies with 1,600,830 individuals evaluated the effect of vaccination on post–COVID-19 conditions, of which 6 studies were included in the meta-analysis. The pooled DOR for post–COVID-19 conditions among individuals vaccinated with at least 1 dose was 0.708 (95% confidence interval (CI), 0.692–0.725) with an estimated vaccine effectiveness of 29.2% (95% CI, 27.5%–30.8%). The vaccine effectiveness was 35.3% (95% CI, 32.3%–38.1%) among those who received the COVID-19 vaccine before having COVID-19, and 27.4% (95% CI, 25.4%–29.3%) among those who received it after having COVID-19.

COVID-19 vaccination both before and after having COVID-19 significantly decreased post–COVID-19 conditions for the circulating variants during the study period although vaccine effectiveness was low.

We sought to determine whether an electronic hand hygiene (HH) system could monitor HH compliance at similar rates to direct human observation.

This 4-year proof-of-concept study was conducted in an intensive care unit (ICU) of a private tertiary-care hospital in São Paulo, Brazil, where electronic HH systems were installed in 2 rooms. HH compliance was reported respectively using direct observation and electronic counter devices with an infrared system for detecting HH opportunities.

In phase 1, HH compliance by human observers was 56.3% (564 of 1,001 opportunities), while HH compliance detected by the electronic observer was 51.0% (515 of 1,010 opportunities). In phase 2, human observers registered 484 HH opportunities with a HH compliance rate of 64.7% (313 of 484) versus 70.6% (346 of 490) simultaneously detected by the electronic system. In addition, an enhanced HH electronic system monitored activity 24 hours per day and HH compliance without the presence of a human observer was 40.3% (10,642 of 26,421 opportunities), providing evidence for the Hawthorne effect.

The electronic HH monitoring system had good correlation with human HH observation, but compliance was remarkably lower when human observers were not present due to the Hawthorne effect (25%–30% absolute difference). Electronic monitoring systems can replace direct observation and can markedly reduce the Hawthorne effect.

Most hand hygiene (HH) intervention studies use a quasi-experimental design, are primarily uncontrolled before-and-after studies, or are controlled before-and-after studies with a nonequivalent control group. Well-funded studies with improved designs and HH interventions are needed.

To evaluate healthcare worker (HCW) HH compliance with alcohol-based hand rub (ABHR) through direct observation (human observer), 2 electronic technologies, a radio frequency identification (RFID) badge system, and an invasive device sensor.

In our controlled experimental study, 2,269 observations were made over a 6-month period from July 1 to December 30, 2020, in a 4-bed intensive care unit. We compared HH compliance between a basic feedback loop system with RFID badges and an enhanced feedback loop system that utilized sensors on invasive devices.

Real-time feedback by wireless technology connected to a patient’s invasive device (enhanced feedback loop) resulted in a significant increase in HH compliance (69.5% in the enhanced group vs 59.1% in the basic group; P = .0001).

An enhanced feedback loop system connected to invasive devices, providing real-time alerts to HCWs, is effective in improving HH compliance.

We investigated real-world vaccine effectiveness for Oxford-AstraZeneca (ChAdOx1) and CoronaVac against laboratory-confirmed severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among healthcare workers (HCWs).

We conducted a retrospective cohort study among HCWs (aged ≥18 years) working in a private healthcare system in Brazil between January 1, 2021 and August 3, 2021, to assess vaccine effectiveness. We calculated vaccine effectiveness as 1 − rate ratio (RR), with RR determined by adjusting Poisson models with the occurrence of SARS-CoV-2 infection as the outcome and the vaccination status as the main variable. We used the logarithmic link function and simple models adjusting for sex, age, and job types.

In total, 13,813 HCWs met the inclusion criteria for this analysis. Among them, 6,385 (46.2%) received the CoronaVac vaccine, 5,916 (42.8%) received the ChAdOx1 vaccine, and 1,512 (11.0%) were not vaccinated. Overall, COVID-19 occurred in 6% of unvaccinated HCWs, 3% of HCWs who received 2 doses of CoronaVac vaccine, and 0.7% of HCWs who received 2 doses of ChAdOx1 vaccine (P < .001). In the adjusted analyses, the estimated vaccine effectiveness rates were 51.3% for CoronaVac, and 88.1% for ChAdOx1 vaccine. Both vaccines reduced the number of hospitalizations, the length of hospital stay, and the need for mechanical ventilation. In addition, 19 SARS-CoV-2 samples from 19 HCWs were screened for mutations of interest. Of 19 samples, 18 were the γ (gamma) variant.

Although both COVID-19 vaccines (viral vector and inactivated virus) can significantly prevent COVID-19 among HCWs, CoronaVac was much less effective. The COVID-19 vaccines were also effective against the dominant γ variant.