Assess the efficacy of staged interventions aimed to reduce inappropriate Clostridioides difficile testing and hospital-onset C. difficile infection (HO-CDI) rates.

Interrupted time series.

Community-based.

National Healthcare Safety Network (NHSN) C. difficile metrics from January 2019 to November 2022 were analyzed after three interventions at a community-based healthcare system. Interventions included: (1) an electronic medical record (EMR) based hard stop requiring confirming ≥3 loose or liquid stools over 24 h, (2) an infectious diseases (ID) review and approval of testing >3 days of hospital admission, and (3) an infection control practitioner (ICP) reviews combined with switching to a reverse two-tiered clinical testing algorithm.

After all interventions, the number of C. difficile tests per 1,000 patient-days (PD) and HO-CDI cases per 10,000 PD decreased from 20.53 to 6.92 and 9.80 to 0.20, respectively. The EMR hard stop resulted in a (28%) reduction in the CDI testing rate (adjusted incidence rate ratio ((aIRR): 0.72; 95% confidence interval [CI], 0.53 to 0.96)) and ID review resulted in a (42%) reduction in the CDI testing rate (aIRR: 0.58; 95% CI, 0.42–0.79). Changing to the reverse testing algorithm reduced reported HO-CDI rate by (95%) (cIRR: 0.05; 95% CI; 0.01–0.40).

Staged interventions aimed at improving diagnostic stewardship were effective in overall reducing CDI testing in a community healthcare system.

Clostridioides difficile infection (CDI) is a common and often nosocomial infection associated with increased mortality and morbidity. Antibiotic use is the most important modifiable risk factor, but many patients require empiric antibiotics. We estimated the increased risk of hospital-onset CDI with one daily dose-equivalent (DDE) of various empiric antibiotics compared to management without that daily dose-equivalent.

Using a multicenter retrospective cohort of adults admitted between March 2, 2020 and February 11, 2021 for the treatment of SARS-CoV-2, we used a series of three-level logistic regression models to estimate the probability of receiving each of several antibiotics of interest. For each antibiotic, we then limited our data set to patient-days at intermediate probability of receipt and used augmented inverse-probability weighted models to estimate the average treatment effect of one daily dose-equivalent, compared to management without that daily dose-equivalent, on the probability of hospital-onset CDI.

In 24,406 patient-days at intermediate probability of receipt, parenteral vancomycin increased risk of hospital-onset CDI, with an average treatment effect of 0.0096 cases per daily dose-equivalent (95% CI: 0.0053—0.0138). In 38,003 patient-days at intermediate probability of receipt, cefepime also increased subsequent CDI risk, with an estimated effect of 0.0074 more cases per daily dose-equivalent (95% CI: 0.0022—0.0126).

Among common empiric antibiotics, parenteral vancomycin and cefepime appeared to increase risk of hospital-onset CDI. Causal inference observational study designs can be used to estimate patient-level harms of interventions such as empiric antimicrobials.

Previous studies have linked social behaviors to COVID-19 risk in the general population. The impact of these behaviors among healthcare personnel, who face higher workplace exposure risks and possess greater prevention awareness, remains less explored.

We conducted a Prospective cohort study from December 2021 to May 2022, using monthly surveys. Exposures included (1) a composite of nine common social activities in the past month and (2) similarity of social behavior compared to pre-pandemic. Outcomes included self-reported SARS-CoV-2 infection (primary)and testing for SARS-CoV-2 (secondary). Mixed-effect logistic regression assessed the association between social behavior and outcomes, adjusting for baseline and time-dependent covariates. To account for missed surveys, we employed inverse probability-of-censoring weighting with a propensity score approach.

An academic healthcare system.

Healthcare personnel.

Of 1,302 healthcare personnel who completed ≥2 surveys, 244 reported ≥1 positive test during the study, resulting in a cumulative incidence of 19%. More social activities in the past month and social behavior similar to pre-pandemic levels were associated with increased likelihood of SARS-CoV-2 infection (recent social activity composite: OR = 1.11, 95% CI 1.02–1.21; pre-pandemic social similarity: OR = 1.14, 95% CI 1.07–1.21). Neither was significantly associated with testing for SARS-CoV-2.

Healthcare personnel social behavior outside work was associated with a higher risk for COVID-19. To protect the hospital workforce, risk mitigation strategies for healthcare personnel should focus on both the community and workplace.

Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.

Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.

We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.

Anxiety disorders and treatment-resistant major depressive disorder (TRD) are often comorbid. Studies suggest ketamine has anxiolytic and antidepressant properties.

To investigate if subcutaneous racemic ketamine, delivered twice weekly for 4 weeks, reduces anxiety in people with TRD.

The Ketamine for Adult Depression Study was a multisite 4-week randomised, double-blind, active (midazolam)-controlled trial. The study initially used fixed low dose ketamine (0.5 mg/kg, cohort 1), before protocol revision to flexible, response-guided dosing (0.5–0.9 mg/kg, cohort 2). This secondary analysis assessed anxiety using the Hamilton Anxiety (HAM-A) scale (primary measure) and ‘inner tension’ item 3 of the Montgomery–Åsberg Depression Rating Scale (MADRS), at baseline, 4 weeks (end treatment) and 4 weeks after treatment end. Analyses of change in anxiety between ketamine and midazolam groups included all participants who received at least one treatment (n = 174), with a mixed effects repeated measures model used to assess the primary anxiety measure. The trial was registered at www.anzctr.org.au (ACTRN12616001096448).

In cohort 1 (n = 68) the reduction in HAM-A score was not statistically significant: −1.4 (95% CI [−8.6, 3.2], P = 0.37), whereas a significant reduction was seen for cohort 2 (n = 106) of −4.0 (95% CI [−10.6, −1.9], P = 0.0058), favouring ketamine over midazolam. These effects were mediated by total MADRS and were not maintained at 4 weeks after treatment end. MADRS item 3 was also significantly reduced in cohort 2 (P = 0.026) but not cohort 1 (P = 0.96).

Ketamine reduces anxiety in people with TRD when administered subcutaneously in adequate doses.

The prenatal and early-life periods pose a crucial neurodevelopmental window whereby disruptions to the intestinal microbiota and the developing brain may have adverse impacts. As antibiotics affect the human intestinal microbiome, it follows that early-life antibiotic exposure may be associated with later-life psychiatric or neurocognitive outcomes.

To explore the association between early-life (in utero and early childhood (age 0–2 years)) antibiotic exposure and the subsequent risk of psychiatric and neurocognitive outcomes.

A search was conducted using Medline, PsychINFO and Excerpta Medica databases on 20 November 2023. Risk of bias was assessed using the Newcastle-Ottawa scale, and certainty was assessed using the grading of recommendations, assessment, development and evaluation (GRADE) certainty assessment.

Thirty studies were included (n = 7 047 853 participants). Associations were observed between in utero antibiotic exposure and later development of autism spectrum disorder (ASD) (odds ratio 1.09, 95% CI: 1.02–1.16) and attention-deficit hyperactivity disorder (ADHD) (odds ratio 1.19, 95% CI: 1.11–1.27) and early-childhood exposure and later development of ASD (odds ratio 1.19, 95% CI: 1.01–1.40), ADHD (odds ratio 1.33, 95% CI: 1.20–1.48) and major depressive disorder (MDD) (odds ratio 1.29, 95% CI: 1.04–1.60). However, studies that used sibling control groups showed no significant association between early-life exposure and ASD or ADHD. No studies in MDD used sibling controls. Using the GRADE certainty assessment, all meta-analyses but one were rated very low certainty, largely owing to methodological and statistical heterogeneity.

While there was weak evidence for associations between antibiotic use in early-life and later neurodevelopmental outcomes, these were attenuated in sibling-controlled subgroup analyses. Thus, associations may be explained by genetic and familial confounding, and studies failing to utilise sibling-control groups must be interpreted with caution. PROSPERO ID: CRD42022304128