To evaluate the impact of a diagnostic stewardship intervention on Clostridioides difficile healthcare-associated infections (HAI).

Quality improvement study.

Two urban acute care hospitals.

All inpatient stool testing for C. difficile required review and approval prior to specimen processing in the laboratory. An infection preventionist reviewed all orders daily through chart review and conversations with nursing; orders meeting clinical criteria for testing were approved, orders not meeting clinical criteria were discussed with the ordering provider. The proportion of completed tests meeting clinical criteria for testing and the primary outcome of C. difficile HAI were compared before and after the intervention.

The frequency of completed C. difficile orders not meeting criteria was lower [146 (7.5%) of 1,958] in the intervention period (January 10, 2022–October 14, 2022) than in the sampled 3-month preintervention period [26 (21.0%) of 124; P < .001]. C. difficile HAI rates were 8.80 per 10,000 patient days prior to the intervention (March 1, 2021–January 9, 2022) and 7.69 per 10,000 patient days during the intervention period (incidence rate ratio, 0.87; 95% confidence interval, 0.73–1.05; P = .13).

A stringent order-approval process reduced clinically nonindicated testing for C. difficile but did not significantly decrease HAIs.

To determine the proportion of hospitals that implemented 6 leading practices in their antimicrobial stewardship programs (ASPs). Design: Cross-sectional observational survey.

Acute-care hospitals.

ASP leaders.

Advance letters and electronic questionnaires were initiated February 2020. Primary outcomes were percentage of hospitals that (1) implemented facility-specific treatment guidelines (FSTG); (2) performed interactive prospective audit and feedback (PAF) either face-to-face or by telephone; (3) optimized diagnostic testing; (4) measured antibiotic utilization; (5) measured C. difficile infection (CDI); and (6) measured adherence to FSTGs.

Of 948 hospitals invited, 288 (30.4%) completed the questionnaire. Among them, 82 (28.5%) had <99 beds, 162 (56.3%) had 100–399 beds, and 44 (15.2%) had ≥400+ beds. Also, 230 (79.9%) were healthcare system members. Moreover, 161 hospitals (54.8%) reported implementing FSTGs; 214 (72.4%) performed interactive PAF; 105 (34.9%) implemented procedures to optimize diagnostic testing; 235 (79.8%) measured antibiotic utilization; 258 (88.2%) measured CDI; and 110 (37.1%) measured FSTG adherence. Small hospitals performed less interactive PAF (61.0%; P = .0018). Small and nonsystem hospitals were less likely to optimize diagnostic testing: 25.2% (P = .030) and 21.0% (P = .0077), respectively. Small hospitals were less likely to measure antibiotic utilization (67.8%; P = .0010) and CDI (80.3%; P = .0038). Nonsystem hospitals were less likely to implement FSTGs (34.3%; P < .001).

Significant variation exists in the adoption of ASP leading practices. A minority of hospitals have taken action to optimize diagnostic testing and measure adherence to FSTGs. Additional efforts are needed to expand adoption of leading practices across all acute-care hospitals with the greatest need in smaller hospitals.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Benzodiazepine (BZD) prescription rates have increased over the past decade in the United States. Available literature indicates that sociodemographic factors may influence diagnostic patterns and/or prescription behaviour. Herein, the aim of this study is to determine whether the gender of the prescriber and/or patient influences BZD prescription.

Cross-sectional study using data from the Florida Medicaid Managed Medical Assistance Program from January 1, 2018 to December 31, 2018. Eligible recipients ages 18 to 64, inclusive, enrolled in the Florida Medicaid plan for at least 1 day, and were dually eligible. Recipients either had a serious mental illness (SMI), or non-SMI and anxiety.

Total 125 463 cases were identified (i.e., received BZD or non-BZD prescription). Main effect of patient and prescriber gender was significant F(1, 125 459) = 0.105, P = 0 .745, partial η2 < 0.001. Relative risk (RR) of male prescribers prescribing a BZD compared to female prescribers was 1.540, 95% confidence intervals (CI) [1.513, 1.567], whereas the RR of male patients being prescribed a BZD compared to female patients was 1.16, 95% CI [1.14, 1.18]. Main effects of patient and prescriber gender were statistically significant F(1, 125 459) = 188.232, P < 0.001, partial η2 = 0.001 and F(1, 125 459) = 349.704, P < 0.001, partial η2 = 0.013, respectively.

Male prescribers are more likely to prescribe BZDs, and male patients are more likely to receive BZDs. Further studies are required to characterize factors that influence this gender-by-gender interaction.

To update current estimates of non–device-associated pneumonia (ND pneumonia) rates and their frequency relative to ventilator associated pneumonia (VAP), and identify risk factors for ND pneumonia.

Cohort study.

Academic teaching hospital.

All adult hospitalizations between 2013 and 2017 were included. Pneumonia (device associated and non–device associated) were captured through comprehensive, hospital-wide active surveillance using CDC definitions and methodology.

From 2013 to 2017, there were 163,386 hospitalizations (97,485 unique patients) and 771 pneumonia cases (520 ND pneumonia and 191 VAP). The rate of ND pneumonia remained stable, with 4.15 and 4.54 ND pneumonia cases per 10,000 hospitalization days in 2013 and 2017 respectively (P = .65). In 2017, 74% of pneumonia cases were ND pneumonia. Male sex and increasing age we both associated with increased risk of ND pneumonia. Additionally, patients with chronic bronchitis or emphysema (hazard ratio [HR], 2.07; 95% confidence interval [CI], 1.40–3.06), congestive heart failure (HR, 1.48; 95% CI, 1.07–2.05), or paralysis (HR, 1.72; 95% CI, 1.09–2.73) were also at increased risk, as were those who were immunosuppressed (HR, 1.54; 95% CI, 1.18–2.00) or in the ICU (HR, 1.49; 95% CI, 1.06–2.09). We did not detect a change in ND pneumonia risk with use of chlorhexidine mouthwash, total parenteral nutrition, all medications of interest, and prior ventilation.

The incidence rate of ND pneumonia did not change from 2013 to 2017, and 3 of 4 nosocomial pneumonia cases were non–device associated. Hospital infection prevention programs should consider expanding the scope of surveillance to include non-ventilated patients. Future research should continue to look for modifiable risk factors and should assess potential prevention strategies.

To update current estimates of non–device-associated urinary tract infection (ND-UTI) rates and their frequency relative to catheter-associated UTIs (CA-UTIs) and to identify risk factors for ND-UTIs.

Cohort study.

Academic teaching hospital.

All adult hospitalizations between 2013 and 2017 were included. UTIs (device and non-device associated) were captured through comprehensive, hospital-wide active surveillance using Centers for Disease Control and Prevention case definitions and methodology.

From 2013 to 2017 there were 163,386 hospitalizations (97,485 unique patients) and 1,273 UTIs (715 ND-UTIs and 558 CA-UTIs). The rate of ND-UTIs remained stable, decreasing slightly from 6.14 to 5.57 ND-UTIs per 10,000 hospitalization days during the study period (P = .15). However, the proportion of UTIs that were non–device related increased from 52% to 72% (P < .0001). Female sex (hazard ratio [HR], 1.94; 95% confidence interval [CI], 1.50–2.50) and increasing age were associated with increased ND-UTI risk. Additionally, the following conditions were associated with increased risk: peptic ulcer disease (HR, 2.25; 95% CI, 1.04–4.86), immunosuppression (HR, 1.48; 95% CI, 1.15–1.91), trauma admissions (HR, 1.36; 95% CI, 1.02–1.81), total parenteral nutrition (HR, 1.99; 95% CI, 1.35–2.94) and opioid use (HR, 1.62; 95% CI, 1.10–2.32). Urinary retention (HR, 1.41; 95% CI, 0.96–2.07), suprapubic catheterization (HR, 2.28; 95% CI, 0.88–5.91), and nephrostomy tubes (HR, 2.02; 95% CI, 0.83–4.93) may also increase risk, but estimates were imprecise.

Greater than 70% of UTIs are now non–device associated. Current targeted surveillance practices should be reconsidered in light of this changing landscape. We identified several modifiable risk factors for ND-UTIs, and future research should explore the impact of prevention strategies that target these factors.

There is a known high prevalence of genetic and clinical syndrome diagnoses in the paediatric cardiac population. These disorders often have multisystem effects, which may have an important impact on neurodevelopmental outcomes. Taken together, these facts suggest that patients and families may benefit from consultation by genetic specialists in a cardiac neurodevelopmental clinic.

This study assessed the burden of genetic disorders and utility of genetics evaluation in a cardiac neurodevelopmental clinic.

A retrospective chart review was conducted of patients evaluated in a cardiac neurodevelopmental clinic from 6 December, 2011 to 16 April, 2013. All patients were seen by a cardiovascular geneticist with genetic counselling support.

A total of 214 patients were included in this study; 64 of these patients had a pre-existing genetic or syndromic diagnosis. Following genetics evaluation, an additional 19 were given a new clinical or laboratory-confirmed genetic diagnosis including environmental such as teratogenic exposures, malformation associations, chromosomal disorders, and single-gene disorders. Genetic testing was recommended for 112 patients; radiological imaging to screen for congenital anomalies for 17 patients; subspecialist medical referrals for 73 patients; and non-genetic clinical laboratory testing for 14 patients. Syndrome-specific guidelines were available and followed for 25 patients with known diagnosis. American Academy of Pediatrics Red Book asplenia guideline recommendations were given for five heterotaxy patients, and family-based cardiac screening was recommended for 23 families affected by left ventricular outflow tract obstruction.

Genetics involvement in a cardiac neurodevelopmental clinic is helpful in identifying new unifying diagnoses and providing syndrome-specific care, which may impact the patient’s overall health status and neurodevelopmental outcome.

Cognitive dysfunction is common in major depressive disorder (MDD) and a critical determinant of health outcome. Anhedonia is a criterion item toward the diagnosis of a major depressive episode (MDE) and a well-characterized domain in MDD. We sought to determine the extent to which variability in self-reported cognitive function correlates with anhedonia.

A post hoc analysis was conducted using data from (N=369) participants with a Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM-IV-TR)-defined diagnosis of MDD who were enrolled in the International Mood Disorders Collaborative Project (IMDCP) between January 2008 and July 2013. The IMDCP is a collaborative research platform at the Mood Disorders Psychopharmacology Unit, University of Toronto, Toronto, Canada, and the Cleveland Clinic, Cleveland, Ohio. Measures of cognitive function, anhedonia, and depression severity were analyzed using linear regression equations.

A total of 369 adults with DSM-IV-TR–defined MDD were included in this analysis. Self-rated cognitive impairment [ie, as measured by the Adult ADHD Self-Report Scale (ASRS)] was significantly correlated with a proxy measure of anhedonia (r=0.131, p=0.012). Moreover, total depression symptom severity, as measured by the total Montgomery–Åsberg Depression Rating Scale (MADRS) score, was also significantly correlated with self-rated measures of cognitive dysfunction (r=0.147, p=0.005). The association between anhedonia and self-rated cognitive dysfunction remained significant after adjusting for illness severity (r=0.162, p=0.007).

These preliminary results provide empirical data for the testable hypothesis that anhedonia and self-reported cognitive function in MDD are correlated yet dissociable domains. The foregoing observation supports the hypothesis of overlapping yet discrete neurobiological substrates for these domains.