To identify risk factors for methicillin-susceptible (MSSA) and methicillin-resistant S. aureus (MRSA) nasal carriage and surgical site infection (SSI) among patients undergoing fracture fixation procedures who were included in a quality improvement protocol involving screening patients for S. aureus nasal carriage and treating carriers with intranasal mupirocin and chlorhexidine bathing.

Retrospective cohort study.

Level 1 trauma center.

1,254 adults who underwent operative fixation of 1,298 extremity or pelvis fractures between 8/1/2014 – 7/31/2017.

We calculated rates of S. aureus nasal carriage and SSI. We used multivariable stepwise logistic regression and selected the final models based on Akaike information criterion.

Of the 1,040 screened first procedures, 262 (25.19%) were performed on S. aureus nasal carriers: 211 (20.29%) on MSSA carriers and 51 (4.90%) on MRSA carriers. Long-term care facility residence (odds ratio [OR] 3.38; 95% confidence interval [CI] 1.17–9.76) was associated with MRSA nasal carriage. After adjusting for statistically and clinically significant variables, MRSA carriage was significantly associated with any SSI (OR 4.58; 95% CI 1.63–12.88), S. aureus SSI (OR 10.11; 95% CI 3.25–31.42), and MRSA SSI (OR 27.25; 95% CI 5.33–139.24), whereas MSSA carriage was not. Among S. aureus carriers, any chlorhexidine use was documented for 232 (88.55%), and any intranasal mupirocin was documented for 85 (40.28%) MSSA carriers and 33 (64.71%) MRSA carriers.

MRSA carriage was associated with a significant risk of SSI after operative fracture fixation. Many carriers did not undergo decolonization, suggesting that a simplified decolonization protocol is needed.

Negative symptoms are a key feature of several psychiatric disorders. Difficulty identifying common neurobiological mechanisms that cut across diagnostic boundaries might result from equifinality (i.e., multiple mechanistic pathways to the same clinical profile), both within and across disorders. This study used a data-driven approach to identify unique subgroups of participants with distinct reward processing profiles to determine which profiles predicted negative symptoms.

Participants were a transdiagnostic sample of youth from a multisite study of psychosis risk, including 110 individuals at clinical high-risk for psychosis (CHR; meeting psychosis-risk syndrome criteria), 88 help-seeking participants who failed to meet CHR criteria and/or who presented with other psychiatric diagnoses, and a reference group of 66 healthy controls. Participants completed clinical interviews and behavioral tasks assessing four reward processing constructs indexed by the RDoC Positive Valence Systems: hedonic reactivity, reinforcement learning, value representation, and effort–cost computation.

k-means cluster analysis of clinical participants identified three subgroups with distinct reward processing profiles, primarily characterized by: a value representation deficit (54%), a generalized reward processing deficit (17%), and a hedonic reactivity deficit (29%). Clusters did not differ in rates of clinical group membership or psychiatric diagnoses. Elevated negative symptoms were only present in the generalized deficit cluster, which also displayed greater functional impairment and higher psychosis conversion probability scores.

Contrary to the equifinality hypothesis, results suggested one global reward processing deficit pathway to negative symptoms independent of diagnostic classification. Assessment of reward processing profiles may have utility for individualized clinical prediction and treatment.

Information on the time spent completing cognitive testing is often collected, but such data are not typically considered when quantifying cognition in large-scale community-based surveys. We sought to evaluate the added value of timing data over and above traditional cognitive scores for the measurement of cognition in older adults.

We used data from the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (LASI-DAD) study (N = 4,091), to assess the added value of timing data over and above traditional cognitive scores, using item-specific regression models for 36 cognitive test items. Models were adjusted for age, gender, interviewer, and item score.

Compared to Quintile 3 (median time), taking longer to complete specific items was associated (p < 0.05) with lower cognitive performance for 67% (Quintile 5) and 28% (Quintile 4) of items. Responding quickly (Quintile 1) was associated with higher cognitive performance for 25% of simpler items (e.g., orientation for year), but with lower cognitive functioning for 63% of items requiring higher-order processing (e.g., digit span test). Results were consistent in a range of different analyses adjusting for factors including education, hearing impairment, and language of administration and in models using splines rather than quintiles.

Response times from cognitive testing may contain important information on cognition not captured in traditional scoring. Incorporation of this information has the potential to improve existing estimates of cognitive functioning.

The association between cannabis and psychosis is established, but the role of underlying genetics is unclear. We used data from the EU-GEI case-control study and UK Biobank to examine the independent and combined effect of heavy cannabis use and schizophrenia polygenic risk score (PRS) on risk for psychosis.

Genome-wide association study summary statistics from the Psychiatric Genomics Consortium and the Genomic Psychiatry Cohort were used to calculate schizophrenia and cannabis use disorder (CUD) PRS for 1098 participants from the EU-GEI study and 143600 from the UK Biobank. Both datasets had information on cannabis use.

In both samples, schizophrenia PRS and cannabis use independently increased risk of psychosis. Schizophrenia PRS was not associated with patterns of cannabis use in the EU-GEI cases or controls or UK Biobank cases. It was associated with lifetime and daily cannabis use among UK Biobank participants without psychosis, but the effect was substantially reduced when CUD PRS was included in the model. In the EU-GEI sample, regular users of high-potency cannabis had the highest odds of being a case independently of schizophrenia PRS (OR daily use high-potency cannabis adjusted for PRS = 5.09, 95% CI 3.08–8.43, p = 3.21 × 10−10). We found no evidence of interaction between schizophrenia PRS and patterns of cannabis use.

Regular use of high-potency cannabis remains a strong predictor of psychotic disorder independently of schizophrenia PRS, which does not seem to be associated with heavy cannabis use. These are important findings at a time of increasing use and potency of cannabis worldwide.

This review aims to identify the mechanistic relationships related to periodontal diseases and its possible association with changes in human milk composition and the composition and function of infants’ gut microbiome.

Maternal health conditions, especially inflammatory, are associated with altered human milk composition. It is not known whether maternal oral inflammatory diseases, including periodontal diseases, deleteriously affect human milk composition.

A narrative review was conducted according to SANRA, the Scale for the Assessment of Narrative Review Articles, guidelines. PubMed, Google Scholar, and Cochrane database of systematic reviews were searched from September 2019 up to December 2023 using keywords such as breast/human milk, maternal health/infections, and periodontal diseases. Reference lists of relevant articles were also screened. Our primary outcome of interest was human milk composition (i.e., any changes in macronutrients, immunological components, etc.). Secondary outcomes included changes in human milk microbiome and subsequent changes in the infant gut microbiome. Outcomes were synthesized using a narrative approach where the existing evidence and current literature were summarized. No risk of bias assessment of the studies was performed in this review.

The search yielded no studies investigating the relationship between periodontal diseases in nursing mothers and changes in human milk composition. However, a dose–response relationship exists between the severity of periodontal diseases and the risk of adverse pregnancy outcomes such as preterm birth. Mastitis and diabetes affected milk lipids. Immunoglobulin A (sIgA) was increased in mastitis, whereas reduced concentrations were reported in diabetes. Potential biological pathways through which periodontal diseases can negatively affect human milk composition include the systemic dissemination of inflammatory cytokines like IL-6, PGE2, and tumor necrosis factor (TNF)-β that can be up-regulated by bacterial by-products. This biological plausibility needs to be investigated, given the potentially negative impact on the quality of human milk that could be caused by periodontal inflammation.

The ability to remotely monitor cognitive skills is increasing with the ubiquity of smartphones. The Mobile Toolbox (MTB) is a new measurement system that includes measures assessing Executive Functioning (EF) and Processing Speed (PS): Arrow Matching, Shape-Color Sorting, and Number-Symbol Match. The purpose of this study was to assess their psychometric properties.

MTB measures were developed for smartphone administration based on constructs measured in the NIH Toolbox® (NIHTB). Psychometric properties of the resulting measures were evaluated in three studies with participants ages 18 to 90. In Study 1 (N = 92), participants completed MTB measures in the lab and were administered both equivalent NIH TB measures and other external measures of similar cognitive constructs. In Study 2 (N = 1,021), participants completed the equivalent NIHTB measures in the lab and then took the MTB measures on their own, remotely. In Study 3 (N = 168), participants completed MTB measures twice remotely, two weeks apart.

All three measures exhibited very high internal consistency and strong test-retest reliability, as well as moderately high correlations with comparable NIHTB tests and moderate correlations with external measures of similar constructs. Phone operating system (iOS vs. Android) had a significant impact on performance for Arrow Matching and Shape-Color Sorting, but no impact on either validity or reliability.

Results support the reliability and convergent validity of MTB EF and PS measures for use across the adult lifespan in remote, self-administered designs.

Diagnosis of acute ischemia typically relies on evidence of ischemic lesions on magnetic resonance imaging (MRI), a limited diagnostic resource. We aimed to determine associations of clinical variables and acute infarcts on MRI in patients with suspected low-risk transient ischemic attack (TIA) and minor stroke and to assess their predictive ability.

We conducted a post-hoc analysis of the Diagnosis of Uncertain-Origin Benign Transient Neurological Symptoms (DOUBT) study, a prospective, multicenter cohort study investigating the frequency of acute infarcts in patients with low-risk neurological symptoms. Primary outcome parameter was defined as diffusion-weighted imaging (DWI)-positive lesions on MRI. Logistic regression analysis was performed to evaluate associations of clinical characteristics with MRI-DWI-positivity. Model performance was evaluated by Harrel’s c-statistic.

In 1028 patients, age (Odds Ratio (OR) 1.03, 95% Confidence Interval (CI) 1.01–1.05), motor (OR 2.18, 95%CI 1.27–3.65) or speech symptoms (OR 2.53, 95%CI 1.28–4.80), and no previous identical event (OR 1.75, 95%CI 1.07–2.99) were positively associated with MRI-DWI-positivity. Female sex (OR 0.47, 95%CI 0.32–0.68), dizziness and gait instability (OR 0.34, 95%CI 0.14–0.69), normal exam (OR 0.55, 95%CI 0.35–0.85) and resolved symptoms (OR 0.49, 95%CI 0.30–0.78) were negatively associated. Symptom duration and any additional symptoms/symptom combinations were not associated. Predictive ability of the model was moderate (c-statistic 0.72, 95%CI 0.69–0.77).

Detailed clinical information is helpful in assessing the risk of ischemia in patients with low-risk neurological events, but a predictive model had only moderate discriminative ability. Patients with clinically suspected low-risk TIA or minor stroke require MRI to confirm the diagnosis of cerebral ischemia.

Pediatric medical devices lag behind adult devices due to economic barriers, smaller patient populations, changing anatomy and physiology of patients, regulatory hurdles, and especially difficulties in executing clinical trials. We investigated the requirements, challenges, associated timeline, and costs of conducting a multi-site pivotal clinical trial for a Class II pediatric physiologic monitoring device.

This case study focused on the negotiation of clinical trial agreements (CTAs), budgets, and Institutional Review Board (IRB) processing times for a pediatric device trial. We identified key factors contributing to delays in clinical trial execution and potential best practices to expedite the process while maintaining safety, ethics, and efficacy.

The total time from site contact to first patient enrollment averaged 14 months. CTA and budget negotiations were the most time-consuming processes, averaging nearly 10 and 9 months, respectively. Reliance and local IRB processing also contributed significantly to the timeline, overall adding an average of 6.5 months across institutions. Nearly half of all costs were devoted to regulatory oversight. The COVID-19 pandemic caused significant slowdowns and delays at multiple institutions during study enrollment. Despite these pandemic-induced delays, it is important to note that the issues and themes highlighted remain relevant and have post-pandemic applicability.

Our case study results underscore the importance of establishing efficient and standardized processing of CTAs, budget negotiations, and use of reliance IRBs to expedite clinical trial execution for pediatric devices. The findings also highlight the need for a national clinical trials network to streamline the clinical trial process.