Because pediatric anxiety disorders precede the onset of many other problems, successful prediction of response to the first-line treatment, cognitive-behavioral therapy (CBT), could have a major impact. This study evaluates whether structural and resting-state functional magnetic resonance imaging can predict post-CBT anxiety symptoms.

Two datasets were studied: (A) one consisted of n = 54 subjects with an anxiety diagnosis, who received 12 weeks of CBT, and (B) one consisted of n = 15 subjects treated for 8 weeks. Connectome predictive modeling (CPM) was used to predict treatment response, as assessed with the PARS. The main analysis included network edges positively correlated with treatment outcome and age, sex, and baseline anxiety severity as predictors. Results from alternative models and analyses are also presented. Model assessments utilized 1000 bootstraps, resulting in a 95% CI for R2, r, and mean absolute error (MAE).

The main model showed a MAE of approximately 3.5 (95% CI: [3.1–3.8]) points, an R2 of 0.08 [−0.14–0.26], and an r of 0.38 [0.24–0.511]. When testing this model in the left-out sample (B), the results were similar, with an MAE of 3.4 [2.8–4.7], R2−0.65 [−2.29–0.16], and r of 0.4 [0.24–0.54]. The anatomical metrics showed a similar pattern, where models rendered overall low R2.

The analysis showed that models based on earlier promising results failed to predict clinical outcomes. Despite the small sample size, this study does not support the extensive use of CPM to predict outcomes in pediatric anxiety.

Previous studies identified clusters of first-episode psychosis (FEP) patients based on cognition and premorbid adjustment. This study examined a range of socio-environmental risk factors associated with clusters of FEP, aiming a) to compare clusters of FEP and community controls using the Maudsley Environmental Risk Score for psychosis (ERS), a weighted sum of the following risks: paternal age, childhood adversities, cannabis use, and ethnic minority membership; b) to explore the putative differences in specific environmental risk factors in distinguishing within patient clusters and from controls.

A univariable general linear model (GLS) compared the ERS between 1,263 community controls and clusters derived from 802 FEP patients, namely, low (n = 223) and high-cognitive-functioning (n = 205), intermediate (n = 224) and deteriorating (n = 150), from the EU-GEI study. A multivariable GLS compared clusters and controls by different exposures included in the ERS.

The ERS was higher in all clusters compared to controls, mostly in the deteriorating (β=2.8, 95% CI 2.3 3.4, η2 = 0.049) and the low-cognitive-functioning cluster (β=2.4, 95% CI 1.9 2.8, η2 = 0.049) and distinguished them from the cluster with high-cognitive-functioning. The deteriorating cluster had higher cannabis exposure (meandifference = 0.48, 95% CI 0.49 0.91) than the intermediate having identical IQ, and more people from an ethnic minority (meandifference = 0.77, 95% CI 0.24 1.29) compared to the high-cognitive-functioning cluster.

High exposure to environmental risk factors might result in cognitive impairment and lower-than-expected functioning in individuals at the onset of psychosis. Some patients’ trajectories involved risk factors that could be modified by tailored interventions.

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.

With the rise of online references, podcasts, webinars, self-test tools, and social media, it is worthwhile to understand whether textbooks continue to provide value in medical education, and to assess the capacity they serve during fellowship training.

A prospective mixed-methods study based on surveys that were disseminated to seven paediatric cardiology fellowship programmes around the world. Participants were asked to read an assigned chapter of Anderson’s Pediatric Cardiology 4th Edition textbook, followed by the completion of the survey. Open-ended questions included theming and grouping responses as appropriate.

The survey was completed by 36 participants. When asked about the content, organisation, and utility of the chapter, responses were generally positive, at greater than 89%. The chapters, overall, were rated relatively easy to read, scoring at 6.91, with standard deviations plus or minus 1.72, on a scale from 1 to 10, with higher values meaning better results. When asked to rank their preferences in where they obtain educational content, textbooks were ranked the second highest, with in-person teaching ranking first. Several themes were identified including the limitations of the use of textbook use, their value, and ways to enhance learning from their reading. There was also a near-unanimous desire for more time to self-learn and read during fellowship.

Textbooks are still highly valued by trainees. Many opportunities exist, nonetheless, to improve how they can be organised to deliver information optimally. Future efforts should look towards making them more accessible, and to include more resources for asynchronous learning.

To evaluate temporal trends in the prevalence of gram-negative bacteria (GNB) with difficult-to-treat resistance (DTR) in the southeastern United States. Secondary objective was to examine the use of novel β-lactams for GNB with DTR by both antimicrobial use (AU) and a novel metric of adjusted AU by microbiological burden (am-AU).

Retrospective, multicenter, cohort.

Ten hospitals in the southeastern United States.

GNB with DTR including Enterobacterales, Pseudomonas aeruginosa, and Acinetobacter spp. from 2015 to 2020 were tracked at each institution. Cumulative AU of novel β-lactams including ceftolozane/tazobactam, ceftazidime/avibactam, meropenem/vaborbactam, imipenem/cilastatin/relebactam, and cefiderocol in days of therapy (DOT) per 1,000 patient-days was calculated. Linear regression was utilized to examine temporal trends in the prevalence of GNB with DTR and cumulative AU of novel β-lactams.

The overall prevalence of GNB with DTR was 0.85% (1,223/143,638) with numerical increase from 0.77% to 1.00% between 2015 and 2020 (P = .06). There was a statistically significant increase in DTR Enterobacterales (0.11% to 0.28%, P = .023) and DTR Acinetobacter spp. (4.2% to 18.8%, P = .002). Cumulative AU of novel β-lactams was 1.91 ± 1.95 DOT per 1,000 patient-days. When comparing cumulative mean AU and am-AU, there was an increase from 1.91 to 2.36 DOT/1,000 patient-days, with more than half of the hospitals shifting in ranking after adjustment for microbiological burden.

The overall prevalence of GNB with DTR and the use of novel β-lactams remain low. However, the uptrend in the use of novel β-lactams after adjusting for microbiological burden suggests a higher utilization relative to the prevalence of GNB with DTR.

To understand how healthcare facilities employ contact precautions for patients with multidrug-resistant organisms (MDROs) in the post–coronavirus disease 2019 (COVID-19) era and explore changes since 2014.

Cross-sectional survey.

Emerging Infections Network (EIN) physicians involved in infection prevention or hospital epidemiology.

In September 2022, we sent via email an 8-question survey on contact precautions and adjunctive measures to reduce MDRO transmission in inpatient facilities. We also asked about changes since the COVID-19 pandemic. We used descriptive statistics to summarize data and compared results to a similar survey administered in 2014.

Of 708 EIN members, 283 (40%) responded to the survey and 201 reported working in infection prevention. A majority of facilities (66% and 69%) routinely use contact precautions for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) respectively, compared to 93% and 92% in 2014. Nearly all (>90%) use contact precautions for Candida auris, carbapenem-resistant Enterobacterales (CRE), and carbapenem-resistant Acinetobacter baumannii. More variability was reported for carbapenem-resistant Pseudomonas aeruginosa and extended-spectrum β-lactamase–producing gram-negative organisms. Compared to 2014, fewer hospitals perform active surveillance for MRSA and VRE. Overall, 90% of facilities used chlorhexidine gluconate bathing in all or select inpatients, and 53% used ultraviolet light or hydrogen peroxide vapor disinfection at discharge. Many respondents (44%) reported changes to contact precautions since COVID-19 that remain in place.

Heterogeneity exists in the use of transmission-based precautions and adjunctive infection prevention measures aimed at reducing MDRO transmission. This variation reflects a need for updated and specific guidance, as well as further research on the use of contact precautions in healthcare facilities.

Despite infection control guidance, sporadic nosocomial coronavirus disease 2019 (COVID-19) outbreaks occur. We describe a complex severe acute respiratory coronavirus virus 2 (SARS-CoV-2) cluster with interfacility spread during the SARS-CoV-2 δ (delta) pandemic surge in the Midwest.

This study was conducted in (1) a hematology-oncology ward in a regional academic medical center and (2) a geographically distant acute rehabilitation hospital.

We conducted contact tracing for each COVID-19 case to identify healthcare exposures within 14 days prior to diagnosis. Liberal testing was performed for asymptomatic carriage for patients and staff. Whole-genome sequencing was conducted for all available clinical isolates from patients and healthcare workers (HCWs) to identify transmission clusters.

In the immunosuppressed ward, 19 cases (4 patients, 15 HCWs) shared a genetically related SARS-CoV-2 isolate. Of these 4 patients, 3 died in the hospital or within 1 week of discharge. The suspected index case was a patient with new dyspnea, diagnosed during preprocedure screening. In the rehabilitation hospital, 20 cases (5 patients and 15 HCWs) positive for COVID-19, of whom 2 patients and 3 HCWs had an isolate genetically related to the above cluster. The suspected index case was a patient from the immune suppressed ward whose positive status was not detected at admission to the rehabilitation facility. Our response to this cluster included the following interventions in both settings: restricting visitors, restricting learners, restricting overflow admissions, enforcing strict compliance with escalated PPE, access to on-site free and frequent testing for staff, and testing all patients prior to hospital discharge and transfer to other facilities.

Stringent infection control measures can prevent nosocomial COVID-19 transmission in healthcare facilities with high-risk patients during pandemic surges. These interventions were successful in ending these outbreaks.

Clinical and experimental neuropsychology patients are not always able to complete a given test due to limitations in their functioning and it can lead to frustration and time wasted, leading researchers to examine the value of metrics that can be derived earlier in a test so as to ascertain and salvage useful information. The Trail Making Test (TMT) is an oft-utilized test of executive function and has been the focus of such exploration (e.g., first error vs. time to complete Trails B which can be lengthy in dementia cases and lead to discontinuation and loss of scorable data; Christidi et al., 2013; Correia et al., 2015). The present retrospective study utilized archival chart review to examine the association between a patient's diagnosis and occurrence of the first error on Trails B (TB1err).

De-identified data was culled from adult private practice records (n=137) in the northeastern United States (the study was conducted in compliance with local IRB review). Trails A and B times, as well as Digit Span scores (for checking construct validity) were pulled from reports, and Trails B record forms were scored to extract the enumerated stimulus where any first error was observed in the patient's rendering of the trail connecting alternating numbers and letters. Paired t-tests compared the average TB1err of normative individuals (no diagnosis) with patients with a primary diagnosis of mood disorder, traumatic brain injury (TBI), mild cognitive impairment (MCI), or dementia. Additionally, Pearson's correlations were computed comparing TB1err with Trails B time, and another test of executive function (Digit Span backwards).

The order of diagnoses according to the average occurrence of the first error on Trails B (from later, to sooner occurrence) was as follows: normative (no diagnosis), mood disorder, TBI, MCI, and finally dementia. There was a significant difference on this first error metric (TB1err) when comparing normative and dementia patients (p = .03; 8.3 vs 4.2 for the average enumeration of 1st error on Trails B). Furthermore, significant correlations were found between this derived TB1err metric and Digit Span backwards (r = .31; p <.001) as well as overall TrailsB performance (r = -.39; p < .001).

The present study adds to a growing literature on the utility of deriving test metrics to maximize useful data for clinical and experimental neuropsychology. Results from this retrospective chart review indicate additional validity data to support the use of extracting the first error on Trails B as a way to salvage useful data even when a patient may not be able to complete the full TMT as designed. In this preliminary sample there was a significant difference found for normative vs. dementia patients on this derived TB1err metric and suggests it is worthy of additional research to see if it can reliably differentiate various diagnoses. We expect this finding will also be useful in experimental designs wherein time is often limited and loss of data due to incomplete testing might be avoided by extracting the first error on TrailsB.

This narrative review updates the evidence base for cancer-related post-traumatic stress disorder (PTSD). Databases were searched in December 2021, and included EMBASE, Medline, PsycINFO and PubMed. Adults diagnosed with cancer who had symptoms of PTSD were included.

The initial search identified 182 records, and 11 studies were included in the final review. Psychological interventions were varied, and cognitive–behavioural therapy and eye movement desensitisation and reprocessing were perceived to be most efficacious. The studies were also independently rated for methodological quality, which was found to be hugely variable.

There remains a lack of high-quality intervention studies for PTSD in cancer, and there is a wide range of approaches to managing these conditions, with a large heterogeneity in the cancer populations examined and methodologies used. Specific studies designed with patient and public engagement and that tailor the PTSD intervention to particular cancer populations under investigation are required.

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.