This study introduces the prostate cancer linear energy transfer sensitivity index (PCLSI) as a novel method to predict relative biological effectiveness (RBE) in prostate cancer using linear energy transfer (LET) in proton therapy based on screening for DNA repair mutations.

Five prostate cancer cell lines with DNA repair mutations known to cause sensitivity to LET and DNA repair inhibitors were examined using published data. Relative Du145 LET sensitivity data were leveraged to deduce the LET equivalent of olaparib doses. The PCLSI model was built using three of the prostate cancer cell lines (LNCaP, 22Rv1 and Du145) with DNA mutation frequency from patient cohorts. The PCLSI model was compared against two established RBE models, McNamara and McMahon, for LET-optimized prostate cancer treatment plans.

The PCLSI model relies on the presence of eight DNA repair mutations: AR, ATM, BRCA1, BRCA2, CDH1, ETV1, PTEN and TP53, which are most likely to predict increased LET sensitivity and RBE in proton therapy. In the LET-optimized plan, the PCLSI model indicates that prostate cancer cells with these DNA repair mutations are more sensitive to increased LET than the McNamara and McMahon RBE models, with expected RBE increases ranging from 11%–33% at 2keV/µm.

The PCLSI model predicts increasing RBE as a function of LET in the presence of certain genetic mutations. The integration of LET-optimized proton therapy and genetic mutation profiling could be a significant step toward the use of individualized medicine to improve outcomes using RBE escalation without the potential toxicity of physical dose escalation.

Data evaluating timeliness of antibiotic therapy in Clostridioides difficile infections (CDI) are not well established. The study’s purpose was to evaluate the impact of time-to-CDI treatment on disease progression.

A case–control study was performed among hospitalized patients with CDI from 1/2018 to 2/2022. Inclusion criteria were age ≥65 years, first occurrence, non-severe CDI at symptom onset, and CDI treatment for ≥72 hours. Cases included patients who progressed to severe or fulminant CDI; controls were patients without CDI progression. Time to CDI treatment was evaluated in three ways: a classification and regression tree (CART)-defined threshold, time as a continuous variable, and time as a categorical variable.

272 patients were included; 136 with CDI progression, 136 patients without. The median (IQR) age was 74 (69–81) years, 167 (61%) were women, and 108 (40%) were immunosuppressed. CDI progression patients more commonly were toxin positive (66 [49%] vs 52 [38%], P = .087) with hospital-acquired disease (57 [42%] vs 29 [21%], P < 0.001). A CART-derived breakpoint for optimal time-to-CDI treatment of 64 hours established early (184, 68%) and delayed treatment (88, 32%). When accounting for confounding variables, delayed CDI treatment was associated with disease progression (adjOR, 4.6; 95%CI, 2.6–8.2); this was observed regardless of how time-to-CDI-active therapy was evaluated (continuous adjOR, 1.02; categorical adjOR, 2.11).

Delayed CDI treatment was associated with disease progression and could represent an important antimicrobial stewardship measure with future evaluation.

This study describes the local Emergency Medical Services (EMS) response and patient encounters corresponding to the civil unrest occurring over a four-day period in Spring 2020 in Indianapolis, Indiana (USA).

This study describes the non-conventional EMS response to civil unrest. The study included patients encountered by EMS in the area of the civil unrest occurring in Indianapolis, Indiana from May 29 through June 1, 2020. The area of civil unrest defined by Indianapolis Metropolitan Police Department covered 15 blocks by 12 blocks (roughly 4.0 square miles) and included central Indianapolis. The study analyzed records and collected demographics, scene times, interventions, dispositions, EMS clinician narratives, transport destinations, and hospital course with outcomes from receiving hospitals for patients extracted from the area of civil unrest by EMS.

Twenty-nine patients were included with ages ranging from two to sixty-eight years. In total, EMS transported 72.4% (21 of 29) of the patients, with the remainder declining transport. Ballistic injuries from gun violence accounted for 10.3% (3 of 29) of injuries. Two additional fatalities from penetrating trauma occurred among patients without EMS contact within and during the civil unrest. Conditions not involving trauma occurred in 37.9% (11 of 29). Among transported patients, 33.3% (7 of 21) were admitted to the hospital and there was one fatality.

While most EMS transports did not result in hospitalization, it is important to note that the majority of EMS calls did result in a transport. There was a substantial amount of non-traumatic patient encounters. Trauma in many of the encounters was relatively severe, and the findings imply the need for rapid extraction methods from dangerous areas to facilitate timely in-hospital stabilization.

White matter hyperintensity (WMH) burden is greater, has a frontal-temporal distribution, and is associated with proxies of exposure to repetitive head impacts (RHI) in former American football players. These findings suggest that in the context of RHI, WMH might have unique etiologies that extend beyond those of vascular risk factors and normal aging processes. The objective of this study was to evaluate the correlates of WMH in former elite American football players. We examined markers of amyloid, tau, neurodegeneration, inflammation, axonal injury, and vascular health and their relationships to WMH. A group of age-matched asymptomatic men without a history of RHI was included to determine the specificity of the relationships observed in the former football players.

240 male participants aged 45-74 (60 unexposed asymptomatic men, 60 male former college football players, 120 male former professional football players) underwent semi-structured clinical interviews, magnetic resonance imaging (structural T1, T2 FLAIR, and diffusion tensor imaging), and lumbar puncture to collect cerebrospinal fluid (CSF) biomarkers as part of the DIAGNOSE CTE Research Project. Total WMH lesion volumes (TLV) were estimated using the Lesion Prediction Algorithm from the Lesion Segmentation Toolbox. Structural equation modeling, using Full-Information Maximum Likelihood (FIML) to account for missing values, examined the associations between log-TLV and the following variables: total cortical thickness, whole-brain average fractional anisotropy (FA), CSF amyloid ß42, CSF p-tau181, CSF sTREM2 (a marker of microglial activation), CSF neurofilament light (NfL), and the modified Framingham stroke risk profile (rFSRP). Covariates included age, race, education, APOE z4 carrier status, and evaluation site. Bootstrapped 95% confidence intervals assessed statistical significance. Models were performed separately for football players (college and professional players pooled; n=180) and the unexposed men (n=60). Due to differences in sample size, estimates were compared and were considered different if the percent change in the estimates exceeded 10%.

In the former football players (mean age=57.2, 34% Black, 29% APOE e4 carrier), reduced cortical thickness (B=-0.25, 95% CI [0.45, -0.08]), lower average FA (B=-0.27, 95% CI [-0.41, -.12]), higher p-tau181 (B=0.17, 95% CI [0.02, 0.43]), and higher rFSRP score (B=0.27, 95% CI [0.08, 0.42]) were associated with greater log-TLV. Compared to the unexposed men, substantial differences in estimates were observed for rFSRP (Bcontrol=0.02, Bfootball=0.27, 994% difference), average FA (Bcontrol=-0.03, Bfootball=-0.27, 802% difference), and p-tau181 (Bcontrol=-0.31, Bfootball=0.17, -155% difference). In the former football players, rFSRP showed a stronger positive association and average FA showed a stronger negative association with WMH compared to unexposed men. The effect of WMH on cortical thickness was similar between the two groups (Bcontrol=-0.27, Bfootball=-0.25, 7% difference).

These results suggest that the risk factor and biological correlates of WMH differ between former American football players and asymptomatic individuals unexposed to RHI. In addition to vascular risk factors, white matter integrity on DTI showed a stronger relationship with WMH burden in the former football players. FLAIR WMH serves as a promising measure to further investigate the late multifactorial pathologies of RHI.

Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians.

In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance.

Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12.

Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.

Delayed cerebral ischemia (DCI) is a complication of aneurysmal subarachnoid hemorrhage (aSAH) and is associated with significant morbidity and mortality. There is little high-quality evidence available to guide the management of DCI. The Canadian Neurosurgery Research Collaborative (CNRC) is comprised of resident physicians who are positioned to capture national, multi-site data. The objective of this study was to evaluate practice patterns of Canadian physicians regarding the management of aSAH and DCI.

We performed a cross-sectional survey of Canadian neurosurgeons, intensivists, and neurologists who manage aSAH. A 19-question electronic survey (Survey Monkey) was developed and validated by the CNRC following a DCI-related literature review (PubMed, Embase). The survey was distributed to members of the Canadian Neurosurgical Society and to Canadian members of the Neurocritical Care Society. Responses were analyzed using quantitative and qualitative methods.

The response rate was 129/340 (38%). Agreement among respondents was limited to the need for intensive care unit admission, use of clinical and radiographic monitoring, and prophylaxis for the prevention of DCI. Several inconsistencies were identified. Indications for starting hyperdynamic therapy varied. There was discrepancy in the proportion of patients who felt to require IV milrinone, IA vasodilators, or physical angioplasty for treatment of DCI. Most respondents reported their facility does not utilize a standardized definition for DCI.

DCI is an important clinical entity for which no homogeneity and standardization exists in management among Canadian practitioners. The CNRC calls for the development of national standards in the definition, identification, and treatment of DCI.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

To assess the mental health of pregnant women, with reference to anxiety, depression and obsessive-compulsive (OC) symptoms, during the COVID-19 pandemic.

A cross-sectional survey was conducted in Ireland during the third wave of the pandemic between February and March 2021. Psychiatric, social and obstetric information was collected from pregnant women in a Dublin maternity hospital, alongside self-reported measures of mental health status.

Of 392 women responding, 23.7% had anxiety, scoring >9 for GAD-7 (7-item generalised anxiety disorder), 20.4% had depression, scoring >9 for PHQ-9 (9-item depression screening tool: Patient health questionnaire) and 10.3% had obsessive-compulsive disorder (OCD), scoring >13 for Yale–Brown obsessive-compulsive scale symptom checklist (Y-BOCS). Amongst self-reported OCD symptoms, there was a preponderance for obsessions rather than compulsions. Of 392 women, 36.2% described their mental health as worse during the pandemic, most frequently describing symptoms of anxiety and sleep disturbance. When analysed against test scores, self-reported worsening of mental health was significantly associated with higher scores on the GAD-7, PHQ-9 and Y-BOCS scales. The three scores were positively interrelated. Poor mental health scores were associated with self-reported strain in relationship with the baby’s father, and current or previous history of mental illness.

This study found high levels of depression, anxiety and OC symptoms amongst pregnant women during COVID-19. This highlights the vulnerability of this group to mental illness and the importance of enhanced screening and support during pandemics.