Recruitment for rare disease studies is challenging due to small eligible populations. Traditional clinical research management systems often lack tools to track recruitment contacts prior to enrollment. The NET-PRO study, focused on neuroendocrine tumors (NETs), implemented a participation monitoring system to enhance recruitment efficiency and representativeness.

NET-PRO is a multicenter cohort study of 2538 adults diagnosed with gastroenteropancreatic (GEP) or lung NETs between January 2018 and September 2024. Recruitment occurred from January 2022 to February 2025 across 14 U.S. medical centers. Sites used flexible recruitment methods (email, mail, phone, in-clinic) and tracked contacts using REDCap-based tools. Participant characteristics were analyzed by enrollment mode (online or mail) and recruitment difficulty (number of contacts required prior to enrollment) using standardized mean differences, chi-square tests, and ANOVA.

Of 9279 contacted patients, 2675 consented (28.8%) and 2538 enrolled (27.4%). Most enrolled online (83.2%), while 16.8% enrolled by mail. Mail respondents were older, had lower education and income, and more comorbidities. Among those enrolled, recruitment difficulty was associated with older age, lower education and income, but not comorbidity. Over half of the most difficult-to-recruit participants enrolled online. Contact methods varied by attempt, with email dominating early contacts and phone/mail used more in later attempts.

A participation monitoring tool supported flexible, multimodal recruitment and improved sample representativeness in a rare cancer study. Tracking recruitment contacts enabled adaptive strategies and may reduce bias in observational research by enabling better outreach to harder-to-reach populations.

This study investigates the seasonal and regional distribution of paediatric laryngomalacia admissions in the United States, hypothesizing higher admission rates in winter and colder regions due to reduced sunlight exposure affecting vitamin D levels.

We analyzed data from the 2016 Kids’ Inpatient Database (KID), focusing on children under three years old. Laryngomalacia cases were identified using International Classification of Diseases and Related Health Problems 10th Revision (ICD-10) code Q31.5. Seasonal and regional differences in admission rates were assessed using Pearson’s chi-squared test, with a significance level of p less than 0.05.

Of 4,512,196 estimated national admissions, 11,638 were due to laryngomalacia. Admissions increased by 10.0 per cent in winter and decreased by 10.9 per cent in summer (p < 0.005). Regionally, admissions were higher in the Midwest/Central (18.6 per cent) and Northeast (9.3 per cent) and lower in the South (7.4 per cent) and West (11.1 per cent) (p < 0.005).

Laryngomalacia admissions are significantly influenced by seasonal and regional factors, likely related to environmental conditions affecting vitamin D synthesis.

Blood-based biomarkers represent a scalable and accessible approach for the detection and monitoring of Alzheimer’s disease (AD). Plasma phosphorylated tau (p-tau) and neurofilament light (NfL) are validated biomarkers for the detection of tau and neurodegenerative brain changes in AD, respectively. There is now emphasis to expand beyond these markers to detect and provide insight into the pathophysiological processes of AD. To this end, a reactive astrocytic marker, namely plasma glial fibrillary acidic protein (GFAP), has been of interest. Yet, little is known about the relationship between plasma GFAP and AD. Here, we examined the association between plasma GFAP, diagnostic status, and neuropsychological test performance. Diagnostic accuracy of plasma GFAP was compared with plasma measures of p-tau181 and NfL.

This sample included 567 participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC) Longitudinal Clinical Core Registry, including individuals with normal cognition (n=234), mild cognitive impairment (MCI) (n=180), and AD dementia (n=153). The sample included all participants who had a blood draw. Participants completed a comprehensive neuropsychological battery (sample sizes across tests varied due to missingness). Diagnoses were adjudicated during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using the Simoa platform. Binary logistic regression analyses tested the association between GFAP levels and diagnostic status (i.e., cognitively impaired due to AD versus unimpaired), controlling for age, sex, race, education, and APOE e4 status. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate diagnostic groups compared with plasma p-tau181 and NfL. Linear regression models tested the association between plasma GFAP and neuropsychological test performance, accounting for the above covariates.

The mean (SD) age of the sample was 74.34 (7.54), 319 (56.3%) were female, 75 (13.2%) were Black, and 223 (39.3%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having cognitive impairment (GFAP z-score transformed: OR=2.233, 95% CI [1.609, 3.099], p<0.001; non-z-transformed: OR=1.004, 95% CI [1.002, 1.006], p<0.001). ROC analyses, comprising of GFAP and the above covariates, showed plasma GFAP discriminated the cognitively impaired from unimpaired (AUC=0.75) and was similar, but slightly superior, to plasma p-tau181 (AUC=0.74) and plasma NfL (AUC=0.74). A joint panel of the plasma markers had greatest discrimination accuracy (AUC=0.76). Linear regression analyses showed that higher GFAP levels were associated with worse performance on neuropsychological tests assessing global cognition, attention, executive functioning, episodic memory, and language abilities (ps<0.001) as well as higher CDR Sum of Boxes (p<0.001).

Higher plasma GFAP levels differentiated participants with cognitive impairment from those with normal cognition and were associated with worse performance on all neuropsychological tests assessed. GFAP had similar accuracy in detecting those with cognitive impairment compared with p-tau181 and NfL, however, a panel of all three biomarkers was optimal. These results support the utility of plasma GFAP in AD detection and suggest the pathological processes it represents might play an integral role in the pathogenesis of AD.

Blood-based biomarkers offer a more feasible alternative to Alzheimer’s disease (AD) detection, management, and study of disease mechanisms than current in vivo measures. Given their novelty, these plasma biomarkers must be assessed against postmortem neuropathological outcomes for validation. Research has shown utility in plasma markers of the proposed AT(N) framework, however recent studies have stressed the importance of expanding this framework to include other pathways. There is promising data supporting the usefulness of plasma glial fibrillary acidic protein (GFAP) in AD, but GFAP-to-autopsy studies are limited. Here, we tested the association between plasma GFAP and AD-related neuropathological outcomes in participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC).

This sample included 45 participants from the BU ADRC who had a plasma sample within 5 years of death and donated their brain for neuropathological examination. Most recent plasma samples were analyzed using the Simoa platform. Neuropathological examinations followed the National Alzheimer’s Coordinating Center procedures and diagnostic criteria. The NIA-Reagan Institute criteria were used for the neuropathological diagnosis of AD. Measures of GFAP were log-transformed. Binary logistic regression analyses tested the association between GFAP and autopsy-confirmed AD status, as well as with semi-quantitative ratings of regional atrophy (none/mild versus moderate/severe) using binary logistic regression. Ordinal logistic regression analyses tested the association between plasma GFAP and Braak stage and CERAD neuritic plaque score. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate autopsy-confirmed AD status. All analyses controlled for sex, age at death, years between last blood draw and death, and APOE e4 status.

Of the 45 brain donors, 29 (64.4%) had autopsy-confirmed AD. The mean (SD) age of the sample at the time of blood draw was 80.76 (8.58) and there were 2.80 (1.16) years between the last blood draw and death. The sample included 20 (44.4%) females, 41 (91.1%) were White, and 20 (44.4%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having autopsy-confirmed AD (OR=14.12, 95% CI [2.00, 99.88], p=0.008). ROC analysis showed plasma GFAP accurately discriminated those with and without autopsy-confirmed AD on its own (AUC=0.75) and strengthened as the above covariates were added to the model (AUC=0.81). Increases in GFAP levels corresponded to increases in Braak stage (OR=2.39, 95% CI [0.71-4.07], p=0.005), but not CERAD ratings (OR=1.24, 95% CI [0.004, 2.49], p=0.051). Higher GFAP levels were associated with greater temporal lobe atrophy (OR=10.27, 95% CI [1.53,69.15], p=0.017), but this was not observed with any other regions.

The current results show that antemortem plasma GFAP is associated with non-specific AD neuropathological changes at autopsy. Plasma GFAP could be a useful and practical biomarker for assisting in the detection of AD-related changes, as well as for study of disease mechanisms.

Remitted psychotic depression (MDDPsy) has heterogeneity of outcome. The study's aims were to identify subgroups of persons with remitted MDDPsy with distinct trajectories of depression severity during continuation treatment and to detect predictors of membership to the worsening trajectory.

One hundred and twenty-six persons aged 18–85 years participated in a 36-week randomized placebo-controlled trial (RCT) that examined the clinical effects of continuing olanzapine once an episode of MDDPsy had remitted with sertraline plus olanzapine. Latent class mixed modeling was used to identify subgroups of participants with distinct trajectories of depression severity during the RCT. Machine learning was used to predict membership to the trajectories based on participant pre-trajectory characteristics.

Seventy-one (56.3%) participants belonged to a subgroup with a stable trajectory of depression scores and 55 (43.7%) belonged to a subgroup with a worsening trajectory. A random forest model with high prediction accuracy (AUC of 0.812) found that the strongest predictors of membership to the worsening subgroup were residual depression symptoms at onset of remission, followed by anxiety score at RCT baseline and age of onset of the first lifetime depressive episode. In a logistic regression model that examined depression score at onset of remission as the only predictor variable, the AUC (0.778) was close to that of the machine learning model.

Residual depression at onset of remission has high accuracy in predicting membership to worsening outcome of remitted MDDPsy. Research is needed to determine how best to optimize the outcome of psychotic MDDPsy with residual symptoms.

To evaluate whether incorporating mandatory prior authorization for Clostridioides difficile testing into antimicrobial stewardship pharmacist workflow could reduce testing in patients with alternative etiologies for diarrhea.

Single center, quasi-experimental before-and-after study.

Tertiary-care, academic medical center in Ann Arbor, Michigan.

Adult and pediatric patients admitted between September 11, 2019 and December 10, 2019 were included if they had an order placed for 1 of the following: (1) C. difficile enzyme immunoassay (EIA) in patients hospitalized >72 hours and received laxatives, oral contrast, or initiated tube feeds within the prior 48 hours, (2) repeat molecular multiplex gastrointestinal pathogen panel (GIPAN) testing, or (3) GIPAN testing in patients hospitalized >72 hours.

A best-practice alert prompting prior authorization by the antimicrobial stewardship program (ASP) for EIA or GIPAN testing was implemented. Approval required the provider to page the ASP pharmacist and discuss rationale for testing. The provider could not proceed with the order if ASP approval was not obtained.

An average of 2.5 requests per day were received over the 3-month intervention period. The weekly rate of EIA and GIPAN orders per 1,000 patient days decreased significantly from 6.05 ± 0.94 to 4.87 ± 0.78 (IRR, 0.72; 95% CI, 0.56–0.93; P = .010) and from 1.72 ± 0.37 to 0.89 ± 0.29 (IRR, 0.53; 95% CI, 0.37–0.77; P = .001), respectively.

We identified an efficient, effective C. difficile and GIPAN diagnostic stewardship approval model.