Pontifícia Universidade Católica do Rio de Janeiro

Generalized anxiety disorder (GAD) and chronic pain often co-occur, and cannabidiol (CBD) has a promising treatment for both conditions. In this study, we evaluated whether chronic systemic treatment with CBD decreases pain sensitivity and anxiety-like behavior in a validated animal model of GAD - the Carioca rat lineages, selectively bred based on extreme responses to contextual fear conditioning: high freezing (CHF), low freezing (CLF), and a non-selected control group (CTL). Male rats from each lineage (n = 32 per group) were submitted to a chronic constriction injury of the sciatic nerve (CCI) or SHAM surgery. Sensory responses were assessed with the von Frey (mechanical sensitivity) and acetone (thermal sensitivity to cold) tests before CCI and on postoperative days 13 and 23. CBD (5 mg/kg, i.p., daily) was administered from day 14-23. Locomotor and anxiety-like behaviors were evaluated using the open field test (OFT) on day 22, and contextual fear conditioning (CFC) was reassessed on day 24. CBD treatment reduced allodynia across all lineages, although this effect was less in CHF rats. In the OFT, CBD exerted an anxiolytic effect in CTL and CHF rats under CCI, and increased locomotion was observed in CLF+SHAM rats. In the CFC, CBD reduced freezing in all SHAM-treated lineages but not in CHF rats with CCI. BDNF expression in the dorsal hippocampus varied by lineages, with CBD restoring BDNF levels in CTL rats. These findings suggest that CBD has differential analgesic and anxiolytic effects across anxiety-prone and anxiety-resistant rat breeding lineages and may modulate hippocampal plasticity through BDNF. Additionally, these preclinical results can improve future strategies for managing patients with GAD and chronic pain.

Severe community-acquired pneumonia (sCAP) strains ICU resources, demands efficient allocation and robust performance metrics for value-based care. Current ICU assessment methods often lack the necessary detail and risk adjustment for effective resource management, especially for complex patient populations such as those with sCAP.

This study investigated whether the machine learning-based Standardized Length of Stay Ratio (SLOSR) could reliably measure risk-adjusted LOS for sCAP patients, enabling benchmarking. SLOSR is calculated as the sum of observed length of stay (LOS) divided by the sum of predicted LOS, enabling ICU benchmarking for resource use.

We conducted a multicenter retrospective cohort study of 16,985 adult sCAP admissions across 220 ICUs in 57 Brazilian hospitals (January-December 2023). Data included demographics, comorbidities, SAPS 3, and ventilatory support. The machine learning model predicted LOS and calculated SLOSR. Rigorous validation included cross-validation, calibration plots, funnel plot analysis, RMSE, MAE, and R².

Hospital mortality was 9.3 %, ICU mortality 6.4 %, median ICU LOS 4 days, mean SAPS 3 score 50; 28.1 % received ventilatory support. The SLOSR demonstrated a robust grouped R² of 0.89. The model achieved RMSE = 4.57 and MAE = 3.10, with excellent calibration. Funnel plot analysis revealed a median SLOSR of 1.13 (Q1 = 0.9; Q3 = 1.34), underscoring its potential for benchmarking.

SLOSR shows promise as tool for assessing adjusted LOS as a surrogate of resource use in sCAP patients in the context of Brazilian ICUs. Further research is needed to validate its performance in other settings.