Analysis of trajectory changes and predictive factors of sense of coherence in patients after colorectal cancer surgery.

OBJECTIVE: To investigate the trajectories and potential categories of changes in the sense of coherence (SOC) in patients after colorectal cancer surgery and to analyze predictive factors. METHODS: From January to July 2023, 175 patients with colorectal cancer treated at a tertiary Grade A oncology hospital in Jiangsu Province were selected as the study subjects. Prior to surgery, SOC-13 scale, Patient-Generated Subjective Global Assessment (PG-SGA), Brief Illness Perception Questionnaire (BIPQ), and Social Support Rating Scale (SSRS) were used to survey the patients. SOC levels were measured multiple times at 1 week, 1 month, and 3 months post-surgery. Growth Mixture Modeling (GMM) was applied to fit the trajectory changes of SOC in patients after colorectal cancer surgery. Multinomial logistic regression was used to analyze the predictive factors of SOC trajectory changes. RESULTS: The SOC scores of patients at points T1-T4 were (65.27 ± 9.20), (63.65 ± 10.41), (63.85 ± 11.84), and (61.56 ± 12.65), respectively. Multinomial logistic regression results indicated that gender, employment status, disease stage, household monthly income, intestinal stoma, nutritional status, illness perception, and social support were predictors of SOC trajectory changes (P < 0.05). CONCLUSION: There is heterogeneity in the trajectory changes of SOC in patients after colorectal cancer surgery. Healthcare professionals should implement early precision interventions based on the patterns of changes and predictive factors in each trajectory category.

Identification of abnormal closed-loop pathways in patients with MRI-negative pharmacoresistant epilepsy.

Epilepsy is a disorder of brain networks, that is usually combined with cognitive and emotional impairment. However, most of the current research on closed-loop pathways in epilepsy is limited to the neuronal level or has focused only on known closed-loop pathways, and studies on abnormalities in closed-loop pathways in epilepsy at the whole-brain network level are lacking. A total of 26 patients with magnetic resonance imaging-negative pharmacoresistant epilepsy (MRIneg-PRE) and 26 healthy controls (HCs) were included in this study. Causal brain networks and temporal-lag brain networks were constructed from resting-state functional MRI data, and the Johnson algorithm was used to identify stable closed-loop pathways. Abnormal closed-loop pathways in the MRIneg-PRE cohort compared with the HC group were identified, and the associations of these pathways with indicators of cognitive and emotional impairments were examined via Pearson correlation analysis. The results revealed that the abnormal stable closed-loop pathways were distributed across the frontal, parietal, and occipital lobes and included altered functional connectivity values both within and between cerebral hemispheres. Four abnormal closed-loop pathways in the occipital lobe were associated with emotional and cognitive impairments. These abnormal pathways may serve as biomarkers for the diagnosis and guidance of individualized treatments for MRIneg-PRE patients.

Structural and functional changes in the default mode network in drug-resistant epilepsy.

PURPOSE: To investigate brain network properties and connectivity abnormalities of the default mode network (DMN) in drug-resistant epilepsy (DRE). The study was based on probabilistic fiber tracking and functional connectivity (FC) analysis, to explore the structural and functional connectivity patterns change between frontal lobe epilepsy (FLE) and temporal lobe epilepsy (TLE). METHODS: A total of 33 DRE patients (18 TLE and 15 FLE) and 30 healthy controls (HCs) were recruited. The volume fraction of the septal brain region of the DMN in DRE was calculated using FreeSurfer. The FC analysis was performed using Data Processing and Analysis for Brain Imaging in MATLAB. The structural connections between brain regions of the DMN were calculated based on probabilistic fiber tracking. RESULTS: The left precuneus (PCUN) volumes in epilepsy groups were lower than that in HCs. Compared with FLE, TLE showed reduced FC between the left hippocampus (HIP) and PCUN/medial frontal gyrus, and between the right inferior parietal lobule (IPL) and right superior temporal gyrus. Compared with HCs, FLE showed increased FCs between the right IPL and occipital lobe, and between the left superior frontal gyrus (SFG) and bilateral superior temporal gyrus. In terms of structural connectivity, TLE exhibited increased connectivity strength between the left SFG and left PCUN, and showed reduced connection strength between the left HIP and left posterior cingulate gyrus/left PCUN, when compared with the FLE. CONCLUSIONS: TLE and FLE patients showed structural and functional changes in the DMN. Compared with FLE patients, the TLE patients showed reduced structural and functional connection strengths between the left HIP and PCUN. These alterations in connection strengths holds promise for the identification of TLE and FLE.