To investigate the influence of seasonal dynamics on the endophytic fungal community of Camphora bodinieri with citral chemotype, we employed standardized sampling and high-throughput sequencing to analyze the diversity, composition, and structure of endophytic fungi across different seasons. A total of 1825 Amplicon Sequence Variants (ASVs) were obtained, belonging to 12 phyla, 43 classes, 104 orders, 239 families, 449 genera, and 663 species. Among them, 23 ASVs were shared across all four seasons, suggesting the presence of a core fungal community. The number of season-specific ASVs was highest in autumn (730), followed by summer (336), spring (325), and winter (202). The results showed that season significantly affected the Shannon (F3,9 = 5.927, p = 0.016) and Simpson (F3,9 = 4.892, p = 0.026) indices, with the diversity and species richness of endophytic fungi being highest in autumn and lowest in winter. Across different tissues, the similarity of endophytic fungal communities between leaves and stems was comparatively higher than that with roots. Furthermore, different fungal taxa exhibited differential distribution patterns along temperature–moisture gradients. This study explored the seasonal diversity of endophytic fungi in C. bodinieri with citral chemotype, providing a theoretical basis for understanding host–endophyte interactions.
AIM
Elderly patients admitted to the intensive care unit (ICU) after emergency surgery represent a uniquely high-risk population for postoperative delirium (POD). However, the key risk factors specific to this group have not been comprehensively integrated, and a corresponding clinical prediction tool is lacking. This study aimed to elucidate the clinical features, identify independent risk factors for POD, and develop and validate a prediction model tailored for elderly patients in the emergency surgical ICU.
METHODS
This retrospective study included 496 elderly patients (≥60 years) admitted post-emergency surgery. Delirium was assessed using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Patients were randomly divided in a 7:3 ratio into training (n = 347) and validation (n = 149) sets. Logistic regression identified independent predictors, which were used to construct a nomogram. Model performance was evaluated via receiver operating characteristic (ROC) curves, calibration, and decision curve analysis (DCA).
RESULTS
POD incidence was 33.1%, predominantly the hypoactive subtype (64.6%), with peak onset on postoperative day 2 (57.9%). Five independent risk factors were identified: higher Sequential Organ Failure Assessment (SOFA) score (Odds Ratio [OR] = 3.818), elevated Procalcitonin (PCT) (OR = 1.594), longer mechanical ventilation (OR = 1.283), intraoperative hypotension (OR = 2.666), and physical restraint use (OR = 3.003). A nomogram was developed using these variables, which demonstrated excellent discriminative performance, with area under the curves (AUCs) of 0.937 and 0.913, in the training and validation datasets, respectively. DCA confirmed the clinical utility of our proposed model.
CONCLUSIONS
This study identified five key and modifiable risk factors for POD in elderly emergency surgical ICU patients and successfully developed and validated a high-performance nomogram prediction tool. This model aids in the early identification of high-risk patients, providing a basis for implementing targeted bundled prevention strategies, which holds promise for improving clinical outcomes in this vulnerable population.
Xiaojiao Liu, F. Pan, Liqin Hu et al.· Annali italiani di chirurgia· 0 citations
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