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To systematically identify and appraise existing risk prediction models for EN aspiration in adult inpatients.
A systematic search was conducted across PubMed, Web of Science Core Collection, Embase, Cochrane Library, CINAHL, China National Knowledge Infrastructure (CNKI), Wanfang Database, China Biomedical Literature Database (CBM) and VIP Database from inception to 1 March 2025.
Systematic review of observational studies.
Two researchers independently performed literature screening and data extraction using the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS). The Prediction Model Risk of Bias Assessment Tool (PROBAST) was employed to evaluate both the risk of bias and the clinical applicability of the included models.
A total of 17 articles, encompassing 29 prediction models, were included. The incidence of aspiration was 9.45%–57.00%. Meta-analysis of high-frequency predictors identified the following significant predictors of aspiration: history of aspiration, depth of endotracheal intubation, impaired consciousness, sedation use, nutritional risk, mechanical ventilation and gastric residual volume (GRV). The area under the curve (AUC) was 0.771–0.992. Internal validation was performed in 12 studies, while both internal and external validation were conducted in 5 studies. All studies demonstrated a high risk of bias, primarily attributed to retrospective design, geographic bias (all from different parts of China), inadequate data analysis, insufficient validation strategies and lack of transparency in the research process.
Current risk prediction models for enteral nutrition-associated aspiration show moderate to high discriminative accuracy but suffer from critical methodological limitations, including retrospective design, geographic bias (all models derived from Chinese cohorts, limiting global generalisability) and inconsistent outcome definitions.
Recognising the high bias of existing models, prospective multicentre data and standardised diagnostics are needed to develop more accurate and clinically applicable predictive models for enteral nutrition malabsorption.
Not applicable.
PROSPERO: CRD420251016435
It is extremely significant to explore the relationship between ruminative thinking and breathlessness catastrophizing among elderly COPD patients. However, the impact of self-efficacy on this relationship is still unclear. This study attempted to explore the mediating role of self-efficacy between ruminative thinking and breathlessness catastrophizing.
A cross-sectional study was reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.
This study was conducted between 10 November 2024 and 25 January 2025, with 225 patients. Data were collected using the valid and reliable instruments, including the Ruminative Response Scale (RRS), the COPD Self-Efficacy Scale (CSES) and the Breathlessness Catastrophizing Scale (BCS). Additionally, IBM SPSS v28.0 software was used to explore the mediating effect.
The scores for BCS of most patients were at moderate and high levels. Scores for the RRS and CSES were significantly correlated with the BCS. The analysis of the mediating effect demonstrated that ruminative thinking has a direct predictive effect on breathlessness catastrophizing. Additionally, ruminative thinking can also predict breathlessness catastrophizing indirectly through the mediation of self-efficacy. The direct effect accounted for 64.4% of the total effect.
This research revealed that self-efficacy played a partial mediating role in the relationship between ruminative thinking and breathlessness catastrophizing. Specifically, patients who were trapped in ruminative thinking were more likely to experience heightened breathlessness catastrophizing, but this relationship was mitigated by their level of self-efficacy.
This finding underscores the significant psychological burden that accompanies the physical symptoms of COPD in this demographic. It is imperative that nurses adopt a holistic approach in the management of elderly COPD patients.
Voluntary patients with elderly COPD hospitalised in the pneumology department were included in the study.
To investigate the risk factors associated with frailty in older patients with ischaemic stroke, develop a nomogram and apply it clinically.
A cross-sectional study.
Altogether, 567 patients who experienced ischaemic strokes between March and December 2023 were temporally divided into training (n = 452) and validation (n = 115) sets and dichotomised into frail and non-frail groups using the Tilburg Frailty Indicator scale. In the training set, feature selection was performed using least absolute shrinkage and selection operator regression and random forest recursive feature elimination, followed by nomogram construction using binary logistic regression. Internal validation was performed through bootstrap re-sampling and the validation set was used to assess model generalisability. The receiver operating characteristic curve, Hosmer–Lemeshow test, Brier score, calibration curve, decision curve analysis and clinical impact curve were used to evaluate nomogram performance.
The prevalence of frailty was 58.6%. Marital status, smoking, history of falls (in the preceding year), physical exercise, polypharmacy, albumin levels, activities of daily living, dysphagia and cognitive impairment were predictors in the nomogram. Receiver operating characteristic curve analysis indicated outstanding discrimination of the nomogram. The Hosmer–Lemeshow test, calibration curve and Brier score results confirmed good model consistency and predictive accuracy. The clinical decision and impact curve demonstrated notable clinical utility. This free, dynamic nomogram, created for interactive use and promotion, is available at: https://dongdongshen.shinyapps.io/DynNomapp/.
This nomogram may serve as an effective tool for assessing frailty risk in older patients with ischaemic stroke.
The nomogram in this study may assist healthcare professionals in identifying high-risk patients with frailty and understanding related factors, thereby providing more personalised risk management.
TRIPOD checklist.
No patient or public contribution.
FreshRSS 