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To construct and validate a prediction model for enteral feeding intolerance in critically ill patients during the first 7 days of enteral feeding.
A retrospective cohort study.
We reviewed the medical records of two intensive care units from January 2015 to August 2023, to develop a prediction model by univariate analysis and logistic regression analysis. Model's performance was evaluated through discrimination, calibration and decision curve analysis.
This study involved a total of 471 patients, with an enteral feeding intolerance incidence rate of 35.7%. The prediction model comprised six variables, namely neurological disease, chronic gastrointestinal disease, Acute Physiological and Chronic Health Assessment II score, sedatives, acid suppressants and serum albumin. The model showed robust discrimination, calibration and clinical net benefit, indicating significant potential for practical application with readily available variables.
The model demonstrated strong predictive performance in assessing the risk of enteral feeding intolerance during the early stage of nutrition initiation.
Enhancing clinicians' capacity to reduce the incidence of enteral feeding intolerance and improve patient outcomes.
The prediction model shows a good capacity to discriminate critically ill patients at risk of enteral feeding intolerance, is helpful to provide personalised care.
TRIPOD + AI checklist.
No patient or public contribution.
Trial Registration: https://www.chictr.org.cn/ ChiCTR2400090757
The clinical significance of cancer-related stigma on patients' well-being has been widely established. Stigma can be perceived and internalised by cancer patients or implemented by the general population and healthcare workers. Various interventions have been carried out to reduce cancer-related stigma, but their effectiveness is not well-understood. This review aims to synthesise evidence on the effectiveness of interventions to reduce cancer-related stigma.
An integrative review.
This integrative review combined both qualitative and quantitative studies and followed five steps to identify problems, search for the literature, appraise the literature quality, analyse data, and present data. Mixed Methods Appraisal Tool (version 2018) was applied to evaluate the quality of the included studies.
Databases included Web of Science, MEDLINE, SpringerLink, Wiley Online Journals, Cochrane Library, ScienceDirect, OVID, and China National Knowledge Infrastructure (from the inception of each database to 30 April 2021).
Eighteen quantitative, six qualitative, and five mixed-methods studies were included in this review. Cultural factors should be considered when conducting interventions to reduce cancer-related stigma. For cancer patients, multi-component interventions have demonstrated a positive effect on their perceived stigma. For general population, interactive interventions show promise to reduce their implemented stigma towards cancer patients. For healthcare workers, there is a paucity of studies to reduce their implemented stigma. Existing studies reported inconclusive evidence, partially due to the lack of a robust study design with an adequate sample size.
Multi-component and interactive interventions show promise to relieve cancer-related stigma. More methodologically robust studies should be conducted in different cultures to elucidate the most appropriate interventions for different populations to reduce cancer-related stigma.
These findings will facilitate healthcare workers to design and implement interventions to reduce cancer-related stigma, thus improving the quality of life for cancer patients.
No patient and public contribution.
FreshRSS 