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To explore the latent categories and influencing factors of dyadic decision self-efficacy among stroke patients and their caregivers.
A cross-sectional survey involving 305 patient-caregiver pairs was conducted using standardised questionnaires. Latent profile analysis was used to identify dyadic self-efficacy categories and multinomial logistic regression was employed to analyse influencing factors.
The dyadic decision self-efficacy of stroke patients and their caregivers was classified into three categories: low common decision self-efficacy group (35.6%), patients' high decision self-efficacy and caregivers' moderate decision self-efficacy group (38.6%), and high common decision self-efficacy group (25.8%). Influencing factors included patients' education level, income and health literacy, as well as caregivers' education, caregiving duration and social support.
The levels of dyadic decision self-efficacy among stroke patients and their caregivers are heterogeneous. Clinicians can develop targeted interventions involving both patients and caregivers, based on the population's characteristics and influencing factors, to improve their dyadic decision self-efficacy.
This study was conducted and reported in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines.
This study was to create an interpretable machine learning model to predict the risk of mortality within 90 days for ICU patients suffering from pressure ulcers.
We retrospectively analysed 1774 ICU pressure ulcer patients from the Medical Information Mart for Intensive Care (MIMIC)-IV database.
We used the LASSO regression and the Boruta algorithm for feature selection. The dataset was split into training and test sets at a 7:3 ratio for constructing machine learning models. We employed logistic regression and nine other machine learning algorithms to build the prediction model. Restricted cubic spline (RCS) was used to analyse the linear relationship between the Braden score and the outcome, whereas the SHAP (Shapley additive explanations) method was applied to visualise the model's characteristics.
This study compared the predictive ability of the Braden Scale with other scoring systems (SOFA, APSIII, Charlson, SAPSII). The results showed that the Braden Scale model had the highest performance, and SHAP analysis indicated that the Braden Scale is an important influencing factor for the risk of 90-day mortality in the ICU. The restricted cubic spline curve demonstrated a significant negative correlation between the Braden Scale and mortality. Subgroup analysis showed no significant interaction effects among subgroups except for age.
The machine learning-enhanced Braden Scale has been developed to forecast the 90-day mortality risk for ICU patients suffering from pressure ulcers, and its efficacy as a clinically reliable tool has been substantiated.
Patients or public members were not directly involved in this study.
To compare contextual factors influencing discharge practices in three intensive care units (ICUs).
A prospective observational study.
Data were collected using a discharge process report form (DPRF) between May and September 2023. Descriptive statistics were performed to analyse demographic and clinical data. One-way analysis of variance (ANOVA) was used to test the time interval differences among the three sites.
Overall, 69 patients' discharge processes were observed. Among them, 41 (59%) experienced discharge delay, and 1 in 5 patients experienced after-hours discharge. There were statistically significant differences in mean hours in various time intervals during the discharge processes among the three sites. Patients in Hospital C waited the longest time (mean = 31.9 h) for the ward bed to be ready after the bed was requested and for being eventually discharged after ICU nurses to get them ready for discharge (mean = 26.7 h) compared to Hospital A and Hospital B.
We found that discharge delay and after-hours discharge were common and there were significant differences in mean hours of various time intervals during the discharge processes occurred among the three sites. The influence of contextual factors in different hospitals/ICU needs to be considered to improve the ICU discharge process.
Researchers and clinicians should consider targeted context-specific interventions and strategies to optimise patient discharge process from ICUs.
The study findings will inform the development of tailored interventions to reduce the discharge delay and after-hours discharge and, in turn, improve the quality and safety of patient care and health service efficiency.
The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.
Patients' discharge processes were observed, and consumer representatives were involved in the study design.
To identify the contaminated areas of the hand collection and analyse the distribution characteristics of bacteria in the hand after swab collection.
This study used a cross-sectional design.
A cross-sectional study sampling 50 pairs of hands (sampling hand and auxiliary hand) of healthcare workers was performed. Ten samples were collected from each participant. The optimal hand hygiene rates and bacterial colony counts of the whole hand and different hand sections without hand hygiene were identified as the primary outcomes.
The optimal hand hygiene rates of the sampling hand and auxiliary hand were 88.8% (222/250) and 91.6% (229/250), respectively. The lowest optimal hand hygiene rates for the sampling hand and the auxiliary hand were both on the dorsal side of the finger and the dorsum of the hand (86.0%, 86.0% vs. 90.0%, 86.0%); the optimal hand hygiene rates for both sites of the sampling hand were 86.0% (43/50), and the optimal hand hygiene rates for the auxiliary hand were 90.0% (45/50) and 86.0% (43/50). The bacteria colony counts did not differ between the sampling hands and auxiliary hand.
The dorsal side of the finger and dorsum of the hand were the most likely to be contaminated during oropharyngeal swab collection. Therefore, it is essential to pay extra attention to hand hygiene care of these two sites during the collection process to minimize the risk of cross-contamination.
The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines were adopted in this study.
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