Conectar
To develop and validate decision trees using conditional probabilities to identify the predictors of mortality and morbidity deterioration in trauma patients.
A quasi-experimental longitudinal study conducted at a Level 1 Trauma Center in São Paulo, Brazil.
The study analysed 201 patient records using standardised nursing documentation (NANDA International and Nursing Outcomes Classification). Decision trees were constructed using the chi-squared automatic interaction detection (CHAID) algorithm and validated through K-fold cross-validation to ensure model reliability.
Decision trees identified key predictors of survival and mobility deterioration. Patients who did not require (NOC 0414) Cardiopulmonary Status but required (NOC 0210) Transfer Performance had a 97.4% survival rate. Conversely, those requiring (NOC 0414) Cardiopulmonary Status had a 25% risk of worsening mobility, compared to 9% for those who did not. K-fold cross-validation confirmed the model's predictive accuracy, reinforcing the robustness of the decision tree approach (Value).
Decision trees demonstrated strong predictive capabilities for mobility outcomes and mortality risk, offering a structured, data-driven framework for clinical decision-making. These findings underscore the importance of early mobilisation, tailored rehabilitation interventions and assistive devices in improving patient recovery. This study is among the first to apply decision trees in this context, highlighting its novelty and potential to enhance trauma critical care practices.
This study highlights the potential of decision trees, a supervised machine learning method, in nursing practice by providing clear, evidence-based guidance for clinical decision-making. By enabling early identification of high-risk patients, decision trees facilitate timely interventions, reduce complications and support personalised rehabilitation strategies that enhance patient safety and recovery.
This research addresses the challenge of improving outcomes for critically ill and trauma patients with impaired mobility by identifying effective strategies for early mobilisation and rehabilitation. The integration of artificial intelligence-driven decision trees strengthens evidence-based nursing practice, enhances patient education and informs scalable interventions that reduce trauma-related complications. These findings have implications for healthcare providers, rehabilitation specialists and policymakers seeking to optimise trauma care and improve long-term patient outcomes.
Patients provided authorisation for the collection of their clinical data from medical records during hospitalisation.
(1) To analyse individual and institutional-level factors associated with urinary incontinence in older adults living in nursing homes; (2) to estimate the prevalence of urinary, faecal and double incontinence in nursing home residents.
Cross-sectional study.
Residents aged 65+ living in 22 nursing homes in Catalonia (Spain) were included. Descriptive, bivariate, and multilevel analyses were performed.
The final sample comprised 452 residents (75.9% female, mean age of 87.0 years). The prevalence of urinary, faecal and double incontinence was 77.5%, 46.1% and 45.7%, respectively. Urinary incontinence was statistically significantly associated with neurological conditions, moderate cognitive impairment, moderate dementia, severe cognitive impairment, very severe cognitive impairment and age.
Approximately three out of four nursing home residents suffered from urinary incontinence and almost half of the sample from faecal or double incontinence. Individual-level factors (cognition, neurological conditions and age) played a more important role than institutional-level factors for urinary incontinence.
The findings of this study highlight the importance of individual-level interventions to prevent and manage urinary incontinence in nursing homes.
In Catalonian nursing homes, individual factors such as cognitive impairment and neurological conditions were more strongly associated with urinary incontinence than institutional factors. This has implications for improving care provided to older adults, particularly those with dementia and neurological conditions.
STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines.
Nursing home residents were not involved in this study.
To understand the social representations of bedside milk expression (BME) among mothers of preterm newborns in neonatal intensive care units (NICUs).
Qualitative descriptive study.
The study was conducted from July to August 2024 in two NICUs of a referral maternity hospital in Fortaleza, Brazil. Nineteen mothers of hospitalised premature newborns participated. Semi-structured interviews were conducted and subjected to thematic content analysis.
Mothers perceived BME as a meaningful act of protection and bonding, though some were unfamiliar with the practice. Emotional ambivalence was common, shaped by prior breastfeeding experiences and the context of prematurity. Discomfort related to privacy and shared spaces was noted. Support from healthcare professionals was essential to promote understanding and adherence.
Social representations of BME are shaped by emotional, social and institutional experiences. Anchored in prior breastfeeding experiences and cultural meanings of maternal care, the practice is objectified through both gestures of affection and tangible barriers.
Healthcare professionals, particularly nurses, should receive training to support mothers in BME. Structural improvements, privacy and emotional support are essential for fostering maternal autonomy and confidence.
This study highlights the barriers to BME, emphasising the role of healthcare support and the need for better infrastructure, privacy and training to enhance maternal confidence and breastfeeding.
The study followed the Consolidated Criteria for Reporting Qualitative Research checklist.
None.
This paper highlights the pivotal role of healthcare professional support in overcoming barriers to BME and promoting breastfeeding practices.
Fresh breast milk is considered the gold standard for reducing complications and improving survival in preterm infants. BME is recommended as an effective strategy to ensure the availability of fresh breast milk. Mothers' social representations of this practice remain underexplored within the neonatal intensive care context.
Explores mothers' social representations of BME in NICUs, addressing a significant gap in qualitative research. Reveals how emotional, social and institutional factors shape mothers' perceptions, motivations and challenges related to BME. Highlights the need for targeted professional support, improved infrastructure and privacy to enhance maternal autonomy and adherence to milk expression practices.
Healthcare professionals, particularly nurses, should receive specialised training to provide technical guidance and emotional support, enhancing mothers' confidence and autonomy in BME. Improving infrastructure and ensuring privacy in NICUs are crucial to creating supportive environments that facilitate milk expression and strengthen maternal–infant bonding. Institutional policies should integrate maternal-centred strategies to support breastfeeding continuity and promote humanised neonatal care.
FreshRSS 