Irene Llagostera-Reverter

Objectives: Functional capacity is frequently used to estimate the care needs of hospitalised patients, although it does not necessarily capture all components of nursing care intensity. This study aimed to analyse the association between functional capacity and the intensity of the basic and technical care delivered and to examine whether these associations varied during hospitalisation among adults admitted to general inpatient units. A secondary objective was to examine the gradient in basic and technical care needs across functional capacity categories. Methods: A prospective longitudinal observational study was conducted in seven adult inpatient units. The baseline Barthel Index assessment was performed within the first 24 h of hospitalisation, with daily assessments thereafter. CUDYR-D and CUDYR-R were first recorded on the second day and then daily, summarising the care delivered during the preceding 24 h. Analyses included cross-sectional correlations, correlations adjusted for age and comorbidity, differences between functional categories, and longitudinal associations assessed using linear mixed-effects models. Results: The analytical sample included 188 patients and 789 daily assessments. The Barthel Index was more strongly associated with CUDYR-D (ρ = −0.823; 95% CI: −0.868 to −0.762) than with CUDYR-R (ρ = −0.472; 95% CI: −0.580 to −0.346); this difference persisted after adjustment for age and comorbidity (Δ|ρ| = 0.360; 95% CI: 0.248 to 0.484). The gradient across functional categories was higher for CUDYR-D than for CUDYR-R. In the longitudinal models, the standardised coefficients for the Barthel Index were −0.838 for CUDYR-D and −0.508 for CUDYR-R. Interactions with time were small and not statistically significant. Conclusions: Functional capacity was strongly associated with the intensity of basic care delivered but was only moderately associated with technical care and clinical surveillance. The Barthel Index should not be used alone as a proxy for overall care intensity or nursing workload.

Background/Objectives: The aim of this study is to analyse the association between sociodemographic and obstetric characteristics and perceived or suspected obstetric violence in Spain, informed by an intersectional framework. Methods: A cross-sectional study was conducted using a non-probabilistic online survey of women who gave birth in Spain between March 2020 and April 2021. “Yes” and “do not know” responses were combined as perceived or suspected obstetric violence. Descriptive and bivariate analyses (chi-squared and Fisher’s exact tests) were followed by a multivariable binary logistic regression including, a priori, age, occupation, educational level, social class, ethnicity, type of birth, type of healthcare and autonomous community. Results: Of 6060 women, 33.5% (n = 2030) reported or suspected obstetric violence. In the adjusted model (n = 5978; Nagelkerke R² = 0.071), the outcome was associated with all variables except social class. Odds were higher after urgent caesarean section (aOR = 2.16) and instrumental birth (aOR = 2.76) than after vaginal birth, and lower in private than in public healthcare (aOR = 0.67). Estimates for ethnic minorities were very imprecise because of the small size of these groups. Conclusions: Perceived or suspected obstetric violence was associated with several sociodemographic, obstetric and healthcare characteristics, most strongly with type of birth, although the explanatory capacity of the model was low. These findings support reviewing interventionist obstetric practices and using sampling strategies that include minority groups.

The aim of the present study is to analyse the relationship between sociodemographic variables and the perception of obstetric violence in Spain. A cross-sectional study was carried out through an online questionnaire. A descriptive analysis of all variables was performed followed by a bivariate analysis using the Chi-Squared test. Finally, all statisti-cally significant variables were included in a multivariate binary logistic regression mod-el. Data were processed and graphs created using Jamovi 2.3.28 software. Statistical sig-nificance was set at p< 0.05. A total of 6060 women were included in the study. Some 33.5% (n=1578) referred to having experienced obstetric violence or not being aware of it. Variables that showed a statistically significant relationship with obstetric violence were (p< 0.05): aged between 18 and 25 years, being a student, being of Romani ethnicity, being treated in public health, and labour being completed with urgent caesarean section or in-strumental delivery. The binary logistic regression model proved significant (X2=314; p< 0.001), with high sensitivity (0.970), an AUC=0.647 and a Nagelkerke pseudo-R2 deter-mination of 0.079. Young women face higher obstetric violence, influenced by occupation and ethnicity, reflecting socioeconomic and cultural care impacts. Improving obstetric practices is crucial for women's autonomy and respectful childbirth care.

Aim: To develop a three-item short form of the EAT-10 by identifying the smallest subset of items that preserves the screening performance of the full questionnaire in hospitalized older adults. Design: Multicentre cross-sectional observational study. Methods: The study was conducted in nine public hospitals in Spain within the NUTRIFAG project. Hospitalized patients aged ≥65 years with a length of stay ≥48 h were included. Patients receiving enteral or parenteral nutrition at admission, those in terminal condition, or with a primary diagnosis of cancer were excluded. Suspected dysphagia was assessed using the Eating Assessment Tool (EAT-10), with a score ≥3 considered positive. Multivariate logistic regression models with forward item selection were used to identify the most informative symptoms indicators. The sample was randomly divided into a training subset (60%) and an internal assessment subset (40%). Model performance was evaluated using Nagelkerke’s pseudo R ² , the Hosmer–Lemeshow test, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). Results: The sample included 2,519 participants. Three symptom indicators emerged as the most informative for identifying patients with suspected dysphagia: requiring extra effort to swallow liquids, requiring extra effort to swallow solids, and coughing while eating. Together, these indicators showed high agreement with the classification obtained using the full EAT-10 in the training phase ( R ² = 0.861; sensitivity = 0.863; specificity = 0.979; AUC = 0.982), which similar classification performance in the internal assessment subset (sensitivity = 0.881; specificity = 0.984). Conclusion: The proposed three-item subset represents a shortened version of the EAT-10 that preserved much of the screening performance of the full questionnaire in hospitalized older adults. Although it may facilitate dysphagia screening by reproducing the classification obtained with the full EAT-10 in routine nursing assessment, independent external validation against clinical reference standards is required before its diagnostic use can be recommended.

Background: Hospital-at-home (HaH) programs provide an effective and safe alternative to conventional hospitalization, particularly for patients with multimorbidity or complex chronic conditions. In this setting, nursing assessment plays a key role, given the intermittent nature of care and the limited presence of other professionals. However, nursing documentation in HaH remains challenging because of organizational heterogeneity, fragmented records, and the coexistence of multiple assessment tools that create redundancy and compromise information quality. The overall objective of this study is to develop and validate a meta-instrument (VALENF-HAD) that integrates the assessment of functional capacity, pressure injury risk, fall risk, frailty, nutritional status, and sleep quality in patients admitted to hospital-at-home units on the basis of the analysis of other validated measurement instruments used in nursing assessment. Methods: A multicentre, cross-sectional study will be conducted in four public hospitals in Castellón Province, Spain. Participants will include adults (≥18 years) admitted to HaH units. Sociodemographic and care-related variables, along with risk-related variables, will be collected using the following instruments: functional capacity (Barthel Index and Lawton & Brody Scale), risk of pressure injuries (Braden Scale), risk of falls (STRATIFY Scale), frailty (FRAIL questionnaire), nutritional status (Nutritional Screening Initiative tool), and sleep quality (Athens Insomnia Scale). The development process of the meta-instrument consists of four phases: (I) analysis of instruments, constructs, and items; (II) meta-instrument design; (III) initial validation; and (IV) determination of clinimetric properties. Discussion: This study is expected to produce a parsimonious and specific meta-instrument for hospital-at-home settings that is capable of integrating functional, nutritional, sleep, fall risk, frailty, and pressure injury assessments. Its implementation will enhance the quality and standardization of nursing documentation, reduce administrative workload, facilitate early risk detection, and free up time for direct patient care. Ultimately, this study will contribute to advancing evidence-based nursing practices in home hospitalization.

Background: Patient safety is a global priority, as adverse events represent the 14th leading cause of morbidity and mortality worldwide. Among the most common complications in hospitalized adults are functional decline, pressure injuries, and falls, all of which increase hospital stays, healthcare costs, and mortality. Although these risks are typically assessed independently, their interaction has been scarcely explored, and the identification of integrated patient risk profiles could better guide nursing care. Objective: To establish profiles of adult inpatients based simultaneously on their level of functional capacity, risk of pressure injuries, and risk of falls. Design: Cross‐sectional observational study. Participants: A total of 2.666 patients were admitted to adult inpatient units in a Spanish hospital. Methods: Data from the Barthel, Braden, and Downton scales collected within 24 h of admission were analyzed. A hierarchical cluster analysis followed by the k‐means method was used to classify patients. Relationship between profiles and clinical variables were explored through multiple correspondence analysis, and predictors for each profile were identified using multinomial logistic regression. Results: Three patient profiles were identified: profile 1 (low risk), minor dependency, low risk of pressure injuries and falls (68.5%); profile 2 (moderate risk), moderate dependency and intermediate risk (15.4%); and profile 3 (high risk), severe dependency with high risk of pressure injuries and falls (16.1%). Older age, female sex, and higher comorbidity were significantly associated with higher‐risk profiles ( p < 0.001). Conclusions: Hospitalized adults can be reliably classified into risk profiles based on functional capacity and the risk of pressure injuries and falls. Implications: The identification of combined risk profiles may potentially guide nursing strategies to enhance patient safety, support individualized care planning, and contribute to optimizing resource distribution in hospital settings. Impact: Loss of functional capacity, pressure injuries, and falls are key nursing‐sensitive indicators of care quality. Profile‐based stratification offers a new framework for personalized, data‐driven, and safety‐oriented nursing care. Clinical Relevance: The identification of integrated risk profiles based on functional capacity, pressure injury risk, and fall risk may support more comprehensive nursing assessment in hospitalized adults. These profiles may help inform care prioritization, facilitate early identification of vulnerable patients, and contribute to more efficient allocation of nursing resources. Incorporating multidimensional risk stratification into clinical practice may enhance coordinated and patient‐centered care planning.

Background/Objectives: Pressure injuries and falls are frequent hospital adverse events. Identifying high-risk periods may help guide preventive strategies. In this exploratory study, we aimed to estimate the time from hospital admission to the occurrence of pressure injuries and/or falls and analyze its relationship with the nursing assessment at admission. Methods: A longitudinal observational study was conducted with a systematic sample of 314 adult patients admitted between January and May 2024. Nursing assessment at admission was performed using the VALENF Instrument, which integrates functional capacity, pressure injury risk, and fall risk. Survival analysis was performed to describe the temporal distribution of adverse events and compare their occurrence across nursing assessment variables using the log-rank test. Poisson Generalized Linear Models were applied to explore associated factors. Results: Nineteen adverse events were recorded (15 pressure injuries and 4 falls). Twelve of the 19 total events (63%) occurred within the first five days of admission. Patients with lower functional capacity (log-rank p < 0.001) and high-pressure injury risk (log-rank p < 0.001) according to the VALENF Instrument, showed an earlier occurrence of new pressure injuries in the Kaplan–Meier analysis. Similarly, fall risk scores (log-rank p = 0.037) obtained with the same instrument were associated with falls. Patients classified as high risk for pressure injuries showed an approximately nine-fold higher incidence rate of developing new injuries (Wald χ², p < 0.001), while urgent admission further increased this risk more than six-fold (Wald χ², p = 0.015). Conclusions: In this exploratory study with a limited number of events, most adverse events occurred early during hospitalization. The findings suggest that early nursing assessment using the VALENF Instrument may help stratify patients for closer monitoring early in admission, pending confirmation in larger studies.

BackgroundFailure to Rescue (FTR) is defined as the occurrence of clinical and/or functional deterioration that could potentially have been prevented through early detection and appropriate intervention. Early identification is essential for patient safety, as it is closely associated with quality of care and hospital mortality. Nevertheless, organisational and methodological limitations remain, hindering timely recognition and effective response. Overcoming these challenges requires optimising predictive algorithms and integrating clinical process management with the supporting information systems.ObjectiveTo design and validate predictive models based on machine learning and process mining to anticipate Failure to Rescue events in adult inpatient units.MethodsA retrospective observational study will be conducted based on electronic health records (EHRs) from Hospital Universitario de La Plana (La Plana University Hospital). The cohort will include all patients aged 18 years and older who were admitted between March 2023 and February 2024. Sociodemographic variables, care process-related variables, nursing assessments, laboratory parameters, and situations susceptible to FTR will be collected.