Edgar Benitez

Purpose: Late-onset intrauterine growth restriction (IUGR) is difficult to detect and is associated with adverse perinatal outcomes. This systematic review and meta-analysis evaluated the performance of artificial intelligence (AI) models, including machine learning (ML) and deep learning, for predicting late-onset IUGR in singleton pregnancies.Methods: PubMed, Scopus, and Web of Science were searched for studies published during the past decade that used AI to predict IUGR. Nineteen studies including 13,379 pregnancies were analyzed. Sensitivity, specificity, likelihood ratios, and diagnostic odds ratios were pooled using DerSimonian-Laird random-effects models; the area under the summary receiver operating characteristic curve (AUC) was estimated in STATA.Results: In the primary analysis (one model per study, k=17), pooled sensitivity was 0.83 (95% confidence interval [CI], 0.74 to 0.89), specificity was 0.89 (95% CI, 0.85 to 0.91), the positive and negative likelihood ratios were 6.6 (95% CI, 5.3 to 8.1) and 0.22 (95% CI, 0.16 to 0.30), and the AUC was 0.93 (95% CI, 0.91 to 0.95). Estimates were unchanged when all model entries were included (k=51). No threshold effect or funnel-plot asymmetry was detected. Subgroup estimates for support vector machines, random forests, and logistic regression were similar but reflected indirect comparisons.Conclusion: AI/ML models showed high pooled discriminative accuracy for late-onset IUGR. However, the evidence derives mainly from retrospective, single-center case-control studies without external validation; calibration was reported in six of 19 studies and decision-curve analysis in none. These estimates are an optimistic upper bound, not evidence of superiority over current ultrasound practice.

1. Xenograft studies are widely regarded as an essential component of drug discovery and development programs in oncology. These experiments involved implanting approximately 106 tumor cells into t...

Aim(s): To translate, culturally adapt and validate the first Spanish version of the Person‐centred Practice Inventory‐Care (PCPI‐C) instrument. Design: Cross‐cultural adaptation and psychometric validation. Methods: Two‐phase research design: (1) the PCPI‐C's translation and cultural adaptation from English to Spanish following the ‘Translation and Cultural Adaptation of Patient‐Reported Outcomes Measures‐Principles Guide of Good Practice’ tool; and (2) a cross‐sectional quantitative survey to assess the Spanish version's psychometric properties. Results: A sample of 200 patients participated to obtain the PCPI‐C's Spanish version. No significant issues arose during the translation process or the consulting sessions. No item exhibited an inadequate value following adjustment via the weighted kappa index (−scale‐level content validity average of 0.95 for clarity and 0.97 for relevance). Psychometric evaluation revealed acceptable internal consistency (Cronbach's alpha from 0.67 to 0.84) and strong construct validity. Exploratory and confirmatory factor analyses supported a five‐dimensional structure consistent with the domain Person‐Centred Processes. Fit indices improved after model refinements, achieving CFI = 0.92, SRMR = 0.05 and RMSEA = 0.07. This study's observed psychometric properties confirm that the PCPI‐C's Spanish version retains the original instrument's theoretical integrity, while showing strong reliability and validity in the new context. Conclusion: The PCPI‐C's Spanish translation was psychometrically valid when tested with Spanish patients, thus providing a culturally appropriate, psychometrically sound tool to evaluate Spanish‐speaking patients' perception of person‐centred care. Impact: This study provides a validated instrument that allows for the assessment of person‐centred practice in Spanish‐speaking clinical environments. It enables healthcare professionals to measure patients' perceptions, track the implementation of person‐centred principles and supports international comparative studies, contributing to the development of more ethical and responsive models of care. Patient or Public Contribution: Patients participated in cognitive consultations and completed the survey for psychometric testing, ensuring that the translated items were understandable, culturally appropriate and reflective of their experiences of person‐centred care.

Background: Person-centredness, a global movement in healthcare, is consistent with international developments in healthcare policy. It is important to have instruments to measure person-centred care. The Person-Centred Practice Inventory-Staff (PCPI-S) is an internationally recognized instrument that aims to measure how healthcare staff experience person-centred practice. Aim: To perform the cultural adaptation and psychometric testing of a Spanish version of the PCPI-S (PCPI-S (Sp)). Method: A two-stage research design was implemented as follows: (1) the translation and cultural adaptation of the PCPI-S from English to Spanish using the “Translation and Cultural Adaptation of Patient Reported Outcomes Measures-Principles of Good Practice”; (2) a quantitative cross-sectional survey for the psychometric evaluation of the PCPI-S. Test–retest reliability was evaluated using the Kendall tau concordance coefficient, internal reliability was assessed through the ordinal theta (OT) coefficient, and confirmatory factor analysis was performed to examine the theoretical measurement model. Results: A Spanish version of the PCPI-S was obtained. There were no significant difficulties in the translation process or the consulting sessions. A sample of 287 healthcare professionals participated in the study at least once. All the items showed at least a fair level of test–retest reliability. The OT scores were adequate (>0.69). The model showed good to adequate levels of fit: CFI = 0.89, SRMR = 0.068; RMSEA = 0.060 with CI90% (0.056–0.063). Conclusions: The Spanish translation of the PCPI-S was psychometrically valid when tested with Spanish healthcare professionals. This instrument will help identify professionals’ perceptions of person-centred practice, track the evolution of this practice over time, and assess interventions aimed at improving person-centred practice.

In this study, the combined use of structural equation modeling (SEM) and Bayesian network modeling (BNM) in causal inference analysis is revisited. The perspective highlights the debate between proponents of using BNM as either an exploratory phase or even as the sole phase in the definition of structural models, and those advocating for SEM as the superior alternative for exploratory analysis. The individual strengths and limitations of SEM and BNM are recognized, but this exploration evaluates the contention between utilizing SEM's robust structural inference capabilities and the dynamic probabilistic modeling offered by BNM. A case study of the work of, \citet{balaguer_2022} in a structural model for personal positive youth development (\textit{PYD}) as a function of positive parenting (\textit{PP}) and perception of the climate and functioning of the school (\textit{CFS}) is presented. The paper at last presents a clear stance on the analytical primacy of SEM in exploratory causal analysis, while acknowledging the potential of BNM in subsequent phases.

Background: Despite a steady increase in palliative care (PC)-oriented research, authentic engagement of stakeholders with findings needs to be more used. Objective: This study aimed to explore how ATLANTES Observatory can effectively promote the global development of PC by engaging with stakeholders and addressing their specific needs and priorities. Design: An international e-survey among Observatory collaborators explored key audiences, best ways to reach them, and priority activities. Answers were evaluated according to respondents' roles (Academics, Policymakers, and clinicians) and toward impact on diverse key stakeholders. Correlation between respondents' roles with select products was studied. Results: One hundred fifty-five collaborators participated. The collaborators suggested addressing ATLANTES Global Observatory's activities to policymakers (5,6/7), professional associations (5,2/7), and health care practitioners (4,4/7). Preferred activity to reach all stakeholders is the use of websites and social networks, while particularly for policymakers, academics, and general practitioners, the conduction of atlases and articles stand out. Conclusions: Our study emphasizes prioritizing policymakers and all health care practitioners as key stakeholders in promoting PC and driving global development and integration into health care systems. By leveraging innovative web tools and social networks for dissemination, our aim is to extend the reach of our efforts beyond the PC community.

The state of the art related to parameter correlation in two‐parameter models has been reviewed in this paper. The apparent contradictions between the different authors regarding the ability of D‐optimality to simultaneously reduce the correlation and the area of the confidence ellipse in two‐parameter models were analyzed. Two main approaches were found: (1) those who consider that the optimality criteria simultaneously control the precision and correlation of the parameter estimators and (2) those that consider a combination of criteria to achieve the same objective. An analytical criterion combining in its structure both the optimality of the precision of the estimators of the parameters and the reduction of the correlation between their estimators is provided. The criterion was tested both in a simple linear regression model, considering all possible design spaces, and in a nonlinear model with strong correlation of the estimators of the parameters (Michaelis–Menten) to show its performance. This criterion showed a superior behavior to all the strategies and criteria to control at the same time the precision and the correlation.

The main objective of this study was to analyze the relationship between structured, unstructured, and family leisure activities on the frequency of adolescent alcohol intake across three different countries (Spain, Peru, and The Netherlands). The self-control of adolescents was also investigated as a moderator in the relationship between leisure activities and alcohol consumption. Methodology: This research involved 4608 adolescents aged between 12 and 17 from three countries (Spain, Peru, and The Netherlands). In Spain and Peru, data was collected through a self-report questionnaire which was part of the Your Life project. In The Netherlands, a self-questionnaire was used, collected by the University of Utrecht. A multiple logistic regression was performed for each country. Results: The results showed that participation in unstructured leisure activities increased the likelihood of drinking more frequently and more heavily in all three countries. Structured leisure activities, in general, did not have a significant predictive effect on alcohol consumption in any of the countries. Family leisure activities reduced the risk of engaging in yearly alcohol use and yearly binge drinking among adolescents, especially in The Netherlands and Spain. The protective effect of family leisure and unstructured leisure risk on yearly alcohol use applied especially to Dutch adolescents with a low level of self-control. Discussion: The article emphasizes the need for parents to engage in leisure activities with their child; participation in unstructured activities is not to be encouraged.