Repositorio Institucional
Sistema de Bibliotecas Universidad Finis Terrae
El Repositorio Institucional de la Universidad FinisTerrae, es gestionado por el Sistema de Bibliotecas y tiene por objetivo permitir el acceso libre a la producción académica e institucional de la Universidad, aumentando la visibilidad de sus contenidos y garantizando su conservación.
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School violence and convivencia escolar in Chilean public policy in the post-pandemic context
(Springer Nature, 2026) Carrasco-Aguilar, Claudia; Castro-Carrasco, Pablo J.; Rodríguez-Pastene Vicencio, Fabiana; Caamaño-Vega, Vladimir; Gubbins-Foxley, Verónica; Zelaya, Martina
The return to in-person schooling after the pandemic heightened public concern about school violence and convivencia escolar in Chile. This study examines how the Chilean Ministry of Education constructs these phenomena. Using critical discourse analysis, we analyzed 34 official documents published between 2022 and 2024. The analysis involved coding excerpts referring to violence, convivencia escolar, and mental health, examining recurring discursive strategies, and grouping the excerpts into interpretive repertoires according to shared semantic and pragmatic patterns: (a) From conflict to violence: an institutional reading; (b) School violence and convivencia as objects of institutional regulation and control; and (c) Convivencia escolar as formative learning. The findings are discussed in relation to tensions among punitive, regulatory, and formative approaches, as well as school management. Limitations include the exclusive use of Ministry documents and the inability to generalize the results.
National Parent Associations’ Subjective Theories of Post-Pandemic School Violence in Chile: A Qualitative Exploratory Study
(MPDI, 2026) Gubbins, Verónica; Flores, Paula; Carrasco-Aguilar, Claudia; Castro-Carrasco, Pablo J.; Caamaño-Vega, Vladimir; Rodríguez-Pastene Vicencio, Fabiana
The aim of this study was to reconstruct the subjective theories of national parent associations in Chile regarding school violence in the post-pandemic period. We performed a collective case study, employing a qualitative, interpretative, and exploratory approach. Information was produced through semi-structured interviews with leaders of four national associations. The information was examined using inductive thematic analysis. In general, parent association representatives largely described school violence as a loss of parental and pedagogical authority, weakening of the family–school bond, centralized school administration, and social vulnerability factors, intensified by the psychosocial impact of the COVID-19 pandemic lockdowns. The interviewees emphasized preventive and community-based approaches, including strengthening family involvement, incorporating school climate specialists, and implementing educational and recreational activities. Overall, the interviews show that parent association representatives tended to regard violence as a multisystemic phenomenon that, according to their accounts, requires joint efforts involving families, schools, the state, and communities rather than punitive or individualized approaches.
Activity and Outcomes of a Multidisciplinary Sepsis Unit: Fifty Thousand Consultations over Thirteen Years
(MDPI, 2026-07-30) Borges-Sa, Marcio
Resumen: Background. Sepsis is a leading, time-dependent cause of in-hospital death, and guidelines now prioritize organized care such as code-sepsis protocols. Yet little is known about the long-term activity, organization and outcomes of permanent, hospital-scale programs. We characterized the activity of a hospital-wide multidisciplinary sepsis unit (MSU) over thirteen years and evaluated mortality trends. Methods. Retrospective cohort study using the registry of a hospital-wide MSU (2011-2023). The analysis unit was the sepsis event. Activity, referral pathways, interventions, follow-up and mortality were analyzed; temporal trends used multivariable logistic regression and standardized mortality ratios (SMR). Results. The unit attended 10,874 patients across 15,723 events and 50,925 consultations (median age 67; 59.3% men), referred mainly through the sepsis code (45.0%) and, increasingly, proactive early-warning detection (15.2%). An antibiotic change was recommended in 57.2% of events, and 89.8% of all suggested changes were implemented. Follow-up was sustained (median 3 visits; 61.8%). In-hospital mortality was 7.6%, and 11.8% in protocol-confirmed sepsis. Crude mortality did not fall, but severity rose (organ dysfunctions 1.67 to 2.72; septic shock 8 to 13%; both p < 0.001) with stable age; after adjustment the calendar-year effect disappeared (adjusted OR 1.00/year p = 0.70) and the SMR stayed near 1.0, including pandemic years. Age, ICU admission (OR 2.65) and organ-dysfunction count (OR 1.37) independently predicted death. Conclusions. Over thirteen years, this hospital-wide MSU delivered large-scale, multi-channel, longitudinal care to an increasingly severe population while maintaining stable risk-adjusted mortality, supporting the long-term feasibility of a model integrating early detection, multidisciplinary decision-making, antimicrobial stewardship and follow-up.
The PRECISE framework: a structured approach to antibiogram interpretation for antimicrobial optimization at the bedside
(Sociedad Española de Quimioterapia, 2026-08-31) Pérez-Oliva, Claudio
Resumen: Antimicrobial resistance claimed an estimated 4.95 million lives in 2019. When clinicians prescribe empiric therapy that follows guidelines, mortality drops by roughly a third; when they de-escalate on the basis of culture results, it drops by more than half. Yet the document that should drive both decisions, the antibiogram, is often read superficially or misinterpreted, particularly by physicians without infectious-disease training. Existing stewardship frameworks address prescribing principles, timing, or ecological impact, but none walks the clinician step by step through an individual susceptibility report and out the other side with a treatment plan. PRECISE is a seven-step mnemonic designed for that purpose. Each letter corresponds to a clinical action: Pathogen assessment, Resistance phenotype interpretation, Evaluate MIC, Curtail spectrum, Individualize PK/PD, Switch route, and Endpoint optimization. Three clinical vignettes (including one in which the steps deliberately collide) illustrate how the framework operates in practice.
Prospective economic evaluation of a predictive artificial intelligence model for sepsis: Effects on hospital costs and return on investment
(PLOS, 2026-08-31) Giglio, Andres
Resumen: Early sepsis detection is essential for improving outcomes and reducing costs, but traditional rule-based systems have limited accuracy and real-world evidence for machine-learning alternatives remains scarce. In this context, BIAlert-Sepsis predicts sepsis risk within 24 hours using historical hospital data, and evaluating its implementation in a tertiary hospital setting provides an opportunity to quantify its clinical benefits and economic value. We conducted a retrospective quasi-experimental before–after study including all septic patients admitted from January 2011 to June 2024. The baseline period (Jan 2011 – Mar 2019) was compared with the AI implementation period (Apr 2019 – June 2024), excluding the COVID-19 interval. Outcomes were assessed using adjusted generalized linear models and interrupted time series regression. A hospital-perspective economic evaluation incorporated implementation and maintenance costs, and a 5-year model estimated net benefit and return on investment (ROI), supported by deterministic and probabilistic sensitivity analyses. A total of 8,039 patients were included (6,168 baseline period; 1,871 AI period). Demographic and clinical characteristics were comparable across periods. During the AI period, ICU admissions decreased from 34.4% to 30.4% (adjusted p = 0.001), accompanied by significant reductions of 0.35 ICU days and 0.59 ward days per patient. Mean admission costs declined from 26,517€ to 24,630€ (adjusted p = 0.005). After covariate adjustment, AI implementation was associated with a 26.1–31.1% reduction in mean admission costs across GLM models. Interrupted time series analysis identified a modest immediate cost level change after AI implementation and a larger sustained decline during the post-COVID period. The 5-year economic model projected a cumulative discounted net benefit of 3.55M€ and a 528% ROI. BIAlert-Sepsis was associated with favourable clinical outcomes and lower costs, with economic modelling suggesting early breakeven and positive financial returns