Loading...
4 results
Search Results
Now showing 1 - 4 of 4
- Tratamento pré-hospitalar da dor traumática aguda: um estudo observacionalPublication . Mota, Mauro; Santos, Margarida Reis; Santos, Eduardo; Henriques, Carla; Matos, Cristina Bico Rodrigues de; Cunha, MadalenaObjective: To describe and analyze the effectiveness of nurses’ interventions in pain reduction among patients with traumatic injury. Methods: Prospective cohort study conducted in the Immediate Life Support Ambulances in Portugal from March 1, 2019 to April 30, 2020. We have collected data on the kind of interventions implemented and the time elapsed during rescue procedures. To investigate the course of acute trauma pain, a 11-point Numeric Rating Scale was used. Changes in the level of pain registered throughout the three assessment moments were studied using linear mixed-effects models with random intercepts to account for the repeated measurements conducted on the same patient. These changes were assessed before and after the administration of the pain relief interventions. Results: 596 patients were included in this study. Most of them were male (65.9%) and had a mean age of 53.05±19.72 years. There was a reduction in the average pain intensity of 2.44 points (p
- Morbidity and mortality in preterm infants less than 29 weeks of gestational agePublication . Marques, B.R.; Dinis, A.C.; Rocha, G.; Flôr-de-Lima, F.; Matos, Ana; Henriques, C.; Guimarães, H.Background: Preterm birth is certainly a public health problem. Aside from being an important cause of mortality, prematurity increases the risk of serious lifetime disabilities. Objective: To assess the overall survival, causes of death and neonatal morbidities associated with prematurity of newborns less than 29 weeks of gestational age (GA). Methods: Retrospective study including all preterm infants less than 29 weeks of GA admitted to the level III Neonatal Intensive Care Unit (NICU) at Centro Hospital São João in Porto, Portugal, between January 1st, 2005 and December 31st, 2016. Newborns were grouped into three groups according to their GA: G23+0-24+6, G25+0-26+6, G27+0-28+6. Results: In this 12-year-period, 160 preterm neonates less than 29 weeks of GA admitted to this NICU met our inclusion criteria. Overall deaths were 60 (37.5%), variating between 25 (92.6%) in the G23+0-24+6, 23 (46%) in the G25+0-26+6 and 12 (14.5%) in the G27+0-28+6. The leading causes of death were intraventricular hemorrhage (IVH) and sepsis. Early neonatal mortality was 20.6%. Among survivors, 41% had bronchopulmonary dysplasia (BPD), 69% developed late sepsis, 56% retinopathy of prematurity (ROP), 44% IVH and 10% cystic periventricular leukomalacia (cPVL). Conclusions: Mortality rates in this preterm group were high in spite of all the technological and scientific advances. Pulmonary conditions (respiratory distress syndrome and BPD), sepsis and neurologic outcomes (ROP, IVH and cPVL) were still major causes of morbidity. In line with other series, the limit of viability in this cohort of preterm infants is 25 weeks of GA. Prenatal, perinatal and postnatal care still all have a long road ahead, especially when it comes to these “gray zone” newborns.
- Pattern Recognition in Older Adults’ Activities of Daily LivingPublication . Augusto, Gonçalo F.; P. Duarte, Rui; Cunha, Carlos; Matos, AnaMonitoring daily activities and behaviors is essential for improving quality of life in elderly care, where early detection of behavioral anomalies can lead to timely interventions and enhanced well-being. However, monitoring systems often struggle with scalability, high rates of false positives and negatives, and lack of interpretability in understanding anomalies within collected data. Addressing these limitations requires an adaptable, accurate solution to detect patterns and reliably identify outliers in elderly behavior data. This work aims to design a scalable monitoring system that identifies patterns and anomalies in elderly activity data while prioritizing interpretability to make well-informed decisions. The proposed system employs pattern recognition to detect and analyze outliers in behavior analysis, incorporating a service worker generated with Crontab Guru for automated data gathering and organization. Validation is conducted through statistical measures such as accumulated values, percentiles, and probability analyses to minimize false detections and ensure reliable performance. Experimental results indicate the system achieves high accuracy, with an occupancy probability across compartments and fewer outliers detected. The system demonstrates effective scalability and robust anomaly detection. By combining pattern recognition with a focus on interpretability, the proposed system provides actionable insights into elderly activity patterns and behaviors. This approach enhances the well-being of older adults, offering caregivers reliable information to support timely interventions and improve overall quality of life.
- Derivation and validation of the SLE Disease Activity Score (SLE-DAS): a new SLE continuous measure with high sensitivity for changes in disease activityPublication . Jesus, Diogo; Cristina Bico Rodrigues de Matos, Ana; Henriques, C.; Zen, Margherita; Larosa, Maddalena; Iaccarino, Luca; Da Silva, José António Pereira; Doria, Andrea; Inês, Luís SousaObjectives To derive and validate a new disease activity measure for systemic lupus erythematosus (SLE), the SLE Disease Activity Score (SLE-DAS), with improved sensitivity to change as compared with SLE Disease Activity Index (SLEDAI), while maintaining high specificity and easiness of use. Methods We studied 520 patients with SLE from two tertiary care centres (derivation and validation cohorts). At each visit, disease activity was scored using the Physician Global Assessment (PGA) and SLEDAI 2000 (SLEDAI-2K). To construct the SLE-DAS, we applied multivariate linear regression analysis in the derivation cohort, with PGA as dependent variable. The formula was validated in a different cohort through the study of: (1) correlations between SLE-DAS, PGA and SLEDAI-2K; (2) performance of SLEDAI-2K and SLE-DAS in identifying a clinically meaningful change in disease activity (ΔPGA≥0.3); and (3) accuracy of SLEDAI-2K and SLE-DAS time-adjusted means in predicting damage accrual. Results The final SLE-DAS instrument included 17 items. SLE-DAS was highly correlated with PGA (r=0.875, p<0.0005) and SLEDAI-2K (r=0.943, p<0.0005) in the validation cohort. The optimal discriminative ΔSLE-DAS cut-off to detect a clinically meaningful change was 1.72. In the validation cohort, SLE-DAS showed a higher sensitivity than SLEDAI-2K (change ≥4) to detect a clinically meaningful improvement (89.5% vs 47.4%, p=0.008) or worsening (95.5% vs 59.1%, p=0.008), while maintaining similar specificities. SLE-DAS performed better in predicting damage accrual than SLEDAI-2K. Conclusion SLE-DAS has a good construct validity and has better performance than SLEDAI-2K in identifying clinically significant changes in disease activity and in predicting damage accrual.