Coleção de Artigos Acadêmicos
URI permanente para esta coleçãohttps://repositorio.insper.edu.br/handle/11224/3227
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9 resultados
Resultados da Pesquisa
Artigo Científico Performance Measurement in a Brazilian Clinical Trials Unit(2021) Aquino, Thomaz Martins de; Bonizio, Roni Cleber; Padua, Silvia Ines Dallavalle de; Coelho, Eduardo Barbosa; Faustino, Gabriela GimenezBackground: There is growing interest on costs of clinical trials; critical topic for business decision making; therefore, the aim of this work is to identify how a successful Brazilian case measures its economic performance even with restriction regarding its accounting data. Methods: Single case qualitative method. Interviews with four people of different hierarchical levels and the analysis of the 2005 balance sheet, payrolls and payment slips were carried out. Results: Besides indicating how the clinical research unit of the case measures its results, a diagram of how other units and organizations could follow such procedure to carry out their own performance measurement was pointed out as well. Conclusion: The use of contribution margin and break-even point for the performance calculation benefited the managerial decision-making of the unit studied, serving as basis for its own strategy and use of its idleness. This is a reference model for decision-making of managers in other research units.Artigo Científico Early identification of older individuals at risk of mobility decline with machine learning(2022) Nascimento, Carla Ferreira do; ANDRE FILIPE DE MORAES BATISTA; Duarte, Yeda Aparecida Oliveira; Chiavegatto Filho, Alexandre Dias PortoBackground: : The early identification of individuals at risk of mobility decline can improve targeted strategies of prevention. Aims: : To evaluate the predictive performance of machine learning (ML) algorithms in identifying older in dividuals at risk of future mobility decline. Methods: : We used data from the SABE Study (Health, Well-being and Aging Study), a representative sample of people aged 60 years and more, living in the Municipality of São Paulo, Brazil. Mobility decline was assessed 5 years after admission in the study by self-reported difficulty to walk a block, climb steps, being able to stoop, crouch and kneel, or lifting or carrying weights greater than 5 kg. Popular machine learning algorithms were trained in 70% of the sample with 10-fold cross-validation, and predictive performance metrics were obtained from applying the trained algorithms to the other 30% (test set). Results: : Of the 1,615 individuals, 48% developed difficulty in at least one of the four tasks, 32% in stooping, crouching and kneeling, and 30% in carrying weights. The random forest algorithm had the best predictive performance for most outcomes. The tasks that the algorithm was able to predict with better performance were crouching and kneeling (AUC-ROC: 0.81[0.76–0.85]), and lifting or carrying weights (AUC-ROC: 0.80 [0.75–0.84]). Age was the most important variable for the algorithms, followed by education and back pain, according to the SHAP (SHapley Additive exPlanations) values. Conclusion: : Applications of ML algorithms are a promising tool to identify older patients at risk of mobility decline, with the potential of improving targeted preventive programs.Artigo Científico How Reliable Are The Screening Tools As A Triage Element For The Application Of The Global Leadership Initiative On Malnutrition (Glim)? Prospective Multicenter Observational Study(2023) Lopes, G.G.; Piovacari, S. M. F.; Moraes, J. R.; Santos, H. B. C.; Rakovicius, A. K. Z.; ANDRE FILIPE DE MORAES BATISTA; Pereira, A.J.Rationale: The international GLIM guideline recommends on the use of nutritional screening for the diagnosis of hospital malnutrition. However, as clinical outcomes were not included in the original validation of these instruments and their sensitivity (true positive rate) is unknown, it is not possible to report a chance of a truly at nutritional risk patient not being identified by screening and consequently not being evaluated by the GLIM. Methods: Multicenter, prospective observational trial in 3 Brazilian tertiary hospitals, carried out between December/21 to February/22. A convenience sample was used based on patients with expected length of stay at hospital longer than 48 hours. Pregnant women, under 18 years old, palliative care, lymphedema and muscle atrophy of neurological causes patients were excluded. NRS 2002, MNA-SF and ESPEN 2019 tools were applied to the specific populations (following international guidelines) by trained and validated Dietitians. Hospital mortality data were extracted from the local electronic medical records. Results: 676 patients were included, 54% male, 90% white with a mean age of 63 years (SD: ±21) and BMI of 27.50 kg/m2 (SD: ±4.72), hospitalized in the wards (68%). The most used nutritional screening was NRS 2002 (52%). In the sample, 39% were at nutritional risk, of these 5.6% died. An overview of nutritional screening tools’ performance are shown in the Table. In addition, accuracy found was 0.59 and area under the curve was 0,69 for predicting in-hospital deaths.Artigo Científico Identification of alterations associated with age in the clustering structure of functional brain networks(2018) Guzman, Grover E. C.; Sato, Joao R.; MACIEL CALEBE VIDAL; Fujita, AndreInitial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals’ functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.Artigo Científico Granger Causality among Graphs and Application to Functional Brain Connectivity in Autism Spectrum Disorder(2021) Ribeiro, Adèle Helena; MACIEL CALEBE VIDAL; Sato, João Ricardo; Fujita, AndréGraphs/networks have become a powerful analytical approach for data modeling. Besides, with the advances in sensor technology, dynamic time-evolving data have become more common. In this context, one point of interest is a better understanding of the information flow within and between networks. Thus, we aim to infer Granger causality (G-causality) between networks’ time series. In this case, the straightforward application of the well-established vector autoregressive model is not feasible. Consequently, we require a theoretical framework for modeling time-varying graphs. One possibility would be to consider a mathematical graph model with time-varying parameters (assumed to be random variables) that generates the network. Suppose we identify G-causality between the graph models’ parameters. In that case, we could use it to define a G-causality between graphs. Here, we show that even if the model is unknown, the spectral radius is a reasonable estimate of some random graph model parameters. We illustrate our proposal’s application to study the relationship between brain hemispheres of controls and children diagnosed with Autism Spectrum Disorder (ASD). We show that the G-causality intensity from the brain’s right to the left hemisphere is different between ASD and controls.Artigo Científico The Lysyl Oxidase Inhibitor, b-Aminopropionitrile, Diminishes the Metastatic Colonization Potential of Circulating Breast Cancer Cells(2009) Bondareva, Alla; Downey, Charlene M.; FABIO JOSE AYRES; Liu, Wei; Boyd, Steven K.; Hallgrimsson, Benedikt; Jirik, Frank R.Lysyl oxidase (LOX), an extracellular matrix remodeling enzyme, appears to have a role in promoting breast cancer cell motility and invasiveness. In addition, increased LOX expression has been correlated with decreases in both metastases-free, and overall survival in breast cancer patients. With this background, we studied the ability of b-aminopropionitrile (BAPN), an irreversible inhibitor of LOX, to regulate the metastatic colonization potential of the human breast cancer cell line, MDA MB-231. BAPN was administered daily to mice starting either 1 day prior, on the same day as, or 7 days after intracardiac injection of luciferase expressing MDA-MB-231-Luc2 cells. Development of metastases was monitored by in vivo bioluminescence imaging, and tumor-induced osteolysis was assessed by micro-computed tomography (mCT). We found that BAPN administration was able to reduce the frequency of metastases. Thus, when BAPN treatment was initiated the day before, or on the same day as the intra-cardiac injection of tumor cells, the number of metastases was decreased by 44%, and 27%, and whole-body photon emission rates (reflective of total tumor burden) were diminished by 78%, and 45%, respectively. In contrast, BAPN had no effect on the growth of established metastases. Our findings suggest that LOX activity is required during extravasation and/or initial tissue colonization by circulating MDA-MB-231 cells, lending support to the idea that LOX inhibition might be useful in metastasis prevention.Artigo Científico Detection of the Optic Nerve Head in Fundus Images of the Retina with Gabor Filters and Phase Portrait Analysis(2010) Rangayyan, Rangaraj M.; Zhu, Xiaolu; FABIO JOSE AYRES; Ells, Anna L.We propose a method using Gabor filters and phase portraits to automatically locate the optic nerve head (ONH) in fundus images of the retina. Because the center of the ONH is at or near the focal point of convergence of the retinal vessels, the method includes detection of the vessels using Gabor filters, detection of peaks in the node map obtained via phase portrait analysis, and an intensity-based condition. The method was tested on 40 images from the Digital Retinal Images for Vessel Extraction (DRIVE) database and 81 images from the Structured Analysis of the Retina (STARE) database. An ophthalmologist independently marked the center of the ONH for evaluation of the results. The evaluation of the results includes free-response receiver operating characteristics (FROC) and a measure of distance between the manually marked and detected centers. With the DRIVE database, the centers of the ONH were detected with an average distance of 0.36 mm (18 pixels) to the corresponding centers marked by the ophthalmologist. FROC analysis indicated a sensitivity of 100% at 2.7 false positives per image. With the STARE database, FROC analysis indicated a sensitivity of 88.9% at 4.6 false positives per image.Artigo Científico Wildfire-sourced fine particulate matter and preterm birth risks in Brazil: A nationwide population-based cohort study(2024) Zhang, Yiwen; Huang, Wenzhong; Xu, Rongbin; Ye, Tingting; Chen, Gongbo; Yue, Xu; Coêl , Micheline de Sousa Zanotti Stagliorio; Saldiva, Paulo Hilario Nascimento; Song, Jiangning; Guo, Yuming; Li, ShanshanWildfire-specific particulate matter with diameters ≤ 2.5 µm (PM2.5) is the key component of wildfire smoke, with potentially higher toxicity than PM2.5 from other sources. In this nationwide population-based cohort study, we included 22,163,195 births from Brazil during 2010–2019. Daily wildfire-specific PM2.5 was estimated through the chemical transport model. Time-varying Cox proportional hazards models were used to characterize the exposure-time-response (E-T-R) relationship between weekly wildfire-specific PM2.5 exposure and preterm birth (PTB) risks, followed by subgroup analyses. A 10 µg/m3 increment in wildfire-specific PM2.5 was associated with a hazard ratio of 1.047 (95 % confidence interval [CI]: 1.032–1.063) for PTB. Stronger associations between wildfire-specific PM2.5 and PTB were observed during earlier pregnancy, among female infants, and pregnant women < 18 years old, in ethnic minorities, with a length of education ≥ 11 years, from low-income or high temperature municipalities, and residing in North/Northeast regions. An estimated 1.47 % (95 % CI: 1.01 %–1.94 %) of PTBs were attributable to wildfire-specific PM2.5 in Brazil, increasing from 2010 to 2019. The PTBs attributable to wildfire-specific PM2.5 surpassed those attributed to non-wildfire PM2.5 (0.31 %, 95% CI: 0.09 %–0.57 %). Wildfire emerged as a critical source contributing to the PM2.5-linked PTBs. Prioritized fire management and emission control strategies are warranted for PTB prevention.Artigo CientíficoGEOLOGIA Comparison of weather station and climate reanalysis data for modelling temperature‑related mortality(2022) Mistry, Malcolm N.; Schneider, Rochelle; Masselot, Pierre; Royé, Dominic; Armstrong, Ben; Kyselý, Jan; Orru, Hans; Sera, Francesco; ShiluTong1; Lavigne, Éric; Urban, Aleš; Madureira, Joana; García‑León, David; Ibarreta, Dolores; Ciscar, Juan‑Carlos; Feyen, Luc; Schrijver, Evan de; Coelho, Micheline de Sousa Zanotti Stagliorio; Pascal, Mathilde; Tobias, Aurelio; Multi-Country Multi-City (MCC) Collaborative Research Network; Guo, Yuming; Vicedo‑Cabrera, Ana M.; Gasparrini, AntonioEpidemiological analyses of health risks associated with non-optimal temperature are traditionally based on ground observations from weather stations that offer limited spatial and temporal coverage. Climate reanalysis represents an alternative option that provide complete spatio-temporal exposure coverage, and yet are to be systematically explored for their suitability in assessing temperature-related health risks at a global scale. Here we provide the first comprehensive analysis over multiple regions to assess the suitability of the most recent generation of reanalysis datasets for health impact assessments and evaluate their comparative performance against traditional station-based data. Our findings show that reanalysis temperature from the last ERA5 products generally compare well to station observations, with similar non-optimal temperature-related risk estimates. However, the analysis offers some indication of lower performance in tropical regions, with a likely underestimation of heat-related excess mortality. Reanalysis data represent a valid alternative source of exposure variables in epidemiological analyses of temperature-related risk.