Notas sobre o pesquisar em cena(s) / Notes on researching in scenes / Notas sobre la investigación en escena(s)

O presente artigo tem como objetivo apresentar a construção metodológica desenvolvida em uma pesquisa de mestrado, na qual sustentamos a escrita de cenas como método de pesquisa da escuta clínica. As cenas do trabalho em questão foram recolhidas ao longo do tempo, no contorno da experiência de um projeto de extensão universitária de atenção à infância e adolescência em situação de vulnerabilidade social, situado em uma comunidade periférica. Apresentamos, neste texto, as interrogações que se elaboraram em torno da escolha pelo trabalho com cenas, e compartilhamos o resgate histórico dessas como um método de escrever a clínica, bem como a retomada de sua análise a partir da tradição psicanalítica. Amparadas nesta teoria e em leituras e contribuições do filósofo francês Jacques Derrida, embasamos a noção de que a cena se constitui como um lugar de produção, ao engendrar a configuração particular de elementos significantes nos processos de subjetivação e de construção social. A cena não é, então, compreendida aqui como uma representação do que acontece na clínica, mas como um modo de produzir a escuta e os seus processos de investigação.(AU)

This article aims to present the methodological construction developed in a master's research, in which the writing of scenes as a method of clinical listening research was endorsed. The scenes from the study in question were collected over time, from the experience gained in a project conducted within a university extension program on care in childhood and adolescence in social vulnerability, in a peripheral community. In this study, we present some questions that were elaborated surrounding the choices of working with scenes; and we share the historical rescue of this work as a method of writing on clinic practices and resuming their analysis from the psychoanalytic tradition. Based on the psychoanalytic theory and on the readings and contributions of the French philosopher Jacques Derrida, we corroborate the notion that the scene is constituted as a place of production, engendering the particular configuration of significant elements in the processes of subjectivation and social construction. Here, the scene is not a representation of clinical practice but one mode of producing listening and its research processes.(AU)

Este artículo tiene como objetivo presentar la construcción metodológica desarrollada en una investigación de maestría, en la que sostenemos la escritura de escenas como método de investigación de la escucha clínica. Las escenas del trabajo en cuestión se recogieron a lo largo del tiempo desde la experiencia en un proyecto de extensión universitario de atención a la niñez y adolescencia en situación de vulnerabilidad social aplicado en una comunidad periférica. En este texto, presentamos los interrogantes que se elaboraron en torno a la elección por el trabajo con escenas y compartimos el rescate histórico de las mismas como un método de escribir la clínica y la reanudación del análisis a partir de la tradición psicoanalítica. Amparadas en el psicoanálisis y en lecturas y contribuciones del filósofo francés Jacques Derrida, nos basaremos en la noción de que la escena se constituye como un lugar de producción, engendrando la configuración particular de elementos significantes en los procesos de subjetivación y de construcción social. La escena no es aquí una representación de lo que pasa en la clínica, sino un modo de producir escucha y sus procesos de investigación.(AU)

Allergy to Gibberellin-Regulated Proteins (Peamaclein) in Children.

BACKGROUND: Gibberellin-regulated proteins (GRPs, Peamaclein) are allergens recently identified in plant-derived food allergy (FA), and little is known about the clinical manifestations of this allergic condition in the European population, especially in children. OBJECTIVE: Our study aimed to identify and characterize pediatric patients with pollen-FA due to GRP sensitization. METHODS: We retrospectively analyzed the charts of patients referred to the Allergy Unit of the Meyer Children's Hospital in Florence for suspected FA. Three main eligibility criteria based on the actual knowledge of GRP allergy were used to select patients deserving further investigations: (1) systemic reactions after consumption of fruit or an unknown culprit food, (2) positive skin prick tests to both cypress pollen and Pru p 3-enriched peach peel extracts, (3) negative in vitro test results for Pru p 3 serum-specific Immunoglobulin E (sIgE). We performed the in vitro test to determine the anti-rPru p 7 (Peamaclein) sIgE levels in the selected patients. RESULTS: We identified 10 pediatric patients with Pru p 7 allergy and described their characteristics. The use of our eligibility criteria showed a high accuracy in identifying these patients: 100% of the selected patients had positive in vitro results for Pru p 7. We therefore proposed a diagnostic algorithm for Pru p 7 allergy. CONCLUSION: This is the first case series of European pediatric patients with a demonstrated Peamaclein allergy. These findings broaden our knowledge on GRP allergy in pediatric populations and could help clinicians to suspect, diagnose, and manage this recently discovered plant-derived FA.

AGA Technical Review on Intragastric Balloons in the Management of Obesity.

Several strategies are available to address the obesity epidemic and range from noninvasive lifestyle interventions to medications and bariatric surgical procedures. Endoscopic bariatric techniques, such as intragastric balloons, have become an attractive alternative as a tool for weight loss that can augment the effect of lifestyle interventions. This technical review includes multiple systematic reviews performed to support a clinical practice guideline by the American Gastroenterological Association on the role of intragastric balloons as a tool for weight loss. The systematic reviews targeted a priori selected clinical questions about the effectiveness and periprocedural care of intragastric balloons and concomitant and subsequent weight-loss strategies.

Point-Counterpoint: Indirect Calorimetry Is not Necessary for Optimal Nutrition Therapy in Critical Illness.

Clinicians have widely recognized that indirect calorimetry (IC) is the "gold standard" for measuring energy expenditure (EE) and thus would intuitively anticipate that its use would be needed to provide optimal nutrition support in critical illness. Recent studies in the literature as well as dramatic changes in clinical practice over the past decade, though, would suggest that such a precise measure by IC to set energy goals is not required to maximize clinical benefit from early feeding in the intensive care unit (ICU). Results from randomized controlled trials evaluating permissive underfeeding, use of supplemental parenteral nutrition to achieve tight calorie control, and caloric density of formulas to increase energy delivery have provided an important perspective on 3 pertinent issues. First, a simple weight-based predictive equation (25 kcal/kg/day) provides a clinically useful approximation of EE. Second, a precise measure of EE by IC does not appear to improve outcomes compared with use of this less accurate estimation of energy requirements. And third, providing some percentage of requirements (50%-80%), achieves similar clinical benefit to full feeding (100%) in the early phases of critical illness. The value from IC use lies in the determination of caloric requirements in conditions for which weight-based equations are rendered inaccurate (anasarca, amputation, severe obesity) or the clinical state is markedly altered (such as the prolonged hyperinflammatory state of coronavirus disease 2019 [COVID-19]). In most other circumstances, routine use of IC would not be expected to change clinical outcomes from early nutrition therapy in the ICU.

Development of a clinical decision tool to reduce diagnostic testing for primary aldosteronism in patients with difficult-to-control hypertension.

BACKGROUND: Satisfactory tools to preclude low-risk patients from intensive diagnostic testing for primary aldosteronism (PA) are lacking. Therefore, we aimed to develop a decision tool to determine which patients with difficult-to-control hypertension have a low probability of PA, thereby limiting the exposure to invasive testing while at the same time increasing the efficiency of testing in the remaining patients. METHODS: Data from consecutive patients with difficult-to-control hypertension, analysed through a standardized diagnostic protocol between January 2010 and October 2017 (n = 824), were included in this cross-sectional study. PA was diagnosed by a combined approach: 1) elevated aldosterone-to-renin ratio (> 5.0 pmol/fmol/s), confirmed with 2) non-suppressible aldosterone after standardized saline infusion (≥280 pmol/L). Multivariable logistic regression analyses including seven pre-specified clinical variables (age, systolic blood pressure, serum potassium, potassium supplementation, serum sodium, eGFR and HbA1c) was performed. After correction for optimism, test reliability, discriminative performance and test characteristics were determined. RESULTS: PA was diagnosed in 40 (4.9%) of 824 patients. Predicted probabilities of PA agreed well with observed frequencies and the c-statistic was 0.77 (95% confidence interval (95%CI) 0.70-0.83). Predicted probability cut-off values of 1.0-2.5% prevented unnecessary testing in 8-32% of the patients with difficult-to-control hypertension, carrying sensitivities of 0.98 (95%CI 0.96-0.99) and 0.92 (0.83-0.97), and negative predictive values of 0.99 (0.98-1.00) and 0.99 (0.97-0.99). CONCLUSIONS: With a decision tool, based on seven easy-to-measure clinical variables, patients with a low probability of PA can be reliably selected and a considerable proportion of patients with difficult-to-control hypertension can be spared intensive diagnostic testing.

Treatment of Hepatocellular Carcinoma in the Precision Medicine Era: From Treatment Stage Migration to Therapeutic Hierarchy.

Treatment allocation is extremely complex in patients with hepatocellular carcinoma (HCC) because this neoplasm arises, in most cases, in patients with cirrhosis and additional comorbidities. The "stage hierarchy" approach, which involves linking each stage (or substage) of the disease to a specific treatment, has become the main proposed treatment strategy for the clinical management of HCC, particularly in the West. The Barcelona Clinic Liver Cancer (BCLC) scheme serves as the main example of the application of this strategy. In an attempt to increase the plasticity of the "stage hierarchy" approach as well as its adaptability to the requirements of real-world clinical practice, the latest versions of European and American guidelines have introduced certain relevant elements of flexibility, which were not intrinsic to the original BCLC scheme. These elements are as follows: the "treatment stage migration" strategy, which allows moving to another treatment (generally the one that is associated with the subsequent stage) if the approach linked with the current stage proves to be unfeasible, and the "treatment stage alternative" approach, which proposes further therapeutic options for each BCLC-defined stage. In regard to most of the solid cancers, another potential strategy is to consider the treatment decision to be hierarchically dictated by the efficacy of each therapy with complete or partial independence from the tumor stage. This concept of "therapeutic hierarchy" has been historically endorsed by the Asia-Pacific treatment algorithm as well as by the recent Italian multisociety guidelines. The present review provides a critical analysis of the different conceptual approaches to HCC management, highlighting their advantages and disadvantages and focusing on the remarkable differences between the stage-guided and the hierarchical strategies.

International validation and update of the Amsterdam model for prediction of survival after pancreatoduodenectomy for pancreatic cancer.

BACKGROUND: The objective of this study was to validate and update the Amsterdam prediction model including tumor grade, lymph node ratio, margin status and adjuvant therapy, for prediction of overall survival (OS) after pancreatoduodenectomy for pancreatic cancer. METHODS: We included consecutive patients who underwent pancreatoduodenectomy for pancreatic cancer between 2000 and 2017 at 11 tertiary centers in 8 countries (USA, UK, Germany, Italy, Sweden, the Netherlands, Korea, Australia). Model performance for prediction of OS was evaluated by calibration statistics and Uno's C-statistic for discrimination. Validation followed the TRIPOD statement. RESULTS: Overall, 3081 patients (53% male, median age 66 years) were included with a median OS of 24 months, of whom 38% had N2 disease and 77% received adjuvant chemotherapy. Predictions of 3-year OS were fairly similar to observed OS with a calibration slope of 0.72. Statistical updating of the model resulted in an increase of the C-statistic from 0.63 to 0.65 (95% CI 0.64-0.65), ranging from 0.62 to 0.67 across different countries. The area under the curve for the prediction of 3-year OS was 0.71 after updating. Median OS was 36, 25 and 15 months for the low, intermediate and high risk group, respectively (P < 0.001). CONCLUSIONS: This large international study validated and updated the Amsterdam model for survival prediction after pancreatoduodenectomy for pancreatic cancer. The model incorporates readily available variables with a fairly accurate model performance and robustness across different countries, while novel markers may be added in the future. The risk groups and web-based calculator www.pancreascalculator.com may facilitate use in daily practice and future trials.

A risk prediction model for heart failure hospitalization in type 2 diabetes mellitus.

BACKGROUND: Antidiabetic therapies have shown disparate effects on hospitalization for heart failure (HHF) in clinical trials. This study developed a prediction model for HHF in type 2 diabetes mellitus (T2DM) using real world data to identify patients at high risk for HHF. HYPOTHESIS: Type 2 diabetics at high risk for HHF can be identified using information generated during usual clinical care. METHODS: This electronic medical record- (EMR-) based retrospective cohort study included patients with T2DM free of HF receiving healthcare through a single, large integrated healthcare system. The primary endpoint was HHF, defined as a hospital admission with HF as the primary diagnosis. Cox regression identified the strongest predictors of HHF from 80 candidate predictors derived from EMRs. High risk patients were defined according to the 90th percentile of estimated risk. RESULTS: Among 54,452 T2DM patients followed on average 6.6 years, estimated HHF rates at 1, 3, and 5 years were 0.3%, 1.1%, and 2.0%. The final 9-variable model included: age, coronary artery disease, blood urea nitrogen, atrial fibrillation, hemoglobin A1c, blood albumin, systolic blood pressure, chronic kidney disease, and smoking history (c = 0.782). High risk patients identified by the model had a >5% probability of HHF within 5 years. CONCLUSIONS: The proposed model for HHF among T2DM demonstrated strong predictive capacity and may help guide therapeutic decisions.

Clinical rule-guided pharmacists' intervention in hospitalized patients with hypokalaemia: A time series analysis.

WHAT IS KNOWN AND OBJECTIVE: Physicians' response to moderate and severe hypokalaemia in hospitalized patients is frequently suboptimal, leading to increased risk of cardiac arrhythmias and sudden death. While actively alerting physicians on all critical care values using telephone or electronic pop-ups can improve response, it can also lead to alert fatigue and frustration due to non-specific and overdue alerts. Therefore, a new method was tested. A clinical rule built into a clinical decision support system (CDSS) generated alerts for patients with a serum potassium level (SPL) <2.9 mmol/L without a prescription for potassium supplementation. If the alert was deemed clinically relevant, a pharmacist contacted the physician. The aim of this study was to evaluate the impact of the clinical rule-guided pharmacists' intervention compared to showing passive alerts in the electronic health records on outcome in patients who developed hypokalaemia (<2.9 mmol/L) during hospitalization. METHODS: A before (2007-2009) and after (2010-2017) study with time series design was performed. Pre-intervention, physicians were shown passive alerts for hypokalaemia in the electronic health records. During the intervention period, in addition to these passive alerts, a pharmacist provided the physician with a specific advice on patients with untreated hypokalaemia, guided by the generated alerts. Unique patients >18 years with SPL <2.9 mmol/L measured at least 24 hours after hospitalization in whom no potassium supplementation was initiated within 4 hours after measurement and normalization of SPL was not achieved within these 4 hours were included. Haemodialysis patients were excluded. The percentage of hypokalaemic patients with a subsequent prescription for potassium supplementation, time to subsequent potassium supplementation prescription, the percentage of patients who achieved normokalaemia (SPL ≥ 3.0 mmol/L), time to achieve normokalaemia and total duration of hospitalization were compared. RESULTS AND DISCUSSION: A total of 693 patients were included, of whom 278 participated in the intervention phase. The percentage of patients prescribed supplementation as well as time to prescription improved from 76.0% in 31.1 hours to 92.0% in 11.3 hours (P < .01). Time to achieve SPL ≥3.0 mmol/L improved, P < .009. No changes, however, were observed in the percentage of patients who achieved normokalaemia or time to reach normokalaemia, 87.5% in 65.2 hours pre-intervention compared to 90.2% (P = .69) in 64.0 hours (P = .71) in the intervention group. A non-significant decrease of 8.2 days was observed in the duration of hospitalization: 25.4 compared to 17.2 days (P = .29). WHAT IS NEW AND CONCLUSION: Combining CDSS alerting with a pharmacist evaluation is an effective method to improve response rate, time to supplementation and time to initial improvement, defined as SPL ≥3.0 mmol/L. However, it showed no significant effect on the percentage of patients achieving normokalaemia, time to normokalaemia or hospitalization. The discrepancy between rapid supplementation and improvement on the one hand and failure to improve time to normokalaemia on the other warrants further study.

Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction.

OBJECTIVE: The neonatal period of a child is considered the most crucial phase of its physical development and future health. As per the World Health Organization, India has the highest number of pre-term births [1], with over 3.5 million babies born prematurely, and up to 40% of them are babies with low birth weights, highly prone to a multitude of diseases such as Jaundice, Sepsis, Apnea, and other Metabolic disorders. Apnea is the primary concern for caretakers of neonates in intensive care units. The real-time medical data is known to be noisy and nonlinear and to address the resultant complexity in classification and prediction of diseases; there is a need for optimizing learning models to maximize predictive performance. Our study attempts to optimize neural network architectures to predict the occurrence of apneic episodes in neonates, after the first week of admission to Neonatal Intensive Care Unit (NICU). The primary contribution of this study is the formulation and description of a set of generic steps involved in selecting various model-specific, training and hyper-parametric optimization algorithms, as well as model architectures for optimal predictive performance on complex and noisy medical datasets. METHODS: The data used for the study being inherently complex and noisy, Kernel Principal Component Analysis (PCA) is used to reduce dataset dimensionality for the analysis such as interpretations and visualization of the dataset. Hyper-parametric and parametric optimization, in different categories, are considered, including learning rate updater algorithms, regularization methods, activation functions, gradient descent algorithms and depth of the network, based on their performance on the validation set, to obtain a holistically optimized neural network, that best model the given complex medical dataset. Deep Neural Network Architectures such as Deep Multilayer Perceptron's, Stacked Auto-encoders and Deep Belief Networks are employed to model the dataset, and their performance is compared to the optimized neural network obtained from the parametric exploration. Further, the results are compared with Support Vector Machine (SVM), K Nearest Neighbor, Decision Tree (DT) and Random Forest (RF) algorithms. RESULTS: The results indicate that the optimized eight layer Multilayer Perceptron (MLP) model, with Adam Decay and Stochastic Gradient Descent (AUC 0.82) can outperform the conventional machine learning models, and perform comparably to the Deep Auto-encoder model (AUC 0.83) in predicting the presence of apnea in neonates. CONCLUSION: The study shows that an MLP model can undergo significant improvements in predictive performance, by the proposed step-wise optimization. The optimized MLP is proved to be as accurate as deep neural network models such as Deep Belief Networks and Deep Auto-encoders for noisy and nonlinear data sets, and outperform all conventional models like Support Vector Machine (SVM), Decision Tree (DT), K Nearest Neighbor and Random Forest (RF) algorithms. The generic nature of the proposed step-wise optimization provides a framework to optimize neural networks on such complex nonlinear datasets. The investigated models can help neonatologists as a diagnostic tool.

Prevalence and predictors of chronic kidney disease among Ghanaian patients with hypertension and diabetes mellitus: A multicenter cross-sectional study.

The burden of chronic kidney disease (CKD) is rapidly rising in developing countries due to astronomical increases in key risk factors including hypertension and diabetes. We sought to assess the burden and predictors of CKD among Ghanaians with hypertension and/or diabetes mellitus in a multicenter hospital-based study. We conducted a cross-sectional study in the Ghana Access and Affordability Program (GAAP) involving adults with hypertension only (HPT), hypertension with diabetes mellitus (HPT + DM), and diabetes mellitus only (DM) in 5 health facilities in Ghana. A structured questionnaire was administered to collect data on demographic variables, medical history, and clinical examination. Serum creatinine and proteinuria were measured, and estimated glomerular filtration rate derived using the CKD-EPI formula. A multivariable logistic regression model was used to identify factors associated with CKD. A total of 2781 (84.4%) of 3294 participants had serum creatinine and proteinuria data available for analysis. The prevalence of CKD was 242 (28.5%) among participants with both DM and HPT, 417 (26.3%) among participants with HPT, and 56 (16.1%) among those with DM alone. Predictors of CKD were increasing age aOR 1.26 (1.17-1.36), low educational level aOR 1.7 (1.23-2.35), duration of HPT OR, 1.02 (1.01-1.04), and use of herbal medications aOR 1.39 (1.10-1.75). Female gender was protective of CKD aOR 0.75 (0.62-0.92). Among patients with DM, increasing age and systolic blood pressure were associated with CKD. There is high prevalence of CKD among DM and hypertension patients in Ghana. Optimizing blood pressure control and limiting the use of herbal preparations may mitigate CKD occurrence in high cardiovascular risk populations in developing countries.

A Simpler Prediction Rule for Rebound Hyperbilirubinemia.

OBJECTIVES: We previously reported a clinical prediction rule to estimate the probability of rebound hyperbilirubinemia using gestational age (GA), age at phototherapy initiation, and total serum bilirubin (TSB) relative to the treatment threshold at phototherapy termination. We investigated (1) how a simpler 2-variable model would perform and (2) the absolute rebound risk if phototherapy were stopped at 2 mg/dL below the threshold for treatment initiation. METHODS: Subjects for this retrospective cohort study were infants born 2012-2014 at ≥35 weeks' gestation at 1 of 17 Kaiser Permanente hospitals who underwent inpatient phototherapy before age 14 days. TSB reaching the phototherapy threshold within 72 hours of phototherapy termination was considered rebound. We simplified by using the difference between the TSB level at the time of phototherapy termination and the treatment threshold at the time of phototherapy initiation as 1 predictor, and kept GA as the other predictor. RESULTS: Of the 7048 infants treated with phototherapy, 4.6% had rebound hyperbilirubinemia. The area under the receiver operating characteristic curve was 0.876 (95% confidence interval, 0.854 to 0.899) for the 2-variable model versus 0.881 (95% confidence interval, 0.859 to 0.903) for the 3-variable model. The rebound probability after stopping phototherapy at 2 mg/dL below the starting threshold was 2.5% for infants ≥38 weeks' GA and 10.2% for infants <38 weeks' GA. CONCLUSIONS: Rebound hyperbilirubinemia can be predicted by a simpler 2-variable model consisting of GA and the starting threshold-ending TSB difference. Infants <38 weeks' gestation may need longer phototherapy because of their higher rebound risk.