RESUMEN

This article implements a hybrid Machine Learning (ML) model to classify stoppage events in a copper-crushing equipment, more specifically, a conveyor belt. The model combines Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) with Principal Component Analysis (PCA) to identify the type of stoppage event when they occur in an industrial sector that is significant for the Chilean economy. This research addresses the critical need to optimise maintenance management in the mining industry, highlighting the technological relevance and motivation for using advanced ML techniques. This study focusses on combining and implementing three ML models trained with historical data composed of information from various sensors, real and virtual, as well from maintenance reports that report operational conditions and equipment failure characteristics. The main objective of this study is to improve the efficiency when identifying the nature of a stoppage serving as a basis for the subsequent development of a reliable failure prediction system. The results indicate that this approach significantly increases information reliability, addressing the persistent challenges in data management within the maintenance area. With a classification accuracy of 96.2% and a recall of 96.3%, the model validates and automates the classification of stoppage events, significantly reducing dependency on interdepartmental interactions. This advancement eliminates the need for reliance on external databases, which have previously been prone to errors, missing critical data, or containing outdated information. By implementing this methodology, a robust and reliable foundation is established for developing a failure prediction model, fostering both efficiency and reliability in the maintenance process. The application of ML in this context produces demonstrably positive outcomes in the classification of stoppage events, underscoring its significant impact on industry operations.

RESUMEN

Introduction: The COVID-19 pandemic has prompted global research efforts to reduce infection impact, highlighting the potential of cross-disciplinary collaboration to enhance research quality and efficiency. Methods: At the FMUSP-HC academic health system, we implemented innovative flow management routines for collecting, organizing and analyzing demographic data, COVID-related data and biological materials from over 4,500 patients with confirmed SARS-CoV-2 infection hospitalized from 2020 to 2022. This strategy was mainly planned in three areas: organizing a database with data from the hospitalizations; setting-up a multidisciplinary taskforce to conduct follow-up assessments after discharge; and organizing a biobank. Additionally, a COVID-19 curated collection was created within the institutional digital library of academic papers to map the research output. Results: Over the course of the experience, the possible benefits and challenges of this type of research support approach were identified and discussed, leading to a set of recommended strategies to enhance collaboration within the research institution. Demographic and clinical data from COVID-19 hospitalizations were compiled in a database including adults and a minority of children and adolescents with laboratory confirmed COVID-19, covering 2020-2022, with approximately 350 fields per patient. To date, this database has been used in 16 published studies. Additionally, we assessed 700 adults 6 to 11 months after hospitalization through comprehensive, multidisciplinary in-person evaluations; this database, comprising around 2000 fields per subject, was used in 15 publications. Furthermore, thousands of blood samples collected during the acute phase and follow-up assessments remain stored for future investigations. To date, more than 3,700 aliquots have been used in ongoing research investigating various aspects of COVID-19. Lastly, the mapping of the overall research output revealed that between 2020 and 2022 our academic system produced 1,394 scientific articles on COVID-19. Discussion: Research is a crucial component of an effective epidemic response, and the preparation process should include a well-defined plan for organizing and sharing resources. The initiatives described in the present paper were successful in our aim to foster large-scale research in our institution. Although a single model may not be appropriate for all contexts, cross-disciplinary collaboration and open data sharing should make health research systems more efficient to generate the best evidence.

Asunto(s)

RESUMEN

ABSTRACT BACKGROUND: Precisely determining the aspects related to an instrument's validity and reliability measures allows for greater assurance of the quality of the results. OBJECTIVES: To analyze the psychometric properties of The Providers Survey in the Brazilian context of mental health services. DESIGN AND SETTING: The instrument validation study was conducted in Montes Claros, Minas Gerais, Brazil. METHODS: The validation study was conducted using the Consensus-based Standards for the Selection of Health Measurement Instruments checklist to analyze its validity and reliability. RESULTS: A committee of expert judges performed content validation after which the Content Validity Index was calculated. Construct validation took place through Exploratory Factor Analysis using the Kaiser-Meyer-Olkin Test criterion and Bartlett's Sphericity Test. Reliability was verified using test-retest reliability. The significance level adopted for the statistical tests was 5% (P < 0.05). The final instrument comprised 54 questions. The Content Validity Index was 97%. Exploratory Factor Analysis identified a Kaiser-Meyer-Olkin index of 0.901 and Bartlett's Sphericity Test with P < 0.001. We obtained a Cronbach's alpha coefficient of 0.95 and an intraclass correlation coefficient of 0.849. CONCLUSIONS: The Providers Survey, translated and adapted into Portuguese, was named the Work Assessment Instrument for the Recovery of Mental Health. It presented adequate psychometric properties for evaluating work-related practices for the recovery of psychosocial care network users.

RESUMEN

Abstract Background: Alarms alert healthcare professionals of deviations from normal/physiologic status. However, alarm fatigue may occur when their high pitch and diversity overwhelm clinicians, possibly leading to alarms being disabled, paused, and/or ignored. We aimed to determine whether a staff educational program on customizing alarm settings of bedside monitors may decrease inconsistent alarms in the Post-Anesthesia Care Unit (PACU). Methods: This is a prospective, analytic, quantitative, pragmatic, open-label, single-arm study. The outcome was evaluated on PACU admission before (P1) and after (P2) the implementation of the educational program. The heart rate, blood pressure, and oxygen saturation alarms were selected for clinical consistency. Results: A total of 260 patients were included and 344 clinical alarms collected, with 270 (78.4%) before (P1), and 74 (21.6%) after (P2) the intervention. Among the 270 alarms in P1, 45.2% were inconsistent (i.e., false alarms), compared to 9.4% of the 74 in P2. Patients with consistent alarms occurred in 30% in the P1 and 27% in the P2 (p = 0.08). Patients with inconsistent alarms occurred in 25.4% in the P1 and in 3.8% in the P2. Ignored consistent alarms were reduced from 21.5% to 2.6% (p = 0.004) in the P2 group. The educational program was a protective factor for the inconsistent clinical alarm (OR = 0.11 [95% CI 0.04-0.3]; p < 0.001) after adjustments for age, gender, and ASA physical status. Conclusion: Customizing alarm settings on PACU admission proved to be a protective factor against inconsistent alarm notifications of multiparametric monitors.

RESUMEN

Data management "behind the scenes" refers to collection, cleaning, imputation, and demarcation; and despite of being indispensable processes, they are usually neglected and thus, generate erroneous information. During the collection are errors: omission of covariates, deviation from the objective, and insufficient quality. The omission of covariates distorts the result attributed to the main manoeuvre. Deviation from the primary objective commonly occurs when the outcome is rare, delayed, or subjective and promotes substitution by non-equivalent surrogate variables. Moreover, insufficient quality occurs due to inadequate instruments, omission of the measurement procedure, or measurements out of context, such as attribution at the wrong time or equivalent. Furthermore, cleaning implies identifying erroneous, extreme, and missing values, which may or may not be imputed, depending on the percentage. The values of the manoeuvre or the outcome are never imputed, nor are patients eliminated due to a lack of values. Finally, the demarcation of each variable seeks to give it a clinical meaning about the outcome, for which a hierarchical sequence of criteria is followed: 1) previous clinical study, 2) expert agreement, 3) clinical judgment of the investigator/investigators, and 4) statistics. Acting without quality controls in data management frequently causes involuntary lies and confuses instead of clarifying.

El manejo de datos "tras bambalinas" se refiere a los procesos de recopilación, limpieza, imputación y demarcación; los cuales, aun siendo indispensables, usualmente suelen ser descuidados, por lo que generan información errónea. Durante la recopilación son errores: omisión de covariables, desvío del objetivo, y calidad insuficiente. La omisión de covariables distorsiona el resultado atribuido a la maniobra principal. El desvío del objetivo primario es común cuando el desenlace es raro, tardado o subjetivo y promueve la sustitución por variables subrogadas no equivalentes. Además, la calidad insuficiente, sucede por instrumentos inadecuados, omisión del procedimiento de medición, o medición fuera de contexto -como atribución a destiempo o equivalente-. Por otro lado, la limpieza implica identificar valores erróneos, extremos y faltantes, que podrán ser o no imputados, dependiendo del porcentaje se imputará comúnmente por la medida de resumen. Nunca se imputan los valores de la maniobra ni del desenlace, ni se eliminan pacientes por falta de valores. Finalmente, la demarcación de cada variable busca un significado clínico en referencia al desenlace, para ello se sigue una secuencia jerárquica de criterios: 1) estudio clínico previo, 2) acuerdo de expertos, 3) juicio clínico del investigador/investigadores y 4) estadística. Actuar sin controles de calidad en el manejo de datos provoca frecuentemente mentiras involuntarias y confunde en lugar de esclarecer.

Asunto(s)

RESUMEN

Data quality monitoring plays a crucial role in multicenter prospective registries. By maintaining high data accuracy, completeness, and consistency, researchers can improve the overall quality and reliability of the registry data, enabling meaningful conclusions and supporting evidence-based decisions. The purpose of the present study was to evaluate data quality metrics (completeness, accuracy, and temporal plausibility) of a Multicenter Registry of Cardiac Implantable Electronic Devices (CIEDs) and to perform a direct data audit of a random sample of records to assess the agreement levels with the source documents. The CIED Registry was a prospective, multicenter, real-world observational study carried out from January 2020 to December 2022 in five designated centers across Sao Paulo, Brazil. We assessed the data quality of the CIED Registry by using two distinct approaches:•Dynamic data monitoring using features of the REDCap (Research Electronic Data Capture) software, including data reports and data quality rules•Direct data audit in which information from a random sample of 10 % of cases from the coordinating center was compared with original source documents Our findings suggest that the methodological approach applied to the CIED Registry resulted in high data completeness, accuracy, temporal plausibility, and excellent agreement levels with the source documents.

RESUMEN

BACKGROUND: Alarms alert healthcare professionals of deviations from normal/physiologic status. However, alarm fatigue may occur when their high pitch and diversity overwhelm clinicians, possibly leading to alarms being disabled, paused, and/or ignored. We aimed to determine whether a staff educational program on customizing alarm settings of bedside monitors may decrease inconsistent alarms in the Post-Anesthesia Care Unit (PACU). METHODS: This is a prospective, analytic, quantitative, pragmatic, open-label, single-arm study. The outcome was evaluated on PACU admission before (P1) and after (P2) the implementation of the educational program. The heart rate, blood pressure, and oxygen saturation alarms were selected for clinical consistency. RESULTS: A total of 260 patients were included and 344 clinical alarms collected, with 270 (78.4%) before (P1), and 74 (21.6%) after (P2) the intervention. Among the 270 alarms in P1, 45.2% were inconsistent (i.e., false alarms), compared to 9.4% of the 74 in P2. Patients with consistent alarms occurred in 30% in the P1 and 27% in the P2 (p = 0.08). Patients with inconsistent alarms occurred in 25.4% in the P1 and in 3.8% in the P2. Ignored consistent alarms were reduced from 21.5% to 2.6% (p = 0.004) in the P2 group. The educational program was a protective factor for the inconsistent clinical alarm (OR = 0.11 [95% CI 0.04-0.3]; p < 0.001) after adjustments for age, gender, and ASA physical status. CONCLUSION: Customizing alarm settings on PACU admission proved to be a protective factor against inconsistent alarm notifications of multiparametric monitors.

RESUMEN

AIMS: This article aims to perform a Systematic Literature Review (SLR) to better understand the structures of different methods, techniques, models, methodologies, and technologies related to provenance data management in health information systems (HISs). The SLR developed here seeks to answer the questions that contribute to describing the results. METHOD: An SLR was performed on six databases using a search string. The backward and forward snowballing technique was also used. Eligible studies were all articles in English that presented on the use of different methods, techniques, models, methodologies, and technologies related to provenance data management in HISs. The quality of the included articles was assessed to obtain a better connection to the topic studied. RESULTS: Of the 239 studies retrieved, 14 met the inclusion criteria described in this SLR. In order to complement the retrieved studies, 3 studies were included using the backward and forward snowballing technique, totaling 17 studies dedicated to the construction of this research. Most of the selected studies were published as conference papers, which is common when involving computer science in HISs. There was a more frequent use of data provenance models from the PROV family in different HISs combined with different technologies, among which blockchain and middleware stand out. Despite the advantages found, the lack of technological structure, data interoperability problems, and the technical unpreparedness of working professionals are still challenges encountered in the management of provenance data in HISs. CONCLUSION: It was possible to conclude the existence of different methods, techniques, models, and combined technologies, which are presented in the proposal of a taxonomy that provides researchers with a new understanding about the management of provenance data in HISs.

RESUMEN

ABSTRACT Objectives: to analyze the accuracy of the clinical indicators of ineffective airway clearance in adult intensive care unit patients. Methods: diagnostic accuracy study, performed in the intensive care unit of a university hospital in northeastern Brazil. The sample consisted of 104 patients hospitalized between June and October 2019. Results: the prevalence of ineffective airway clearance was 36.54%. The indicators with high specificity included absence of cough (0.8326), orthopnea (0.6817), adventitious breath sounds (0.8175), and diminished breath sounds (0.8326). The clinical indicators with high sensitivity and specificity were alteration in respiratory rate (0.9999) and alteration in respiratory pattern (0.9999). Conclusions: six clinical indicators provided an accurate identification of ineffective airway clearance. The clinical indicators alteration in respiratory rate and alteration in respiratory pattern were the most accurate for critical adult patients. The findings of this study contribute to accurate diagnostic inferences and to prevention of respiratory complications in these patients.

RESUMO Objetivos: analisar a acurácia dos indicadores clínicos de desobstrução ineficaz de vias aéreas em pacientes de unidade de terapia intensiva adulto. Métodos: estudo de acurácia diagnóstica em unidade de terapia intensiva de um hospital universitário do nordeste do Brasil. Amostra de 104 pacientes internados entre junho e outubro de 2019. Resultados: a prevalência de desobstrução ineficaz de vias aéreas foi de 36,54%. Os indicadores com alta especificidade foram ausência de tosse (0,8326), ortopneia (0,6817), sons respiratórios adventícios (0,8175) e sons respiratórios diminuídos (0,8326). Os indicadores clínicos com alta sensibilidade e especificidade foram alteração na frequência respiratória (0,9999) e alteração no padrão respiratório (0,9999). Conclusões: seis indicadores clínicos forneceram identificação precisa da desobstrução ineficaz de vias aéreas. Os indicadores clínicos alteração na frequência respiratória e alteração no padrão respiratório foram os mais precisos para pacientes críticos. Os achados contribuem para inferências diagnósticas precisas e para prevenção de complicações respiratórias nesses pacientes.

RESUMEN Objetivos: analizar la precisión de indicadores clínicos de limpieza ineficaz de las vías aéreas en pacientes de unidades de cuidados intensivos adulto. Métodos: estudio de precisión diagnóstica en unidad de cuidados intensivos de hospital universitario en noreste brasileño. Muestra de 104 pacientes hospitalizados entre junio y octubre de 2019. Resultados: prevalencia de limpieza ineficaz de las vías aéreas del 36,54%. Indicadores con alta especificidad; ausencia de tos (0,8326), ortopnea (0,6817), ruidos respiratorios adventicios (0,8175) y ruidos respiratorios disminuidos (0,8326). Indicadores clínicos con alta sensibilidad y especificidad; cambio en la frecuencia respiratoria (0,9999) y cambio en el patrón de respiración (0,9999). Conclusiones: seis indicadores clínicos proporcionaron identificación precisa de la limpieza ineficaz de las vías aéreas; cambio en la frecuencia respiratoria y cambio en el patrón de respiración fueron los más precisos para pacientes críticos. Nuestros hallazgos contribuyen a inferencias diagnósticas precisas y la prevención de complicaciones respiratorias en estos pacientes.

RESUMEN

The aim of this study was to predict production indicators and to determine their potential economic impact on a poultry integration system using artificial neural networks (ANN) models. Forty zootechnical and production parameters from broiler breeder farms, one hatchery, broiler production flocks, and one slaughterhouse were selected as variables. The ANN models were established for four output variables: "saleable hatching", "weight at the end of week 5," "partial condemnation," and "total condemnation" and were analyzed in relation to the coefficient of multiple determination (R2), correlation coefficient (R), mean error (E), mean squared error (MSE), and root mean square error (RMSE). The production scenarios were simulated and the economic impacts were estimated. The ANN models were suitable for simulating production scenarios after validation. For "saleable hatching", incubator and egg storage period are likely to increase the financial gains. For "weight at the end of the week 5" the lineage (A) is important to increase revenues. However, broiler weight at the end of the first week may not have a significant influence. Flock sex (female) may influence the "partial condemnation" rates, while chick weight at first day may not. For "total condemnation", flock sex and type of chick may not influence condemnation rates, but mortality rates and broiler weight may have a significant impact.

O objetivo deste trabalho foi predizer os indicadores de produção e determinar o seu potencial impacto econômico em um sistema de integração utilizando as redes neurais artificiais (RNA). Quarenta parâmetros zootécnicos e de produção de granjas de matrizes e de frango de corte, um incubatório e um abatedouro foram selecionados como variáveis. Os modelos de RNA foram estabelecidos para quatro variáveis de saída ("eclosão vendável", "peso ao final da quinta semana", "condenações parciais" e "condenações totais") e foram analisados em relação ao coeficiente de determinação múltipla (R2), coeficiente de correlação (R), erro médio (E), erro quadrático médio (EQM) e raiz do erro quadrático médio (REQM). Os cenários produtivos foram simulados e os impactos foram estimados. Os modelos de RNA gerados foram adequados para simular diferentes cenários produtivos após o treinamento. Para "eclosão vendável", o modelo de incubadora e o período de incubação aumentaram os ganhos financeiros. Para "peso ao final da quinta semana", a linhagem também demonstrou influencia no retorno financeiro, o que não aconteceu com o peso ao final da primeira semana. O sexo do lote possui influência nas taxas de "condenação parcial", ao contrário do peso do frango no primeiro dia. As taxas de mortalidade e o peso do frango apresentaram influência na "condenação total", mas o sexo do lote e o tipo de pinto não tiverem influência.

Asunto(s)

RESUMEN

INTRODUCTION: CHDs are the most common type of birth defect. One in four newborns with a heart defect has a critical CHD. In Mexico, there is a lack of data available to determine its prevalence. Pulse oximetry screening programmes have been implemented worldwide, reporting opportunity areas in algorithm interpretation and data management. Our study aims to share preliminary results of a 3-year experience of a multicentre pulse oximetry screening programme that addresses critical challenges. MATERIALS AND METHODS: This retrospective study examined the reports of newborns screened from February 2016 to July 2019 from five hospitals. Two algorithms -the New Jersey and the American Academy of Pediatrics- were implemented over consecutive periods. The algorithms' impact was assessed through the calculation of the false-positive rate in an eligible population. RESULTS: A total of 8960 newborns were eligible for the study; from it, 32.27% were screened under the New Jersey and 67.72% under the American Academy of Pediatrics algorithm - false-positive rate: 1% (CI 95: ± 0.36%) and 0.71% (CI 95: ± 0.21%), respectively. Seventy-nine newborns were referred, six were diagnosed with critical CHD, and six with CHD. The critical CHD estimated prevalence was 6.69:10,000 newborns (CI 95: ± 5.36). Our results showed that the algorithm was not related to the observable false-positive rate reduction. DISCUSSION: Other factors may play a role in decreasing the false-positive rate. Our experience implementing this programme was that a systematic screening process led to more confident results, newborn's report interpretation, and follow-up.

RESUMEN

RESUMEN Fundamento: existen muchas herramientas computacionales para administrar imágenes y conjuntos de datos; reducir la dimensión de estos favorece el manejo de la información. Objetivo: reducir la dimensión de un conjunto de datos para un mejor manejo de la información. Métodos: se utilizó el conjunto de datos de Breast Cancer Wisconsin (información de biopsias - células nucleares) y la plataforma Python Jupyter. Se implementaron técnicas de análisis de la componente principal (PCA) y Kernel PCA (kPCA) para reducir la dimensión a 2, 4, 6. Se hizo una validación cruzada para seleccionar los mejores hiperparámetros de los algoritmos de máquina de vectores de soporte y regresión logística. La clasificación se realizó con el training test original, training test (PCA y kPCA) y training test (datos transformados de PCA y kPCA). Se analizó la exactitud, precisión, exhaustividad, recuperación y el área bajo la curva. Resultados: la PCA con seis componentes explicó la tasa de variación casi en 90 %. Los mejores hiperparámetros hallados para máquina de soporte de vectores: kernel lineal y C = 100, para regresión logística fueron C = 100, Newton-cg solución (solver) e I2. Los mejores resultados de las métricas fueron para PCA 2 y 4(0,99; 0,99; 1; 0,99; 0,99). Para el training set con datos originales fueron 0,96; 0,95; 0,99; 0,97; 0,95. Para regresión logística los mejores resultados fueron para kPCA con seis componentes. Los resultados estadísticos fueron iguales a 1. Para el training set con datos originales, esos valores fueron 0,96; 0,95; 0,99; 0,97; 0.95. Conclusiones: los resultados de las métricas mejoraron utilizando PCA y kPCA.

ABSTRACT Background: there are many computational tools for managing images and data sets; reducing the size of these favors the management of information. Objective: reduce the data set size for better information management. Methods: the Breast Cancer Wisconsin data set (biopsy information - nuclear cells) and the Python Jupyter platform were used. Principal Component Analysis (PCA) and Kernel PCA (kPCA) techniques were implemented to reduce the dimension to 2, 4, 6. Cross-validation was made to select the best hyperparameters of the regression and support vector machine algorithms Logistics. The classification was carried out with the original training test, training test (PCA and kPCA) and training test (data transformed from PCA and kPCA). Accuracy, precision, completeness, recovery, and area under the curve were analyzed. Results: the PCA with six components explained the variation rate by almost 90%. The best hyperparameters found for the vector support machine: linear kernel and C = 100, for logistic regression were C = 100, Newton-cg solution (solver) and I2. The best results of the metrics were for PCA 2 and 4 (0.99, 0.99, 1, 0.99, 0.99). For the training set with original data they were 0.96; 0.95; 0.99; 0.97; 0.95. For logistic regression the best results were for kPCA with 6 components. The statistical results were equal to 1. For the training set with original data, these values were 0.96; 0.95; 0.99; 0.97; 0.95. Conclusions: the results of the metrics improved using PCA and kPCA.

RESUMEN

Abstract Introduction: This study examines early- and long-term outcomes of mitral valve repairs in a low-volume cardiac surgery centre in the Caribbean. Methods: Ninety-six consecutive patients underwent mitral valve repair from April 2009 to December 2018. Patients were divided into two groups: functional mitral regurgitation requiring simple mitral annuloplasty (FMR, n=63) or structural degenerative mitral regurgitation requiring more complex repair (DMR, n=33). Data collected prospectively were retrospectively analysed from the unit-maintained cardiac surgery database. Results: Thirty-day mortality in the whole series was 2.1%, with 3% in the FMR group and 0% in the DMR group. Early post-operative echocardiography in the FMR group demonstrated 51 patients (83.6%) without mitral regurgitation, 8 patients (13.1%) with trivial to mild regurgitation, and 2 patients (3.3%) with moderate regurgitation. However, at a mean follow-up of 98.2±50.8, only 21 patients (42.8%) were in NYHA class I, with 7 (14.2%) in class II, 16 (32.6%) in class III, and 5 (10.2%) in class IV. There were 9 cardiac-related deaths at final follow-up, with freedom from re-operation and survival of 98% and 75.6%, respectively. In the DMR group, early post-operative echocardiography demonstrated 29 patients (87.9%) without mitral regurgitation, 3 patients (9.1%) with trivial regurgitation and 1 patient (3.0%) with mild regurgitation. At a mean follow-up of 114.1±25.4 months, there was a good functional post-operative status in this group with 93.3% in NYHA class I, and 6.7% in class II. No patient required reintervention, 96.3% of patients had mild or no mitral regurgitation and survival was 90.9%. Conclusion: Despite challenges of maintaining skills in a low-volume centre, mitral valve repair can be performed safely with good early- and long-term results.

RESUMEN

ABSTRACT BACKGROUND: Multiple opinion-based communications have highlighted the actions of the Brazilian government during the pandemic. Nevertheless, none have appraised public data to identify factors associated with worsening of the healthcare system. OBJECTIVE: To analyze and collate data from public health and treasury information systems in order to understand the escalating process of weakening of Brazilian healthcare and welfare since the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. DESIGN AND SETTING: Secondary data study conducted using multiple public databases administered by the Brazilian federal government. METHODS: We processed information from multiple national databases and appraised health and economic-related data. RESULTS: Based on our analyses, there were substantial reductions in inpatient hospital admissions and in the numbers of patients seeking primary care services, along with a decrease in immunization coverage. Moreover, we observed a considerable decline in government transfers to hospital services (reduction of 82.0%) and a diminution of public outlays in several healthcare-related subfunctions ("hospital and outpatient care", "primary care", "prophylactic and therapeutic support" and "epidemiological surveillance"). We observed an increase in the overall mortality rate over the period analyzed, especially regarding all group-based diseases. Notably, there were remarkable differences among geographic, racial, gender and other parameters, thus revealing the impact of vulnerabilities on COVID-19 outcomes. CONCLUSION: This assessment of documentation of public expenditure and the shrinkage of investment in sensitive areas of the healthcare system in Brazil emphasized areas that still require collective attention in order to guarantee national welfare.

Asunto(s)

RESUMEN

Forensic investigations, especially those related to missing persons and unidentified remains, produce different types of data that must be managed and understood. The data collected and produced are extensive and originate from various sources: the police, non-governmental organizations (NGOs), medical examiner offices, specialised forensic teams, family members, and others. Some examples of information include, but are not limited to, the investigative background information, excavation data of burial sites, antemortem data on missing persons, and postmortem data on the remains of unidentified individuals. These complex data must be stored in a secured place, analysed, compared, shared, and then reported to the investigative actors and the public, especially the families of missing persons, who should be kept informed of the investigation. Therefore, a data management system with the capability of performing the tasks relevant to the goals of the investigation and the identification of an individual, while respecting the deceased and their families, is critical for standardising investigations. Data management is crucial to assure the quality of investigative processes, and it must be recognised as a holistic integrated system. The aim of this article is to discuss some of the most important components of an effective forensic data management system. The discussion is enriched by examples, challenges, and lessons learned from the erratic development and launching of databases for missing and unidentified persons in Brazil. The main objective of this article is to bring attention to the urgent need for an effective and integrated system in Brazil.

RESUMEN

INTRODUCTION: This study examines early- and long-term outcomes of mitral valve repairs in a low-volume cardiac surgery centre in the Caribbean. METHODS: Ninety-six consecutive patients underwent mitral valve repair from April 2009 to December 2018. Patients were divided into two groups: functional mitral regurgitation requiring simple mitral annuloplasty (FMR, n=63) or structural degenerative mitral regurgitation requiring more complex repair (DMR, n=33). Data collected prospectively were retrospectively analysed from the unit-maintained cardiac surgery database. RESULTS: Thirty-day mortality in the whole series was 2.1%, with 3% in the FMR group and 0% in the DMR group. Early post-operative echocardiography in the FMR group demonstrated 51 patients (83.6%) without mitral regurgitation, 8 patients (13.1%) with trivial to mild regurgitation, and 2 patients (3.3%) with moderate regurgitation. However, at a mean follow-up of 98.2±50.8, only 21 patients (42.8%) were in NYHA class I, with 7 (14.2%) in class II, 16 (32.6%) in class III, and 5 (10.2%) in class IV. There were 9 cardiac-related deaths at final follow-up, with freedom from re-operation and survival of 98% and 75.6%, respectively. In the DMR group, early post-operative echocardiography demonstrated 29 patients (87.9%) without mitral regurgitation, 3 patients (9.1%) with trivial regurgitation and 1 patient (3.0%) with mild regurgitation. At a mean follow-up of 114.1±25.4 months, there was a good functional post-operative status in this group with 93.3% in NYHA class I, and 6.7% in class II. No patient required reintervention, 96.3% of patients had mild or no mitral regurgitation and survival was 90.9%. CONCLUSION: Despite challenges of maintaining skills in a low-volume centre, mitral valve repair can be performed safely with good early- and long-term results.

Asunto(s)

RESUMEN

In digital curation, data are essential for actions, enabling better administrative management and greater efficiency in a sector or activity. In a research animal facility, the collection of management data associated with management systems or control sheets is the basis for ensuring quality information that subsidizes research and generates performance indicators and the needs and challenges to be transposed in the breeding and maintenance of animals. The inconsistency of data or incomplete records compromises the choices adopted in husbandry management practices or the interpretation of research results. For this reason, a survey was carried out about software available on the market that helps laboratory animal facilities with the management regarding software used in non-human primate breeding institutions (NHP) for scientific or conservation purposes. We identified 38 software that supports the handling of lab animals used in biomedical research; most of them with functionalities of environmental control (63.15%), control of animal files/tags (63.15%), and control of reproductive management (60%) and only two software related to the management of nonhuman primates kept under human care in research institutions. Regarding the tools used to manage the breeding of non-human primates in captivity in Brazilian institutions, five of the institutions questioned and reported that none currently uses software for colony management. In conclusion, there are several software for managing laboratory animals, but most of them are geared toward the management of rodent animal facilities. There is a lack of specific software on the market for use in animal facilities managing non-human primate breeding, which indicates the need for software developed to meet the management needs of animal facilities for these facilities.

Asunto(s)

RESUMEN

In recent years, egg production has had an intense growth in Brazil, and Brazilian egg consumption per capita has significantly increased in the last decade. To reduce sanitary and financial risks, decisions regarding the production and health status of the flock must be made based on objective criteria. Our aim was to determine the main "input" variables for the prediction of egg production performance in commercial laying breeder flocks using an ANN model. The software NeuroShellClassifier and NeuroShell Predictor were used to build the ANN. A total of 26 egg-production traits were selected as input variables and eight as output variables. A database of 44,120 Excel cells was generated. For the training and validation of the models, 74.9% and 25.1% of the data were used, respectively. The accuracy of the ANN models was calculated and compared using the analysis of coefficient of multiple determination (R2), mean squared error (MSE), and an assessment of uniform scatter in the residual plots. The models for the outputs "weekly egg production," "weekly incubated egg,", "accumulated commercial egg," and "viability" showed an R2 greater than 0.8. Other models yielded R2 values lower than 0.8. The ANN predicts adequately eight egg-production traits in the breeders of commercial laying hens. The method is an option for data management analysis in the egg industry, providing estimates of the relative contribution of each input variable to the outputs.(AU)

Asunto(s)

RESUMEN

Este estudo aborda o tema de sistemas de informação utilizados na gestão de recursos humanos em saúde na Secretaria de Estado de Saúde do Rio de Janeiro (SES/RJ), órgão da Administração Direta do Poder Executivo do Estado. A SES/RJ é responsável por definir políticas de saúde no Estado, a qual utiliza vários sistemas de informação para gestão de sua força de trabalho, com evidências de fragmentação dos dados, dificuldade na gestão das informações e prejuízo na definição de estratégias. Nesse sentido, este trabalho tem como objetivo descrever os sistemas de informação de recursos humanos em uso na SES/RJ, no contexto dos modelos de gestão adotados em suas unidades de saúde, e contribuir para melhorar a gestão de recursos humanos e das informações geradas no âmbito da instituição, fornecendo subsídios para o processo de tomada de decisão. Para tanto, fez-se, primeiramente, uma revisão bibliográfica sobre o tema desde o ano de 1995, período da Reforma do Estado, e uma pesquisa documental em portais e legislações, tanto da SES/RJ como de outros órgãos estaduais, assim como das esferas federal e municipal. Em seguida, o trabalho discute as possibilidades e os subsídios que possam favorecer a interoperabilidade desses sistemas e, assim, facilitar a gestão da força de trabalho na instituição.

This study investigates the use of information systems in the administration of human resources in health at the Rio de Janeiro State Department of Health (SES/RJ), which is part of the Direct Administration of the State Government. SES/RJ oversees establishing state health policies and managing its staff using a variety of information systems, with evidence of data fragmentation, information management challenges, and strategy development impairment. In this sense, this study aims to describe the human resources information systems in use at SES/RJ in relation to the management models used in its health units, as well as to contribute to improving human resources management and the information generated within the institution by providing decision-making inputs. To that end, we conducted a bibliographic review of the topic dating back to 1995, during the State Reform period, as well as document search in the portals and legislation of SES/RJ and other state agencies, as well as federal and municipal domains. The study then moves on to the possibilities and advantages that may encourage system interoperability and, as a result, make labor management in the institution easier.

Asunto(s)

RESUMEN

INTRODUCCIÓN: La Fibrosis Pulmonar Idiopática (FPI) es una de las enfermedades respiratorias crónicas del adulto de mayor impacto y letalidad, diversos estudios epidemiológicos muestran tendencias progresivas al aumento de las tasas de mortalidad por FPI. En Chile no existen reportes sobre las tendencias de las tasas de mortalidad por FPI. El objetivo del presente estudio es determinar las tendencias de la mortalidad por FPI en Chile entre los años 2002 y 2015. MÉTODO: Estudio descriptivo de diseño ecológico, a partir de la información de bases de datos secundarias de libre disposición de las estadísticas vitales del Departamento de Estadísticas e Información de Salud (DEIS) y del Instituto Nacional de Estadísticas (INE) de Ministerio de Salud de Chile entre los años 2002 y 2015 se obtuvieron las tasas crudas de mortalidad por fibrosis pulmonar idiopática en población de 45 años y más en ambos sexos y las tasas ajustadas por sexo y edad por regiones, se calculó también la frecuencia mensual de las muertes por FPI y se compararon las tasas medias de mortalidad por regiones. RESULTADOS: Se observó un incremento progresivo de la tasa nacional cruda de mortalidad por FPI entre los años 2002 a 2015, la que fue de 18,5 fallecidos por 100.000 habitantes en el año 2002 hasta 24,6 fallecidos por 100.000 habitantes en el año 2015 con una pendiente de ascenso por año de +0,27 por 100.000 habitantes (p = 0,013). En las mujeres las tasas fueron más altas que en los hombres, pero las pendientes de ascenso no presentaron diferencias entre sexos. En la gran mayoría de las regiones las tasas ajustadas presentaron tendencias significativas al ascenso y las tasas medias más altas se presentaron en las regiones del norte de Chile. Se observó un comportamiento estacional de las muertes siendo las frecuencias más altas en los meses de invierno. CONCLUSIONES: Las tasas de mortalidad por FPI en Chile presentan una tendencia progresiva al aumento, con marcadas diferencias regionales lo que lleva a considerar, entre otros factores, influencia ambiental y contaminación del aire y de suelos que se debieran investigar para poder realizar intervenciones de salud pública que permitan reducir la mortalidad de esta enfermedad en nuestro país.

BACKGROUND: Idiopathic Pulmonary Fibrosis (IPF) is one of the chronic respiratory diseases in adults with the greatest impact and high case fatality rate. Various epidemiological studies show progressive trends towards increasing IPF mortality rates. In Chile there are no national reports on country and regional trends in IPF mortality rates. The objective of this study is to determine trends in mortality due to IPF in Chile from year 2002 to 2015. METHOD: Epidemiological study of ecological design based on information from public databases of vital statistics of the Department of Health Statistics and Information (DEIS) and the National Institute of Statistics (INE) of the Ministry of Health of Chile. Crude mortality rates due to IPF in the population aged 45 years and over in both sexes were obtained from years 2002 to 2015. Besides the adjusted mortality rates for sex and age by region, the monthly frequency of IPF deaths during the same period and the average mortality rates by Chilean regions were calculated. RESULTS: A progressive increasing trend in the crude national IPF mortality rate was observed between years 2002 to 2015, which went from 18.5 deaths per 100,000 inhabitants in 2002 to 24.6 deaths per 100,000 inhabitants in 2015 with a slope of ascent per year of +0.27 per 100,000 inhabitants (p = 0.013); female rates were higher than men rates, but without differences in the slopes between sexes; in the vast majority of the regions the rates showed significant upward trends with the higher ones in the northern regions of Chile. A seasonal behavior of the death's frequency was observed being the highest in the winter term. CONCLUSIONS: Mortality rates due to IPF in Chile show a progressive upward trend, with marked regional differences which leads to consider, among other factors, environmental influence and air and soil contamination that should be investigated to carry out public health interventions that allow reducing the mortality of this disease in our country.

Asunto(s)