Background: Data on the performance of saliva specimens for diagnosing COVID-19 in ambulatory patients are scarce and inconsistent. We assessed saliva-based specimens for detecting SARS-CoV-2 by RT-PCR in the community setting and compared three different collection methods. Method: Prospective study conducted in three primary care centres. RT-PCR was performed in paired nasopharyngeal swabs (NPS) and saliva samples collected from outpatients with a broad clinical spectrum of illness. To assess differences in collection methods, saliva specimens were obtained in a different way in each of the participating centres: supervised collection (SVC), oropharyngeal washing (OPW) and self-collection (SC). Results: NPS and saliva pairs of samples from 577 patients (median age 39 years, 44% men, 42% asymptomatic) were collected and tested, and 120 (20.8%) gave positive results. The overall agreement with NPS and kappa coefficients (Ƙ) for SVC, OPW and SC were 95% (Ƙ=0.85), 93.4% (Ƙ=0.76), and 93.3% (Ƙ=0.76), respectively. The sensitivity (95% CI) of the saliva specimens varied from 86% (72.6-93.7) for SVC to 66.7% (50.4-80) for SC samples. The sensitivity was higher in samples with lower cycle threshold (Ct) values. The best performance of RT-PCR was observed for SVC, with sensitivity (95% CI) for Ct values ≤30 of 100% (85.9-100) in symptomatic, and 88.9% (50.7-99.4) in asymptomatic individuals. Conclusions: Saliva is an acceptable specimen for the detection of SARS-CoV-2 in the community setting. Specimens collected under supervision perform comparably to NPS and can effectively identify individuals with higher risk of transmission in real life conditions.

Background: Data on the performance of saliva specimens for diagnosing COVID-19 in ambulatory patients are scarce and inconsistent. We assessed saliva-based specimens for detecting SARS-CoV-2 by RT-PCR in the community setting and compared three different collection methods. Method: Prospective study conducted in three primary care centres. RT-PCR was performed in paired nasopharyngeal swabs (NPS) and saliva samples collected from outpatients with a broad clinical spectrum of illness. To assess differences in collection methods, saliva specimens were obtained in a different way in each of the participating centres: supervised collection (SVC), oropharyngeal washing (OPW) and self-collection (SC). Results: NPS and saliva pairs of samples from 577 patients (median age 39 years, 44% men, 42% asymptomatic) were collected and tested, and 120 (20.8%) gave positive results. The overall agreement with NPS and kappa coefficients (κ) for SVC, OPW and SC were 95% (κ=0.85), 93.4% (κ=0.76), and 93.3% (κ=0.76), respectively. The sensitivity (95% CI) of the saliva specimens varied from 86% (72.6-93.7) for SVC to 66.7% (50.4-80) for SC samples. The sensitivity was higher in samples with lower cycle threshold (Ct) values. The best performance of RT-PCR was observed for SVC, with sensitivity (95% CI) for Ct values ≤32 of 97% (82.5-99.8) in symptomatic, and 88.9% (50.7-99.4) in asymptomatic individuals. Conclusions: Saliva is an acceptable specimen for the detection of SARS-CoV-2 in the community setting. Specimens collected under supervision perform comparably to NPS and can effectively identify individuals with higher risk of transmission in real life conditions.

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Background Negative urine cultures to rule out urinary tract infections (UTI) generate a considerable laboratory workload; thus, a rapid screening test is desirable. We evaluated the performance of a new automated microscopy analyzer, cobas u 701 (Roche Diagnostics International, Rotkreuz, Switzerland) for the screening of UTI, and developed a rule-out strategy to reduce the number of samples requiring culture. We also assessed squamous epithelial cell (SEC) count as a predictor of culture contamination. Methods In total, 1,604 urine samples from outpatients were analyzed with cobas u 701 and culture. Bacterial (BAC) and white blood cell (WBC) counts were used for sample interpretation. To determine a useful cut-off point to predict negative cultures, we selected the highest sensitivity and specificity values obtained from ROC curves. Diagnostic accuracy by age and gender was evaluated. Results Urine culture showed growth of ≥10 4 colony forming units (CFU)/mL in 256 samples (16.0%). The highest sensitivity (91.8%) and specificity (68.4%) were obtained for cut-off points of 119 BAC/µL and 22 WBC/µL. The combination of BAC and WBC improved the performance of the rule-out strategy with a low rate of false-negative results (1.5%) and a high negative predictive value (NPV, 97.3%). Fifty-seven percent of the samples would not have required culture. SEC count was a poor predictor of culture contamination. Conclusions cobas u 701 can substantially reduce the number of urine samples requiring culture, with a low false-negative rate and a high NPV.

The inadequate formation of software project teams is a problem that affects the software industry worldwide. The team formation process becomes very complex when taking into account several factors such as, assigning team roles to people with the right competences, consideration of incompatibilities between the members and workload, among others. This situation becomes more complex in medium and large organizations due to the large number of combinations of possible assignments. This stage becomes virtually impossible to address efficiently without the aid of mathematical models. These models represent the problem to be solved as objectively as possible. This paper takes as its antecedent a model that includes both individual and team factors which proposes to maximize the competence of workers, minimize incompatibilities between team members and balance the workload. An expanded version of the model includes the minimization of cost associated to the development software remotely. The model used corresponds to a multiobjective combinatorial optimization problem. To solve this problem multiobjective variants of metaheuristic algorithms such as Tabu Search, Simulated Annealing and Hill Climbing were used. The experimental study conducted has led to the identification of various algorithms which produced the best results for this problem. The algorithms identified are: Multi-case Multiobjective Simulated Annealing, and multiobjective variants of Hill Climbing Algorithms such as Multiobjective Stochastic Hill Climbing, Multiobjective Hill Climbing by Greater Distance and Multiobjective Hill Climbing with Restart. Resumen La inadecuada conformación de equipos de proyecto de software es un problema que afecta a la industria de software a nivel mundial. Este proceso resulta complejo, teniendo en cuenta que debe considerar varios factores, como son, asignar a los roles del equipo las personas con las competencias apropiadas, considerar las incompatibilidades entre los miembros y la carga de trabajo, entre otros. Esta situación se torna más compleja en organizaciones medianas y grandes, debido a la gran cantidad de combinaciones de asignaciones posibles, por lo que esta etapa es prácticamente imposible de abordar de manera eficiente, sin la ayuda de modelos matemáticos que representen el problema a resolver lo más objetivamente posible. Este trabajo toma como antecedente un modelo que incluye tanto factores individuales como factores de equipo y plantea: maximizar las competencias de los trabajadores, minimizar las incompatibilidades entre los miembros del equipo y balancear la carga de trabajo. Incluye además, en una versión ampliada del modelo, minimizar el costo de desarrollar software a distancia. El modelo citado responde a un problema de optimización combinatorio multiobjetivo, por lo que para su solución se utilizaron algunas variantes multiobjetivo de los algoritmos metaheurísticos: Búsqueda Tabú, Recocido Simulado y Escalador de Colinas. El estudio experimental realizado ha llevado a identificar que las varian...

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The inadequate formation of software project teams is a problem that affects the software industry worldwide. The team formation process becomes very complex when taking into account several factors such as, assigning team roles to people with the right competences, consideration of incompatibilities between the members and workload, among others. This situation becomes more complex in medium and large organizations due to the large number of combinations of possible assignments. This stage becomes virtually impossible to address efficiently without the aid of mathematical models. These models represent the problem to be solved as objectively as possible. This paper takes as its antecedent a model that includes both individual and team factors which proposes to maximize the competence of workers, minimize incompatibilities between team members and balance the workload. An expanded version of the model includes the minimization of cost associated to the development software remotely. The model used corresponds to a multiobjective combinatorial optimization problem. To solve this problem multiobjective variants of metaheuristic algorithms such as Tabu Search, Simulated Annealing and Hill Climbing were used. The experimental study conducted has led to the identification of various algorithms which produced the best results for this problem. The algorithms identified are: Multi-case Multiobjective Simulated Annealing, and multiobjective variants of Hill Climbing Algorithms such as Multiobjective Stochastic Hill Climbing, Multiobjective Hill Climbing by Greater Distance and Multiobjective Hill Climbing with Restart.Resumen La inadecuada conformación de equipos de proyecto de software es un problema que afecta a la industria de software a nivel mundial. Este proceso resulta complejo, teniendo en cuenta que debe considerar varios factores, como son, asignar a los roles del equipo las personas con las competencias apropiadas, considerar las incompatibilidades entre los miembros y la carga de trabajo, entre otros. Esta situación se torna más compleja en organizaciones medianas y grandes, debido a la gran cantidad de combinaciones de asignaciones posibles, por lo que esta etapa es prácticamente imposible de abordar de manera eficiente, sin la ayuda de modelos matemáticos que representen el problema a resolver lo más objetivamente posible. Este trabajo toma como antecedente un modelo que incluye tanto factores individuales como factores de equipo y plantea: maximizar las competencias de los trabajadores, minimizar las incompatibilidades entre los miembros del equipo y balancear la carga de trabajo. Incluye además, en una versión ampliada del modelo, minimizar el costo de desarrollar software a distancia. El modelo citado responde a un problema de optimización combinatorio multiobjetivo, por lo que para su solución se utilizaron algunas variantes multiobjetivo de los algoritmos metaheurísticos: Búsqueda Tabú, Recocido Simulado y Escalador de Colinas. El estudio experimental realizado ha llevado a identificar que las...