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Virtual microscopy (VM) is a widely used teaching method in Medical Education in many developed countries. In Brazil, however, this is not the case for most medical schools, considering Brazilian social inequality and uneven access to technology. Recently, the Covid-19 pandemic has also challenged Universities to seek and make a transition toward more effective methods of full-time online education. Thus, the main goal of this work was to verify student's perception and academic performance, assessed upon VM implementation in a Brazilian Medical School. Ribeirao Preto Medical School students answered a 26-question survey with regards to optical microscopy (OM) and VM. Academic performance was compared between participants that were (year of 2019) or were not (year of 2015) exposed to VM. Taken the results together, subjective impressions such as handling, suitability, learning effectiveness, and pleasure using the tools, have shown a higher score for virtual microscopy (median = 29), when compared to optical microscopy (median = 24) with a P-value < 0.001 by Wilcoxon rank test, upon measurement using an ordinal scale. Regarding academic performance, no statistically significant differences were found between groups (P-value = 0.38, Cohen's d = 0.19). Therefore, VM proved to be adequate to the Brazilian medical education in light of Brazilian social contexts and Covid-19 pandemic.

Objective: The purposeof this study was to compare the physical activity of pregnant women with and without gestational diabetes mellitus regarding the physical activity domains and to verify possible associations between socio-demographic characteristics, nutritional status, and lifestyle with gestational diabetes. Design /Methods: Consists in a study including 798 adult pregnant women attended by the Unique Health System in Ribeirão Preto, Brazil from 2011 to 2012. The variables studied were recorded using questionnaires, as well as frequency (weekly), duration (minutes) and the metabolic equivalent. The frequency of the categorical variables and the mean and standard deviation (SD) of the continuous variables were calculated and the Mann Whitney test, Student’s t test and the X²test calculated the differences of the study variables according to the presence of diabetes. The adopted significance level was α = 5%. Results:Indicate that pregnant women with diabetes have lower average energy expenditure in the physical activity domains. However, we found a significant difference between groups regarding the average energy expenditure related to the occupational domain. Considering the Physical Activity (PA) pattern, we found that the sedentary percentage was higher in both groups. However, there were no relevant differences between them. The variables: previously diabetes, nutritional status, pre-gestational and current body mass index were associated with the development of diabetes. Conclusion: Further studies are needed to explore physical activities in different domains in pregnancy and its relationship with gestational diabetes, especially in the occupational domain. [ABSTRACT FROM AUTHOR]

Background Escalation in the global rates of labour interventions, particularly cesarean section and oxytocin augmentation, has renewed interest in a better understanding of natural labour progression. Methodological advancements in statistical and computational techniques addressing the limitations of pioneer studies have led to novel findings and triggered a re-evaluation of current labour practices. As part of the World Health Organization's Better Outcomes in Labour Difficulty (BOLD) project, which aimed to develop a new labour monitoring-to-action tool, we examined the patterns of labour progression as depicted by cervical dilatation over time in a cohort of women in Nigeria and Uganda who gave birth vaginally following a spontaneous labour onset. Methods and findings This was a prospective, multicentre, cohort study of 5,606 women with singleton, vertex, term gestation who presented at [less than or equal to] 6 cm of cervical dilatation following a spontaneous labour onset that resulted in a vaginal birth with no adverse birth outcomes in 13 hospitals across Nigeria and Uganda. We independently applied survival analysis and multistate Markov models to estimate the duration of labour centimetre by centimetre until 10 cm and the cumulative duration of labour from the cervical dilatation at admission through 10 cm. Multistate Markov and nonlinear mixed models were separately used to construct average labour curves. All analyses were conducted according to three parity groups: parity = 0 (n = 2,166), parity = 1 (n = 1,488), and parity = 2+ (n = 1,952). We performed sensitivity analyses to assess the impact of oxytocin augmentation on labour progression by re-examining the progression patterns after excluding women with augmented labours. Labour was augmented with oxytocin in 40% of nulliparous and 28% of multiparous women. The median time to advance by 1 cm exceeded 1 hour until 5 cm was reached in both nulliparous and multiparous women. Based on a 95th percentile threshold, nulliparous women may take up to 7 hours to progress from 4 to 5 cm and over 3 hours to progress from 5 to 6 cm. Median cumulative duration of labour indicates that nulliparous women admitted at 4 cm, 5 cm, and 6 cm reached 10 cm within an expected time frame if the dilatation rate was [greater than or equal to] 1 cm/hour, but their corresponding 95th percentiles show that labour could last up to 14, 11, and 9 hours, respectively. Substantial differences exist between actual plots of labour progression of individual women and the 'average labour curves' derived from study population-level data. Exclusion of women with augmented labours from the study population resulted in slightly faster labour progression patterns. Conclusions Cervical dilatation during labour in the slowest-yet-normal women can progress more slowly than the widely accepted benchmark of 1 cm/hour, irrespective of parity. Interventions to expedite labour to conform to a cervical dilatation threshold of 1 cm/hour may be inappropriate, especially when applied before 5 cm in nulliparous and multiparous women. Averaged labour curves may not truly reflect the variability associated with labour progression, and their use for decision-making in labour management should be de-emphasized., Author(s): Olufemi T. Oladapo 1,*, Joao Paulo Souza 1, Bukola Fawole 2, Kidza Mugerwa 3, Gleici Perdoná 4, Domingos Alves 4, Hayala Souza 4, Rodrigo Reis 4, Livia Oliveira-Ciabati 4, [...]

This paper aims to discuss the Bayesian estimation approach for the zero-inflated cure class of models, which extends the standard cure model by accommodating zero-inflated data in the survival analysis context. A comprehensive simulation study is carried out to assess the performance of the estimation procedure. A new estimation methodology is illustrated using a real dataset related to women diagnosed with invasive cervical cancer in Brazil. [ABSTRACT FROM AUTHOR]

In obstetrics and gynecology, knowledge about how women's features are associated with childbirth is important. This leads to establishing guidelines and can help managers to describe the dynamics of pregnant women's hospital stays. Then, time is a variable of great importance and can be described by survival models. An issue that should be considered in the modeling is the inclusion of women for whom the duration of labor cannot be observed due to fetal death, generating a proportion of times equal to zero. Additionally, another proportion of women's time may be censored due to some intervention. The aim of this paper was to present the Log-Normal zero-inflated cure regression model and to evaluate likelihood-based parameter estimation by a simulation study. In general, the inference procedures showed a better performance for larger samples and low proportions of zero inflation and cure. To exemplify how this model can be an important tool for investigating the course of the childbirth process, we considered the Better Outcomes in Labor Difficulty project dataset and showed that parity and educational level are associated with the main outcomes. We acknowledge the World Health Organization for granting us permission to use the dataset. [ABSTRACT FROM AUTHOR]

Doctors, nurses, and other healthcare professionals use software that affects the patients. Directly Observed Treatment, Short-course is the name given to the tuberculosis control strategy recommended by the World Health Organization. The main goal of this work is to propose a protocol for evaluating the impact of healthcare software supporting Directly Observed Treatment, Short-course on patients, healthcare professionals, and services. The proposed protocol consists of a set of instruments and steps. The instruments are reliable and validated existing questionnaires to be applied before and after using the software tool. The literature points out the need for standards on the software assessment. This is particularly critical when software affects patients directly. The present protocol is a universal tool to assess the impact of software used to support the fight against the tragedy of tuberculosis where a rigorous evaluation of IT in healthcare is highly recommended and of great importance. [ABSTRACT FROM AUTHOR]

Long-term survivor models have been extensively used for modelling time-to-event data with a significant proportion of patients who do not experience poor outcome. In this paper, we propose a new long-term survivor hazard model, which accommodates comprehensive families of cure rate models as particular cases, including modified Weibull, exponentiated Weibull, Weibull, exponential and Rayleigh distribution, among others. The maximum likelihood estimation procedure is presented. A simulation study evaluates bias and mean square error of the considered estimation procedure as well as the coverage probabilities of the parameters asymptotic and bootstrap confidence intervals. A real Brazilian dataset on breast cancer illustrates the methodology. From the practical point of view, under our modelling, we provide a parameter that works as a metric to quantify and compare the risk between different stages of the disease. We emphasize that, we developed an online platform for oncologists to calculate the probability of survival of patients diagnosed with breast cancer according to the stage of the disease in real time. [ABSTRACT FROM AUTHOR]