Severe perineal lacerations were associated with operative delivery, primiparity, gestational age, and epidural anesthesia. Episiotomy was not protective.

BackgroundElectronic health (eHealth) interventions may improve the quality of care by providing timely, accessible information about one patient or an entire population. Electronic patient care information forms the nucleus of computerized health information systems. However, interoperability among systems depends on the adoption of information standards. Additionally, investing in technology systems requires cost-effectiveness studies to ensure the sustainability of processes for stakeholders.ObjectiveThe objective of this study was to assess cost-effectiveness of the use of electronically available inpatient data systems, health information exchange, or standards to support interoperability among systems.MethodsAn overview of systematic reviews was conducted, assessing the MEDLINE, Cochrane Library, LILACS, and IEEE Library databases to identify relevant studies published through February 2016. The search was supplemented by citations from the selected papers. The primary outcome sought the cost-effectiveness, and the secondary outcome was the impact on quality of care. Independent reviewers selected studies, and disagreement was resolved by consensus. The quality of the included studies was evaluated using a measurement tool to assess systematic reviews (AMSTAR).ResultsThe primary search identified 286 papers, and two papers were manually included. A total of 211 were systematic reviews. From the 20 studies that were selected after screening the title and abstract, 14 were deemed ineligible, and six met the inclusion criteria. The interventions did not show a measurable effect on cost-effectiveness. Despite the limited number of studies, the heterogeneity of electronic systems reported, and the types of intervention in hospital routines, it was possible to identify some preliminary benefits in quality of care. Hospital information systems, along with information sharing, had the potential to improve clinical practice by reducing staff errors or incidents, improving automated harm detection, monitoring infections more effectively, and enhancing the continuity of care during physician handoffs.ConclusionsThis review identified some benefits in the quality of care but did not provide evidence that the implementation of eHealth interventions had a measurable impact on cost-effectiveness in hospital settings. However, further evidence is needed to infer the impact of standards adoption or interoperability in cost benefits of health care; this in turn requires further research.

BackgroundCurrent methods to assess the gestational age during prenatal care or at birth are a global challenge. Disadvantages, such as low accessibility, high costs, and imprecision of clinical tests and ultrasonography measurements, may compromise health decisions at birth, based on the gestational age. Newborns’ organs and tissues can indirectly indicate their physical maturity, and we hypothesized that evolutionary changes in their skin, detected using an optoelectronic device meter, may aid in estimating the gestational age. This study analyzed the feasibility of using newborn skin reflectance to estimate the gestational age at birth noninvasively.Methods and findingsA cross-sectional study evaluated the skin reflectance of selected infants, preferably premature, at birth. The first-trimester ultrasound was the reference for gestational age. A prototype of a new noninvasive optoelectronic device measured the backscattering of light from the skin, using a light emitting diode at wavelengths of 470 nm, 575 nm, and 630 nm. Univariate and multivariate regression analysis models were employed to predict gestational age, combining skin reflectance with clinical variables for gestational age estimation. The gestational age at birth of 115 newborns from 24.1 to 41.8 weeks of gestation correlated with the light at 630 nm wavelength reflectance 3.3 mm/6.5 mm ratio distant of the sensor, at the forearm and sole (Pearson’s correlation = 0.505, P < 0.001 and 0.710, P < 0.001, respectively). The best-combined variables to predict the gold standard gestational age at birth was the skin reflectance at wavelengths of 630 nm and 470 nm in combination with birth weight, phototherapy, and adjusted to include incubator stay, and sex (R2 = 0.828, P < 0.001). The main limitation of the study is that it was very specific to the premature population we studied and needs to be studied in a broader spectrum of newborns.ConclusionsA novel automated skin reflectometer device, in combination with clinical variables, was able to predict the gestational age and could be useful when the information is in doubt or is unknown. Multivariable predictive models associated the skin reflectance with easy to obtain clinical parameters, at the birth scenario. External validation needs to be proven in an actual population with the real incidence of premature infants.

Abstract-Neurological findings in preeclampsia fulfill diagnostic criteria of posterior reversible encephalopathy syndrome (PRES), which is related to cerebral autoregulation impairment associated with high blood pressure. In preeclampsia, PRES may occur without a significant increase in blood pressure.

Background No treatment for COVID-19 is yet available; therefore, providing access to information about SARS-CoV-2, the transmission route of the virus, and ways to prevent the spread of infection is a critical sanitary measure worldwide. Serious games have advantages in the dissemination of reliable information during the pandemic; they can provide qualified content while offering interactivity to the user, and they have great reach over the internet. Objective This study aimed to develop a serious game with the purpose of providing science-based information on the prevention of COVID-19 and personal care during the pandemic while assessing players’ knowledge about COVID-19–related topics. Methods The study was conducted with the interdisciplinary collaboration of specialists in health sciences, computing, and design at the Federal University of Minas Gerais, Brazil. The health recommendations were grouped into six thematic blocks, presented in a quiz format. The software languages were based on the progressive web app development methodology with the Ionic framework, JavaScript, HTML5, cascading style sheets, and TypeScript (Angular). Open data reports of how users interact with the serious game were obtained using the Google Analytics application programming interface. The visual identity, logo, infographics, and icons were carefully developed by considering a selection of colors, typography, sounds, and images that are suitable for young audiences. Cards with cartoon characters were introduced at the end of each thematic topic to interact with the player, reinforcing their correct answers or alerting them to the need to learn more about the disease. The players’ performance was assessed by the rate of incorrect and correct answers and analyzed by linear correlation coefficient over 7 weeks. The agile SCRUM development methodology enabled quick and daily interactions of developers through a webchat and sequential team meetings. Results The game “COVID-19–Did You Know?” was made available for free on a public university website on April 1, 2020. The game had been accessed 17,571 times as of September 2020. Dissemination actions such as reports on social media and television showed a temporal correspondence with the access number. The players’ error rate in the topic “Mask” showed a negative trend (r=–.83; P=.01) over the weeks of follow-up. The other topics showed no significant trend over the weeks. Conclusions The gamification strategy for health education content on the theme of COVID-19 reached a young audience, which is considered to be a priority in the strategy of orientation toward social distancing. Specific educational reinforcement measures were proposed and implemented based on the players’ performance. The improvement in the users’ performance on the topic about the use of masks may reflect an increase in information about or adherence to mask use over time.

BackgroundNew methodologies to estimate gestational age (GA) at birth are demanded to face the limited access to obstetric ultrasonography and imprecision of postnatal scores. The study analyzed the correlation between neonatal skin thickness and pregnancy duration. Secondarily, it investigated the influence of fetal growth profiles on tissue layer dimensions.Methods and findingsIn a feasibility study, 222 infants selected at a term-to-preterm ratio of 1:1 were assessed. Reliable information on GA was based on the early ultrasonography-based reference. The thicknesses of the epidermal and dermal skin layers were examined using high-frequency ultrasonography. We scanned the skin over the forearm and foot plantar surface of the newborns. A multivariate regression model was adjusted to determine the correlation of GA with skin layer dimensions. The best model to correlate skin thickness with GA was fitted using the epidermal layer on the forearm site, adjusted to cofactors, as follows: Gestational age (weeks) = −28.0 + 12.8 Ln (Thickness) − 4.4 Incubator staying; R2 = 0.604 (P<0.001). In this model, the constant value for the standard of fetal growth was statistically null. The dermal layer thickness on the forearm and plantar surfaces had a negative moderate linear correlation with GA (R = −0.370, P<0.001 and R = −0.421, P<0.001, respectively). The univariate statistical analyses revealed the influence of underweight and overweight profiles on neonatal skin thickness at birth. Of the 222 infants, 53 (23.9%) had inappropriate fetal growths expected for their GA. Epidermal thickness was not fetal growth standard dependent as follows: 172.2 (19.8) μm for adequate for GA, 171.4 (20.6) μm for SGA, and 177.7 (15.2) μm for LGA (P = 0.525, mean [SD] on the forearm).ConclusionsThe analysis highlights a new opportunity to relate GA at birth to neonatal skin layer thickness. As this parameter was not influenced by the standard of fetal growth, skin maturity can contribute to clinical applications.

These results indicate that PlGF is related to MAP in pregnant women.

The main cause of admission was a decisive factor for maternal survival in the obstetric ICU. Direct obstetric complications had a better prognosis.