Hoarseness Among Young Children in Day-Care Centers

BackgroundChronic respiratory symptoms among toddlers are assumed to be due to allergies and common respiratory infections. Because symptoms and respiratory disease in this age group often continue on to school age and later life, it is important to know the possible risk factors for prevention of the chronic hoarseness.AimWe aimed to determine the current prevalence of hoarseness and other chronic respiratory symptoms among toddlers and young children. Another aim was to examine the risk factors for hoarseness in the building environments of day-care centers (DCC).MaterialAn electronic symptom survey was sent to all parents of children in day-care centers of a large city in southern Finland. In all, 3721 individuals completed the questionnaire (38%), 53.4% were the parents of boys and 46.6% girls.ResultsThe prevalence of hoarseness was 5.6%. The boy's parents reported hoarseness more often than the girls, but no significant difference was observed. Risk factors for hoarseness in a built environment in this age group were noise, visible dust and dirt, mold and a cellar like odor, a sewer smell, other unpleasant smells, stuffiness of the indoor air, a too high or too low temperatures, a cold floor, insufficient ventilation, the age of the DCC building, and wood as the bearing construction of the building. The lifestyle factors that correlated with the prevalence of hoarseness were the amount of time spent outdoors; however, passive smoking, the number of siblings and pets at home did not correlate with hoarseness. Hoarseness was significantly correlated with other chronic respiratory symptoms such as rhinitis, coughs, eye irritation, tiredness, headaches, and stomach problems and also with the regular or periodic use of medication. Hoarseness was also significantly correlated with asthma and allergic rhinitis and also with repeated infections, such as a common cold, cold with a fever, laryngitis, otitis media and acute bronchitis, but not with tonsillitis or pneumonia.When potential confounders had been controlled for with a logistic regression model, the following risk factors in the built environment remained statistically significant: noise, high room temperature, insufficient ventilation and the stuffiness of the indoor air, a solvent odor, wood as the bearing construction and the age of the building.ConclusionsWe conclude that in day-care centers, buildings should be maintained, cleaned and ventilated properly. Concrete and brick used in the construction were protective compared with wood. The acoustic environment should be planned to reduce noise indoors and solvent based chemicals should be avoided. Neither having pets at home or the number of siblings were risk factors, but they were also not found to be protective in this material. All measures that reduce the occurrence of respiratory infections probably also reduce chronic voice problems.</p

Pregnancy and delivery outcomes of HIV infected women in Switzerland 2003-2008

Objective: Rates of vertical HIV transmission between mother and child are low, allowing many HIV positive women to have children with near impunity. In this study, data from the Swiss Mother and Child HIV Cohort Study were used to describe maternal characteristics and their association with pregnancy outcomes in HIV positive women. Study design: HIV positive women were followed prospectively during their pregnancies and deliveries by anonymous questionnaires between January 2003 and October 2008. Adverse pregnancy outcomes included preterm delivery, preeclampsia and gestational diabetes mellitus. Results: This study included 266 HIV positive women, of which 67 (25.2%) were first diagnosed with HIV during pregnancy. Thirty percent (n=80) of the women had pregnancy complications after 24weeks of gestation. Preterm delivery was noted in 72 (27%) patients. Other complications included preeclampsia (n=7; 2.6%) and gestational diabetes (n=7; 2.6%). Older maternal age was the only risk factor associated with adverse pregnancy outcomes (adjusted odds ratio: 1.06, 95% confidence interval 1.01-1.12, P=0.02). Conclusions: HIV positive women, especially with advanced maternal age, have high-risk pregnancies and should be monitored as in an interdisciplinary setting. The preponderance of initial HIV diagnosis during pregnancy confirms the importance of HIV screening in pregnant wome

Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation

Pregnancy is a unique time when many mothers gain awareness of their lifestyle and its impacts on the fetus. High-quality care during pregnancy is needed to identify possible complications early and ensure the mother's and her unborn baby's health and well-being. Different studies have thus far proposed maternal health monitoring systems. However, they are designed for a specific health problem or are limited to questionnaires and short-term data collection methods. Moreover, the requirements and challenges have not been evaluated in long-term studies. Maternal health necessitates a comprehensive framework enabling continuous monitoring of pregnant women. In this paper, we present an Internet-of-Things (IoT)-based system to provide ubiquitous maternal health monitoring during pregnancy and postpartum. The system consists of various data collectors to track the mother's condition, including stress, sleep, and physical activity. We carried out the full system implementation and conducted a real human subject study on pregnant women in Southwestern Finland. We then evaluated the system's feasibility, energy efficiency, and data reliability. Our results show that the implemented system is feasible in terms of system usage during nine months. We also indicate the smartwatch, used in our study, has acceptable energy efficiency in long-term monitoring and is able to collect reliable photoplethysmography data. Finally, we discuss the integration of the presented system with the current healthcare system

Personalized Maternal Sleep Quality Assessment: An Objective IoT-based Longitudinal Study

Sleep is a composite of physiological and behavioral processes that undergo substantial changes during and after pregnancy. These changes might lead to sleep disorders and adverse pregnancy outcomes. Several studies have investigated this issue; however, they were restricted to subjective measurements or short-term actigraphy methods. This is insufficient for a longitudinal maternal sleep quality evaluation. A longitudinal study a) requires a long-term data collection approach to acquire data from everyday routines of mothers and b) demands a sleep quality assessment method exploiting a large volume of multivariate data to assess sleep adaptations and overall sleep quality. In this paper, we present an Internet-of-Things based long-term monitoring system to perform an objective sleep quality assessment. We conduct longitudinal monitoring where 20 pregnant mothers are remotely monitored for six months of pregnancy and one month postpartum. To evaluate sleep quality adaptations, we a) extract several sleep attributes and study their variations during the monitoring and b) propose a semi-supervised machine learning approach to create a personalized sleep model for each subject. The model provides an abnormality score which allows an explicit representation of the sleep quality in a clinical routine, reflecting possible sleep quality degradation with respect to her own data. Sleep data of 13 participants (out of 20) are included in our analysis, as their data are adequate for the study, including 172.15 ± 33.29 days of sleep data per person. Our fine-grained objective measurements indicate the sleep duration and sleep efficiency are deteriorated in pregnancy and notably in postpartum. In comparison to the mid of the second trimester, the sleep model indicates the increase of sleep abnormality at the end of pregnancy (2.87 times) and postpartum (5.62 times). We also show the model enables individualized and effective care for sleep disturbances during pregnancy, as compared to a baseline method.</p

A comprehensive accuracy assessment of Samsung smartwatch heart rate and heart rate variability

Background: Photoplethysmography (PPG) is a low-cost and easy-to-implement method to measure vital signs, including heart rate (HR) and pulse rate variability (PRV) which widely used as a substitute of heart rate variability (HRV). The method is used in various wearable devices. For example, Samsung smartwatches are PPG-based open-source wristbands used in remote well-being monitoring and fitness applications. However, PPG is highly susceptible to motion artifacts and environmental noise. A validation study is required to investigate the accuracy of PPG-based wearable devices in free-living conditions.Objective: We evaluate the accuracy of PPG signals-collected by the Samsung Gear Sport smartwatch in free-living conditions-in terms of HR and time-domain and frequency-domain HRV parameters against a medical-grade chest electrocardiogram (ECG) monitor.Methods: We conducted 24-hours monitoring using a Samsung Gear Sport smartwatch and a Shimmer3 ECG device. The monitoring included 28 participants (14 male and 14 female), where they engaged in their daily routines. We evaluated HR and HRV parameters during the sleep and awake time. The parameters extracted from the smartwatch were compared against the ECG reference. For the comparison, we employed the Pearson correlation coefficient, Bland-Altman plot, and linear regression methods.Results: We found a significantly high positive correlation between the smartwatch's and Shimmer ECG's HR, time-domain HRV, LF, and HF and a significant moderate positive correlation between the smartwatch's and shimmer ECG's LF/HF during sleep time. The mean biases of HR, time-domain HRV, and LF/HF were low, while the biases of LF and HF were moderate during sleep. The regression analysis showed low error variances of HR, AVNN, and pNN50, moderate error variances of SDNN, RMSSD, LF, and HF, and high error variances of LF/HF during sleep. During the awake time, there was a significantly high positive correlation of AVNN and a moderate positive correlation of HR, while the other parameters indicated significantly low positive correlations. RMSSD and SDNN showed low mean biases, and the other parameters had moderate mean biases. In addition, AVNN had moderate error variance while the other parameters indicated high error variances.Conclusion: The Samsung smartwatch provides acceptable HR, time-domain HRV, LF, and HF parameters during sleep time. In contrast, during the awake time, AVNN and HR show satisfactory accuracy, and the other HRV parameters have high errors.</p

Presence Of A Congenitally Bicuspid Aortic Valve Among Patients Having Combined Mitral And Aortic Valve Replacement

Although bicuspid aortic valve occurs in an estimated 1% of adults and mitral valve prolapse in an estimated 5% of adults, occurrence of the 2 in the same patient is infrequent. During examination of operatively excised aortic and mitral valves because of dysfunction (stenosis and/or regurgitation), we encountered 16 patients who had congenitally bicuspid aortic valves associated with various types of dysfunctioning mitral valves. Eleven of the 16 patients had aortic stenosis (AS): 5 of them also had mitral stenosis, of rheumatic origin in 4 and secondary to mitral annular calcium in 1; the other 6 with aortic stenosis had pure mitral regurgitation (MR) secondary to mitral valve prolapse in 3, to ischemia in 2, and to unclear origin in 1. Of the 5 patients with pure aortic regurgitation, each also had pure mitral regurgitation: in 1 secondary to mitral valve prolapse and in 4 secondary to infective endocarditis. In conclusion, various types of mitral dysfunction severe enough to warrant mitral valve replacement occur in patients with bicuspid aortic valves. A proper search for mitral valve dysfunction in patients with bicuspid aortic valves appears warranted. (C) 2012 Elsevier Inc. All rights reserved. (Am J Cardiol 2012;109:263-271)Integrative Biolog

Increasing carbon sinks in European forests: effect of afforestation and changes in mean growing stock volume

In Europe, both forest area and growing stock have increased since the 1950s, and European forests have acted as a carbon sink during the last six decades. However, the contribution of different factors affecting the sink is not yet clear. In this study, historical inventory data were combined with land-use modelling data to reconstruct the development of forest area and age-structure between 1950 and 2010 without afforestation in two case study countries, Finland and the Czech Republic. These reconstructions were then used in a scenario analysis to assess the effects of afforestation, development of mean growing stock volume and age structure of forests on the forest biomass carbon stock. The results show that afforestation has affected the development of the mean age of forests, but has not changed its trend. There have been large increases in the mean volume of growing stock over the study period in both countries; the increase has occurred both in younger and older age-classes, and in both coniferous and broadleaved species. As not many countries have sufficiently detailed inventory data available for such analysis, the presented case studies are valuable in demonstrating that these changes occurred under very different circumstances. In both countries, the increase in the mean volume of growing stock has been the dominant factor explaining the increase in the forest biomass carbon stock compared with the effect of afforestation