Thermal and cardiorespiratory newborn adaptations during hot tub bath

Objective: To evaluate thermal and cardiorespiratory adaptation during hot tub bath and shower in healthy newborns in the first hours of life. Study design: This is a randomized blind controlled trial, registered in ReBEC (No. RBR-4z26f3) with 184 newborns divided into hot tub group (n=84) and shower (n=100). Newborns from intervention group were immersed in a hot tub with warm water up to the neck, without exposure to air flow, and control group received traditional shower. Heart rate, respiratory rate and temperature were measured before and immediately after bath by an investigator blinded to the type of bath. Results: Groups were similar in gender, gestational age, birth weight, Apgar score at 5th minute and hours of life, p => 0.05. To analyze thermal and cardiorespiratory adjustments, difference between post-bath variables and pre-bath was calculated. In this analysis, it was found statistically significant difference between two types of bath regarding heart rate, respiratory rate and temperature. Hot tub bath decreases heart and respiratory rates and increases temperature, whereas shower provides the opposite effect (0.0001). Conclusion: This study demonstrates that hot tub baths and shower, in healthy newborns, promote thermal and cardiorespiratory adaptations, reflecting thermal, cardiac and respiratory positive reactions after hot tub bath

Spectrochemical analysis in blood plasma combined with subsequent chemometrics for fibromyalgia detection

Fibromyalgia is a rheumatologic condition characterized by multiple and chronic body pain, and other typical symptoms such as intense fatigue, anxiety and depression. It is a very complex disease where treatment is often made by non-medicated alternatives in order to alleviate symptoms and improve the patient’s quality of life. Herein, we propose a method to detect patients with fibromyalgia (n = 252, 126 controls and 126 patients with fibromyalgia) through the analysis of their blood plasma using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy in conjunction with chemometric techniques, hence, providing a low-cost, fast and accurate diagnostic approach. Different chemometric algorithms were tested to classify the spectral data; genetic algorithm with linear discriminant analysis (GA-LDA) achieved the best diagnostic results with a sensitivity of 89.5% in an external test set. The GA-LDA model identified 24 spectral wavenumbers responsible for class separation; amongst these, the Amide II (1,545 cm−1) and proteins (1,425 cm−1) were identified to be discriminant features. These results reinforce the potential of ATR-FTIR spectroscopy with multivariate analysis as a new tool to screen and detect patients with fibromyalgia in a fast, low-cost, non-destructive and minimally invasive fashion