Objective: We sought to study the effects of gestational age and maternal position on peak expiratory flow rates.
Methods: Peak expiratory flow rates were measured in the standing, sitting, and supine positions in 38 healthy pregnant women at 4-week intervals starting at less than 10 weeks until delivery and again at 6 weeks postpartum. The highest reading of 3 consecutive peak expiratory flow rate measurements for each encounter and position was used in the analysis. Repeated measures analysis of covariance was performed with subjects, gestational age, position, and gestational age times position as the model effects. Least squares mean peak expiratory flow rates were compared among positions at different gestation ages using Bonferroni-adjusted least significant difference t tests.
Results: Peak expiratory flow rate declined significantly throughout gestation in all positions (P < .001) with mean rate of decline of 0.65 L/min per week). The slopes of linear trends were not statistically different between positions (P = .222). However, the rate of decline for the supine position was higher than for standing and sitting positions (0.86 compared with 0.46 and 0.57 L/min per week), respectively. On average, the postpartum peak expiratory flow rate returned to 71.9% of its measurement in early gestation. Nomograms depicting mean and the 5th and 95th percentiles of peak expiratory flow rates were constructed for each position.
Conclusion: Peak expiratory flow rate measurements are affected by maternal position and advancing gestational age, especially in the supine position. Adjustment of patient's flow rate in relation to gestational age and maternal position is recommended, especially in pregnant women with asthma.
Level Of Evidence: III.
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http://dx.doi.org/10.1097/01.AOG.0000152303.80103.69 | DOI Listing |
Alzheimers Dement
December 2024
University of Minnesota, Minneapolis, MN, USA.
Background: With the emerging role of the blood biomarkers in Alzheimer's Disease (AD) clinical practice and trials, it is crucial to identify and address factors influencing the concentrations of these biomarkers in circulation for enhanced clinical utility. We aim to assess the impact of lung function on plasma AD biomarker levels and elucidate the relationship between lung function and Alzheimer's Disease and Related Dementias (ADRD).
Method: We used the Peak Expiratory Flow (PEF), plasma biomarkers of AD (Amyloid beta 42/40 (Aβ42/40) ratio, phosphorylated-tau181 (p-tau181), Neurofilament light chain (NfL) and Glial fibrillary acidic protein (GFAP)) measured in the Health and Retirement Study (HRS) 2016 survey participants (n = 3801) and incident dementia (n = 142) over 4 years.
Alzheimers Dement
December 2024
Centre for Brain Research, Indian Institute of Science, Bangalore, Karnataka, India.
Background: Pulmonary Function Tests (PFTs) are the non-invasive tests to measure the lung function. Relationship between pulmonary function and cognition is an emerging area of research, understanding this is crucial for prevention and management of dementia. Hence this study aims to investigate the association between pulmonary function and cognition.
View Article and Find Full Text PDFJ Indian Prosthodont Soc
January 2025
Department of Dental Materials, Vishnu Dental College, Bhimavaram, Andhra Pradesh, India.
Aim: This study aimed to evaluate the effect of partially edentulous ()PED condition on lung function through spirometry tests and comparison of airflow rates between dentulous and PED subjects.
Settings And Design: The study design was a cross-sectional study conducted in the department of prosthodontics.
Materials And Methods: Twenty-eight dentulous and 28 PED patients with an age range of 25-50 years were included in the study.
Sci Rep
December 2024
Peking University School of Nursing, 38 Xueyuan Road, Haidian District, Beijing, China.
This study examined the effect of obesity on lung ventilation function in middle-aged and older adults using data from the China Health and Retirement Longitudinal Study. Lung function was measured using peak expiratory flow, and obesity was assessed using waist circumference and body mass index (BMI). Logistic regression and the bivariate logit model were applied to analyze the data.
View Article and Find Full Text PDFBackground: Frailty in older adults is linked to increased risks and lower quality of life. Pre-frailty, a condition preceding frailty, is intervenable, but its determinants and assessment are challenging. This study aims to develop and validate an explainable machine learning model for pre-frailty risk assessment among community-dwelling older adults.
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