Rationale: Symptoms and respiratory function tests may be difficult to assess and interpret in obese patients with asthma, particularly if the asthma is severe. It is unclear whether the dynamic changes that occur during bronchoconstriction differ between obese versus nonobese patients with asthma.
Objectives: To explore whether the changes in airway caliber and lung volumes that occur with acute bronchoconstriction are different in obese and nonobese patients with asthma and whether any differences contribute to the quality and intensity of symptoms.
Methods: Thirty female patients with asthma were studied. Spirometry, lung volume measurements, and dyspnea scores were obtained before and immediately after bronchoconstriction induced by methacholine, aiming to provoke a reduction in FEV1 of 30%.
Measurements And Main Results: Body mass index was independently associated with changes in lung volume after adjustment for baseline airway caliber and hyperresponsiveness. Increases in functional residual capacity and decreases in inspiratory capacity were significantly greater in obese participants (P < 0.001 and P = 0.003, respectively).
Conclusions: Changes in respiratory function, notably dynamic hyperinflation, are greater in obese individuals with bronchoconstriction. This may potentially alter the perception and assessment of asthma severity in obese patients with asthma.
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http://dx.doi.org/10.1164/rccm.200711-1738OC | DOI Listing |
J Asthma
January 2025
School of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China.
Background: Studies have suggested associations between montelukast and increased risks of sleep disorders, including overall sleeping problems and insomnia. However, the results of observational studies are not consistent. Understanding these associations is crucial, particularly in patients solely diagnosed with allergic rhinitis, where montelukast use remains prevalent.
View Article and Find Full Text PDFIntroductionAsthma attacks are set off by triggers such as pollutants from the environment, respiratory viruses, physical activity and allergens. The aim of this research is to create a machine learning model using data from mobile health technology to predict and appropriately warn a patient to avoid such triggers.MethodsLightweight machine learning models, XGBoost, Random Forest, and LightGBM were trained and tested on cleaned asthma data with a 70-30 train-test split.
View Article and Find Full Text PDFPEC Innov
June 2025
Department of Respiratory Medicine, Royal Devon and Exeter Hospital, University of Exeter, Exeter, United Kingdom.
Objective: To assess the feasibility and acceptability of adapting a psychoeducation course (Body Reprogramming) for severe asthma and finding suggestions for improvement.
Methods: Severe asthma patients were recruited from a single centre and enrolled in an online group-based course. Each course consisted of four sessions: introduction to BR, stress, exercise, and diet.
Cureus
December 2024
Obstetrics and Gynecology, Cape Fear Valley Health, Fayetteville, USA.
Pelvic masses in women can originate from both gynecological and non-gynecological sources, necessitating careful evaluation to ensure appropriate treatment. Gynecological masses can range from functional ovarian cysts and tubo-ovarian abscesses to malignant and benign tumors. This case report presents a mucinous borderline ovarian tumor (BOT), a rare type of ovarian neoplasm.
View Article and Find Full Text PDFRev Med Liege
January 2025
Service de Pneumologie, CHU Liège, Belgique.
Asthma is a common respiratory disease, accounting for 3 to 10 % of severe cases. Among these, bronchiectasis is more frequent (prevalence between 15.5 % and 67.
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