Objective: To investigate the effect of regular paracetamol on bronchial hyper-responsiveness (BHR) and asthma control in adult asthma.
Setting: Single research-based outpatient clinic.
Participants: 94 adults with mild-to-moderate asthma received randomised treatment; 85 completed the study. Key inclusion criteria were age 18-65 years, forced expiratory volume in 1 s (FEV1) >70% predicted, provocation concentration of methacholine causing a 20% reduction in FEV1 (PC20) between 0.125 and 16 mg/mL. Key exclusion criteria included an asthma exacerbation within the previous 2 months, current regular use of paracetamol, use of high-dose aspirin or non-steroidal anti-inflammatory drugs, current or past cigarette smoking >10 pack-years.
Interventions: In a 12-week randomised, double-blind, placebo-controlled, parallel-group study, participants received 12 weeks of 1 g paracetamol twice daily or placebo twice daily.
Primary And Secondary Outcome Measures: The primary outcome variable was BHR, measured as the PC20 at week 12. Secondary outcome variables included FEV1, fractional exhaled nitric oxide (FeNO) and asthma control questionnaire (ACQ) score.
Results: At 12 weeks, the mean (SD) logarithm base two PC20 was 1.07 (2.36) in the control group (N=54) and 0.62 (2.09) in the paracetamol group (N=31). After controlling for baseline PC20, the mean difference (paracetamol minus placebo) was -0.48 doubling dose worsening in BHR in the paracetamol group (95% CI -1.28 to 0.32), p=0.24. There were no statistically significant differences (paracetamol minus placebo) in log FeNO (0.09 (95% CI -0.097 to 0.27)), FEV1 (-0.07 L (95% CI -0.15 to 0.01)) or ACQ score (-0.04 (95% CI -0.27 to 0.18)).
Conclusions: There was no significant effect of paracetamol on BHR and asthma control in adults with mild-to-moderate asthma. However, the study findings are limited by low power and the upper confidence limits did not rule out clinically relevant adverse effects.
Trial Registration: Australia New Zealand Clinical Trials Registry Number: NZCTR12609000551291.
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http://dx.doi.org/10.1136/bmjopen-2013-004324 | DOI Listing |
IntroductionAsthma 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 PDFWorld J Diabetes
January 2025
Department of Medicine, The Royal College of Surgeons in Ireland-Bahrain, Busiateen 15503, Muharraq, Bahrain.
Background: The relationship between diabetes mellitus (DM) and asthma is complex and can impact disease trajectories.
Aim: To explore the bidirectional influences between the two conditions on clinical outcomes and disease control.
Methods: We systematically reviewed the literature on the relationship between DM and asthma, focusing on their impacts, mechanisms, and therapeutic implications.
J Inflamm Res
January 2025
Department of Geriatric Respiratory and Critical Care, The First Affiliated Hospital of Anhui Medical University, Anhui Geriatric Institute, Hefei, Anhui, People's Republic of China.
Aim: We sought to investigate the impact of CpG oligodeoxynucleotides (CpG-ODN) administration on the lung and gut microbiota in asthmatic mice, specifically focusing on changes in composition, diversity, and abundance, and to elucidate the microbial mechanisms underlying the therapeutic effects of CpG-ODN and identify potential beneficial bacteria indicative of its efficacy.
Methods: HE staining were used to analyze inflammation in lung, colon and small intestine tissues. High-throughput sequencing technology targeting 16S rRNA was employed to analyze the composition, diversity, and correlation of microbiome in the lung, colon and small intestine of control, model and CpG-ODN administration groups.
Rev 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.
View Article and Find Full Text PDFGenome-wide association studies (GWAS) have identified genetic variants robustly associated with asthma. A potential near-term clinical application is to calculate polygenic risk score (PRS) to improve disease risk prediction. The value of PRS, as part of numerous multi-source variables used to define asthma, remains unclear.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!