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  1. Pirabbasi E, Najafiyan M, Cheraghi M, Shahar S, Abdul Manaf Z, Rajab N, et al.
    Glob J Health Sci, 2013 Jan;5(1):70-8.
    PMID: 23283038 DOI: 10.5539/gjhs.v5n1p70
    Imbalance between antioxidant and oxidative stress is a major risk factor for pathogenesis of some chronic diseases such as chronic obstructive pulmonary disease (COPD). This study aimed to determine antioxidant and oxidative stress status, and also theirs association with respiratory function of male COPD patients to find the antioxidant predictors' factors. A total of 149 subjects were involved in a cross-sectional study. The study was conducted at two medical centers in Kuala Lumpur, Malaysia. Results of the study showed that plasma vitamin C was low in most of the subjects (86.6%). Total antioxidant capacity was the lowest in COPD stage IV compare to other stages (p < 0.05). Level of plasma vitamin A (p= 0.012) and vitamin C (p= 0.007) were low in malnourished subjects. The predictors for total antioxidant capacity were forced vital capacity (FVC) % predicted and intake of ?-carotene (R2= 0.104, p= 0.002). Number of cigarette (pack/ year) and smoking index (number/ year) were not associated with total antioxidant capacity of this COPD population. Plasma oxidative stress as assessed plasma lipid peroxidation (LPO) was only positively correlated with plasma glutathione (p= 0.002). It might be a need to evaluate antioxidant status especially in older COPD patients to treat antioxidant deficiency which is leading to prevent COPD progression.
    Study site: Outpatient clinics, Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM) and Institute of Respiratory Medicine, Kuala Lumpur, Malaysia
    Matched MeSH terms: Pulmonary Disease, Chronic Obstructive/blood*
  2. Poh TY, Tiew PY, Lim AYH, Thng KX, Binte Mohamed Ali NA, Narayana JK, et al.
    Chest, 2020 08;158(2):512-522.
    PMID: 32184111 DOI: 10.1016/j.chest.2020.02.048
    BACKGROUND: Chitinase activity is an important innate immune defence mechanism against infection that includes fungi. The 2 human chitinases: chitotriosidase (CHIT1) and acidic mammalian chitinase are associated to allergy, asthma, and COPD; however, their role in bronchiectasis and bronchiectasis-COPD overlap (BCO) is unknown.

    RESEARCH QUESTION: What is the association between chitinase activity, airway fungi and clinical outcomes in bronchiectasis and bronchiectasis-COPD overlap?

    STUDY DESIGN AND METHODS: A prospective cohort of 463 individuals were recruited across five hospital sites in three countries (Singapore, Malaysia, and Scotland) including individuals who were not diseased (n = 35) and who had severe asthma (n = 54), COPD (n = 90), bronchiectasis (n = 241) and BCO (n = 43). Systemic chitinase levels were assessed for bronchiectasis and BCO and related to clinical outcomes, airway Aspergillus status, and underlying pulmonary mycobiome profiles.

    RESULTS: Systemic chitinase activity is elevated significantly in bronchiectasis and BCO and exceed the activity in other airway diseases. CHIT1 activity strongly predicts bronchiectasis exacerbations and is associated with the presence of at least one Aspergillus species in the airway and frequent exacerbations (≥3 exacerbations/y). Subgroup analysis reveals an association between CHIT1 activity and the "frequent exacerbator" phenotype in South-East Asian patients whose airway mycobiome profiles indicate the presence of novel fungal taxa that include Macroventuria, Curvularia and Sarocladium. These taxa, enriched in frequently exacerbating South-East Asian patients with high CHIT1 may have potential roles in bronchiectasis exacerbations.

    INTERPRETATION: Systemic CHIT1 activity may represent a useful clinical tool for the identification of fungal-driven "frequent exacerbators" with bronchiectasis in South-East Asian populations.

    Matched MeSH terms: Pulmonary Disease, Chronic Obstructive/blood
  3. Mohktar MS, Redmond SJ, Antoniades NC, Rochford PD, Pretto JJ, Basilakis J, et al.
    Artif Intell Med, 2015 Jan;63(1):51-9.
    PMID: 25704112 DOI: 10.1016/j.artmed.2014.12.003
    BACKGROUND: The use of telehealth technologies to remotely monitor patients suffering chronic diseases may enable preemptive treatment of worsening health conditions before a significant deterioration in the subject's health status occurs, requiring hospital admission.
    OBJECTIVE: The objective of this study was to develop and validate a classification algorithm for the early identification of patients, with a background of chronic obstructive pulmonary disease (COPD), who appear to be at high risk of an imminent exacerbation event. The algorithm attempts to predict the patient's condition one day in advance, based on a comparison of their current physiological measurements against the distribution of their measurements over the previous month.
    METHOD: The proposed algorithm, which uses a classification and regression tree (CART), has been validated using telehealth measurement data recorded from patients with moderate/severe COPD living at home. The data were collected from February 2007 to January 2008, using a telehealth home monitoring unit.
    RESULTS: The CART algorithm can classify home telehealth measurement data into either a 'low risk' or 'high risk' category with 71.8% accuracy, 80.4% specificity and 61.1% sensitivity. The algorithm was able to detect a 'high risk' condition one day prior to patients actually being observed as having a worsening in their COPD condition, as defined by symptom and medication records.
    CONCLUSION: The CART analyses have shown that features extracted from three types of physiological measurements; forced expiratory volume in 1s (FEV1), arterial oxygen saturation (SPO2) and weight have the most predictive power in stratifying the patients condition. This CART algorithm for early detection could trigger the initiation of timely treatment, thereby potentially reducing exacerbation severity and recovery time and improving the patient's health. This study highlights the potential usefulness of automated analysis of home telehealth data in the early detection of exacerbation events among COPD patients.
    Matched MeSH terms: Pulmonary Disease, Chronic Obstructive/blood
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