Displaying publications 61 - 64 of 64 in total

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  1. Ching SM, Mokshashri NR, Kannan MM, Lee KW, Sallahuddin NA, Ng JX, et al.
    BMC Complement Med Ther, 2021 Jan 06;21(1):8.
    PMID: 33407414 DOI: 10.1186/s12906-020-03172-3
    BACKGROUND: The benefits of qigong for systolic and diastolic blood pressure (BP) reduction have been noted in previously published systematic reviews; however, the data on its effectiveness has been at best scarce. We aimed to update the evidence of qigong on blood pressure reduction after taking into consideration the risks of random error and reliability of data in the cumulative meta-analysis using trial sequential analysis (TSA).

    METHODS: Included trials were assessed using Cochrane risk of bias instrument. We performed meta-analysis with random-effects model and random errors were evaluated with TSA. We performed the search for the eligible randomized controlled trial (RCT) through Medline, Cinahl, Cochrane Central Register of Controlled Trials and also PubMed.

    RESULTS: A total of 370 subjects sourced from seven eligible RCTs were entered into the analysis. The pooled results demonstrated the significant reduction with the use of qigong of the systolic blood pressure [weighted mean difference (WMD), - 10.66 mmHg (95% confidence interval (CI) = - 17.69,-3.62, p 

  2. Lee KW, Ching SM, Ramachandran V, Yee A, Hoo FK, Chia YC, et al.
    BMC Pregnancy Childbirth, 2018 Dec 14;18(1):494.
    PMID: 30547769 DOI: 10.1186/s12884-018-2131-4
    BACKGROUND: Gestational diabetes mellitus (GDM) is a of the major public health issues in Asia. The present study aimed to determine the prevalence of, and risk factors for GDM in Asia via a systematic review and meta-analysis.

    METHODS: We systematically searched PubMed, Ovid, Scopus and ScienceDirect for observational studies in Asia from inception to August 2017. We selected cross sectional studies reporting the prevalence and risk factors for GDM. A random effects model was used to estimate the pooled prevalence of GDM and odds ratio (OR) with 95% confidence interval (CI).

    RESULTS: Eighty-four studies with STROBE score ≥ 14 were included in our analysis. The pooled prevalence of GDM in Asia was 11.5% (95% CI 10.9-12.1). There was considerable heterogeneity (I2 > 95%) in the prevalence of GDM in Asia, which is likely due to differences in diagnostic criteria, screening methods and study setting. Meta-analysis demonstrated that the risk factors of GDM include history of previous GDM (OR 8.42, 95% CI 5.35-13.23); macrosomia (OR 4.41, 95% CI 3.09-6.31); and congenital anomalies (OR 4.25, 95% CI 1.52-11.88). Other risk factors include a BMI ≥25 kg/m2 (OR 3.27, 95% CI 2.81-3.80); pregnancy-induced hypertension (OR 3.20, 95% CI 2.19-4.68); family history of diabetes (OR 2.77, 2.22-3.47); history of stillbirth (OR 2.39, 95% CI 1.68-3.40); polycystic ovary syndrome (OR 2.33, 95% CI1.72-3.17); history of abortion (OR 2.25, 95% CI 1.54-3.29); age ≥ 25 (OR 2.17, 95% CI 1.96-2.41); multiparity ≥2 (OR 1.37, 95% CI 1.24-1.52); and history of preterm delivery (OR 1.93, 95% CI 1.21-3.07).

    CONCLUSION: We found a high prevalence of GDM among the Asian population. Asian women with common risk factors especially among those with history of previous GDM, congenital anomalies or macrosomia should receive additional attention from physician as high-risk cases for GDM in pregnancy.

    TRIAL REGISTRATION: PROSPERO (2017: CRD42017070104 ).

  3. Lee KW, Khan AHKY, Ching SM, Kumar SJ, Raj CLVP, Chia PK, et al.
    Neurol India, 2024 May 01;72(3):476-486.
    PMID: 39041960 DOI: 10.4103/neuroindia.NI_981_20
    BACKGROUND: Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a severe autoimmune encephalitis due to immune production of anti-NMDAR antibodies against the NR1 subunit of the NMDA receptor which is present throughout the central nervous system. This condition had been reported to be prevalent in patients with certain medical conditions; however so far, there have been limited systematic reviews and meta-analyses on the prevalence and factors associated.

    OBJECTIVE: This study was to determine the prevalence and factors associated with anti-NMDAR encephalitis among affected patients.

    MATERIAL AND METHODS: The protocol of this study has been registered (2019: CRD42019142002) with the International Prospective Register of Systematic Reviews (PROSPERO). The primary outcome was the incidence or prevalence of anti-NMDAR encephalitis and secondary outcomes were factors associated with anti-NMDAR encephalitis.

    RESULTS: There were 11 studies and a total of 873 million patients taken from high-risk populations across 11 countries that were included in the primary analysis. The overall pooled prevalence of anti-NMDAR encephalitis among patients with medical conditions was 7.0% (95% CI = 4.4, 9.6). Those with first episode of psychosis or schizophrenia were at a higher risk of developing anti-NMDAR encephalitis with an odds ratio of 5.976 (95% CI = 1.122, 31.825).

    CONCLUSION: We found that almost one-tenth of patients with medical conditions had anti-NMDAR encephalitis; particularly those with first episode of psychosis or schizophrenia were among the high-risk medical conditions.

  4. Duong KNC, Nguyen DT, Kategeaw W, Liang X, Khaing W, Visnovsky LD, et al.
    Lancet Reg Health Am, 2024 Jul;35:100806.
    PMID: 38948323 DOI: 10.1016/j.lana.2024.100806
    During COVID-19 in the US, social determinants of health (SDH) have driven health disparities. However, the use of SDH in COVID-19 vaccine modeling is unclear. This review aimed to summarize the current landscape of incorporating SDH into COVID-19 vaccine transmission modeling in the US. Medline and Embase were searched up to October 2022. We included studies that used transmission modeling to assess the effects of COVID-19 vaccine strategies in the US. Studies' characteristics, factors incorporated into models, and approaches to incorporate these factors were extracted. Ninety-two studies were included. Of these, 11 studies incorporated SDH factors (alone or combined with demographic factors). Various sets of SDH factors were integrated, with occupation being the most common (8 studies), followed by geographical location (5 studies). The results show that few studies incorporate SDHs into their models, highlighting the need for research on SDH impact and approaches to incorporating SDH into modeling.

    FUNDING: This research was funded by the Centers for Disease Control and Prevention (CDC).

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