MyMedR (Malaysian Medical Repository) is an open access collection of Malaysian health and biomedical research. The materials are imported from PubMed and MyJurnal. We gratefully acknowledge the permission to reuse the materials from the National Library of Medicine of the United States and the Malaysian Citation Centre. This project is funded by Academy of Family Physicians of Malaysia. The project team members are: CL Teng, CJ Ng, EM Khoo, Mastura Ismail, Abrizah Abdullah, TK Chiew, Thanaletchumi Dharmalingam.
Please note that some citations are non-Malaysian publications. Common reasons are: (1) One or more authors had a Malaysian affiliation; (2) The article abstract mentioned Malaysia; (3) The study subjects included Malay ethnic group.
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DESIGN: Cross-sectional observational study.
SETTING: Twenty-three Asian countries and regions, covering 92.1% of the continent's population.
PARTICIPANTS: Ten low-income and lower-middle-income economies, five upper-middle-income economies, and eight high-income economies according to the World Bank classification.
INTERVENTIONS: Data closest to 2017 on critical care beds, including ICU and intermediate care unit beds, were obtained through multiple means, including government sources, national critical care societies, colleges, or registries, personal contacts, and extrapolation of data.
MEASUREMENTS AND MAIN RESULTS: Cumulatively, there were 3.6 critical care beds per 100,000 population. The median number of critical care beds per 100,000 population per country and region was significantly lower in low- and lower-middle-income economies (2.3; interquartile range, 1.4-2.7) than in upper-middle-income economies (4.6; interquartile range, 3.5-15.9) and high-income economies (12.3; interquartile range, 8.1-20.8) (p = 0.001), with a large variation even across countries and regions of the same World Bank income classification. This number was independently predicted by the World Bank income classification on multivariable analysis, and significantly correlated with the number of acute hospital beds per 100,000 population (r = 0.19; p = 0.047), the universal health coverage service coverage index (r = 0.35; p = 0.003), and the Human Development Index (r = 0.40; p = 0.001) on univariable analysis.
CONCLUSIONS: Critical care bed capacity varies widely across Asia and is significantly lower in low- and lower-middle-income than in upper-middle-income and high-income countries and regions.
RESEARCH QUESTION: We aim to determine if clusters of Chinese patients with COPD exist and their association with clinical outcomes and inflammation.
STUDY DESIGN AND METHODS: Chinese patients with stable COPD were prospectively recruited into two cohorts (derivation and validation) from six hospitals across three Southeast Asian countries (Singapore, Malaysia, and Hong Kong; n = 1,480). Each patient was followed more than 2 years. Clinical data (including co-morbidities) were employed in unsupervised hierarchical clustering (followed by validation) to determine the existence of patient clusters and their prognostic outcome. Accompanying systemic cytokine assessments were performed in a subset (n = 336) of patients with COPD to determine if inflammatory patterns and associated networks characterized the derived clusters.
RESULTS: Five patient clusters were identified including: (1) ex-TB, (2) diabetic, (3) low comorbidity: low-risk, (4) low comorbidity: high-risk, and (5) cardiovascular. The cardiovascular and ex-TB clusters demonstrate highest mortality (independent of Global Initiative for Chronic Obstructive Lung Disease assessment) and illustrate diverse cytokine patterns with complex inflammatory networks.
INTERPRETATION: We describe clusters of Chinese patients with COPD, two of which represent high-risk clusters. The cardiovascular and ex-TB patient clusters exhibit high mortality, significant inflammation, and complex cytokine networks. Clinical and inflammatory risk stratification of Chinese patients with COPD should be considered for targeted intervention to improve disease outcomes.
DESIGN: This was a single-center prospective observational study that compared resting energy expenditure estimated by 15 commonly used predictive equations against resting energy expenditure measured by indirect calorimetry at different phases. Degree of agreement between resting energy expenditure calculated by predictive equations and resting energy expenditure measured by indirect calorimetry was analyzed using intraclass correlation coefficient and Bland-Altman analyses. Resting energy expenditure values calculated from predictive equations differing by ± 10% from resting energy expenditure measured by indirect calorimetry was used to assess accuracy. A score ranking method was developed to determine the best predictive equations.
SETTING: General Intensive Care Unit, University of Malaya Medical Centre.
PATIENTS: Mechanically ventilated critically ill patients.
MEASUREMENTS AND MAIN RESULTS: Indirect calorimetry was measured thrice during acute, late, and chronic phases among 305, 180, and 91 ICU patients, respectively. There were significant differences (F= 3.447; p = 0.034) in mean resting energy expenditure measured by indirect calorimetry among the three phases. Pairwise comparison showed mean resting energy expenditure measured by indirect calorimetry in late phase (1,878 ± 517 kcal) was significantly higher than during acute phase (1,765 ± 456 kcal) (p = 0.037). The predictive equations with the best agreement and accuracy for acute phase was Swinamer (1990), for late phase was Brandi (1999) and Swinamer (1990), and for chronic phase was Swinamer (1990). None of the resting energy expenditure calculated from predictive equations showed very good agreement or accuracy.
CONCLUSIONS: Predictive equations tend to either over- or underestimate resting energy expenditure at different phases. Predictive equations with "dynamic" variables and respiratory data had better agreement with resting energy expenditure measured by indirect calorimetry compared with predictive equations developed for healthy adults or predictive equations based on "static" variables. Although none of the resting energy expenditure calculated from predictive equations had very good agreement, Swinamer (1990) appears to provide relatively good agreement across three phases and could be used to predict resting energy expenditure when indirect calorimetry is not available.
METHODS AND RESULTS : Cardiovascular magnetic resonance was performed in 400 asymptomatic hypertensive patients. The newly derived RI (EDV3t, where EDV is LV end-diastolic volume and t is the maximal wall thickness across 16 myocardial segments) stratified hypertensive patients: no LVH, LVH with normal RI (LVHNormal-RI), and LVH with low RI (LVHLow-RI). The primary outcome was a composite of all-cause mortality, acute coronary syndromes, strokes, and decompensated heart failure. LVHLow-RI was associated with increased LV mass index, fibrosis burden, impaired myocardial function and elevated biochemical markers of myocardial injury (high-sensitive cardiac troponin I), and wall stress. Over 18.3 ± 7.0 months (601.3 patient-years), 14 adverse events occurred (2.2 events/100 patient-years). Patients with LVHLow-RI had more than a five-fold increase in adverse events compared to those with LVHNormal-RI (11.6 events/100 patient-years vs. 2.0 events/100 patient-years, respectively; log-rank P