METHODS: Asian countries were categorised into three groups; 'lower middle-income country', 'upper middle-income country' and 'high-income country'. The Medline/PubMed database was searched for articles published from January 2005 to December 2014 using relevant key words. Articles were excluded if they examined a specific injury mechanism, referred to a specific age group, and/or did not have full text available. We extracted information and variables on pre-hospital and hospital care factors, and regionalised system factors and compared them across countries.
RESULTS: A total of 46 articles were identified from 13 countries, including Pakistan, India, Vietnam and Indonesia from lower middle-income countries; the Islamic Republic of Iran, Thailand, China, Malaysia from upper middle-income countries; and Saudi Arabia, the Republic of Korea, Japan, Hong Kong and Singapore from high-income countries. Trauma patients were transported via various methods. In six of the 13 countries, less than 20% of trauma patients were transported by ambulance. Pre-hospital trauma teams primarily comprised emergency medical technicians and paramedics, except in Thailand and China, where they included mainly physicians. In Iran, Pakistan and Vietnam, the proportion of patients who died before reaching hospital exceeded 50%. In only three of the 13 countries was it reported that trauma surgeons were available. In only five of the 13 countries was there a nationwide trauma registry.
CONCLUSION: Trauma care systems were poorly developed and unorganised in most of the selected 13 Asian countries, with the exception of a few highly developed countries.
METHODS AND FINDINGS: We conducted a retrospective cohort study of trauma patients transported from the scene to hospitals by emergency medical service (EMS) from January 1, 2016, to November 30, 2018, using data from the Pan-Asia Trauma Outcomes Study (PATOS) database. Prehospital time intervals were categorized into response time (RT), scene to hospital time (SH), and total prehospital time (TPT). The outcomes were 30-day mortality and functional status at hospital discharge. Multivariable logistic regression was used to investigate the association of prehospital time and outcomes to adjust for factors including age, sex, mechanism and type of injury, Injury Severity Score (ISS), Revised Trauma Score (RTS), and prehospital interventions. Overall, 24,365 patients from 4 countries (645 patients from Japan, 16,476 patients from Korea, 5,358 patients from Malaysia, and 1,886 patients from Taiwan) were included in the analysis. Among included patients, the median age was 45 years (lower quartile [Q1]-upper quartile [Q3]: 25-62), and 15,498 (63.6%) patients were male. Median (Q1-Q3) RT, SH, and TPT were 20 (Q1-Q3: 12-39), 21 (Q1-Q3: 16-29), and 47 (Q1-Q3: 32-60) minutes, respectively. In all, 280 patients (1.1%) died within 30 days after injury. Prehospital time intervals were not associated with 30-day mortality. The adjusted odds ratios (aORs) per 10 minutes of RT, SH, and TPT were 0.99 (95% CI 0.92-1.06, p = 0.740), 1.08 (95% CI 1.00-1.17, p = 0.065), and 1.03 (95% CI 0.98-1.09, p = 0.236), respectively. However, long prehospital time was detrimental to functional survival. The aORs of RT, SH, and TPT per 10-minute delay were 1.06 (95% CI 1.04-1.08, p < 0.001), 1.05 (95% CI 1.01-1.08, p = 0.007), and 1.06 (95% CI 1.04-1.08, p < 0.001), respectively. The key limitation of our study is the missing data inherent to the retrospective design. Another major limitation is the aggregate nature of the data from different countries and unaccounted confounders such as in-hospital management.
CONCLUSIONS: Longer prehospital time was not associated with an increased risk of 30-day mortality, but it may be associated with increased risk of poor functional outcomes in injured patients. This finding supports the concept of the "golden hour" for trauma patients during prehospital care in the countries studied.
METHODS: A cohort study was conducted in 77,425 men and women free of NAFLD and metabolic abnormalities at baseline, who were followed-up annually or biennially for an average of 4.5 years. Being metabolically healthy was defined as not having any metabolic syndrome component and having a homeostasis model assessment of insulin resistance <2.5. The presence of fatty liver was determined using ultrasound.
RESULTS: During 348,193.5 person-years of follow-up, 10,340 participants developed NAFLD (incidence rate, 29.7 per 1,000 person-years). The multivariable adjusted hazard ratios (95% confidence intervals) for incident NAFLD comparing overweight and obese with normal-weight participants were 2.15 (2.06-2.26) and 3.55 (3.37-3.74), respectively. In detailed dose-response analyses, increasing baseline BMI showed a strong and approximately linear relationship with the incidence of NAFLD, with no threshold at no risk. This association was present in both men and women, although it was stronger in women (P for interaction <0.001), and it was evident in all clinically relevant subgroups evaluated, including participants with low inflammation status.
CONCLUSIONS: In a large cohort of strictly defined metabolically healthy men and women, overweight and obesity were strongly and progressively associated with an increased incidence of NAFLD, suggesting that the obese phenotype per se, regardless of metabolic abnormalities, can increase the risk of NAFLD.