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BackgroundAntimicrobial resistance has emerged as a major concern in developing countries. The present study sought to define the pattern of antimicrobial resistance in ICU patients with ventilator-associated pneumonia.MethodsBetween November 2014 and September 2015, we enrolled 220 patients (average age ~ 71 yr) who were admitted to ICU in a major tertiary hospital in Ho Chi Minh City, Vietnam. Data concerning demographic characteristics and clinical history were collected from each patient. The Bauer–Kirby disk diffusion method was used to detect the antimicrobial susceptibility.ResultsAntimicrobial resistance was commonly found in ceftriaxone (88%), ceftazidime (80%), ciprofloxacin (77%), cefepime (75%), levofloxacin (72%). Overall, the rate of antimicrobial resistance to any drug was 93% (n = 153/164), with the majority (87%) being resistant to at least 2 drugs. The three commonly isolated microorganisms were Acinetobacter (n = 75), Klebsiella (n = 39), and Pseudomonas aeruginosa (n = 29). Acinetobacter baumannii were virtually resistant to ceftazidime, ceftriaxone, piperacilin, imipenem, meropenem, ertapenem, ciprofloxacin and levofloxacin. High rates (>70%) of ceftriaxone and ceftazidime-resistant Klebsiella were also observed.ConclusionThese data indicated that critically ill patients on ventilator in Vietnam were at disturbingly high risk of antimicrobial resistance. The data also imply that these Acinetobacter, Klebsiella, and Pseudomonas aeruginosa and multidrug resistance pose serious therapeutic problems in ICU patients. A concerted and systematic effort is required to rapidly identify high risk patients and to reduce the burden of antimicrobial resistance in developing countries.

Although the susceptibility to fracture is partly determined by genetic factors, the contribution of newly discovered genetic variants to fracture prediction is still unclear. This study sought to define the predictive value of a genetic profiling for fracture prediction. Sixty-two bone mineral density (BMD)-associated single-nucleotide polymorphisms (SNPs) were genotyped in 557 men and 902 women who had participated in the Dubbo Osteoporosis Epidemiology Study. The incidence of fragility fracture was ascertained from X-ray reports between 1990 and 2015. Femoral neck BMD was measured by dual-energy X-ray absorptiometry. A weighted polygenic risk score (genetic risk score [GRS]) was created as a function of the number of risk alleles and their BMD-associated regression coefficients for each SNP. The association between GRS and fracture risk was assessed by the Cox proportional hazards model. Individuals with greater GRS had lower femoral neck BMD (p < 0.01), but the variation in GRS accounted for less than 2% of total variance in BMD. Each unit increase in GRS was associated with a hazard ratio of 1.20 (95% CI, 1.04 to 1.38) for fracture, and this association was independent of age, prior fracture, fall, and in a subset of 33 SNPs, independent of femoral neck BMD. The significant association between GRS and fracture was observed for the vertebral and wrist fractures, but not for hip fracture. The area under the receiver-operating characteristic (ROC) curve (AUC) for the model with GRS and clinical risk factors was 0.71 (95% CI, 0.68 to 0.74). With GRS, the correct reclassification of fracture versus nonfracture ranged from 12% for hip fracture to 23% for wrist fracture. A genetic profiling of BMD- associated genetic variants could improve the accuracy of fracture prediction over and above that of clinical risk factors alone, and help stratify individuals by fracture status. © 2016 American Society for Bone and Mineral Research.

Hip fracture is one of the most serious health problems among post-menopausal women with osteoporosis. It is very difficult to predict hip fracture, because it is affected by multiple risk factors. Existing statistical models for predicting hip fracture risk yield area under the receiver operating characteristic curve (AUC) ~0.7-0.85. In this study, we trained an artificial neural network (ANN) to predict hip fracture in one cohort, and validated its predictive performance in another cohort. The data for training and validation included age, bone mineral density (BMD), clinical factors, and lifestyle factors which had been obtained from a longitudinal study that involved 1167 women aged 60 years and above. The women had been followed up for up to 10 years, and during the period, the incidence of new hip fractures was ascertained. We applied feed-forward neural networks to learn from the data, and then used the learning for predicting hip fracture. Results of prediction showed that the accuracy of model I (which included only lumbar spine and femoral neck BMD) and model II (which included non-BMD factors) was 82% and 84%, respectively. When both BMD and non-BMD factors were combined (Model III), the accuracy increased to 87%. The AUC for model III was 0.94. These findings indicate that ANNs are able to predict hip fracture more accurately than any existing statistical models, and that ANNs can help stratify individuals for clinical management.

Osteoporotic fracture increases the risk of premature mortality. Muscle weakness is associated with both increased fracture risk and low bone mineral density (BMD). However, the role of muscle strength in post-fracture mortality is not well understood. This study examines the change of muscle strength measured at quadriceps (QS) before and after fracture and defines the relationship between muscle strength and post-fracture mortality. The study involved 889 women and 295 men (who were participating in the Dubbo Osteoporosis Study) who had at least one low-trauma fracture (ascertained from X-ray reports) after the age of 50 years. Median follow-up time was 11 years (range 1 to 24). To determine the change in muscle strength before and after a fracture, we selected a subset of 344 women and 99 men who had had at least two muscle strength measurements before the fracture event and a subset of 407 women and 105 men who had had at least two measurements after the fracture. During the follow-up period, 366 (41.2%) women and 150 (50.9%) men died. The annual rate of decrease in height-adjusted muscle strength before fracture was 0.27 kg/m (1.85%) in women and 0.40 kg/m (1.79%) in men. Strength loss after fracture was not significantly different from that before fracture. In women, after adjusting for baseline age and BMD, each SD (5 kg/m) lower height-adjusted pre- and post-fracture quadriceps strength was associated with a 27% (hazard ratio [HR] = 1.27; 95% confidence interval [CI] 1.07, 1.50) and 18% (HR = 1.18; 95% CI 1.01, 1.38) increase in post-fracture mortality risk, respectively. Similarly, in men, each SD (5 kg/m) lower height-adjusted pre- and post-fracture QS was associated with increased mortality before fracture (HR = 1.33; 95% CI 1.09, 1.63) and after fracture (HR = 1.43; 95% CI 1.16, 1.78). Muscle weakness accounted for 15% (95% CI 0.05, 0.24) of premature deaths after fracture in women and 23% (95% CI 0.11, 0.35) in men. These results indicate that in the older individuals, lower muscle strength is an independent risk factor for post-fracture mortality. © 2017 American Society for Bone and Mineral Research.

Objectives Calcaneal quantitative ultrasound measurement (QUS) has been considered an alternative to dual-energy X-ray absorptiometry (DXA) based bone mineral density (BMD) for assessing bone health. This study sought to examine the utility of QUS as an osteoporosis screening tool by evaluating the correlation between QUS and DXA. Methods The study was a part of the Vietnam Osteoporosis Study that involved 1270 women and 773 men aged 18 years and older. BMD at the femoral neck, total hip and lumbar spine was measured using DXA. Osteoporosis was diagnosed based on the femoral neck T-score using World Health Organization criteria. Broadband ultrasound attenuation (BUA) at the calcaneus was measured by QUS. The concordance between BUA and BMD was analyzed by the linear regression model. Results In all individuals, BUA modestly correlated with femoral neck BMD (r = 0.35; P < 0.0001) and lumbar spine BMD (r = 0.34; P < 0.0001) in both men and women. In individuals aged 50 years and older, approximately 16% (n = 92/575) of women and 3.2% (n = 10/314) of men were diagnosed to have osteoporosis. Only 0.9% (n = 5/575) women and 1.0% (n = 3/314) men were classified as “Low BUA”. The kappa coefficient of concordance between BMD and BUA classification was 0.09 (95% CI, 0.04 to 0.15) for women and 0.12 (95% CI, 0.03 to 0.22) for men. Conclusions In this population-based study, QUS BUA modestly correlated with DXA BMD, suggesting that BUA is not a reliable method for screening of osteoporosis.

Context Although bone mineral density (BMD) is strongly associated with fracture and postfracture mortality, the burden of fractures attributable to low BMD has not been investigated. Objectives We sought to estimate the population attributable fraction of fractures and fracture-related mortality that can be attributed to low BMD. Design and Setting This study is a part of an ongoing population-based prospective cohort study, the Dubbo Osteoporosis Epidemiology study. In total, 3700 participants aged ≥50 years participated in the study. Low-trauma fracture was ascertained by X-ray reports, and mortality was ascertained from the Birth, Death and Marriage Registry. Results Overall, 21% of women and 11% of men had osteoporotic BMD. In univariable analysis, 21% and 16% of total fractures in women and men, respectively, were attributable to osteoporosis. Osteoporosis combined with advancing age (>70 years) accounted for 34% and 35% of fractures in women and men, respectively. However, these two factors accounted for ∼60% of hip fractures. About 99% and 66% of postfracture mortality in women and men, respectively, were attributable to advancing age, osteoporosis, and fracture; however, most of the attributable proportion was accounted for by advancing age. Conclusions A substantial health care burden of fracture is on people aged <70 years or nonosteoporosis, suggesting that treatment of people with osteoporosis is unlikely to reduce a large number of fractures in the general population.

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