METHODS: Hospitalised adult patients on EID gentamicin were selected. We considered a DFP of between 2 and 8 h as appropriate. Data from two blood samples (2 and 6 h postdose) from each patient were used to estimate the duration of DFP (i.e. DFP method 1). DFP was also calculated for the same patient using an empirically estimated elimination rate constant (Ke ) and the same 6 h postdose concentration value (DFP method 2). Correlation between the two methods was made. An alternative graphical method to estimate DFP was attempted.
KEY FINDINGS: Correlation between Ke and age was favourable (r = -0.453; P = 0.001). Ke derived from this empirical relationship was used to estimate DFP method 2. DFP method 1 correlated well with DFP method 2 (r = 0.742; P
METHODS: We reanalyzed the empirical data from the Health Insurance Plan trial in 1963 to the UK age trial in 1991 and their follow-up data published until 2015. We first performed Bayesian conjugated meta-analyses on the heterogeneity of attendance rate, sensitivity, and over-detection and their impacts on advanced stage breast cancer and death from breast cancer across trials using Bayesian Poisson fixed- and random-effect regression model. Bayesian meta-analysis of causal model was then developed to assess a cascade of causal relationships regarding the impact of both attendance and sensitivity on 2 main outcomes.
RESULTS: The causes of heterogeneity responsible for the disparities across the trials were clearly manifested in 3 components. The attendance rate ranged from 61.3% to 90.4%. The sensitivity estimates show substantial variation from 57.26% to 87.97% but improved with time from 64% in 1963 to 82% in 1980 when Bayesian conjugated meta-analysis was conducted in chronological order. The percentage of over-detection shows a wide range from 0% to 28%, adjusting for long lead-time. The impacts of the attendance rate and sensitivity on the 2 main outcomes were statistically significant. Causal inference made by linking these causal relationships with emphasis on the heterogeneity of the attendance rate and sensitivity accounted for the variation in the reduction of advanced breast cancer (none-30%) and of mortality (none-31%). We estimated a 33% (95% CI: 24-42%) and 13% (95% CI: 6-20%) breast cancer mortality reduction for the best scenario (90% attendance rate and 95% sensitivity) and the poor scenario (30% attendance rate and 55% sensitivity), respectively.
CONCLUSION: Elucidating the scenarios from high to low performance and learning from the experiences of these trials helps screening policy-makers contemplate on how to avoid errors made in ineffective studies and emulate the effective studies to save women lives.
METHODS: Dentists were recruited through two main dental associations in Malaysia and attended a 1-day training session on recognizing abnormalities within the oral cavity. Following the training, the dentists conducted screening and provided risk habits cessation advice at their respective clinics for 6 months. The impact of the program was evaluated by determining the number of patients who were screened and/or provided with risk habits cessation advice.
RESULTS: Twenty-six dentists took part in the program and conducted opportunistic screening on a total of 2603 individuals. On average, they screened about 23.0% of their patients and 5.1% were given risk habits cessation advice. Notably, dentists who had lower patient load were more likely to conduct opportunistic screening.
CONCLUSIONS: While the participating private dentists state that they have a role in performing opportunistic screening and providing risk habits cessation advice, these activities are still not a priority area in the private clinics, strongly suggesting that strategies to motivate dentists in this setting are urgently needed.
METHODS: Sociodemographic data, anthropometric measurements and 3 day dietary intake record were collected from 54 ADHD children and 54 typical development (TD) children. The Behavioral Pediatrics Feeding Assessment Scale was used to assess feeding problems.
RESULTS: Mean subject age was 8.6 ± 2.1 years. On anthropometric assessment, 11.1% of the ADHD children had wasting, while 1.9% had severe wasting. In contrast, none of the TD children had wasting. Approximately 5.6% of the ADHD children had stunting, as compared with 3.7% of the TD children, while none of the TD children had severe stunting compared with 3.7% of the ADHD children. More than half of the ADHD children had mid-upper arm circumference (MUAC) below the 5th percentile, indicating undernutrition, compared with only 35.2% of TD children. More than one-third of the ADHD children had feeding problems compared with 9.3% of TD children. There was a significant negative relationship between the ADHD children's feeding problems and bodyweight (r = -0338, P = 0.012), body mass index (r = -0322, P = 0.017) and MUAC (r = -0384, P = 0.004).
CONCLUSION: Almost half of the ADHD children had suboptimal nutrition compared with 11.1% of the TD children. It is imperative to screen ADHD children for nutritional status and feeding problems to prevent negative health impacts later on.