METHODOLOGY: Tracheal aspirates were obtained from neonates on ventilatory support. The SM test was carried out on specimens of tracheal aspirate immediately after collection. Levels of SP-A in tracheal aspirates were determined by enzyme-linked immunosorbent assay (ELISA) method. The results of the SM test and SP-A level of the tracheal aspirates were compared against the clinical diagnosis of RDS based on clinical, radiological and bacteriological findings.
RESULTS: Both the median microbubble counts (6 microbubbles/mm2, range = 0-90) and median SP-A levels (100 micrograms/L, range = 0-67447) of infants with RDS were significantly lower than those of infants with no obvious lung pathology (P < 0.0001), and pneumonia (P < 0.0001). The SM test of tracheal aspirates had higher overall accuracy for the diagnosis of RDS than measurement of SP-A levels (94.6% vs 82.4%). When the receiver operating characteristic (ROC) curves of both tests for RDS were compared, the area under the ROC curve of the SM test was larger (0.9689) than that of the SP-A method (0.8965).
CONCLUSIONS: This study showed that the SM test of tracheal aspirate was a useful bedside diagnostic test for RDS. It could be carried out at any time after birth on infants requiring ventilatory support.
MATERIALS AND METHODS: This prospective study was conducted between July 2012 and December 2013. Stool samples of 59 dyspeptic patients who underwent upper endoscopy were evaluated for H. pylori stool antigen.
RESULTS: From the 59 patients who participated in this study, there were 36 (61%) males and 23 (39%) females. H. pylori was diagnosed in 24 (40.7%) gastric biopsies, 22 (91.7 %) of these being positive for the Atlas H. pylori antigen test. The sensitivity, specificity, PPV, NPV and accuracy were 91.7%, 100%, 100%, 94.6% and 96.6% respectively.
CONCLUSIONS: The Atlas H. pylori antigen test is a new non-invasive method which is simple to perform and avails reliable results in a few minutes. Thus it can be the best option for the diagnosis of H. pylori infection due to its high sensitivity and specificity.
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.