Development of a circuit for functional electrical stimulation

Author name used in this publication: Kai-Yu Tong2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

9631318125

Background: Endometrial ablation (EA) is a frequently used treatment for abnormal uterine bleeding, mainly due to the low risks, low costs and short recovery time associated with the procedure. On the short term, it seems successful, long-term follow-up however, shows decreasing patient satisfaction as well as treament efficacy. There even is a post-ablation hysterectomy rate up to 21%. Multiple factors seem to` influence the outcome of EA. Due to dissimilarities in and variety of these factors, it has not been possible so far to predict the success rate of EA based on pre-operative factors.Therefore, the aim of this study is to develop two prediction models to help counsel patients for failure of EA or necessity of surgical re-intervention within 2years after EA. Methods: We designed a retrospective two-centred cohort study in Catharina Hospital, Eindhoven and Elkerliek Hospital, Helmond, both non-university teaching hospitals in the Netherlands. The study population consisted of 446 pre-menopausal women who underwent EA for abnormal uterine bleeding, with a minimum follow-up time of 2years. Multivariate logistic regression analysis was used to create the prediction models. Results: The mean age of the patients was 43.8years (range 20-55), 97.3% had complaints of menorrhagia, 57.4% of dysmenorrhoea and 61.0% had complaints of intermittent or irregular bleeding. 18.8% of patients still needed a hysterectomy after EA. The risk of re-intervention was significantly greater in women with menstrual duration >7days or a previous caesarean section, while pre-operative menorrhagia was significantly associated with success of EA. Younger age, parity 5 and dysmenorrhea were significant multivariate predictors in both models. These predictors were used to develop prediction models, which had a C-index of 0.71 and 0.68 respectively. Conclusion: We propose two multivariate models to predict the chance of failure and surgical re-intervention within 2years after EA. Due to the permanent character of EA, the increasing number of post-operative failure and re-interventions, these prediction models could be useful for both the doctor and patient and may contribute to the shared decision-making

Relative drifts and biases between six ozone limb satellite measurements from the last decade

As part of European Space Agency\u27s (ESA) climate change initiative, high vertical resolution ozone profiles from three instruments all aboard ESA\u27s Envisat (GOMOS, MIPAS, SCIAMACHY) and ESA\u27s third party missions (OSIRIS, SMR, ACE-FTS) are to be combined in order to create an essential climate variable data record for the last decade. A prerequisite before combining data is the examination of differences and drifts between the data sets. In this paper, we present a detailed analysis of ozone profile differences based on pairwise collocated measurements, including the evolution of the differences with time. Such a diagnosis is helpful to identify strengths and weaknesses of each data set that may vary in time and introduce uncertainties in long-term trend estimates. The analysis reveals that the relative drift between the sensors is not statistically significant for most pairs of instruments. The relative drift values can be used to estimate the added uncertainty in physical trends. The added drift uncertainty is estimated at about 3 % decade-1 (1s). Larger differences and variability in the differences are found in the lowermost stratosphere (below 20 km) and in the mesosphere

Prospective evaluation of antibody response to Streptococcus gallolyticus and risk of colorectal cancer

The gut microbiome is increasingly implicated in colorectal cancer (CRC) development. A subgroup of patients diagnosed with CRC show high antibody responses to Streptococcus gallolyticus subspecies gallolyticus (SGG). However, it is unclear whether the association is also present pre‐diagnostically. We assessed the association of antibody responses to SGG proteins in pre‐diagnostic serum samples with CRC risk in a case–control study nested within a prospective cohort. Pre‐diagnostic serum samples from 485 first incident CRC cases (mean time between blood draw and diagnosis 3.4 years) and 485 matched controls in the European Prospective Investigation into Nutrition and Cancer (EPIC) study were analyzed for antibody responses to 11 SGG proteins using multiplex serology. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using multivariable conditional logistic regression models. Antibody positivity for any of the 11 SGG proteins was significantly associated with CRC risk with 56% positive controls compared to 63% positive cases (OR: 1.36, 95% CI: 1.04–1.77). Positivity for two or more proteins of a previously identified SGG 6‐marker panel with greater CRC‐specificity was also observed among 9% of controls compared to 17% of CRC cases, corresponding to a significantly increased CRC risk (OR: 2.17, 95% CI: 1.44–3.27). In this prospective nested case–control study, we observed a positive association between antibody responses to SGG and CRC development in serum samples taken before evident disease onset. Further work is required to establish the possibly etiological significance of these observations and whether SGG serology may be applicable for CRC risk stratification