37 research outputs found
Bladder cancer index: cross-cultural adaptation into Spanish and psychometric evaluation
BACKGROUND: The Bladder Cancer Index (BCI) is so far the only instrument applicable across all bladder cancer patients, independent of tumor infiltration or treatment applied. We developed a Spanish version of the BCI, and assessed its acceptability and metric properties. METHODS: For the adaptation into Spanish we used the forward and back-translation method, expert panels, and cognitive debriefing patient interviews. For the assessment of metric properties we used data from 197 bladder cancer patients from a multi-center prospective study. The Spanish BCI and the SF-36 Health Survey were self-administered before and 12 months after treatment. Reliability was estimated by Cronbach's alpha. Construct validity was assessed through the multi-trait multi-method matrix. The magnitude of change was quantified by effect sizes to assess responsiveness. RESULTS: Reliability coefficients ranged 0.75-0.97. The validity analysis confirmed moderate associations between the BCI function and bother subscales for urinary (r = 0.61) and bowel (r = 0.53) domains; conceptual independence among all BCI domains (r ≤ 0.3); and low correlation coefficients with the SF-36 scores, ranging 0.14-0.48. Among patients reporting global improvement at follow-up, pre-post treatment changes were statistically significant for the urinary domain and urinary bother subscale, with effect sizes of 0.38 and 0.53. CONCLUSIONS: The Spanish BCI is well accepted, reliable, valid, responsive, and similar in performance compared to the original instrument. These findings support its use, both in Spanish and international studies, as a valuable and comprehensive tool for assessing quality of life across a wide range of bladder cancer patients
Combined clinical and histopathological risk stratification for prediction of (severe) endoscopic postoperative recurrence in patients with Crohn’s disease after ileocolic resection:results from a prospective multicenter cohort study
Objective: This study assessed the association of histopathological features in the resection specimen of CD patients with (severe) endoscopic postoperative recurrence (ePOR) in a large prospective, multicenter cohort study. Summary Background Data: The predictive value of histopathologic features of the intestinal resection specimen for the risk of Crohn’s disease (CD) recurrence after ileocolic (re-)resection (ICR) remains a matter of debate. Methods: CD patients (≥16 years) scheduled for ICR (n=293) were included. Outcome measures were ePOR (modified Rutgeerts’ score ≥i2b) and severe ePOR (≥i3) at six months postoperatively. Histopathological assessment of resection margins and mesentery/mesocolon was performed by expert gastrointestinal pathologists. Logistic regression was performed and ROC curves were delineated to explore the association and accuracy of histopathology with (severe) ePOR. Results: ePOR and severe ePOR was observed in 37% and 9% of patients. Only moderate to severe inflammation at the ileal resection margin (OR 2.5; 95%CI 1.1-5.6) was associated with ePOR in multivariable analysis. Area under the curve for individual histopathological risk factors varied between 0.53-0.58 for ePOR (active inflammation at the resection margins, submucosal plexitis and transmural inflammation) and 0.69-0.71 for severe ePOR (submucosal plexitis, transmural inflammation and mesenteric granulomas). Clinical risk factors alone (active smoking and postoperative prophylactic medication) had an AUC of 0.66 and 0.74 for ePOR and severe ePOR. Combined histopathological and clinical risk stratification increased the AUC up to 0.71 for ePOR and up to 0.79 for severe ePOR. Conclusions: Only moderate to severe inflammation at the ileal margin was independently associated with ePOR. A combined approach of clinical risk stratification and assessment of histopathological features in the resection specimen provides an adequate predictive value for (severe) ePOR after ICR in patients with CD.</p
Telemedicine for management of inflammatory bowel disease (myIBDcoach): a pragmatic, multicentre, randomised controlled trial
Cellular mechanisms in basic and clinical gastroenterology and hepatolog
Exigência nutricional de treonina digestível para galinhas poedeiras no período de 34 a 50 semanas de idade
On-line scheduling of small open shops
Includes bibliographical referencesAvailable from British Library Document Supply Centre- DSC:9261. 954(306) / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo
The effect of bilayer period and degree of unbalancing on magnetron sputtered Cr/CrN nano-multilayer wear and corrosion
Airborne wind retrieval using GPS delay-Doppler maps
Global Navigation Satellite System Reflectometry (GNSSR)
has emerged recently as a promising remote sensing tool
to retrieve various geophysical parameters of Earth’s
surface. GNSS-reflected signals, after being received and
processed by the airborne or space-borne receiver, are
available as delay correlation waveforms or as delay-
Doppler maps. In the case of a rough ocean surface, those
characteristics can be related to the RMS of L-band limited
slopes of the surface waves, and from there to the surface
wind speed. The raw GNSS-reflected signal can be
processed either in real time by the receiver, or can be
recorded and stored onboard and post-processed in a
laboratory. The latter approach leveraging a software
receiver allows more flexibility while processing the raw
data. This work analyzes Delay Doppler Maps (DDM)
obtained as a result of processing of the data collected by the
GPS data logger/software receiver onboard the NOAA
Gulfstream-IV jet aircraft. Thereafter, the DDMs were used
to retrieve surface wind speed employing several different
metrics that characterize the DDM extent in the Doppler
frequency-delay domain. In contrast to previous works in
which winds have been retrieved by fitting the theoretically
modeled curves into measured correlation waveforms, here
we do not rely on any model for the determination. Instead,
the approach is based on a linear regression between DDMs
observables and the wind speeds obtained in simultaneous
GPS dropsonde measurements.Peer Reviewe
