VC-dimension of short Presburger formulas

We study VC-dimension of short formulas in Presburger Arithmetic, defined to have a bounded number of variables, quantifiers and atoms. We give both lower and upper bounds, which are tight up to a polynomial factor in the bit length of the formula

Is Preoperative Patient-Reported Health Status Associated with Mortality after Total Hip Replacement?

The influence of comorbidities and worse physical status on mortality following total hip replacement (THR) leads to the idea that patient-reported health status may also be a predictor of mortality. The aim of this study was to investigate the relationship between patient-reported health status before THR and the risk of dying up to 5 years post-operatively. For these analyses, we used register data on 42,862 THR patients with primary hip osteoarthritis operated between 2008 and 2012. The relative survival ratio was calculated by dividing the observed survival in the patient group by age- and sex-adjusted expected survival of the general population. Pre-operative responses to the five EQ-5D-3L (EuroQol Group) dimensions along with age, sex, education status, year of surgery, and hospital type were used as independent variables. Results shown that, as a group, THR patients had a better survival than the general population. Broken down by the five EQ-5D-3L dimensions we observed differentiated survival patters. For all dimensions, those reporting extreme problems had higher mortality than those reporting moderate or no problems. In conclusion, worse health status according to the EQ-5-3L before THR is associated with higher mortality up to five years after surgery. EQ-5D-3L responses may be useful in a multifactorial individualized risk assessment before THR.This article is freely available via Open Access. Click on the Additional Link above to access the full-text via the publisher's site

Up-regulation of cell cycle arrest protein BTG2 correlates with increased overall survival in breast cancer, as detected by immunohistochemistry using tissue microarray

<p>Abstract</p> <p>Background</p> <p>Previous studies have shown that the <it>ADIPOR1</it>, <it>ADORA1</it>, <it>BTG2 </it>and <it>CD46 </it>genes differ significantly between long-term survivors of breast cancer and deceased patients, both in levels of gene expression and DNA copy numbers. The aim of this study was to characterize the expression of the corresponding proteins in breast carcinoma and to determine their correlation with clinical outcome.</p> <p>Methods</p> <p>Protein expression was evaluated using immunohistochemistry in an independent breast cancer cohort of 144 samples represented on tissue microarrays. Fisher's exact test was used to analyze the differences in protein expression between dead and alive patients. We used Cox-regression multivariate analysis to assess whether the new markers predict the survival status of the patients better than the currently used markers.</p> <p>Results</p> <p>BTG2 expression was demonstrated in a significantly lower proportion of samples from dead patients compared to alive patients, both in overall expression (<it>P </it>= 0.026) and cell membrane specific expression (<it>P </it>= 0.013), whereas neither ADIPOR1, ADORA1 nor CD46 showed differential expression in the two survival groups. Furthermore, a multivariate analysis showed that a model containing BTG2 expression in combination with HER2 and Ki67 expression along with patient age performed better than a model containing the currently used prognostic markers (tumour size, nodal status, HER2 expression, hormone receptor status, histological grade, and patient age). Interestingly, BTG2 has previously been described as a tumour suppressor gene involved in cell cycle arrest and p53 signalling.</p> <p>Conclusions</p> <p>We conclude that high-level BTG2 protein expression correlates with prolonged survival in patients with breast carcinoma.</p

Linking Swedish health data registers to establish a research database and a shared decision-making tool in hip replacement.

Sweden offers a unique opportunity to researchers to construct comprehensive databases that encompass a wide variety of healthcare related data. Statistics Sweden and the National Board of Health and Welfare collect individual level data for all Swedish residents that ranges from medical diagnoses to socioeconomic information. In addition to the information collected by governmental agencies the medical profession has initiated nationwide Quality Registers that collect data on specific diagnoses and interventions. The Quality Registers analyze activity within healthcare institutions, with the aims of improving clinical care and fostering clinical research.This article is freely available via Open Access. Click on the Additional Link above to access the full-text via the publisher's site

Variance Inflation Due to Censoring in Survival Probability Estimates

One of the most obvious features of time-to-event data is the occurrence of censoring. Rarely, if ever, studies are conducted until all participants experience the event of interest. Some participants survive beyond the end of follow-up time, some drop out from the studies for various non-study related reasons. During research planning it is paramount to consider the effect of censoring the follow-up times on the estimates. Herein, we look into the possibility of assessingthe loss of information, as measured by the variability of the survival probability estimates under right censoring. We provide the researchers with an easy to use formula to assess the magnitude of variance inflation due to censoring. Additionally, we conducted simulation studies assuming various survival distributions. We conclude that the provided variance inflation estimator can be an accurate practical tool for applied statisticians