In-Person Communication Between Radiologists and Acute Care Surgeons Leads to Significant Alterations in Surgical Decision Making

PurposeThe aim of this study was to determine if direct in-person communication between an acute care surgical team and radiologists alters surgical decision making.MethodsInformed consent was waived for this institutional review board-exempt, HIPAA-compliant, prospective quality improvement study. From January 29, 2015 to December 10, 2015, semiweekly rounds lasting approximately 60 min were held between the on-call acute care surgery team (attending surgeon, chief resident, and residents) and one of three expert abdominal radiologists. A comprehensive imaging review was performed of recent and comparison examinations for cases selected by the surgeons in which medical and/or surgical decision making was pending. All reviewed examinations had available finalized reports known to the surgical team. RADPEER interradiologist concordance scores were assigned to all reviewed examinations. The impression and plan of the attending surgeon were recorded before and after each in-person review.ResultsOne hundred patients were reviewed with 11 attending surgeons. The in-person meetings led to changes in surgeons’ diagnostic impressions in 43% (43 of 100) and changes in medical and/or surgical planning in 43% (43 of 100; 20 acute changes, 23 nonacute changes, 19 changes in operative management) of cases. There were major discrepancies (RADPEER score ≥3) between the impression of the reviewing radiologist and the written report in 11% of cases (11 of 100).ConclusionsTargeted in-person collaboration between radiologists and acute care surgeons is associated with substantial and frequent changes in patient management, even when the original written report contains all necessary data. The primary mechanism seems to be promotion of a shared mental model that facilitates the exchange of complex information.     

Prediction of spurious HLA class II typing results using probabilistic classification

While modern high-throughput sequence-based HLA genotyping methods generally provide highly accurate typing results, artefacts may nonetheless arise for numerous reasons, such as sample contamination, sequencing errors, read misalignments, or PCR amplification biases. To help detecting spurious typing results, we tested the performance of two probabilistic classifiers (binary logistic regression and random forest models) based on population-specific genotype frequencies. We trained the model using high-resolution typing results for HLA-DRB1, DQB1, and DPB1 from large samples of German, Polish and UK-based donors. The high predictive capacity of the best models replicated both in 10-fold cross-validation for each gene and in using independent evaluation data (AUC 0.820–0.893). While genotype frequencies alone provide enough predictive power to render the model generally useful for highlighting potentially spurious typing results, the inclusion of workflow-specific predictors substantially increases prediction specificity. Low initial DNA concentrations in combination with low-volume PCR reactions form a major source of stochastic error specific to the Fluidigm chip-based workflow at DKMS Life Science Lab. The addition of DNA concentrations as a predictor variable thus substantially increased AUC (0.947–0.959) over purely frequency-based models.     

基于2D电阻抗成像的位置误差和相对数量指数的后处理方法

本文提出了一种基于2D电阻抗成像的位置误差和相对数量指数的后处理方法,用于多种电导率分布的确定、组织成分的识别以及位置信息的确定。此外,还介绍了一种基于现有两种重建算法的混合正则化算法,并将三种重建算法重建的结果进行了比较。结果证明,这种后处理方法可以提高2D电阻抗成像的位置精度和空间分辨率,使得电阻抗成像适用于临床检查和过程监测。     

Identification and estimation of single‐index models with measurement error and endogeneity

Economic variables are often measured with an error and may be endogenous. In this paper, we give new identification results for the ratio of partial effects in linear index models with measurement error and endogeneity. The identification restrictions include independence of covariates and error terms, and the derivative of some conditional mean functions being nonzero. We propose a local polynomial regression estimator to estimate the single‐index parameters. We apply these tools to estimate the labour‐supply elasticity and find that the labour‐supply elasticity for married men is positive, while the coefficients for married women are negative for the full sample and positive for the working sample.     

Medications and the Culture of Safety: Conference Title: At the Precipice of Quality Health Care: The Role of the Toxicologist in Enhancing Patient and Medication Safety Venue ACMT Pre-Meeting Symposium, 2014 North American Congress of Clinical Toxicology,New Orleans,LA

Medication mishaps are a common cause of morbidity and mortality both within and outside of hospitals. While the use of a variety of technologies and techniques have promised to improve these statistics, instead of eliminating errors, new ones have appeared as quickly as old ones have been improved. To truly improve safety across the entire enterprise, we must ensure that we create a culture that is willing to accept that errors occur in normal course of operation to the best of people. Focus must not be on punishment and shame, but rather building a fault tolerant system that maintains safety of both staff and patients.     

Sensitivity of regression calibration to non‐perfect validation data with application to the Norwegian Women and Cancer Study

Measurement error occurs when we observe error‐prone surrogates, rather than true values. It is common in observational studies and especially so in epidemiology, in nutritional epidemiology in particular. Correcting for measurement error has become common, and regression calibration is the most popular way to account for measurement error in continuous covariates. We consider its use in the context where there are validation data, which are used to calibrate the true values given the observed covariates. We allow for the case that the true value itself may not be observed in the validation data, but instead, a so‐called reference measure is observed. The regression calibration method relies on certain assumptions.This paper examines possible biases in regression calibration estimators when some of these assumptions are violated. More specifically, we allow for the fact that (i) the reference measure may not necessarily be an ‘alloyed gold standard’ (i.e., unbiased) for the true value; (ii) there may be correlated random subject effects contributing to the surrogate and reference measures in the validation data; and (iii) the calibration model itself may not be the same in the validation study as in the main study; that is, it is not transportable. We expand on previous work to provide a general result, which characterizes potential bias in the regression calibration estimators as a result of any combination of the violations aforementioned. We then illustrate some of the general results with data from the Norwegian Women and Cancer Study. Copyright © 2015 John Wiley & Sons, Ltd.     

On generalized fixed sequence procedures for controlling the FWER

Testing a sequence of pre‐ordered hypotheses to decide which of these can be rejected or accepted while controlling the familywise error rate (FWER) is of importance in many scientific studies such as clinical trials. In this paper, we first introduce a generalized fixed sequence procedure whose critical values are defined by using a function of the numbers of rejections and acceptances, and which allows follow‐up hypotheses to be tested even if some earlier hypotheses are not rejected. We then construct the least favorable configuration for this generalized fixed sequence procedure and present a sufficient condition for the FWER control under arbitrary dependence. Based on the condition, we develop three new generalized fixed sequence procedures controlling the FWER under arbitrary dependence. We also prove that each generalized fixed sequence procedure can be described as a specific closed testing procedure. Through simulation studies and a clinical trial example, we compare the power performance of these proposed procedures with those of the existing FWER controlling procedures. Finally, when the pairwise joint distributions of the true null p‐values are known, we further improve these procedures by incorporating pairwise correlation information while maintaining the control of the FWER. Copyright © 2015 John Wiley & Sons, Ltd.