Citations

Purpose To identify clinical variables that affect a surgeon's decision to recommend arthroscopic partial meniscectomy (APM). Methods Members of 2 orthopaedic specialty societies were invited to participate in an online survey by e‐mail. The survey consisted of surgeon demographics and case scenarios to evaluate clinical decision making for APM. Posterior probabilities were calculated to determine the effect of clinical factors on the likelihood of recommending APM. Results Of the respondents with valid e‐mail addresses, 733 (19.3%) returned a completed survey, but only 533 (14.1%) met the eligibility criteria (treated or referred an APM candidate within the past year). Respondents were aged 46.7 ± 9.4 and had performed a mean of 115 APMs in the previous year. Posterior probabilities for a combination of 6 clinical indicators identified 3 factors that most influenced a surgeon's decision to recommend APM: radiographic findings, McMurray test, and failure of nonoperative management. Conclusions Significant variation exists among practicing orthopaedic surgeons with regard to decision making for APM. The 3 clinical factors that most influenced a surgeon's decision to recommend APM were normal radiographic findings, failed nonoperative treatment, and the presence of positive physical examination findings (i.e., positive McMurray test, joint line tenderness, and effusion). Level of Evidence Level III, decision analysis.

Abstract:BackgroundThe clinical features and outcome of prosthetic joint infection (PJI) among solid organ transplant (SOT) recipients have not been characterized. We performed a retrospective, matched case‐control study to examine potential risk factors.MethodsWe reviewed cases ofPJIamong transplant recipients who were evaluated at the Mayo Clinic between 1989 and 2009. Cases were matched to non‐infected controls based on transplant type, prosthetic joint type, and order of organ transplantation/joint implantation.ResultsAmong 367 patients with both a joint prosthesis and anSOT, there were 12 cases of infection in those receiving immunosuppression. These occurred in 8 renal recipients, 3 liver recipients, and 1 heart transplant recipient. Six subjects had hip and 6 had knee arthroplasty infections. The observed time to prosthesis failure ranged from 0.5 to 148 months after implantation. Gram‐positive bacteria (staphylococci and streptococci) caused the infection in 8 subjects. Two cases were caused by nontuberculous mycobacteria, whereas the remaining 2 cases were culture‐negative in the setting of antimicrobial use. We did not find a statistically significant association between obesity, diabetes mellitus, or antimicrobial prophylaxis (given in the setting of immunosuppression) and development ofPJI. A marginal association was seen betweensurgical site infectionand the risk ofPJI; however, this did not reach statistical significance.ConclusionIn our series, infection was mainly caused by gram‐positive bacterial pathogens, similar to the commonly encountered organisms in the immunocompetent host, although opportunistic pathogens were also isolated.

Abstract Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3,628 breast cancer cases and 5,190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of single-nucleotide polymorphisms (SNP) were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case–control status as the outcome. This analysis was repeated using 10 different cutoff points for the most significant density SNPs (1%–10% representing 5,222–50,899 SNPs). Permutation analysis was also conducted across all 10 cutoff points. The association between risk score and breast cancer was significant for all cutoff points from 3% to 10% of top density SNPs, being most significant for the 6% (2-sided P = 0.002) to 10% (P = 0.001) cutoff points (overall permutation P = 0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR = 1.31; 95% confidence interval (CI), 1.08–1.59] compared with women in the bottom 10%. Together, our results show that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants. Cancer Res; 72(6); 1478–84. ©2012 AACR.

Background: Communication breakdowns are a common cause of adverse events in high consequence industries. It has become increasingly evident that within healthcare systems that poor communication is the causal factor of a large percentage of sentinel events. Methods: All communication exchanges between surgeon and perfusionist were monitored via observation for 18 cardiovascular surgery cases. Breakdowns were analyzed by stage and type of breakdown and a communication protocol designed based on the breakdowns. The protocol was then implemented, and use of the protocol was then monitored for 16 cardiovascular surgery cases. Results: Breakdowns decreased at each stage of cardiovascular surgery. Specific types of breakdowns decreased dramatically, most by more than half. Conclusions: This study shows that protocolizing communication can have a profound impact on communication breakdowns in the cardiovascular surgery operating theatre.

Background: Many researchers have previously explored the correlation between surgical flow disruptions (distractions and interruptions) and error in cardiac surgery, however there is no reliable tool to prospectively categorize surgical flow disruptions and the conditions that predispose a surgical team to error. Methods and Results: Two independent raters of different medical and human factors expertise observed 12 cardiovascular operations and iteratively designed a tool to characterize surgical flow disruptions and the latent factors that contribute to error. Categories to characterize surgical flow disruptions were based on human factors models of human error. Following the design period, both raters observed 10 surgical cases using the tool, to assess validity and inter-rater reliability. Rating agreement (weighted kappa) for each category across the 10 surgeries was moderate to very high, resulting in strong inter-rater reliability for each category on the surgical flow disruption tool (SFDT). Conclusions: This research depicts the development and utility of a tool to analyze surgical flow disruptions in the cardiovascular operating room with satisfactory inter-rater reliability. This tool is an important first step in systematically categorizing and measuring surgical flow disruptions and their impact on patient safety in the operating room.