Safety of overlapping inpatient orthopaedic surgery: A multicenter study

BackgroundAlthough overlapping surgery is used to maximize efficiency, more empirical data are needed to guide patient safety. We conducted a retrospective cohort study to evaluate the safety of overlapping inpatient orthopaedic surgery, as judged by the occurrence of perioperative complications.MethodsAll inpatient orthopaedic surgical procedures performed at 5 academic institutions from January 1, 2015, to December 31, 2015, were included. Overlapping surgery was defined as 2 skin incisions open simultaneously for 1 surgeon. In comparing patients who underwent overlapping surgery with those who underwent non-overlapping surgery, the primary outcome was the occurrence of a perioperative complication within 30 days of the surgical procedure, and secondary outcomes included all-cause 30-day readmission, length of stay, and mortality. To determine if there was an association between overlapping surgery and a perioperative complication, we tested for non-inferiority of overlapping surgery, assuming a null hypothesis of an increased risk of 50%. We used an inverse probability of treatment weighted regression model adjusted for institution, procedure type, demographic characteristics (age, sex, race, comorbidities), admission type, admission severity of illness, and clustering by surgeon.ResultsAmong 14,135 cases, the frequency of overlapping surgery was 40%. The frequencies of perioperative complications were 1% in the overlapping surgery group and 2% in the non-overlapping surgery group. The overlapping surgery group was non-inferior to the non-overlapping surgery group (odds ratio [OR], 0.61 [90% confidence interval (CI), 0.45 to 0.83]; p < 0.001), with reduced odds of perioperative complications (OR, 0.61 [95% CI, 0.43 to 0.88]; p = 0.009). For secondary outcomes, there was a significantly lower chance of all-cause 30-day readmission in the overlapping surgery group (OR, 0.67 [95% CI, 0.52 to 0.87]; p = 0.003) and shorter length of stay (e, 0.94 [95% CI, 0.89 to 0.99]; p = 0.012). There was no difference in mortality.ConclusionsOur results suggest that overlapping inpatient orthopaedic surgery does not introduce additional perioperative risk for the complications that we evaluated. The suitability of this practice should be determined by individual surgeons on a case-by-case basis with appropriate informed consent.Level of evidenceTherapeutic Level III. See Instructions for Authors for a complete description of levels of evidence

Modeling Anti-HIV-1 HSPC-Based Gene Therapy in Humanized Mice Previously Infected with HIV-1.

Investigations of anti-HIV-1 human hematopoietic stem/progenitor cell (HSPC)-based gene therapy have been performed by HIV-1 challenge after the engraftment of gene-modified HSPCs in humanized mouse models. However, the clinical application of gene therapy is to treat HIV-1-infected patients. Here, we developed a new method to investigate an anti-HIV-1 HSPC-based gene therapy in humanized mice previously infected with HIV-1. First, humanized mice were infected with HIV-1. When plasma viremia reached >107 copies/mL 3 weeks after HIV-1 infection, the mice were myeloablated with busulfan and transplanted with anti-HIV-1 gene-modified CD34+ HSPCs transduced with a lentiviral vector expressing two short hairpin RNAs (shRNAs) against CCR5 and HIV-1 long terminal repeat (LTR), along with human thymus tissue under the kidney capsule. Anti-HIV-1 vector-modified human CD34+ HSPCs successfully repopulated peripheral blood and lymphoid tissues in HIV-1 previously infected humanized mice. Anti-HIV-1 shRNA vector-modified CD4+ T lymphocytes showed selective advantage in HIV-1 previously infected humanized mice. This new method will be useful for investigations of anti-HIV-1 gene therapy when testing in a more clinically relevant experimental setting

Merging microsatellite data: enhanced methodology and software to combine genotype data for linkage and association analysis

<p>Abstract</p> <p>Background</p> <p>Correctly merged data sets that have been independently genotyped can increase statistical power in linkage and association studies. However, alleles from microsatellite data sets genotyped with different experimental protocols or platforms cannot be accurately matched using base-pair size information alone. In a previous publication we introduced a statistical model for merging microsatellite data by matching allele frequencies between data sets. These methods are implemented in our software MicroMerge version 1 (v1). While MicroMerge v1 output can be analyzed by some genetic analysis programs, many programs can not analyze alignments that do not match alleles one-to-one between data sets. A consequence of such alignments is that codominant genotypes must often be analyzed as phenotypes. In this paper we describe several extensions that are implemented in MicroMerge version 2 (v2).</p> <p>Results</p> <p>Notably, MicroMerge v2 includes a new one-to-one alignment option that creates merged pedigree and locus files that can be handled by most genetic analysis software. Other features in MicroMerge v2 enhance the following aspects of control: 1) optimizing the algorithm for different merging scenarios, such as data sets with very different sample sizes or multiple data sets, 2) merging small data sets when a reliable set of allele frequencies are available, and 3) improving the quantity and 4) quality of merged data. We present results from simulated and real microsatellite genotype data sets, and conclude with an association analysis of three familial dyslipidemia (FD) study samples genotyped at different laboratories. Independent analysis of each FD data set did not yield consistent results, but analysis of the merged data sets identified strong association at locus D11S2002.</p> <p>Conclusion</p> <p>The MicroMerge v2 features will enable merging for a variety of genotype data sets, which in turn will facilitate meta-analyses for powering association analysis.</p

Reasons for cessation of clean intermittent catheterization after spinal cord injury: Results from the Neurogenic Bladder Research Group spinal cord injury registry

IntroductionClean intermittent catheterization (CIC) is recommended for bladder management after spinal cord injury (SCI) since it has the lowest complication rate. However, transitions from CIC to other less optimal strategies, such as indwelling catheters (IDCs) are common. In individuals with SCI who stopped CIC, we sought to determine how individual characteristics affect the bladder‐related quality of life (QoL) and the reasons for CIC cessation.MethodsThe Neurogenic Bladder Research Group registry is an observational study, evaluating neurogenic bladder‐related QoL after SCI. From 1479 participants, those using IDC or urinary conduit were asked if they had ever performed CIC, for how long, and why they stopped CIC. Multivariable regression, among participants discontinuing CIC, established associations between demographics, injury characteristics, and SCI complications with bladder‐related QoL.ResultsThere were 176 participants who had discontinued CIC; 66 (38%) were paraplegic and 110 (63%) were male. The most common reasons for CIC cessation among all participants were inconvenience, urinary leakage, and too many urine infections. Paraplegic participants who discontinued CIC had higher mean age, better fine motor scores, and lower educational attainment and employment. Multivariable regression revealed years since SCI was associated with worse bladder symptoms (neurogenic bladder symptom score), ≥4 urinary tract infections (UTIs) in a year was associated with worse satisfaction and feelings about bladder symptoms (SCI‐QoL difficulties), while tetraplegia was associated better satisfaction and feelings about bladder symptoms (SCI‐QoL difficulties).ConclusionsTetraplegics who have discontinued CIC have an improved QoL compared with paraplegics. SCI individuals who have discontinued CIC and have recurrent UTIs have worse QoL.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153674/1/nau24172_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153674/2/nau24172.pd

Quantification of Cytokeratin 5 mRNA Expression in the Circulation of Healthy Human Subjects and after Lung Transplantation

Circulating epithelial progenitor cells are important for repair of the airway epithelium in a mouse model of tracheal transplantation. We therefore hypothesized that circulating epithelial progenitor cells would also be present in normal human subjects and could be important for repair of the airway after lung injury. As lung transplantation is associated with lung injury, which is severe early on and exacerbated during episodes of infection and rejection, we hypothesized that circulating epithelial progenitor cell levels could predict clinical outcome following lung transplantation.Quantitative Real Time PCR was performed to determine peripheral blood mRNA levels of cytokeratin 5, a previously characterized marker of circulating epithelial progenitor cells. Cytokeratin 5 levels were evaluated in healthy human subjects, in lung transplant recipients immediately post-transplant and serially thereafter, and in heart transplant recipients. All normal human subjects examined expressed cytokeratin 5 in their buffy coat in amounts that were not significantly influenced by age or gender. There was a profound, statistically significant decrease in cytokeratin 5 mRNA expression levels in lung transplant patients compared to healthy human subjects (p = 3.1x10(-13)) and to heart transplant recipients. There was a moderate negative correlation between improved circulating cytokeratin 5 mRNA levels in lung transplant recipients with recovering lung function, as measured by improved FEV1 values (rho = -0.39).Levels of cytokeratin 5 mRNA, a proxy marker for circulating epithelial progenitor cells, inversely correlated with disease status in lung transplant recipients. It may therefore serve as a biomarker of the clinical outcome of lung transplant patients and potentially other patients with airway injury

Predictors of low urinary quality of life in spinal cord injury patients on clean intermittent catheterization

ObjectiveClean intermittent catheterization (CIC) is a preferred method of bladder management for many patients with spinal cord injury (SCI), but long‐term adherence is low. The aim of this study is to identify factors associated with low urinary quality of life (QoL) in SCI adults performing CIC.MethodsOver 1.5 years, 1479 adults with SCI were prospectively enrolled through the Neurogenic Bladder Research Group registry, and 753 on CIC with no prior surgeries were included. Injury characteristics, complications, hand function, and Neurogenic Bladder Symptom Score (NBSS) were analyzed. The NBSS QoL question (overall satisfaction with urinary function) was dichotomized to generate comparative groups (dissatisfied vs neutral/satisfied).ResultsThe cohort was 32.9% female with a median age of 43.2 (18‐86) years, time since the injury of 9.8 (0‐48.2) years, and 69.0% had an injury at T1 or below. Overall 36.1% were dissatisfied with urinary QoL. On multivariable analysis, female gender (odds ratio [OR], 1.63; 95% confidence interval [CI], 1.15‐2.31; P = 0.016), earlier injury (OR, 0.95 per year; 95% CI, 0.93‐0.97; P < 0.001), ≥4 urinary tract infections (UTIs) per year (OR, 2.36; 95% CI, 1.47‐3.81; P = 0.001), and severe bowel dysfunction (OR, 1.42; 95% CI, 1.02‐1.98; P = 0.035) predicted dissatisfaction. Level of injury, fine motor hand function, and caregiver dependence for CIC were not associated with dissatisfaction.ConclusionsIn a mature SCI cohort, physical disability does not predict dissatisfaction with urinary QoL but severe bowel dysfunction and recurrent UTIs have a significant negative impact. With time the rates of dissatisfaction decline but women continue to be highly dissatisfied on CIC and may benefit from early intervention to minimize the burden of CIC on urinary QoL.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149763/1/nau23983.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149763/2/nau23983_am.pd

Integrated Weighted Gene Co-expression Network Analysis with an Application to Chronic Fatigue Syndrome

<p>Abstract</p> <p>Background</p> <p>Systems biologic approaches such as Weighted Gene Co-expression Network Analysis (WGCNA) can effectively integrate gene expression and trait data to identify pathways and candidate biomarkers. Here we show that the additional inclusion of genetic marker data allows one to characterize network relationships as causal or reactive in a chronic fatigue syndrome (CFS) data set.</p> <p>Results</p> <p>We combine WGCNA with genetic marker data to identify a disease-related pathway and its causal drivers, an analysis which we refer to as "Integrated WGCNA" or IWGCNA. Specifically, we present the following IWGCNA approach: 1) construct a co-expression network, 2) identify trait-related modules within the network, 3) use a trait-related genetic marker to prioritize genes within the module, 4) apply an integrated gene screening strategy to identify candidate genes and 5) carry out causality testing to verify and/or prioritize results. By applying this strategy to a CFS data set consisting of microarray, SNP and clinical trait data, we identify a module of 299 highly correlated genes that is associated with CFS severity. Our integrated gene screening strategy results in 20 candidate genes. We show that our approach yields biologically interesting genes that function in the same pathway and are causal drivers for their parent module. We use a separate data set to replicate findings and use Ingenuity Pathways Analysis software to functionally annotate the candidate gene pathways.</p> <p>Conclusion</p> <p>We show how WGCNA can be combined with genetic marker data to identify disease-related pathways and the causal drivers within them. The systems genetics approach described here can easily be used to generate testable genetic hypotheses in other complex disease studies.</p

NEXUS/Physics: An interdisciplinary repurposing of physics for biologists

In response to increasing calls for the reform of the undergraduate science curriculum for life science majors and pre-medical students (Bio2010, Scientific Foundations for Future Physicians, Vision & Change), an interdisciplinary team has created NEXUS/Physics: a repurposing of an introductory physics curriculum for the life sciences. The curriculum interacts strongly and supportively with introductory biology and chemistry courses taken by life sciences students, with the goal of helping students build general, multi-discipline scientific competencies. In order to do this, our two-semester NEXUS/Physics course sequence is positioned as a second year course so students will have had some exposure to basic concepts in biology and chemistry. NEXUS/Physics stresses interdisciplinary examples and the content differs markedly from traditional introductory physics to facilitate this. It extends the discussion of energy to include interatomic potentials and chemical reactions, the discussion of thermodynamics to include enthalpy and Gibbs free energy, and includes a serious discussion of random vs. coherent motion including diffusion. The development of instructional materials is coordinated with careful education research. Both the new content and the results of the research are described in a series of papers for which this paper serves as an overview and context.Comment: 12 page

Protein expression based multimarker analysis of breast cancer samples

<p>Abstract</p> <p>Background</p> <p>Tissue microarray (TMA) data are commonly used to validate the prognostic accuracy of tumor markers. For example, breast cancer TMA data have led to the identification of several promising prognostic markers of survival time. Several studies have shown that TMA data can also be used to cluster patients into clinically distinct groups. Here we use breast cancer TMA data to cluster patients into distinct prognostic groups.</p> <p>Methods</p> <p>We apply weighted correlation network analysis (WGCNA) to TMA data consisting of 26 putative tumor biomarkers measured on 82 breast cancer patients. Based on this analysis we identify three groups of patients with low (5.4%), moderate (22%) and high (50%) mortality rates, respectively. We then develop a simple threshold rule using a subset of three markers (p53, Na-KATPase-β1, and TGF β receptor II) that can approximately define these mortality groups. We compare the results of this correlation network analysis with results from a standard Cox regression analysis.</p> <p>Results</p> <p>We find that the rule-based grouping variable (referred to as WGCNA*) is an independent predictor of survival time. While WGCNA* is based on protein measurements (TMA data), it validated in two independent Affymetrix microarray gene expression data (which measure mRNA abundance). We find that the WGCNA patient groups differed by 35% from mortality groups defined by a more conventional stepwise Cox regression analysis approach.</p> <p>Conclusions</p> <p>We show that correlation network methods, which are primarily used to analyze the relationships between gene products, are also useful for analyzing the relationships between patients and for defining distinct patient groups based on TMA data. We identify a rule based on three tumor markers for predicting breast cancer survival outcomes.</p