Predicting complication risk in spine surgery: a prospective analysis of a novel risk assessment tool.

OBJECTIVE The ability to assess the risk of adverse events based on known patient factors and comorbidities would provide more effective preoperative risk stratification. Present risk assessment in spine surgery is limited. An adverse event prediction tool was developed to predict the risk of complications after spine surgery and tested on a prospective patient cohort. METHODS The spinal Risk Assessment Tool (RAT), a novel instrument for the assessment of risk for patients undergoing spine surgery that was developed based on an administrative claims database, was prospectively applied to 246 patients undergoing 257 spinal procedures over a 3-month period. Prospectively collected data were used to compare the RAT to the Charlson Comorbidity Index (CCI) and the American College of Surgeons National Surgery Quality Improvement Program (ACS NSQIP) Surgical Risk Calculator. Study end point was occurrence and type of complication after spine surgery. RESULTS The authors identified 69 patients (73 procedures) who experienced a complication over the prospective study period. Cardiac complications were most common (10.2%). Receiver operating characteristic (ROC) curves were calculated to compare complication outcomes using the different assessment tools. Area under the curve (AUC) analysis showed comparable predictive accuracy between the RAT and the ACS NSQIP calculator (0.670 [95% CI 0.60-0.74] in RAT, 0.669 [95% CI 0.60-0.74] in NSQIP). The CCI was not accurate in predicting complication occurrence (0.55 [95% CI 0.48-0.62]). The RAT produced mean probabilities of 34.6% for patients who had a complication and 24% for patients who did not (p = 0.0003). The generated predicted values were stratified into low, medium, and high rates. For the RAT, the predicted complication rate was 10.1% in the low-risk group (observed rate 12.8%), 21.9% in the medium-risk group (observed 31.8%), and 49.7% in the high-risk group (observed 41.2%). The ACS NSQIP calculator consistently produced complication predictions that underestimated complication occurrence: 3.4% in the low-risk group (observed 12.6%), 5.9% in the medium-risk group (observed 34.5%), and 12.5% in the high-risk group (observed 38.8%). The RAT was more accurate than the ACS NSQIP calculator (p = 0.0018). CONCLUSIONS While the RAT and ACS NSQIP calculator were both able to identify patients more likely to experience complications following spine surgery, both have substantial room for improvement. Risk stratification is feasible in spine surgery procedures; currently used measures have low accuracy.

Predicting Occurrence of Spine Surgery Complications Using "Big Data" Modeling of an Administrative Claims Database.

BACKGROUND: Postoperative metrics are increasingly important in determining standards of quality for physicians and hospitals. Although complications following spinal surgery have been described, procedural and patient variables have yet to be incorporated into a predictive model of adverse-event occurrence. We sought to develop a predictive model of complication occurrence after spine surgery. METHODS: We used longitudinal prospective data from a national claims database and developed a predictive model incorporating complication type and frequency of occurrence following spine surgery procedures. We structured our model to assess the impact of features such as preoperative diagnosis, patient comorbidities, location in the spine, anterior versus posterior approach, whether fusion had been performed, whether instrumentation had been used, number of levels, and use of bone morphogenetic protein (BMP). We assessed a variety of adverse events. Prediction models were built using logistic regression with additive main effects and logistic regression with main effects as well as all 2 and 3-factor interactions. Least absolute shrinkage and selection operator (LASSO) regularization was used to select features. Competing approaches included boosted additive trees and the classification and regression trees (CART) algorithm. The final prediction performance was evaluated by estimating the area under a receiver operating characteristic curve (AUC) as predictions were applied to independent validation data and compared with the Charlson comorbidity score. RESULTS: The model was developed from 279,135 records of patients with a minimum duration of follow-up of 30 days. Preliminary assessment showed an adverse-event rate of 13.95%, well within norms reported in the literature. We used the first 80% of the records for training (to predict adverse events) and the remaining 20% of the records for validation. There was remarkable similarity among methods, with an AUC of 0.70 for predicting the occurrence of adverse events. The AUC using the Charlson comorbidity score was 0.61. The described model was more accurate than Charlson scoring (p < 0.01). CONCLUSIONS: We present a modeling effort based on administrative claims data that predicts the occurrence of complications after spine surgery. CLINICAL RELEVANCE: We believe that the development of a predictive modeling tool illustrating the risk of complication occurrence after spine surgery will aid in patient counseling and improve the accuracy of risk modeling strategies.

Risk of cardiovascular events associated with current exposure to HIV antiretroviral therapies in a US veteran population.

BACKGROUND: To characterize the association of antiretroviral drug combinations on risk of cardiovascular events. METHODS: Certain antiretroviral medications for human immunodeficiency virus (HIV) have been implicated in increasing risk of cardiovascular disease. However, antiretroviral drugs are typically prescribed in combination. We characterized the association of current exposure to antiretroviral drug combinations on risk of cardiovascular events including myocardial infarction, stroke, percutaneous coronary intervention, and coronary artery bypass surgery. We used the Veterans Health Administration Clinical Case Registry to analyze data from 24 510 patients infected with HIV from January 1996 through December 2009. We assessed the association of current exposure to 15 antiretroviral drugs and 23 prespecified combinations of agents on the risk of cardiovascular event by using marginal structural models and Cox models extended to accommodate time-dependent variables. RESULTS: Over 164 059 person-years of follow-up, 934 patients had a cardiovascular event. Current exposure to abacavir, efavirenz, lamivudine, and zidovudine was significantly associated with increased risk of cardiovascular event, with odds ratios ranging from 1.40 to 1.53. Five combinations were significantly associated with increased risk of cardiovascular event, all of which involved lamivudine. One of these-efavirenz, lamivudine, and zidovudine-was the second most commonly used combination and was associated with a risk of cardiovascular event that is 1.60 times that of patients not currently exposed to the combination (odds ratio = 1.60, 95% confidence interval, 1.25-2.04). CONCLUSIONS: In the VA cohort, exposure to both individual drugs and drug combinations was associated with modestly increased risk of a cardiovascular event.

Assessing gene-level translational control from ribosome profiling.

MOTIVATION: The translational landscape of diverse cellular systems remains largely uncharacterized. A detailed understanding of the control of gene expression at the level of messenger RNA translation is vital to elucidating a systems-level view of complex molecular programs in the cell. Establishing the degree to which such post-transcriptional regulation can mediate specific phenotypes is similarly critical to elucidating the molecular pathogenesis of diseases such as cancer. Recently, methods for massively parallel sequencing of ribosome-bound fragments of messenger RNA have begun to uncover genome-wide translational control at codon resolution. Despite its promise for deeply characterizing mammalian proteomes, few analytical methods exist for the comprehensive analysis of this paired RNA and ribosome data. RESULTS: We describe the Babel framework, an analytical methodology for assessing the significance of changes in translational regulation within cells and between conditions. This approach facilitates the analysis of translation genome-wide while allowing statistically principled gene-level inference. Babel is based on an errors-in-variables regression model that uses the negative binomial distribution and draws inference using a parametric bootstrap approach. We demonstrate the operating characteristics of Babel on simulated data and use its gene-level inference to extend prior analyses significantly, discovering new translationally regulated modules under mammalian target of rapamycin (mTOR) pathway signaling control.

Parent-specific copy number in paired tumor-normal studies using circular binary segmentation.

MOTIVATION: High-throughput techniques facilitate the simultaneous measurement of DNA copy number at hundreds of thousands of sites on a genome. Older techniques allow measurement only of total copy number, the sum of the copy number contributions from the two parental chromosomes. Newer single nucleotide polymorphism (SNP) techniques can in addition enable quantifying parent-specific copy number (PSCN). The raw data from such experiments are two-dimensional, but are unphased. Consequently, inference based on them necessitates development of new analytic methods. METHODS: We have adapted and enhanced the circular binary segmentation (CBS) algorithm for this purpose with focus on paired test and reference samples. The essence of paired parent-specific CBS (Paired PSCBS) is to utilize the original CBS algorithm to identify regions of equal total copy number and then to further segment these regions where there have been changes in PSCN. For the final set of regions, calls are made of equal parental copy number and loss of heterozygosity (LOH). PSCN estimates are computed both before and after calling. RESULTS: The methodology is evaluated by simulation and on glioblastoma data. In the simulation, PSCBS compares favorably to established methods. On the glioblastoma data, PSCBS identifies interesting genomic regions, such as copy-neutral LOH. AVAILABILITY: The Paired PSCBS method is implemented in an open-source R package named PSCBS, available on CRAN (http://cran.r-project.org/).

New models and online calculator for predicting non-sentinel lymph node status in sentinel lymph node positive breast cancer patients.

BACKGROUND: Current practice is to perform a completion axillary lymph node dissection (ALND) for breast cancer patients with tumor-involved sentinel lymph nodes (SLNs), although fewer than half will have non-sentinel node (NSLN) metastasis. Our goal was to develop new models to quantify the risk of NSLN metastasis in SLN-positive patients and to compare predictive capabilities to another widely used model. METHODS: We constructed three models to predict NSLN status: recursive partitioning with receiver operating characteristic curves (RP-ROC), boosted Classification and Regression Trees (CART), and multivariate logistic regression (MLR) informed by CART. Data were compiled from a multicenter Northern California and Oregon database of 784 patients who prospectively underwent SLN biopsy and completion ALND. We compared the predictive abilities of our best model and the Memorial Sloan-Kettering Breast Cancer Nomogram (Nomogram) in our dataset and an independent dataset from Northwestern University. RESULTS: 285 patients had positive SLNs, of which 213 had known angiolymphatic invasion status and 171 had complete pathologic data including hormone receptor status. 264 (93%) patients had limited SLN disease (micrometastasis, 70%, or isolated tumor cells, 23%). 101 (35%) of all SLN-positive patients had tumor-involved NSLNs. Three variables (tumor size, angiolymphatic invasion, and SLN metastasis size) predicted risk in all our models. RP-ROC and boosted CART stratified patients into four risk levels. MLR informed by CART was most accurate. Using two composite predictors calculated from three variables, MLR informed by CART was more accurate than the Nomogram computed using eight predictors. In our dataset, area under ROC curve (AUC) was 0.83/0.85 for MLR (n = 213/n = 171) and 0.77 for Nomogram (n = 171). When applied to an independent dataset (n = 77), AUC was 0.74 for our model and 0.62 for Nomogram. The composite predictors in our model were the product of angiolymphatic invasion and size of SLN metastasis, and the product of tumor size and square of SLN metastasis size. CONCLUSION: We present a new model developed from a community-based SLN database that uses only three rather than eight variables to achieve higher accuracy than the Nomogram for predicting NSLN status in two different datasets.

Orthopaedic surgery core curriculum: foot and ankle reconstruction.

BACKGROUND: The purpose of this study was to develop a core curriculum for orthopaedic surgery and to conduct a national survey to assess the importance of 281 curriculum items. Attention was focused on 45 items pertaining to the foot and ankle. METHODS: A 281-item curriculum was developed. A content review and cross-sectional survey of a random selection of orthopaedic surgeons with primary nonacademic affiliations was completed. Data were analyzed descriptively and quantitatively using histograms, modified Hotelling's T(2)-statistic, and the Benjamini-Hochberg procedure. Our analyses assumed that each respondent answered questions independently of the answers of any other respondent but that the answers to different questions by the same respondent might be dependent. RESULTS: Of the 156 orthopaedic surgeons contacted, 131 (86%) participated in this study. Eighty-two percent (37 of 45) of the items were ranked by respondents with an average mean score higher than 3.5/4.0 and 42 higher than 3.0/40, thus suggesting that 93% of the items are important or probably important to know by the end of residency (p

Orthopaedic surgery core curriculum: the spine.

OBJECTIVE: To develop a core curriculum for orthopaedic surgery and to conduct a national survey to assess the importance of 281 items in the curriculum. Attention was focused specifically on 24 items pertaining to the curriculum that are pertinent to the spine. STUDY DESIGN: A cross-sectional survey of a random sample of orthopaedic surgeons whose primary affiliation was non-academic, representing the provinces and territories of Canada METHODS: A questionnaire containing 281 items was developed. A random group of 131 (out of 156) orthopaedic surgeons whose primary affiliation is non-academic completed the questionnaire. The data were analysed quantitatively using average mean scores, histograms, the modified Hotelling's T2 test and the Benjimini-Hochberg procedure. RESULTS: 131 of 156 (84%) orthopaedic surgeons participated, in this study. 14 of 24 items were ranked at no less than 3 out of 4 thus suggesting that 58% of the items are important or probably important to know by the end of residency (SD< or =0.07). Residents need to learn the diagnosis and principles of managing patients with common conditions of the spine. CONCLUSIONS: The study shows, with reliable statistical evidence, that orthopaedic residents are no longer expected to be able to perform spinal fusions with proficiency on completion of residency. Is the exposure to surgical spine problems and the ability to be comfortable with operating expectations specific to the fellowship level? If so, the focus during residency or increasing accredited spine fellowships needs to be addressed to ensure that enough spine surgeons are educated to meet the future healthcare demands projected for Canada.

Genome-wide linkage scans for loci affecting total cholesterol, HDL-C, and triglycerides: the Family Blood Pressure Program.

Atherosclerosis accounts for 75% of all deaths from cardiovascular disease and includes coronary heart disease (CHD), stroke, and other diseases of the arteries. More than half of all CHD is attributable to abnormalities in levels and metabolism of lipids. To locate genes that affect total cholesterol, high density lipoprotein cholesterol (HDL-C), and triglycerides, genome-wide linkage scans for quantitative trait loci were performed using variance components methods as implemented in SOLAR on a large diverse sample recruited as part of the Family Blood Pressure Program. Phenotype and genetic marker data were available for 9,299 subjects in 2,953 families for total cholesterol, 8,668 subjects in 2,736 families for HDL, and 7,760 subjects in 2,499 families for triglycerides. Mean lipid levels were adjusted for the effects of sex, age, age2, age-by-sex interaction, body mass index, smoking status, and field center. HDL-C and triglycerides were further adjusted for average total alcoholic drinks per week and estrogen use. Significant linkage was found for total cholesterol on chromosome 2 (LOD=3.1 at 43 cM) in Hispanics and for HDL-C on chromosome 3 (LOD=3.0 at 182 cM) and 12 (LOD=3.5 at 124 cM) in Asians. In addition, there were 13 regions that showed suggestive linkage (LOD >or= 2.0); 7 for total cholesterol, 4 for HDL, and 2 for triglycerides. The identification of these loci affecting lipid phenotypes and the apparent congruence with previous linkage results provides increased support that these regions contain genes influencing lipid levels.

A polymorphism in the beta1 adrenergic receptor is associated with resting heart rate.

Resting heart rate is significantly associated with cardiovascular morbidity and mortality. However, the extent to which resting heart rate is genetically determined is poorly understood, and no genes have been found that contribute to variation in resting heart rate. Because signaling through the beta1 adrenergic receptor is a key determinant of cardiac function, we tested whether polymorphisms in this receptor are associated with resting heart rate. A cohort of >1,000 individuals of Chinese and Japanese descent, from nuclear families, was genotyped for two polymorphisms, resulting in a serine/glycine substitution at amino acid 49 (Ser49Gly) and an arginine/glycine substitution at residue 389 (Arg389Gly), in the beta1 adrenergic receptor. For comparison, polymorphisms in the beta2 and beta3 adrenergic receptors were also evaluated. The Ser49Gly polymorphism was significantly associated (P=.0004) with resting heart rate, independent of other variables, such as body-mass index, age, sex, ethnicity, exercise, smoking, alcohol intake, hypertension status, and treatment with beta blockers. The data support an additive model in which individuals heterozygous for the Ser49Gly polymorphism had mean heart rates intermediate to those of either type of homozygote, with Ser homozygotes having the highest mean heart rate and with Gly homozygotes having the lowest. Neither the Arg389Gly polymorphism in the beta1 adrenergic receptor nor polymorphisms in the beta2 and beta3 adrenergic receptors were associated with resting heart rate. The heritability of heart rate was 39.7% +/- 7.1% (P<10-7).