Digital Fluoroscopic Navigation for Limb Length Restoration During Anterior Total Hip Arthroplasty.

Background: Restoration of limb length is important in total hip arthroplasty. Clinical evaluation and preoperative templating establish the intended lengthening. The purpose of this study was to assess whether digital fluoroscopic navigation (DF) improved the accuracy of planned lengthening in direct anterior approach total hip arthroplasty (DAA-THA). Methods: Planned lengthening measurements on 100 consecutive unilateral DAA-THA patients, along with patient characteristics, were prospectively collected by 2 surgeons. One surgeon utilized DF to achieve intended length (n = 50), while the other utilized unaided standard fluoroscopy (SF; n = 50). A third surgeon blinded to the procedures assessed actual limb length using an ipsilateral overlay technique on the 6-week postoperative radiograph. The difference between the mean planned and actual limb lengthening stratified by DF and SF was assessed using bivariate and multivariate statistics. Results: The mean (standard deviation) planned lengthening in DF and SF groups was 3.96 (2.1) and 3.47 (2.2) mm, respectively. The mean (standard deviation) actual lengthening in DF and SF groups was 3.11 (4.0) and 0.68 (4.6) mm, respectively. After accounting for age, sex, body mass index, laterality, and the Bone Index, multivariate regression results showed that the average difference between planned and actual limb lengthening in the DF group was significantly lower than that in the SF group (ß = -1.92; 95% confidence interval: -3.51, -0.33; P < .02). A greater percentage of patients in the DF group (66% vs 40%) were within 3 mm of the intended plan (P < .01). Conclusions: Fluoroscopy helps achieve the intended surgical lengthening in DAA-THA. The use of DF resulted in more accurate execution of lengthening.

Population PBPK modeling using parametric and nonparametric methods of the Simcyp Simulator, and Bayesian samplers.

Physiologically-based pharmacokinetic (PBPK) models usually include a large number of parameters whose values are obtained using in vitro to in vivo extrapolation. However, such extrapolations can be uncertain and may benefit from inclusion of evidence from clinical observations via parametric inference. When clinical interindividual variability is high, or the data sparse, it is essential to use a population pharmacokinetics inferential framework to estimate unknown or uncertain parameters. Several approaches are available for that purpose, but their relative advantages for PBPK modeling are unclear. We compare the results obtained using a minimal PBPK model of a canonical theophylline dataset with quasi-random parametric expectation maximization (QRPEM), nonparametric adaptive grid estimation (NPAG), Bayesian Metropolis-Hastings (MH), and Hamiltonian Markov Chain Monte Carlo sampling. QRPEM and NPAG gave consistent population and individual parameter estimates, mostly agreeing with Bayesian estimates. MH simulations ran faster than the others methods, which together had similar performance.

Evolving Patient Perception of Limb Length Discrepancy Following Total Hip Arthroplasty.

BACKGROUND: Limb length discrepancy (LLD) is a known complication of total hip arthroplasty (THA), leading to decreased patient function and satisfaction. It remains unknown how a patient's perception of LLD evolves over time. The aim of this study is to evaluate the relationship between measured and perceived LLD, and to assess whether perceived LLD resolved with time in most patients. METHODS: This study retrospectively reviewed radiographs of 140 consecutive patients undergoing primary THA by a single surgeon via a direct anterior approach, calculating postoperative change in limb length (ΔL). Patient perceptions of LLD were recorded at standard postoperative visit intervals. A P-value of .05 was used to determine statistical significance. RESULTS: Of 130 patients (mean ΔL = +7.9 mm), 22 patients endorsed perceived postoperative LLD and the remainder were asymptomatic (mean ΔL +11.1 mm vs +7.3 mm, P = .03). Seventeen patients reported mild symptoms and 5 reported severe symptoms (mean ΔL +10.2 mm vs +13.8 mm, P = .4). After 1 year, 45% (10) patients reported complete resolution of perceived LLD (mean follow-up 364 days), 18% (4) reported notable improvement, and 36% (8) reported no improvement. Four excluded patients endorsed perceived LLD (2 mild, 2 severe), which resolved after contralateral THA. CONCLUSION: This study noted a correlation between increasing postoperative ΔL and perceived LLD. A majority of patients (63%) experienced either improvement or full resolution of symptoms during the follow-up period. This data may have a role in reassuring the orthopedic surgeon and the patient regarding the natural course of postoperative LLD. Further investigation is needed to help identify risk factors for persistent LLD. LEVEL OF EVIDENCE: Level III (Prognostic).

Quantifying the effect of posterior spinal instrumentation on the MRI signal of adjacent intervertebral discs.

STUDY DESIGN: Ex vivo porcine imaging study. OBJECTIVES: Quantitatively evaluate change in MRI signal at the discs caudal to spinal fusion instrumentation. Individuals who receive posterior spinal instrumentation are at risk of developing accelerated disc degeneration at adjacent levels. Degeneration is associated with a loss of biochemical composition and mechanical integrity of the disc, which can be noninvasively assessed through quantitative T2* (qT2*) MRI techniques. However, qT2* is sensitive to magnetic susceptibility introduced by metal. METHODS: Nine ex vivo porcine lumbar specimens were imaged with 3 T MRI. Fast spin-echo T2-weighted (T2w) images and gradient-echo qT2* maps were acquired, both without and with posterior spinal fusion instrumentation. Average T2* relaxation times of the nuclei pulposi (NP) were measured at the adjacent and sub-adjacent discs and measurements were compared using t tests before and after instrumentation. The size of the signal void and metal artifact were determined (modified ASTM F2119-07) within the vertebral body and spinal cord for both MRI sequences. The relationship between T2* signal loss and distance from the instrumentation was evaluated using Pearson's correlation. RESULTS: There was no significant difference between adjacent and sub-adjacent NP T2* relaxation time prior to instrumentation (p = 0.86). Following instrumentation, there was a significant decrease in the T2* relaxation time at the adjacent NP (average = 20%, p = 0.02), and no significant difference at the sub-adjacent NP (average = - 3%, p = 0.30). Furthermore, there was a significant negative correlation between signal loss and distance to disc (r = - 0.61, p < 0.01). CONCLUSIONS: Spinal fusion instrumentation interferes with T2* relaxation time measurements at the adjacent disc but not at the sub-adjacent discs. However, there is sufficient signal at the adjacent disc to quantify changes in the T2* relaxation time following spinal fusion. Hence, baseline MRI scan following spinal fusion surgery are required to interpret and track changes in disc health at the caudal discs. LEVEL OF EVIDENCE: N/A.

An Algorithm for Nonparametric Estimation of a Multivariate Mixing Distribution with Applications to Population Pharmacokinetics.

Population pharmacokinetic (PK) modeling has become a cornerstone of drug development and optimal patient dosing. This approach offers great benefits for datasets with sparse sampling, such as in pediatric patients, and can describe between-patient variability. While most current algorithms assume normal or log-normal distributions for PK parameters, we present a mathematically consistent nonparametric maximum likelihood (NPML) method for estimating multivariate mixing distributions without any assumption about the shape of the distribution. This approach can handle distributions with any shape for all PK parameters. It is shown in convexity theory that the NPML estimator is discrete, meaning that it has finite number of points with nonzero probability. In fact, there are at most N points where N is the number of observed subjects. The original infinite NPML problem then becomes the finite dimensional problem of finding the location and probability of the support points. In the simplest case, each point essentially represents the set of PK parameters for one patient. The probability of the points is found by a primal-dual interior-point method; the location of the support points is found by an adaptive grid method. Our method is able to handle high-dimensional and complex multivariate mixture models. An important application is discussed for the problem of population pharmacokinetics and a nontrivial example is treated. Our algorithm has been successfully applied in hundreds of published pharmacometric studies. In addition to population pharmacokinetics, this research also applies to empirical Bayes estimation and many other areas of applied mathematics. Thereby, this approach presents an important addition to the pharmacometric toolbox for drug development and optimal patient dosing.

Mycobacteriumabscessus-associated vertebral osteomyelitis in an immunocompetent patient: a rare case report and literature review.

Introduction: Vertebral osteomyelitis (VO) is an uncommon infection with Staphylococcus aureus as the most commonly implicated organism. VO caused by nontuberculous mycobacteria (NTM) such as Mycobacteriumabscessus (M. abscesscus) is exceedingly rare with only eight cases reported in literature. Case presentation: We report a rare case of an 82-year-old male with a remote history of trauma who was diagnosed with NTM vertebral osteomyelitis. The patient initially underwent a vertebroplasty of T12 and kyphoplasty of L1 for pathologic compression fractures. Subsequent cultures revealed M. abscessus. The patient further underwent an anterior T12-L2 corpectomy and debridement with instrumented fusion, as well as a posterior T9-L4 instrumentation and fusion. He received multi-agent antibiotic therapy; however, was ultimately unable to tolerate the aggressive treatment regimen and his prolonged postoperative course. Discussion: Nontuberculous mycobacteria vertebral osteomyelitis is exceedingly rare. NTM vertebral osteomyelitis is challenging to treat. Surgical management plays a limited role in early VO, but is the mainstay treatment in chronic VO. Early recognition of the condition and shared patient management with multidisciplinary teams is key to successfully treating cases of NTM VO.

The 100 most cited papers in spinal deformity surgery: a bibliometric analysis.

Spinal deformity is a condition that has been recognized for many millennia. There have been major advances in the treatment of spinal deformity in recent years and studies outlining new ideas can inspire others to further advance the speciality. The number of citations a paper receives may indicate the influence of that paper. It is therefore important that we evaluate and analyze the most cited works in our field. The aim of this study is to identify the 100 most cited papers relevant to spinal deformity surgery in the literature. A search through the Thomson Reuters Web of Science™ for citations related to spinal deformity surgery was performed. The number of citations, mean citation number (total number citations/years since publication), journal, authors, year of publication and country of origin of the top 100 papers was recorded. The top 100 papers were cited a combined 17,646 times, ranging from 453 to 112. The majority of papers originated from the United States (71) and were published in 20 different journals. The decade 1990-1999 was the most prolific, with 36 of the 100 papers published during this time. Papers pertaining to the management of scoliosis (49) were the most common. This study identifies the top 100 most cited papers in the field of spinal deformity surgery. While citation is not a specific marker of the scientific quality of a paper, it is a surrogate for the influence a paper has had on the orthopedic community. This list of papers provides an invaluable resource for both those in training and those actively practicing and involved in the further development of spinal deformity surgery.

Two general methods for population pharmacokinetic modeling: non-parametric adaptive grid and non-parametric Bayesian.

Population pharmacokinetic (PK) modeling methods can be statistically classified as either parametric or nonparametric (NP). Each classification can be divided into maximum likelihood (ML) or Bayesian (B) approaches. In this paper we discuss the nonparametric case using both maximum likelihood and Bayesian approaches. We present two nonparametric methods for estimating the unknown joint population distribution of model parameter values in a pharmacokinetic/pharmacodynamic (PK/PD) dataset. The first method is the NP Adaptive Grid (NPAG). The second is the NP Bayesian (NPB) algorithm with a stick-breaking process to construct a Dirichlet prior. Our objective is to compare the performance of these two methods using a simulated PK/PD dataset. Our results showed excellent performance of NPAG and NPB in a realistically simulated PK study. This simulation allowed us to have benchmarks in the form of the true population parameters to compare with the estimates produced by the two methods, while incorporating challenges like unbalanced sample times and sample numbers as well as the ability to include the covariate of patient weight. We conclude that both NPML and NPB can be used in realistic PK/PD population analysis problems. The advantages of one versus the other are discussed in the paper. NPAG and NPB are implemented in R and freely available for download within the Pmetrics package from www.lapk.org.

Differential modulation of the oligodendrocyte transcriptome by sonic hedgehog and bone morphogenetic protein 4 via opposing effects on histone acetylation.

Differentiation of oligodendrocyte progenitor cells (OPCs) into mature oligodendrocytes is regulated by the interplay between extrinsic signals and intrinsic epigenetic determinants. In this study, we analyze the effect that the extracellular ligands sonic hedgehog (Shh) and bone morphogenetic protein 4 (BMP4), have on histone acetylation and gene expression in cultured OPCs. Shh treatment favored the progression toward oligodendrocytes by decreasing histone acetylation and inducing peripheral chromatin condensation. BMP4 treatment, in contrast, inhibited the progression toward oligodendrocytes and favored astrogliogenesis by favoring global histone acetylation and retaining euchromatin. Pharmacological treatment or silencing of histone deacetylase 1 (Hdac1) or histone deacetylase 2 (Hdac2) in OPCs did not affect BMP4-dependent astrogliogenesis, while it prevented Shh-induced oligodendrocyte differentiation and favored the expression of astrocytic genes. Transcriptional profiling of treated OPCs, revealed that BMP4-inhibition of oligodendrocyte differentiation was accompanied by increased levels of Wnt (Tbx3) and Notch-target genes (Jag1, Hes1, Hes5, Hey1, and Hey2), decreased recruitment of Hdac and increased histone acetylation at these loci. Similar upregulation of Notch-target genes and increased histone acetylation were observed in the corpus callosum of mice infused with BMP4 during cuprizone-induced demyelination. We conclude that Shh and Bmp4 differentially regulate histone acetylation and chromatin structure in OPCs and that BMP4 acts as a potent inducer of gene expression, including Notch and Wnt target genes, thereby enhancing the crosstalk among signaling pathways that are known to inhibit myelination and repair.

A variable cytoplasmic domain segment is necessary for γ-protocadherin trafficking and tubulation in the endosome/lysosome pathway.

Clustered protocadherins (Pcdhs) are arranged in gene clusters (α, ß, and γ) with variable and constant exons. Variable exons encode cadherin and transmembrane domains and ~90 cytoplasmic residues. The 14 Pcdh-αs and 22 Pcdh-γs are spliced to constant exons, which, for Pcdh-γs, encode ~120 residues of an identical cytoplasmic moiety. Pcdh-γs participate in cell-cell interactions but are prominently intracellular in vivo, and mice with disrupted Pcdh-γ genes exhibit increased neuronal cell death, suggesting nonconventional roles. Most attention in terms of Pcdh-γ intracellular interactions has focused on the constant domain. We show that the variable cytoplasmic domain (VCD) is required for trafficking and organelle tubulation in the endolysosome system. Deletion of the constant cytoplasmic domain preserved the late endosomal/lysosomal trafficking and organelle tubulation observed for the intact molecule, whereas deletion or excision of the VCD or replacement of the Pcdh-γA3 cytoplasmic domain with that from Pcdh-α1 or N-cadherin dramatically altered trafficking. Truncations or internal deletions within the VCD defined a 26-amino acid segment required for trafficking and tubulation in the endolysosomal pathway. This active VCD segment contains residues that are conserved in Pcdh-γA and Pcdh-γB subfamilies. Thus the VCDs of Pcdh-γs mediate interactions critical for Pcdh-γ trafficking.

γ-protocadherins are enriched and transported in specialized vesicles associated with the secretory pathway in neurons.

Gamma protocadherins (Pcdh-γs) resemble classical cadherins and have the potential to engage in cell-cell interactions with homophilic properties. Emerging evidence suggests non-conventional roles for some protocadherins in neural development. We sought to determine whether Pcdh-γ trafficking in neurons is consistent with an intracellular role for these molecules. Here we show that, in contrast to the largely surface localization of classical cadherins, endogenous Pcdh-γs are primarily intracellular in rat neurons in vivo and are equally distributed within organelles of subsynaptic dendritic and axonal compartments. A strikingly higher proportion of Pcdh-γ-containing organelles in synaptic compartments was observed at postnatal day 16. To determine the origin of Pcdh-γ-trafficking organelles, we isolated organelles with Pcdh-γ antibody-coupled magnetic beads from brain organelle suspensions. Vesicles with high levels of COPII and endoplasmic reticulum-Golgi intermediate compartment (ERGIC) components were isolated with the Pcdh-γ antibody but not with the classical cadherin antibody. In cultured hippocampal neurons, Pcdh-γ immunolabeling partially overlapped with calnexin- and COPII-positive puncta in dendrites. Mobile Pcdh-γ-GFP profiles dynamically codistributed with a DsRed construct coupled to ER retention signals by live imaging. Pcdh-γ expression correlated with accumulations of tubulovesicular and ER-like organelles in dendrites. Our results are consistent with the possibility that Pcdh-γs could have a unique function within the secretory pathway in addition to their documented surface roles.

Impact of sample size on the performance of multiple-model pharmacokinetic simulations.

Monte Carlo simulations are increasingly used to predict pharmacokinetic variability of antimicrobials in a population. We investigated the sample size necessary to provide robust pharmacokinetic predictions. To obtain reasonably robust predictions, a nonparametric model derived from a sample population size of >/=50 appears to be necessary as the input information.

Parametric and nonparametric population methods: their comparative performance in analysing a clinical dataset and two Monte Carlo simulation studies.

BACKGROUND AND OBJECTIVES: This study examined parametric and nonparametric population modelling methods in three different analyses. The first analysis was of a real, although small, clinical dataset from 17 patients receiving intramuscular amikacin. The second analysis was of a Monte Carlo simulation study in which the populations ranged from 25 to 800 subjects, the model parameter distributions were Gaussian and all the simulated parameter values of the subjects were exactly known prior to the analysis. The third analysis was again of a Monte Carlo study in which the exactly known population sample consisted of a unimodal Gaussian distribution for the apparent volume of distribution (V(d)), but a bimodal distribution for the elimination rate constant (k(e)), simulating rapid and slow eliminators of a drug. METHODS: For the clinical dataset, the parametric iterative two-stage Bayesian (IT2B) approach, with the first-order conditional estimation (FOCE) approximation calculation of the conditional likelihoods, was used together with the nonparametric expectation-maximisation (NPEM) and nonparametric adaptive grid (NPAG) approaches, both of which use exact computations of the likelihood. For the first Monte Carlo simulation study, these programs were also used. A one-compartment model with unimodal Gaussian parameters V(d) and k(e) was employed, with a simulated intravenous bolus dose and two simulated serum concentrations per subject. In addition, a newer parametric expectation-maximisation (PEM) program with a Faure low discrepancy computation of the conditional likelihoods, as well as nonlinear mixed-effects modelling software (NONMEM), both the first-order (FO) and the FOCE versions, were used. For the second Monte Carlo study, a one-compartment model with an intravenous bolus dose was again used, with five simulated serum samples obtained from early to late after dosing. A unimodal distribution for V(d) and a bimodal distribution for k(e) were chosen to simulate two subpopulations of 'fast' and 'slow' metabolisers of a drug. NPEM results were compared with that of a unimodal parametric joint density having the true population parameter means and covariance. RESULTS: For the clinical dataset, the interindividual parameter percent coefficients of variation (CV%) were smallest with IT2B, suggesting less diversity in the population parameter distributions. However, the exact likelihood of the results was also smaller with IT2B, and was 14 logs greater with NPEM and NPAG, both of which found a greater and more likely diversity in the population studied. For the first Monte Carlo dataset, NPAG and PEM, both using accurate likelihood computations, showed statistical consistency. Consistency means that the more subjects studied, the closer the estimated parameter values approach the true values. NONMEM FOCE and NONMEM FO, as well as the IT2B FOCE methods, do not have this guarantee. Results obtained by IT2B FOCE, for example, often strayed visibly away from the true values as more subjects were studied. Furthermore, with respect to statistical efficiency (precision of parameter estimates), NPAG and PEM had good efficiency and precise parameter estimates, while precision suffered with NONMEM FOCE and IT2B FOCE, and severely so with NONMEM FO. For the second Monte Carlo dataset, NPEM closely approximated the true bimodal population joint density, while an exact parametric representation of an assumed joint unimodal density having the true population means, standard deviations and correlation gave a totally different picture. CONCLUSIONS: The smaller population interindividual CV% estimates with IT2B on the clinical dataset are probably the result of assuming Gaussian parameter distributions and/or of using the FOCE approximation. NPEM and NPAG, having no constraints on the shape of the population parameter distributions, and which compute the likelihood exactly and estimate parameter values with greater precision, detected the more likely greater diversity in the parameter values in the population studied. In the first Monte Carlo study, NPAG and PEM had more precise parameter estimates than either IT2B FOCE or NONMEM FOCE, as well as much more precise estimates than NONMEM FO. In the second Monte Carlo study, NPEM easily detected the bimodal parameter distribution at this initial step without requiring any further information. Population modelling methods using exact or accurate computations have more precise parameter estimation, better stochastic convergence properties and are, very importantly, statistically consistent. Nonparametric methods are better than parametric methods at analysing populations having unanticipated non-Gaussian or multimodal parameter distributions.

Bacterial-population responses to drug-selective pressure: examination of garenoxacin's effect on Pseudomonas aeruginosa.

The emergence of resistance to antibiotics is a serious problem often related to suboptimal drug dosing; such suboptimal dosing results in the preferential killing of drug-susceptible microbial subpopulations, allowing amplification of drug-resistant microbial subpopulations. We determined the effect that fluctuating concentrations of quinolone drugs have on both the total population and the resistant subpopulation of Pseudomonas aeruginosa, by employing, over a 48-h period, human pharmacokinetics and multiple regimens in an in vitro-infection model. All data were simultaneously modeled by use of 3 parallel inhomogeneous differential equations. Model parameters were used to derive the minimal, or breakpoint, drug exposure necessary to suppress amplification of the resistant subpopulation. In a prospective-validation study, we found that a drug exposure near to but below the calculated breakpoint amplified the resistant subpopulation, whereas a drug exposure at the breakpoint suppressed it. This approach allows delineation of target drug exposures (area under the concentration/time curve for 24 h : minimal inhibitory concentration [AUC(24) : MIC] = 190) that will suppress amplification of the antibiotic-resistant subpopulation, thereby preserving the susceptibility of target pathogens.

Application of a mathematical model to prevent in vivo amplification of antibiotic-resistant bacterial populations during therapy.

The worldwide increase in the prevalence of multi-antibiotic-resistant bacteria has threatened the physician's ability to provide appropriate therapy for infections. The relationship between antimicrobial drug concentration and infecting pathogen population reduction is of primary interest. Using data derived from mice infected with the bacterium Pseudomonas aeruginosa and treated with a fluoroquinolone antibiotic, a mathematical model was developed that described relationships between antimicrobial drug exposures and changes in drug-susceptible and -resistant bacterial subpopulations at an infection site. Dosing regimens and consequent drug exposures that amplify or suppress the emergence of resistant bacterial subpopulations were identified and prospectively validated. Resistant clones selected in vivo by suboptimal regimens were characterized. No mutations were identified in the quinolone resistance-determining regions of gyrA/B or parC/E. However, all resistant clones demonstrated efflux pump overexpression. At base line, MexAB-OprM, MexCD-OprJ, and MexEF-OprN were represented in the drug-resistant population. After 28 hours of therapy, MexCD-OprJ became the predominant pump expressed in the resistant clones. The likelihood of achieving resistance-suppression exposure in humans with a clinically prescribed antibiotic dose was determined. The methods developed in this study provide insight regarding how mathematical models can be used to identify rational dosing regimens that suppress the amplification of the resistant mutant population.