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Objectives: We aimed to evaluate the distribution, clinical presentations and severity of common acute respiratory infections (ARI) viruses in infants across 3 clinical settings., Study Design: In a prospective virus surveillance study, infants under 1 year with fever and/or respiratory symptoms were enrolled from outpatient, emergency department, and inpatient settings from December 16, 2019 through April 30, 2020. Demographic and clinical characteristics were collected through parent/guardian interviews, medical chart abstractions, and follow-up surveys. Nasal swabs were collected and tested for viruses using quantitative reverse-transcription polymerase chain reaction., Results: We enrolled 366 infants and tested nasal swabs on 360 (98%); median age was 6.3 months, 50% male. In total, 295 (82%) had at least 1 virus detected; rhinovirus/enterovirus (RV/EV; 42%), respiratory syncytial virus (RSV; 34%), and influenza (15%) were the most common. RSV was the most frequently detected virus in the inpatient (63%) and emergency department (37%) settings, and RV/EV was most frequently detected virus in the outpatient setting (54%). RSV-positive infants had a lower median age (4.9 months) and were more likely to have respiratory distress, and RV/EV-positive infants were less likely to have respiratory distress. Influenza-positive infants had a higher median age (8 months) and were more likely to have systemic symptoms. RSV infection and younger age were associated with higher odds of hospitalization in multivariable logistic regression., Conclusions: Across 3 clinical settings, and combining virologic, patient, and health-system information, our results highlight the burden of viral ARI among infants. Overall, RSV, RV/EV, and influenza were most commonly detected, with RSV having the highest disease severity., (Copyright © 2021 Elsevier Inc. All rights reserved.)

In cohort studies, non-random medication use can pose barriers to estimation of the natural history trend in a mean biomarker value-namely, the association between a predictor of interest and a biomarker outcome that would be observed in the total absence of biomarker-specific treatment. Common causes of treatment and outcomes are often unmeasured, obscuring our ability to easily account for medication use with assumptions commonly invoked in causal inference such as conditional ignorability. Further, without a high degree of confidence in the availability of a variable satisfying the exclusion restriction, use of instrumental variable approaches may be difficult to justify. Heckman's hybrid model with structural shift (sometimes referred to less specifically as the treatment effects model) can be used to correct endogeneity bias via a homogeneity assumption (i.e., that average treatment effects do not vary across covariates) and parametric specification of a joint model for the outcome and treatment. In recent work, we relaxed the homogeneity assumption by allowing observed covariates to serve as treatment effect modifiers. While this method has been shown to be reasonably robust in settings of cross-sectional data, application of this methodology to settings of longitudinal data remains unexplored. We demonstrate how the assumptions of the treatment effects model can be extended to accommodate clustered data arising from longitudinal studies. Our proposed approach is semi-parametric in nature in that valid inference can be obtained without the need to specify any component of the longitudinal correlation structure. As an illustrative example, we use data from the Multi-Ethnic Study of Atherosclerosis to evaluate trends in low-density lipoprotein by age and gender. Results from a collection of simulation studies, as well as our illustrative example, confirm that our generalization of the treatment effects model can serve as a useful tool to uncover natural history trends in longitudinal data that are obscured by endogenous treatment.

Considerations regarding clinical effectiveness and cost are essential in comparing the overall value of two treatments. There has been growing interest in methodology to integrate cost and effectiveness measures in order to inform policy and promote adequate resource allocation. The net monetary benefit aggregates information on differences in mean cost and clinical outcomes; the cost-effectiveness acceptability curve was developed to characterize the extent to which the strength of evidence regarding net monetary benefit changes with fluctuations in the willingness-to-pay threshold. Methods to derive insights from characteristics of the cost/clinical outcomes besides mean differences remain undeveloped but may also be informative. We propose a novel probabilistic measure of cost-effectiveness based on the stochastic ordering of the individual net benefit distribution under each treatment. Our approach is able to accommodate features frequently encountered in observational data including confounding and censoring, and complements the net monetary benefit in the insights it provides. We conduct a range of simulations to evaluate finite-sample performance and illustrate our proposed approach using simulated data based on a study of endometrial cancer patients.

Background: Parainfluenza virus (PIV) is a leading cause of acute respiratory illness (ARI) in children. However, few studies have characterized the clinical features and outcomes associated with PIV infections among young children in the Middle East., Methods: We conducted hospital-based surveillance for ARI among children < 2 years of age in a large referral hospital in Amman, Jordan. We systematically collected clinical data and respiratory specimens for pathogen detection using reverse transcription polymerase chain reaction. We compared clinical features of PIV-associated ARI among individual serotypes 1, 2, 3, and 4 and among PIV infections compared with other viral ARI and ARI with no virus detected. We also compared the odds of supplemental oxygen use using logistic regression., Results: PIV was detected in 221/3168 (7.0%) children hospitalized with ARI. PIV-3 was the most commonly detected serotype (125/221; 57%). Individual clinical features of PIV infections varied little by individual serotype, although admission diagnosis of 'croup' was only associated with PIV-1 and PIV-2. Children with PIV-associated ARI had lower frequency of cough (71% vs 83%; p < 0.001) and wheezing (53% vs 60% p < 0.001) than children with ARI associated with other viruses. We did not find a significant difference in supplemental oxygen use between children with PIV-associated infections (adjusted odds ratio [aOR] 1.12, 95% CI 0.66-1.89, p = 0.68) and infections in which no virus was detected., Conclusions: PIV is frequently associated with ARI requiring hospitalization in young Jordanian children. Substantial overlap in clinical features may preclude distinguishing PIV infections from other viral infections at presentation.

Background: Acute gastroenteritis (AGE) is a common reason for children to receive medical care. However, the viral etiology of AGE illness is not well described in the post-rotavirus vaccine era, particularly in the outpatient (OP) setting., Methods: Between 2012 and 2015, children 15 days through 17 years old presenting to Vanderbilt Children's Hospital, Nashville, Tennessee, with AGE were enrolled prospectively from the inpatient, emergency department, and OP settings, and stool specimens were collected. Healthy controls (HCs) were enrolled and frequency matched for period, age group, race, and ethnicity. Stool specimens were tested by means of reverse-transcription real-time quantitative polymerase chain reaction for norovirus, sapovirus, and astrovirus RNA and by Rotaclone enzyme immunoassay for rotavirus antigen, followed by polymerase chain reaction verification of antigen detection., Results: A total of 3705 AGE case patients and 1563 HCs were enrolled, among whom 2885 case patients (78%) and 1110 HCs (71%) provided stool specimens that were tested. All 4 viruses were more frequently detected in AGE case patients than in HCs (norovirus, 22% vs 8%, respectively; rotavirus, 10% vs 1%; sapovirus, 10% vs 5%; and astrovirus, 5% vs 2%; P < .001 for each virus). In the OP setting, rates of AGE due to norovirus were higher than rate for the other 3 viruses. Children <5 years old had higher OP AGE rates than older children for all viruses., Conclusions: Norovirus remains the most common virus detected in all settings, occurring nearly twice as frequently as the next most common pathogens, sapovirus and rotavirus. Combined, norovirus, sapovirus, rotavirus, and astrovirus were associated with almost half of all AGE visits and therefore are an important reason for children to receive medical care., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Rising medical costs are an emerging challenge in policy decisions and resource allocation planning. When cumulative medical cost is the outcome, right-censoring induces informative missingness due to heterogeneity in cost accumulation rates across subjects. Inverse-weighting approaches have been developed to address the challenge of informative cost trajectories in mean cost estimation, though these approaches generally ignore post-baseline treatment changes. In post-hysterectomy endometrial cancer patients, data from a linked database of Medicare records and the Surveillance, Epidemiology, and End Results program of the National Cancer Institute reveal substantial within-subject variation in treatment over time. In such a setting, the utility of existing intent-to-treat approaches is generally limited. Estimates of population mean cost under a hypothetical time-varying treatment regime can better assist with resource allocation when planning for a treatment policy change; such estimates must inherently take time-dependent treatment and confounding into account. In this paper, we develop a nested g-computation approach to cost analysis to address this challenge, while accounting for censoring. We develop a procedure to evaluate sensitivity to departures from baseline treatment ignorability. We further conduct a variety of simulations and apply our nested g-computation procedure to two-year costs from endometrial cancer patients.

Objective: To evaluate the clinical features, pathologic features, and prevalence of human papilloma virus (HPV) in squamous cell carcinoma (SCC) of the bladder. SCC of the bladder is known to be associated with conditions that cause chronic inflammation/irritation. The literature is inconsistent regarding the association of HPV with pure SCC of the bladder., Methods: A multi-institutional study identified cases of SCC of the bladder. Pure squamous histology and the absence of urothelial carcinoma in situ were required for inclusion. Clinical and pathologic features were collected, and tissues were evaluated for high-risk HPV using p16 immunohistochemistry and in situ hybridization., Results: We identified 207 cases of SCC of the bladder. Risk factors for bladder cancer included smoking (133/207, 64%) and chronic bladder irritation (83/207, 40%). The majority (155/207, 75%) of patients had > pT2 disease. Mean tumor size was 5.6 ± 3.0 cm and 36/207 (17%) patients had lymph node positive disease. p16 immunohistochemistry was positive in 52/204 (25%) cases but high-risk HPV was identified with in situ hybridization in only 1 (0.5%) case. Tumor size, stage, number of lymph nodes removed, number of positive lymph nodes, lymphovascular invasion, perineural invasion, and positive margins each were associated with cancer-specific mortality when adjusted for demographic factors. A multivariate analysis of variable importance further revealed sex and race as important factors in predicting cancer-specific mortality., Conclusion: SCC of the bladder is an aggressive histologic subtype. Although bladder SCC can express p16, it is not typically associated with high-risk HPV, although rare cases can occur., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: The World Health Organization created the Severe Acute Respiratory Infection (SARI) criteria in 2011 to monitor influenza (flu)-related hospitalization. Many studies have since used the SARI case definition as inclusion criteria for surveillance studies. We sought to determine the sensitivity, specificity, positive predictive value, and negative predictive value of the SARI criteria for detecting ten different respiratory viruses in a Middle Eastern pediatric cohort., Materials and Methods: The data for this study comes from a prospective acute respiratory surveillance study of hospitalized children <2 years in Amman, Jordan from March 16, 2010 to March 31, 2013. Participants were recruited if they had a fever and/or respiratory symptoms. Nasal and throat swabs were obtained and tested by real-time RT-PCR for eleven viruses. Subjects meeting SARI criteria were determined post-hoc. Sensitivity, specificity, positive predictive value, and negative predictive value of the SARI case definition for detecting ten different viruses were calculated and results were stratified by age., Results: Of the 3,175 patients enrolled, 3,164 were eligible for this study, with a median age of 3.5 months, 60.4% male, and 82% virus-positive (44% RSV and 3.8% flu). The sensitivity and specificity of the SARI criteria for detecting virus-positive patients were 44% and 77.9%, respectively. Sensitivity of SARI criteria for any virus was lowest in children <3 months at 22.4%. Removing fever as a criterion improved the sensitivity by 65.3% for detecting RSV in children <3 months; whereas when cough was removed, the sensitivity improved by 45.5% for detecting flu in same age group., Conclusions: The SARI criteria have poor sensitivity for detecting RSV, flu, and other respiratory viruses-particularly in children <3 months. Researchers and policy makers should use caution if using the criteria to estimate burden of disease in children., Competing Interests: N.H. received grants from Sanofi and Quidel and consulting fees for Moderna, and Karius outside the submitted work. J.V.W. reports personal fees from Quidel, personal fees from GlaxoSmithKline outside the submitted work. For the remaining authors, none were declared. This work was supported by the UBS Optimus Foundation; National Institutes of Health: R01AI085062, and the CTSA award UL1TR000445 from the National Center for Advancing Translational Sciences. Its contents are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health.

Previous studies indicate racial/ethnic differences in health care utilization for pediatric atopic dermatitis (AD), but do not account for disease severity impact. We sought to examine the relationship between race/ethnicity and health care utilization, both overall and by specific visit type, while accounting for AD control. A longitudinal cohort study of children with AD in the United States was performed to evaluate the association between race/ethnicity and health care utilization for AD. AD control and health care utilization were assessed biannually. Our study included 7,522 children (34.2% white, 54.2% black, and 11.5% Hispanic) who were followed for a median of 4 years (interquartile range 0.9-8.4 years). After adjusting for sociodemographic and other factors, black and Hispanic children were up to nearly threefold more likely than white children to receive medical care for AD across almost all levels of AD control. Black and Hispanic children had higher odds of primary care and emergency visits compared to whites. Black children with poorly controlled AD were significantly less likely to see a dermatologist than white children with similarly poorly controlled AD (odds ratio = 0.74, 95% confidence interval = 0.64-0.85 for limited control; odds ratio = 0.59, 95% confidence interval = 0.47-0.76 for uncontrolled AD). Together, these findings suggest the presence of racial/ethnic disparities in health care utilization for AD., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

In the modern era, cardiovascular biomarkers are often measured in the presence of medication use, such that the observed biomarker value for the treated participants is different than their underlying natural history value. However, for certain predictors (e.g. age, gender, and genetic exposures) the observed biomarker value is not of primary interest. Rather, we are interested in estimating the association between these predictors and the natural history of the biomarker that would have occurred in the absence of treatment. Nonrandom medication use obscures our ability to estimate this association in cross-sectional observational data. Structural equation methodology (e.g. the treatment effects model), while historically used to estimate treatment effects, has been previously shown to be a reasonable way to correct endogeneity bias when estimating natural biomarker associations. However, the assumption that the effects of medication use on the biomarker are uniform across participants on medication is generally not thought to be reasonable. We derive an extension of the treatment effects model to accommodate effect modification. Based on several simulation studies and an application to data from the Multi-Ethnic Study of Atherosclerosis, we show that our extension substantially improves bias in estimating associations of interest, particularly when effect modifiers are associated with the biomarker or with medication use, without a meaningful cost of efficiency.

In patients with chronic kidney disease (CKD), clinical interest often centers on determining treatments and exposures that are causally related to renal progression. Analyses of longitudinal clinical data in this population are often complicated by clinical competing events, such as end-stage renal disease (ESRD) and death, and time-dependent confounding, where patient factors that are predictive of later exposures and outcomes are affected by past exposures. We developed multistate marginal structural models (MS-MSMs) to assess the effect of time-varying systolic blood pressure on disease progression in subjects with CKD. The multistate nature of the model allows us to jointly model disease progression characterized by changes in the estimated glomerular filtration rate (eGFR), the onset of ESRD, and death, and thereby avoid unnatural assumptions of death and ESRD as noninformative censoring events for subsequent changes in eGFR. We model the causal effect of systolic blood pressure on the probability of transitioning into 1 of 6 disease states given the current state. We use inverse probability weights with stabilization to account for potential time-varying confounders, including past eGFR, total protein, serum creatinine, and hemoglobin. We apply the model to data from the Chronic Renal Insufficiency Cohort Study, a multisite observational study of patients with CKD., (Copyright © 2017 John Wiley & Sons, Ltd.)

Repeated low-dose challenge designs in nonhuman primate studies have recently received attention in the literature as a means of evaluating vaccines for HIV prevention and identifying immune surrogates for their protective effects. Existing methods for surrogate identification in this type of study design rely on the assumption of homogeneity across subjects (namely, independent infection risks after each challenge within each subject and conditional on covariates). In practice, random variation across subjects is likely to occur because of unmeasured biologic factors. Failure to account for this heterogeneity or within-subject correlation can result in biased inference regarding the surrogate value of immune biomarkers and underpowered study designs for detecting surrogate endpoints. In this paper, we adopt a discrete-time survival model with random effects to account for between-subject heterogeneity, and we develop estimators and testing procedures for evaluating principal surrogacy of immune biomarkers. Simulation studies reveal that the heterogeneous model achieves substantial bias reduction compared to the homogeneous model, with little cost of efficiency. We recommend the use of this heterogeneous model as a complementary tool to existing methods when designing and analyzing repeated low-dose challenge studies for evaluating surrogate endpoints., (Copyright © 2017 John Wiley & Sons, Ltd.)

Objective: We investigated T cell responses to myelin proteins in the blood of healthy controls and 2 groups of patients with relapsing-remitting multiple sclerosis (RRMS) who exhibited lesions either predominantly in the brain or predominantly in the spinal cord in order to assess whether distinct neuroinflammatory patterns were associated with different myelin protein-specific T cell effector function profiles and whether these profiles differed from healthy controls., Methods: Peripheral blood mononuclear cells were obtained from patients with brain-predominant RRMS, patients with spinal cord-predominant RRMS, and age-matched healthy controls and analyzed by enzyme-linked immunosorbent spot assays to quantify interferon gamma-secreting (Th1) and interleukin 17-secreting (Th17) cells responding directly ex vivo to myelin basic protein (MBP) and myelin oligodendrocyte glycoprotein (MOG)., Results: Although MBP and MOG elicited different responses, patients with multiple sclerosis (MS) who had spinal cord-predominant lesions exhibited significantly higher Th17:Th1 ratios in response to both MBP and MOG compared to patients with brain-predominant MS. Incorporating the cytokine responses to both antigens into logistic regression models showed that these cytokine responses were able to provide good discrimination between patients with distinct neuroinflammatory patterns., Conclusions: Our findings suggest that the localization of lesions within the brain vs the spinal cord in patients with MS is associated with different effector T cell responses to myelin proteins. Further investigation of the relationship between T cell effector function, antigen specificities, and lesion sites may reveal features of pathogenic pathways that are distinct to patients with different neuroinflammatory patterns.

Purpose: Subclinical coronary artery calcification is an established predictor of cardiovascular events. While a history of kidney stones has been linked to subclinical carotid atherosclerosis, to our knowledge no study has examined its relationship with coronary artery calcification. We studied the association between kidney stone history and prevalent coronary artery calcification in MESA (Multi-Ethnic Study of Atherosclerosis)., Materials and Methods: MESA is a multisite cohort study of participants 45 to 84 years old without known cardiovascular disease at baseline from 2000 to 2002. Computerized tomography was done in 3,282 participants at followup in 2010 to 2012 to determine coronary artery calcification and kidney stone history was assessed by self-report. Coronary artery calcification scores were categorized as none-0, mild-1 to 99, moderate-100 to 399 or severe-400 or greater. Cross-sectional analysis was performed adjusting for demographic and dietary factors related to kidney stones., Results: The prevalence of kidney stone disease history was approximately 9%, mean ± SD participant age was 69.5 ± 9.3 years, 39% of participants were Caucasian, 47% were men and 69% had detectable coronary artery calcification (score greater than 0). No difference in the score was seen between single stone formers and nonstone formers. Recurrent kidney stone formation was associated with moderate or severe calcification on multivariable logistic regression vs none or mild calcification (OR 1.80, 95% CI 1.22-2.67). When coronary artery calcification scores were separated into none, mild, moderate and severe calcification, recurrent stone formation was associated with a higher score category on multivariable ordinal logistic regression (OR 1.44 per category, 95% CI 1.04-2.01)., Conclusions: Recurrent kidney stone formation is associated with subclinical coronary atherosclerosis. This association appeared stronger with coronary artery calcification severity than with coronary artery calcification presence., (Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.)

Purpose: In cross-sectional observational data, evaluation of biomarker-to-exposure associations is often complicated by nonrandom medication use. Traditional approaches often lead to biased estimates, consistent with known results involving confounding by indication. More sophisticated, yet easy to implement approaches such as inverse probability weighting and censored normal regression can address medication use in certain settings but have poor performance when medication use depends on off-medication biomarker values. More sophisticated approaches are necessary., Methods: Heckman's treatment effects model resembles the process that gives rise to cross-sectional data. In this study, we conduct a variety of simulation studies to illustrate why traditional approaches are inappropriate when medication use depends on underlying biomarker values. We illustrate how Heckman's model can accommodate this feature. We also apply the models to data from the Multi-Ethnic Study of Atherosclerosis., Results: Inverse probability weighting and censored normal regression are sensitive to how strongly medication use is associated with untreated biomarker values (the untreated value acts as an unmeasured predictor of medication use in this context). Heckman's model can often adequately remove bias and is robust to certain forms of model misspecification but relies on knowing important predictors of medication use, even when they are independent of the biomarker. The advantages of Heckman's model can be negated if the effect of medication on biomarker values is proportionate to the underlying biomarker., Conclusions: If predictors of medication use are measured, data are cross-sectional, and effects are approximately additive, then Heckman's model is more accurate relative to alternative approaches., Competing Interests: The authors have no conflicts of interest to declare., (Copyright © 2015 John Wiley & Sons, Ltd.)

Objective: To assess the potential of electrical impedance myography (EIM) to serve as a marker of muscle fiber atrophy and secondarily as an indicator of bone deterioration by assessing the effects of spaceflight or hind limb unloading., Methods: In the first experiment, 6 mice were flown aboard the space shuttle (STS-135) for 13 days and 8 earthbound mice served as controls. In the second experiment, 14 mice underwent hind limb unloading (HLU) for 13 days; 13 additional mice served as controls. EIM measurements were made on ex vivo gastrocnemius muscle. Quantitative microscopy and areal bone mineral density (aBMD) measurements of the hindlimb were also performed., Results: Reductions in the multifrequency phase-slope parameter were observed for both the space flight and HLU cohorts compared to their respective controls. For ground control and spaceflight groups, the values were 24.7±1.3°/MHz and 14.1±1.6°/MHz, respectively (p=0.0013); for control and HLU groups, the values were 23.9±1.6°/MHz and 19.0±1.0°/MHz, respectively (p=0.014). This parameter also correlated with muscle fiber size (ρ=0.65, p=0.011) for spaceflight and hind limb aBMD (ρ=0.65, p=0.0063) for both groups., Conclusions: These data support the concept that EIM may serve as a useful tool for assessment of muscle disuse secondary to immobilization or microgravity.

Introduction: We sought to determine whether electrical impedance myography (EIM) could serve as a diagnostic procedure for evaluation of radiculopathy., Methods: Twenty-seven patients with clinically and radiologically diagnosed cervical or lumbosacral radiculopathy who met a "gold standard" definition underwent EIM and standard needle electromyography (EMG) of multiple upper or lower extremity muscles., Results: EIM reactance values revealed consistent reductions in the radiculopathy-affected myotomal muscles as compared with those on the unaffected side; the degree of asymmetry was associated strongly with the degree of EMG abnormality (P < 0.001). EIM had a sensitivity of 64.5% and a specificity of 77.0%; in comparison, EMG had a sensitivity of 79.7% but a specificity of 69.7%., Conclusions: These findings support the potential for EIM to serve as a new non-invasive tool to assist in diagnosis of radiculopathy; however, further refinement of the technique is needed for this specific application., (Copyright © 2013 Wiley Periodicals, Inc.)

Objectives: Methods are needed for quantifying muscle deconditioning due to immobilization, aging, or spaceflight. Electrical impedance myography (EIM) is one technique that may offer easy-to-follow metrics. Here, we evaluate the time course and character of the change in single- and multi-frequency EIM parameters in the hind-limb suspension model of muscle deconditioning in rats., Methods: Sixty-two rats were studied with EIM during a two-week period of hind limb unloading followed by a two-week recovery period. Random subsets of animals were sacrificed at one-week time intervals to measure muscle fiber size., Results: Significant alterations were observed in nearly all impedance parameters. The 50 kHz phase and multi-frequency phase-slope, created by taking the slope of a line fitted to the impedance values between 100-500 kHz, appeared most sensitive to disuse atrophy, the latter decreasing by over 33.0±6.6% (p<0.001), a change similar to the maximum reduction in muscle fiber size. Impedance alterations, however, lagged changes in muscle fiber size., Conclusions: EIM is sensitive to disuse change in the rat, albeit with a delay relative to alterations in muscle fiber size. Given the rapidity and simplicity of EIM measurements, the technique could prove useful in providing a non-invasive approach to measuring disuse change in animal models and human subjects.

Objective: Recent developments in electrical impedance myography (EIM) have led to the use of handheld electrode arrays (HEAs) for data acquisition. Although preferable for several reasons, this approach tends to be more affected by subcutaneous fat (SF) than the original approach in which the impedance-measuring electrodes are widely spaced. In this study, we seek to identify the EIM parameter least impacted by subcutaneous fat (SF) when using an HEA., Methods: 18 normal subjects underwent 50 kHz EIM and ultrasound of the medial gastrocnemius muscles on the dominant side. Coefficients of determination (R(2) values) were calculated for each of the three major EIM variables (reactance, resistance, and phase) and SF thickness., Results: For both resistance and phase, a strong relationship to SF thickness was observed (R(2) = 0.64 and R(2) = 0.70, respectively, p < 0.001 for both). In contrast, for reactance, the relationship was non-significant, with R(2) = 0.07, p = 0.30., Conclusions: Unlike resistance and phase, both of which are highly impacted by SF thickness, the reactance shows no significant relationship., Significance: Future clinical studies employing HEA's to perform EIM should evaluate alterations in reactance in addition to those in resistance and phase., (Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Introduction: Electrical impedance myography (EIM) is a noninvasive technique used for assessment of muscle health in which a high-frequency, low-amplitude electric current is applied to the skin overlying a muscle, and the resulting surface voltage is measured. We have previously used adhesive electrodes, application of which is inconvenient. We present data using a handheld electrode array (HEA) that we devised to expedite the EIM procedure in a clinical setting., Methods: Thirty-four healthy volunteers and 24 radiculopathy subjects underwent EIM testing using the HEA and adhesive electrodes., Results: The HEA was shown to have good test-retest reproducibility, with intraclass correlation coefficients as high as 0.99. HEA data correlated strongly with data from adhesive electrodes, ρ = 0.85 in healthy volunteers (P < 0.001) and ρ = 0.75 in radiculopathy subjects (P < 0.001)., Conclusions: These data support the potential use of a handheld array for performing rapid localized surface impedance measurements., (Copyright © 2012 Wiley Periodicals, Inc.)

Objective: Human studies have shown that electrical impedance myography (EIM), a technique based on the surface application of high-frequency, low-intensity electrical current to localized areas of muscle, is sensitive to muscle denervation. In this study, we examined the role of EIM as a potential biomarker for assessing ALS disease progression in the SOD1 transgenic rat by comparing it to motor unit number estimation (MUNE)., Methods: Multi-frequency EIM and MUNE were performed twice weekly in 16 rats from approximately 10 weeks of age onward. Four different EIM measures were evaluated, including the previously studied 50 kHz phase and three condensed multi-frequency parameters., Results: The rate of deterioration in the multi-frequency phase data from 100-500 kHz had the strongest correlation to survival (ρ=0.79, p<0.001), surpassing that of MUNE (ρ=0.57, p=0.020). These two measures were also strongly correlated (ρ=-0.94, p<0.001) to one another., Conclusions: These findings support that EIM is an effective tool for assessing disease progression in the ALS rat., Significance: Given its ease of application and ability to assess virtually any superficial muscle, EIM deserves further study as a biomarker in human ALS clinical therapeutic trials., (Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Electrical impedance myography (EIM) is a surface-based, non-invasive technique of evaluation of muscle health, involving the application of high frequency, low-amplitude current to the skin over a muscle of interest. Results from a previous animal study suggest that the finite element method can relate disease-induced changes in electrical properties of the muscle to alterations in surface impedance measurements; however, whether such an approach will prove useful in human models is uncertain. Therefore, to further investigate this question, we have created a single finite element model of the human biceps muscle using data from one healthy subject and one with spinal muscular atrophy (SMA), each of whom had comparable age, limb girth, muscle size, and subcutaneous fat thickness. Since healthy human tissue was unavailable, permittivity and conductivity measurements were obtained from five healthy and five advanced amyotrophic lateral sclerosis rat gastrocnemius muscles immediately after sacrifice; their data were input into the human biceps model and the expected surface voltages calculated. We then compared the results of this model to the actual surface EIM data for both individuals. Although the actual resistance and reactance values varied and the peak values were displaced, the resulting maximum phase predicted by the model approximated that obtained with surface recordings. These results support that alterations in the primary characteristics of muscle impact the surface impedance measurements in meaningful and likely predictable ways.