Connectomic Profiling Identifies Responders to Vagus Nerve Stimulation.

OBJECTIVE: Vagus nerve stimulation (VNS) is a common treatment for medically intractable epilepsy, but response rates are highly variable, with no preoperative means of identifying good candidates. This study aimed to predict VNS response using structural and functional connectomic profiling. METHODS: Fifty-six children, comprising discovery (n = 38) and validation (n = 18) cohorts, were recruited from 3 separate institutions. Diffusion tensor imaging was used to identify group differences in white matter microstructure, which in turn informed beamforming of resting-state magnetoencephalography recordings. The results were used to generate a support vector machine learning classifier, which was independently validated. This algorithm was compared to a second classifier generated using 31 clinical covariates. RESULTS: Treatment responders demonstrated greater fractional anisotropy in left thalamocortical, limbic, and association fibers, as well as greater connectivity in a functional network encompassing left thalamic, insular, and temporal nodes (p < 0.05). The resulting classifier demonstrated 89.5% accuracy and area under the receiver operating characteristic (ROC) curve of 0.93 on 10-fold cross-validation. In the external validation cohort, this model demonstrated an accuracy of 83.3%, with a sensitivity of 85.7% and specificity of 75.0%. This was significantly superior to predictions using clinical covariates alone, which exhibited an area under the ROC curve of 0.57 (p < 0.008). INTERPRETATION: This study provides the first multi-institutional, multimodal connectomic prediction algorithm for VNS, and provides new insights into its mechanism of action. Reliable identification of VNS responders is critical to mitigate surgical risks for children who may not benefit, and to ensure cost-effective allocation of health care resources. ANN NEUROL 2019;86:743-753.

Characterization of Autism Spectrum Disorder across the Age Span by Intrinsic Network Patterns.

Autism spectrum disorder (ASD) is characterized by abnormal functional organization of brain networks, which may underlie the cognitive and social impairments observed in affected individuals. The present study characterizes unique intrinsic connectivity within- and between- neural networks in children through to adults with ASD, relative to controls. Resting state fMRI data were analyzed in 204 subjects, 102 with ASD and 102 age- and sex-matched controls (ages 7-40 years), acquired on a single scanner. ASD was assessed using the autism diagnostic observation schedule (ADOS). BOLD correlations were calculated between 47 regions of interest, spanning seven resting state brain networks. Partial least squares (PLS) analyses evaluated the association between connectivity patterns and ASD diagnosis as well as ASD severity scores. PLS demonstrated dissociable connectivity patterns in those with ASD, relative to controls. Similar patterns were observed in the whole cohort and in a subgroup analysis of subjects under 18 years of age. Greater inter-network connectivity was seen in ASD with greater intra-network connectivity in controls. In conclusion, stronger inter-network and weaker intra-network resting state-fMRI BOLD correlations characterize ASD and may differentiate control and ASD cohorts. These findings are relevant to understanding ASD as a disruption of network topology.

Phase-amplitude coupling within the anterior thalamic nuclei during seizures.

Cross-frequency phase-amplitude coupling (cfPAC) subserves an integral role in the hierarchical organization of interregional neuronal communication and is also expressed by epileptogenic cortex during seizures. Here, we sought to characterize patterns of cfPAC expression in the anterior thalamic nuclei during seizures by studying extra-operative recordings in patients implanted with deep brain stimulation electrodes for intractable epilepsy. Nine seizures from two patients were analyzed in the peri-ictal period. CfPAC was calculated using the modulation index and interregional functional connectivity was indexed using the phase-locking value. Statistical analysis was performed within subjects on the basis of nonparametric permutation and corrected with Gaussian field theory. Five of the nine analyzed seizures demonstrated significant cfPAC. Significant cfPAC occurred during the pre-ictal and ictal periods in three seizures, as well as the postictal windows in four seizures. The preferred phase at which cfPAC occurred differed 1) in space, between the thalami of the epileptogenic and nonepileptogenic hemispheres; and 2) in time, at seizure termination. The anterior thalamic nucleus of the epileptogenic hemisphere also exhibited altered interregional phase-locking synchrony concurrent with the expression of cfPAC. By analyzing extraoperative recordings from the anterior thalamic nuclei, we show that cfPAC associated with altered interregional phase synchrony is lateralized to the thalamus of the epileptogenic hemisphere during seizures. Electrophysiological differences in cfPAC, including preferred phase of oscillatory interactions may be further investigated as putative targets for individualized neuromodulation paradigms in patients with drug-resistant epilepsy. NEW & NOTEWORTHY The association between fast brain activity and slower oscillations is an integral mechanism for hierarchical neuronal communication, which is also manifested in epileptogenic cortex. Our data suggest that the same phenomenon occurs in the anterior thalamic nuclei during seizures. Further, the preferred phase of modulation shows differences in space, between the epileptogenic and nonepileptogenic hemispheres and time, as seizures terminate. Our data encourage the study of cross-frequency coupling for targeted, individualized closed-loop stimulation paradigms.

Longitudinal Study of White Matter Development and Outcomes in Children Born Very Preterm.

Identifying trajectories of early white matter development is important for understanding atypical brain development and impaired functional outcomes in children born very preterm (<32 weeks gestational age [GA]). In this study, 161 diffusion images were acquired in children born very preterm (median GA: 29 weeks) shortly following birth (75), term-equivalent (39), 2 years (18), and 4 years of age (29). Diffusion tensors were computed to obtain measures of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), which were aligned and averaged. A paediatric atlas was applied to obtain diffusion metrics within 12 white matter tracts. Developmental trajectories across time points demonstrated age-related changes which plateaued between term-equivalent and 2 years of age in the majority of posterior tracts and between 2 and 4 years of age in anterior tracts. Between preterm and term-equivalent scans, FA rates of change were slower in anterior than posterior tracts. Partial least squares analyses revealed associations between slower MD and RD rates of change within the external and internal capsule with lower intelligence quotients and language scores at 4 years of age. These results uniquely demonstrate early white matter development and its linkage to cognitive functions.

Brain biomarkers and pre-injury cognition are associated with long-term cognitive outcome in children with traumatic brain injury.

BACKGROUND: Children with traumatic brain injury (TBI) are frequently at risk of long-term impairments of attention and executive functioning but these problems are difficult to predict. Although deficits have been reported to vary with injury severity, age at injury and sex, prognostication of outcome remains imperfect at a patient-specific level. The objective of this proof of principle study was to evaluate a variety of patient variables, along with six brain-specific and inflammatory serum protein biomarkers, as predictors of long-term cognitive outcome following paediatric TBI. METHOD: Outcome was assessed in 23 patients via parent-rated questionnaires related to attention deficit hyperactivity disorder (ADHD) and executive functioning, using the Conners 3rd Edition Rating Scales (Conners-3) and Behaviour Rating Inventory of Executive Function (BRIEF) at a mean time since injury of 3.1 years. Partial least squares (PLS) analyses were performed to identify factors measured at the time of injury that were most closely associated with outcome on (1) the Conners-3 and (2) the Behavioural Regulation Index (BRI) and (3) Metacognition Index (MI) of the BRIEF. RESULTS: Higher levels of neuron specific enolase (NSE) and lower levels of soluble neuron cell adhesion molecule (sNCAM) were associated with higher scores on the inattention, hyperactivity/impulsivity and executive functioning scales of the Conners-3, as well as working memory and initiate scales of the MI from the BRIEF. Higher levels of NSE only were associated with higher scores on the inhibit scale of the BRI. CONCLUSIONS: NSE and sNCAM show promise as reliable, early predictors of long-term attention-related and executive functioning problems following paediatric TBI.

Associations of Perinatal Clinical and Magnetic Resonance Imaging Measures with Developmental Outcomes in Children Born Very Preterm.

OBJECTIVE: To identify perinatal risk factors associated with long-term neurocognitive and behavioral impairments in children born very preterm using a multivariate, partial least squares approach. STUDY DESIGN: Twenty-seven perinatal clinical and magnetic resonance imaging measures were collected at birth and during the neonatal intensive care stay for 105 neonates born very preterm (≤ 32 weeks gestational age). One-half of the children returned for neuropsychological assessments at 2 and 4 years of age. Parent-reported behavioral measures were also obtained at 4 years of age. Three partial least squares analyses were performed to determine associations between clinical and radiologic measures with cognitive outcomes at 2 and 4 years of age, as well as with behavioral measures at 4 years of age. RESULTS: Within the first components of each analysis, only intrauterine growth restriction, male sex, and absence of antenatal corticosteroid use were associated with poorer cognitive and language ability at 2 and 4 years of age, accounting for 79.6% and 71.4% of the total variance, respectively. In addition, white matter injury at term-equivalent age contributed to more problematic internalizing behaviors, behavioral symptoms, and impaired executive function at 4 years of age, accounting for 67.9% of the total variance. CONCLUSIONS: Using this data-driven multivariate approach, specific measures in prenatal and early postnatal life are shown to be selectively and significantly associated with cognitive and behavioral outcomes in children born very preterm. Early detection of risk factors can help inform prognoses of children at greatest risk of long-term impairments.

Longitudinal cerebellar growth following very preterm birth.

PURPOSE: To measure cerebellar growth in a longitudinal cohort of very preterm infants to identify early predictors of subsequent brain growth. Although the cerebellum grows rapidly during late gestation, the rate and variability of growth following premature birth, and the effects of associated injury, are largely unknown. MATERIALS AND METHODS: In all, 105 very-preterm born infants (24-32 weeks GA) were imaged using magnetic resonance imaging (MRI) at birth, term-equivalent, 2, and 4 years of age. Cerebellar and total cerebral volumes were estimated from 1 mm isotropic T1 -weighted scans acquired at 1.5T and 3T, using an atlas-based approach. Linear models were used to analyze cerebellar volume as cross-sectional and longitudinal functions of age, clinical, and radiological correlates. Linear models were also used to test for associations between volume and cognitive outcome. RESULTS: Cerebellar volume increased rapidly with age-at-scan during both the preterm (0.7 mL/wk, P < 0.001) and term periods (1.8 mL/wk, P < 0.001). Infants with grade 3 or 4 germinal matrix hemorrhage (GMH) had smaller cerebellar volumes as a percentage of total brain volume starting at birth and continuing to 4 years of age (-0.43%, -0.57%, -1.09% at preterm, term, and 4 years, respectively, P < 0.01). Irrespective of age-at-scan, early cerebellar volume was predictive of volume at 4 years of age (slope = 1.3, P < 0.001). Cerebellar volumes were not found to predict cognitive outcome at 4 years of age; P < 0.2. CONCLUSION: High-grade GMH and small perinatal cerebellar size is predictive of cerebellar development up to 4 years of age. These findings suggest that it is possible to identify individuals at high risk of reduced cerebellar volumes at an early age. J. Magn. Reson. Imaging 2016;43:1462-1473.

Diffusion tensor imaging-based assessment of white matter tracts and visual-motor outcomes in very preterm neonates.

INTRODUCTION: The purpose of this study was to assess the impact of brain injury on white matter development and long-term outcomes in very preterm (VPT) neonates. METHODS: Eighty-five VPT neonates (born <32/40 weeks gestational age (GA)) scanned within 2 weeks of birth were divided into three groups based on the presence of perinatal cerebral injury: (i) no injury, (ii) mild/moderate injury and (iii) severe injury. Diffusion tensor imaging (DTI) was acquired for each neonate and fractional anisotropy (FA), and diffusivity measures were calculated in the posterior limb of the internal capsule (PLIC) and optic radiation (OR). At 2 and 4 years of age, 41 and 44 children were assessed for motor and visual-motor abilities. Analyses determined the relation between GA and DTI measures, injury groups and DTI measures as well as developmental assessments. RESULTS: GA was related to all DTI measures within the PLIC bilaterally, FA in the OR bilaterally and AD in the left OR. The severely injured group had significantly different DTI measures in the left PLIC compared to the other two groups, independent of lateralization of lesions. Group differences in the left OR were also found, due to higher incidence of the white matter injury in the left hemisphere. No differences were found between groups and outcome measures at 2 and 4 years, with the exception of destructive periventricular venous haemorrhagic infarction (PVHI). CONCLUSIONS: DTI measures of the PLIC and OR were affected by injury in VPT neonates. These findings seen shortly after birth did not always translate into long-term motor and visual-motor impairments suggesting compensatory mechanisms.

Deep grey matter growth predicts neurodevelopmental outcomes in very preterm children.

We evaluated whether the volume and growth rate of critical brain structures measured by MRI in the first weeks of life following very preterm (<32/40 weeks) birth could predict subsequent neurodevelopmental outcomes at 4 years of age. A significant proportion of children born very prematurely have cognitive deficits, but these problems are often only detected at early school age. Structural T2-weighted magnetic resonance images were acquired in 96 very preterm neonates scanned within 2 weeks of birth and 70 of these at term-equivalent age. An automated 3D image analysis procedure was used to measure the volume of selected brain structures across all scans and time points. At 4 years of age, 53 children returned for neuropsychological assessments evaluating IQ, language and visual motor integration. Associations with maternal education and perinatal measures were also explored. Multiple regression analyses revealed that growth of the caudate and globus pallidus between preterm birth and term-equivalent age predicted visual motor integration scores after controlling for sex and gestational age. Further associations were found between caudate and putamen growth with IQ and language scores. Analyses at either preterm or term-equivalent age only found associations between normalized deep grey matter growth and visual motor integration scores at term-equivalent age. Maternal education levels were associated with measures of IQ and language, but not visual motor integration. Thalamic growth was additionally linked with perinatal measures and presence of white matter lesions. These results highlight deep grey matter growth rates as promising biomarkers of long-term outcomes following very preterm birth, and contribute to our understanding of the brain-behaviour relations in these children.

Resilience of developing brain networks to interictal epileptiform discharges is associated with cognitive outcome.

The effects of interictal epileptiform discharges on neurocognitive development in children with medically-intractable epilepsy are poorly understood. Such discharges may have a deleterious effect on the brain's intrinsic connectivity networks, which reflect the organization of functional networks at rest, and in turn on neurocognitive development. Using a combined functional magnetic resonance imaging-magnetoencephalography approach, we examine the effects of interictal epileptiform discharges on intrinsic connectivity networks and neurocognitive outcome. Functional magnetic resonance imaging was used to determine the location of regions comprising various intrinsic connectivity networks in 26 children (7-17 years), and magnetoencephalography data were reconstructed from these locations. Inter-regional phase synchronization was then calculated across interictal epileptiform discharges and graph theoretical analysis was applied to measure event-related changes in network topology in the peri-discharge period. The magnitude of change in network topology (network resilience/vulnerability) to interictal epileptiform discharges was associated with neurocognitive outcomes and functional magnetic resonance imaging networks using dual regression. Three main findings are reported: (i) large-scale network changes precede and follow interictal epileptiform discharges; (ii) the resilience of network topologies to interictal discharges is associated with stronger resting-state network connectivity; and (iii) vulnerability to interictal discharges is associated with worse neurocognitive outcomes. By combining the spatial resolution of functional magnetic resonance imaging with the temporal resolution of magnetoencephalography, we describe the effects of interictal epileptiform discharges on neurophysiological synchrony in intrinsic connectivity networks and establish the impact of interictal disruption of functional networks on cognitive outcome in children with epilepsy. The association between interictal discharges, network changes and neurocognitive outcomes suggests that it is of clinical importance to suppress discharges to foster more typical brain network development in children with focal epilepsy.

Thalamocortical connectivity is enhanced following functional hemispherotomy for intractable lateralized epilepsy.

Although developmental outcomes may improve following functional hemispherotomy for lateralized, catastrophic childhood epilepsy, the neuronal processes mediating these improvements are unknown. We report the case of a 14-year-old child with neurocognitive impairment who underwent functional hemispherotomy with longitudinal resting-state fMRI. Compared with preoperative fMRI, we report significantly more robust thalamo-default mode network connectivity on postoperative neuroimaging. Furthermore, we show decreased connectivity to nodes within the disconnected hemisphere, providing direct evidence that functional interactions are dependent upon structural connectivity. Since the vascular supply to these nodes remains intact, although they are disconnected from the remainder of the brain, these findings also confirm that blood-oxygen level dependent oscillations are driven primarily by neuronal activity. The current study highlights the importance of thalamocortical interactions in the understanding of neural oscillations and cognitive function, and their impairment in childhood epilepsy.

A partial least squares analysis of seizure outcomes following resective surgery for tuberous sclerosis complex in children with intractable epilepsy.

INTRODUCTION: Previous studies aimed at identifying predictors of seizure outcomes following resective surgery for tuberous sclerosis complex (TSC) are limited by multicollinearity among predictors, whereby the high degree of correlation between covariates precludes detection of potentially significant findings. PURPOSE: Here, we apply a data-driven method, partial least squares (PLS) to model multidimensional variance and study significant patterns in data that are associated with seizure outcomes. METHODS: Post hoc analysis of 186 children with TSC who underwent resective epilepsy surgery derived from an individual participant data meta-analysis was performed. PLS was used to derive a latent variable (component) that relates clinical covariates with Engel classification. Permutation testing was performed to evaluate the significance of the component, and bootstrapping was used to identify significant contributors to the component. RESULTS: A significant component was identified, which represents the pattern of covariates related to Engel class. The strongest and significant factors contributing to this component were focal ictal electroencephalogram and concordance of electroencephalography (EEG)-magnetic resonance imaging (MRI) abnormality. Interestingly, covariates contributing the least to the seizure-free patient phenotype were continent of treatment and age at the time of surgery. CONCLUSION: Using a data-driven, multivariate method, PLS, we describe patient phenotypes that are associated with seizure-freedom following resective surgery for TSC.

Patient phenotypes associated with outcomes after aneurysmal subarachnoid hemorrhage: a principal component analysis.

BACKGROUND AND PURPOSE: Predictors of outcome after aneurysmal subarachnoid hemorrhage have been determined previously through hypothesis-driven methods that often exclude putative covariates and require a priori knowledge of potential confounders. Here, we apply a data-driven approach, principal component analysis, to identify baseline patient phenotypes that may predict neurological outcomes. METHODS: Principal component analysis was performed on 120 subjects enrolled in a prospective randomized trial of clazosentan for the prevention of angiographic vasospasm. Correlation matrices were created using a combination of Pearson, polyserial, and polychoric regressions among 46 variables. Scores of significant components (with eigenvalues>1) were included in multivariate logistic regression models with incidence of severe angiographic vasospasm, delayed ischemic neurological deficit, and long-term outcome as outcomes of interest. RESULTS: Sixteen significant principal components accounting for 74.6% of the variance were identified. A single component dominated by the patients' initial hemodynamic status, World Federation of Neurosurgical Societies score, neurological injury, and initial neutrophil/leukocyte counts was significantly associated with poor outcome. Two additional components were associated with angiographic vasospasm, of which one was also associated with delayed ischemic neurological deficit. The first was dominated by the aneurysm-securing procedure, subarachnoid clot clearance, and intracerebral hemorrhage, whereas the second had high contributions from markers of anemia and albumin levels. CONCLUSIONS: Principal component analysis, a data-driven approach, identified patient phenotypes that are associated with worse neurological outcomes. Such data reduction methods may provide a better approximation of unique patient phenotypes and may inform clinical care as well as patient recruitment into clinical trials. CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifier: NCT00111085.

Oscillations, networks, and their development: MEG connectivity changes with age.

Magnetoencephalographic (MEG) investigations of inter-regional amplitude correlations have yielded new insights into the organization and neurophysiology of resting-state networks (RSNs) first identified using fMRI. Inter-regional MEG amplitude correlations in adult RSNs have been shown to be most prominent in alpha and beta frequency ranges and to express strong congruence with RSN topologies found using fMRI. Despite such advances, little is known about how oscillatory connectivity in RSNs develops throughout childhood and adolescence. This study used a novel fMRI-guided MEG approach to investigate the maturation of resting-state amplitude correlations in physiologically relevant frequency ranges within and among six RSNs in 59 participants, aged 6-34 years. We report age-related increases in inter-regional amplitude correlations that were largest in alpha and beta frequency bands. In contrast to fMRI reports, these changes were observed both within and between the various RSNs analyzed. Our results provide the first evidence of developmental changes in spontaneous neurophysiological connectivity in source-resolved RSNs, which indicate increasing integration within and among intrinsic functional brain networks throughout childhood, adolescence, and early adulthood.

Impaired development of intrinsic connectivity networks in children with medically intractable localization-related epilepsy.

Typical childhood development is characterized by the emergence of intrinsic connectivity networks (ICNs) by way of internetwork segregation and intranetwork integration. The impact of childhood epilepsy on the maturation of ICNs is, however, poorly understood. The developmental trajectory of ICNs in 26 children (8-17 years) with localization-related epilepsy and 28 propensity-score matched controls was evaluated using graph theoretical analysis of whole brain connectomes from resting-state functional magnetic resonance imaging (fMRI) data. Children with epilepsy demonstrated impaired development of regional hubs in nodes of the salience and default mode networks (DMN). Seed-based connectivity and hierarchical clustering analysis revealed significantly decreased intranetwork connections, and greater internetwork connectivity in children with epilepsy compared to controls. Significant interactions were identified between epilepsy duration and the expected developmental trajectory of ICNs, indicating that prolonged epilepsy may cause progressive alternations in large-scale networks throughout childhood. DMN integration was also associated with better working memory, whereas internetwork segregation was associated with higher full-scale intelligence quotient scores. Furthermore, subgroup analyses revealed the thalamus, hippocampus, and caudate were weaker hubs in children with secondarily generalized seizures, relative to other patient subgroups. Our findings underscore that epilepsy interferes with the developmental trajectory of brain networks underlying cognition, providing evidence supporting the early treatment of affected children.

The development of regional functional connectivity in preterm infants into early childhood.

INTRODUCTION: Resting state networks are proposed to reflect the neuronal connectivity that underlies cognitive processes. Consequently, abnormal behaviour of these networks due to disease or altered development may predict poor cognitive outcome. To understand how very preterm birth may affect the development of resting state connectivity, we followed a cohort of very preterm-born infants from birth through to 4 years of age using resting state functional MRI. METHODS: From a larger longitudinal cohort of infants born very preterm (<32 weeks gestational age), 36 at birth, 30 at term, 21 two-year and 22 four-year resting state fMRI datasets were acquired. Using seed-based connectivity analyses with seeds in the anterior cingulate cortex, posterior cingulate cortex, left and right motor-hand regions and left and right temporal lobes, we investigated local and inter-region connectivity as a function of group and age. RESULTS: We found strong local connectivity during the preterm period, which matured into inter-hemispheric and preliminary default-mode network correlations by 4 years of age. This development is comparable to the resting state networks found in term-born infants of equivalent age. CONCLUSION: The results of this study suggest that differences in developmental trajectory between preterm-born and term-born infants are small and, if present, would require a large sample from both populations to be detected.

Postoperative cerebellar mutism syndrome is an acquired Autism-like network disturbance.

BACKGROUND: Cerebellar mutism syndrome (CMS) is a common and debilitating complication of posterior fossa tumour surgery in children. Affected children exhibit communication and social impairments that overlap phenomenologically with subsets of deficits exhibited by children with Autism spectrum disorder (ASD). Although both CMS and ASD are thought to involve disrupted cerebro-cerebellar circuitry, they are considered independent conditions due to an incomplete understanding of their shared neural substrates. METHODS: In this study, we analyzed post-operative cerebellar lesions from 90 children undergoing posterior fossa resection of medulloblastoma, 30 of whom developed CMS. Lesion locations were mapped to a standard atlas, and the networks functionally connected to each lesion were computed in normative adult and paediatric datasets. Generalizability to ASD was assessed using an independent cohort of children with ASD and matched controls (n=427). RESULTS: Lesions in children who developed CMS involved the vermis and inferomedial cerebellar lobules. They engaged large-scale cerebellothalamocortical circuits with a preponderance for the prefrontal and parietal cortices in the paediatric and adult connectomes, respectively. Moreover, with increasing connectomic age, CMS-associated lesions demonstrated stronger connectivity to the midbrain/red nuclei, thalami and inferior parietal lobules and weaker connectivity to prefrontal cortex. Importantly, the CMS-associated lesion network was independently reproduced in ASD and correlated with communication and social deficits, but not repetitive behaviours. CONCLUSIONS: Our findings indicate that CMS-associated lesions result in an ASD-like network disturbance that occurs during sensitive windows of brain development. A common network disturbance between CMS and ASD may inform improved treatment strategies for affected children.

Long-term outcomes of kidney donors.

PURPOSE OF REVIEW: Living kidney donors face a unique decision of self-sacrifice that is not without potential risk. The purpose of this review is to highlight existing research regarding the perioperative morbidity, mortality and long-term outcomes of living kidney donors. RECENT FINDINGS: Recent studies of long-term donor survival have affirmed that the life expectancy for living kidney donors is excellent and their risk of end-stage renal disease (ESRD) is not increased. Long-term health outcomes for living donors representing minority groups, however, may not be as favorable. Recent studies conclude that African-American and Hispanic donors, similarly to nondonors of the same race, are at higher risk of developing chronic kidney disease (CKD), hypertension, and diabetes mellitus. Outcomes in medically complex donors have also generated considerable attention, and the evidence on outcomes among otherwise healthy obese and older donors appears to be reassuring. SUMMARY: Living kidney donation is a superior transplantation option for many individuals with ESRD. The survival and health consequences of living donation have proven to be excellent. These favorable outcomes stem from careful screening measures, and further research endeavors are needed to ensure long-term living donor safety in high-risk donors.

A partial least squares analysis of functional status, disability, and quality of life after surgical decompression for degenerative cervical myelopathy.

Previous studies aimed at identifying predictors of clinical outcomes following surgical decompression for degenerative cervical myelopathy (DCM) are limited by multicollinearity among predictors, whereby the high degree of correlation between covariates precludes detection of potentially significant findings. We apply partial least squares (PLS), a data-driven approach, to model multi-dimensional variance and dissociate patient phenotypes associated with functional, disability, and quality of life (QOL) outcomes in DCM. This was a post-hoc analysis of DCM patients enrolled in the prospective, multi-center AOSpine CSM-NA/CSM-I studies. Baseline clinical covariates evaluated as predictors included demographic (e.g., age, sex), clinical presentation (e.g., signs and symptoms), and treatment (e.g., surgical approach) characteristics. Outcomes evaluated included change in functional status (∆mJOA), disability (∆NDI), and QOL (∆SF-36) at 2 years. PLS was used to derive latent variables (LVs) relating specific clinical covariates with specific outcomes. Statistical significance was estimated using bootstrapping. Four hundred and seventy-eight patients met eligibility criteria. PLS identified 3 significant LVs. LV1 indicated an association between presentation with hand muscle atrophy, treatment by an approach other than laminectomy alone, and greater improvement in physical health-related QOL outcomes (e.g., SF-36 Physical Component Summary). LV2 suggested the presence of comorbidities (respiratory, rheumatologic, psychological) was associated with lesser improvements in functional status post-operatively (i.e., mJOA score). Finally, LV3 reflected an association between more severe myelopathy presenting with gait impairment and poorer mental health-related QOL outcomes (e.g., SF-36 Mental Component Summary). Using PLS, this analysis uncovered several novel insights pertaining to patients undergoing surgical decompression for DCM that warrant further investigation: (1) comorbid status and frailty heavily impact functional outcome; (2) presentation with hand muscle atrophy is associated with better physical QOL outcomes; and (3) more severe myelopathy with gait impairment is associated with poorer mental QOL outcomes.

A needs assessment of pediatric epilepsy surgery in Haiti.

OBJECTIVE: Epilepsy disproportionately affects low- and/or middle-income countries (LMICs). Surgical treatments for epilepsy are potentially curative and cost-effective and may improve quality of life and reduce social stigmas. In the current study, the authors estimate the potential need for a surgical epilepsy program in Haiti by applying contemporary epilepsy surgery referral guidelines to a population of children assessed at the Clinique d'Épilepsie de Port-au-Prince (CLIDEP). METHODS: The authors reviewed 812 pediatric patient records from the CLIDEP, the only pediatric epilepsy referral center in Haiti. Clinical covariates and seizure outcomes were extracted from digitized charts. Electroencephalography (EEG) and neuroimaging reports were further analyzed to determine the prevalence of focal epilepsy or surgically amenable syndromes and to assess the lesional causes of epilepsy in Haiti. Lastly, the toolsforepilepsy instrument was applied to determine the proportion of patients who met the criteria for epilepsy surgery referral. RESULTS: Two-thirds of the patients at CLIDEP (543/812) were determined to have epilepsy based on clinical and diagnostic evaluations. Most of them (82%, 444/543) had been evaluated with interictal EEG, 88% of whom (391/444) had abnormal findings. The most common finding was a unilateral focal abnormality (32%, 125/391). Neuroimaging, a prerequisite for applying the epilepsy surgery referral criteria, had been performed in only 58 patients in the entire CLIDEP cohort, 39 of whom were eventually diagnosed with epilepsy. Two-thirds (26/39) of those patients had abnormal findings on neuroimaging. Most patients (55%, 18/33) assessed with the toolsforepilepsy application met the criteria for epilepsy surgery referral. CONCLUSIONS: The authors' findings suggest that many children with epilepsy in Haiti could benefit from being evaluated at a center with the capacity to perform basic brain imaging and neurosurgical treatments.