Citations

Background: There is a wide range of literature on patellar tendon injury, making it increasingly difficult to stay informed on the most influential studies in this field. It is essential to be familiar with the foundational articles of patellar tendon injury research to understand the current state of the literature and deliver high quality care. Purpose: To objectively identify the 50 most influential articles relating to patellar tendon injury and conduct a bibliometric analysis to identify key features of these articles. Study Design: Cross-sectional study. Methods: The Clarivate Analytics Web of Knowledge database was utilized to gather metrics on the 50 most cited articles on patellar tendon injury on June 27, 2022. The information extracted from each article included publication year, number of citations, author information, article type, level of evidence, country of origin, journal name, study focus, and industry influence. Results: The top 50 studies were cited a total of 8543 times and published between 1977 and 2015. The majority of articles were published after 2003, and the majority of citations were accrued after 2011. The most prevalent article types were cohort studies (n = 23), and the majority of studies were of evidence level 2 (n = 14) or 4 (n = 13). Australia and the United States (US) each published the most studies (n = 11). Only 4 (8%) studies focused on patellar tendon rupture, and 12 (24%) of the top 50 studies were associated with industry. Conclusion: The majority of the top 50 most influential articles in patellar tendon injury were published and accumulated citations in the past 10 to 20 years. Non-US countries, institutions, and journals published many of the top 50 studies, reflecting a global interest and commitment to research in this field. Patellar tendon rupture and surgical repair represents a minority of research in the top 50 studies and could be a point of growth in the future.

Purpose To evaluate the superior to inferior glenoid height as a reliable reference in best‐fit circle creation for glenoid anatomy. Methods The morphology of the native glenoid was evaluated using magnetic resonance imaging (MRI) in patients without shoulder instability. Using T1 sagittal MRI images, 2 reviewers independently estimated glenoid size using the two‐thirds technique and the “best‐fit circle” technique at 2 different times. A Student t ‐test was used to determine significant difference between the two methodologies. Inter‐ and intra‐rater reliability were calculated using interclass and intraclass coefficients. Results This study included 112 patients. Using the results of glenoid height and “best‐fit circle” diameter, the diameter of the “best‐fit circle” was found to intersect the glenoid line at 67.8% of the glenoid height on average. We found no significant difference between the 2 measures of glenoid diameter (27.6 vs 27.9, P = .456). The interclass and intraclass coefficients for the two‐third method were 0.85 and 0.88, respectively. The interclass and intraclass coefficients for the perfect circle methods were 0.84 and 0.73, respectively. Conclusions We determined that the diameter of a circle placed on the inferior glenoid using the “best‐fit circle” technique corresponds to 67.8% of the glenoid height. Additionally, we found that constructing a perfect circle using a diameter equal to two‐thirds the height of the glenoid may improve intraclass reliability. Level of Evidence Level IV, retrospective cohort study.

AbstractBackgroundSpecific pretransplant infections have been associated with poor posttransplant outcomes. However, the impact of pretransplant Nocardia isolation has not been studied.MethodsWe performed a retrospective study from three centers in Arizona, Florida, and Minnesota of patients with Nocardia infection or colonization who subsequently underwent solid organ or hematopoietic stem cell transplantation from November 2011 through April 2022. Outcomes included posttransplant Nocardia infection and mortality.ResultsNine patients with pretransplant Nocardia were included. Two patients were deemed colonized with Nocardia, and the remaining seven had nocardiosis. These patients underwent bilateral lung (N = 5), heart (N = 1), heart‐kidney (N = 1), liver‐kidney (N = 1), and allogeneic stem cell transplantation (N = 1) at a median of 283 (interquartile range [IQR] 152–283) days after Nocardia isolation. Two (22.2%) patients had disseminated infection, and two were receiving active Nocardia treatment at the time of transplantation. One Nocardia isolate was resistant to trimethoprim‐sulfamethoxazole (TMP‐SMX) and all patients received TMP‐SMX prophylaxis posttransplant, often for extended durations. No patients developed posttransplant nocardiosis during a median follow‐up of 1.96 (IQR 0.90–6.33) years. Two patients died during follow‐up, both without evidence of nocardiosis.ConclusionsThis study did not identify any episodes of posttransplant nocardiosis among nine patients with pretransplant Nocardia isolation. As patients with the most severe infections may have been denied transplantation, further studies with larger sample sizes are needed to better analyze any impact of pretransplant Nocardia on posttransplant outcomes. However, among patients who receive posttransplant TMP‐SMX prophylaxis, these data suggest pretransplant Nocardia isolation may not impart a heightened risk of posttransplant nocardiosis. image

AbstractFunctional magnetic resonance imaging (fMRI) studies have often recorded robust univariate group effects in the amygdala of subjects exposed to emotional stimuli. Yet it is unclear to what extent this effect also holds true when multi‐voxel pattern analysis (MVPA) is applied at the level of the individual participant. Here we sought to answer this question. To this end, we combined fMRI data from two prior studies (N = 112). For each participant, a linear support vector machine was trained to decode the valence of emotional pictures (negative, neutral, positive) based on brain activity patterns in either the amygdala (primary region‐of‐interest analysis) or the whole‐brain (secondary exploratory analysis). The accuracy score of the amygdala‐based pattern classifications was statistically significant for only a handful of participants (4.5%) with a mean and standard deviation of 37% ± 5% across all subjects (range: 28–58%; chance‐level: 33%). In contrast, the accuracy score of the whole‐brain pattern classifications was statistically significant in roughly half of the participants (50.9%), and had an across‐subjects mean and standard deviation of 49% ± 6% (range: 33–62%). The current results suggest that the information conveyed by the emotional pictures was encoded by spatially distributed parts of the brain, rather than by the amygdala alone, and may be of particular relevance to studies that seek to target the amygdala in the treatment of emotion regulation problems, for example via real‐time fMRI neurofeedback training.

AbstractBackgroundDementia with Lewy bodies (DLB) is the second most common neurodegenerative dementia, after Alzheimer’s disease (AD). While alpha‐synuclein pathology is the hallmark of DLB, AD and cerebrovascular pathologies are common in DLB patients. However, the contribution of these pathologies towards neurodegeneration in DLB is largely unknown. We investigated associations of amyloid‐beta, tau, and cerebrovascular biomarkers with regional gray matter (GM) volume in DLB patients and cognitively unimpaired (CU) controls.MethodWe included 30 DLB patients (69.3±10.2 years old, 87% men) and 100 CU individuals balanced on age and sex (Table 1). We used 11C‐Pittsburgh Compound‐B (PiB) and 18F‐Flortaucipir positron emission tomography (PET) to assess amyloid‐beta and tau in‐vivo. We used structural MRI to assess white matter hyperintensity (WMH) volume, a marker of cerebrovascular lesion load, and regional GM volume (a marker of neurodegeneration). We used correlations and ANCOVA in the whole dataset and structural equation modelling in the DLB patients to investigate associations of WMH volume and regional amyloid‐beta and tau PET standardized uptake value ratios (SUVRs) with regional GM volume.ResultDLB patients showed lower GM volume across all cortical and subcortical regions except for cuneus, putamen, and pallidum (Fig.1). Greater WMH volume was associated with lower volume in the medial and orbital frontal cortices, insula, fusiform cortex, and thalamus in DLB patients (Fig.2). Greater PiB SUVR was associated with lower volume in the inferior temporal cortex, while Flortaucipir SUVR did not correlate with GM volume (Fig.2). Structural equation modelling showed that higher age and positivity for the APOE e4 genotype were significant predictors of greater WMH, and WMH in turn was a significant predictor of GM volume in medial and orbital frontal cortices, insula, and inferior temporal cortex (Fig.3). In contrast, we observed two distinct paths for the fusiform cortex, with age having an effect through PiB and Flortaucipir SUVRs on the one path, and through WMH on the other path (Fig.3).ConclusionDLB patients have widespread cortical atrophy, most of which likely is influenced by alpha‐synuclein pathology. Although amyloid‐beta, tau, and cerebrovascular pathologies often coexist in DLB, their contributions to neurodegeneration seem to be region specific.

AbstractBackgroundTamoxifen is used as a selective estrogen receptor modifier (SERM) to treat hormone receptor‐positive breast cancer. Raloxifene, another SERM, has been used for the treatment of osteoporosis in post‐menopausal women. The aim of this cross‐sectional study was to examine whether a history of tamoxifen or raloxifene use was associated with cognitive performance, odds of mild cognitive impairment (MCI), or structural neurodegenerative MRI markers.MethodThe study included women with and without a personal history of breast cancer enrolled in the Mayo Clinic Study of Aging (MCSA). A history of breast cancer and use of SERMs before the MCSA enrollment visit was abstracted using the Rochester Epidemiology Project medical‐linkage system. Participants had a diagnosis of MCI (prevalent) at the time of enrollment into the MCSA. Logistic regression was used to examine associations of SERMs with odds of MCI. Linear regression models were used to examine associations of SERMs with cognitive measures z‐scores (Memory, Executive Function, Language, Visuospatial Skills, Global Cognition), hippocampal volume, and Alzheimer’s disease signature cortical thickness.ResultAmong the women aged ≥ 50 at enrollment in the MCSA, 151 had a history of breast cancer, and 2235 had no prior history of any cancer. Of the 151 women with a history of breast cancer, 42 (28%) had taken tamoxifen and 109 (72%) had not at enrollment in the MCSA; 54 had neuroimaging data (tamoxifen = 16; no tamoxifen = 38). Among the women without prior history of cancer at enrollment in the MCSA, 76 (3%) had taken raloxifene and 2159 (97%) had not; 755 had neuroimaging data (raloxifene = 25; no raloxifene = 730). No significant associations between tamoxifen with global or domain‐specific cognition or odds of MCI were observed among women with a history of breast cancer after adjusting for confounders (Table 1). Likewise raloxifene was not significantly associated with global or domain‐specific cognition or odds of MCI in women without a history of cancer after adjusting for confounders (Table 2). We did not find significant associations between SERMs and any neuroimaging outcome (Table 3).ConclusionOur results suggest use of tamoxifen or raloxifene is not significantly associated with cognition in postmenopausal women.

AbstractBackgroundTwo pathways that help explain cognitive health are 1) brain maintenance – referring to the relative absence of brain changes over time; 2) cognitive reserve – a property of the brain that allows for sustained cognitive ability in the presence of brain pathology. Both pathways influence cognitive aging and are best understood using longitudinal data. Our goal was to assess the effect of modifiable vascular/metabolic and lifestyle enrichment factors on these pathways using longitudinal brain changes measured on structural magnetic resonance imaging (MRI) and longitudinal cognitive decline. Lastly, we combined these pathways and their relationships in the same model.MethodWe identified 1250 participants from a well‐characterized sample of older adults from the Mayo Clinic Study of Aging with both longitudinal MRI and cognitive data. Linear mixed models were performed to assess the impact of modifiable factors on brain maintenance and cognitive reserve. Latent growth curve models (SEM) were used to assess the impact of brain structure and cognitive reserve on longitudinal cognition.ResultThe mean age of our sample was 78.8 years, with 45.4% female, and 27.1% APOE4 carriers. Mean follow‐up time was 4.0 years with a mean of 3.2 MRI scans per participant. Linear mixed models showed that poorer vascular/metabolic health (presence of vascular/metabolic conditions) was associated with lower cross‐sectional temporal region cortical thickness (‐0.014 (0.003), p<0.001) and lower global cognition (‐0.042 (0.018), p = 0.024). Higher estimated cognitive reserve at baseline as assessed by education/occupation composite (0.103 (0.01), p<0.001) was associated with higher global cognition. Unexpectedly, late‐life physical activities were related to lower global cognition (‐0.05 (0.007), p = 0.004). Our final latent growth curve SEM fit the data well showing temporal associations between unmodifiable characteristics, cognitive reserve, and brain structural pathways, as well as the influence of modifiable vascular/metabolic factors.ConclusionWe found that brain maintenance and cognitive reserve pathways were related to better cognition over time. We further showed that vascular/metabolic health impacts long‐term cognitive outcomes (i.e. cognitive aging) primarily through the brain maintenance pathway. These data provide a modeling scheme for future studies and can aid in assessing the pathways by which individual factors may influence cognitive aging.

AbstractBackgroundWomen have higher rates of hypertension at the time of menopausal transition than men. Although elevated systolic and diastolic blood pressures (SBP and DBP) are risk factors for white matter (WM) injury both in women and men, WM hyperintensities (WMH), a marker of WM injury, are more common in women than in men after the age of 60. Thus, women may be vulnerable to the effects of elevated BP on WM integrity during menopausal transition. We investigated the association of BP in recently postmenopausal women with good cardiovascular health with WMH volume assessed 13 years later.MethodWomen (n = 212; median age = 67; range 58‐72), who were previously enrolled in a multi‐site randomized menopausal hormone therapy trial, Kronos Early Estrogen Prevention Study (KEEPS), participated in the present observational KEEPS Continuation Study. SBP and DBP were measured at KEEPS baseline (median age = 54 years; range 44‐59). Participants who were on antihypertensive medications at KEEPS baseline were excluded from the analysis (n = 34). Approximately 9 years after the end of KEEPS menopausal hormones versus placebo 4‐year interventions, WM integrity was assessed with automated WMH volume measurements from 3D‐FLAIR MRI. Associations of baseline SBP and DBP with logWMH volume measured 13 years later were tested by linear regression analyses. Model 1 was adjusted for age, study site, and total intracranial volume. Model 2 was adjusted for covariates of model 1, triglycerides, low density lipoproteins, and waist/hip ratio.ResultThe median SBP was 116 (range 83‐158) and DBP was 74 (range 56‐98). Higher SBP was associated with greater WMH volume (model 1:p = 0.005; model 2:p = 0.005). Similarly, higher DBP was associated with greater WMH volume (model 1:p = 0.008; model 2:p = 0.006) (Figure 1). Neither menopausal hormone therapies versus placebo, nor having high/low SBP (≥120/<120) modified these associations. Voxel‐based analyses demonstrate the association of BPs with the spatial distribution of WMHs (Figure 2).ConclusionHigher BPs in recently menopausal women were associated with greater WM injury more than a decade later after adjusting for CVD risk factors. Early postmenopausal stage is a critical time for BP control in women, which may reduce the risk of WM injury later in life.

AbstractBackgroundPreclinical Alzheimer’s cognitive composites (PACC) are designed to detect subtle cognitive changes in clinical trials. PACCs often include measures of memory, attention, and semantic fluency, with variations based on available measures. We created a Mayo Clinic PACC (Mayo‐PACC) to address limitations of existing PACCs by prioritizing parsimony, non‐proprietary measures, clinical applicability, and psychometric properties. We developed a Mayo‐PACC and examined sensitivity to detecting longitudinal cognitive change in amyloid positive (A+) older adults relative to the Preclinical Alzheimer’s Cognitive Composite‐Revised (PACC‐R). Exploratory analyses included comparison to other composites.MethodParticipants included 614 individuals in the Mayo Clinic Study of Aging (428 A‐ and 186 A+) age 65‐85 who were cognitively unimpaired at baseline with 7 years mean follow‐up. A+ was defined as PiB‐PET meta‐ROI SUVR ≥ 1.48 (centiloid 22). The Mayo‐PACC included the AVLT sum of trials (trials 1‐5, short delay, long delay), Trails B and Animal fluency. Measures included in the PACC‐R and other comparison composites are listed in Table 1. We calculated study‐specific z‐scores and examined psychometric properties of component measures including test‐retest reliability, practice effects, and distributional properties (ceiling/floor effects, skew, kurtosis). We examined sensitivity to preclinical cognitive change using slope estimates (difference in annualized change across A+ and A‐ groups) from linear mixed models (LMMs) for each composite. A jackknife procedure was used to calculate the standard error and subsequent confidence intervals of differences in rates of change (A+>A‐ indicating more significant decline in A+). Significance was determined based on whether the 95% Confidence Interval (CI) contained 0 (alpha = .05).ResultAll composites showed sensitivity to amyloid‐related longitudinal cognitive decline (A+>A‐ annualized change p<.05; see Table 2). Jack‐knife comparisons revealed comparable utility of Mayo‐PACC and PACC‐R (CI contained 0, see Table 3). Exploratory analyses revealed Mayo‐PACC performed similarly to an adaptation of the ADCS‐PACC, Global‐z, Memory‐z and Attention‐z. The Mayo‐PACC performed better than a 2‐measure Mayo‐PACC‐remote and a single memory measure.ConclusionThe Mayo‐PACC provides a parsimonious composite score that has comparable utility for detecting A+>A‐ cognitive decline compared to the PACC‐R and other composites and can be widely used in both research and clinical settings.

Abstract Posterior cortical atrophy and logopenic progressive aphasia are atypical clinical presentations of Alzheimer’s disease. Resting-state functional connectivity studies have shown functional network disruptions in both phenotypes, particularly involving the language network in logopenic progressive aphasia and the visual network in posterior cortical atrophy. However, little is known about how connectivity differs both within and between brain networks in these atypical Alzheimer’s disease phenotypes. A cohort of 144 patients was recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, USA, and underwent structural and resting-state functional MRI. Spatially preprocessed data were analysed to explore the default mode network and the salience, sensorimotor, language, visual and memory networks. The data were analysed at the voxel and network levels. Bayesian hierarchical linear models adjusted for age and sex were used to analyse within- and between-network connectivity. Reduced within-network connectivity was observed in the language network in both phenotypes, with stronger evidence of reductions in logopenic progressive aphasia compared to controls. Only posterior cortical atrophy showed reduced within-network connectivity in the visual network compared to controls. Both phenotypes showed reduced within-network connectivity in the default mode and sensorimotor networks. No significant change was noted in the memory network, but a slight increase in the salience within-network connectivity was seen in both phenotypes compared to controls. Between-network analysis in posterior cortical atrophy showed evidence of reduced visual-to-language network connectivity, with reduced visual-to-salience network connectivity, compared to controls. An increase in visual-to-default mode network connectivity was noted in posterior cortical atrophy compared to controls. Between-network analysis in logopenic progressive aphasia showed evidence of reduced language-to-visual network connectivity and an increase in language-to-salience network connectivity compared to controls. Findings from the voxel-level and network-level analysis were in line with the Bayesian hierarchical linear model analysis, showing reduced connectivity in the dominant network based on diagnosis and more crosstalk between networks in general compared to controls. The atypical Alzheimer’s disease phenotypes were associated with disruptions in connectivity, both within and between brain networks. Phenotype-specific differences in connectivity patterns were noted in the visual network for posterior cortical atrophy and the language network for logopenic progressive aphasia.