Citations

AbstractIntroductionThe distal radius is a common location for giant cell tumors (GCTs) of bone. Management includes intralesional curettage or wide excision, however, long‐term comparisons of treatment options are limited. The purpose of the current study was to evaluate our institutions' outcomes of treatment of these tumors.MethodsWe reviewed 24 GCT of the distal radius in 23 patients (12 males: 11 females) with a mean age of 42 years at the time of surgery. Functional outcomes were collected including the Musculoskeletal Tumor Society Score (MSTS), QuickDash, the Visual Analog Scale (VAS), and the Patient Rated Wrist Evaluation (PRWE). The mean follow‐up was 13 years.ResultsTumor grade included Campanacci Grade II (n = 14) and Grade III (n = 10). Treatment included extended intralesional curettage (n = 16) and wide excision (n = 8). Reconstruction mainly included bone grafting/cement (n = 16) or free vascularized fibula radiocarpal arthrodesis (n = 5). At most recent follow‐up, there was no difference in MSTS, VAS, and PRWE (p > 0.05) between patients undergoing a joint sparing or arthrodesis. Patients undergoing arthrodesis had a lower QuickDASH score (13.7 vs. 20.8, p = 0.04)ConclusionsTreatment for GCT of the distal radius is individualized however in the setting of articular surface involvement, arthrodesis can lead to superior functional results at long‐term follow‐up.

Objective Chronic lymphocytic leukemia and small lymphocytic lymphoma remain the most prevalent adult leukemia in Western countries. Novel therapeutics have established long-term efficacy and have changed the landscape in patient management. In contrast, novel approaches pose opportunities for patients to be treated for finite durations. In this manuscript, we highlight long-term safety and efficacy data with Bruton's tyrosine kinase inhibitors and combination BCL2 + anti-CD20 therapies. We also offer key considerations for treatment selection and outline ongoing trials which may continue to expand therapeutic options and approaches. Data sources An electronic search of the PubMed database was performed to obtain key literature in chronic lymphocytic leukemia and small lymphocytic lymphoma published using the following search terms: chronic lymphocytic leukemia/small lymphocytic lymphoma, Richter syndrome, and histologic transformation. The search results were narrowed by selecting studies in humans published in English. Results were confined to the following article types: Clinical Trial, Phase II; Clinical Trial, Phase III; Clinical Trial, Phase IV; Guideline; Randomized Controlled Trial; Meta-Analysis; Systematic Reviews; and Validation Studies. Data summary Chronic lymphocytic leukemia and small lymphocytic lymphoma are different manifestations of the same disease and are managed in much the same way. Bruton's tyrosine kinase inhibitors have demonstrated long and durable efficacy benefits in patients with newly diagnosed chronic lymphocytic leukemia/small lymphocytic lymphoma and in the relapsed/refractory setting. Despite these benefits, long terms adverse events have posed challenges for patients and have led to treatment discontinuations. Additionally, the use of monotherapy Bruton's tyrosine kinase inhibitor's requires chronic use of the medications leading to added financial implications. BCL2 inhibition with venetoclax in combination with anti-CD20 monoclonal antibodies has offered a novel and finite treatment approach in frontline and relapsed chronic lymphocytic leukemia/small lymphocytic lymphoma. Ongoing clinical trials are in investigating this modality further to enhance durable responses utilizing a combination Bruton's tyrosine kinase inhibitor's and BCL2 inhibitors. Conclusion The treatment armamentarium of chronic lymphocytic leukemia/small lymphocytic lymphoma continues to evolve. Despite the long term, durable responses with Bruton's tyrosine kinase inhibitor's, it is likely that finite treatment durations could become the standard of care as a result of continued, long-term responses.

OBJECTIVE Pineal cyst (PC) is a relatively common true cyst in the pineal gland. Its long-term natural course remains ill defined. This study aims to evaluate the long-term natural history of PC and examine MRI risk factors for cyst growth and shrinkage to help better define which patients might benefit from surgical intervention. METHODS The records and MRI of 409 consecutive patients with PC were retrospectively examined (nonsurgical cohort). Cyst growth and shrinkage were defined as a ≥ 2-mm increase and decrease in cyst diameter in any direction, respectively. In addition to size, MRI signal intensity ratios were analyzed. RESULTS The median radiological follow-up period was 10.7 years (interquartile range [IQR] 6.4–14.3 years). The median change in maximal diameter was −0.6 mm (IQR −1.5 to 1.3 mm). During the observation period, cyst growth was confirmed in 21 patients (5.1%). Multivariate logistic regression analysis revealed that only age (odds ratio [OR] 0.96, 95% confidence interval [CI] 0.93–0.99, p < 0.01) was significantly associated with cyst growth. No patient required resection during the observation period. Cyst shrinkage was confirmed in 57 patients (13.9%). Multivariate analysis revealed that maximal diameter (OR 1.22, 95% CI 1.12–1.35, p < 0.01) and cyst CSF T2 signal intensity ratio (OR 9.06, 95% CI 1.38–6.62 × 101, p = 0.02) were significantly associated with cyst shrinkage. CONCLUSIONS Only 5% of PCs, mainly in patients younger than 50 years of age, have the potential to grow, while cyst shrinkage is more likely to occur across all age groups. Younger age is associated with cyst growth, while larger diameter and higher signal intensity on T2-weighted imaging are associated with shrinkage. Surgery is rarely needed for PCs, despite the possibility of a certain degree of growth.

AbstractTo date, the unpredictability of seizures remains a source of suffering for people with epilepsy, motivating decades of research into methods to forecast seizures. Originally, only few scientists and neurologists ventured into this niche endeavor, which, given the difficulty of the task, soon turned into a long and winding road. Over the past decade, however, our narrow field has seen a major acceleration, with trials of chronic electroencephalographic devices and the subsequent discovery of cyclical patterns in the occurrence of seizures. Now, a burgeoning science of seizure timing is emerging, which in turn informs best forecasting strategies for upcoming clinical trials. Although the finish line might be in view, many challenges remain to make seizure forecasting a reality. This review covers the most recent scientific, technical, and medical developments, discusses methodology in detail, and sets a number of goals for future studies.

PURPOSE: This study assessed the long-term quality of life (QOL) of patients with aggressive lymphoma subtypes treated with autologous hematopoietic cell transplant (autoHCT) compared with those without history of transplant. METHODS: Patient-reported QOL measures were prospectively gathered from patients enrolled in the Iowa/Mayo Specialized Program of Research Excellence Molecular Epidemiology Resource cohort with aggressive lymphoma subtypes. QOL was measured using the Functional Assessment of Cancer Therapy-General (FACT-G), Functional Assessment of Chronic Illness Therapy–Fatigue Scale, State-Trait Anxiety Inventory (STAI), and Profile of Mood States instruments and with a numeric rating scale for overall QOL and spiritual QOL. The autoHCT group and no HCT groups were compared at 3 years (FU3) and 6 years (FU6) after lymphoma diagnosis. RESULTS: In total, 980 patients with lymphoma (106 autoHCT and 874 no HCT) diagnosed between 2002 and 2013 were included for analysis. The mean FACT-G total score was similar in the autoHCT and no HCT groups at FU3 (89.9 v 90.1, P = .64) and also at FU6 (91.5 v 89.6, P = .44). No differences between the autoHCT and no HCT groups were identified in the FACT subscales. The STAI identified lower anxiety in the autoHCT group by mean STAI1 (state) at FU3 (30.1 v 33.4, P < .01) and by mean STAI2 (trait) at FU6 (30.1 v 33.5, P = .02). No other clinically meaningful differences were identified between the two groups using the other QOL instruments. CONCLUSION: Patients remaining in remission at 3 and 6 years after diagnosis had a high level of QOL with no significant differences associated with history of treatment with autoHCT.

Abstract Objective To investigate the impact of having headaches prior to traumatic brain injury (TBI) on headache features and long‐term patient health outcomes. Background and Methods This was an exploratory analysis of patients with TBI who were enrolled in the American Registry for Migraine Research (ARMR), a multicenter, prospective, longitudinal patient registry composed of patients with International Classification of Headache Disorders, 3rd edition (ICHD‐3)–defined headache diagnoses. The ARMR study enrolled 2,707 patients between February 1, 2016 and May 6, 2020, 565 of whom qualified for this analysis. Those with headaches prior to their TBI were compared to those without headaches prior to their TBI for ICHD‐3 diagnoses, headache frequency and intensity, headache‐related disability (Migraine Disability Assessment score), symptoms of anxiety (General Anxiety Disorder [GAD‐7]), depression (two items from Patient Health Questionnaire‐9), post‐traumatic stress disorder (PTSD), cutaneous allodynia (12‐item Allodynia Symptom Checklist [ASC‐12]), cognitive dysfunction (Migraine Attacks Subjective Cognitive Impairments Scale [Mig‐SCog]), pain interference (Patient‐Reported Outcomes Measurement Information System‐Pain Interference), and work productivity (Work Productivity and Activity Impairment). Results Among 565 participants with TBI, 350 had headaches prior to their TBI. Those with pre‐TBI headaches were less likely to receive a diagnosis of post‐traumatic headache (PTH; 14/350 [4.0%] vs. 21/215 [9.8%], p = 0.006), even though 25.7% reported new or worsening headaches within 7 days of their TBI. Those with pre‐TBI headaches had higher ASC‐12 scores (2.4 ± 3.5 vs. 1.8 ± 3.4, p = 0.030), Mig‐SCog scores (9.3 ± 4.7 vs. 8 ± 4.9, p = 0.004), and GAD‐7 scores (6.9 ± 5.1 vs. 6.2 ± 5.4, p = 0.039), and were more likely to have a migraine diagnosis (335/350 [95.7%] vs. 192/215 [89.3%], p = 0.003). Conclusions Those with headaches prior to TBI are less likely to receive a diagnosis of PTH. They have more severe symptoms of cutaneous allodynia, cognitive impairment, and generalized anxiety. This analysis suggests that pre‐TBI headaches might impact post‐TBI headache diagnoses and associated features.

Abstract Aims Some artificial intelligence models applied in medical practice require ongoing retraining, introduce unintended racial bias, or have variable performance among different subgroups of patients. We assessed the real-world performance of the artificial intelligence-enhanced electrocardiogram to detect left ventricular systolic dysfunction with respect to multiple patient and electrocardiogram variables to determine the algorithm’s long-term efficacy and potential bias in the absence of retraining. Methods and results Electrocardiograms acquired in 2019 at Mayo Clinic in Minnesota, Arizona, and Florida with an echocardiogram performed within 14 days were analyzed (n = 44 986 unique patients). The area under the curve (AUC) was calculated to evaluate performance of the algorithm among age groups, racial and ethnic groups, patient encounter location, electrocardiogram features, and over time. The artificial intelligence-enhanced electrocardiogram to detect left ventricular systolic dysfunction had an AUC of 0.903 for the total cohort. Time series analysis of the model validated its temporal stability. Areas under the curve were similar for all racial and ethnic groups (0.90–0.92) with minimal performance difference between sexes. Patients with a ‘normal sinus rhythm’ electrocardiogram (n = 37 047) exhibited an AUC of 0.91. All other electrocardiogram features had areas under the curve between 0.79 and 0.91, with the lowest performance occurring in the left bundle branch block group (0.79). Conclusion The artificial intelligence-enhanced electrocardiogram to detect left ventricular systolic dysfunction is stable over time in the absence of retraining and robust with respect to multiple variables including time, patient race, and electrocardiogram features.

Abstract Background Measurement of cholesterol within lipoprotein subfractions may aid in cardiovascular disease prediction. Simple, homogenous enzymatic assays for the direct measurement of lipoprotein subfractions have been developed to measure small dense low-density lipoprotein cholesterol (sdLDL-C), high-density lipoprotein-3 cholesterol (HDL3-C), and triglyceride-rich lipoprotein (TRL-C) cholesterol. The objective of this study was to determine biological variability for sdLDL-C, HDL3-C, and TRL-C in a healthy reference population to facilitate interpretation of these analytes. Methods Serum samples were collected from 24 healthy subjects (n = 14 female/10 male) daily for 3 days while non-fasting, and daily for 5 days, weekly for 4 weeks, and monthly for 6 months after overnight fasting. sdLDL-C, HDL3-C, and TRL-C cholesterol were measured by homogenous enzymatic assays. Sources of variability (between-subject, within-subject, and analytical) were calculated using random-effects regression models. Reference change value (RCV) and index of individuality (II) for each time period were determined from the variance components. Results Analytic variability (daily, weekly, and monthly CVA) was &lt;3% for each analyte. Monthly within-subject variability (CVI) was 17.1% for sdLDL-C, 7.4% for HDL3-C, and 25.7% for TRL-C. Most of the monthly variation was attributed to between-subject variation for all 3 analytes. Overall RCVs for monthly measurements were 18.1 mg/dL for sdLDL-C, 6.1 mg/dL for HDL3-C, and 16.0 mg/dL for TRL-C. IIs were &lt;0.6 for sdLDL-C and HDL3-C, and 0.81 for TRL-C. Conclusions sdLDL-C, HDL3-C, and TRL-C showed moderate within-subject variability, but high between-subject variability, in a healthy reference population. Given the high individuality of each analyte, population-based reference intervals may be inadequate to detect clinically significant changes.

Introduction: CRT optimizations has the potential to improve the 30% non-response rate. Randomized trials (RCTs) comparing device and echo-guided CRT optimization have been overall small and results have been conflicting. Methods: We searched the EMBASE and MEDLINE databases from January 2008 through September 2020 for RCTs and prospective observational studies that randomized patients to either echo-guided or device-based CRT optimization. Included studies had to report on at least one of the following outcomes of interest: all-cause mortality, heart failure hospitalization (HFH), NYHA class improvement, mean EF at follow up, LVEDD, 6MWD, and QoL. A meta-analyses on the outcomes of interest was performed using random effects models. Results: We included seven RCTs representing a total of 2,730 patients. Of those, 1,113 patients were randomized to echo-guided optimization, and 1,617 were randomized to device-based optimization. The mean age of patients was 64.5 years, and they were predominantly men (60%). In the device-based optimization group, there was 93 deaths (5.7%) and 142 HFH (5.1%). In the echo-guided optimization group, there was 57 deaths (10.2%) and 112 HFH (12.4%). On random effects meta-analysis, the device-based optimization group had a lower rate of HFH compared with the echo-guided optimization group (OR 0.81, 95% CL 0.70-0.95, Figure). However, differences in the following outcomes between the two groups were not statistically significant: all-cause mortality, mean follow up EF, LVEDD, NYHA class improvement, 6MWD improvement range or QoL. Conclusions: This meta-analysis suggests that echo-guided optimization of CRT is equivalent to device-based optimization in relation to the clinical outcomes of death, EF, LVEDD, NYHA and 6MWD but suggests that device-related optimization could reduce HFH. The latter merits further investigation in relation to different device-base optimization algorithms.