Citations

AbstractObjectiveThis study was undertaken to determine whether the vertical parasagittal approach or the lateral peri‐insular/peri‐Sylvian approach to hemispheric surgery is the superior technique in achieving long‐term seizure freedom.MethodsWe conducted a post hoc subgroup analysis of the HOPS (Hemispheric Surgery Outcome Prediction Scale) study, an international, multicenter, retrospective cohort study that identified predictors of seizure freedom through logistic regression modeling. Only patients undergoing vertical parasagittal, lateral peri‐insular/peri‐Sylvian, or lateral trans‐Sylvian hemispherotomy were included in this post hoc analysis. Differences in seizure freedom rates were assessed using a time‐to‐event method and calculated using the Kaplan–Meier survival method.ResultsData for 672 participants across 23 centers were collected on the specific hemispherotomy approach. Of these, 72 (10.7%) underwent vertical parasagittal hemispherotomy and 600 (89.3%) underwent lateral peri‐insular/peri‐Sylvian or trans‐Sylvian hemispherotomy. Seizure freedom was obtained in 62.4% (95% confidence interval [CI] = 53.5%–70.2%) of the entire cohort at 10‐year follow‐up. Seizure freedom was 88.8% (95% CI = 78.9%–94.3%) at 1‐year follow‐up and persisted at 85.5% (95% CI = 74.7%–92.0%) across 5‐ and 10‐year follow‐up in the vertical subgroup. In contrast, seizure freedom decreased from 89.2% (95% CI = 86.3%–91.5%) at 1‐year to 72.1% (95% CI = 66.9%–76.7%) at 5‐year to 57.2% (95% CI = 46.6%–66.4%) at 10‐year follow‐up for the lateral subgroup. Log‐rank test found that vertical hemispherotomy was associated with durable seizure‐free progression compared to the lateral approach (p = .01). Patients undergoing the lateral hemispherotomy technique had a shorter time‐to‐seizure recurrence (hazard ratio = 2.56, 95% CI = 1.08–6.04, p = .03) and increased seizure recurrence odds (odds ratio = 3.67, 95% CI = 1.05–12.86, p = .04) compared to those undergoing the vertical hemispherotomy technique.SignificanceThis pilot study demonstrated more durable seizure freedom of the vertical technique compared to lateral hemispherotomy techniques. Further studies, such as prospective expertise‐based observational studies or a randomized clinical trial, are required to determine whether a vertical approach to hemispheric surgery provides superior long‐term seizure outcomes.

AbstractBackground:The role of methylation in pancreatic cancer risk remains unclear. We integrated genome and methylome data to identify CpG sites (CpG) with the genetically predicted methylation to be associated with pancreatic cancer risk. We also studied gene expression to understand the identified associations.Methods:Using genetic data and white blood cell methylation data from 1,595 subjects of European descent, we built genetic models to predict DNA methylation levels. After internal and external validation, we applied prediction models with satisfactory performance to the genetic data of 8,280 pancreatic cancer cases and 6,728 controls of European ancestry to investigate the associations of predicted methylation with pancreatic cancer risk. For associated CpGs, we compared their measured levels in pancreatic tumor versus benign tissue.Results:We identified 45 CpGs at nine loci showing an association with pancreatic cancer risk, including 15 CpGs showing an association independent from identified risk variants. We observed significant correlations between predicted methylation of 16 of the 45 CpGs and predicted expression of eight adjacent genes, of which six genes showed associations with pancreatic cancer risk. Of the 45 CpGs, we were able to compare measured methylation of 16 in pancreatic tumor versus benign pancreatic tissue. Of them, six showed differentiated methylation.Conclusions:We identified methylation biomarker candidates associated with pancreatic cancer using genetic instruments and added additional insights into the role of methylation in regulating gene expression in pancreatic cancer development.Impact:A comprehensive study using genetic instruments identifies 45 CpG sites at nine genomic loci for pancreatic cancer risk.

AbstractAcute kidney injury (AKI) may develop in patients with coronavirus disease 2019 (COVID‐19) and is associated with in‐hospital death. We investigated the incidence of AKI in 223 hospitalized COVID‐19 patients and analyzed the influence factors of AKI. The incidence of cytokine storm syndrome and its correlation with other clinicopathologic variables were also investigated. We retrospectively enrolled adult patients with virologically confirmed COVID‐19 who were hospitalized at three hospitals in Wuhan and Guizhou, China between February 13, 2020, and April 8, 2020. We included 124 patients with moderate COVID‐19 and 99 with severe COVID‐19. AKI was present in 35 (15.7%) patients. The incidence of AKI was 30.3% for severe COVID‐19 and 4.0% for moderate COVID‐19 (p < 0.001). Furthermore, cytokine storm was found in 30 (13.5%) patients and only found in the severe group. Kidney injury at admission (odds ratio [OR]: 3.132, 95% confidence interval [CI]: 1.150–8.527; p = 0.025), cytokine storm (OR: 4.234, 95% CI: 1.361–13.171; p = 0.013), and acute respiratory distress syndrome (ARDS) (OR: 7.684, 95% CI: 2.622–22.523; p < 0.001) were influence factors of AKI. Seventeen (48.6%) patients who received invasive mechanical ventilation developed AKI, of whom 64.7% (11/17) died. Up to 86.7% of AKI patients with cytokine storms may develop a secondary bacterial infection. The leukocyte counts were significantly higher in AKI patients with cytokine storm than in those without (13.0 × 10⁹/L, interquartile range [IQR] 11.3 vs. 8.3 × 10⁹/L, IQR 7.5, p = 0.005). Approximately 1/6 patients with COVID‐19 eventually develop AKI. Kidney injury at admission, cytokine storm and ARDS are influence factors of AKI. Cytokine storm and secondary bacterial infections may be responsible for AKI development in COVID‐19 patients.

Purpose Diffusion‐weighted imaging allows investigators to identify structural, microstructural, and connectivity‐based differences between subjects, but variability due to session and scanner biases is a challenge. Methods To investigate DWI variability, we present MASiVar, a multisite data set consisting of 319 diffusion scans acquired at 3 T from b = 1000 to 3000 s/mm 2 across 14 healthy adults, 83 healthy children (5 to 8 years), three sites, and four scanners as a publicly available, preprocessed, and de‐identified data set. With the adult data, we demonstrate the capacity of MASiVar to simultaneously quantify the intrasession, intersession, interscanner, and intersubject variability of four common DWI processing approaches: (1) a tensor signal representation, (2) a multi‐compartment neurite orientation dispersion and density model, (3) white‐matter bundle segmentation, and (4) structural connectomics. Respectively, we evaluate region‐wise fractional anisotropy, mean diffusivity, and principal eigenvector; region‐wise CSF volume fraction, intracellular volume fraction, and orientation dispersion index; bundle‐wise shape, volume, fractional anisotropy, and length; and whole connectome correlation and maximized modularity, global efficiency, and characteristic path length. Results We plot the variability in these measures at each level and find that it consistently increases with intrasession to intersession to interscanner to intersubject effects across all processing approaches and that sometimes interscanner variability can approach intersubject variability. Conclusions This study demonstrates the potential of MASiVar to more globally investigate DWI variability across multiple levels and processing approaches simultaneously and suggests harmonization between scanners for multisite analyses should be considered before inference of group differences on subjects.

AbstractIntroductionThe efficacy of cardiac resynchronization therapy (CRT) has been widely studied in the medical literature; however, about 30% of candidates fail to respond to this treatment strategy. Smart computational approaches based on clinical data can help expose hidden patterns useful for identifying CRT responders.MethodsWe retrospectively analyzed the electronic health records of 1664 patients who underwent CRT procedures from January 1, 2002 to December 31, 2017. An ensemble of ensemble (EoE) machine learning (ML) system composed of a supervised and an unsupervised ML layers was developed to generate a prediction model for CRT response.ResultsWe compared the performance of EoE against traditional ML methods and the state‐of‐the‐art convolutional neural network (CNN) model trained on raw electrocardiographic (ECG) waveforms. We observed that the models exhibited improvement in performance as more features were incrementally used for training. Using the most comprehensive set of predictors, the performance of the EoE model in terms of the area under the receiver operating characteristic curve and F1‐score were 0.76 and 0.73, respectively. Direct application of the CNN model on the raw ECG waveforms did not generate promising results.ConclusionThe proposed CRT risk calculator effectively discriminates which heart failure (HF) patient is likely to respond to CRT significantly better than using clinical guidelines and traditional ML methods, thus suggesting that the tool can enhanced care management of HF patients by helping to identify high‐risk patients.

Background: Dietary advanced glycation end-products (AGEs) are linked to cognitive decline. However, clinical trials have not tested the effect of AGEs on cognition in older adults. Objective: The aim of the current pilot trial was to examine the feasibility of an intervention to reduce dietary AGEs on cognition and on cerebral blood flow (CBF). Methods: The design is a pilot randomized controlled trial of dietary AGEs reduction in older adults with type 2 diabetes. Seventy-five participants were randomized to two arms. The control arm received standard of care (SOC) guidelines for good glycemic control; the intervention arm, in addition to SOC guidelines, were instructed to reduce their dietary AGEs intake. Global cognition and CBF were assessed at baseline and after 6 months of intervention. Results: At baseline, we found a reverse association between AGEs and cognitive functioning, possibly reflecting the long-term toxicity of AGEs on the brain. There was a significant improvement in global cognition at 6 months in both the intervention and SOC groups which was more prominent in participants with mild cognitive impairment. We also found that at baseline, higher AGEs were associated with increased CBF in the left inferior parietal cortex; however, 6 months of the AGEs lowering intervention did not affect CBF levels, despite lowering AGEs exposure in blood. Conclusion: The current pilot trial focused on the feasibility and methodology of intervening through diet to reduce AGEs in older adults with type 2 diabetes. Our results suggest that participants with mild cognitive impairment may benefit from an intensive dietary intervention.