42 research outputs found
Aneurysm treatment within 6 h versus 6-24 h after rupture in patients with subarachnoid hemorrhage
BACKGROUND
The risk of rebleeding after aneurysmal subarachnoid hemorrhage (aSAH) is the highest during the initial hours after rupture. Emergency aneurysm treatment may decrease this risk, but is a logistic challenge and economic burden. We aimed to investigate whether aneurysm treatment <6 h after rupture is associated with a decreased risk of poor functional outcome compared to aneurysm treatment 6-24 h after rupture.
METHODS
We used data of patients included in the ULTRA trial (NCT02684812). All patients in ULTRA were admitted within 24 h after aneurysm rupture. For the current study, we excluded patients in whom the aneurysm was not treated <24 h after rupture. We calculated crude and adjusted risk ratios (aRR) with 95% confidence intervals using Poisson regression analyses for poor functional outcome (death or dependency, assessed by the modified Rankin Scale) after aneurysm treatment <6 h versus 6-24 h after rupture. Adjustments were made for age, sex, clinical condition on admission (WFNS scale), amount of extravasated blood (Fisher score), aneurysm location, tranexamic acid treatment, and aneurysm treatment modality.
RESULTS
We included 497 patients. Poor outcome occurred in 63/110 (57%) patients treated within 6 h compared to 145/387 (37%) patients treated 6-24 h after rupture (crude RR: 1.53, 95% CI: 1.24-1.88; adjusted RR: 1.36, 95% CI: 1.11-1.66).
CONCLUSION
Aneurysm treatment <6 h is not associated with better functional outcome than aneurysm treatment 6-24 h after rupture. Our results do not support a strategy aiming to treat every patient with a ruptured aneurysm <6 h after rupture
Aneurysm treatment within 6 h versus 6–24 h after rupture in patients with subarachnoid hemorrhage
Background: The risk of rebleeding after aneurysmal subarachnoid hemorrhage (aSAH) is the highest during the initial hours after rupture. Emergency aneurysm treatment may decrease this risk, but is a logistic challenge and economic burden. We aimed to investigate whether aneurysm treatment <6 h after rupture is associated with a decreased risk of poor functional outcome compared to aneurysm treatment 6–24 h after rupture. Methods: We used data of patients included in the ULTRA trial (NCT02684812). All patients in ULTRA were admitted within 24 h after aneurysm rupture. For the current study, we excluded patients in whom the aneurysm was not treated <24 h after rupture. We calculated crude and adjusted risk ratios (aRR) with 95% confidence intervals using Poisson regression analyses for poor functional outcome (death or dependency, assessed by the modified Rankin Scale) after aneurysm treatment <6 h versus 6–24 h after rupture. Adjustments were made for age, sex, clinical condition on admission (WFNS scale), amount of extravasated blood (Fisher score), aneurysm location, tranexamic acid treatment, and aneurysm treatment modality. Results: We included 497 patients. Poor outcome occurred in 63/110 (57%) patients treated within 6 h compared to 145/387 (37%) patients treated 6–24 h after rupture (crude RR: 1.53, 95% CI: 1.24–1.88; adjusted RR: 1.36, 95% CI: 1.11–1.66). Conclusion: Aneurysm treatment <6 h is not associated with better functional outcome than aneurysm treatment 6–24 h after rupture. Our results do not support a strategy aiming to treat every patient with a ruptured aneurysm <6 h after rupture
Spatial concordance of DNA methylation classification in diffuse glioma.
BACKGROUND: Intratumoral heterogeneity is a hallmark of diffuse gliomas. DNA methylation profiling is an emerging approach in the clinical classification of brain tumors. The goal of this study is to investigate the effects of intratumoral heterogeneity on classification confidence.
METHODS: We used neuronavigation to acquire 133 image-guided and spatially separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma (7 IDH-wildtype and 2 IDH-mutant glioblastoma, 6 diffuse astrocytoma, IDH-mutant and 1 oligodendroglioma, IDH-mutant and 1p19q codeleted), which we characterized using DNA methylation arrays. Samples were obtained from regions with and without abnormalities on contrast-enhanced T1-weighted and fluid-attenuated inversion recovery MRI. Methylation profiles were analyzed to devise a 3-dimensional reconstruction of (epi)genetic heterogeneity. Tumor purity was assessed from clonal methylation sites.
RESULTS: Molecular aberrations indicated that tumor was found outside imaging abnormalities, underlining the infiltrative nature of this tumor and the limitations of current routine imaging modalities. We demonstrate that tumor purity is highly variable between samples and explains a substantial part of apparent epigenetic spatial heterogeneity. We observed that DNA methylation subtypes are often, but not always, conserved in space taking tumor purity and prediction accuracy into account.
CONCLUSION: Our results underscore the infiltrative nature of diffuse gliomas and suggest that DNA methylation subtypes are relatively concordant in this tumor type, although some heterogeneity exists
Neurological recovery after traumatic spinal cord injury:what is meaningful? A patients' and physicians' perspective
Study design: Cross-sectional survey. Objectives: Most studies on neurological recovery after traumatic spinal cord injury (tSCI) assess treatment effects using the American Spinal Injury Association Impairment Scale (AIS grade) or motor points recovery. To what extent neurological recovery is considered clinically meaningful is unknown. This study investigated the perceived clinical benefit of various degrees of neurological recovery one year after C5 AIS-A tSCI. Setting: The Netherlands. Methods: By means of a web-based survey SCI patients and physicians evaluated the benefit of various scenarios of neurological recovery on a scale from 0 to 100% (0% no benefit to 100% major benefit). Recovery to AIS-C and D, was split into C/C+ and D/D+, which was defined by the lower and upper limit of recovery for each grade. Results: A total of 79 patients and 77 physicians participated in the survey. Each AIS grade improvement from AIS-A was considered significant benefit (all p < 0.05), ranging from 47.8% (SD 26.1) for AIS-B to 86.8% (SD 24.3) for AIS-D+. Motor level lowering was also considered significant benefit (p < 0.05), ranging from 66.1% (SD 22.3) for C6 to 81.7% (SD 26.0) for C8. Conclusions: Meaningful recovery can be achieved without improving in AIS grade, since the recovery of functional motor levels appears to be as important as improving in AIS grade by both patients and physicians. Moreover, minor neurological improvements within AIS-C and D are also considered clinically meaningful. Future studies should incorporate more detailed neurological outcomes to prevent potential underestimation of neurological recovery by only using the AIS grade
The immunological landscape of peripheral blood in glioblastoma patients and immunological consequences of age and dexamethasone treatment
Background: Glioblastomas manipulate the immune system both locally and systemically, yet, glioblastoma-associated changes in peripheral blood immune composition are poorly studied. Age and dexamethasone administration in glioblastoma patients have been hypothesized to limit the effectiveness of immunotherapy, but their effects remain unclear. We compared peripheral blood immune composition in patients with different types of brain tumor to determine the influence of age, dexamethasone treatment, and tumor volume. Methods: High-dimensional mass cytometry was used to characterise peripheral blood mononuclear cells of 169 patients with glioblastoma, lower grade astrocytoma, metastases and meningioma. We used blood from medically-refractory epilepsy patients and healthy controls as control groups. Immune phenotyping was performed using FlowSOM and t-SNE analysis in R followed by supervised annotation of the resulting clusters. We conducted multiple linear regression analysis between intracranial pathology and cell type abundance, corrected for clinical variables. We tested correlations between cell type abundance and survival with Cox-regression analyses. Results: Glioblastoma patients had significantly fewer naive CD4+ T cells, but higher percentages of mature NK cells than controls. Decreases of naive CD8+ T cells and alternative monocytes and an increase of memory B cells in glioblastoma patients were influenced by age and dexamethasone treatment, and only memory B cells by tumor volume. Progression free survival was associated with percentages of CD4+ regulatory T cells and double negative T cells. Conclusion: High-dimensional mass cytometry of peripheral blood in patients with different types of intracranial tumor provides insight into the relation between intracranial pathology and peripheral immune status. Wide immunosuppression associated with age and pre-operative dexamethasone treatment provide further evidence for their deleterious effects on treatment with immunotherapy
The immunological landscape of peripheral blood in glioblastoma patients and immunological consequences of age and dexamethasone treatment
BackgroundGlioblastomas manipulate the immune system both locally and systemically, yet, glioblastoma-associated changes in peripheral blood immune composition are poorly studied. Age and dexamethasone administration in glioblastoma patients have been hypothesized to limit the effectiveness of immunotherapy, but their effects remain unclear. We compared peripheral blood immune composition in patients with different types of brain tumor to determine the influence of age, dexamethasone treatment, and tumor volume.MethodsHigh-dimensional mass cytometry was used to characterise peripheral blood mononuclear cells of 169 patients with glioblastoma, lower grade astrocytoma, metastases and meningioma. We used blood from medically-refractory epilepsy patients and healthy controls as control groups. Immune phenotyping was performed using FlowSOM and t-SNE analysis in R followed by supervised annotation of the resulting clusters. We conducted multiple linear regression analysis between intracranial pathology and cell type abundance, corrected for clinical variables. We tested correlations between cell type abundance and survival with Cox-regression analyses.ResultsGlioblastoma patients had significantly fewer naive CD4+ T cells, but higher percentages of mature NK cells than controls. Decreases of naive CD8+ T cells and alternative monocytes and an increase of memory B cells in glioblastoma patients were influenced by age and dexamethasone treatment, and only memory B cells by tumor volume. Progression free survival was associated with percentages of CD4+ regulatory T cells and double negative T cells.ConclusionHigh-dimensional mass cytometry of peripheral blood in patients with different types of intracranial tumor provides insight into the relation between intracranial pathology and peripheral immune status. Wide immunosuppression associated with age and pre-operative dexamethasone treatment provide further evidence for their deleterious effects on treatment with immunotherapy
Detection and localization of early- and late-stage cancers using platelet RNA
Cancer patients benefit from early tumor detection since treatment outcomes are more favorable for less advanced cancers. Platelets are involved in cancer progression and are considered a promising biosource for cancer detection, as they alter their RNA content upon local and systemic cues. We show that tumor-educated platelet (TEP) RNA-based blood tests enable the detection of 18 cancer types. With 99% specificity in asymptomatic controls, thromboSeq correctly detected the presence of cancer in two-thirds of 1,096 blood samples from stage I–IV cancer patients and in half of 352 stage I–III tumors. Symptomatic controls, including inflammatory and cardiovascular diseases, and benign tumors had increased false-positive test results with an average specificity of 78%. Moreover, thromboSeq determined the tumor site of origin in five different tumor types correctly in over 80% of the cancer patients. These results highlight the potential properties of TEP-derived RNA panels to supplement current approaches for blood-based cancer screening
Deep learning-based preoperative predictive analytics for patient-reported outcomes following lumbar diskectomy: feasibility of center-specific modeling
Background Context: There is considerable variability in patient-reported outcome measures following surgery for lumbar disk herniation. Individualized prediction tools that are derived from center- or even surgeon-specific data could provide valuable insights for shared decision-making. Purpose: To evaluate the feasibility of deriving robust deep learning-based predictive analytics from single-center, single-surgeon data. Study Design: Derivation of predictive models from a prospective registry. Patient Sample: Patients who underwent single-level tubular microdiskectomy for lumbar disk herniation. Outcome Measures: Numeric rating scales for leg and back pain severity and Oswestry Disability Index scores at 12 months postoperatively. Methods: Data were derived from a prospective registry. We trained deep neural network-based and logistic regression-based prediction models for patient-reported outcome measures. The primary endpoint was achievement of the minimum clinically important difference (MCID) in numeric rating scales and Oswestry Disability Index, defined as a 30% or greater improvement from baseline. Univariate predictors of MCID were also identified using conventional statistics. Results: A total of 422 patients were included (mean [SD] age: 48.5 [11.5] years; 207 [49%] female). After 1 year, 337 (80%), 219 (52%), and 337 (80%) patients reported a clinically relevant improvement in leg pain, back pain, and functional disability, respectively. The deep learning models predicted MCID with high area-under-the-curve of 0.87, 0.90, and 0.84, as well as accuracy of 85%, 87%, and 75%. The regression models provided inferior performance measures for each of the outcomes. Conclusions: Our study demonstrates that generating personalized and robust deep learning-based analytics for outcome prediction is feasible even with limited amounts of center-specific data. With prospective validation, the ability to preoperatively and reliably inform patients about the likelihood of symptom improvement could prove useful in patient counselling and shared decision-making