Abstract
BACKGROUND AND AIMS
There is incomplete information on the impact of a third dose of the SARS-CoV-2 vaccine in advance chronic kidney disease (CKD). The aim of the present analysis was to ...evaluate the kinetics of humoral response in the CKD spectrum (KT, HD, PD and ND-CKD) 6 months after completing the initial vaccine schedule. Some patients of each group received a third dose before 6 months, providing a pragmatic insight into real-world responses to different vaccine schedules in patients with advanced CKD not on dialysis, on dialysis or in KT recipients.
METHOD
The SENCOVAC study describes the humoral response and safety of different SARS-CoV-2 vaccines in a real-world setting in 3687 CKD patients: 787 kidney transplant (KT), 319 peritoneal dialysis (PD), 2297 haemodialysis (HD) and 284 non-dialysis-CKD (ND-CKD) patients. Anti-Spike antibodies were assessed in an efficacy analysis at 28 days (n = 1755), 3 months (n = 1386), and 6 months (n = 1018, of whom 628 had received a third vaccine dose). Adverse events (AEs) were registered during follow-up, including SARS-CoV-2 infections in the safety analysis.
RESULTS
Among the patients included in the efficacy analysis, KT recipients presented lower anti-Spike antibody titers than other CKD cohorts at 28 days and 3 months (P < .001 for all). A total of 943 patients 249 (26%) KT, 108 (11%) PD, 511 (54%) HD and 75 (8%) ND-CKD had negative baseline anti-Spike antibodies. Again, at 28 days or 3 months, KT recipients developed lower anti-Spike antibody titers than PD (P < .001), HD (P < .001) and ND-CKD (P< .001) patients. At 6 months, patients that had received a third vaccine dose had higher anti-Spike antibody titers than those without the third dose 1837 (507–9726) UI/mL versus 80 (19–409) ml/UI; P < .001 and this was evident in all CKD cohorts. Anti-Spike titers after the third dose were higher in patients boosted with mRNA-1273 than with BNT162b2 1710 (322–9615) versus 472 (34–2094); P < .001). At 6 months, in patients that had received a third dose, a positive humoral response (anti-Spike antibodies > 36 UI/mL) was achieved in 584 (93%): 94 (80%) of 118 KT recipients, 20 (100%) of 20 patients on PD, 436 (96%) of 455 patients on HD and 34 (97%) of 35 patients with ND-CKD (Fig. 1). Among patients without humoral response 3 months after completing the initial vaccination schedule, 72 (69%) seroconverted after the third dose (62% KT, 76% HD, 100% ND-CKD, all PD patients had a positive humoral response at 3 months). Independent predictors of a positive humoral response at 6 months were not-KT (HR for KT 0.26, P = .011), third dose (HR 22.9, P < .001), initial mRNA-1273 (HT 1.78, P = .017) and humoral response at 3 months (HR 26.2, P < .001). Breakthrough SARS-CoV-2 infections occurred in 1.1% of patients, and mortality was 14.6%, none after the third dose.
CONCLUSION
In the CKD spectrum, anti-Spike antibody titers continued to decrease from 3 to 6 months after complete vaccination, and KT recipients presented higher rates of negative humoral response at 6 months. A third dose of mRNA vaccine increased anti-Spike antibody titers but was still insufficient to spur a humoral immune response in at least 38% of KT recipients and 24% of patients on HD that lacked anti-SARS-CoV-2 antibodies 3 months post-initial vaccination. New strategies are urgently needed to protect CKD patients that remain negative for anti-SARS-CoV-2 antibodies, given the high mortality of breakthrough SARS-CoV-2 infections.
FIGURE 1:
Presence of anti-Spike antibodies during follow-up in the different CKD cohorts. Data expressed as % of patients with presence of anti-Spike antibodies (i.e. titer > 36 IU/mL).
GRAPHICAL ABSTRACT
Graphical Abstract
During 2006–2021, Canada had 55 laboratory-confirmed outbreaks of foodborne botulism, involving 67 cases. The mean annual incidence was 0.01 case/100,000 population. Foodborne botulism in Indigenous ...communities accounted for 46% of all cases, which is down from 85% of all cases during 1990–2005. Among all cases, 52% were caused by botulinum neurotoxin type E, but types A (24%), B (16%), F (3%), and AB (1%) also occurred; 3% were caused by undetermined serotypes. Four outbreaks resulted from commercial products, including a 2006 international outbreak caused by carrot juice. Hospital data indicated that 78% of patients were transferred to special care units and 70% required mechanical ventilation; 7 deaths were reported. Botulinum neurotoxin type A was associated with much longer hospital stays and more time spent in special care than types B or E. Foodborne botulism often is misdiagnosed. Increased clinician awareness can improve diagnosis, which can aid epidemiologic investigations and patient treatment.
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DOBA, IZUM, KILJ, NUK, ODKLJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Aims
Paediatric cancer is a leading cause of non-communicable disease deaths for children worldwide, with more than 90% of deaths occurring in low-and-middle-income countries (LMICs). The ...COVID-19 pandemic may have exacerbated disparities in paediatric cancer outcomes between LMICs and HICs. The World Health Organization (WHO) Global Initiative for Childhood Cancer has identified gliomas as a common cancer that can act as a benchmark for assessing global paediatric cancer care. This study aims to ascertain the short and medium-term outcome across 17 countries during the COVID-19 pandemic by determining 30- and 90-day all-cause mortality rates for paediatric glioma patients who underwent treatment.
Method
A multicentre, international, mixed- (retrospective and prospective), collaborative cohort study in 17 countries. Patients were recruited between March 12th 2020 and July 12th 2020.
Results
129 patients were recruited with the majority being histologically diagnosed as low-grade gliomas (n = 86/118, 72.9%). Seven children had a change to their planned chemotherapy treatment because of the COVID-19 pandemic. Similarly, seven children and eleven children had a change to their planned radiotherapy treatment and surgical treatment respectively because of the COVID-19 pandemic. Five patients died within the 30-day follow-up period, with all five patients being in LMICs. A sixth child, also in a LMIC, died within the 90-day follow-up period. This significant difference in mortality between LMICs and HICs was present when controlling for confounding for factors such as grade, ASA status, sex, weight, and age.
Conclusion
There has been relatively minimal change to the treatment of paediatric gliomas worldwide compared to their initial planned care. There was a significant difference in mortality for childhood gliomas between LMICS and high-income countries during the COVID-19 pandemic. There needs to be a concerted effort to improve equity in health outcomes globally.
Abstract
Aims
Key governing guidelines recognise that the holistic and complex needs of neuro-oncology patients are best served by a cohesive multidisciplinary team (MDT). Achieving a joint Clinical ...Nurse Specialist (CNS) and Allied Healthcare Professional (AHP) clinic (including Speech and Language Therapy, Physiotherapy, Dietetics and Occupational Therapy) for neuro-oncology patients has been a longstanding vision at Velindre Cancer Centre (VCC) in Cardiff. A successful funding application to Welsh Government in July 2020 allowed the establishment of a virtual “one stop shop” clinic with CNS and AHPs available along the care trajectory to improve patient and carer quality of life. The project reports on whether this innovative clinic model successfully achieved the desired coordinated, anticipatory and holistic care.
Method
The project utilised service improvement methodology principles with aims inherent within quarterly timeframes. This included robust data collection on patient attendances and interventions, improving patient education and self-management and wide patient, care and staff engagement by means of questionnaires and semi-structured interviews. The mixed methods approach yielded rich quantitative and qualitative data.
Results
The data demonstrates an increasing demand for the joint neuro-oncology clinic indicating that additional resources may be required. From triangulation of patient, carer and wider team engagement the key benefits were perceived to be having accessibility to the team in a convenient way, the provision of support and timely information and the overall perception of enhanced holistic care.
Conclusion
The data demonstrates the huge successes of the joint neuro-oncology clinic so far, including improvements to patient and carer quality of life, wider VCC benefits and cost saves. The persuasive case was presented to Welsh Government, and ongoing endorsement has been achieved for the next financial year.
Abstract
Aims
Ependymomas (tumours arising from ependymal cells) are rare in the adult population and therefore there is limited class 1 evidence on the treatment and management of these patients. We ...present our experience from a large single center. We address whether management should be undertaken by sub-specialised surgeons with high volume experience.
Method
Retrospective comparative study.
Results
High volume surgeons operated on larger volume (16.14 mm3, 8.31mm3, p=0.10) and more complex tumours (multi-centric cases p=0.10). We find a non-significant improvement in complication rate (p=0.77), extent of gross total resection (70.8% against 65.7%) and a positive change in performance status for high volume surgeons (p=0.84). Length of hospital stay is significantly prolonged when complications occur (14.2 and 48.4 days, p<0.05).
Conclusion
Surgeons who have higher case load of ependymomas operate on more complex tumours. In addition, our results indicate there is a technical advantage of high volume surgeons compared to low volume surgeons, which translates into improved clinical outcomes for patients. We show that this has a significant impact on length of hospital stay, as well as the associated economical implications. For rare tumours such as ependymomas, super-specialisation and referral to surgeons with higher case volume will likely improve patient outcomes.
We call for a multi-centre, prospective studies to combine data in demonstrating statistical significance (power calculation for complication rate, N=150, p=0.05).
Abstract
Aims
Glioblastoma Multiforme (GBM) is one of the most aggressive primary brain tumors with poor prognosis (median survival 18 months) and no cure. Management strategies often involve maximum ...safe resection followed by chemoradiotherapy. There has been a move from managing such patients electively rather than the traditional model of treating them as an emergency. While this may have advantages, this can delay the time from presentation to operation. This delay has recently been further compounded by the current COVID-19 pandemic.
There is no data available as to whether the surgical delays that are currently occurring have an impact on patient care, and may outweigh the benefits of elective management on health services.
We aimed to conduct a single centre observational study to assess how long patients should be waiting prior to surgery. We hypothesised that the longer the wait, the higher the pre-operative complication rate and worse the outcomes.
Method
698 patients in a GBM database over a 5-year period (29/10/14- 8/11/19) were studied. All patient data was accessed via electronic patient records
Surgical delay was defined as the interval between date of being put on the waiting list (the date seen in the neuro-oncology clinic) to date of surgery.
Primary outcome measure was preoperative complications, which was categorised into transient neurological decline, stroke, seizures, diabetes/erratic blood sugars, emergency admission, others (e.g., cardiovascular compromise, steroid complications, blood disorders)
Inclusion criteria included: First presentation supratentorial WHO Grade 4 GBM confirmed on histology (this included histological variants such as Gliosarcoma and Epithelioid Glioblastoma), and all patients who had been seen in the neuro-oncology clinic prior to surgery.
Exclusion criteria included all patients who were not thought to have a GBM or high-grade glioma on initial imaging, those admitted as an emergency without being seen in a neuro-oncology clinic, recurrent or secondary GBMs.
Results
460 patients met the inclusion criteria in this study. There was a pre-operative complication rate of 14.6% (67/460). 55% of complications were due to a transient neurological decline (37/67) with 16.4 % (11/67) of patients presenting with seizures. For those with surgical delays ≤7 days pre-operative complication rates were 2.2 % vs 15.9% in those with delays >7 days, p value 0.012, Odds ratio 8.53 (95% CI 1.48- 88.09). Results were statistically significant in those with delays greater than 10 and 14 days (p values 0.0026 and 0.0004 respectively)
ROC Curve analysis revealed an AUC of 0.66 with sensitivities of 99%, 90% and 76% at surgical delays of 7,10 and 14 days respectively.
The median length of hospital admission in both groups of patients was 5 days (p= 0.2065)
All statistical analysis was carried out using Prism 9 and SPSS
Conclusion
In spite of unchanged length of hospital stay, we note a significant increase in pre-operative complication rates as a result of surgical delays greater than 7,10 and 14 days, which introduces an interesting debate in the merit of delaying operations for further assessment in clinic. Our objectives would be to minimize complication rate, therefore a high sensitivity i.e. true positive rate would be most desirable. The 99% levels achieved at 7 days In the ROC analysis lends weight to introducing policy to fast-track admissions for primary GBM patients.
Further directions could include assessing the impact reduced surgical services and redeployment might have had on complications rates and length of hospital stay on patients admitted over the COVID 19 pandemic.
Abstract
Aims
Glioblastoma multiforme (GBM) is an aggressive brain malignancy. Performance status is an important prognostic factor but is subjectively evaluated, resulting in inaccuracy. Objective ...markers of frailty/physical condition, such as measures of skeletal muscle mass can be evaluated on cross-sectional imaging and is associated with cancer survival. In GBM, temporalis muscle has been identified as a skeletal muscle mass surrogate and a prognostic factor. However, current manual muscle quantification is time consuming, limiting clinical adoption. We previously developed a deep learning system for automated temporalis muscle quantification, with high accuracy (Dice coefficient 0.912), and showed muscle cross-sectional area is independently significantly associated with survival in GBM (HR 0.380). However, it required manual selection of the temporalis muscle-containing MRI slice. Thus, in this work we aimed to develop a fully automatic deep-learning system, using the eyeball as an anatomic landmark for automatic slice selection, to quantify temporalis and validate on independent datasets.
Method
3D brain MRI scans were obtained from four datasets: our in-house glioblastoma patient dataset, TCGA-GBM, IVY-GAP and REMBRANDT. Manual eyeball and temporalis segmentations were performed on 2D MRI images by two experienced readers. Two neural networks (2D U-Nets) were trained, one to automatically segment the eyeball and the other to segment the temporalis muscle on 2D MRI images using Dice loss function. The cross sectional area of eyeball segmentations were quantified and thresholded, to select the superior orbital MRI slice from each scan. This slice underwent temporalis segmentation, whose cross sectional area was then quantified. Accuracy of automatically predicted eyeball and temporalis segmentations were compared to manual ground truth segmentations on metrics of Dice coefficient, precision, recall and Hausdorff distance. Accuracy of MRI slice selection (by the eyeball segmentation model) for temporalis segmentation was determined by comparing automatically selected slices to slices selected manually by a trained neuro-oncologist.
Results
398 images from 185 patients and 366 images from 145 patients were used for the eyeball and temporalis segmentation models, respectively. 61 independent TCGA-GBM scans formed a validation cohort to assess the performance of the full pipeline. The model achieved high accuracy in eyeball segmentation, with test set Dice coefficient of 0.9029 ± 0.0894, precision of 0.8842 ± 0.0992, recall of 0.9297 ± 0.6020 and Hausdorff distance of 2.8847 ± 0.6020. High segmentation accuracy was also achieved by the temporalis segmentation model, with Dice coefficient of 0.8968 ± 0.0375, precision of 0.8877 ± 0.0679, recall of 0.9118 ± 0.0505 and Hausdorff distance of 1.8232 ± 0.3263 in the test set. 96.1% of automatically selected slices for temporalis segmentation were within 2 slices of the manually selected slice.
Conclusion
Temporalis muscle cross-sectional area can be rapidly and accurately assessed from 3D MRI brain scans using a deep learning-based system in a fully automated pipeline. Combined with our and others’ previous results that demonstrate the prognostic significance of temporalis cross-sectional area and muscle width, our findings suggest a role for deep learning in muscle mass and sarcopenia screening in GBM, with the potential to add significant value to routine imaging. Possible clinical applications include risk profiling, treatment stratification and informing interventions for muscle preservation. Further work will be to validate the prognostic value of temporalis muscle cross sectional area measurements generated by our fully automatic deep learning system in the multiple in-house and external datasets.
Abstract
Aims
The co-existence of non-epileptic attacks (NEAD) in patients with brain tumour related epilepsy (BTRE) is poorly described. Non epileptic attacks (NEAD) co-occur in up to 30% of ...patients with epilepsy PWE. Adverse life events are associated with development of NEAD; their co-occurrence in those with BTRE is potentially un-surprising.
We sought to characterise the evolution of symptoms in this cohort.
Method
Clinical trajectories of patients with BTRE and co-existing NEAD were characterised. The diagnosis of NEAD was based on the epilepsy specialist’s observation of attacks and /or capture of attacks on video. Some patients had additional video EEG correlate.
Patients had been referred because of persisting symptoms in spite of escalating antiepileptic therapy.
Results
Of eight patients, six were initially misdiagnosed with escalating seizures. One patient developed NEAD de novo following tumour biopsy, the remaining patients developed NEAD following onset of BTRE. Onset of NEAD was not temporally linked with the diagnosis of a brain tumour. In five patients, NEAD onset occurred when seizures were controlled (< 1 seizure/ month). All patients reported fear of developing uncontrolled seizures as being associated with their symptoms and identified their NEAD as more disabling than their epilepsy.
Patients were eventually managed with polytherapy -two found adjunctive clobazam helpful and four were offered antidepressant/ anxiolytic medication. Behavourial strategies including mindfulness were also discussed. At time of last follow up, seven patients had on-going NEAD symptoms in spite of good seizure control.
Conclusion
NEAD can co-occur with BTRE and should be considered in those with rapidly escalating symptoms in spite of antiepileptic therapy and radiologically stable lesions. Both making the diagnosis of NEAD and providing ongoing support is challenging. These patients require a multidisciplinary approach with support from allied specialties including neuropsychiatry and neuropsychology.
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